Evolutionary Design for Computational Visual Attention

A new framework for simulating the visual attention system in primates is introduced. The proposed architecture is an abstraction of existing approaches influenced by the work of Koch and Ullman, and Tompa. Each stage of the attentional hierarchy is chosen with consideration for both psychophysics and mathematical optimality. A set of attentional operators are derived that act on basic image channels of intensity, hue and orientation to produce maps representing perceptual importance of each image pixel. The development of such operators is realized within the context of a genetic optimization. The model includes the notion of an information domain where feature maps are transformed to a domain that more closely corresponds to the human visual system. A careful analysis of various issues including feature extraction, density estimation and data fusion is presented within the context of the visual attention problem

Concurrent, Integrated and Multicriteria Design Support for Mechatronic Systems

RÉSUMÉ Les systèmes mécatroniques sont une combinaison coopérative de composantes mécaniques, électroniques, de contrôle et logiciels. Dans les dernières décennies, Ils ont trouvé diverses applications dans l'industrie et la vie quotidienne. En raison de leur aspect multi-physique, du nombre élevé de leurs composantes et des interconnexions dynamiques entre les différents domaines impliqués dans leur fonctionnement, les dispositifs mécatroniques sont souvent considérés comme hautement complexes ce qui rend la tâche de les concevoir très difficile pour les ingénieurs. Cette complexité inhérente a attiré l’attention de la communauté de recherche en conception, en particulier dans le but d’atteindre une conception optimale des systèmes multi-domaines. Ainsi, cette thèse, représente une recherche originale sur le développement d'un paradigme de conception systématique, intégrée et multi-objectifs pour remplacer l'approche de conception séquentielle traditionnelle qui tend à traiter les différents domaines de la mécatronique séparément. Dans le but d'augmenter l'efficacité, la fiabilité, la facilité de contrôle et sa flexibilité, tout en réduisant la complexité et le coût effectif, ainsi que l'intégration systèmes, cette thèse présente de nouvelles approches pour la conception concurrente et optimale des systèmes mécatroniques aux stades de design conceptuel et détaillé. Les modèles mathématiques et les fondements qui soutiennent cette pensée sont présentés dans cette thèse. Les contributions des travaux de recherche de ce doctorat ont commencé par l'introduction d'un vecteur d'indices appelé le profile mécatronique multicritère (PMM) utilisé pour l'évaluation des concepts lors de la conception des systèmes mécatroniques. Les intégrales floues non linéaires de la théorie de décisions multicritères sont utilisées pour agréger les critères de conception et pour gérer les interactions possibles entre elles. Ensuite, une méthodologie de conception conceptuelle systématique est proposée et formulée. Le soutien à l'intégration d'outils d’aide à la décision multicritère dans le processus de conception est un autre objectif de cette thèse où un certain nombre de cadres de travail sont proposés pour aider les ingénieurs concepteurs à évaluer l’importance de certains critères et des paramètres d'interaction. Ces cadres de travail ne s'appliquent pas uniquement l'évaluation de la conception et de la conception optimales, mais aussi à la détermination des possibles façons d'améliorer les concepts développés. Des méthodes basées sur l’exploitation de données ainsi que des algorithmes d'optimisation sémantique sont utilisées pour identifier les paramètres flous avec le peu d’information disponibles sur les différents choix de concepts et les préférences des concepteurs.----------ABSTRACT Mechatronic systems are a combination of cooperative mechanical, electronics, control and software components. They have found vast applications in industry and everyday life during past decades. Due to their multi-physical aspect, the high number of their components, and the dynamic inter-connections between the different domains involved, mechatronic devices are often considered to be highly complex which makes the design task very tedious and non-trivial. This inherent complexity, has attracted a great deal of attention in the research community, particularly in the context of optimal design of multi-domain systems. To this end, the present thesis represents an original investigation into the development of a systematic, integrated and multi-objective design paradigm to replace the traditional sequential design approach that tends to deal with the different domains separately. With the aim of increasing efficiency, reliability, controllability and flexibility, while reducing complexity and effective cost, and finally facilitating system integration, this thesis presents new approaches towards concurrent and optimal design of mechatronic systems in conceptual and detailed design stages. The mathematical models and foundations which support this thinking are presented in the thesis. The contributions of our research work start with introducing an index vector called Mechatronic Multi-criteria Profile (MMP) used for concept evaluation in design of mechatronic systems. Nonlinear fuzzy integrals from multicriteria decision theory are utilized to aggregate design criteria and for handling possible interactions among them. Then, a systematic conceptual design methodology is proposed and formulated. Supporting the incorporation of multicriteria decision making tools into the design process, is another focus of this work where a number of frameworks are proposed to help the designers with assessment of criteria importance and interaction parameters. These frameworks are not only applicable in optimal design and design evaluation procedures, but also for determining possible ways for design improvements. Both data-driven methods as well as semantic-based optimization algorithms are used to identify the fuzzy parameters with limited available information about the design alternatives and designer preferences. Moreover, a fuzzy-based multi-objective approach has been undertaken for proposing and formulating a detailed design methodology. A unified performance evaluation index is introduced by the means of Choquet integrals and then optimized using a constrained particle swarm optimization (PSO) algorithm

Preference mining techniques for customer behavior analysis

The thesis has studied a number of critical problems in data mining for customer behavior analysis and has proposed novel techniques for better modeling of the customers’ decision making process, more efficient analysis of their travel behavior, and more effective identification of their emerging preference

ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

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Algebraic Structures of Neutrosophic Triplets, Neutrosophic Duplets, or Neutrosophic Multisets

Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (, , ), where is an entity {i.e. element, concept, idea, theory, logical proposition, etc.}, is the opposite of , while is the neutral (or indeterminate) between them, i.e., neither nor .Based on neutrosophy, the neutrosophic triplets were founded, which have a similar form (x, neut(x), anti(x)), that satisfy several axioms, for each element x in a given set.This collective book presents original research papers by many neutrosophic researchers from around the world, that report on the state-of-the-art and recent advancements of neutrosophic triplets, neutrosophic duplets, neutrosophic multisets and their algebraic structures – that have been defined recently in 2016 but have gained interest from world researchers. Connections between classical algebraic structures and neutrosophic triplet / duplet / multiset structures are also studied. And numerous neutrosophic applications in various fields, such as: multi-criteria decision making, image segmentation, medical diagnosis, fault diagnosis, clustering data, neutrosophic probability, human resource management, strategic planning, forecasting model, multi-granulation, supplier selection problems, typhoon disaster evaluation, skin lesson detection, mining algorithm for big data analysis, etc