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Balıkesir, Turkey

Wang Q.,Science and Technology on Integrated Information System Laboratory | Wang H.,Science and Technology on Integrated Information System Laboratory | Wang H.,CAS Institute of Software | Zhang C.,Science and Technology on Integrated Information System Laboratory | And 3 more authors.
IEEE International Conference on Data Mining Workshops, ICDMW | Year: 2015

In current days, data tend to become much bigger than before, and the distributed computing system is an prevalent option to deal with them. As one of powerful tools, MapReduce framework provides a cheap and efficient way to write parallel programs to run on distributed computing systems. Chance discovery (CD) is an extension of data mining, where chance refers to rare but important events or situations. Idea Graph is an efficient algorithm proposed to detect chances. However, the traditional implementation of Idea Graph is sequential, and its performance encounters some bottlenecks when dealing with big data. In this paper, we propose a parallel implementation of Idea Graph using MapReduce to better meet with the challenge of big data. First, we introduce the MapReduce framework, and then Idea Graph is introduced in brief. After that, we present the details on how we design the parallel Idea Graph implementation. In the end of the paper, several experiments are conducted to evaluate the proposed implementation. The experimental results demonstrate the validation of the proposed implementation and its better performance as compared with that of sequential Idea Graph implementation when handling big data. © 2014 IEEE. Source


Yang Z.,National Laboratory of Information Control | Qiu Y.,National Laboratory of Information Control | Li X.,National Laboratory of Information Control | Kang Y.,NCO Academy
Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010 | Year: 2010

In this paper, distributed data fusion for satellite passive localization is examined. The traditional single or multiple satellite passive localization systems usually use a fixed localization mode which commonly has poor fault tolerance capability. We investigate a distributed passive localization scheme using angle only measurements from multiple satellites. However, recursive fusion algorithms are subject to different tradeoffs regarding their speed of convergence and convergence accuracy, and the satellite passive localization applications usually suffer large initial error. The convex combination is recently used to combine different adaptive filters to obtain better filtering performance than the original filters. To improve the fusion performance, data fusion algorithm using convex combination is developed based on sigma point Kalman filter(SPKF). Computer simulation experiments are performed to show the effectiveness of the proposed localization scheme and algorithm. © 2010 IEEE. Source


Chengtian S.,Beijing Institute of Technology | Zhiliang S.,NCO Academy | Xi P.,Beijing Institute of Technology
Advances in Intelligent and Soft Computing | Year: 2012

An review on the development and extrodinary properties of left-handed materials is first coverd.Based on the current research, left-handed materials is applied to the microstrip antenna design.Two miniaturized antenna are designed by using the left-handed materials, which makes futhur miniaturization of microstrip antenna possible. © 2012 Springer-Verlag GmbH. Source


Usakli A.B.,NCO Academy
Computational Intelligence and Neuroscience | Year: 2010

The aim of this study is to present some practical state-of-the-art considerations in acquiring satisfactory signals for electroencephalographic signal acquisition. These considerations are important for users and system designers. Especially choosing correct electrode and design strategy of the initial electronic circuitry front end plays an important role in improving the system's measurement performance. Considering the pitfalls in the design of biopotential measurement system and recording session conditions creates better accuracy. In electroencephalogram (EEG) recording electrodes, system electronics including filtering, amplifying, signal conversion, data storing, and environmental conditions affect the recording performance. In this paper, EEG electrode principles and main points of electronic noise reduction methods in EEG signal acquisition front end are discussed, and some suggestions for improving signal acquisition are presented. Copyright © 2010 Ali Bulent Usakli. Source


Zhou J.-D.,PLA Air Force Aviation University | Zhou J.-D.,Fourth Laboratory of Complex System | Wang X.-D.,NCO Academy | Zhou H.-J.,Fourth Laboratory of Complex System | And 2 more authors.
Optical Engineering | Year: 2012

It is known that error-correcting output codes (ECOC) is a common way to model multiclass classification problems, in which the research of encoding based on data is attracting more and more attention. We propose a method for learning ECOC with the help of a single-layered perception neural network. To achieve this goal, the code elements of ECOC are mapped to the weights of network for the given decoding strategy, and an object function with the constrained weights is used as a cost function of network. After the training, we can obtain a coding matrix including lots of subgroups of class. Experimental results on artificial data and University of California Irvine with logistic linear classifier and support vector machine as the binary learner show that our scheme provides better performance of classification with shorter length of coding matrix than other state-of-the-art encoding strategies. © 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). Source

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