In this research will show a method for sound-recognition with artificial neural network backpropagation concept. The artificial neural network use sigmoid activation function to all layer. Steps to the extraction, fi...
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This paper studies some fundamental properties on signal propagation in one-dimensional cellular neural networks with the antisymmetric template under the assumption that the initial output has only one connected comp...
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In this paper we introduce an application layer for mobile devices that delivers knowledge sharing and remote collaboration to the end users. This layer is a part of a much wider knowledge sharing system called Intern...
In this paper we introduce an application layer for mobile devices that delivers knowledge sharing and remote collaboration to the end users. This layer is a part of a much wider knowledge sharing system called Internet Medical Consultant. Our main focus is on the user interface and data processing according to the mobility issues of the application. This will contribute to effective completion of application's main goal - quick, easy and intuitive reach of knowledge as well as manipulation with well defined and rich data content in the remote collaboration process.
One of the main issues in wireless sensor networks is energy efficiency. Most of the energy is used for wireless transmission. To reduce an amount of data being sent, if a particular compression algorithm is used, tha...
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One of the main issues in wireless sensor networks is energy efficiency. Most of the energy is used for wireless transmission. To reduce an amount of data being sent, if a particular compression algorithm is used, than it can significantly reduce a power consumption and increase node's operating lifetime. Presented in this paper is a research, in which the possibility of use of IEEE 802.15.4 wireless sensor networks in electrocardiogram (ECG) monitoring applications is analyzed. ECG signal, measured from a patient heart, is in the first step compressed that uses Autoregressive (AR) predictive coding and then again, using Huffman's entropy coding. It has been studied, through the use of simulations, how reduction in data rate of compressed data will affect node's average power consumption. The results obtained from data compression of ECG signal show that sufficient energy saving can be achieved.
Multi-agent systems (MAS) are a research topic with ever-increasing importance. This is due to their inherently distributed organization that copes more naturally with real-life problems whose solution requires people...
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Multi-agent systems (MAS) are a research topic with ever-increasing importance. This is due to their inherently distributed organization that copes more naturally with real-life problems whose solution requires people to coordinate efforts. One of its most prominent challenges consists on the creation of efficient coordination methodologies to enable the harmonious operation of teams of agents in adversarial environments. This challenge has been promoted by the Robot World Cup (RoboCup) international initiative every year since 1995. RoboCup provides a pragmatic testbed based on standardized platforms for the systematic evaluation of developed MAS coordination techniques. This initiative encompasses a simulated robotic soccer league in which 11 against 11 simulated robots play a realistic soccer game that is particularly suited for researching coordination methodologies. This paper presents a comprehensive overview of the most relevant coordination techniques proposed up till now in the simulated robotic soccer domain.
Digital Library is a way to represent, retrieval, and study Thai E-san culture heritages without directly accessing and touching. It may help to reduce a dilapidation of Thai E-san culture heritages. We commence our p...
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Digital Library is a way to represent, retrieval, and study Thai E-san culture heritages without directly accessing and touching. It may help to reduce a dilapidation of Thai E-san culture heritages. We commence our project with organizing a collection of images through classification technique. Therefore, this work is motivated by two main drivers. Firstly, we aim to apply an alternative dimension of CBIR to classify a collection of Thai E-san heritage images into two classes: the class of heritage images which involve human activities, and the class of heritage images with non-human activities (e.g. images of ancient remains and antiques). Secondly, we also propose a new method of images classification. It is to apply Naïve Bayes to produce image classifier based on edge histogram features. This approach is valuable for the automatically classifying heritage images, where it is a time-consuming and labour-intensive process if it is done by manual classification. After testing, the experimental results show an effective accuracy. This would demonstrate that our approach is sufficiently reliable for use.
Acquisition of pervasive sensor data can be often unsuccessful due to power outage at nodes, time synchronization issues, interference, network transmission failures or sensor hardware issues. Such failures can lead t...
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TraSMAPI (Traffic Simulation Manager Application Programming Interface) is designed to provide real-time interaction with Traffic Simulators, collect relevant metrics and statistics, and offer an integrated framework ...
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TraSMAPI (Traffic Simulation Manager Application Programming Interface) is designed to provide real-time interaction with Traffic Simulators, collect relevant metrics and statistics, and offer an integrated framework to develop Multi-Agent Systems. It is presented as a tool for the simulation of dynamic control systems in road networks with special focus on Multi-Agent Systems. The abstraction over the simulator opens up the possibility of running different traffic simulators using the same API (application programming interface) allowing the comparison of results of the same application in different simulators. The proposed approach is, therefore, expected to be a key asset in supporting and enhancing engineers and practitioners to make more effective control decisions and implement more efficient management policies while analyzing and addressing traffic related problems in urban areas.
From the very beginning of computer systems and networks, there has been a severe lack of analytical techniques enabling effective performance evaluation/prediction for actual systems and networks. Such techniques wer...
In this paper we aim to estimate the differential student knowledge model in a probabilistic domain within an intelligent tutoring system. The suggested algorithm aims to estimate the actual student model through the ...
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ISBN:
(纸本)9780615375298
In this paper we aim to estimate the differential student knowledge model in a probabilistic domain within an intelligent tutoring system. The suggested algorithm aims to estimate the actual student model through the student answers to questions requiring diagnosing skills. Updating and verification of the model are conducted based on the matching between the student and model answers. Two different approaches to updating namely coarse and refined model are suggested. Results suggest that the refined model, although takes more computational resources, provides a slightly better approximation of the student model.
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