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Boosting classification accuracy using an efficient stochastic optimization technique for feature selection in high-dimensional data

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Swarm and Evolutionary Computation 2025年 97卷

作者： Noureen Talpur Shoaib-ul Hassan Mohd Hafizul Afifi Abdullah Abdulrahman Aminu Ghali Ambreen Abdul Raheem Shazia Khatoon Norshakirah Aziz Sivashankari Alaganandham Centre for Research in Data Science (CeRDaS) Universiti Teknologi PETRONAS 32610 Seri Iskandar Perak Malaysia Faculty of Information and Communication Technology (FICT) Universiti Tunku Abdul Rahman 31900 Kampar Malaysia NED University of Engineering & Technology Karachi City 75500 Sindh Pakistan Iqra University Karachi City 75500 Sindh Pakistan Centre for Cyber-Physical Systems (C2PS) Universiti Teknologi PETRONAS 32610 Seri Iskandar Perak Malaysia Department of Computing and Information Systems Sunway University 47500 Bandar Sunway Selangor Malaysia

Many real-world problems involve a large number of features, among which several features are irrelevant or redundant. This problem not only increases the dimensionality but also reduces the classification performance of machine learning models. To address this issue, feature selection methods have been extensively used in the literature, either by applying existing algorithms or developing new algorithms. However, many of these approaches suffer from limitations such as insufficient feature reduction due to getting trapped in local minima in the large search space. Hence, this study proposed a recent stochastic optimization-based technique called the Osprey Optimization Algorithm (OOA). The OOA algorithm has the capability of balancing exploration and exploitation effectively during the search process, making it suitable for solving high-dimensional optimization tasks. To validate the efficiency of the selected feature subsets, the study employs the k -nearest neighbor ( k -NN) classifier. Comparative results between OOA and five state-of-the-art algorithms show that OOA achieves the highest average classification accuracy of 89.22 %, while selecting the fewest average features of 70.63 and reduces the feature burden by 62.80 %. Moreover, the results of a non-parametric Wilcoxon signed-rank test based on classification accuracy show a p -value less than 5.00E-02, confirming a statistically significant difference in performance among the six algorithms.

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Risk-Aware Control and Games in engineering

Risk-Aware Control and Games in Engineering

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IEEE Conference on Decision and Control

作者： Julian Barreiro-Gomez Hamidou Tembine Leonardo Stella Dario Bauso Patrizio Colaneri Learning & Game Theory Laboratory (L&G-Lab) and Center on Stability Instability and Turbulence (SITE) New York University Abu Dhabi (NYUAD) United Arab Emirates Faculty of Electronics Computing and Mathematics University of Derby United Kingdom Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen The Netherlands Università di Palermo Italy Politecnico di Milano Italy

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

We present a brief tutorial on risk-aware control and game theory applied to engineering problems by solving a backward-forward partial-integro differential system composed of the Hamilton-Jacobi-Bellman and Fokker-Planck coupled equations. First, we discuss about the role that risk terms play in the engineering field. Then, both the risk-aware control and game problems are stated and the computation of the corresponding solutions is presented. We mainly focus on a basic propagation regulation of the coronavirus disease by using mean-field-type control. Hence, we discuss other engineering applications that can be addressed by using the same riskaware perspective. Among such applications, we discuss about the electric vehicles, and the bio-inspired collective decision-making.

关键词： Games Game theory Economics COVID-19 Mathematical model Standards Statistics

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Correction to: An evaluation of the formalised AcciMap approach for accident analysis in healthcare

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Cognition, Technology & Work 2021年第1期24卷 209-209页

作者： Igene, Oseghale Osezua Johnson, Christopher W. Long, Jenny School of Computing Science University of Glasgow Glasgow United Kingdom Faculty of Engineering and Physical Sciences Queen’s University Belfast Belfast United Kingdom Unscheduled Care Improvement National Health Service Lothian Edinburgh United Kingdom

A correction to this paper has been published: https://***/10.1007/s10111-021-00676-x

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Mobility in MANET Using Robot: A Review 1st

Mobility in MANET Using Robot: A Review

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1st International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2018

作者： Muchtar, Farkhana Abdullah, Abdul Hanan Ahmmad, Siti Nor Zawani Kumar, Yugal Faculty of Computing Universiti Teknologi Malaysia SkudaiJohor81310 Malaysia School of Computer Sciences Universiti Sains Malaysia GelugorPenang11800 Malaysia Instrumentation and Control Engineering University Kuala Lumpur MITEC Persiaran Sinaran Ilmu Bandar Seri Alam MasaiJohor81750 Malaysia Department of Science and Engineering and Information Technology Jaypee University of Information Technology Waknaghat SolanHimachal Pradesh173234 India

ISBN: (纸本)9789811338038

Recently, MANET (Mobile Ad Hoc Network) researchers have shown increased interest towards using mobile robot technology for their testbed platforms. Despite the existence of articles that discuss the usage of mobile robot technology pertaining to MANET testbed from the perspective of MANET researcher, the discussion provided in the papers are rather lacklustre as it is not the sole purpose of those articles. Hence, this review aims to discuss MANET testbeds that were facilitated with mobile robot technology from previous undertaken researches. With the wealth of information provided in this paper, it is hoped that this paper will be the ultimate source of reference for other MANET researchers who need to choose the most suitable mobile robots with real mobility in their MANET testbeds. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Mobile robots

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NTIRE 2023 Quality Assessment of Video Enhancement Challenge

arXiv

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arXiv 2023年

作者： Liu, Xiaohong Min, Xiongkuo Sun, Wei Zhang, Yulun Zhang, Kai Timofte, Radu Zhai, Guangtao Gao, Yixuan Cao, Yuqin Kou, Tengchuan Dong, Yunlong Jia, Ziheng Li, Yilin Wu, Wei Hu, Shuming Deng, Sibin Xiao, Pengxiang Chen, Ying Li, Kai Zhao, Kai Yuan, Kun Sun, Ming Cong, Heng Wang, Hao Fu, Lingzhi Zhang, Yusheng Zhang, Rongyu Shi, Hang Xu, Qihang Xiao, Longan Ma, Zhiliang Agarla, Mirko Celona, Luigi Rota, Claudio Schettini, Raimondo Huang, Zhiwei Li, Yanan Wang, Xiaotao Lei, Lei Liu, Hongye Hong, Wei Chuang, Ironhead Lin, Allen Guan, Drake Chen, Iris Lou, Kae Huang, Willy Tasi, Yachun Kao, Yvonne Fan, Haotian Kong, Fangyuan Zhou, Shiqi Liu, Hao Lai, Yu Chen, Shanshan Wang, Wenqi Wu, Haoning Chen, Chaofeng Zhu, Chunzheng Guo, Zekun Zhao, Shiling Yin, Haibing Wang, Hongkui Meftah, Hanene Brachemi Fezza, Sid Ahmed Hamidouche, Wassim Déforges, Olivier Shi, Tengfei Mansouri, Azadeh Motamednia, Hossein Bakhtiari, Amir Hossein Aznaveh, Ahmad Mahmoudi Shanghai Jiao Tong University China ETH Zürich Switzerland University of Würzburg Germany Department of Tao Technology Alibaba Group China Kuaishou Technology China Interactive Entertainment Group of Netease Inc Guangzhou China Transsion China Vrobotit Lab Beijing University of Posts and Telecommunications China Hefei University of Technology China Department of Informatics Systems and Communication University of Milano - Bicocca Italy Xiaomi Inc. China China Ji Liang University China FreeTech China Advanced Research Center KKCompany Taiwan ByteDance China MGTV China Fuzhou University China Shopee Information Technology Co. Ltd. China S-Lab Nanyang Technological University Singapore Hunan University China Hangzhou Dianzi University China INSA Rennes CNRS IETR - UMR 6164 Rennes France National Higher School of Telecommunications and ICT Oran Algeria BUAA China Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Cyberspace Research Institute Shahid Beheshti University Tehran Iran

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2023. This challenge is to address a major challenge in the field of video processing, namely, video quality assessment (VQA) for enhanced videos. The challenge uses the VQA Dataset for Perceptual Video Enhancement (VDPVE), which has a total of 1211 enhanced videos, including 600 videos with color, brightness, and contrast enhancements, 310 videos with deblurring, and 301 deshaked videos. The challenge has a total of 167 registered participants. 61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions. A total of 176 submissions were submitted by 37 participating teams during the final testing phase. Finally, 19 participating teams submitted their models and fact sheets, and detailed the methods they used. Some methods have achieved better results than baseline methods, and the winning methods have demonstrated superior prediction performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

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Author Correction: Sub-femtonewton force sensing in solution by super-resolved photonic force microscopy

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Nature Photonics 2024年 998页

作者： Xuchen Shan Dajing Wang Jinlong Shi Hongyan Zhu Xiaolan Zhong Baolei Liu Weichang Hao Fan Wang Lei Ding Qian Peter Su Shihui Wen Dayong Jin Lei Jiang Chaohao Chen Yang Wang Zhaocun Huang Lingqian Chang Shen S. J. Wang Peter John Reece Wei Ren Xunyu Lu Jie Lu Lingdong Sun School of Physics Beihang University Beijing People’s Republic of China Science and Technology Center for Quantum Biology National Institute of Extremely-Weak Magnetic Field Infrastructure Hangzhou People’s Republic of China School of Biomedical Engineering Faculty of Engineering and Information Technology University of Technology Sydney Sydney New South Wales Australia Centre for Atomaterials and Nanomanufacturing School of Science RMIT University Melbourne Victoria Australia Institute for Biomedical Materials and Devices (IBMD) School of Mathematical and Physical Sciences Faculty of Science University of Technology Sydney Sydney New South Wales Australia Eastern Institute for Advanced Study Eastern Institute of Technology Ningbo People’s Republic of China Key Laboratory of Bio-Inspired Materials and Interfaces Sciences Technical Institute of Physics and Chemistry Chinese Academy of Sciences Beijing People’s Republic of China Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems Department of Electronic Materials Engineering Research School of Physics The Australian National University Canberra Australian Capital Territory Australia Key Laboratory of Biomechanics and Mechanobiology (Ministry of Education) Beijing Advanced Innovation Center for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing People’s Republic of China Computing and Information Systems Department Melbourne School of Engineering University of Melbourne Melbourne Victoria Australia School of Physics The University of New South Wales Sydney New South Wales Australia School of Chemistry & Chemical Engineering Shaanxi Normal University Xi’an People’s Republic of China Particles and Catalysis Research Laboratory School of Chemical Engineering The University of New South Wales Sydney New South Wales Australia Australian Artificial Intelligence Institute Faculty of Engineering and IT University of Technology

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Fabrication of acrylic hydrogel incorporated with magnetic nanoparticles and its physical and thermal properties

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AIP Conference Proceedings 2020年第1期2233卷

作者： Jong Hui Li Nozieana Khairuddin Md Bazlul Mobin Siddique Department of Chemical Engineering and Science Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Campus 93500 Kuching Sarawak Malaysia Department of Engineering Faculty of Agriculture Science and Technology Universiti Putra Malaysia Bintulu Sarawak Campus 97008 Bintulu Sarawak Malaysia

In this research, acrylic acid based hydrogels were prepared and impregnated with magnetic nanoparticles to enhance the efficiency of the adsorption and desorption of heavy metals. Acrylic acid and itaconic acid both are short chain and possess -COOH group, therefore, they are easily copolymerized and hydrophilic in nature. The acrylic based hydrogel acts as a support to hold the magnetic nanoparticles. Hydrogels were synthesized by using acrylic acid and itaconic acid as monomers at different monomer ratios. The magnetic particles were incorporated through in situ precipitation method by immersing into 0.25 M Fe (II) and 0.5 M Fe (III) ion aqueous solutions in the molar ratio of 1:2 for metal ions loading. The swelling behaviour of the plain acylic acid hydrogel and plain acrylic acid-co-itaconic acid hydrogel that were soaked in two different water solutions such as sea water and distilled water were studied. Result shows that plain acrylic acid-co-itaconic acid hydrogel has the tendency to swell more than plain acrylic acid hydrogel. The absorption and desorption capacity of the materials were tested in 0.1 M of cobalt and lead solutions. The materials show promising results and can be used to remove pollutants from industrial effluent.

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V1294 Aql = HD 184279: A bad boy among Be stars or an important clue to the Be phenomenon?

arXiv

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arXiv 2022年

作者： Harmanec, Petr Božić, H. Koubský, P. Yang, S. Ruždjak, D. Sudar, D. Šlechta, M. Wolf, M. Korčáková, D. Zasche, P. Oplištilová, A. Vršnak, D. Ak, H. Eenens, P. Bakiş, H. Bakiş, V. Otero, S. Chini, R. Demsky, T. Barlow, B.N. Svoboda, P. Jonák, J. Vitovský, K. Harmanec, A. Astronomical Institute of Charles University Faculty of Mathematics and Physics V Holešovičkách 2 - Troja Praha 8CZ-180 00 Czech Republic Hvar Observatory Faculty of Geodesy University of Zagreb Kačićeva 26 Zagreb10000 Croatia Astronomical Institute Czech Academy of Sciences OndřejovCZ-251 65 Czech Republic Physics & Astronomy Department University of Victoria PO Box 3055 STN CSC VictoriaBCV8W 3P6 Canada Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 Zagreb10000 Croatia Astronomy and Space Sci. Dept. Science Faculty Erciyes University Kayseri38039 Turkey Dept. of Astronomy University of Guanajuato GTO Guanajuato36000 Mexico Dept. of Space Sciences and Technology Akdeniz University Antalya07058 Turkey 49 Bay State Road CambridgeMA02138 United States Astronomisches Institut Ruhr–Universität Bochum Universitätsstr. 150 Bochum44801 Germany Instituto de Astronomía Universidad Católica del Norte Avenida Angamos 0610 Casilla Antofagasta1280 Chile Department of Physics High Point University One University Way High PointNC27268 United States Private Observatory Vypustky 5 BrnoCZ-614 00 Czech Republic Faculty of Mathematics and Physics Charles University Prague Czech Republic

A reliable determination of the basic physical properties and variability patterns of hot emission-line stars is important for understanding the Be phenomenon and ultimately, the evolutionary stage of Be stars. This study is devoted to one of the most remarkable Be stars, V1294 Aql = HD 184279. We collected and analysed spectroscopic and photometric observations covering a time interval of about 25000 d (68 yr). We present evidence that the object is a single-line 192.9 d spectroscopic binary and estimate that the secondary probably is a hot compact object with a mass of about 1.1-1.2 M . We found and documented very complicated orbital and long-term spectral, light, and colour variations, which must arise from a combination of several distinct variability patterns. Attempts at modelling them are planned for a follow-up study. We place the time behaviour of V1294 Aql into context with variations known for some other systematically studied Be stars and discuss the current ideas about the nature of the Be phenomenon. © 2022, CC BY.

关键词： Stars

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人工智能赋能癌症免疫治疗——创新探索与未来机遇（英文）

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engineering 2025年第1期 12-16页

作者： Wei Xiang Lu Yu Xiaoyuan Chen Marco J.Herold Australian Centre for Artificial Intelligence in Medical Innovation La Trobe University School of Computing Engineering and Mathematical Sciences La Trobe University Department of Diagnostic Radiology Yong Loo Lin School of Medicine National University of Singapore Department of Chemical and Biomolecular Engineering College of Design and Engineering National University of Singapore Department of Biomedical Engineering College of Design and Engineering National University of Singapore Department of Pharmacy and Pharmaceutical Sciences Faculty of Science National University of Singapore Clinical Imaging Research Centre Centre for Translational Medicine Yong Loo Lin School of Medicine National University of Singapore Nanomedicine Translational Research Program Yong Loo Lin School of Medicine National University of Singapore Theranostics Center of Excellence(TCE) Yong Loo Lin School of Medicine National University of Singapore Institute of Molecular and Cell Biology Agency for Science Technology and Research(A*STAR) Olivia Newton-John Cancer Research Institute School of Cancer Medicine La Trobe University The Walter and Eliza Hall Institute of Medical Research Department of Medical Biology University of Melbourne

1. Introduction Cancer continues to be a major cause of global mortality rates, with conventional treatments such as chemotherapy and radiotherapy exhibiting inconsistent efficacy, high costs, and considerable side effects. Over the past decade, a promising alternative has emerged: cancer immunotherapy, which leverages the body's immune system to identify and eradicate cancer cells [1].

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Sp(2N) Yang-Mills theories on the lattice: scale setting and topology

arXiv

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arXiv 2022年

作者： Bennett, Ed Hong, Deog Ki Lee, Jong-Wan Lin, C.-J. David Lucini, Biagio Piai, Maurizio Vadacchino, Davide Swansea Academy of Advanced Computing Swansea University Fabian Way Swansea WalesSA1 8EN United Kingdom Department of Physics Pusan National University Busan46241 Korea Republic of Institute for Extreme Physics Pusan National University Busan46241 Korea Republic of Institute of Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Center for High Energy Physics Chung-Yuan Christian University Chung-Li32023 Taiwan Centre for Theoretical and Computational Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Physics Division National Centre for Theoretical Sciences Taipei10617 Taiwan Department of Mathematics Faculty of Science and Engineering Swansea University Fabian Way Swansea WalesSA1 8EN United Kingdom Department of Physics Faculty of Science and Engineering Swansea University Singleton Park Swansea WalesSA2 8PP United Kingdom School of Mathematics Hamilton Mathematics Institute Trinity College Dublin 2 Ireland Centre for Mathematical Sciences University of Plymouth PlymouthPL4 8AA United Kingdom

We study Yang-Mills lattice theories with Sp(Nc) gauge group, with Nc = 2N, for N = 1, ···, 4. We show that if we divide the renormalised couplings appearing in the Wilson flow by the quadratic Casimir C2(F) of the Sp(Nc) group, then the resulting quantities display a good agreement among all values of Nc considered, over a finite interval in flow time. We use this scaled version of the Wilson flow as a scale-setting procedure, compute the topological susceptibility of the Sp(Nc) theories, and extrapolate the results to the continuum limit for each Nc. © 2022, CC BY.

关键词： Lattice theory

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