The spike-timing-dependent-plasticity (STDP) is a mechanism for adjusting the efficacies of biological synapses that was observed and studied in vitro. However, the STDP effect for natural neurons in vivo is subject o...
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The spike-timing-dependent-plasticity (STDP) is a mechanism for adjusting the efficacies of biological synapses that was observed and studied in vitro. However, the STDP effect for natural neurons in vivo is subject of debate because in several experiments when the neurons are stimulated indirectly by natural paths the STDP effect was insignificant. Starting from these aspects this work studies by simulation the STDP long-term effect on synaptic plasticity in order to determine whether the long-term potentiation (LTP) and the long-term depression (LTD) could compensate each other during long-term activity of the neural network. The results show that for some synapses the weights start to oscillate in small intervals around long term stable values that are different from the limits of the weights variation interval. This behavior is caused by the fact that, indeed, the effects of LTP and LTD compensate each other at certain weight values when the same pattern of the input stimuli is presented repeatedly to the network input. The LTP and LTD compensation that determines long term weights stability to other values than the weight variation limits could improve the sensitivity of the learning process in the biological networks because no neuron specific limitation is introduced.
Depth information from a captured scene can provide a more complete description of objects which can be exploited for recognition purposes. In this paper we propose a new approach to static hand gesture recognition th...
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Depth information from a captured scene can provide a more complete description of objects which can be exploited for recognition purposes. In this paper we propose a new approach to static hand gesture recognition that explores only depth information acquired with a Microsoft Kinect camera. Firstly, the regions of interest are extracted from depth data and a 3D point cloud is created taking into consideration the capture device settings. Then, for each 3D point in the simplified point cloud the local spin image descriptor is computed. The performance of hand pose detection greatly depends on the 3D shape descriptor used. KPCA is used for dimensionality reduction and for noise elimination from obtained spin image histograms. The most relevant features in terms of principal components are served as input for a SVM classifier. Experimental results show a high level of accuracy in recognizing static hand gestures using spin images in 3D point clouds.
Wireless sensors networks is an active research topic. The sensor nodes (i.e. motes) are the main building blocks of these networks. There is a permanent concern for building more and more efficient motes in order to ...
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Wireless sensors networks is an active research topic. The sensor nodes (i.e. motes) are the main building blocks of these networks. There is a permanent concern for building more and more efficient motes in order to satisfy the demanding specifications of a sensor network. This paper introduces a new mote device: aceMOTE which is based on a 32 bit microcontroller. The hardware structure of the mote is presented and a comparison is made with similar popular devices. An experimental analysis is made regarding the energy consumption and the results prove that a 32 bit microcontroller is a viable choice for usage in mote design compared with the more frequently used 8 bit and 16 bit microcontrollers.
In this paper, an adaptive observer is proposed for the joint estimation of states and parameters of a fractional nonlinear system with external perturbations. The convergence of the proposed observer is derived in te...
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In this paper authors will expose a work developed with the aim to submit an educational innovation project proposal to a competitive call for Educational Innovation Projects 2013-2015 of the Education Advisory Servic...
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In this paper authors will expose a work developed with the aim to submit an educational innovation project proposal to a competitive call for Educational Innovation Projects 2013-2015 of the Education Advisory Service of the Basque Country University (UPV/EHU, Spain). This project is being carried out in the computer Structure and computer Architecture sub-module of the Degree in computer Management and Information Systems engineering of the University College of engineering of Vitoria-Gasteiz, University of the Basque Country (UPV/EHU). The project is based on the active learning, more specifically, on cooperative learning. In this paper we have given deeper insight the dependencies between all the subjects belonging to the analyzed sub-module, which is composed of two subjects named computer Structure and computer Architecture. We have included in such analysis a previous subject named Principles of Digital Systems Design, which does not belong to that sub-module, but plays an important role in the acquisition of the knowledge and competencies of the two previously referenced subjects.
Embedded network systems use serial communication protocols and simplified media access control schemes in order to exchange information among several interconnected nodes. Within this paper a generalization of the cl...
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Embedded network systems use serial communication protocols and simplified media access control schemes in order to exchange information among several interconnected nodes. Within this paper a generalization of the classical media access control (MAC) protocols used in small embedded serial networks of microcontrollers is investigated and an implementation platform for testing the proposed MAC schemes is described. Thus, the classic master-slave and token-bus protocols turn out to be just two particular cases of the proposed generalized media access control (GMAC) algorithms: a centralized and a distributed one, respectively. By applying these generalized algorithms in practice, significant increase in data throughput is obtained, as it resulted from the simulation tests and then by practical implementation on a typical embedded network of microcontrollers.
This paper presents a combination of programming languages and web technologies used to deploy a modern remote controlled system. The hardware part of the system is a parallel port interface board that contains differ...
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This paper presents a combination of programming languages and web technologies used to deploy a modern remote controlled system. The hardware part of the system is a parallel port interface board that contains different types display devices, user-input components and some relays. The system functionality is based on some software applications developed using different techniques: the communication between the parallel interface, local computer and webserver PC is based on standard C, the user interface is developed using php, mysql, html and javascript technologies. Users can access full resources of the system if they are registered or only some demonstration and training sections as guest users.
This paper presents a study about how efficient implementation of software changes helps students to better understanding of programming techniques and algorithms. The study is performed during last three years on fir...
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This paper presents a study about how efficient implementation of software changes helps students to better understanding of programming techniques and algorithms. The study is performed during last three years on first year students, considering applications classes for two first year courses: computer programming part I and part II. There are taken into account some partial results during the semester, final exams and also some questionnaires accomplished by students. The ratings for this study are imported from a database. The study is regarding around eight hundred students.
A series of modelling methodologies based on artificial intelligence tools are applied to solve a complex real-world problem. Neural networks and support vector machines are used as models and differential evolution a...
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A series of modelling methodologies based on artificial intelligence tools are applied to solve a complex real-world problem. Neural networks and support vector machines are used as models and differential evolution and clonal selection algorithms as optimizers for structural and parametric optimization of the models. The goal is to make a comparative analysis of these methods for the case study of the free radical polymerization of styrene, a complex, difficult to model process, where the monomer conversion and molecular masses are predicted as a function of reaction conditions, i.e. temperature, amount of initiator and time. Four modelling methodologies are developed and evaluated in terms of accuracy.
Nowadays parallel manipulators are used widely in bioengineering applications;this leads to many exciting expectations as well as challenges. The kinematic analysis of parallel manipulators with their differential kin...
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