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Titlebook: Intelligent Data analysis and its Applications, Volume I; Proceeding of the Fi Jeng-Shyang Pan,Vaclav Snasel,Shyue-Liang Wang Conference pr

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书目名称Intelligent Data analysis and its Applications, Volume I
副标题Proceeding of the Fi
编辑Jeng-Shyang Pan,Vaclav Snasel,Shyue-Liang Wang
视频videohttp://file.papertrans.cn/470/469603/469603.mp4
概述Recent research on Intelligent Data Analysis and Applications.Proceedings of the First Euro- China Conference on Intelligent Data Analysis and Applications, held June 13-15, 2014 in Shenzhen, China.Pr
丛书名称Advances in Intelligent Systems and Computing
图书封面Titlebook: Intelligent Data analysis and its Applications, Volume I; Proceeding of the Fi Jeng-Shyang Pan,Vaclav Snasel,Shyue-Liang Wang Conference pr
描述.This volume presents the proceedings of the First Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2014), which was hosted by Shenzhen Graduate School of Harbin Institute of Technology and was held in Shenzhen City on June 13-15, 2014. ECC 2014 was technically co-sponsored by Shenzhen Municipal People’s Government, IEEE Signal Processing Society, Machine Intelligence Research Labs, VSB-Technical University of Ostrava (Czech Republic), National Kaohsiung University of Applied Sciences (Taiwan), and Secure E-commerce Transactions (Shenzhen) Engineering Laboratory of Shenzhen Institute of Standards and Technology..
出版日期Conference proceedings 2014
关键词Computational Intelligence; Intelligent Applications; Intelligent Data Analysis
版次1
doihttps://doi.org/10.1007/978-3-319-07776-5
isbn_softcover978-3-319-07775-8
isbn_ebook978-3-319-07776-5Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer International Publishing Switzerland 2014
The information of publication is updating

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Information Security Management for Higher Education Institutionsation security to be effectively enforced, good management practices comprising policies and controls should be established. This paper investigates the information security management for higher education institutions. Based on the conventional CIA (confidentiality, integrity and availability) tria
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Shape Estimation from 3D Point Cloudsics. It is challenging because the data is typically noisy, cluttered, partly missing and unordered. We address shape estimation using a template object under a fully statistical model, where the data is assumed to be modeled using a Poisson process on the object’s boundary (surfaces), corrupted by
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Deterministic Data Sampling Based on Neighborhood Analysis sample. Such sample allows us to use a great variety of analytical methods, the direct application of which on original data would be unfeasible. There are many methods used for different purposes and with different results. In this paper, we outline a simple, flexible and straightforward approach
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