17 research outputs found

    Semiotic analysis of neuroenergetic networks in the construction of intelligent agents

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    Orientador: Ricardo Ribeiro GudwinDisserta√ß√£o (mestrado) - Universidade Estadual de Campinas. Faculdade de Engenharia Eletrica e de Computa√ß√£oResumo: Neste trabalho desenvolvemos uma an√°lise das redes neuroenerg√©ticas (propostas por Leonid B. Emelyanov-Yaroslavsky) e a especifica√ß√£o de um agente inteligente constru'ido com estas redes, comparando-o com outras especifica√ßoes de agentes existentes na literatura e tamb√©m avaliando suas capacidades semi√≥ticas. As redes neuroenerg√©ticas caracterizam-se por serem autoorganiz√°veis em torno do objetivo de minimiza√ß√£o do consumo de energia de seus neur√īnios. A partir deste objetivo, e dadas algumas restri√ß√Ķes, Emelyanov-Yaroslavsky sugere que deveriam surgir no agente neuroenerg√©tico caracter√≠sticas t√≠picas de sistemas inteligentes como mem√≥ria, voli√ß√£o, aprendizado, capacidade de generaliza√ß√£o, etc. Este trabalho visa dar os primeiros passos na valida√ß√£o das propostas de Emelyanov-Yaroslavsky por meio da compreens√£o das caracter√≠sticas b√°sicas do modelo e sua reprodu√ß√£o e simula√ß√£o. Uma vers√£o computacional da rede neuroenerg√©tica foi implementada demonstrando sua viabilidade operacional e capacidade de auto-organiza√ß√£o. Embora n√£o tenha sido implementado, o modelo do agente neuroenerg√©tico abre perspectivas no sentido de criar sistemas cognitivos capazes de atuar nos mais diversos ambientes e dom√≠niosAbstract: This work presents an analysis of the neuroenergetic networks (proposed by Leonid B. Emelyanov-Yaroslavsky) and the specification of an intelligent agent constructed with these networks, comparing it to other existing agent specifications in the literature and also evaluating its semiotic capabilities. The neuroenergetic networks are characterized by their capability of selforganizing, aiming at minimizing the energy consumption of their neurons. With this aim in mind, and given some restrictions, Emelyanov-Yaroslavsky suggests that the neuroenergetic agent should develop some typical characteristics of intelligent systems such as: memory, volition, learning and, generalizationcapabilities, etc. This work aims at making the first steps validating Emelyanov-Yaroslavsky¬Ņs proposals through the comprehension of the model¬Ņs basic features and its reproduction and simulation. A computational version of the neuroenergetic network was implemented, demonstrating its operational viability and capacity of selforganization. Even though it has not yet been implemented, the model of the neuroenergetic agent opens perspectives in the direction of creating cognitive systems, capable to act in most diverse environments and domainsMestradoEngenharia de Computa√ß√£oMestre em Engenharia El√©tric

    A Benchmark for Iris Location and a Deep Learning Detector Evaluation

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    The iris is considered as the biometric trait with the highest unique probability. The iris location is an important task for biometrics systems, affecting directly the results obtained in specific applications such as iris recognition, spoofing and contact lenses detection, among others. This work defines the iris location problem as the delimitation of the smallest squared window that encompasses the iris region. In order to build a benchmark for iris location we annotate (iris squared bounding boxes) four databases from different biometric applications and make them publicly available to the community. Besides these 4 annotated databases, we include 2 others from the literature. We perform experiments on these six databases, five obtained with near infra-red sensors and one with visible light sensor. We compare the classical and outstanding Daugman iris location approach with two window based detectors: 1) a sliding window detector based on features from Histogram of Oriented Gradients (HOG) and a linear Support Vector Machines (SVM) classifier; 2) a deep learning based detector fine-tuned from YOLO object detector. Experimental results showed that the deep learning based detector outperforms the other ones in terms of accuracy and runtime (GPUs version) and should be chosen whenever possible.Comment: Accepted for presentation at the International Joint Conference on Neural Networks (IJCNN) 201

    A parallel robot with three translational degrees of freedom for machining operations

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    This paper proposes a new machine tool structure design for machining based on a Delta Robot architecture as object of study, known as Tsai's Manipulator, patented by Tsai in 1997. The new architecture employs only rotary joints instead of spherical ones as it is usual for Delta Robots. The rotary joints allow its mount under pretension to eliminate clearances or backlash, avoiding the use of expensive spherical joints. All the other mechanical parts are standard components, which makes the solution attractive in terms of cost. A simplified inverse kinematic solution over the one proposed by Tsai is presented, based on a practical approach. The simplified solution reduces the number of steps to solve the inverse kinematics without any loss of performance. In addition, a solution to deal with the coupled axis without parasitic motion is presented. To increase the accuracy and the stiffness of the robot, a special attention was given to the rotary joints using preload rotational ball bearing joints. The structure parts were manufactured mostly by laser cutting with almost no complementary machining processes. In order to evaluate the proposed solutions, a prototype was built and a dedicated control software was developed for this particular robot. Workpieces were milled with the robot to demonstrate its capability and the advantages regarding the proposed machine architecture

    Aquisi√ß√£o de impress√Ķes palmares em formato digital para a identifica√ß√£o biom√©trica de rec√©m-nascidos /

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    Orientadoras: Prof¬™ Dr¬™ Monica Nunes Lima Cat e Prof¬™ Dr¬™ Olga Regina Pereira BellonTese (doutorado) - Universidade Federal do Paran√°, Setor de Ci√™ncias da Sa√ļde, Programa de P√≥s-Gradua√ß√£o em Sa√ļde da Crian√ßa e do Adolescente. Defesa: Curitiba, 2007Inclui bibliografiaArea de concentra√ß√£o : Informatica em sa√ļde - Processamento de imagen

    Aquisi√ß√£o de impress√Ķes palmares em formato digital para a identifica√ß√£o biom√©trica de rec√©m-nascidos /

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    Orientadoras: Prof¬™ Dr¬™ Monica Nunes Lima Cat e Prof¬™ Dr¬™ Olga Regina Pereira BellonTese (doutorado) - Universidade Federal do Paran√°, Setor de Ci√™ncias da Sa√ļde, Programa de P√≥s-Gradua√ß√£o em Sa√ļde da Crian√ßa e do Adolescente. Defesa: Curitiba, 2007Inclui bibliografiaArea de concentra√ß√£o : Informatica em sa√ļde - Processamento de imagen

    Extens√£o em CUDA para o framework waLBerla

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    Este trabalho apresenta uma extens√£o em CUDA para o framework waLBerla. waLBerla √© um framework massivamente paralelo que utiliza¬†algoritmos baseados em stencil operando sobre uma grid estruturada de blocos¬†com principal aplica√ß√£o em simula√ß√Ķes de fluido com geometria complexa¬†usando o LBM. Para aumentar a performance e permitir o uso de computa√ß√£o¬†heterog√™nea um novo m√≥dulo em CUDA foi criado. Al√©m disso, esse trabalho¬†tamb√©m levou em conta o desempenho das simula√ß√Ķes utilizando mem√≥ria¬†alocada de maneira linear e alinhada e tamb√©m analisou diferentes tamanhos de¬†dom√≠nio com a finalidade de definir um crit√©rio para aloca√ß√£o eficiente de grids¬†de blocos de threads para a GPU. Os resultados obtidos, usando opera√ß√Ķes de¬†ponto flutuante de dupla precis√£o, est√£o de acordo com a literatura. O m√≥dulo¬†CUDA alcan√ßou 612 MLUPS com ECC desabilitado e 489 MLUPS usando ECC¬†na GPU Tesla K40m

    Contact AuthorEmergence of Multiagent Spatial Coordination Strategies through Artificial Coevolution

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    This paper describes research investigating the evolution of coordination strategies in robot soccer teams. Each player (viewed as an agent) is provided with a common set of skills and is assigned to perform over a delimited area inside a soccer field. The idea is to optimize the whole team behavior by means of a spatial coadaptation process in which new players are selected in such a way to comply with the already existing ones. The main results show that, through coevolution, we progressively create teams whose members act on complementary areas of the playing field, being capable of prevailing over a standard opponent team with a fixed formation. Keyword

    Hierarchical Evolution of Heterogeneous Neural Networks

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    Abstract ‚Äď This paper describes a hierarchical evolutionary technique developed to design and train feedforward neural networks with different activation functions on their hidden layer neurons (Heterogeneous Neural Networks). At an upper level, a genetic algorithm is used to determine the number of neurons in the hidden layer and the type of the activation function of those neurons. At a second level, neural nets compete against each other across generations so that the nets with the lowest test errors survive. Finally, on a third level, a coevolutionary approach is used to train each of the created networks by adjusting both the weights of the hidden layer neurons and the parameters for their activation functions

    PROINFODATA: Monitoring a Large Park of Computational Laboratories

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    Part 8: Case Studies and Demonstrations of Open Source ProjectsInternational audienceThis paper briefly presents a model for monitoring a large, heterogeneous and geographically scattered computer park. The data collection is performed by a software agent. The collected data are sent to the central server over the Internet, and stored by the storage system. An on-line portal makes up the visualization system, featuring charts, reports, and other tools for assessing the state of the park. This system is currently monitoring circa 150,000 machines
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