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Nearest-Better Network for Fitness Landscape Analysis of Continuous Optimization Problems

IEEE Transactions on Evolutionary Computation 2024年

作者： Diao, Yiya Li, Changhe Zeng, Sanyou Yang, Shengxiang Coello, Carlos A. Coello China University of Geosciences School of Automation Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Anhui University of Sciences and Technology School of Artificial Intelligence Hefei China China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan China De Montfort University School of Computer Science and Informatics LeicesterLE1 9BH United Kingdom Department of Computer Science CINVESTAV-IPN 07360 Mexico Tecnologico de Monterrey Faculty of Excellence The School of Engineering and Sciences N.L. Monterrey Mexico

Fitness landscape analysis (FLA) is quite important in evolutionary computation. In this paper, we propose a novel FLA method, the nearest-better network (NBN), which uses the nearest-better relationship to simplify the original fitness landscape of continuous optimization problems. We introduce an efficient algorithm to calculate NBN for continuous problems. We also propose four numerical measurements and a 3D visualization method based on NBN. Experiments show that compared to the other main FLA methods, the four numerical measurements proposed here can effectively measure the four intended features: neutrality, ruggedness, modality, and basin of attraction, respectively, and common features of the fitness landscape can be maintained in 3D NBN visualization, regardless of the scale of the problem. NBN also provides a view of how algorithms search in high-dimensional problems with the help of the 3D NBN visualization. © 1997-2012 IEEE.

关键词： Optimization algorithms

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Single trial ERP amplitudes reveal the time course of acquiring representations of novel faces in individual participants

arXiv

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arXiv 2020年

作者： Sommer, Werner Stapor, Katarzyna Kończak, Grzegorz Kotowski, Krzysztof Fabian, Piotr Ochab, Jeremi Bereś, Anna Ślusarczyk, Grażyna Humboldt-University at Berlin Department of Psychology Germany Silesian University of Technology Institute of Computer Science Gliwice Poland University of Economics in Katowice Department of Statistics Econometrics and Mathematics Poland Silesian University of Technology Department of Applied Informatics Gliwice Poland Silesian University of Technology Department of Algorithmics and Software Gliwice Poland Jagiellonian University Department of Theory of Complex Systems Krakow Poland Jagiellonian University Department of Cognitive Neuroscience and Neuroergonomics Krakow Poland Jagiellonian University Department of Design and Computer Graphics Krakow Poland Institut für Psychologie Humboldt-Universität zu Berlin Rudower Chaussee 18 Berlin12489 Germany Faculty of Automatic Control Electronics and Computer Science Department of Applied Informatics Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

The neural correlates of face individuation – the acquisition of memory representations for novel faces – have been studied only in coarse detail and disregarding individual differences between learners. In their seminal study, (Tanaka, Curran, Porterfield, & Collins, 2006) required the identification of a particular novel face across 70 trials and found that the N250 component in the ERP became more negative from the first to the second half of the experiment, where it reached a similar amplitude as a well-known face. We were unable to directly replicate this finding in our study when we used the original spilt of trials. However, when we applied a different split of trials we observed very similar changes in N250 amplitude. Then, we developed and applied a new two-step explorative-confirmative non-parametric method based on permutation testing to determine the time course of face individuation in individual participants based on single trial N250 amplitudes. We show that the assumption of a steep initial increase of N250 amplitude across multiple presentations of the target face, followed by a plateau, yields plausible results in fitting linear trends for most participants. The transition point from initial acquisition to the plateau phase differed strongly between participants and tended to be earlier when performance in target face recognition was better. Hence, face individuation may be accounted for by a biphasic process of early, fast acquisition, followed by a slower, asymptotic consolidation or maintenance phase. The current approach might be fruitfully applied to further investigations into face individuation and their neural correlates. © 2020, CC BY-NC-ND.

关键词： Face recognition

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Electronic Funds Transfer: control Issues in a Cashless, Checkless Society

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EDPACS 2006年第9期27卷 1-7页

作者： Loida Tison-dualan Frederick Gallegos Tison-Dualan is a senior IS audit analyst at Pricewaterhouse Coopers in San Francisco. Before assuming this position she worked on ARCO's SAP implementation team as a senior analyst. Tison-Dualan has more than 12 years' experience in IS audit and control. She received her masters of science in business administration degree (option: IS auditing) from California State Polytechnic University in Pomona and has passed the CISA exam. The MSBA-IS audit advisor and a faculty member of the Computer Information Systems Department of California State Polytechnic University in Pomona. He has more than 28 years' experience in IS audit and control. Gallegos has taught for 25 years in this field at the academic and professional level and has published three books and more than 150 articles in the IS field.

Electronic funds transfer (EFT)is a complex payment network that provides an alternative to the use of checks and currency as a payment method. Financial transactions can be executed in this environment by means of el...

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Eight Become One: the EURECA-PRO University Network

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BHM Berg- und Huttenmannische Monatshefte 2022年第10期167卷 462-471页

作者： Kircher, Volkmar Feiel, Susanne Bongaerts, Jan C. Sishchuk, Julia Drebenstedt, Carsten Lagoudakis, Michail Fragkedaki, Konstantina García-Llamas, Paula Suárez-Corona, Adriana Fernández-Raga, María Baelo-Álvarez, Roberto Górski, Marcin Pawelczyk, Marek Hochstein, Synnöve Walter, Stefanie Speck, Maria Ravas, Oana Van Hellemont, Elke Vancauwenbergh, Sadia Resources Innovation Center Leoben Montanuniversität Leoben Leoben Austria Public Relations Office International Relations and University Cooperation Montanuniversität Leoben Leoben Austria Faculty of Business Administration Technische Universität Bergakademie Freiberg Freiberg Germany EURECA-PRO Head of work package education and studies Technische Universität Bergakademie Freiberg Freiberg Germany EURECA-PRO Head of educational council Technische Universität Bergakademie Freiberg Freiberg Germany School of Electrical and Computer Engineering Technical University of Crete Chania Greece EURECA-PRO European University Technical University of Crete Chania Greece Department of General and Specific Didactics and Educational Theory University of León Leon24071 Spain Department of Mathematical Sciences Universidad de León León24071 Spain Department of Applied Physics University of León León24071 Spain Faculty of Civil Engineering Silesian University of Technology Gliwice Poland Department of Measurements and Control Systems Silesian University of Technology Gliwice Poland Fakultät Medien Hochschule Mittweida Mittweida Germany International Relation Office University of Petroşani Petroşani Romania Rector’s Office Hasselt University Hasselt Belgium Directorate Research Library and Internationalisation Hasselt University Hasselt Belgium

The United Nations Sustainable Development Goal 12 is the foundation of the European University on Responsible Consumption and Production consortium (EURECA-PRO). This article introduces the eight EURECA-PRO partner universities: Montanuniversität Leoben (Austria), Technische Universität Bergakademie Freiberg (Germany), Technical University of Crete (Greece), University of León (Spain), Silesian University of Technology (Poland), Mittweida University of Applied Sciences (Germany), University of Petroşani (Romania), and Hasselt University (Belgium). In addition, each university’s role within the alliance and unique research and study programmes are outlined. The synergy created by EURECA-PRO enables the pursuit of an ambitious research agenda with five research "Lighthouse Missions" as well as the implementation of joint study programmes. © 2022, The Author(s).

关键词： Sustainable development

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Generalization of the Self-Shrinking Generator in the Galois Field GF(pn)

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Advances in Artificial Intelligence 2011年第1期2011卷

作者： Antoniya Todorova Tasheva Zhaneta Nikolova Tasheva Aleksandar Petrov Milev Computer Systems Department Faculty of Computer Systems and Control Technical University of Sofia 8 Kliment Ohridski Street Sofia 1000 Bulgariatu-sofia.bg Communication and Computer Technique Department National Military University “Vasil Levski” 1a Karel Shkorpil Street Shumen 9701 Bulgarianvu.bg Computer System and Technology Department University of Shumen “Bishop Konstantin Preslavsky” 115 Universitetska Street Shumen 9712 ***

The proposed by Meier and Staffelbach Self-Shrinking Generator (SSG) which has efficient hardware implementation only with a single Linear Feedback Shift Register is suitable for low-cost and fast stream cipher applications. In this paper we generalize the idea of the SSG for arbitrary Galois Field GF( p n ). The proposed variant of the SSG is called the p -ary Generalized Self-Shrinking Generator (pGSSG). We suggest a method for transformation of a non-binary self-shrunken pGSSG sequence into balanced binary sequence. We prove that the keystreams of the pGSSG have large period and good statistical properties. The analysis of the experimental results shows that the pGSSG sequences have good randomness properties. We examine the complexity of exhaustive search and entropy attacks of the pGSSG. We show that the pGSSG is more secure than SSG and Modified SSG against these attacks. We prove that the complexity of the used pGSSG attacks increases with increasing the prime p . Previously mentioned properties give the reason to say that the pGSSG satisfy the basic security requirements for a stream chipper and can be useful as a part of modern stream ciphers.

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Random asynchronous iterations in distributed coordination algorithms

arXiv

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arXiv 2018年

作者： Chen, Yao Xia, Weiguo Cao, Ming Lü, Jinhu Department of Computer Science Southwestern University of Finance and Economics Chengdu611130 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China Faculty of Science and Engineering ENTEG University of Groningen Groningen9747 AG Netherlands School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

Distributed coordination algorithms (DCA) carry out information processing processes among a group of networked agents without centralized information fusion. Though it is well known that DCA characterized by an SIA (stochastic, indecomposable, aperiodic) matrix generate consensus asymptotically via synchronous iterations, the dynamics of DCA with asynchronous iterations have not been studied extensively, especially when viewed as stochastic processes. This paper aims to show that for any given irreducible stochastic matrix, even non-SIA, the corresponding DCA lead to consensus successfully via random asynchronous iterations under a wide range of conditions on the transition probability. Particularly, the transition probability is neither required to be independent and identically distributed, nor characterized by a Markov chain. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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Distributed Learning Mechanisms for Anomaly Detection in Privacy-Aware Energy Grid Management systems

引用

ACM Transactions on Sensor Networks 1000年

作者： Jia-Hao Syu Jerry Chun-Wei Lin Gautam Srivastava National Taiwan University Taiwan Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and IT Devices Silesian University of Technology Poland Mathematics and Computer Science Brandon University Canada and Research Centre for Interneural Computing China Medical University Taiwan and Computer Science and Mathematics Lebanese American University Lebanon

Smart grids have become an emerging topic due to net-zero emissions and the rapid development of artificial intelligence (AI) technology focused on achieving targeted energy distribution and maintaining operating reserves. In order to prevent cyber-physical attacks, issues related to the security and privacy of grid systems are receiving much attention from researchers. In this paper, privacy-aware energy grid management systems with anomaly detection networks and distributed learning mechanisms are proposed. The anomaly detection network consists of a server and a client learning network, which collaboratively learn patterns without sharing data, and periodically train and exchange knowledge. We also develop learning mechanisms with federated, distributed, and split learning to improve privacy and use Q-learning for decision-making to facilitate interpretability. To demonstrate the effectiveness and robustness of the proposed schemes, extensive simulations are conducted in different energy grid environments with different target distributions, ORRs, and attack scenarios. The experimental results show that the proposed schemes not only improve management performance but also enhance privacy and security levels. We also compare the management performance and privacy level of the different learning machines and provide usage recommendations.

关键词： Anomaly Detection Distributed Learning Federated Learning Split Learning Energy Grid Management

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Review of Approaches to the Use of UAVs, Remote Sensing and GIS in Humanitarian Demining: Ukrainian Case

SSRN

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SSRN 2024年

作者： Hutsul, Taras Khobzei, Mykola Tkach, Vladyslav Krulikovskyi, Oleh Moisiuk, Oleksandr Ivashko, Victor Samila, Andrii Department of Geomatics Land and Agromanagement Yuriy Fedkovych Chernivtsi National University Kotsyubynsky 2 Chernivtsi58002 Ukraine Department of Radio Engineering and Information Security Yuriy Fedkovych Chernivtsi National University Kotsyubynsky 2 Chernivtsi58002 Ukraine Department of Computer Sciences Yuriy Fedkovych Chernivtsi National University Kotsyubynsky 2 Chernivtsi58002 Ukraine Integrated Center for Research Development and Innovation in Advanced Materials Nanotechnologies and Distributed Systems for Fabrication and Control Stefan cel Mare University of Suceava Street University 13 Suceava720229 Romania Faculty of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Street University 13 Suceava720229 Romania

The history of the use of mines dates back almost two centuries. The geography of their use and the associated social harm have made them, without exaggeration, a global problem. At the same time, searches were underway for safe methods of their neutralization using various technical means. In so doing, until now, none of the existing methods provides a 100% guarantee of cleaning the territory, which determines the purpose of finding innovative methods and the possibility of combining them with existing ones. Unmanned aerial vehicles (UAVs) are becoming a real modern breakthrough in the field of intellectual achievements. Obtaining optimal results when solving a wide range of different problems, together with the development of composite materials, software, and the latest navigation equipment, make the tasks assigned to them and the expected results more and more difficult. UAVs allow people not to be in life-threatening conditions, to conduct activities beyond their physiological and psychophysiological abilities. The combination of the ability to collect spatial data during flight in various ranges of remote sensing with the possibility of carrying variants of useful equipment opens up prospects for their use in the field of demining territories. Supplementing UAV technologies with modern information systems for processing and analysis of information (expert systems, machine learning, computational intelligence, distributed artificial intelligence, neural networks, etc.), including spatial (GIS), opens up great prospects in the field of humanitarian demining of territories. © 2024, The Authors. All rights reserved.

关键词： Geographic information systems

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The applied principles of EEG analysis methods in neuroscience and clinical neurology

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Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

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YOLO-Ant: A Lightweight Detector via Depthwise Separable Convolutional and Large Kernel Design for Antenna Interference Source Detection

arXiv

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arXiv 2024年

作者： Tang, Xiaoyu Chen, Xingming Cheng, Jintao Wu, Jin Fan, Rui Zhang, Chengxi Zhou, Zebo The School of Electronic and Information Engineering Faculty of Engineering South China Normal University Guangdong Foshan528225 China The School of Physics South China Normal University Guangdong Guangzhou510000 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China The School of Internet of Things Engineering Jiangnan University Wuxi214122 China The School of Aeronautics Astronautics University of Electronic Science and Technology of China and Aircraft swarm intelligent sensing and cooperative control Key Laboratory of Sichuan Province Chengdu610097 China The National Laboratory on Adaptive Optics Chengdu610209 China

In the era of 5G communication, removing interference sources that affect communication is a resource-intensive task. The rapid development of computer vision has enabled unmanned aerial vehicles to perform various high-altitude detection tasks. Because the field of object detection for antenna interference sources has not been fully explored, this industry lacks dedicated learning samples and detection models for this specific task. In this article, an antenna dataset is created to address important antenna interference source detection issues and serves as the basis for subsequent research. We introduce YOLO-Ant, a lightweight CNN and transformer hybrid detector specifically designed for antenna interference source detection. Specifically, we initially formulated a lightweight design for the network depth and width, ensuring that subsequent investigations were conducted within a lightweight framework. Then, we propose a DSLK-Block module based on depthwise separable convolution and large convolution kernels to enhance the network’s feature extraction ability, effectively improving small object detection. To address challenges such as complex backgrounds and large interclass differences in antenna detection, we construct DSLKVit-Block, a powerful feature extraction module that combines DSLK-Block and transformer structures. Considering both its lightweight design and accuracy, our method not only achieves optimal performance on the antenna dataset but also yields competitive results on public datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Antennas

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