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A new online field feature selection algorithm based on streaming data

Journal of Ambient Intelligence and Humanized Computing 2024年第2期15卷 1365-1377页

作者： Zhang, Zhenjiang Song, Fuxing Zhang, Peng Chao, Han-Chieh Zhao, Yingsi School of Software Engineering Beijing Jiaotong University Beijing100044 China Department of Electronic and Information Engineering Key Laboratory of Communication and Information Systems Beijing Municipal Commission of Education Beijing Jiaotong University Beijing100044 China School of Information Science and Engineering Fujian University of Technology Fuzhou350118 China School of Mathematics and Computer Science Wuhan Polytechnic University Wuhan430023 China Department of Electrical Engineering National Dong Hwa University Hualien97401 Taiwan School of Economics and Management Beijing Jiaotong University Beijing100044 China

The rapid development of Internet technology derived out a massive network text data. Therefore, how to classify the massive text data efficiently has important theoretical significance and application value. In order to acquire accurate classification results, the process has been divided into two parts. In terms of text representation, this paper proposes an online field feature selection algorithm (OFFS algorithm) based on streaming data, which solves the problems of low efficiency and memory consumption of traditional feature selection algorithms. With improvements in the vector space model, the new algorithm can select the real-time feature of the data and quickly generate text vector. In the aspect of classifier design, an OFFS-BP neural network text classifier based on BP neutral network and OFFS algorithm is designed. It adapts to the distributed parallel computing, reduces the training time and balances the computation efficiency and classification accuracy. Finally based on the Spark platform, the OFFS-BP neural network classifier is implemented. The experimental results show that the OFFS-BP neural network classifier is more suitable for big data environment with less computation time and higher classification efficiency. © Springer-Verlag GmbH Germany, part of Springer Nature 2018.

关键词： Neural networks

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A single channel EMI signal separation method based on directly-mean empirical mode decomposition

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Journal of Information and Computational science 2015年第17期12卷 6333-6340页

作者： Li, Hongyi Song, Ziming Zhao, Di Wang, Pidong Chen, Jiaxin LMIB School of Mathematics and Systems Science Beihang University Beijing China School of Software Beihang University Beijing China School of Reliability and Systems Engineering Beihang University Beijing China School of Computer Science and Engineering Beihang University Beijing China

ICA is a powerful decomposition method for time-domain series, except for the requirement that the number of observed signals and the source signals should be the same, which makes ICA fail to process single channel signals. In this paper, we propose a new method using directly-mean EMD, which is utilized to extract independent components from a single channel mixture. The proposed method could overcome the side effect of original EMD, and can be applied to the separation of EMI signals to locate interference sources. Simulation experimental results demonstrate the effectiveness of the proposed method, and show that the proposed method outperforms the comparison methods, such as the original EMD ICA and wavelet ICA. © 2015 by Binary Information Press.

关键词： Empirical mode decomposition

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High Dimensional Electromagnetic Interference Signal Clustering Based On SOM Neural Network

Electronics

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Electronics 2016年第1期20卷 27-31页

作者： Li, Hongyi Zhao, Di Xu, Shaofeng Wang, Pidong Chen, Jiaxin LMIB School of Mathematics and Systems Science Beihang University Beijing100191 China School of Mathematics and Systems Science Beihang University Beijing100191 China School of Software Beihang University China School of Reliability and Systems Engineering Beihang University Beijing100191 China School of Computer Science and Engineering Beihang University Beijing100191 China

In this paper, we study the spectral characteristics and global representations of strongly nonlinear, non-stationary electromagnetic interferences (EMI), which is of great significance in analysing the mathematical modelling of electromagnetic capability (EMC) for a large scale integrated system. We firstly propose to use Self-Organizing Feature Map Neural Network (SOM) to cluster EMI signals. To tackle with the high dimensionality of EMI signals, we combine the dimension reduction and clustering approaches, and find out the global features of different interference factors, in order to finally provide precise mathematical simulation models for EMC design, analysis, forecasting and evaluation. Experimental results have demonstrated the validity and effectiveness of the proposed method. © (2016) All rights reserved.

关键词： Signal interference

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Threshold concepts and threshold skills in computing 12

Threshold concepts and threshold skills in computing

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9th Annual International Conference on International Computing Education Research, ICER 2012

作者： Sanders, Kate Boustedt, Jonas Eckerdal, Anna Mccartney, Robert Moström, Jan Erik Thomas, Lynda Zander, Carol Mathematics and Computer Science Department Rhode Island College Providence RI United States Faculty of Engineering and Sustainable Development University of Gävle Gävle Sweden Department of Information Technology Uppsala University Uppsala Sweden Department of Computer Science and Engineering University of Connecticut Storrs CT United States Department of Computing Science Umeå University 901 87 Umeå Sweden Department of Computer Science Aberystwyth University Aberystwyth United Kingdom Computing and Software Systems University of Washington Bothell WA United States

ISBN: (纸本)9781450316040

Threshold concepts can be used to both organize disciplinary knowledge and explain why students have difficulties at certain points in the curriculum. Threshold concepts transform a student's view of the discipline;before being learned, they can block a student's progress. In this paper, we propose that in computing, skills, in addition to concepts, can sometimes be thresholds. Some students report finding skills more difficult than concepts. We discuss some computing skills that may be thresholds and compare threshold skills and threshold concepts. Copyright 2012 ACM.

关键词： Students

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Self-directed learning: Stories from industry 12

Self-directed learning: Stories from industry

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12th Koli Calling International Conference on Computing Education Research, Koli Calling 2012

作者： Zander, Carol Boustedt, Jonas Eckerdal, Anna Mccartney, Robert Moström, Jan Erik Sanders, Kate Thomas, Lynda Computing and Software Systems University of Washington Bothell Bothell WA United States Faculty of Engineering and Sustainable Development University of Gävle Gävle Sweden Department of InformationTechnology Uppsala University Uppsala Sweden Department of Computer Science and Engineering University of Connecticut Storrs CT United States Department of Computing Science Umeå University 901 87 Umeå Sweden Mathematics and Computer Science Department Rhode Island College Providence RI United States Department of Computer Science Aberystwyth University Aberystwyth United Kingdom

ISBN: (纸本)9781450317955

We report preliminary results from an ongoing investigation of how computing professionals perceive and value selfdirected learning, based on a qualitative analysis of interviews with ten computing professionals. The professionals expect that future colleagues will have a well-developed ability to learn on their own. They indicate that professionals use a range of resources, strategies, and collaborators to help them learn. They find their work-related self-directed learning enjoyable, expressing a sense of confidence and pride;yet they often also find it to be a stressful never-ending process. Copyright 2012 ACM.

关键词： informal learning self-directed learning industry perspective

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'Permanent' algorithm for the meeting shedule problem 16

'Permanent' algorithm for the meeting shedule problem

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16th IEEE International Conference on computer science and Information Technologies, CSIT 2021

作者： Turbal, Yuriy Babych, Sergii Kunanets, Nataliia Melnyk, Leonid Pasichnyk, Volodymyr National University of Water and Environmental Engineering Department of Computer Science and Applied Mathematics Rivne Ukraine College of National University of Life and Environmental Sciences of Ukraine Software Engineering Rivne Ukraine National University 'Lviv Polytechnic' Department of Information Systems and Networks Lviv Ukraine National University of Water and Environmental Engineering Department of Finance and Economic Security Rivne Ukraine

ISBN: (纸本)9781665442572

An algorithm for solving the problem of scheduling meetings in the process of working on a project is proposed in the paper. The problem of project managers meetings with working groups is considered under certain restrictions., the possibility of a simultaneous meeting of the project manager with one or several project groups is considered. The proposed procedure for finding the permanent allows to build all possible combinations of the meeting schedule at a given time. The specificity of the proposed approach is the ability to take into account any number of additional conditions. © 2021 IEEE.

关键词： Managers

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A Hybrid Case Based Reasoning System Using Fuzzy-Rough Sets and Formal Concept Analysis

A Hybrid Case Based Reasoning System Using Fuzzy-Rough Sets ...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Jirapond Tadrat Veera Boonjing Puntip Pattaraintakorn Software Systems Engineering Laboratory Department of Mathematics and Computer Science King Mongkut''s Institute of Technology Ladkrabang Bangkok Thailand Department of Mathematics and Computer Science King Mongkut''s Institute of Technology Ladkrabang Bangkok Thailand

In this paper, we propose a new hybrid case based reasoning system based on rough set theory, formal concept analysis and fuzzy sets. This system applies rough set theory to assure minimally sufficient cases in its case base. It uses formal concept analysis to reveal knowledge of attribute dependencies in terms of concept lattices. Numeric attributes are transformed to be suitable for formal concept analysis using fuzzy sets.

关键词： Fuzzy sets mathematics computer science Set theory Lattices Information systems software systems systems engineering and theory Laboratories Rough sets

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Assertions in object oriented software maintenance: analysis and case study

Assertions in object oriented software maintenance: analysis...

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International Conference on software Maintenance (ICSM)

作者： M. Satpathy N.T. Siebel D. Rodriguez Applied Software Engineering Group Department of Computer Science University of Reading Reading UK COGNITIVE Systems Group Institute of Computer Science and Applied Mathematics Christian-Albrechts University Kiel Germany

Assertions had their origin in program verification. For the systems developed in industry, construction of assertions and their use in showing program correctness is a near-impossible task. However, they can be used to show that some key properties are satisfied during program execution. We first present a survey of the special roles that assertions can play in object oriented software construction. We then analyse such assertions by relating them to the case study of an automatic surveillance system. In particular, we address the following two issues: What types of assertions can be used most effectively in the context of object oriented software? How can you discover them and where should they be placed? During maintenance, both the design and the software are continuously changed. These changes can mean that the original assertions, if present, are no longer valid for the new software. Can we automatically derive assertions for the changed software?.

关键词： software maintenance computer aided software engineering

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Small sets of genuinely nonlocal Greenberger-Horne-Zeilinger states in multipartite systems

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Physical Review A 2024年第2期109卷 022428-022428页

作者： Zong-Xing Xiong Yongli Zhang Mao-Sheng Li Lvzhou Li Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-Sen University Guangzhou 510006 China School of Mathematics and Systems Science Guangdong Polytechnic Normal University Guangzhou 510665 China School of Mathematics South China University of Technology Guangzhou 510641 China

A set of orthogonal multipartite quantum states are called (distinguishability-based) genuinely nonlocal if they are locally indistinguishable across any bipartition of the subsystems. In this work, we consider the problem of constructing small genuinely nonlocal sets consisting of generalized Greenberger-Horne-Zeilinger (GHZ) states in multipartite systems. For system (C2)⊗N where N is large, using the language of group theory, we show that a tiny proportion Θ(1/2N) of the states among the N-qubit GHZ basis suffice to exhibit genuine nonlocality. Similar arguments also hold for the canonical generalized GHZ bases in systems (Cd)⊗N, wherever d is even and N is large. What is more, moving to the condition that any fixed N is given, we show that d+1 genuinely nonlocal generalized GHZ states exist in (Cd)⊗N, provided the local dimension d is sufficiently large. As an additional merit, within and beyond an asymptotic sense, the latter result also indicates some evident limitations of the “trivial othogonality-preserving local measurements” (TOPLM) technique that has been utilized frequently for detecting genuine nonlocality.

关键词： Nonlocality Quantum correlations in quantum information

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Efficient Privacy-Preserving ML for IoT: Cluster-Based Split Federated Learning Scheme for Non-IID Data 7

Efficient Privacy-Preserving ML for IoT: Cluster-Based Split...

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7th Cyber Security in Networking Conference, CSNet 2023

作者： Arafeh, Mohamad Wazzeh, Mohamad Ould-Slimane, Hakima Talhi, Chamseddine Mourad, Azzam Otrok, Hadi Department of Software and It Engineering Montreal Canada Department of Mathematics and Computer Science Canada New York University Division of Science Abu Dhabi United Arab Emirates Cyber Security Systems and Applied Ai Research Center Lebanese American University Department of Csm Beirut Lebanon Khalifa University Department of Eecs Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350342871

This paper proposes a scheme addressing the challenges of integrating privacy-preserving distributed machine learning in the Internet of Things (IoT) context while improving the efficiency of the learning process and accelerating the convergence of the model. Specifically, it addresses the presence of non-independent and identically distributed (Non-IID) data and device heterogeneity, which occurs during parallel training and are common characteristics of IoT environments. In this context, SplitFed is a privacy-preserving technique that combines Federated Learning (FL) and Split Learning (SL) to enable fast and privacy-preserving model training on IoT devices. Through parallelism, FL allows fast and parallel model training. Furthermore, SL enables weak devices to train models through model splitting. However, SplitFed suffers from the increasing convergence time due to the FL parallelism introducing Non-IID and stragglers issues. In this paper, we aim to address the aforementioned problems by proposing a clustering parallelization scheme. As such, similar clients are combined based on their weight divergence and considered a single FL unit addressing the Non-IID problem. Moreover, to improve time efficiency and overcome the stragglers' presence, we offer a second clustering stage that separates clients by efficiency and uses FedAsync for model aggregation. © 2023 IEEE.

关键词： Internet of things

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