941 resultados para intelligent bin


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The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

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Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems’ sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players’ responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.

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In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

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Manuel encyclopédique pour l'éducation.Composé par Chen Bin gong et annoté par Wang Bai gu ; explications de Li Zhuo wu († 1610). Ouvrage gravé par Wu Qi xiang (1628) ; comprenant : vie de Confucius, — en haut des pages, abrégé historique, en bas, vocabulaire méthodique, — renseignements divers, modèles de lettres, etc.2 + 32 + 6 feuillets.

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The "Java Intelligent Tutoring System" (JITS) research project focused on designing, constructing, and determining the effectiveness of an Intelligent Tutoring System for beginner Java programming students at the postsecondary level. The participants in this research were students in the School of Applied Computing and Engineering Sciences at Sheridan College. This research involved consistently gathering input from students and instructors using JITS as it developed. The cyclic process involving designing, developing, testing, and refinement was used for the construction of JITS to ensure that it adequately meets the needs of students and instructors. The second objective in this dissertation determined the effectiveness of learning within this environment. The main findings indicate that JITS is a richly interactive ITS that engages students on Java programming problems. JITS is equipped with a sophisticated personalized feedback mechanism that models and supports each student in his/her learning style. The assessment component involved 2 main quantitative experiments to determine the effectiveness of JITS in terms of student performance. In both experiments it was determined that a statistically significant difference was achieved between the control group and the experimental group (i.e., JITS group). The main effect for Test (i.e., pre- and postiest), F( l , 35) == 119.43,p < .001, was qualified by a Test by Group interaction, F( l , 35) == 4.98,p < .05, and a Test by Time interaction, F( l , 35) == 43.82, p < .001. Similar findings were found for the second experiment; Test by Group interaction revealed F( 1 , 92) == 5.36, p < .025. In both experiments the JITS groups outperformed the corresponding control groups at posttest.

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Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

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Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

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Cette thèse vise à définir une nouvelle méthode d’enseignement pour les systèmes tutoriels intelligents dans le but d’améliorer l’acquisition des connaissances. L’apprentissage est un phénomène complexe faisant intervenir des mécanismes émotionnels et cognitifs de nature consciente et inconsciente. Nous nous intéressons à mieux comprendre les mécanismes inconscients du raisonnement lors de l’acquisition des connaissances. L’importance de ces processus inconscients pour le raisonnement est bien documentée en neurosciences, mais demeure encore largement inexplorée dans notre domaine de recherche. Dans cette thèse, nous proposons la mise en place d’une nouvelle approche pédagogique dans le domaine de l’éducation implémentant une taxonomie neuroscientifique de la perception humaine. Nous montrons que cette nouvelle approche agit sur le raisonnement et, à tour de rôle, améliore l’apprentissage général et l’induction de la connaissance dans un environnement de résolution de problème. Dans une première partie, nous présentons l’implémentation de notre nouvelle méthode dans un système tutoriel visant à améliorer le raisonnement pour un meilleur apprentissage. De plus, compte tenu de l’importance des mécanismes émotionnels dans l’apprentissage, nous avons également procédé dans cette partie à la mesure des émotions par des capteurs physiologiques. L’efficacité de notre méthode pour l’apprentissage et son impact positif observé sur les émotions a été validée sur trente et un participants. Dans une seconde partie, nous allons plus loin dans notre recherche en adaptant notre méthode visant à améliorer le raisonnement pour une meilleure induction de la connaissance. L’induction est un type de raisonnement qui permet de construire des règles générales à partir d’exemples spécifiques ou de faits particuliers. Afin de mieux comprendre l’impact de notre méthode sur les processus cognitifs impliqués dans ce type de raisonnement, nous avons eu recours à des capteurs cérébraux pour mesurer l’activité du cerveau des utilisateurs. La validation de notre approche réalisée sur quarante-trois volontaires montre l’efficacité de notre méthode pour l’induction de la connaissance et la viabilité de mesurer le raisonnement par des mesures cérébrales suite à l’application appropriée d’algorithmes de traitement de signal. Suite à ces deux parties, nous clorons la thèse par une discussion applicative en décrivant la mise en place d’un nouveau système tutoriel intelligent intégrant les résultats de nos travaux.

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School of Management Studies, Cochin University of Science and Technology

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The goal of this work is to develop an Open Agent Architecture for Multilingual information retrieval from Relational Database. The query for information retrieval can be given in plain Hindi or Malayalam; two prominent regional languages of India. The system supports distributed processing of user requests through collaborating agents. Natural language processing techniques are used for meaning extraction from the plain query and information is given back to the user in his/ her native language. The system architecture is designed in a structured way so that it can be adapted to other regional languages of India

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Association rules are used to investigate large databases. The analyst is usually confronted with large lists of such rules and has to find the most relevant ones for his purpose. Based on results about knowledge representation within the theoretical framework of Formal Concept Analysis, we present relatively small bases for association rules from which all rules can be deduced. We also provide algorithms for their calculation.

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In early stages of architectural design, as in other design domains, the language used is often very abstract. In architectural design, for example, architects and their clients use experiential terms such as "private" or "open" to describe spaces. If we are to build programs that can help designers during this early-stage design, we must give those programs the capability to deal with concepts on the level of such abstractions. The work reported in this thesis sought to do that, focusing on two key questions: How are abstract terms such as "private" and "open" translated into physical form? How might one build a tool to assist designers with this process? The Architect's Collaborator (TAC) was built to explore these issues. It is a design assistant that supports iterative design refinement, and that represents and reasons about how experiential qualities are manifested in physical form. Given a starting design and a set of design goals, TAC explores the space of possible designs in search of solutions that satisfy the goals. It employs a strategy we've called dependency-directed redesign: it evaluates a design with respect to a set of goals, then uses an explanation of the evaluation to guide proposal and refinement of repair suggestions; it then carries out the repair suggestions to create new designs. A series of experiments was run to study TAC's behavior. Issues of control structure, goal set size, goal order, and modification operator capabilities were explored. In addition, TAC's use as a design assistant was studied in an experiment using a house in the process of being redesigned. TAC's use as an analysis tool was studied in an experiment using Frank Lloyd Wright's Prairie houses.