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Asia International Conference on Modeling & Simulation

作者： Mohd Saberi Mohamad Sigeru Omatu Michifumi Yoshioka Safaai Deris Department of Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University Sakai Japan Department of Software Engineering Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia Skudai Johor Malaysia

Recent advances in microarray technology allow scientists to measure expression levels of thousands of genes simultaneously in human tissue samples. This technology has been increasingly used in cancer research because of its potential for classification of the tissue samples based only on gene expression levels. A major problem in these microarray data is that the number of genes greatly exceeds the number of tissue samples. Moreover, these data have a noisy nature. It has been shown from literature review that selecting a small subset of informative genes can lead to an improved classification accuracy. Thus, this paper aims to select a small subset of informative genes that is most relevant for the cancer classification. To achieve this aim, an approach using two hybrid methods has been proposed. This approach is assessed on two well-known microarray data. The experimental results have shown that the gene subsets are very small in size and yield better classification accuracy as compared with other previous works as well as four methods experimented in this work. In addition, a list of informative genes in the best subsets is also presented for biological usage.

关键词： Cancer Gene expression Tumors computer science Genetic mutations Asia Computational modeling computer simulation Hybrid intelligent systems Data engineering

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Opinion dynamics with backfire effect and biased assimilation

arXiv

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arXiv 2019年

作者： Chen, Xi Tsaparas, Panayiotis Lijffijt, Jefrey de Bie, Tijl Dept. of Electronics and Information Systems IDLab Ghent University Department of Computer Science and Engineering University of Ioannina

The democratization of AI tools for content generation, combined with unrestricted access to mass media for all (e.g. through microblogging and social media), makes it increasingly hard for people to distinguish fact from fiction. This raises the question of how individual opinions evolve in such a networked environment without grounding in a known reality. The dominant approach to studying this problem uses simple models from the social sciences on how individuals change their opinions when exposed to their social neighborhood, and applies them on large social networks. We propose a novel model that incorporates two known social phenomena: (i) Biased Assimilation: the tendency of individuals to adopt other opinions if they are similar to their own;(ii) Backfire Effect: the fact that an opposite opinion may further entrench someone in their stance, making their opinion more extreme instead of moderating it. To the best of our knowledge this is the first model that captures the Backfire Effect. A thorough theoretical and empirical analysis of the proposed model reveals intuitive conditions for polarization and consensus to exist, as well as the properties of the resulting opinions. Copyright © 2019, The Authors. All rights reserved.

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Fast Fourier-Galerkin methods for first-kind logarithmic-kernel integral equations on open arcs

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science China Mathematics 2010年第1期53卷 1-22页

作者： WANG Bo1,WANG Rui2 & XU YueSheng3,4,1Academy of Mathematics and systems science,Chinese Academy of sciences,Beijing 100190,China 2School of information science and engineering,Graduate University of the Chinese Academy of sciences,Beijing 100190,China 3Department of Mathematics,Syracuse University,Syracuse,NY 13244,USA 4Department of Scientific Computing and computer Applications,Sun Yat-sen University,Guangzhou 510275,China 1. Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China2. School of Information Science and Engineering Graduate University of the Chinese Academy of Sciences Beijing 100190 China3. Department of Mathematics Syracuse University Syracuse NY 13244 USA4. Department of Scientific Computing and Computer Applications Sun Yat-sen University Guangzhou 510275 China

We propose a fully discrete fast Fourier-Galerkin method for solving an integral equation of the first kind with a logarithmic kernel on a smooth open arc,which is a reformulation of the Dirichlet problem of the Laplace equation in the *** optimal convergence order and quasi-linear complexity order of the proposed method are established.A precondition is *** this method with an efficient numerical integration algorithm for computing the single-layer potential defined on an open arc,we obtain the solution of the Dirichlet problem on a smooth open arc in the *** examples are presented to confirm the theoretical estimates and to demonstrate the efficiency and accuracy of the proposed method.

关键词： Dirichlet problem open arc singular boundary integral equations Fourier-Galerkin methods logarithmic potentials

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The System Adoption Evaluation of RFID Safety Management System on Campus

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International Journal of Network Security 2022年第1期24卷 176-180页

作者： Hsieh, Yu-Ying Chang, Liang-Hsu Liao, Anthony Y. H. Yang, Cheng-Ying Hwang, Min-Shiang Department of Computer Science and Information Engineering Asia University No. 500 Lioufeng Rd. Taichung41354 Taiwan Department of Management Information Systems National Chung Hsing University Taichung403 Taiwan Department of M-Commerce and Multimedia Applications Asia University Taipei10048 Taiwan Department of Computer Science University of Taipei Taipei10048 Taiwan Department of Medical Research China Medical University Hospital China Medical University No. 91 Xueshi Rd. Taichung40402 Taiwan

In this article, we propose a campus safety management system based on radio frequency identification (RFID) technology. In this work, the evaluation based on the system adoption was used to establish a campus-safety management system model and related implementation issues. With the implementation of the RFID system for campus safety management, the system could save the administrators’ time and improve the efficiency of service quality. In addition, it helps to prevent the occurrence of security incidents on campus. The critical success factors of the system include the participation of students and parents. Finally, the evaluation on the system adoption is made by questioners. The results show the first three factors affecting the administrators in the school to decide whether the system is used the convenience of use, agreement of students’ parents, and the relative advantage. However, school competition and school reorganization could not be the preferred factors to adopt the system. © 2022. All Rights Reserved.

关键词： Radio frequency identification (RFID)

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Application of intelligence-based computational techniques for classification and early differential diagnosis of COVID-19 disease

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Data science and Management 2021年第4期4卷 10-18页

作者： Boluwaji A.Akinnuwesi Stephen G.Fashoto Elliot Mbunge Adedoyin Odumabo Andile S.Metfula Petros Mashwama Faith-Michael Uzoka Olumide Owolabi Moses Okpeku Oluwaseun O.Amusa Department of Computer Science Faculty of Science and EngineeringUniversity of Eswatini(Formerly University of Swaziland)Kwaluseni M201ManziniEswatiniSwaziland Department of Computer Science Faculty of ScienceLagos State UniversityOjoLagos State102105Nigeria Department of Computer Science and Information Systems Mount Royal UniversityCalgaryAlbertaT3E6K6Canada Department of Computer Science University of Abuja900105Nigeria Department of Genetics University of KwaZulu-Natal4041South Africa Department of English Studies Faculty of ArtsAdekunle Ajasin UniversityAkungba-AkokoOndo State342111Nigeria

Clinical methods are used for diagnosing COVID-19 infected patients,but reports posit that,several people who were initially tested positive of COVID-19,and who had some underlying diseases,turned out having negative results after further ***,the performance of clinical methods is not always ***,chest X-ray image data of COVID-19 infected patients are mostly used in the computational models for COVID-19 diagnosis,while the use of common symptoms,such as fever,cough,fatigue,muscle aches,headache,*** computational models is not yet *** this study,we employed seven classification algorithms to empirically test and verify their efficacy when applied to diagnose COVID-19 using the aforementioned *** experimented with Logistic Regression(LR),Support Vector Machine(SVM),Naïve Byes(NB),Decision Tree(DT),Multilayer Perceptron(MLP),Fuzzy Cognitive Map(FCM)and Deep Neural Network(DNN)*** techniques were subjected to random undersampling and *** results showed that with class imbalance,MLP and DNN outperform ***,without class imbalance,MLP,FCM and DNN outperform others with the use of random undersampling,but DNN has the best performance by utilizing random *** study identified MLP,FCM and DNN as better classifiers over LR,NB,DT and SVM,so that healthcare software system developers can adopt them to develop intelligence-based expert systems which both medical personnel and patients can use for differential diagnosis of COVID-19 based on the aforementioned ***,the test of performance must not be limited to the traditional performance metrics.

关键词： COVID-19 Coronavirus Machine Learning Intelligent classifier Early differential diagnosis Deep Learning

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Polarization-controlled dual resonant lattice Kerker effects

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Nano Research 2023年第2期16卷 3195-3200页

作者： Lei Xiong Xueqian Zhao Xiang Du Shuai Chen Yuanfu Lu Hongwei Ding Guangyuan Li School of Information Science and Engineering Yunnan UniversityKunming 650500China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China School of Computer Electronic and InformationGuangxi UniversityNanning 530004China College of Physics and Electronic Technology Anhui Normal UniversityWuhu 241000China Tianjin H-Chip Technology Group Corporation Tianjin 300467China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for SocietyShenzhen 518055China

The generalized Kerker effects have attracted increasing interests in recent years due to their abilities to manipulate the far-field properties of ***,the dual-polarized generalized Kerker effect enabling different tailoring of orthogonally-polarized electromagnetic waves has not yet been ***,we demonstrate polarization-controlled dual resonant lattice Kerker effects in periodic silicon *** varying the incident angle,the electric dipole and magnetic dipole surface lattice resonances can spectrally overlap,causing zero reflectance and unitary transmittance,i.e.,the resonant lattice Kerker *** incident angle for achieving this effect can be tuned differently for s-and p-polarizations over large regions by varying the nanodisk size or the lattice *** proposed dual-polarized resonant lattice Kerker effects open up avenues for polarization-controlled manipulation of the phase and wavefront of light with metasurfaces.

关键词： Kerker effect surface lattice resonances dual-polarized silicon metasurface

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An Efficient Node Partitioning Algorithm for the Capacitated Minimum Spanning Tree Problem

An Efficient Node Partitioning Algorithm for the Capacitated...

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International Conference on computer and information science (ACIS)

作者： Jun Han Zhaohao Sun Jinpeng Huai Xian Li School of Computer Science & Engineering Beihang University China School of Economics and Information Systems University of Wollongong Australia

This paper studies the capacitated minimum spanning tree (CMST) problem, which is one of the most fundamental and significant problems in the optimal design of communication networks. A solution method using combined neighborhood search and branch and bound technique is introduced and its performance is presented. The advantage of the algorithm is shown while the process of searching for the optimal solution is illustrated. Computational experiences demonstrate that the proposed strategy significantly improves the efficiency of the previous node-orientated branch and bound algorithm.

关键词： Partitioning algorithms Costs Tree graphs Communication networks Sun computer science Design engineering information systems Algorithm design and analysis Mixed integer linear programming

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Study of the effects of soil physical and fertility factors on rice yield in taiwan area based on statistical, decision tree and association rule methods

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9th FTRA InternationalConference on Future information Technology, FutureTech 2014

作者： Tseng, Kuo-Jin Tsai, Meng-Hsiun Wang, Hsin-Lung Wu, Teng-Yen Department of Environmental Sciences National Chung Hsing University Taichung City Taiwan Department of Management Information Systems Institute of Genomics and Bioinformatics National Chung Hsing University Taichung City Taiwan Department of Computer Science and Information Engineering HungKuang University Taichung City Taiwan Microprogram Information Co. LTD Taichung City Taiwan

ISBN: (纸本)9783642550379

This paper used statistical, decision tree and association rule to research the effect of the reduction potential and bulk density and other soil factors to the production of rice. We finding the Non-exchangeable K., changeable K. Organic Matter and bulk density these factors effected the production of rice. © 2014 Springer-Verlag Berlin Heidelberg.

关键词： Association rules

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Real-time behavior recognition of animal: an IoT-based system design using acceleration data

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Multimedia Tools and Applications 2024年 1-26页

作者： Tran, Duc-Nghia Manh, Do Viet Van Thanh, Pham Shankar, A. Achyut Joshi, Kireet Tran, Duc-Tan Institute of Information Technology Vietnam Academy of Science and Technology Hanoi Viet Nam University of Fire Prevention and Fighting Hanoi100000 Viet Nam Department of Cyber Systems Engineering WMG University of Warwick CoventryCV74AL United Kingdom Department of CSE University Centre for Research & ampDevelopment Chandigarh University Punjab Mohali140413 India School of Computer Science Engineering Lovely Professional University Punjab Phagwara144411 India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun248002 India Center of Research Impact and Outcome Chitkara University Punjab Chandigarh India Department of Computer Science & amp Engineering Graphic Era Deemed to be University Uttarakhand Dehradun248002 India Faculty of Electrical and Electronic Engineering Phenikaa University Hanoi12116 Viet Nam

By analyzing large amounts of animal behavior data, humans can assess cattle’s condition. It leads to research and development a field using accelerometers and machine learning algorithms to ‘study’ behavior from acceleration data. It is challenging to analyze animal behavior due to the activity complexity. For example, acceleration data of some cow behaviors (e.g., feeding and standing) are similar if these behaviors contain similar gestures. In practical, real-time applications even bring more challenging since it is necessary to minimize a data window for behavior consideration. Using short data window often reduces the performance of classification algorithms. This study proposes a new solution for the mentioned challenges by combining neck-mounted and leg-mounted accelerometers, then using the vector of the dynamic body acceleration (VeDBA) and Mean features of synchronized acceleration data for the Decision Tree algorithm. The proposed method is demonstrated that performs well (0.94 accuracy, 0.91 sensitivity, 0.90 positive predictive value) within a low computational complexity algorithm and short data window (3-second data window, at the rate of one sample per second). It is particularly suited for the case of a real-time IoT-based system. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Accelerometers

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SkyCell: A space-pruning based parallel skyline algorithm

arXiv

引用

arXiv 2021年

作者： Li, Chuanwen Gu, Yu Qi, Jianzhong Yu, Ge College of Computer Science and Engineering Northeastern University China School of Computing and Information Systems The University of Melbourne Australia

Skyline computation is an essential database operation that has many applications in multi-criteria decision making scenarios such as recommender systems. Existing algorithms have focused on checking point domination, which lack efficiency over large datasets. We propose a grid-based structure that enables grid cell domination checks. We show that only a small constant number of cells need to be checked which is independent from the number of data points. Our structure also enables parallel processing. We thus obtain a highly efficient parallel skyline algorithm named SkyCell, taking advantage of the parallelization power of graphics processing units. Experimental results confirm the effectiveness and efficiency of SkyCell – it outperforms state-of-the-art algorithms consistently and by up to over two orders of magnitude in the computation time. © 2021, CC BY-NC-ND.

关键词： Large dataset

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