2026-08-13T16:09:53Z https://journal.iberamia.org/index.php/intartif/oai

oai:journal.iberamia.org:article/6 2019-12-02T12:06:44Z intartif:Theses driver

Intelligent Heuristic Techniques for the Optimization of the Transshipment and Storage Operations at Maritime Container Terminals Expósito-Izquierdo, Christopher Intelligent Heuristic Optimization Problem Maritime Container Terminal This paper summarizes the main contributions of the Ph.D. thesis of Christopher Exp\'osito-Izquierdo. This thesis seeks to develop a wide set of intelligent heuristic and meta-heuristic algorithms aimed at solving some of the most highlighted optimization problems associated with the transshipment and storage of containers at conventional maritime container terminals. Under the premise that no optimization technique can have a better performance than any other technique under all possible assumptions, the main point of interest in the domain of maritime logistics is to propose optimization techniques superior in terms of effectiveness and computational efficiency to previous proposals found in the scientific literature when solving individual optimization problems under realistic scenarios. Simultaneously, these optimization techniques should be enough competitive to be potentially implemented in practice. }} Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Theses Summaries application/pdf https://journal.iberamia.org/index.php/intartif/article/view/6 10.4114/intartif.vol20iss60pp20-23 Inteligencia Artificial; Vol. 20 No. 60 (2017): Inteligencia Artificial (December 2017); 20-23 Inteligencia Artificial; Vol. 20 Núm. 60 (2017): Inteligencia Artificial (December 2017); 20-23 Inteligencia Artificial; Vol. 20 N.º 60 (2017): Inteligencia Artificial (December 2017); 20-23 1988-3064 1137-3601 10.4114/intartif.vol20iss60 eng https://journal.iberamia.org/index.php/intartif/article/view/6/51 Copyright (c) 2017 Iberamia & The Authors

oai:journal.iberamia.org:article/8 2019-12-02T12:06:55Z intartif:Ed driver

20 aniversario de 'INTELIGENCIA ARTIFICIAL': Revista Iberoamericana de I.A. Barber, Federico Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-01-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Editorial application/pdf https://journal.iberamia.org/index.php/intartif/article/view/8 10.4114/intartif.vol20iss59pp1-4 Inteligencia Artificial; Vol. 20 No. 59 (2017): Inteligencia Artificial (June 2017); 1-4 Inteligencia Artificial; Vol. 20 Núm. 59 (2017): Inteligencia Artificial (June 2017); 1-4 Inteligencia Artificial; Vol. 20 N.º 59 (2017): Inteligencia Artificial (June 2017); 1-4 1988-3064 1137-3601 10.4114/intartif.vol20iss59 eng https://journal.iberamia.org/index.php/intartif/article/view/8/2

oai:journal.iberamia.org:article/17 2019-12-02T12:06:55Z intartif:Article driver

A Knowledge Representation and Reasoning System for Multimodal Neuroimaging Studies Coelho, Ana Marques, Paulo Magalhães, Ricardo Sousa, Nuno Neves, José Alves, Victor Multimodal Neuroimaging Case-based Reasoning Artificial Intelligence Multimodal neuroimaging analyses are of major interest for both research and clinical practice, enabling the combined evaluation of the structure and function of the human brain. These analyses generate large volumes of data and consequently increase the amount of possibly useful information. Indeed, BrainArchive was developed in order to organize, maintain and share this complex array of neuroimaging data. It stores all the information available for each participant/patient, being dynamic by nature. Notably, the application of reasoning systems to this multimodal data has the potential to provide tools for the identification of undiagnosed diseases. As a matter of fact, in this work we explore how Artificial Intelligence techniques for decision support work, namely Case-Based Reasoning (CBR) that may be used to achieve such endeavour. Particularly, it is proposed a reasoning system that uses the information stored in BrainArchive as past knowledge for the identification of individuals that are at risk of contracting some brain disease. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/17 10.4114/intartif.vol20iss59pp42-52 Inteligencia Artificial; Vol. 20 No. 59 (2017): Inteligencia Artificial (June 2017); 42-52 Inteligencia Artificial; Vol. 20 Núm. 59 (2017): Inteligencia Artificial (June 2017); 42-52 Inteligencia Artificial; Vol. 20 N.º 59 (2017): Inteligencia Artificial (June 2017); 42-52 1988-3064 1137-3601 10.4114/intartif.vol20iss59 eng https://journal.iberamia.org/index.php/intartif/article/view/17/27

oai:journal.iberamia.org:article/21 2019-12-02T12:06:55Z intartif:Article driver

Rational versus Intuitive Outcomes of Reasoning with Preferences: Argumentation Perspective Cyras, Kristijonas Knowledge Representation and Reasoning Argumentation Preferences Reasoning with preference information is a common human activity. As modelling human reasoning is one of the main objectives of AI, reasoning with preferences is an important topic in various fields of AI, such as Knowledge Representation and Reasoning (KR). Argumentation is one particular branch of KR that concerns, among other tasks, modelling common-sense reasoning with preferences. A key issue there, is the lack of consensus on how to deal with preferences. Witnessing this is a multitude of proposals on how to formalise reasoning with preferences in argumentative terms. As a commonality, however, formalisms of argumentation with preferences tend to fulfil various criteria of `"rational" reasoning, notwithstanding the fact that human reasoning is often not `"rational", yet seemingly `"intuitive". In this paper, we study how several formalisms of argumentation with preferences model human intuition behind a particular common-sense reasoning problem. More specifically, we present a common-sense scenario of reasoning with rules and preferences, complemented with a survey of decisions made by human respondents that indicates an "intuitive" solution, and analyse how this problem is tackled in argumentation. We conclude that most approaches to argumentation with preferences afford a ``"rational" solution to the problem, and discuss one recent formalism that yields the "intuitive" solution instead. We argue that our results call for advancements in the area of argumentation with preferences in particular, as well as for further studies of reasoning with preferences in AI at large. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/21 10.4114/intartif.vol20iss59pp40-81 Inteligencia Artificial; Vol. 20 No. 59 (2017): Inteligencia Artificial (June 2017); 70-81 Inteligencia Artificial; Vol. 20 Núm. 59 (2017): Inteligencia Artificial (June 2017); 70-81 Inteligencia Artificial; Vol. 20 N.º 59 (2017): Inteligencia Artificial (June 2017); 70-81 1988-3064 1137-3601 10.4114/intartif.vol20iss59 eng https://journal.iberamia.org/index.php/intartif/article/view/21/29

oai:journal.iberamia.org:article/22 2019-12-02T12:06:55Z intartif:Article driver

Mining Users Mobility at Public Transportation ferreira, joao Wi-Fi, Mobile Device, Tracking, GPS, Artificial Intelligent, Knowledge. In this research work we propose a new approach to estimate the number of passengers in a public transportation and determinate the usersâ€™ route path based on a passive approach without user intervention. The method is based on the probe requests of users mobile device through the collected data in wireless access point. This data is manipulated to extract the information about the numbers of users with mobile devices and track their route path and time. This data can be manipulated to extract useful knowledge related with usersâ€™ habits at public transportation and extract user mobility patterns. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/22 10.4114/intartif.vol20iss59pp32-41 Inteligencia Artificial; Vol. 20 No. 59 (2017): Inteligencia Artificial (June 2017); 32-41 Inteligencia Artificial; Vol. 20 Núm. 59 (2017): Inteligencia Artificial (June 2017); 32-41 Inteligencia Artificial; Vol. 20 N.º 59 (2017): Inteligencia Artificial (June 2017); 32-41 1988-3064 1137-3601 10.4114/intartif.vol20iss59 eng https://journal.iberamia.org/index.php/intartif/article/view/22/28

oai:journal.iberamia.org:article/23 2020-04-09T03:00:16Z intartif:Theses driver

Incremental and developmental perspectives for general-purpose learning systems Martínez-Plumed, Fernando artificial intelligence, general-purpose learning systems, inductive programming, reinforcement learning, forgetting, task difficulty, cognitive development, evaluation of artificial systems, intelligence tests The stupefying success of Articial Intelligence (AI) for specic problems, from recommender systems to self-driving cars, has not yet been matched with a similar progress in general AI systems, coping with a variety of (dierent) problems. This dissertation deals with the long-standing problem of creating more general AI systems, through the analysis of their development and the evaluation of their cognitive abilities. It presents a declarative general-purpose learning system and a developmental and lifelong approach for knowledge acquisition, consolidation and forgetting. It also analyses the use of the use of more ability-oriented evaluation techniques for AI evaluation and provides further insight for the understanding of the concepts of development and incremental learning in AI systems. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Theses Summaries application/pdf https://journal.iberamia.org/index.php/intartif/article/view/23 10.4114/intartif.vol20iss60pp24-27 Inteligencia Artificial; Vol. 20 No. 60 (2017): Inteligencia Artificial (December 2017); 24-27 Inteligencia Artificial; Vol. 20 Núm. 60 (2017): Inteligencia Artificial (December 2017); 24-27 Inteligencia Artificial; Vol. 20 N.º 60 (2017): Inteligencia Artificial (December 2017); 24-27 1988-3064 1137-3601 10.4114/intartif.vol20iss60 eng https://journal.iberamia.org/index.php/intartif/article/view/23/52 Copyright (c) 2017 Iberamia & The Authors

oai:journal.iberamia.org:article/26 2019-12-02T12:06:55Z intartif:Article driver

An Orientation Method with Prediction and Anticipation Features Ramos, João Oliveira, Tiago Satoh, Ken Neves, José Novais, Paulo Orientation system Speculative computation Trajectory data mining Localization system Nowadays, progress is constant and inherent to a living society. This may occur in different arenas, namely in mathematical evaluation and healthcare. Assistive technologies are a topic under this evolution, being extremely important in helping users with diminished capabilities (physical, sensory, intellectual). These technologies assist people in tasks that were difficult or impossible to execute. A common diminished task is orientation, which is crucial for the user autonomy. The adaptation to such technologies should require the minimum effort possible in order to enable the person to use devices that convey assistive functionalities. There are several solutions that help a human being to travel between two different locations, however their authors are essentially concerned with the guidance method, giving special attention to the user interface. The CogHelper system aims to overcome these systems by applying a framework of Speculative Computation, which adds a prediction feature for the next user movement giving an anticipation ability to the system. Thus, an alert is triggered before the user turn towards an incorrect path. The travelling path is also adjusted to the user preferences through a trajectory mining module. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-13 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/26 10.4114/intartif.vol20iss59pp82-95 Inteligencia Artificial; Vol. 20 No. 59 (2017): Inteligencia Artificial (June 2017); 82-95 Inteligencia Artificial; Vol. 20 Núm. 59 (2017): Inteligencia Artificial (June 2017); 82-95 Inteligencia Artificial; Vol. 20 N.º 59 (2017): Inteligencia Artificial (June 2017); 82-95 1988-3064 1137-3601 10.4114/intartif.vol20iss59 eng https://journal.iberamia.org/index.php/intartif/article/view/26/48 Copyright (c) 2017 Iberamia & The Authors

oai:journal.iberamia.org:article/27 2017-02-05T10:56:42Z intartif:Article

oai:journal.iberamia.org:article/32 2017-02-05T11:14:59Z intartif:Article

oai:journal.iberamia.org:article/33 2020-04-09T03:00:18Z intartif:Article driver

Utilizing Gaze Behavior for Inferring Task Transitions Using Abstract Hidden Markov Models Tello Gamarra, Daniel Fernando We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abstract Hidden Markov Model (AHMM). We show that the predicted hand movement transitions occur consistently earlier in AHMM models with gaze than those models that do not include gaze observations. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/33 10.4114/intartif.vol19iss58pp1-16 Inteligencia Artificial; Vol. 19 No. 58 (2016): Inteligencia Artificial (December 2016); 1-16 Inteligencia Artificial; Vol. 19 Núm. 58 (2016): Inteligencia Artificial (December 2016); 1-16 Inteligencia Artificial; Vol. 19 N.º 58 (2016): Inteligencia Artificial (December 2016); 1-16 1988-3064 1137-3601 10.4114/intartif.vol19iss58 eng https://journal.iberamia.org/index.php/intartif/article/view/33/5

oai:journal.iberamia.org:article/34 2020-04-09T03:00:17Z intartif:Article driver

An Intelligent System Prototype to support and sharing diagnoses of maligned tumours, based on personalized medicine philosophy Flores Fonseca, Víctor Manuel Quelopana, Aldo Circulatory systems diseases are one of the most important causes of death in Chilean population according to a report presented by the Chilean National Bureau of Statistics (INE). Undoubtedly, these sad numbers arise an opportunity to analyse ways to improve this situation. Personalized Medicine is a new approach used to adapt standard medical treatments to individual characteristics of patients. Currently, several kinds of personalized-medicine software applications are building using Artificial Intelligent techniques and supported by techniques as Cloud Computing and Big Data. This architecture provides complex and varied information access, such as clinical data, genome data, patientsâ€™ treatment or drugs information, among others. This document describes a proposal to produce a method for generating and sharing medical information, particularly of maligned tumors in Chile. The prototype will be developed within the framework of the personalized medicine. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/34 10.4114/intartif.vol19iss58pp17-22 Inteligencia Artificial; Vol. 19 No. 58 (2016): Inteligencia Artificial (December 2016); 17-22 Inteligencia Artificial; Vol. 19 Núm. 58 (2016): Inteligencia Artificial (December 2016); 17-22 Inteligencia Artificial; Vol. 19 N.º 58 (2016): Inteligencia Artificial (December 2016); 17-22 1988-3064 1137-3601 10.4114/intartif.vol19iss58 eng https://journal.iberamia.org/index.php/intartif/article/view/34/6

oai:journal.iberamia.org:article/37 2020-04-09T03:00:17Z intartif:Article driver

Artificial Intelligence (AI) techniques to analyze the determinants attributes in housing prices Núñez Tabale, Julia M. Rey Carmona, Francisco J. Caridad y Ocerin, José MÂª The econometric approach to obtain the value of a property began with hedonic modelling, which were based on a set of property attributes, internal or external, associated to each particular dwelling. The final sale value can be estimated, and also the marginal prices of each exogenous explanatory variable. A good alternative to the hedonic approach is based on several Artificial Intelligence (AI) techniques, such as artificial neural networks (ANN), these tend to be more precise. Both methodologies are compared, and a case study is developed using data from Seville, the larger town in the South of Spain. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/37 10.4114/intartif.vol19iss58pp23-38 Inteligencia Artificial; Vol. 19 No. 58 (2016): Inteligencia Artificial (December 2016); 23-38 Inteligencia Artificial; Vol. 19 Núm. 58 (2016): Inteligencia Artificial (December 2016); 23-38 Inteligencia Artificial; Vol. 19 N.º 58 (2016): Inteligencia Artificial (December 2016); 23-38 1988-3064 1137-3601 10.4114/intartif.vol19iss58 eng https://journal.iberamia.org/index.php/intartif/article/view/37/8

oai:journal.iberamia.org:article/38 2019-12-02T12:07:13Z intartif:Theses driver

Model for optimising the execution of anti-spam filters Ruano-Ordás, David During last years, the combination of several filtering techniques for the development of anti-spam systems has gained a enormous popularity. However, although the accuracy achieved by these models has increased considerably, its use has entailed the emergence of new challenges such as the need to reduce the excessive use of computational resources, the increase of filtering speed and the adjustment of the weights used for the combination of several filtering techniques. In order to achieve this goal we have been refined several aspects including: (i) the design and development of small technical improvements to increase the overall performance of the filter, (ii) application of genetic algorithms to increase filtering accuracy and (iii) the use of scheduling algorithms to improve filtering throughput. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Theses Summaries application/pdf https://journal.iberamia.org/index.php/intartif/article/view/38 10.4114/intartif.vol19iss58pp45-48 Inteligencia Artificial; Vol. 19 No. 58 (2016): Inteligencia Artificial (December 2016); 45-48 Inteligencia Artificial; Vol. 19 Núm. 58 (2016): Inteligencia Artificial (December 2016); 45-48 Inteligencia Artificial; Vol. 19 N.º 58 (2016): Inteligencia Artificial (December 2016); 45-48 1988-3064 1137-3601 10.4114/intartif.vol19iss58 eng https://journal.iberamia.org/index.php/intartif/article/view/38/11

oai:journal.iberamia.org:article/40 2019-12-02T12:07:13Z intartif:Theses driver

Reinstatement and Specificty in Argumentation Systems Alessio, Claudio Andres Reinstatement is a principle of argumentation systems that enables the justification of a defeated argument when all its defeaters are in turn ultimately defeated. Some counterexamples to reinstatement have been offered in the literature. Specifically, counterexamples suggest that reinstatement cannot be taken as a general principle of defeasible argumentation because the reinstated arguments may support incorrect conclusions. Some authors argued that the problems are not due to reinstatement but to the formalization of those examples. Then, the solution is to make the language expressive enough to obtain the correct results. They also warn that one should avoid tinkering with the formalization in concrete examples just to get a desired outcome. Therefore, this approach should be combined with the search of general principles for choosing the proper formalization. Taking into account that finding general principles of representation could be a hard enterprise, the goal of this thesis is to identify some criterion that allows i. neutralize the counterexamples, ii. preserve the original formal language as much as possible, and iii. maintain reinstatement as a general principle. To identify that criterion, counterexamples are analyzed and possible causes of the problem are detected. As a result it is found that the preference by specificity among arguments can be used to obtain that criterion. Three approaches based on specificity are proposed and evaluated. Two of them introduce alternative defeat relations among arguments. The third one is based on filtering the non maximally specific arguments. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Theses Summaries application/pdf https://journal.iberamia.org/index.php/intartif/article/view/40 10.4114/intartif.vol19iss58pp39-44 Inteligencia Artificial; Vol. 19 No. 58 (2016): Inteligencia Artificial (December 2016); 39-44 Inteligencia Artificial; Vol. 19 Núm. 58 (2016): Inteligencia Artificial (December 2016); 39-44 Inteligencia Artificial; Vol. 19 N.º 58 (2016): Inteligencia Artificial (December 2016); 39-44 1988-3064 1137-3601 10.4114/intartif.vol19iss58 eng https://journal.iberamia.org/index.php/intartif/article/view/40/12

oai:journal.iberamia.org:article/41 2019-12-02T12:07:26Z intartif:Article driver

Document organization by means of graphs Vallejo Figueroa, Santa Nava Lozano, Valeria Nowadays documents are the main way to represent information and knowledge in several domains. Continuously users store documents in hard disk or online media according to some personal organization based on topics, but such documents can contain one or more topics. This situation makes hard to access documents when is required. The current search engines are based on the name of file or content, but where the desired term or terms must match exactly as are in the content. In this paper, a method for organize documents by means of graphs is proposed, taking into account the topics of the documents. For this a graph for each document is generated taking into account synonyms, semantic related terms, hyponyms, and hypernyms of nouns and verbs contained in documents. The proposal have been compares against Google Desktop and LogicalDoc with interesting results. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/41 Inteligencia Artificial; Vol. 19 No. 57 (2016): Inteligencia Artificial (June 2016); 1-21 Inteligencia Artificial; Vol. 19 Núm. 57 (2016): Inteligencia Artificial (June 2016); 1-21 Inteligencia Artificial; Vol. 19 N.º 57 (2016): Inteligencia Artificial (June 2016); 1-21 1988-3064 1137-3601 10.4114/intartif.vol19iss57 eng https://journal.iberamia.org/index.php/intartif/article/view/41/13

oai:journal.iberamia.org:article/43 2019-12-02T12:07:26Z intartif:Article driver

Spanish Verbs Visualization: A study and scalable experimentation García Serrano, Ana Horcas Pulido,, Jorge López Ostenero, Fernando In this paper it is presented a study on verbs in Spanish and itâ€™s potential to display images from the Wikipedia (Wikimedia). It is designed and developed an Information Retrieval model based on linguistic structures of verbs and an environment that allows all subsequent scaling Spanish verbs. Adesse and EuroWordNet are the linguistic resources selected to bring the theoretical basis of the work. In the absence of an adequate corpus with relevant judgments to the problem, it has been recorded by the second author a subset of visual verbs sufficiently representative and enable to further work on this issue. Finally conclusions about visual verbs as well as the obtained results are provided Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/43 Inteligencia Artificial; Vol. 19 No. 57 (2016): Inteligencia Artificial (June 2016); 26-36 Inteligencia Artificial; Vol. 19 Núm. 57 (2016): Inteligencia Artificial (June 2016); 26-36 Inteligencia Artificial; Vol. 19 N.º 57 (2016): Inteligencia Artificial (June 2016); 26-36 1988-3064 1137-3601 10.4114/intartif.vol19iss57 eng https://journal.iberamia.org/index.php/intartif/article/view/43/14

oai:journal.iberamia.org:article/44 2019-12-02T12:07:26Z intartif:Article driver

Probabilistic Extension to the Concurrent Constraint Factor Oracle Model for Music Improvisation Toro, Mauricio We can program a Real-Time (RT) music improvisation system in C++ without a formal semantic or we can model it with process calculi such as the Non-deterministic Timed Concurrent Constraint (ntcc) calculus. â€œA Concurrent Constraints Factor Oracle (FO) model for Music Improvisationâ€ (Ccfomi) is an improvisation model specified on ntcc. Since Ccfomi improvises non-deterministically, there is no control on choices and therefore little control over the sequence variation during the improvisation. To avoid this, we extended Ccfomi using the Probabilistic Non-deterministic Timed Concurrent Constraint calculus. Our extension to Ccfomi does not change the time and space complexity of building the FO, thus making our extension compatible with RT. However, there was not a ntcc interpreter capable of RT to execute Ccfomi. We developed Ntccrt â€“a RT capable interpreter for ntccâ€“ and we executed Ccfomi on Ntccrt. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-05-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/44 Inteligencia Artificial; Vol. 19 No. 57 (2016): Inteligencia Artificial (June 2016); 37-73 Inteligencia Artificial; Vol. 19 Núm. 57 (2016): Inteligencia Artificial (June 2016); 37-73 Inteligencia Artificial; Vol. 19 N.º 57 (2016): Inteligencia Artificial (June 2016); 37-73 1988-3064 1137-3601 10.4114/intartif.vol19iss57 eng https://journal.iberamia.org/index.php/intartif/article/view/44/15

oai:journal.iberamia.org:article/45 2019-12-02T12:07:26Z intartif:Article driver

Improving Image Retrieval using a Data mining Approach ABED, Houaria ZAOUI, Lynda Recent years have witnessed great interest in developing methods for content-based image retrieval (CBIR). Generally, the image search results which are returned by an image search engine contain multiple topics, and organizing the results into different clusters will facilitate usersâ€™ browsing. Our aim in this research is to optimize image searching time for a general image database. The proposed procedure consists of two steps. First, it represents each image with a data structure which is based on quadtrees and represented by multi-level feature vectors. The similarity between images is evaluated through the distance between their feature vectors; this distance metric reduces the query processing time. Second, response time is further improved by using a secondary clustering technique to achieve high scalability in the case of a very large image database. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-05-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/45 Inteligencia Artificial; Vol. 19 No. 57 (2016): Inteligencia Artificial (June 2016); 97-113 Inteligencia Artificial; Vol. 19 Núm. 57 (2016): Inteligencia Artificial (June 2016); 97-113 Inteligencia Artificial; Vol. 19 N.º 57 (2016): Inteligencia Artificial (June 2016); 97-113 1988-3064 1137-3601 10.4114/intartif.vol19iss57 eng https://journal.iberamia.org/index.php/intartif/article/view/45/16

oai:journal.iberamia.org:article/47 2019-12-02T12:07:26Z intartif:Article driver

Combinatorial logic conceptual clustering: an alternative to Decision Making Reyes González, Yunia Claro Arceo, Alfonso Martínez Sánchez, Natalia Hernández Domínguez, Antonio Solving a problem leads to a process of identification and selection of the appropriate route for it solution. This process is called Decision Making, where a decision is choosing one among several alternatives. The basis of the decision-making process is the information we have of the application domain. With more and better information, better quality in the definition of the problem, proposed solutions, in the analysis of variants and the selection of the most appropriate action. The motivation of this research lies in the use of the main advantage of conceptual clustering algorithms combinatorial logic, giving the cluster an explanation beyond the similarity between objects and groups of objects in the process of decision making. The case-based systems are one of the current technologies for decision making by implementing the proposal. In this paper are describes its key components, the knowledge base or base case, the recovery cases module and tha adaptation module solutions, using LC-conceptual algorithm. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-05-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/47 Inteligencia Artificial; Vol. 19 No. 57 (2016): Inteligencia Artificial (June 2016); 82-96 Inteligencia Artificial; Vol. 19 Núm. 57 (2016): Inteligencia Artificial (June 2016); 82-96 Inteligencia Artificial; Vol. 19 N.º 57 (2016): Inteligencia Artificial (June 2016); 82-96 1988-3064 1137-3601 10.4114/intartif.vol19iss57 eng https://journal.iberamia.org/index.php/intartif/article/view/47/17

oai:journal.iberamia.org:article/48 2019-12-02T12:07:26Z intartif:Article driver

An Automated Defect Prediction Framework using Genetic Algorithms: A Validation of Empirical Studies Murillo-Morera, Juan Castro-Herrera, Carlos Arroyo, Javier Fuentes-Fernandez, Ruben Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding software practitioners. With timely and accurate defect predictions, practitioners can focus their limited testing resources on higher risk areas. This paper reports the results of three empirical studies that uses an automated genetic defect prediction framework. This framework generates and compares different learning schemes (preprocessing + attribute selection + learning algorithms) and selects the best one using a genetic algorithm, with the objective to estimate the defect proneness of a software module. The first empirical study is a performance comparison of our framework with the most important framework of the literature. The second empirical study is a performance and runtime comparison between our framework and an exhaustive framework. The third empirical study is a sensitivity analysis. The last empirical study, is our main contribution in this paper. Performance of the software development defect prediction models (using AUC, Area Under the Curve) was validated using NASA-MDP and PROMISE data sets. Seventeen data sets from NASA-MDP (13) and PROMISE (4) projects were analyzed running a NxM-fold cross-validation. A genetic algorithm was used to select the components of the learning schemes automatically, and to assess and report the results. Our results reported similar performance between frameworks. Our framework reported better runtime than exhaustive framework. Finally, we reported the best configuration according to sensitivity analysis. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-05-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/48 Inteligencia Artificial; Vol. 19 No. 57 (2016): Inteligencia Artificial (June 2016); 114-137 Inteligencia Artificial; Vol. 19 Núm. 57 (2016): Inteligencia Artificial (June 2016); 114-137 Inteligencia Artificial; Vol. 19 N.º 57 (2016): Inteligencia Artificial (June 2016); 114-137 1988-3064 1137-3601 10.4114/intartif.vol19iss57 eng https://journal.iberamia.org/index.php/intartif/article/view/48/18

oai:journal.iberamia.org:article/49 2019-12-02T12:07:26Z intartif:Theses driver

Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledge discovery López-Fernández, Hugo Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS) has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This allows quickly analyzing large sets of samples are in one single batch and doing high-throughput proteomics. In this scenario, bioinformatics methods and computational tools play a key role in MALDI-TOF data analysis, as they are able handle the large amounts of raw data generated in order to extract new knowledge and useful conclusions. A typical MALDI-TOF MS data analysis workflow has three main stages: data acquisition, preprocessing and analysis. Although the most popular use of this technology is to identify proteins through their peptides, analyses that make use of artificial intelligence (AI), machine learning (ML), and statistical methods can be also carried out in order to perform biomarker discovery, automatic diagnosis, and knowledge discovery. In this research work, this workflow is deeply explored and new solutions based on the application of AI, ML, and statistical methods are proposed. In addition, an integrated software platform that supports the full MALDI-TOF MS data analysis workflow that facilitate the work of proteomics researchers without advanced bioinformatics skills has been developed and released to the scientific community. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-05-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Theses Summaries application/pdf https://journal.iberamia.org/index.php/intartif/article/view/49 Inteligencia Artificial; Vol. 19 No. 57 (2016): Inteligencia Artificial (June 2016); 22-25 Inteligencia Artificial; Vol. 19 Núm. 57 (2016): Inteligencia Artificial (June 2016); 22-25 Inteligencia Artificial; Vol. 19 N.º 57 (2016): Inteligencia Artificial (June 2016); 22-25 1988-3064 1137-3601 10.4114/intartif.vol19iss57 eng https://journal.iberamia.org/index.php/intartif/article/view/49/19

oai:journal.iberamia.org:article/50 2019-12-02T12:07:26Z intartif:Theses driver

Application of learning techniques based on kernel methods for the fault diagnosis in industrial processes Bernal-de-Lázaro, Jose M. This article summarizes the main contributions of the PhD thesis titled: "Application of learning techniques based on kernel methods for the fault diagnosis in Industrial processes". This thesis focuses on the analysis and design of fault diagnosis systems (DDF) based on historical data. Specifically this thesis provides: (1) new criteria for adjustment of the kernel methods used to select features with a high discriminative capacity for the fault diagnosis tasks, (2) a proposed approach process monitoring using statistical techniques multivariate that incorporates a reinforced information concerning to the dynamics of the Hotelling's T2 and SPE statistics, whose combination with kernel methods improves the detection of small-magnitude faults; (3) an robustness index to compare the diagnosis classifiers performance taking into account their insensitivity to possible noise and disturbance on historical data. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-05-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Theses Summaries application/pdf https://journal.iberamia.org/index.php/intartif/article/view/50 Inteligencia Artificial; Vol. 19 No. 57 (2016): Inteligencia Artificial (June 2016); 74-81 Inteligencia Artificial; Vol. 19 Núm. 57 (2016): Inteligencia Artificial (June 2016); 74-81 Inteligencia Artificial; Vol. 19 N.º 57 (2016): Inteligencia Artificial (June 2016); 74-81 1988-3064 1137-3601 10.4114/intartif.vol19iss57 eng https://journal.iberamia.org/index.php/intartif/article/view/50/20

oai:journal.iberamia.org:article/52 2020-04-09T03:00:20Z intartif:Article driver

Â¿CuÃ¡l es el eslabÃ³n perdido en nuestra Ciencia de lo Artificial? Negrete Martínez, José La Inteligencia Artificial puede verse como un andamiaje cognitivo [1] de nuestra propia inteligencia y tambiÃ©n como un andamiaje para la cogniciÃ³n de mÃ¡quinas tales como los Robots enactivos [2]. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/52 10.4114/intartif.vol18iss56pp1-2 Inteligencia Artificial; Vol. 18 No. 56 (2015): Inteligencia Artificial (December 2015); 1-2 Inteligencia Artificial; Vol. 18 Núm. 56 (2015): Inteligencia Artificial (December 2015); 1-2 Inteligencia Artificial; Vol. 18 N.º 56 (2015): Inteligencia Artificial (December 2015); 1-2 1988-3064 1137-3601 10.4114/intartif.vol18iss56 eng https://journal.iberamia.org/index.php/intartif/article/view/52/21

oai:journal.iberamia.org:article/53 2020-04-09T03:00:20Z intartif:Article driver

A Neural Network Approach to Weibull Distributed Sea Clutter Parameter's Estimation Machado Fernández, José Raúl Bacallao Vidal, Jesus de la Concepción Chávez Ferry, Nelso The main problem faced by sea radars is the elimination of an undesirable signal that appears mixed with target information: sea clutter. The clutter results from the echo caused by the rebound of the primary emission at sea surface. One of the most popular probability distributions in clutter modelling is the Weibull distribution. Helpful in efficient detectorsâ€™ design, a system able to recognize the Weibull shape parameter knowing a priori that the mean of the distribution is equal to zero is proposed. The result is appropriate for real time operating conditions as it is based on a neural networks approximation in the estimator role. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/53 10.4114/intartif.vol18iss56pp3-13 Inteligencia Artificial; Vol. 18 No. 56 (2015): Inteligencia Artificial (December 2015); 3-13 Inteligencia Artificial; Vol. 18 Núm. 56 (2015): Inteligencia Artificial (December 2015); 3-13 Inteligencia Artificial; Vol. 18 N.º 56 (2015): Inteligencia Artificial (December 2015); 3-13 1988-3064 1137-3601 10.4114/intartif.vol18iss56 eng https://journal.iberamia.org/index.php/intartif/article/view/53/22

oai:journal.iberamia.org:article/54 2020-04-09T03:00:19Z intartif:Article driver

Naive Bayes vs Logistic Regression: Theory, Implementation and Experimental Validation Kumar Bhowmik, Tapan This article presents the theoretical derivation as well as practical steps for implementing Naive Bayes (NB) and Logistic Regression (LR) classifiers. A generative learning under Gaussian Naive Bayes assumption and two discriminative learning techniques based on gradient ascent and Newton-Raphson methods are described to estimate the parameters of LR. Some limitation of learning techniques and implementation issues are discussed as well. A set of experiments are performed for both the classifiers under different learning circumstances and their performances are compared. From the experiments, it is observed that LR learning with gradient ascent technique outperforms general NB classifier. However, under Gaussian Naive Bayes assumption, both classifiers NB and LR perform similar. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/54 10.4114/intartif.vol18iss56pp14-30 Inteligencia Artificial; Vol. 18 No. 56 (2015): Inteligencia Artificial (December 2015); 14-30 Inteligencia Artificial; Vol. 18 Núm. 56 (2015): Inteligencia Artificial (December 2015); 14-30 Inteligencia Artificial; Vol. 18 N.º 56 (2015): Inteligencia Artificial (December 2015); 14-30 1988-3064 1137-3601 10.4114/intartif.vol18iss56 eng https://journal.iberamia.org/index.php/intartif/article/view/54/23

oai:journal.iberamia.org:article/56 2020-04-09T03:00:19Z intartif:Article driver

Forward Models for Following a Moving Target with the Puma 560 Robot Manipulator Tello Gamarra, Daniel Fernando De Souza Leite Cuadros, Marco Antonio This paper describes how a forward model could be applied in a manipulator robot to accomplish the task of following a moving target. The forward model has been implemented in the puma 560 robot manipulator in simulation after a babbling motor phase using ANFIS neural networks. The forward model delivers a rough estimation of the position in the operational space of a moving target. Using this information a Cartesian controller tracks the moving target. An implementation of the proposed architecture and the Piepmeir algorithm for the problem of following a moving target is also shown in the paper. The control architecture proposed in this paper was also tested with MLP and RBF neural networks. Results and simulations are shown to demonstrate the applicability of our proposed architecture for tracking a moving target. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/56 10.4114/intartif.vol18iss56pp31-42 Inteligencia Artificial; Vol. 18 No. 56 (2015): Inteligencia Artificial (December 2015); 31-42 Inteligencia Artificial; Vol. 18 Núm. 56 (2015): Inteligencia Artificial (December 2015); 31-42 Inteligencia Artificial; Vol. 18 N.º 56 (2015): Inteligencia Artificial (December 2015); 31-42 1988-3064 1137-3601 10.4114/intartif.vol18iss56 eng https://journal.iberamia.org/index.php/intartif/article/view/56/24

oai:journal.iberamia.org:article/57 2020-04-09T03:00:18Z intartif:Theses driver

Energetic optimization of the chilled water systems operation at hotels Montero Laurencio, Reineris The hotel exploitation, while continuing to satisfy the customers, needs to decrease the requests of electric power as the principal energy carrier. Solving issues regarding the occupation of a hotel integrally, taking the air conditioning as center of attention, which demands the bigger consumptions of electricity, results in a complex task. To solve this issue, a procedure was implemented to optimize the operation of the water-chilled systems. The procedure integrates an energy model with a strategy of low occupation following energetic criteria based on combinatorial-evolutionary criteria. To classify the information, the formulation of the tasks and the synthesis of the solutions, a methodology of analysis and synthesis of engineering is used. The energetic model considers the variability of the local climatology and the occupation of the selected rooms, and includes: the thermal model of the building obtained by means of artificial neural networks, the hydraulic model and the model of the compression work. These elements allow to find the variable of decision occupation, performing intermediate calculations to obtain the velocity of rotation in the centrifugal pump and the output temperature of the cooler water, minimizing the requirements of electric power in the water-chilled systems. To evaluate the states of the system, a combinatorial optimization is used through the following methods: simple exhaustive, stepped exhaustive or genetic algorithm depending on the quantity of variants of occupation. All calculation tasks and algorithms of the procedure were automated through a computer application. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Theses Summaries application/pdf https://journal.iberamia.org/index.php/intartif/article/view/57 10.4114/intartif.vol18iss56pp43-46 Inteligencia Artificial; Vol. 18 No. 56 (2015): Inteligencia Artificial (December 2015); 43-46 Inteligencia Artificial; Vol. 18 Núm. 56 (2015): Inteligencia Artificial (December 2015); 43-46 Inteligencia Artificial; Vol. 18 N.º 56 (2015): Inteligencia Artificial (December 2015); 43-46 1988-3064 1137-3601 10.4114/intartif.vol18iss56 eng https://journal.iberamia.org/index.php/intartif/article/view/57/25

oai:journal.iberamia.org:article/59 2020-04-09T03:00:22Z intartif:Article driver

Decentralized Cooperative Metaheuristic for the Dynamic Berth Allocation Problem LallaRuiz, Eduardo Expósito Izquierdo, Christopher Melián Batista, Belén MorenoVega, J. Marcos The increasing demand of maritime transport and the great competition among port terminals force their managers to reduce costs by exploiting its resources accurately. In this environment, the Berth Allocation Problem, which aims to allocate and schedule incoming vessels along the quay, plays a relevant role in improving the overall terminal productivity. In order to address this problem, we propose Decentralized Cooperative Metaheuristic (DCM), which is a population-based approach that exploits the concepts of communication and grouping. In DCM, the individuals are organized into groups, where each individual shares information with its group partners. This grouping strategy allows to diversify as well as intensify the search in some regions by means of information shared among the individuals of each group. Moreover, the constrained relation for sharing information among individuals through the proposed grouping strategy allows to reduce computational resources in comparison to the `all to all' communication strategy. The computational experiments for this problem reveal that DCM reports high-quality solutions and identifies promising regions within the search space in short computational times. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-06-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/59 10.4114/intartif.vol18iss55pp1-11 Inteligencia Artificial; Vol. 18 No. 55 (2015): Inteligencia Artificial (June 2015); 1-11 Inteligencia Artificial; Vol. 18 Núm. 55 (2015): Inteligencia Artificial (June 2015); 1-11 Inteligencia Artificial; Vol. 18 N.º 55 (2015): Inteligencia Artificial (June 2015); 1-11 1988-3064 1137-3601 10.4114/intartif.vol18iss55 eng https://journal.iberamia.org/index.php/intartif/article/view/59/30

oai:journal.iberamia.org:article/60 2020-04-09T03:00:17Z intartif:Article driver

Elderly perception about the new technologies Marquine Raymundo, Taiuani da Silva Santana, Carla   Este estudo tem como objetivo analisar a percepÃ§Ã£o de idosos acerca das novas tecnologias e a influÃªncia de variÃ¡veis sociodemogrÃ¡ficas e da capacidade funcional na percepÃ§Ã£o da utilidade das novas tecnologias e facilidade no uso destas. Trata-se de um estudo descritivo, analÃtico e transversal de abordagem quantitativa. Os dados foram coletados por meio de questionÃ¡rios e a anÃ¡lise de dados foi realizada atravÃ©s do mÃ©todo de estatÃstica descritiva, do teste de t-Student, teste Qui-Quadrado e mÃ©todo de regressÃ£o logÃstica simples e mÃºltiplo. Participaram 100 idosos, sendo 77% do gÃªnero feminino e 82% independentes para realizaÃ§Ã£o das atividades instrumentais de vida diÃ¡ria. NÃ£o houve associaÃ§Ã£o significativa entre as variÃ¡veis estudadas. PorÃ©m, apÃ³s anÃ¡lise da presenÃ§a ou nÃ£o de fatores de risco, as mulheres apresentam menor chance de nÃ£o perceberem a utilidade das tecnologias e, os sujeitos com menor nÃvel educacional apresentam oito vezes mais chances de nÃ£o perceberem a utilidade. Conclui-se que variÃ¡veis como gÃªnero e nÃvel de instruÃ§Ã£o educacional sÃ£o fatores de risco para a percepÃ§Ã£o da utilidade das tecnologias e, variÃ¡veis como idade, renda, estado civil e capacidade funcional nÃ£o apresentaram associaÃ§Ãµes significativas com a percepÃ§Ã£o da utilidade e da facilidade no uso de tecnologias. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2016-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/60 10.4114/intartif.vol18iss55pp12-25 Inteligencia Artificial; Vol. 18 No. 55 (2015): Inteligencia Artificial (June 2015); 12-25 Inteligencia Artificial; Vol. 18 Núm. 55 (2015): Inteligencia Artificial (June 2015); 12-25 Inteligencia Artificial; Vol. 18 N.º 55 (2015): Inteligencia Artificial (June 2015); 12-25 1988-3064 1137-3601 10.4114/intartif.vol18iss55 eng https://journal.iberamia.org/index.php/intartif/article/view/60/31

oai:journal.iberamia.org:article/61 2020-04-09T03:00:21Z intartif:Article driver

A Virtual Village Network Architecture for improving the elderly people quality of life Morgavi, Giovanna   Elder people often feel pushed to the margins by the generational shift and suffer from loss of identity and hence they lose motivation, recognition and self-esteem: they are often considered to be no longer capable of performing any service. This paper proposes an ICT network architecture oriented to improve the quality of life of elderly people and their caregivers focused on the user need satisfaction and reducing negative feelings like insecurity, vulnerability, loneliness and depression. This Virtual Village Network architecture is organized on 3 levels: 1. the Virtual Service Centre (VSC) that, through a proper home interface, carries out the support, the monitoring, the prevention and the social facilitation; 2. the Intelligent Domotic Health Networks (DHN) a domotic modular network with high local evaluation ability through which the VSC can monitor the home and/or the userâ€™s state of wellness and of health ; 3. the Dynamical Village Network (DVN) that is an ICT network of users. The idea is to build an ICT network of â€œvirtual social neighboursâ€ facilitating user relationships, able to have positive influences on the interactive abilities and self-image of the elderly, and to prevent or overcome solitude, isolation and their negative effects on the elderly personâ€™s overall quality of life and health. The whole architecture is pervaded by strict attention paid to security and privacy. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-06-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/61 10.4114/intartif.vol18iss55pp26-34 Inteligencia Artificial; Vol. 18 No. 55 (2015): Inteligencia Artificial (June 2015); 26-34 Inteligencia Artificial; Vol. 18 Núm. 55 (2015): Inteligencia Artificial (June 2015); 26-34 Inteligencia Artificial; Vol. 18 N.º 55 (2015): Inteligencia Artificial (June 2015); 26-34 1988-3064 1137-3601 10.4114/intartif.vol18iss55 eng https://journal.iberamia.org/index.php/intartif/article/view/61/32

oai:journal.iberamia.org:article/62 2020-04-09T03:00:21Z intartif:Article driver

Elderly Usersâ€™ Perspective on the Use of Technology in Daily Life: A Comparative Study of a sample in the UK and Brazil da Silva Santana, Carla Leeson, George This paper investigated the perceptions of sample composed by British and Brazilian adults and older people on the use of electronic devices in their daily lives. This is an exploratory, cross-sectional, descriptive study involving 100 adults and elderly subjects, 50 Brazilian and 50 British adults. The data collection included a social-economic questionnaire; an IDLA index â€“ the Lawton & Brody scale (1969), and a self-reported and a structured questionnaire. The results show that exposure time to technology had a positive impact during the most advanced phases of usage, which was supported by reports of fewer difficulties in the use of such devices, a feeling of greater confidence, and a sense of belonging to the modern world. The frequency in the use electronic devices in daily life, the ability to use them, use perception in public as a stressful experience were shown to be the main differences between the British and Brazilian groups. Both are not comfortable in modern society, complain of unsuitable appliances and refer to their lack of contact with these devices in the past. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-06-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/62 10.4114/intartif.vol18iss55pp35-49 Inteligencia Artificial; Vol. 18 No. 55 (2015): Inteligencia Artificial (June 2015); 35-49 Inteligencia Artificial; Vol. 18 Núm. 55 (2015): Inteligencia Artificial (June 2015); 35-49 Inteligencia Artificial; Vol. 18 N.º 55 (2015): Inteligencia Artificial (June 2015); 35-49 1988-3064 1137-3601 10.4114/intartif.vol18iss55 eng https://journal.iberamia.org/index.php/intartif/article/view/62/33

oai:journal.iberamia.org:article/63 2020-04-09T03:00:21Z intartif:Article driver

Artificial Bee Colony (ABC) algorithm and its use in digital image processing Cuevas, Erik Classical methods often face great difficulties in solving image processing problems in images containing noise and distortions. Under such conditions, the use of bio-inspired optimization approaches has been extended. This paper explores the use of the Artificial Bee Colony (ABC) algorithm for digital image processing seen as an optimization problem. ABC is a heuristic algorithm motivated by the biological behaviour of honey-bees which has been successfully employed to solve complex optimization problems. In this paper, image segmentation and circle detection tasks are considered as examples, both issues approached as optimization problems. In segmentation, an image 1-D histogram is approximated through a Gaussian mixture model whose parameters are calculated by the ABC algorithm. On the other hand, the circle detector uses a combination of three edge points as parameters to construct candidate circles. A matching function determines is such candidate circles are actually present in the image. Experimental results show that the generated solutions are able to solve properly the considered problems. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-06-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/63 10.4114/intartif.vol18iss55pp50-68 Inteligencia Artificial; Vol. 18 No. 55 (2015): Inteligencia Artificial (June 2015); 50-68 Inteligencia Artificial; Vol. 18 Núm. 55 (2015): Inteligencia Artificial (June 2015); 50-68 Inteligencia Artificial; Vol. 18 N.º 55 (2015): Inteligencia Artificial (June 2015); 50-68 1988-3064 1137-3601 10.4114/intartif.vol18iss55 eng https://journal.iberamia.org/index.php/intartif/article/view/63/34

oai:journal.iberamia.org:article/64 2019-12-02T12:07:26Z intartif:Article driver

Comparative Study of Clustering Algorithms using OverallSimSUX Similarity Function for XML Documents Magdaleno Guevara, Damny Miranda, Yadriel Fuentes, Ivett Garc ía, María A huge amount of information is represented in XML format. Several tools have been developed to store, and query XML data. It becomes inevitable to develop high performance techniques for efficiently analysing extremely large collections of XML data. One of the methods that many researchers have focused on is clustering, which groups similar XML data, according to their content and structures. In previous work, there has been proposed the similarity function OverallSimSUX, that facilitates to capture the degree of similitude among the documents with a novel methodology for clustering XML documents using both structural and content features. Although this methodology shows good performance, endorsed by experiments with several corpus and statistical tests, on having had impliedly only one clustering algorithm, K-Star, we do not know the effect that it would suffer if we replaced this algorithm by other with dissimilar characteristics. Therefore to endorse completely the methodology, in this work we make a comparative study of the effects of applying the methodology for the OverallSimSUX similarity function calculation, using clustering algorithms of different classifications . Based on our analysis, we arrived to two important results: (1) The Fuzzy-SKWIC clustering algorithm works best both with methodology and without methodology, although there are not present significant differences respect to the K-Star clustering algorithm; (2) For each analysed algorithm when using the methodology, we obtain better results than when it is not taken into account. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-06-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/64 Inteligencia Artificial; Vol. 19 No. 57 (2016): Inteligencia Artificial (June 2016); 69-80 Inteligencia Artificial; Vol. 19 Núm. 57 (2016): Inteligencia Artificial (June 2016); 69-80 Inteligencia Artificial; Vol. 19 N.º 57 (2016): Inteligencia Artificial (June 2016); 69-80 1988-3064 1137-3601 10.4114/intartif.vol19iss57 eng https://journal.iberamia.org/index.php/intartif/article/view/64/35

oai:journal.iberamia.org:article/65 2020-04-09T03:00:22Z intartif:Article driver

The Hybrid ColorAnt-RT Algorithms and an Application to Register Allocation Mulati,, Mauro Lintzmayer, Carla da Silva, Anderson Ant Colony Optimization is a metaheuristic used to create heuristic algorithms to find good solutions for combinatorial optimization problems. This metaheuristic is inspired on the effective behavior present in some species of ants of exploring the environment to find and transport food to the nest. Several works have proposed using Ant Colony Optimization algorithms to solve problems such as vehicle routing, frequency assignment, scheduling and graph coloring. The graph coloring problem essentially consists in finding a number k of colors to assign to the vertices of a graph, so that there are no two adjacent vertices with the same color. This paper presents the hybrid ColorAnt-RT algorithms, a class of algorithms for graph coloring problems which is based on the Ant Colony Optimization metaheuristic and uses Tabu Search as local search. The experiments with ColorAnt-RT algorithms indicate that changing the way to reinforce the pheromone trail results in better results. In fact, the results with ColorAnt-RT show that it is a promising option in finding good approximations of k. The good results obtained by ColorAnt-RT motivated it use on a register allocation based on Ant Colony Optimization, called CARTRA. As a result, this paper also presents CARTRA, an algorithm that extends a classic graph coloring register allocator to use the graph coloring algorithm ColorAnt-RT. CARTRA minimizes the amount of spills, thereby improving the quality of the generated code. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2015-05-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/65 10.4114/intartif.vol18iss55pp81-111 Inteligencia Artificial; Vol. 18 No. 55 (2015): Inteligencia Artificial (June 2015); 81-111 Inteligencia Artificial; Vol. 18 Núm. 55 (2015): Inteligencia Artificial (June 2015); 81-111 Inteligencia Artificial; Vol. 18 N.º 55 (2015): Inteligencia Artificial (June 2015); 81-111 1988-3064 1137-3601 10.4114/intartif.vol18iss55 eng https://journal.iberamia.org/index.php/intartif/article/view/65/36

oai:journal.iberamia.org:article/66 2020-04-09T03:00:25Z intartif:Article driver

ConformaciÃ³n de equipos de proyectos de software aplicando algoritmos metaheurÃsticos de trayectoria multiobjetivo Infante, Ana Lilian André, Margarita Rosete, Alejandro Rampersaud, Lalchandra La inadecuada conformaciÃ³n de equipos de proyecto de software es un problema que afecta a la industria de software a nivel mundial. Este proceso resulta complejo, teniendo en cuenta que debe considerar varios factores, como son, asignar a los roles del equipo las personas con las competencias apropiadas, considerar las incompatibilidades entre los miembros y la carga de trabajo, entre otros. Esta situaciÃ³n se torna mÃ¡s compleja en organizaciones medianas y grandes, debido a la gran cantidad de combinaciones de asignaciones posibles, por lo que esta etapa es prÃ¡cticamente imposible de abordar de manera eficiente, sin la ayuda de modelos matemÃ¡ticos que representen el problema a resolver lo mÃ¡s objetivamente posible. Este trabajo toma como antecedente un modelo que incluye tanto factores individuales como factores de equipo y plantea: maximizar las competencias de los trabajadores, minimizar las incompatibilidades entre los miembros del equipo y balancear la carga de trabajo. Incluye ademÃ¡s, en una versiÃ³n ampliada del modelo, minimizar el costo de desarrollar software a distancia. El modelo citado responde a un problema de optimizaciÃ³n combinatorio multiobjetivo, por lo que para su soluciÃ³n se utilizaron algunas variantes multiobjetivo de los algoritmos metaheurÃsticos: BÃºsqueda TabÃº, Recocido Simulado y Escalador de Colinas. El estudio experimental realizado ha llevado a identificar que las variantes multiobjetivo del Escalador de Colinas: Escalador de Colinas EstocÃ¡tico Multiobjetivo, Escalador de Colinas Multiobjetivo por mayor distancia y Escalador de Colinas Multiobjetivo con Reinicio, asÃ como el algoritmo Recocido Simulado Multiobjetivo Multicaso son los que mejores resultados obtienen en este problema. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2014-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/66 10.4114/intartif.vol17iss54pp1-16 Inteligencia Artificial; Vol. 17 No. 54 (2014): Inteligencia Artificial (December 2014); 1-16 Inteligencia Artificial; Vol. 17 Núm. 54 (2014): Inteligencia Artificial (December 2014); 1-16 Inteligencia Artificial; Vol. 17 N.º 54 (2014): Inteligencia Artificial (December 2014); 1-16 1988-3064 1137-3601 10.4114/intartif.vol17iss54 eng https://journal.iberamia.org/index.php/intartif/article/view/66/37

oai:journal.iberamia.org:article/67 2020-04-09T03:00:24Z intartif:Article driver

Architectural design with simple shape grammars and learning Jiménez-Morales, Eduardo Ruiz-Montiel, Manuela Gavilanes, Juan Boned, Javier Mandow, Lawrence Pérez de la Cruz, José Luís This work presents a proposal for the automatic generation of architectural design. This scheme is based on the training of simple shape grammars through reinforcement learning technics. Finally, the results of the implemented system by this technic for the generation of dwelling design with certain restrictions are presented and analyzed. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2014-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/67 10.4114/intartif.vol17iss54pp21-29 Inteligencia Artificial; Vol. 17 No. 54 (2014): Inteligencia Artificial (December 2014); 21-29 Inteligencia Artificial; Vol. 17 Núm. 54 (2014): Inteligencia Artificial (December 2014); 21-29 Inteligencia Artificial; Vol. 17 N.º 54 (2014): Inteligencia Artificial (December 2014); 21-29 1988-3064 1137-3601 10.4114/intartif.vol17iss54 eng https://journal.iberamia.org/index.php/intartif/article/view/67/38

oai:journal.iberamia.org:article/69 2020-04-09T03:00:24Z intartif:Article driver

A Study of Rescheduling Strategies for the Quay Crane Scheduling Problem under Random Disruptions Expósito-Izquierdo, Christopher Lalla-Ruiz, Eduardo Melian-Batista,, Belén Moreno-Vega, J. Marcos Providing a suitable answer to different types of unforeseen changes in optimization problems is one challenging goal. This paper addresses the Quay Crane Scheduling Problem under random disruptions, whose goal is to determine the sequences of transshipment operations performed by a set of quay cranes in order to load and unload containers onto/from a berthed container vessel. An evolutionary algorithm is used to find an initial solution of the problem with completely deterministic data, whereas several rescheduling strategies are integrated into a dynamism management system aimed at keeping a proper quality level after a random disruption. Computational experiments indicate that using knowledge about previous static problems can largely improve the performance of the implemented schedule. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2014-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/69 10.4114/intartif.vol17iss54pp35-47 Inteligencia Artificial; Vol. 17 No. 54 (2014): Inteligencia Artificial (December 2014); 35-47 Inteligencia Artificial; Vol. 17 Núm. 54 (2014): Inteligencia Artificial (December 2014); 35-47 Inteligencia Artificial; Vol. 17 N.º 54 (2014): Inteligencia Artificial (December 2014); 35-47 1988-3064 1137-3601 10.4114/intartif.vol17iss54 eng https://journal.iberamia.org/index.php/intartif/article/view/69/39

oai:journal.iberamia.org:article/70 2018-02-06T16:53:19Z intartif:Article driver

PSPLIB-ENERGY: a extension of PSPLIB library to assess the energy optimization in the RCPSP Morillo Torres, Daniel Barber, Federico Salido, Miguel A. Scheduling problems is one of the core areas in the planning and development of any project, with a wide applicability to real-world situations. Due to the high complexity of these problems, the solving process is often based on metaheuristics techniques, so that the evaluation of these methods is empirical. Therefore benchmarks, which provide a set of test cases to assess the behavior of algorithms, are generated. This paper extends the PSPLIB library. This extension incorporates to each instance of RCPSP (Resource Constrained Project Scheduling Problem), a realistic mathematical model of energy consumption. This proposal provides an alternative to the current trend in the eld of optimization and manufacturing that requires the inclusion of components and methods that reduce the environmental impact in the process of decision making. Finally a new optimality criterion is proposed to compare dierent search techniques. The PSPLIB-ENERGY is available at http://gps. webs.upv.es/psplib-energy/. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2014-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/70 10.4114/intartif.vol17iss54pp48-61 Inteligencia Artificial; Vol. 17 No. 54 (2014): Inteligencia Artificial (December 2014); 48-61 Inteligencia Artificial; Vol. 17 Núm. 54 (2014): Inteligencia Artificial (December 2014); 48-61 Inteligencia Artificial; Vol. 17 N.º 54 (2014): Inteligencia Artificial (December 2014); 48-61 1988-3064 1137-3601 10.4114/intartif.vol17iss54 eng https://journal.iberamia.org/index.php/intartif/article/view/70/40

oai:journal.iberamia.org:article/71 2020-04-09T03:00:23Z intartif:Theses driver

AnÃ¡lisis y DiseÃ±o de Sistemas Multiagente Normativos Abiertos Garcia, Emilia Giret, Adriana This article summarizes the main contributions of the thesis titled "Engineering Regulated Open Multiagent Systems". This thesis is focused on the analysis and design of normative open systems using multiagent technology. Specifically this thesis offers: (1) a metamodel that allows especifying all the features of systems of this kind; (2) a methodology that covers the analysis through a detailed development process and specific guidelines that include the identification and formalization of the normative context of the system; (3) a CASE tool that integrates the design of the system with the formal verification of its normative context. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2014-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Theses Summaries application/pdf https://journal.iberamia.org/index.php/intartif/article/view/71 10.4114/intartif.vol17iss54pp17-20 Inteligencia Artificial; Vol. 17 No. 54 (2014): Inteligencia Artificial (December 2014); 17-20 Inteligencia Artificial; Vol. 17 Núm. 54 (2014): Inteligencia Artificial (December 2014); 17-20 Inteligencia Artificial; Vol. 17 N.º 54 (2014): Inteligencia Artificial (December 2014); 17-20 1988-3064 1137-3601 10.4114/intartif.vol17iss54 eng https://journal.iberamia.org/index.php/intartif/article/view/71/41

oai:journal.iberamia.org:article/73 2020-04-09T03:00:23Z intartif:Theses driver

New training approaches for classification based on evolutionary neural networks. Application to product and sigmoidal units Tallón-Ballesteros, Antonio J. This paper sums up the main contributions of the PhD Dissertation with an homonymous name to the current article. Specifically, three contributions to train feed-forward neural network models based on evolutionary computation for a classification task are described. The new methodologies have been evaluated in three-layered neural models, including one input, one hidden and one output layer. Particularly, two kind of neurons such as product and sigmoidal units have been considered in an independent fashion for the hidden layer. Experiments have been carried out in a good number of problems, including three complex real-world problems, and the overall assessment of the new algorithms is very outstanding. Statistical tests shed light on that significant improvements were achieved. The applicability of the proposals is wide in the sense that can be extended to any kind of hidden neuron, either to other kind of problems like regression or even optimization with special emphasis in the two first approaches. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2014-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Theses Summaries application/pdf https://journal.iberamia.org/index.php/intartif/article/view/73 10.4114/intartif.vol17iss54pp30-34 Inteligencia Artificial; Vol. 17 No. 54 (2014): Inteligencia Artificial (December 2014); 30-34 Inteligencia Artificial; Vol. 17 Núm. 54 (2014): Inteligencia Artificial (December 2014); 30-34 Inteligencia Artificial; Vol. 17 N.º 54 (2014): Inteligencia Artificial (December 2014); 30-34 1988-3064 1137-3601 10.4114/intartif.vol17iss54 eng https://journal.iberamia.org/index.php/intartif/article/view/73/42

oai:journal.iberamia.org:article/75 2019-12-02T12:06:55Z intartif:Article driver

Energy planning under uncertain decision-making environment: An evidential reasoning approach to prioritize renewable energy sources Sellak, Hamza Ouhbi, Brahim Frikh, Bouchra Nowadays, making strategic decisions in a sensitive sector such as energy planning that usually requiresallocating huge funds, time, and resources is a difficult task. For instance, prioritizing a set of Renewable EnergySources (RES) is a complex multi-dimensional task that typically involves a range of conflicting criteria featuringdifferent forms of evaluation data in an uncertain decision-making environment. This process is aligned withseveral sources that can be uncertain, including imprecise information, limited domain knowledge from decisionmakers,and failures to provide accurate judgments from experts. In this study, we propose to use the EvidentialReasoning (ER) approach to manage the expanding complexities and uncertainties in RES prioritization problem.The ER approach is employed as a multiple criteria framework to assess the appropriateness regarding the use ofdifferent renewable energy technologies. A case study is provided to illustrate the implementation process. Resultsshow that using the ER approach when assessing the sustainability of different RES under uncertainty allowsproviding robust decisions, which brings out a more accurate, effective, and better-informed decision-making toolto conduct the evaluation process. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/75 10.4114/intartif.vol20iss59pp21-31 Inteligencia Artificial; Vol. 20 No. 59 (2017): Inteligencia Artificial (June 2017); 21-31 Inteligencia Artificial; Vol. 20 Núm. 59 (2017): Inteligencia Artificial (June 2017); 21-31 Inteligencia Artificial; Vol. 20 N.º 59 (2017): Inteligencia Artificial (June 2017); 21-31 1988-3064 1137-3601 10.4114/intartif.vol20iss59 eng https://journal.iberamia.org/index.php/intartif/article/view/75/43

oai:journal.iberamia.org:article/76 2019-12-02T12:06:55Z intartif:Article driver

A Review on Intelligent Monitoring and Activity Interpretation Castillo, José Carlos Fernández-Caballero, Antonio López, María Teresa Monitoring Surveillance Activity Interpretation Frameworks This survey paper provides a tour of the various monitoring and activity interpretation frameworks found in the literature. The needs of monitoring and interpretation systems are presented in relation to the area where they have been developed or applied. Their evolution is studied to better understand the characteristics of current systems. After this, the main features of monitoring and activity interpretation systems are defined.  Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-08 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/76 10.4114/intartif.vol20iss59pp53-69 Inteligencia Artificial; Vol. 20 No. 59 (2017): Inteligencia Artificial (June 2017); 53-69 Inteligencia Artificial; Vol. 20 Núm. 59 (2017): Inteligencia Artificial (June 2017); 53-69 Inteligencia Artificial; Vol. 20 N.º 59 (2017): Inteligencia Artificial (June 2017); 53-69 1988-3064 1137-3601 10.4114/intartif.vol20iss59 eng https://journal.iberamia.org/index.php/intartif/article/view/76/45

oai:journal.iberamia.org:article/78 2019-12-02T12:06:55Z intartif:Article driver

Decision Making in Dynamic Information Environments Oliveira, Tiago Montoya, Jose Carlos Novais, Paulo Satoh, Ken If there is no knowledge about the state of the world, getting the appropriate response to an event becomes impossible. Situations of uncertainty are common in the most varied environments and have the potential to impair or even stop the decision-making process. Thus, reaching an outcome in such situations requires the development of decision frameworks that account for missing, contradictory or uncertain information. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-10 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/78 10.4114/intartif.vol20iss59pp5-7 Inteligencia Artificial; Vol. 20 No. 59 (2017): Inteligencia Artificial (June 2017); 5-7 Inteligencia Artificial; Vol. 20 Núm. 59 (2017): Inteligencia Artificial (June 2017); 5-7 Inteligencia Artificial; Vol. 20 N.º 59 (2017): Inteligencia Artificial (June 2017); 5-7 1988-3064 1137-3601 10.4114/intartif.vol20iss59 eng https://journal.iberamia.org/index.php/intartif/article/view/78/47 Copyright (c) 2017 Iberamia & The Authors

oai:journal.iberamia.org:article/80 2019-12-02T12:06:55Z intartif:Article driver

How the ability to analyse tendencies influences decision satisfaction Carneiro, Joao Martinho, Diogo Conceição, Luís Marreiros, Goreti Novais, Paulo Group Decision Support Systems Argumentation Decision Satisfaction Automatic Negotiation Multi-Agent Systems Using agents to represent decision-makers is a complex task. It is important that agents can understand the context and be more proactive. Here we propose a model and an algorithm that will allow the agent to analyse tendencies regarding the number of supporters for each alternative along the process. It is intended that agents can be more dynamic and intelligent and can evaluate different contexts throughout the decision-making process. We believe agents will achieve better and consensual decisions more easily. We tested our model in three simulation environments with different complexity levels. Our model proved that agents that use it will obtain higher average consensus and satisfaction levels. Besides that, agents using this model will obtain those higher consensus and satisfaction levels in most of the times compared to agents that do not use it. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-14 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/80 10.4114/intartif.vol20iss59pp8-20 Inteligencia Artificial; Vol. 20 No. 59 (2017): Inteligencia Artificial (June 2017); 8-20 Inteligencia Artificial; Vol. 20 Núm. 59 (2017): Inteligencia Artificial (June 2017); 8-20 Inteligencia Artificial; Vol. 20 N.º 59 (2017): Inteligencia Artificial (June 2017); 8-20 1988-3064 1137-3601 10.4114/intartif.vol20iss59 eng https://journal.iberamia.org/index.php/intartif/article/view/80/49 Copyright (c) 2017 Iberamia & The Authors

oai:journal.iberamia.org:article/83 2020-04-09T03:00:15Z intartif:Article driver

RevisiÃ³n bibliogrÃ¡ï¬ca sobre funciones objetivo para el apilamiento de contenedores Jacomino, Laidy De Armas Pérez, Rafael Bello Pérez, Carlos Morell Apilar contenedores almacenar contenedores función objetivo optimización  Una terminal de contenedores es una fuente de disÃmiles problemas de Ãndole matemÃ¡tica y por ende computacional. En particular el apilamiento de contenedores en el patio de una terminal marÃtima es una de las operaciones mÃ¡s importantes, debido fundamentalmente, a los cuellos de botella que en Ã©l surgen, con los respectivos incumplimientos de los indicadores de eï¬ciencia. El apilamiento de contenedores se divide en actividades de carga, descarga y recolocaciÃ³n o premarshalling de contenedores. Cuando se realizan estas actividades los operarios y directivos deben determinar las posiciones exactas para los contenedores, descargarlos o recolocarlos haciendo un uso eï¬ciente del espacio de almacenamiento disponible, reduciendo los movimientos improductivos y los costos de transportaciÃ³n, etc. El propÃ³sito del presente trabajo es revisar y describir funciones objetivo encontradas en la literatura sobre problemas de optimizaciÃ³n que surgen durante el apilamiento de contenedores. Las funciones objetivo analizadas estÃ¡n agrupadas en dos clases fundamentales: minimizar movimientos improductivos de las grÃºas de patio y minimizar costo de transportaciÃ³n de los contenedores durante el apilamiento. SegÃºn el conocimiento de los autores no se encuentra disponible en la literatura revisada una clasiï¬caciÃ³n atendiendo a la modelaciÃ³n matemÃ¡tica de las funciones objetivo similar a la propuesta. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-05-19 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/83 10.4114/intartif.vol20iss60pp28-50 Inteligencia Artificial; Vol. 20 No. 60 (2017): Inteligencia Artificial (December 2017); 28-50 Inteligencia Artificial; Vol. 20 Núm. 60 (2017): Inteligencia Artificial (December 2017); 28-50 Inteligencia Artificial; Vol. 20 N.º 60 (2017): Inteligencia Artificial (December 2017); 28-50 1988-3064 1137-3601 10.4114/intartif.vol20iss60 eng https://journal.iberamia.org/index.php/intartif/article/view/83/55 Copyright (c) 2017 Iberamia & The Authors

oai:journal.iberamia.org:article/87 2020-04-09T03:00:16Z intartif:Article driver

Intelligent tutoring Module for a 3Dgame-based science e-learning platform Liu, Donfeng Barba-Guamán, Luis Valdiviezo-Díaz, Priscila Riofrio, Guido Intelligent Tutoring System, 3D Game-based Learning System, Reasoning modelling The three-dimensional (3D) game-based intelligent science tutoring system (GIST) is an e- learningplatform for science. The individual complexity of 3D games and conventional intelligent tutoring systems (ITS)results in extra complexities in system design and development of GIST. It is significant to develop practicalGIST, not just to seek the powerful ones. The main contribution of this paper is the lightweight modelling of theintelligent tutoring module based on the brief-desire-intention (BDI) framework. The tutoring module, which isimplemented by integration of the BDI framework into a game actor, can be able to suggest to each studentspecific learning tasks based on his/her learning histories. As a study case, algebra-based physics are intentionallychosen as the learning contents in this 3D game-based learning system, since the most of existing 3D game-basedlearning systems only focused on the qualitative understanding of physical concepts. Our proposed modelling isonly based on the BDI reasoning mechanism, so it can be easily extended to obtain practical GIST by usingstandard game engines. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-02-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/87 10.4114/intartif.vol20iss60pp1-19 Inteligencia Artificial; Vol. 20 No. 60 (2017): Inteligencia Artificial (December 2017); 1-19 Inteligencia Artificial; Vol. 20 Núm. 60 (2017): Inteligencia Artificial (December 2017); 1-19 Inteligencia Artificial; Vol. 20 N.º 60 (2017): Inteligencia Artificial (December 2017); 1-19 1988-3064 1137-3601 10.4114/intartif.vol20iss60 eng https://journal.iberamia.org/index.php/intartif/article/view/87/50

oai:journal.iberamia.org:article/89 2020-04-09T03:00:15Z intartif:Article driver

A Novel adaptive Discrete Cuckoo Search Algorithm for parameter optimization in computer vision benchikhi, loubna Sadgal, Mohamed Elfazziki, Aziz Mansouri, Fatimaezzahra Computer vision; image processing; parameter optimization; metaheuristic; ADCS; quality control. Computer vision applications require choosing operators and their parameters, in order to provide the best outcomes. Often, the users quarry on expert knowledge and must experiment many combinations to find manually the best one. As performance, time and accuracy are important, it is necessary to automate parameter optimization at least for crucial operators. In this paper, a novel approach based on an adaptive discrete cuckoo search algorithm (ADCS) is proposed. It automates the process of algorithmsâ€™ setting and provides optimal parameters for vision applications. This work reconsiders a discretization problem to adapt the cuckoo search algorithm and presents the procedure of parameter optimization. Some experiments on real examples and comparisons to other metaheuristic-based approaches: particle swarm optimization (PSO), reinforcement learning (RL) and ant colony optimization (ACO) show the efficiency of this novel method. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2017-10-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/89 10.4114/intartif.vol20iss60pp51-71 Inteligencia Artificial; Vol. 20 No. 60 (2017): Inteligencia Artificial (December 2017); 51-71 Inteligencia Artificial; Vol. 20 Núm. 60 (2017): Inteligencia Artificial (December 2017); 51-71 Inteligencia Artificial; Vol. 20 N.º 60 (2017): Inteligencia Artificial (December 2017); 51-71 1988-3064 1137-3601 10.4114/intartif.vol20iss60 eng https://journal.iberamia.org/index.php/intartif/article/view/89/54 Copyright (c) 2017 Iberamia & The Authors

oai:journal.iberamia.org:article/90 2020-04-09T03:00:14Z intartif:Article driver

The Pattern Recognition in Cattle Brand using Bag of Visual Words and Support Vector Machines Multi-Class Silva, Carlos Welfer, Daniel Dornelles, Cláudia Computer vision, Pattern recognition, Machine learning, Bag of Visual Words, Support Vector Machines Multi-Class. The recognition images of cattle brand in an automatic way is a necessity to governmental organs responsible for this activity. To help this process, this work presents a method that consists in using Bag of Visual Words for extracting of characteristics from images of cattle brand and Support Vector Machines Multi-Class for classification. This method consists of six stages: a) select database of images; b) extract points of interest (SURF); c) create vocabulary (K-means); d) create vector of image characteristics (visual words); e) train and sort images (SVM); f) evaluate the classification results. The accuracy of the method was tested on database of municipal city hall, where it achieved satisfactory results, reporting 86.02% of accuracy and 56.705 seconds of processing time, respectively. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-03-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/90 10.4114/intartif.vol21iss61pp1-13 Inteligencia Artificial; Vol. 21 No. 61 (2018): Inteligencia Artificial (June 2018); 1-13 Inteligencia Artificial; Vol. 21 Núm. 61 (2018): Inteligencia Artificial (June 2018); 1-13 Inteligencia Artificial; Vol. 21 N.º 61 (2018): Inteligencia Artificial (June 2018); 1-13 1988-3064 1137-3601 10.4114/intartif.vol21iss61 eng https://journal.iberamia.org/index.php/intartif/article/view/90/56 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/116 2023-02-14T17:46:49Z intartif:Article driver

Sentiment polarity classification of tweets using a extended dictionary Camargo, Jorge E. Vargas-Calderon, Vladimir Vargas, Nelson Calderón-Benavides, Liliana With the purpose of classifying text based on its sentiment polarity (positive or negative), we proposed an extension of a 68,000 tweets corpus through the inclusion of word definitions from a dictionary of the Real Academia Espa\~{n}ola de la Lengua (RAE). A set of 28,000 combinations of 6 Word2Vec and support vector machine parameters were considered in order to evaluate how positively would affect the inclusion of a RAE's dictionary definitions classification performance. We found that such a corpus extension significantly improve the classification accuracy. Therefore, we conclude that the inclusion of a RAE's dictionary increases the semantic relations learned by Word2Vec allowing a better classification accuracy. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-09-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/116 10.4114/intartif.vol21iss62pp1-12 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 1-12 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 1-12 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 1-12 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/116/67 Copyright (c) 2018 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/119 2023-11-28T18:46:22Z intartif:Article driver

Machine Learning-Based Analysis of the Association Between Online Texts and Stock Price Movements Darena, Frantisek Petrovsky, Jonas zizka, Jan prichystal, Jan The paper presents the result of experiments that were designed with the goal of revealing the association between texts published in online environments (Yahoo! Finance, Facebook, and Twitter) and changes in stock prices of the corresponding companies at a micro level. The association between lexicon detected sentiment and stock price movements was not confirmed. It was, however, possible to reveal and quantify such association with the application of machine learning-based classification. From the experiments it was obvious that the data preparation procedure had a substantial impact on the results. Thus, different stock price smoothing, lags between the release of documents and related stock price changes, five levels of a minimal stock price change, three different weighting schemes for structured document representation, and six classifiers were studied. It has been shown that at least part of the movement of stock prices is associated with the textual content if a proper combination of processing parameters is selected. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-05-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/119 10.4114/intartif.vol21iss61pp95-110 Inteligencia Artificial; Vol. 21 No. 61 (2018): Inteligencia Artificial (June 2018); 95-110 Inteligencia Artificial; Vol. 21 Núm. 61 (2018): Inteligencia Artificial (June 2018); 95-110 Inteligencia Artificial; Vol. 21 N.º 61 (2018): Inteligencia Artificial (June 2018); 95-110 1988-3064 1137-3601 10.4114/intartif.vol21iss61 eng https://journal.iberamia.org/index.php/intartif/article/view/119/62 Copyright (c) 2018 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/122 2020-04-09T03:00:10Z intartif:Article driver

aPaRT: A Fast Meta-Heuristic Algorithm using Path-Relinking and Tabu Search for Allocating Machines to Operations in FJSP Problem Jazayeriy, Hamid Bakhtar, Sahar Valinataj, Mojtaba Job shop scheduling Path-relinking Local search Tabu search Makespan This paper proposes a multi-start local search algorithm that solves the flexible job-shop scheduling (FJSP) problem to minimize makespan. The proposed algorithm uses a path-relinking method to generate near optimal solutions. A heuristic parameter, $\alpha$, is used to assign machines to operations.Also, a tabu list is applied to avoid getting stuck at local optimums.The proposed algorithm is tested on two sets of benchmark problems (BRdata and Kacem) to make a comparison with the variable neighborhood search.The experimental results show that the proposed algorithm can produce promising solution in a shorter amount of time. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-05-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/122 10.4114/intartif.vol21iss61pp111-123 Inteligencia Artificial; Vol. 21 No. 61 (2018): Inteligencia Artificial (June 2018); 111-123 Inteligencia Artificial; Vol. 21 Núm. 61 (2018): Inteligencia Artificial (June 2018); 111-123 Inteligencia Artificial; Vol. 21 N.º 61 (2018): Inteligencia Artificial (June 2018); 111-123 1988-3064 1137-3601 10.4114/intartif.vol21iss61 eng https://journal.iberamia.org/index.php/intartif/article/view/122/63 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/127 2020-04-09T03:00:14Z intartif:Article driver

Semantic analysis on faces using deep neural networks: AnÃ¡lisis semÃ¡ntico en rostros utilizando redes neuronales profundas. Pellejero, Nicolás Federico Grinblat, Guillermo Uzal, Lucas Deep, Learning, Emotion, Recognition. In this paper we address the problem of automatic emotion recognition and classification through video. Nowadays there are excellent results focused on lab-made datasets, with posed facial expressions. On the other hand there is room for a lot of improvement in the case of `in the wild' datasets, where light, face angle to the camera, etc. are taken into account. In these cases it could be very harmful to work with a small dataset. Currently, there are not big enough datasets of adequately labeled faces for the task.\\ We use Generative Adversarial Networks in order to train models in a semi-supervised fashion, generating realistic face images in the process, allowing the exploitation of a big cumulus of unlabeled face images. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-03-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/127 10.4114/intartif.vol21iss61pp14-29 Inteligencia Artificial; Vol. 21 No. 61 (2018): Inteligencia Artificial (June 2018); 14-29 Inteligencia Artificial; Vol. 21 Núm. 61 (2018): Inteligencia Artificial (June 2018); 14-29 Inteligencia Artificial; Vol. 21 N.º 61 (2018): Inteligencia Artificial (June 2018); 14-29 1988-3064 1137-3601 10.4114/intartif.vol21iss61 eng https://journal.iberamia.org/index.php/intartif/article/view/127/61 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/136 2020-04-09T03:00:13Z intartif:Article driver

From Imitation to Prediction, Data Compression vs Recurrent Neural Networks for Natural Language Processing Laura, Juan Andres Masi, Gabriel Omar Argerich, Luis Natural Language Processing Compression algorithms Neural networks Predictions In recent studies Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions. In addition, Data Compression is also based on prediction. What the problem comes down to is whether a data compressor could be used to perform as well as recurrent neural networks in the natural language processing tasks of sentiment analysis and automatic text generation. If this is possible, then the problem comes down to determining if a compression algorithm is even more intelligent than a neural network in such tasks. In our journey, a fundamental difference between a Data Compression Algorithm and Recurrent Neural Networks has been discovered. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-03-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/136 10.4114/intartif.vol21iss61pp30-46 Inteligencia Artificial; Vol. 21 No. 61 (2018): Inteligencia Artificial (June 2018); 30-46 Inteligencia Artificial; Vol. 21 Núm. 61 (2018): Inteligencia Artificial (June 2018); 30-46 Inteligencia Artificial; Vol. 21 N.º 61 (2018): Inteligencia Artificial (June 2018); 30-46 1988-3064 1137-3601 10.4114/intartif.vol21iss61 eng https://journal.iberamia.org/index.php/intartif/article/view/136/59 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/137 2020-04-09T03:00:12Z intartif:Article driver

Comparing detection and disclosure of traffic incidents in social networks: an intelligent approach based on Twitter vs. Waze: Comparando la detecciÃ³n y la divulgaciÃ³n de incidentes de trÃ¡nsito en redes sociales: un enfoque inteligente basado en Twitter vs. Waze Vallejos, Sebastián Caimmi, Brian Alonso, Diego Gabriel Berdun, Luis Sebastián Soria, Ãlvaro Incidentes de Tránsito Twitter Waze Aprendizaje de Máquina Procesamiento de Lenguaje Natural Nowadays, social networks have become  in a  communication  medium widely  used to disseminate any type  of  information. In  particular,  the  shared  information  in  social  networks  usually  includes  a  considerable number of traffic incidents reports of specific cities. In light of this, specialized social networks have emerged for detecting and disseminating traffic incidents, differentiating from generic social networks in which a wide variety of  topics  are  communicated.  In this  context,  Twitter  is  a  case  in  point  of  a  generic  social  network  in  which  its users often share information about traffic incidents, while Waze is a social network specialized in traffic. In this paper we present a comparative study between Waze and an intelligent approach that detects traffic incidents by analyzing publications shared in Twitter. The comparative study was carried out considering Ciudad AutÃ³noma de Buenos  Aires  (CABA),  Argentina,  as  the  region  of  interest.  The results of this work suggest that both social networks should be considered as complementary sources of information. This conclusion is based on the fact that the proportion of mutual detections, i.e. traffic incidents detected by both approaches, was considerably low since it did not exceed 6% of the cases. Moreover, the results do not show that any of the approaches tend to anticipate in time to the other one in the detection of traffic incidents. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-03-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/137 10.4114/intartif.vol21iss61pp47-66 Inteligencia Artificial; Vol. 21 No. 61 (2018): Inteligencia Artificial (June 2018); 47-66 Inteligencia Artificial; Vol. 21 Núm. 61 (2018): Inteligencia Artificial (June 2018); 47-66 Inteligencia Artificial; Vol. 21 N.º 61 (2018): Inteligencia Artificial (June 2018); 47-66 1988-3064 1137-3601 10.4114/intartif.vol21iss61 eng https://journal.iberamia.org/index.php/intartif/article/view/137/57 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/138 2020-04-09T03:00:12Z intartif:Article driver

Exploring the impact of word embeddings for disjoint semisupervised Spanish verb sense disambiguation Cardellino, Cristian Alonso Alemany, Laura This work explores the use of word embeddings as features for Spanish  verb sense disambiguation (VSD). This type of learning technique is named disjoint semisupervised learning: an unsupervised algorithm (i.e. the word embeddings) is trained on unlabeled data separately as a first step, and then its results are used by a supervised classifier. In this work we primarily focus on two aspects of VSD trained with unsupervised word representations. First, we show how the domain where the word embeddings are trained affects the performance of the supervised task. A specific domain can improve the results if this domain is shared with the domain of the supervised task, even if the word embeddings are trained with smaller corpora. Second, we show that the use of word embeddings can help the model generalize when compared to not using word embeddings. This means embeddings help by decreasing the model tendency to overfit. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-03-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/138 10.4114/intartif.vol21iss61pp67-81 Inteligencia Artificial; Vol. 21 No. 61 (2018): Inteligencia Artificial (June 2018); 67-81 Inteligencia Artificial; Vol. 21 Núm. 61 (2018): Inteligencia Artificial (June 2018); 67-81 Inteligencia Artificial; Vol. 21 N.º 61 (2018): Inteligencia Artificial (June 2018); 67-81 1988-3064 1137-3601 10.4114/intartif.vol21iss61 eng https://journal.iberamia.org/index.php/intartif/article/view/138/58 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/139 2020-04-09T03:00:11Z intartif:Article driver

From "tactical discussion" in collaboration game to "behaviors": A classification approach in stages.: De "discusiÃ³n tÃ¡ctica" en juego de colaboraciÃ³n a "conductas": enfoque de clasificaciÃ³n en etapas. Serrano, Francisco Berdun, Franco D. Armentano, Marcelo G. automatic classification group dynamic gamification user modeling The analysis of group dynamics is extremely useful for understanding and predicting the performance of teamworkâ€™s, since in this context, collaboration problems can naturally arise. Artificial intelligence, and specially machine learning techniques, enables automating the observation process and the analysis of groups of users who use an online collaborative platform. Among the online collaborative platforms available, games are an attractive alternative for all audiences that enable capturing the playersâ€™ behavior by observing their social interactions, while engaging them in a pleasant activity. In this paper, we present experimental results of classifying observed conversations in an online game to collaborative behaviors, guided by the Interaction Process Analysis, a theory for categorizing social interactions. The proposed automation of the classification process can be used to assist teachers or team leaders to detect alterations in the balance of group reactions and to improve their performance by indicating actions to improve the balance. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-03-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/139 10.4114/intartif.vol21iss61pp82-94 Inteligencia Artificial; Vol. 21 No. 61 (2018): Inteligencia Artificial (June 2018); 82-94 Inteligencia Artificial; Vol. 21 Núm. 61 (2018): Inteligencia Artificial (June 2018); 82-94 Inteligencia Artificial; Vol. 21 N.º 61 (2018): Inteligencia Artificial (June 2018); 82-94 1988-3064 1137-3601 10.4114/intartif.vol21iss61 eng https://journal.iberamia.org/index.php/intartif/article/view/139/60 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/168 2020-04-09T03:00:09Z intartif:Article driver

Reglas para predecir el cumplimiento de la calidad del agua residual en una planta tratadora con minerÃa de datos Martínez, Facundo Cortés Cansino, Alejandro Treviño García, María-Aracelia Alcorta Fraire, Arturo Tadeo Espinoza Esqueda, José Armando Sáenz Velez, Julio Gerardo Lozoya Demanda bioquímica de oxígeno, árbol de decisión, variables nominales, clasificación, minería de datos Un problema que enfrentan los organismos operadores de agua, es el cumplimiento de la normatividaden la calidad del agua residual tratada. Por lo que es recomendable implementar estrategias que favorezcan elcumplimiento de las regulaciones. La minerÃa de datos es una herramienta que permite predecir la calidad del aguaen el efluente de los sistemas de tratamiento. En el presente estudio se propone un criterio para el pre procesado dedatos donde se consideraron variables nominales. Luego se aplicÃ³ el sistema de minerÃa de datos (clasificaciÃ³n)para definir la predicciÃ³n de la calidad del agua. Se aplicaron los siguientes clasificadores: OneR; decisiÃ³n tables,J48, Ã¡rbol de decisiÃ³n de un solo nivel; PART y LMT. Los resultados muestran que el mejor algoritmo fue el J48:87.35 % de instancias correctamente clasificadas. El Ã¡rbol de decisiÃ³n determinÃ³ dos reglas para el cumplimientocon la normatividad. Es importante indicar que a la fecha existen procedimientos con minerÃa de datos parapredecir la calidad del efluente de un sistema de tratamiento, pero utilizan estrictamente variables numÃ©ricas;mientras que en el presente trabajo se utilizaron variables nominales, finalmente se discuten los resultados y seindican los procesos industriales que generan materia orgÃ¡nica y otros contaminantes. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-09-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/168 10.4114/intartif.vol21iss62pp13-24 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 13-24 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 13-24 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 13-24 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/168/64 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/169 2023-02-14T17:31:08Z intartif:Article driver

Fuzzy Neural Networks based on Fuzzy Logic Neurons Regularized by Resampling Techniques and Regularization Theory for Regression Problems Campos Souza, Paulo Vitor de Junio Guimaraes, Augusto Souza Araújo, Vanessa Silva Rezende, Thiago Silva Araújo, Vinicius Jonathan Bootstrap lasso Extreme Learning Machines Regression Problems Fuzzy Neural Network Fuzzy Logic Neurons This paper presents a novel learning algorithm for fuzzy logic neuron based on neural networks and fuzzy systems able to generate accurate and transparent models. The learning algorithm is based on ideas from Extreme Learning Machine [36], to achieve a low time complexity, and regularization theory, resulting in sparse and accurate models. A compact set of incomplete fuzzy rules can be extracted from the resulting network topology. Experiments considering regression problems are detailed. Results suggest the proposed approach as a promising alternative for pattern recognition with a good accuracy and some level of interpretability. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-11-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/169 10.4114/intartif.vol21iss62pp114-133 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 114-133 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 114-133 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 114-133 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/169/77 Copyright (c) 2018 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/184 2020-04-09T03:00:07Z intartif:Article driver

Deep Learning Applied on Refined Opinion Review Datasets Jost, Ingo Valiati, Joao Francisco Deep Learning; Opinion Mining; Feature Selection; Deep Belief Networks Deep Learning has been successfully applied in hard to solve areas, such as image recognition and audioclassification. However, Deep Learning has not yet reached the same performance when employed in textual data,including Opinion Mining. In models that implement a deep architecture, Deep Learning is characterized by theautomatic feature selection step. The impact of previous data refinement in the pre-processing step before theapplication of Deep Learning is investigated to identify opinion polarity. This refinement includes the use of aclassical procedure of textual content and a popular feature selection technique. The results of the experimentsovercome the results of the current literature with the Deep Belief Network application in opinion classification.In addition to overcoming the results, their presentation is broader than the related works, considering the changeof parameter variables. We prove that combining feature selection with a basic preprocessing step, aiming toincrease data quality, might achieve promising results with Deep Belief Network implementation. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-09-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/184 10.4114/intartif.vol21iss62pp91-102 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 91-102 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 91-102 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 91-102 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/184/72 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/198 2020-04-09T03:00:05Z intartif:Article driver

Artificial Neural Network (ANN) in a Small Dataset to determine Neutrality in the Pronunciation of English as a Foreign Language in Filipino Call Center Agents: Neutrality Classification of Filipino Call Center Agent's Pronunciation Baquirin, Rey Benjamin M. Fernandez, Proceso L. Artificial Intelligence Machine Learning Speech Processing Neural Networks Classification MFCC Artificial Neural Networks (ANNs) have continued to be efficient models in solving classification problems. In this paper, we explore the use of an A NN with a small dataset to accurately classify whet her Filipino call center agentsâ€™ pronunciations are neutral or not based on their employerâ€™s standards. Isolated utterances of the ten most commonly used words in the call center were recorded from eleven agents creating a dataset of 110 utterances. Two learning specialists were consulted to establish ground truths and Cohenâ€™s Kappa was computed as 0.82, validating the reliability of the dataset. The first thirteen Mel-Frequency Cepstral Coefficients (MFCCs) were then extracted from each word and an ANN was trained with Ten-fold Stratified Cross Validation. Experimental results on the model recorded a classification accuracy of 89.60% supported by an overall F-Score of 0.92. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-11-12 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/198 10.4114/intartif.vol21iss62pp134-144 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 134-144 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 134-144 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 134-144 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/198/78 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/214 2019-12-02T12:06:23Z intartif:Article driver

Compact Tree Encodings for Planning as QBF Gasquet, Olivier Longin, Dominique Maris, FrÂ´edÂ´eric RÂ´egnier, Pierre Valais, MaÂ¨el Planning, Quantified Boolean Formula, Encodings Considerable improvements in the technology and performance of SAT solvers has made their use possible for the resolution of various problems in artificial intelligence, and among them that of generating plans. Recently, promising Quantified Boolean Formula (QBF) solvers have been developed and we may expect that in a near future they become as efficient as SAT solvers. So, it is interesting to use QBF language that allows us to produce more compact encodings. We present in this article a translation from STRIPS planning problems into quantified propositional formulas. We introduce two new Compact Tree Encodings: CTE-EFA based on Explanatory frame axioms, and CTE-OPEN based on causal links. Then we compare both of them to CTE-NOOP based on No-op Actions proposed in [Cashmore et al. 2012]. In terms of execution time over benchmark problems, CTE-EFA and CTE-OPEN always performed better than CTE-NOOP. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-10-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/214 10.4114/intartif.vol21iss62pp103-113 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 103-113 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 103-113 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 103-113 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/214/76 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/216 2020-04-09T03:00:09Z intartif:Article driver

A Constraint-based Mission Planning Approach for Reconfigurable Multi-Robot Systems Roehr, Thomas M The application of reconfigurable multi-robot systems introduces additional degrees of freedom to design robotic missions compared to classical multi-robot systems. To allow for autonomous operation of such systems, planning approaches have to be investigated that cannot only cope with the combinatorial challenge arising from the increased flexibility of modular systems, but also exploit this flexibility to improve for example the safety of operation. While the problem originates from the domain of robotics it is of general nature and significantly intersects with operations research. This paper suggests a constraint-based mission planning approach, and presents a set of revised definitions for reconfigurable multi-robot systems including the representation of the planning problem using spatially and temporally qualified resource constraints. Planning is performed using a multi-stage approach and a combined use of knowledge-based reasoning, constraint-based programming and integer linear programming. The paper concludes with the illustration of the solution of a planned example mission. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-09-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/216 10.4114/intartif.vol21iss62pp25-39 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 25-39 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 25-39 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 25-39 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/216/65 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/218 2023-02-12T23:46:44Z intartif:Article driver

Planning and Scheduling in Additive Manufacturing Dvorak, Filip Micali, Maxwell Mathieug, Mathias Recent advances in additive manufacturing (AM) and 3D printing technologies have led to significant growth in the use of additive manufacturing in industry, which allows for the physical realization of previously difficult to manufacture designs. However, in certain cases AM can also involve higher production costs and unique in-process physical complications, motivating the need to solve new optimization challenges. Optimization for additive manufacturing is relevant for and involves multiple fields including mechanical engineering, materials science, operations research, and production engineering, and interdisciplinary interactions must be accounted for in the optimization framework. In this paper we investigate a problem in which a set of parts with unique configurations and deadlines must be printed by a set of machines while minimizing time and satisfying deadlines, bringing together bin packing, nesting (two-dimensional bin packing), job shop scheduling, and constraints satisfaction. We first describe the real-world industrial motivation for solving the problem. Subsequently, we encapsulate the problem within constraints and graph theory, create a formal model of the problem, discuss nesting as a subproblem, and describe the search algorithm. Finally, we present the datasets, the experimental approach, and the preliminary results. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-09-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/218 10.4114/intartif.vol21iss62pp40-52 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 40-52 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 40-52 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 40-52 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/218/68 Copyright (c) 2018 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/219 2020-04-09T03:00:08Z intartif:Article driver

Integrating Meeting and Individual Events Scheduling Alexiadis, Anastasios Refanidis, Ioannis Sakellariou, Ilias Scheduling, Optimization, constraint satisfaction, Meeting scheduling, Multi-Agents. Automated meeting scheduling is the task of reaching an agreement on a time slot to schedule a new meeting, taking into account the participantsâ€™ preferences over various aspects of the problem. Such a negotiation is commonly performed in a non-automated manner, that is, the users decide whether they can reschedule existing individual activities and, in some cases, already scheduled meetings in order to accommodate the new meeting request in a particular time slot, by inspecting their schedules. In this work, we take advantage of SelfPlanner, an automated system that employs greedy stochastic optimization algorithms to schedule individual activities under a rich model of preferences and constraints, and we extend that work to accommodate meetings. For each new meeting request, participants decide whether they can accommodate the meeting in a particular time slot by employing SelfPlannerâ€™s underlying algorithms to automatically reschedule existing individual activities. Time slots are prioritized in terms of the number of users that need to reschedule existing activities. An agreement is reached as soon as all agents can schedule the meeting at a particular time slot, without anyone of them experiencing an overall utility loss, that is, taking into account also the utility gain from the meeting. This dynamic multi-agent meeting scheduling approach has been tested on a variety of test problems with very promising results. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-09-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/219 10.4114/intartif.vol21iss62pp53-66 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 53-66 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 53-66 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 53-66 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/219/69 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/225 2020-04-09T03:00:07Z intartif:Article driver

Characterizing and Computing All Delete-Relaxed Dead-ends Muise, Christian deadends dead-ends knowledge compilation d-DNNF BDD SDD Dead-end detection is a key challenge in automated planning, and it is rapidly growing in popularity. Effective dead-end detection techniques can have a large impact on the strength of a planner, and so the effective computation of dead-ends is central to many planning approaches. One of the better understood techniques for detecting dead-ends is to focus on the delete relaxation of a planning problem, where dead-end detection is a polynomial-time operation. In this work, we provide a logical characterization for not just a single dead-end, but for every delete-relaxed dead-end in a planning problem. With a logical representation in hand, one could compile the representation into a form amenable to effective reasoning. We lay the ground-work for this larger vision and provide a preliminary evaluation to this end Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-09-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/225 10.4114/intartif.vol21iss62pp67-74 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 67-74 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 67-74 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 67-74 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/225/71 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/226 2020-04-09T03:00:08Z intartif:Article driver

X and more Parallelism. Integrating LTL-Next into SAT-based Planning with Trajectory Constraints while Allowing for even more Parallelism: Integrating LTL-Next into SAT-based Planning with Trajectory Constraints while Allowing for even more Parallelism Behnke, Gregor Biundo, Susanne Temporally Extended Goals Planning as SAT Linear Temporal Logic Linear temporal logic (LTL) provides expressive means to specify temporally extended goals as well as preferences.Recent research has focussed on compilation techniques, i.e., methods to alter the domain ensuring that every solution adheres to the temporally extended goals.This requires either new actions or an construction that is exponential in the size of the formula.A translation into boolean satisfiability (SAT) on the other hand requires neither.So far only one such encoding exists, which is based on the parallel $\exists$-step encoding for classical planning.We show a connection between it and recently developed compilation techniques for LTL, which may be exploited in the future.The major drawback of the encoding is that it is limited to LTL without the X operator.We show how to integrate X and describe two new encodings, which allow for more parallelism than the original encoding.An empirical evaluation shows that the new encodings outperform the current state-of-the-art encoding. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2018-09-11 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/226 10.4114/intartif.vol21iss62pp75-90 Inteligencia Artificial; Vol. 21 No. 62 (2018): Inteligencia Artificial (December 2018); 75-90 Inteligencia Artificial; Vol. 21 Núm. 62 (2018): Inteligencia Artificial (December 2018); 75-90 Inteligencia Artificial; Vol. 21 N.º 62 (2018): Inteligencia Artificial (December 2018); 75-90 1988-3064 1137-3601 10.4114/intartif.vol21iss62 eng https://journal.iberamia.org/index.php/intartif/article/view/226/70 Copyright (c) 2018 Iberamia & The Authors

oai:journal.iberamia.org:article/237 2020-04-09T03:00:01Z intartif:Article driver

Hybrid Adaptive Computational Intelligence-based Multisensor Data Fusion applied to real-time UAV autonomous navigation Paulino, Ã‚ngelo de Carvalho Guimarães, Lamartine Nogueira Frutuoso Shiguemori, Elcio Hideiti Data Fusion Computational Intelligence Unmanned Aerial Vehicles Autonomous Navigation Nowadays, there is a remarkable world trend in employing UAVs and drones for diverse applications. The main reasons are that they may cost fractions of manned aircraft and avoid the exposure of human lives to risks. Nevertheless, they depend on positioning systems that may be vulnerable. Therefore, it is necessary to ensure that these systems are as accurate as possible, aiming to improve the navigation. In pursuit of this end, conventional Data Fusion techniques can be employed. However, its computational cost may be prohibitive due to the low payload of some UAVs. This paper proposes a Multisensor Data Fusion application based on Hybrid Adaptive Computational Intelligence - the cascaded use of Fuzzy C-Means Clustering (FCM) and Adaptive-Network-Based Fuzzy Inference System (ANFIS) algorithms - that have been shown able to improve the accuracy of current positioning estimation systems for real-time UAV autonomous navigation. In addition, the proposed methodology outperformed two other Computational Intelligence techniques. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-05-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/237 10.4114/intartif.vol22iss63pp162-195 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 162-195 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 162-195 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 162-195 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/237/88 Copyright (c) 2019 Iberamia & The Authors

oai:journal.iberamia.org:article/240 2020-04-09T03:00:03Z intartif:Article driver

Hand Vein Biometric Recognition Approaches Based on Wavelet, SVM, Articial Neural Network and Image Registration Brito, Daniel Ling, Lee Luan Hand vein biometric, Support Vector Machine, Articial Neural Network, Image Registration, Wavelet. This paper describes in detail different hand vein recognition methods based on Wavelet-SVM, Wavelet-ANN and Image Registration. A new image segmentation and processing algorithm is proposed to efficiently locate vein regions and suitable for feature extraction (wavelet coefficients and normalized vein imagens) and classification (SVM, ANN and Image Registration). For real time recognition and high recognition rate, we proposed an integrated system which combines three above mentioned classification methods. The simulation results reveal that the proposed integrated system achieves 1% false rejection rate (FRR) and 0.02% false acceptance rate. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-02-27 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/240 10.4114/intartif.vol22iss63pp101-120 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 101-120 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 101-120 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 101-120 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/240/85 Copyright (c) 2019 Iberamia & The Authors

oai:journal.iberamia.org:article/242 2020-04-09T03:00:04Z intartif:Article driver

Intelligent Classification of Supernovae Using Artificial Neural Networks Brito do Nascimento, Francisca Joamila Arantes Filho, Luis Ricardo Nogueira Frutuoso Guimarães, Lamartine Artificial Neural Networks Intelligent Classification Supernovae The classification of supernovae (explosions of certain stars) divides them into two main types, those of type I do not present Hydrogen in the spectrum while those of type II present. In addition to the division into these two types, there is still a subdivision that establishes types Ia, Ib and Ic. In practice, the classification of supernovae requires specialized knowledge of astronomers and data (light spectra) of good quality. Some automatic/intelligent classifiers have been developed and are reported in the literature, one of them is CIntIa, which uses 4 Artificial Neural Networks to classify supernovae types Ia, Ib, Ic and II. The objective of this work is to improve CIntIa, so that it has more diversity in its learning, proposing CIntIa 2.0. In this way, this work is a hierarchical learning structure that connects Artificial Neural Networks in an integrated system that allows a more secure and unambiguous classification. The computational improvement of this new version included the increased amount of data used at all stages of development of intelligent classifier and a new approach to filtering and processing of spectral data, ensuring better quality of information that are to be trained networks. The results achieved were good, especially in the classification of types Ia and II. A comparison with the works found in theliterature shows that CIntIa 2.0 is superior in quantity and diversity of data and achieves higher classification indices than the other classifiers. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-02-22 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/242 10.4114/intartif.vol22iss63pp39-60 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 39-60 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 39-60 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 39-60 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/242/82 Copyright (c) 2019 Iberamia & The Authors

oai:journal.iberamia.org:article/244 2021-03-18T10:54:26Z intartif:Article driver

Building Dynamic Lexicons for Sentiment Analysis Mechulam, Nicolás Salvia, Damián Rosá, Aiala Etcheverry, Mathias Lexicon Induction Sentiment Analysis Natural Language Processing Nowadays, many approaches for Sentiment Analysis (SA) rely on affective lexicons to identify emotions transmitted in opinions. However, most of these lexicons do not consider that a word can express different sentiments in different predication domains, introducing errors in the sentiment inference. Due to this problem, we present a model based on a context-graph which can be used for building domain specic sentiment lexicons(DL: Dynamic Lexicons) by propagating the valence of a few seed words. For different corpora, we compare the results of a simple rule-based sentiment classier using the corresponding DL, with the results obtained using a general affective lexicon. For most corpora containing specic domain opinions, the DL reaches better results than the general lexicon. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-05-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/244 10.4114/intartif.vol22iss64pp1-13 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 1-13 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 1-13 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 1-13 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/244/90 Copyright (c) 2019 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/247 2020-04-09T03:00:05Z intartif:Article driver

Effects of Dynamic Variable - Value Ordering Heuristics on the Search Space of Sudoku Modeled as a Constraint Satisfaction Problem Cox, James L. Lucci, Stephen Pay, Tayfun Constraint Satisfaction Problems Backtracking-Search Dynamic Variable Ordering Heuristics We carry out a detailed analysis of the effects of different dynamic variable and value ordering heuristics on the search space of Sudoku when the encoding method and the filtering algorithm are fixed. Our study starts by examining lexicographical variable and value ordering and evaluates different combinations of dynamic variable and value ordering heuristics. We eventually build up to a dynamic variable ordering heuristic that has two rounds of tie-breakers, where the second tie-breaker is a dynamic value ordering heuristic. We show that our method that uses this interlinked heuristic outperforms the previously studied ones with the same experimental setup. Overall, we conclude that constructing insightful dynamic variable ordering heuristics that also utilize a dynamic value ordering heuristic in their decision making process could drastically improve the search effort for some constraint satisfaction problems. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-01-10 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/247 10.4114/intartif.vol22iss63pp1-15 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 1-15 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 1-15 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 1-15 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/247/80 Copyright (c) 2019 Iberamia & The Authors

oai:journal.iberamia.org:article/252 2020-04-09T03:00:01Z intartif:Article driver

The importance of context-dependent learning in negotiation agents Kröhling, Dan Ezequiel Chiotti, Omar Martínez, Ernesto Agents Automated Negotiation Negotiation Intelligence Internet of Things Reinforcement Learning Automated negotiation between artificial agents is essential to deploy Cognitive Computing and Internet of Things. The behavior of a negotiation agent depends significantly on the influence of environmental conditions or contextual variables, since they affect not only a given agent preferences and strategies, but also those of other agents. Despite this, the existing literature on automated negotiation is scarce about how to properly account for the effect of context-relevant variables in learning and evolving strategies. In this paper, a novel context-driven representation for automated negotiation is introduced. Also, a simple negotiation agent that queries available information from its environment, internally models contextual variables, and learns how to take advantage of this knowledge by playing against himself using reinforcement learning is proposed. Through a set of episodes against other negotiation agents in the existing literature, it is shown using our context-aware agent that it makes no sense to negotiate without taking context-relevant variables into account. Our context-aware negotiation agent has been implemented in the GENIUS environment, and results obtained are significant and quite revealing. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-05-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/252 10.4114/intartif.vol22iss63pp135-149 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 135-149 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 135-149 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 135-149 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/252/87 Copyright (c) 2019 Iberamia & The Authors

oai:journal.iberamia.org:article/254 2020-04-09T03:00:04Z intartif:Article driver

Stereo Matching through Squeeze Deep Neural Networks Caffaratti, Gabriel Dario Marchetta, Martín Gonzalo Forradellas, Raymundo Quilez Stereo Matching Deep Learning Squeeze Nets Artificial Intelligence Artificial Vision Disparity Maps Visual depth recognition through Stereo Matching is an active field of research due to the numerous applications in robotics, autonomous driving, user interfaces, etc. Multiple techniques have been developed in the last two decades to achieve accurate disparity maps in short time. With the arrival of Deep Leaning architectures, different fields of Artificial Vision, but mainly on image recognition, have achieved a great progress due to their easier training capabilities and reduction of parameters. This type of networks brought the attention of the Stereo Matching researchers who successfully applied the same concept to generate disparity maps. Even though multiple approaches have been taken towards the minimization of the execution time and errors in the results, most of the time the number of parameters of the networks is neither taken into consideration nor optimized. Inspired on the Squeeze-Nets developed for image recognition, we developed a Stereo Matching Squeeze neural network architecture capable of providing disparity maps with a highly reduced network size without a significant impact on quality and execution time compared with state of the art architectures. In addition, with the purpose of improving the quality of the solution and get solutions closer to real time, an extra refinement module is proposed and several tests are performed using different input size reductions. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-02-11 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/254 10.4114/intartif.vol22iss63pp16-38 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 16-38 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 16-38 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 16-38 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/254/81

oai:journal.iberamia.org:article/255 2020-04-09T03:00:02Z intartif:Article driver

A Flexible Supervised Term-Weighting Technique and its Application to Variable Extraction and Information Retrieval Maisonnave, Mariano Delbianco, Fernando Tohmé, Fernando Abel Maguitman, Ana Gabriela Term Weighting Variable Extraction Information Retrieval Query-Term Selection Successful modeling and prediction depend on effective methods for the extraction of domain-relevant variables.  This paper proposes a methodology for identifying domain-specific terms. The proposed methodology relies on a collection of documents labeled as relevant or irrelevant to the domain under analysis. Based on the labeled document collection, we propose a supervised technique that weights terms based on their descriptive and discriminating power. Finally, the descriptive and discriminating values are combined into a general measure that, through the use of an adjustable parameter, allows to independently favor different aspects of  retrieval such as maximizing precision or recall, or achieving a balance between both of them. The proposed technique is applied to the economic domain and is empirically evaluated through a human-subject experiment involving experts and non-experts in Economy. It is also evaluated as a term-weighting technique for query-term selection showing promising results. We finally illustrate the applicability of the proposed technique to address diverse problems such as building prediction models, supporting knowledge modeling, and achieving total recall. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-02-27 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/255 10.4114/intartif.vol22iss63pp61-80 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 61-80 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 61-80 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 61-80 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/255/84 Copyright (c) 2019 Iberamia & The Authors

oai:journal.iberamia.org:article/262 2023-02-14T17:54:48Z intartif:Article driver

Article Users Activity Gesture Recognition on Kinect Sensor Using Convolutional Neural Networks and FastDTW for Controlling Movements of a Mobile Robot Pfitscher, Miguel Welfer, Daniel do Nascimento, Evaristo José Cuadros, Marco Antonio de Souza Leite Gamarra, Daniel Fernando Tello Human gestures recognition, convolutional neural networks, Microsoft Kinect, MSRC-12 dataset, Mobile robot. In this paper, we use data from the Microsoft Kinect sensor that processes the captured imageof a person using and extracting the joints information on every frame. Then, we propose the creation ofan image derived from all the sequential frames of a gesture the movement, which facilitates training in aconvolutional neural network. We trained a CNN using two strategies: combined training and individualtraining. The strategies were experimented in the convolutional neural network (CNN) using theMSRC-12 dataset, obtaining an accuracy rate of 86.67% in combined training and 90.78% of accuracyrate in the individual training.. Then, the trained neural network was used to classify data obtained fromKinect with a person, obtaining an accuracy rate of 72.08% in combined training and 81.25% inindividualized training. Finally, we use the system to send commands to a mobile robot in order to controlit. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-04-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/262 10.4114/intartif.vol22iss63pp121-134 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 121-134 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 121-134 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 121-134 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/262/86 Copyright (c) 2019 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/264 2020-04-09T03:00:03Z intartif:Article driver

An experimental study on feature engineering and learning approaches for aggression detection in social media Tommasel, Antonela Rodriguez, Juan Manuel Godoy, Daniela Cyberaggression Social Media Aggression detection Feature Engineering Machine Learning Deep Learning With the widespread of modern technologies and social media networks, a new form of bullying occurring anytime and anywhere has emerged. This new phenomenon, known as cyberaggression or cyberbullying, refers to aggressive and intentional acts aiming at repeatedly causing harm to other person involving rude, insulting, offensive, teasing or demoralising comments through online social media. As these aggressions represent a threatening experience to Internet users, especially kids and teens who are still shaping their identities, social relations and well-being, it is crucial to understand how cyberbullying occurs to prevent it from escalating. Considering the massive information on the Web, the developing of intelligent techniques for automatically detecting harmful content is gaining importance, allowing the monitoring of large-scale social media and the early detection of unwanted and aggressive situations. Even though several approaches have been developed over the last few years based both on traditional and deep learning techniques, several concerns arise over the duplication of research and the difficulty of comparing results. Moreover, there is no agreement regarding neither which type of technique is better suited for the task, nor the type of features in which learning should be based. The goal of this work is to shed some light on the effects of learning paradigms and feature engineering approaches for detecting aggressions in social media texts. In this context, this work provides an evaluation of diverse traditional and deep learning techniques based on diverse sets of features, across multiple social media sites.  Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-02-27 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/264 10.4114/intartif.vol22iss63pp81-100 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 81-100 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 81-100 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 81-100 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/264/83 Copyright (c) 2019 Iberamia & The Authors

oai:journal.iberamia.org:article/267 2020-04-09T03:00:00Z intartif:Article driver

Genetic Algorithms for Satellite Launcher Attitude Controller Design Silva, Paulo Renato Silva Abreu, Ivanildo Almeida Forte, Paulo Costa do Amaral, Henrique Mariano For proper attitude control of space-crafts conventional optimal Linear Quadratic (LQ) controllers are designed via trial-and-error selection of the weighting matrices. This time consuming method is inefficient and usually results in a high order complex controller. Therefore, this work proposes a genetic algorithm (GA) for the search problem of the attitude controller gains of a satellite launcher. The GA's fitness function considers some control features as eigenstructure, control goals and constraints. According to simulation results, the search problem of controller parameters with evolutionary algorithms was faster than usual approaches and the designed controller reached all the specifications with satisfactory time responses. These results could improve engineering tasks by speeding up the design process and reducing costs. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-05-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/267 10.4114/intartif.vol22iss63pp150-161 Inteligencia Artificial; Vol. 22 No. 63 (2019): Inteligencia Artificial (June 2019); 150-161 Inteligencia Artificial; Vol. 22 Núm. 63 (2019): Inteligencia Artificial (June 2019); 150-161 Inteligencia Artificial; Vol. 22 N.º 63 (2019): Inteligencia Artificial (June 2019); 150-161 1988-3064 1137-3601 10.4114/intartif.vol22iss63 eng https://journal.iberamia.org/index.php/intartif/article/view/267/89 Copyright (c) 2019 Iberamia & The Authors

oai:journal.iberamia.org:article/276 2021-03-18T10:57:39Z intartif:Article driver

Feature Learning with Multi-objective Evolutionary Computation in the generation of Acoustic Features Menezes, José Antonio Alves Cabral, Giordano Gomes, Bruno Pereira, Paulo Automatic audio classification feature learning analytical space evolutionary algorithms multi-objective optimization To choice audio features has been a very interesting theme for audio classification experts. They have seen that this process is probably the most important effort to solve the classification problem. In this sense, there are techniques of Feature Learning for generate new features more suitable for classification model than conventional features. However, these techniques generally do not depend on knowledge domain and they can apply in various types of raw data. However, less agnostic approaches learn a type of knowledge restricted to the area studded. The audio data requires a specific knowledge type. There are many techniques that seek to improve the performance of the new generation of acoustic features, among which stands the technique that use evolutionary algorithms to explore analytical space of function. However, the efforts made leave opportunities for improvement. The purpose of this work is to propose and evaluate a multi-objective alternative to the exploitation of analytical audio features. In addition, experiments were arranged to be validated the method, with the help a computational prototype that implemented the proposed solution. After it was found the effectiveness of the model and ensuring that there is still opportunity for improvement in the chosen segment. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/276 10.4114/intartif.vol22iss64pp14-35 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 14-35 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 14-35 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 14-35 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/276/91 Copyright (c) 2019 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/314 2021-04-05T10:08:52Z intartif:Article driver

An Efficient Probability Estimation Decision Tree Postprocessing Method for Mining Optimal Profitable Knowledge for Enterprises with Multi-Class Customers Naga Muneiah, Janapati SubbaRao, Ch D V Data mining Knowledge Engineering and Applications Machine Learning: Methods and Applications, actionable knowledge discovery, profit maximization Enterprises often classify their customers based on the degree of profitability in decreasing order like C1, C2, ..., Cn. Generally, customers representing class Cn are zero profitable since they migrate to the competitor. They are called as attritors (or churners) and are the prime reason for the huge losses of the enterprises. Nevertheless, customers of other intermediary classes are reluctant and offer an insignificant amount of profits in different degrees and lead to uncertainty. Various data mining models like decision trees, etc., which are built using the customersâ€™ profiles, are limited to classifying the customers as attritors or non-attritors only and not providing profitable actionable knowledge. In this paper, we present an efficient algorithm for the automatic extraction of profit-maximizing knowledge for business applications with multi-class customers by postprocessing the probability estimation decision tree (PET). When the PET predicts a customer as belonging  to any of the lesser profitable classes, then, our algorithm suggests the cost-sensitive actions to change her/him to a maximum possible higher profitable status. In the proposed novel approach, the PET is represented in the compressed form as a Bit patterns matrix and the postprocessing task is performed on the bit patterns by applying the bitwise AND operations. The computational performance of the proposed method is strong due to the employment of effective data structures. Substantial experiments conducted on UCI datasets, real Mobile phone service data and other benchmark datasets demonstrate that the proposed method remarkably outperforms the state-of-the-art methods. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-11-14 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/314 10.4114/intartif.vol22iss64pp63-84 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 63-84 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 63-84 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 63-84 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/314/94 Copyright (c) 2019 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/316 2021-03-18T10:59:01Z intartif:Article driver

On the Enhancement of Classification Algorithms Using Biased Samples Al-mamory, Safaa O. Classification, LOF, Decision Boundary, Biased Sampling, rare class Classification algorithms' performance could be enhanced by selecting many representative points to be included in the training sample. In this paper, a new border and rare biased sampling (BRBS) scheme is proposed by assigning each point in the dataset an importance factor. The importance factor of border points and rare points (i.e. points belong to rare classes) is higher than other points. Then the points are selected to be in the training sample depending on these factors. Including these points in the training sample enhances classifiers experience. The results of experiments on 10 UCI machine learning repository datasets prove that the BRBS algorithm outperforms many sampling algorithms and enhanced the performance of several classification algorithms by about 8%. BRBS is proposed to be easy to configure, covering all points space, and generate a unique samples every time it is executed. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-10-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/316 10.4114/intartif.vol22iss64pp36-46 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 36-46 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 36-46 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 36-46 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/316/92 Copyright (c) 2019 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/336 2021-03-18T11:15:32Z intartif:Article driver

A robust multi-agent Negotiation for advanced Image Segmentation: Design and Implementation Allioui, Hanane Sadgal, Mohamed El Fazziki, Aziz Image segmentation, Region merging, Multi-Agent System, Game Theory, Coalition, Negotiation It is generally accepted that segmentation is a critical problem that influences subsequent tasks during image processing. Often, the proposed approaches provide effectiveness for a limited type of images with a significant lack of a global solution. The difficulty of segmentation lies in the complexity of providing a global solution with acceptable accuracy within a reasonable time. To overcome this problem, some solutions combined several methods. This paper presents a method for segmenting 2D/3D images by merging regions and solving problems encountered during the process using a multi-agent system (MAS). We are using the strengths of MAS by opting for a compromise that satisfies segmentation by agentsâ€™ acts. Regions with high similarity are merged immediately, while the others with low similarity are ignored. The remaining ones, with ambiguous similarity, are solved in a coalition by negotiation. In our system, the agents make decisions according to the utility functions adopting the Pareto optimal in Game theory. Unlike hierarchical merging methods, MAS performs a hypothetical merger planning then negotiates the agreements' subsets to merge all regions at once. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-12-12 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/336 10.4114/intartif.vol22iss64pp102-122 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 102-122 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 102-122 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 102-122 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/336/96 Copyright (c) 2019 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/338 2021-03-18T11:20:40Z intartif:Article driver

Gray-level Co-Occurrence Matrix application to Images Processing of crushed Olives fruits. Márquez, Antonio Jiménez Beltrán Maza, Gabriel Matriz de Co-ocurrencias; Imagen; Masa aceituna This paper shows the results obtained from images processing digitized, taken with a 'smartphone', of 56 samples of crushed olives, using the methodology of the gray-level co-occurrence matrix (GLCM). The values â€‹â€‹of the appropriate direction (Î¸) and distance (D) that two pixel with gray tone are neighbourhood, are defined to extract the information of the parameters: Contrast, Correlation, Energy and Homogeneity. The values â€‹â€‹of these parameters are correlated with several characteristic components of the olives mass: oil content (RGH) and water content (HUM), whose values â€‹â€‹are in the usual ranges during their processing to obtain virgin olive oil in mills and they contribute to generate different mechanical textures in the mass according to their relationship HUM / RGH. The results indicate the existence of significant correlations of the parameters Contrast, Energy and Homogeneity with the RGH and the HUM, which have allowed to obtain, by means of a multiple linear regression (MLR), mathematical equations that allow to predict both components with a high degree of correlation coefficient, r = 0.861 and r = 0.872 for RGH and HUM respectively. These results suggest the feasibility of textural analysis using GLCM to extract features of interest from digital images of the olives mass, quickly and non-destructively, as an aid in the decision making to optimize the production process of virgin olive oil. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-01-27 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/338 10.4114/intartif.vol22iss64pp135-142 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 135-142 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 135-142 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 135-142 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/338/98 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/339 2021-02-20T19:59:56Z intartif:Article driver

Development of an Artificial Intelligence System (AI) Based on Patterns Recognition for the Analysis of Vehicular Routes Röpke, Leonardo Luís Binelo, Manuel Osório Artificial intelligence Artificial neural networks K-means Pattern Recognition Routes This work presents the study and development of an Artificial Intelligence system, with focus on K-means algorithms and Artificial Neural Networks, to assist fleet managers in the identification of routes and route deviations. The developed tool has the objective of modernizing the process of identification of routes and deviations of routes. The results show that the Artificial Neural Networks obtained a 100% accuracy rate in the identification of routes, and in the identification of route deviations the RNAs were able to identify 61% of the routes presented. Therefore, RNAs are an excellent technique to be applied to the identification of routes and deviations of routes. The K-means algorithm presented good results when applied in the discovery of similar routes, thus becoming an important tool applied to the work of monitoring vehicles routes. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-06-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/339 10.4114/intartif.vol23iss65pp67-85 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 67-85 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 67-85 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 67-85 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/339/108 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/345 2021-02-20T19:28:32Z intartif:Article driver

Cost-effective Indoor Localization for Autonomous Robots using Kinect and WiFi Sensors Alves, Raul Cesar Silva de Morais, Josué Yamanaka, Keiji Indoor localization has been considered to be the most fundamental problem when it comes to providing a robot with autonomous capabilities. Although many algorithms and sensors have been proposed, none have proven to work perfectly under all situations. Also, in order to improve the localization quality, some approaches use expensive devices either mounted on the robots or attached to the environment that don't naturally belong to human environments. This paper presents a novel approach that combines the benefits of two localization techniques, WiFi and Kinect, into a single algorithm using low-cost sensors. It uses separate Particle Filters (PFs). The WiFi PF gives the global location of the robot using signals of Access Point devices from different parts of the environment while it bounds particles of the Kinect PF, which determines the robot's pose locally. Our algorithm also tackles the Initialization/Kidnapped Robot Problem by detecting divergence on WiFi signals, which starts a localization recovering process. Furthermore, new methods for WiFi mapping and localization are introduced. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-05-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/345 10.4114/intartif.vol23iss65pp33-55 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 33-55 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 33-55 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 33-55 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/345/104 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/358 2021-03-18T11:17:32Z intartif:Article driver

An Enhanced Discrete Bees Algorithm for Resource Constrained Optimization Problems Nemmich, Mohamed Amine Debbat, Fatima Slimane, Mohamed Optimization Project scheduling Resource-constraints Bees Algorithm Serial Schedule Generation Scheme Activity list representation In this paper, we propose a novel efï¬cient model based on Bees Algorithm (BA) for the Resource-Constrained Project Scheduling Problem (RCPSP). The studied RCPSP is a NP-hard combinatorial optimization problem which involves resource, precedence, and temporal constraints. It has been applied to many applications. The main objective is to minimize the expected makespan of the project. The proposed model, named Enhanced Discrete Bees Algorithm (EDBA), iteratively solves the RCPSP by utilizing intelligent foraging behaviors of honey bees. The potential solution is represented by the multidimensional bee, where the activity list representation (AL) is considered. This projection involves using the Serial Schedule Generation Scheme (SSGS) as decoding procedure to construct the active schedules. In addition, the conventional local search of the basic BA is replaced by a neighboring technique, based on the swap operator, which takes into account the specificity of the solution space of project scheduling problems and reduces the number of parameters to be tuned. The proposed EDBA is tested on well-known benchmark problem instance sets from Project Scheduling Problem Library (PSPLIB) and compared with other approaches from the literature. The promising computational results reveal the effectiveness of the proposed approach for solving the RCPSP problems of various scales. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-12-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/358 10.4114/intartif.vol22iss64pp123-134 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 123-134 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 123-134 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 123-134 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/358/97 Copyright (c) 2019 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/360 2021-03-18T21:46:24Z intartif:Article driver

Uma Nova Meta-heurÃstica Adaptativa Baseada em Vetor de AvaliaÃ§Ãµes para OtimizaÃ§Ã£o de PortfÃ³lios de Investimentos Corrêa Costa, Leticia de Fátima Carmona Cortes, Omar Andres Augusto Costa, Joñao Pedro Meta-Heuristicas Multiobjetivo ABC PSO DE Otimização de Portfólios This article describes a new adaptive metaheuristic based on a vector evaluated approach for solving multiobjective problems. We called our proposed algorithm Vector Evaluated Meta-Heuristic. Its main idea is to evolve two populations independently, exchanging information between them, i.e., the first population evolves according to the best individual of the second population and vice-versa. The choice of which algorithm will be executed on each generation is carried out stochastically among three evolutionary algorithms well known in the literature: PSO, DE, ABC. In order to evaluate the results, we used an established metric in multiobjective evolutionary algorithms called hypervolume. Tests have shown that the adaptive metaheuristic reaches the best hyper-volumes in three of ZDT benchmarks functions and, also, in two portfolios of a real-world problem called portfolio investment optimization. The results show that our algorithm improved the Pareto curve when compared to the hypervolumes of each heuristic separately. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-12-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/360 10.4114/intartif.vol22iss64pp85-101 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 85-101 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 85-101 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 85-101 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/360/95 Copyright (c) 2019 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/363 2021-03-18T11:01:37Z intartif:Article driver

Dealing with Incompatibilities among Procedural Goals under Uncertainty Morveli Espinoza, Mariela Nieves, Juan Carlos Possebom, Ayslan Tacla, Cesar Augusto Argumentation, Goals selection, Uncertainty, Arguments strength, goals conflicts By considering rational agents, we focus on the problem of selecting goals out of a set of incompatible ones. We consider three forms of incompatibility introduced by Castelfranchi and Paglieri, namely the terminal, the instrumental (or based on resources), and the superfluity. We represent the agent's plans by means of structured arguments whose premises are pervaded with uncertainty. We measure the strength of these arguments in order to determine the set of compatible goals. We propose two novel ways for calculating the strength of these arguments, depending on the kind of incompatibility thatexists between them. The first one is the logical strength value, it is denoted by a three-dimensional vector, which is calculated from a probabilistic interval associated with each argument. The vector represents the precision of the interval, the location of it, and the combination of precision and location. This type of representation and treatment of the strength of a structured argument has not been defined before by the state of the art. The second way for calculating the strength of the argument is based on the cost of the plans (regarding the necessary resources) and the preference of the goals associated with the plans. Considering our novel approach for measuring the strength of structured arguments, we propose a semantics for the selection of plans and goals that is based on Dung's abstract argumentation theory. Finally, we make a theoretical evaluation of our proposal. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2019-11-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/363 10.4114/intartif.vol22iss64pp47-62 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 47-62 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 47-62 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 47-62 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/363/93 Copyright (c) 2019 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/381 2021-02-20T19:30:10Z intartif:Article driver

Airport resource allocation using machine learning techniques Mamdouh, Maged Ezzat, Mostafa Hefny, Hesham A. The airport ground handling has a global trend to meet the Service Level Agreement (SLA) requirementsthat represents resource allocation with more restrictions according to flights. That can be achieved by predictingfuture resources demands. this research presents a comparison between the most used machine learning techniquesimplemented in many different fields for demand prediction and resource allocation. The prediction model nomi-nated and used in this research is the Support Vector Machine (SVM) to predict the required resources for eachflight, despite the restrictions imposed by airlines when contracting their services in the Service Level Agreement.The approach has been trained and tested using real data from Cairo International Airport. the proposed (SVM)technique implemented and explained with a varying accuracy of resource allocation prediction, showing thateven for variations accuracy in resource prediction in different scenarios; the Support Vector Machine techniquecan produce a good performance as resource allocation in the airport. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-05-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/381 10.4114/intartif.vol23iss65pp19-32 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 19-32 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 19-32 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 19-32 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/381/103 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/393 2021-02-20T20:02:06Z intartif:Article driver

Classification of Breast Cancer from Digital Mammography Using Deep Learning López-Cabrera, José Daniel López Rodríguez, Luis Alberto Pérez-Díaz, Marlén Deep Learning Image Processing Breast Cancer Breast cancer is the most frequent in females. Mammography has proven to be the most effective method for the early detection of this type of cancer. Mammographic images are sometimes difficult to understand, due to the nature of the anomalies, the low contrast image and the composition of the mammary tissues, as well as various technological factors such as spatial resolution of the image or noise. Computer-aided diagnostic systems have been developed to increase the accuracy of mammographic examinations and be used by physicians as a second opinion in obtaining the final diagnosis, and thus reduce human errors. Convolutional neural networks are a current trend in computer vision tasks, due to the great performance they have achieved. The present investigation was based on this type of networks to classify into three classes, normal, benign and malignant tumour. Due to the fact that the miniMIAS database used has a low number of images, the transfer learning technique was applied to the Inception v3 pre-trained network. Two convolutional neural network architectures were implemented, obtaining in the architecture with three classes, 86.05% accuracy. On the other hand, in the architecture with two neural networks in series, an accuracy of 88.2% was reached. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-05-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/393 10.4114/intartif.vol23iss65pp56-66 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 56-66 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 56-66 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 56-66 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/393/106 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/403 2021-02-20T19:34:25Z intartif:Article driver

Completeness by Modal Deï¬nitions. Application to the Epistemic Logic With Hypotheses Uridia, Levan Walther, Dirk Knowledge representation and reasosning epistemic logic Kripke Completeness Topological Semantics We investigate the variant of epistemic logic S5 for reasoning about knowledge under hypotheses. The logic is equipped with a modal operator of necessity that can be parameterized with a hypothesis representing background assumptions. The modal operator can be described as relative necessity and the resulting logic turns out to be a variant of Chellasâ€™ Conditional Logic. We present an axiomatization of the logic and its extension with the common knowledge operator and distributed knowledge operator. We show that the logics are decidable, complete w.r.t. Kripke as well as topological structures. The topological completeness results are obtained by utilizing the Alexandroï¬€ connection between preorders and Alexandroï¬€ spaces. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-04-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/403 10.4114/intartif.vol23iss65pp1-18 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 1-18 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 1-18 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 1-18 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/403/102 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/404 2021-03-18T11:23:35Z intartif:Article driver

Computational Model for Organizational Learning in Research And Development Centers (R&D) Suárez-Barón, Marco Javier López, José Fdo. Montenegro Marin, Carlos Enrique Gaona-García, Paulo Alonso Montenegro-Marin, Franklin Guillermo Computational Architecture, Strategic Knowledge Management, Social Networks. This work explains for a computational model design focused organizational learning in R&D centers. We explained the first stage of this architecture that enables extracting, retrieval and integrating of lessons learned in the areas of innovation and technological development that have been registered by R&D researchers and personnel in social networks corporative focused to research. In addition, this article provides details about the design and construction of organizational memory as a computational learning mechanism within an organization. The end result of the process is discusses the management of the extraction and retrieval of information as a technological knowledge management mechanism with the goal of consolidating the Organizational Memory. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-02-12 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/404 10.4114/intartif.vol22iss64pp143-151 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 143-151 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 143-151 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 143-151 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/404/99 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/411 2021-03-18T11:24:43Z intartif:Article driver

Augmenting Scalable Communication-Based Role Allocation for a Three-Role Task Martins, Gustavo Urbano, Paulo role allocation, collective robotics, swarm, NEAT, fitness function, artificial evolution, evolutionary robotics In evolutionary robotics role allocation studies, it is common that the role assumed by each robot is strongly associated with specific local conditions, which may compromise scalability and robustness because of the dependency on those conditions. To increase scalability, communication has been proposed as a means for robots to exchange signals that represent roles. This idea was successfully applied to evolve communication-based role allocation for a two-role task. However, it was necessary to reward signal differentiation in the fitness function, which is a serious limitation as it does not generalize to tasks where the number of roles is unknown a priori. In this paper, we show that rewarding signal differentiation is not necessary to evolve communication-based role allocation strategies for the given task, and we improve reported scalability, while requiring less a priori knowledge. Our approach for the two-role task puts fewer constrains on the evolutionary process and enhances the potential of evolving communication-based role allocation for more complex tasks. Furthermore, we conduct experiments for a three-role task where we compare two different cognitive architectures and several fitness functions and we show how scalable controllers might be evolved. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-02-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/411 10.4114/intartif.vol22iss64pp152-165 Inteligencia Artificial; Vol. 22 No. 64 (2019): Inteligencia Artificial (December 2019); 152-165 Inteligencia Artificial; Vol. 22 Núm. 64 (2019): Inteligencia Artificial (December 2019); 152-165 Inteligencia Artificial; Vol. 22 N.º 64 (2019): Inteligencia Artificial (December 2019); 152-165 1988-3064 1137-3601 10.4114/intartif.vol22iss64 eng https://journal.iberamia.org/index.php/intartif/article/view/411/101 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/413 2021-02-20T19:58:00Z intartif:Article driver

Design an efficient disease monitoring system for paddy leaves based on big data mining K, Suresh S, Karthik M, Hanumanthappa Alpha-trimmed mean filter; Fuzzy C-Means (FCM) algorithm; Multi-Verse Optimization (MVO); Adaptive Neuro-Fuzzy Inference System (ANFIS) With the progressions in Information and Communication Technology (ICT), the innumerable electronic devices (like smart sensors) and several software applications can proffer notable contributions to the challenges that are existent in monitoring plants. In the prevailing work, the segmentation accuracy and classification accuracy of the Disease Monitoring System (DMS), is low. So, the system doesn't properly monitor the plant diseases. To overcome such drawbacks, this paper proposed an efficient monitoring system for paddy leaves based on big data mining. The proposed model comprises 5 phases: 1)Â Image acquisition, 2) segmentation, 3) Feature extraction, 4) Feature Selection along with 5) Classification Validation. Primarily, consider the paddy leaf image which is taken as of the dataset as the input. Then, execute image acquisition phase where 3 steps like, i) transmute RGB image to grey scale image, ii) Normalization for high intensity, and iii) preprocessing utilizing Alpha-trimmed mean filter (ATMF) through which the noises are eradicated and its nature is the hybrid of the mean as well as median filters, are performed. Next, segment the resulting image using Fuzzy C-Means (i.e. FCM) Clustering Algorithm. FCM segments the diseased portion in the paddy leaves. In the next phase, features are extorted, and then the resulted features are chosen by utilizing Multi-Verse Optimization (MVO) algorithm. After completing feature selection, the chosen features are classified utilizing ANFIS (Adaptive Neuro-Fuzzy Inference System). Experiential results contrasted with the former SVM classifier (Support Vector Machine) and the prevailing methods in respect of precision, recall, F-measure,sensitivity accuracy, and specificity. In accuracy level, the proposed one has 97.28% but the prevailing techniques only offer 91.2% for SVM classifier, 85.3% for KNN and 88.78% for ANN. Hence, this proposed DMS has more accurate detection and classification process than the other methods. The proposed DMS evinces better accuracy when contrasting with the prevailing methods. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-07-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/413 10.4114/intartif.vol23iss65pp86-99 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 86-99 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 86-99 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 86-99 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/413/113 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/448 2021-02-20T20:05:19Z intartif:Article driver

Ensemble Feature Selection for Breast Cancer Classification using Microarray Data Hengpraprohm, Supoj Jungjit, Suwimol Ensemble approach Feature selection Microarray data Genetic Algorithm For breast cancer data classification, we propose an ensemble filter feature selection approach named â€˜EnSNRâ€™. Entropy and SNR evaluation functions are used to find the features (genes) for the EnSNR subset. A Genetic Algorithm (GA) generates the classification â€˜modelâ€™. The efficiency of the â€˜modelâ€™ is validated using 10-Fold Cross-Validation re-sampling. The Microarray dataset used in our experiments contains 50,739 genes for each of 32 patients. When our proposed â€˜EnSNRâ€™ subset of features is used; as well as giving an enhanced degree of prediction accuracy and reducing the number of irrelevant features (genes), there is also a small saving of computer processing time. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-07-13 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/448 10.4114/intartif.vol23iss65pp100-114 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 100-114 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 100-114 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 100-114 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/448/110 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/454 2021-02-16T08:50:46Z intartif:Article driver

Recognition of Motion-blurred CCTs based on Deep and Transfer Learning Shi, Yun Zhu, Yanyan Chinese character coded target (CCT) deep learning image recognition motion blur transfer learning Considering the need for a large number of samples and the long training time, this paper uses deep and transfer learning to identify motion-blurred Chinese character coded targets (CCTs). Firstly, a set of CCTs are designed, and the motion blur image generation system is used to provide samples for the recognition network. Secondly, the OTSU algorithm, the expansion, and the Canny operator are performed on the real shot blurred image, where the target area is segmented by the minimum bounding box. Thirdly, the sample is selected from the sample set according to the 4:1 ratio as the training set and the test set. Under the Tensor Flow framework, the convolutional layer in the AlexNet model is fixed, and the fully-connected layer is trained for transfer learning. Finally, experiments on simulated and real-time motion-blurred images are carried out. The results show that network training and testing only take 30 minutes and two seconds, and the recognition accuracy reaches 98.6% and 93.58%, respectively. As a result, our method has higher recognition accuracy, does not require a large number of trained samples, takes less time, and can provide a certain reference for the recognition of motion-blurred CCTs. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-08-27 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/454 10.4114/intartif.vol23iss66pp1-8 Inteligencia Artificial; Vol. 23 No. 66 (2020): Inteligencia Artificial (December 2020); 1-8 Inteligencia Artificial; Vol. 23 Núm. 66 (2020): Inteligencia Artificial (December 2020); 1-8 Inteligencia Artificial; Vol. 23 N.º 66 (2020): Inteligencia Artificial (December 2020); 1-8 1988-3064 1137-3601 10.4114/intartif.vol23iss66 eng https://journal.iberamia.org/index.php/intartif/article/view/454/115 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/457 2021-02-20T20:06:31Z intartif:Article driver

Arabic dialect sentiment analysis with ZERO effort. \\ Case study: Algerian dialect Guellil, Imane Mendoza, Marcelo Azouaou, Faical Sentiment analysis Natural language processing Arabic and its dialects Transfert learning zero-effort for corpora construction This paper presents an analytic study showing that it is entirely possible to analyze the sentiment of an Arabic dialect without constructing any resources. The idea of this work is to use the resources dedicated to a given dialect \textit{X} for analyzing the sentiment of another dialect \textit{Y}. The unique condition is to have \textit{X} and \textit{Y} in the same category of dialects. We apply this idea on Algerian dialect, which is a Maghrebi Arabic dialect that suffers from limited available tools and other handling resources required for automatic sentiment analysis. To do this analysis, we rely on Maghrebi dialect resources and two manually annotated sentiment corpus for respectively Tunisian and Moroccan dialect. We also use a large corpus for Maghrebi dialect. We use a state-of-the-art system and propose a new deep learning architecture for automatically classify the sentiment of Arabic dialect (Algerian dialect). Experimental results show that F1-score is up to 83% and it is achieved by Multilayer Perceptron (MLP) with Tunisian corpus and with Long short-term memory (LSTM) with the combination of Tunisian and Moroccan. An improvement of 15% compared to its closest competitor was observed through this study. Ongoing work is aimed at manually constructing an annotated sentiment corpus for Algerian dialect and comparing the results Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-07-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/457 10.4114/intartif.vol23iss65pp124-135 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 124-135 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 124-135 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 124-135 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/457/111 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/460 2021-02-16T09:22:48Z intartif:Article driver

Study on Student-centered artificial intelligence online teaching + home learning model during the COVID-19 epidemic Li, Mingyong An, Ziye Ren, Miaomiao COVID-19 Network Broadcast Teaching Home Study With the rapid development of Internet technology, traditional online learning can no longer meet the adaptive learning needs of students, and smart education concepts, such as mushrooms, use data generated by traditional platforms to use machine learning and depth. Artificial intelligence technology with learning as a means has gradually become a new research hotspot through re-analysis technology. How to further use these big data resources for adaptive learning and push to improve the quality of student training has become an important issue in the current research field. For the protection of students' learning during the COVID-19 epidemic prevention and control, national universities, primary schools and secondary schools solved the problem of â€œClasses Suspended but Learning Continueâ€ through online teaching. Students learn online at home and the family plays a vital role as a special classroom. Based on the analysis of the factors affecting home study, this article compares the live broadcast platforms and constructs a student-centered network broadcast + home learning model under the epidemic situation. After the implementation effect investigation, the evaluation effect is good. It is hoped that this model can provide a reference for teachers and students in the new situation and solve some problems currently facing online teaching at home. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-10-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/460 10.4114/intartif.vol23iss66pp51-65 Inteligencia Artificial; Vol. 23 No. 66 (2020): Inteligencia Artificial (December 2020); 51-65 Inteligencia Artificial; Vol. 23 Núm. 66 (2020): Inteligencia Artificial (December 2020); 51-65 Inteligencia Artificial; Vol. 23 N.º 66 (2020): Inteligencia Artificial (December 2020); 51-65 1988-3064 1137-3601 10.4114/intartif.vol23iss66 eng https://journal.iberamia.org/index.php/intartif/article/view/460/125 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/469 2021-02-20T19:48:46Z intartif:Article driver

Research on High Precision Positioning of Beidou / Inertial Compact Unit for Automatic Driving An, Qing Chen, Xijiang Yuan, Jupu Automatic driving Beidou / inertial compact unit High-precision positioning Neural Networks Adaptive fusion In order to meet the needs of high precision, high availability and high safety positioning for automatic driving, aiming at the technical difficulties of automatic driving positioning in the complex urban environment, an inertial navigation model suitable for the dynamic characteristics of vehicles is established, and a tight combination method of Beidou / inertial high precision positioning is proposed, which solves the problem of rapid accumulation of positioning errors in the weak signal environment of Beidou. The results show that when the Beidou signal is completely interrupted and the INS is combined tightly, the positioning accuracy and continuity are improved significantly, and the maximum error is less than 0.5m, which can realize the automatic driving high-precision continuous navigation and positioning in the complex urban environment. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-08-22 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/469 10.4114/intartif.vol23iss65pp115-123 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 115-123 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 115-123 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 115-123 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/469/116 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/474 2021-02-20T19:42:08Z intartif:Article driver

A survey on plant disease prediction using machine learning and deep learning techniques G, UshaDevi BV, gokulnath Plant disease prediction, Crop productivity, Support vector machine, Deep learning, Meteorological factor, Visual symptoms, Random forest The major agricultural products in India are rice, wheat, pulses, and spices. As our population is increasing rapidly the demand for agriculture products also increasing alarmingly. A huge amount of data are incremented from various field of agriculture. Analysis of this data helps in predicting the crop yield, analyzing soil quality, predicting disease in a plant, and how meteorological factor affects crop productivity. Crop protection plays a vital role in maintaining agriculture product. Pathogen, pest, weed, and animals are responsible for the productivity loss in agriculture product. Machine learning techniques like Random Forest, Bayesian Network, Decision Tree, Support Vector Machine etc. help in automatic detection of plant disease from visual symptoms in the plant. A survey of different existing machine learning techniques used for plant disease prediction was presented in this paper. Automatic detection of disease in plant helps in early diagnosis and prevention of disease which leads to an increase in agriculture productivity. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-07-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/474 10.4114/intartif.vol23iss65pp136-154 Inteligencia Artificial; Vol. 23 No. 65 (2020): Inteligencia Artificial (June 2020); 136-154 Inteligencia Artificial; Vol. 23 Núm. 65 (2020): Inteligencia Artificial (June 2020); 136-154 Inteligencia Artificial; Vol. 23 N.º 65 (2020): Inteligencia Artificial (June 2020); 136-154 1988-3064 1137-3601 10.4114/intartif.vol23iss65 eng https://journal.iberamia.org/index.php/intartif/article/view/474/114 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0

oai:journal.iberamia.org:article/476 2021-02-16T08:59:54Z intartif:Article driver

Design of Small Photovoltaic Power Generation System Based on Maximum Power Point Tracking Cui, Yang Liu, Cheng Cheng, Yanming Niu, Jing photovoltaic power fuzzy variable step algorithm MPPT sun-seeking inverter According to the nonlinear output characteristics of photovoltaic cells, combined with artificial intelligence algorithm the MPPTï¼ˆMaximum Power Point Trackingï¼‰control algorithm based on fuzzy variable step size is proposed, which enables the system to quickly track the maximum power point and improve the energy conversion efficiency of photovoltaic system. This paper designs a small-scale photovoltaic power generation system. The main circuit of the system consists of Perovskite Solar Panels, DC voltage regulator circuit, storage battery and one-way full bridge inverter circuit. The control circuit consists of sun-seeking, inverter and maximum power tracking on constant voltage. Proteus simulation software is used to simulate the sun-seeking part, the inverting part, the general control unit, the keys and the display interface. The results indicate that the functions of the small-scale photovoltaic power generation system can be achieved very well. Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA) 2020-08-27 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Regular Paper application/pdf https://journal.iberamia.org/index.php/intartif/article/view/476 10.4114/intartif.vol23iss66pp26-35 Inteligencia Artificial; Vol. 23 No. 66 (2020): Inteligencia Artificial (December 2020); 26-35 Inteligencia Artificial; Vol. 23 Núm. 66 (2020): Inteligencia Artificial (December 2020); 26-35 Inteligencia Artificial; Vol. 23 N.º 66 (2020): Inteligencia Artificial (December 2020); 26-35 1988-3064 1137-3601 10.4114/intartif.vol23iss66 eng https://journal.iberamia.org/index.php/intartif/article/view/476/117 Copyright (c) 2020 Iberamia & The Authors http://creativecommons.org/licenses/by-nc/4.0 2c5b000a29dda1d6b5e35de804da2cea