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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Ciprian Lupu Luu Duch Lich Nasture Ana-Maria Calianu George Lupu Mircea Chirita Doinita Faculty of Automatic Control and Computers University POLITEHNICA Bucharest Bucharest Romania Faculty of Transportation Mechanical Engineering University of Science and Technology The University of Danang Da Nang Vietnam National Research and Development Institute for Cryogenics and Isotopic Technologies—ICSI Rmmnicu Valcea Faculty of Automatic Control and Computers University POLITEHNICA Bucharest CM. AOSR Transilvania University of Brasov Brasov Romania Faculty of Electronics Telecommunications University POLITEHNICA Bucharest Bucharest Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

Actual industrial processes and production lines contain two or more control loops. One of the main challenges consists in ratio control in case one or more included parameters / elements fails or in disturbances presence. The paper presents solutions of real time balance for two or more parallel control structures and maintaining the ratio between controlled parameters. Applicability is proved on a real time hardware and software control structure of three ratios, a situation encountered to the modern transportation, chemical and other real processes.

关键词： Resistors Process control Transportation computer architecture Production MISO communication Real-time systems Software Robustness Periodic structures

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Network Management devices in an SDN environment

Network Management devices in an SDN environment

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International Conference on control Systems and computer science (CSCS)

作者： Diyar Jamal Hamad Khirota Gorgees Yalda Nicolae Tapus Ibrahim Taner Okumus Faculty of Automatic Control and Computer Science Politehnica University of Bucharest Bucharest Romania Soran Technical college Erbil Polytechnic University Iraq Erbil Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

Network optimization and continued availability depend on a number of capabilities that are part of network management. The Maintenance, operating and also offering a safeguarded interaction network is very complicated. It calls for the network operators to grapple with low-level vendor particular arrangements to execute the high degree network policies which are complicated. A method for monitoring networks with OpenFlow controller is presented in this paper in two separate functions for the same networks. Bandwidth utilization, Meter values, charts and statistics are provided by the method to extend controller monitoring capabilities. The method architecture and implementation will be introduced in order to present the feature set. Additionally, softswitches are used as a switch and Mininet to evaluate a virtualized network. This analysis shows whether Meters or ports value is better for network management.

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A Survey on Security Issues in Cloud Systems

A Survey on Security Issues in Cloud Systems

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Roedunet International Conference (RoEduNet)

作者： Diyar Jamal Hamad Khirota Gorgees Yalda Nicolae Tapus Ibrahim Taner Okumus Faculty of Automatic Control and Computer Science Politehnica University of Bucharest Bucharest Romania Soran Technical college Erbil Polytechnic University Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

“The cloud“ points out to servers, the databases and software that run on those servers. The Internet has always been constructed of infrastructure, servers and clients. Clients send their requests to servers, and servers reply, but cloud computing is distinct in the form that cloud servers are not just replying to requests with on-demand processing but they are saving data and running programs instead of the client. Cloud computing is a technology that is crossing a great expansion today. In cloud computing you can dynamically expand resources without knowledge of a new infrastructure, without developing new software or preparing new staff and to access such great technology the only things that are asked for are an Internet connection and an Internet browser. The goal of this survey is to present the different cloud security threats and recognize the proper security mechanism used to reduce them.

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Reducing the energy consumption required for the disassembly process implemented on an assembly and disassembly line 24

Reducing the energy consumption required for the disassembly...

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24th International Conference on control Systems and computer science, CSCS 2023

作者： Marius-Adrian, Paun Elena, Dragomir Otilia Florin, Dragomir Stelian, Iliescu Sergiu Eugenia, Minca Octavian Gabriel, Duca Valentin, Gurgu Ion University 'Politehnica' of Bucharest Department of Automation and Industrial Informatics Bucharest Romania Valahia University of Targoviste Faculty of Electrical Engineering Electronics and Information Technology Targoviste Romania University 'Politehnica ' of Bucharest Faculty of Automatic Control and Computers Bucharest Romania University 'Dunarea de Jos ' of Galati Department of Automation and Electrical Engineering Galati Romania Institute of Multidisciplinary Research for Science and Technology Valahia University of Targoviste Targoviste Romania

ISBN: (纸本)9798350313390

This paper proposes a method to reduce the energy consumption of an industrial disassembly process implemented on a production line by using an energy-efficient secondary disassembly process. In the case of defective products, the flow directs the simple product with priority to be disassembled in workstation (WS) 7. Therefore, all defective products are redirected to WS7. The disassembly of all simple products in WS7 is problematic for two reasons: the power consumption of WS7 is high compared to the other workstations, additionally there is an increased possibility of bottlenecks in the production line due to the high disassembly time. The proposed solution to reduce the possibility of deadlock and reduce power consumption is to redirect the defective products to the flexible cell (FC). Handling robots located in neighboring stations will participate collaboratively in the disassembly process. The control structure ensures that the two robots 'meet' in the boundary plane of WS3 with WS4 and disassemble each component through collaborative tasks. Collaborative control of disassembly is thought of as a solution to the global 'fluidization' of production, removing the bottleneck, from the overall flow, but also as an ingenious solution to reduce energy consumption. © 2023 IEEE.

关键词： Assembly

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Clustering Interval and Triangular Granular Data: Modeling, Execution, and Assessment

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IEEE Transactions on Neural Networks and Learning Systems 2024年第6期36卷 10000-10014页

作者： Yiming Tang Wenbin Wu Witold Pedrycz Jianwei Gao Xianghui Hu Zhaohong Deng Rui Chen Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada School of Computer and Information Hefei University of Technology Hefei China Faculty of Automatic Control Electronics and Computer Science Silesian University of Tecghnology Gliwice Poland Research Center of Performance and Productivity Analysis Istinye University Istanbul TÃrkiye School of Computer Science and Engineering Southeast University Nanjing China School of Artificial Intelligence and Computer Jiangnan University Wuxi Jiangsu China

In current granular clustering algorithms, numeric representatives were selected by users or an ordinary strategy, which seemed simple; meanwhile, weight settings for granular data could not adequately express their structural characteristics. Aiming at these problems, in this study, a new scheme called a granular weighted kernel fuzzy clustering (GWKFC) algorithm is put forward. We propose the representative selection and granularity generation (RSGG) algorithm enlightened by the density peak clustering (DPC) algorithm. We build interval and triangular granular data on the strength of numeric representatives obtained by RSGG under the principle of justifiable granularity (PJG), in which we establish some combinations of functions and boundary constraints and prove their properties. Furthermore, we present a novel distance formula via the kernel function for granular data and design new weights to affect the coverage and specificity of granular data. In addition, based upon these factors, we come up with the GWKFC algorithm of granular clustering, and its performance with different granularity is assessed. To sum up, a macro framework involving granular modeling, granular clustering, and assessment has been set up. Lastly, the GWKFC algorithm and ten other granular clustering algorithms are compared by experiments on some artificial and UCI datasets together with datasets with large data or those of high dimensionality. It is found that the GWKFC algorithm can provide better granular clustering results by contrast with other algorithms. The originality is embodied as follows. First, we improve the previous density radius and present the RSGG algorithm to acquire numeric representatives. Second, we propose a new strategy to determine granular data boundaries and further obtain novel weights enlightened by the idea of volume. Lastly, we employ the kernel function to calculate the distance between granular data, which has a stronger spatial division ability than the pr

关键词： Clustering algorithms Data models Computational modeling Numerical models Kernel Phase change materials Granular computing Uncertainty Fuzzy sets Noise

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A Simple on-Line Period Estimation for an Iterative Learning Active Noise control Scheme

A Simple on-Line Period Estimation for an Iterative Learning...

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European control Conference (ECC)

作者： Adam Lasota Michał Meller Department of Automatic Control ul. Narutowicza 11/12 Faculty of Electronics Telecommunications and Computer Science Gdańsk University of Technology Gdańsk POLAND PIT-RADWAR S.A. ul. Poligonowa 30 Warsaw POLAND

The paper describes a period/frequency adaptation mechanism applied to an active noise control scheme designed to attenuate disturbances with high autocorrelation characteristics. The proposed modification tracks slowly varying changes in the noise autocorrelation function peak. Moreover, it can switch between different algorithm settings when an abrupt change in noise characteristics is detected. This modification increases the method’s robustness and the area of potential implementations. The algorithm’s behavior and performance are verified with computer simulations using real-world signals and acoustic path models identified experimentally. The results confirm that the previously proposed ANC algorithm can be extended with the period tracking mechanism using little additional computational resources and without apparent degradation in attenuation or stability.

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Towards Automated Detection of Adversarial Attacks on Tabular Data

Towards Automated Detection of Adversarial Attacks on Tabula...

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Federated Conference on computer science and Information Systems (FedCSIS)

作者： Piotr Biczyk Łukasz Wawrowski Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland QED Software sp. z o.o. Warsaw Poland Łukasiewicz Research Network Institute of Innovative Technologies EMAG Katowice Poland

The paper presents a novel approach to investigating adversarial attacks on machine learning classification models operating on tabular data. The employed method involves using diagnostic parameters calculated on an approximated representation of a model under attack and analyzing differences in these diagnostic parameters over time. The hypothesis researched by the authors is that adversarial attack techniques, even if attempting a low-profile modification of input data, influence those diagnostic attributes in a statistically significant way. Thus, changes in diagnostic attributes can be used for detecting attack events. Three attack approaches on real-world datasets were investigated. The experiments confirm the approach as a promising technique to be further developed for detecting adversarial attacks.

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Contrast enhancement of optical videoscope images

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Iran Journal of computer science 2023年第3期6卷 261-275页

作者： Ammar, Reda Aboshosha, Sahar El-Hag, Noha A. Saifeldeen, Reda El-Shafai, Walid El-Banby, Ghada M. Ashiba, Huda I. Khalaf, Ashraf A. M. Elazm, Atef Abou El-Rabaie, El-Sayed M. Abd El-Samie, Fathi E. El-Safrawey, Amir Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Comm. Faculty of Engineering Minia University Minya Egypt Department of Management of Information Systems Higher Institute of Commercial Science El-Mahala El-Kobra Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Communications Engineering Bilbis Higher Institute of Engineering Sharqia Bilbis Egypt Security Engineering Laboratory Computer Science Department Prince Sultan University Riyadh 11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia

The videoscope (VS) images have poor quality and low contrast. Hence, in this paper, three proposed frameworks to improve the quality of VS images are presented. The first framework depends on contrast-limited adaptive histogram equalization (CLAHE) with adaptive gamma correction. The second framework depends on homomorphic processing. The third framework is based on the homomorphic enhancement with histogram equalization. The first one is superior from the entropy perspective, while the third one is superior from the contrast perspective. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

关键词： Fuzzy enhancement Histogram equalization Homomorphic enhancement Spectral entropy

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An Efficient and Secured Energy Management System for Automated Guided Vehicles

An Efficient and Secured Energy Management System for Automa...

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IEEE International Conference on Big Data

作者： Jia-Hao Syu Jerry Chun-Wei Lin Dariusz Mrozek Department of Computer Science and Information Engineering National Taiwan University Taiwan Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Norway Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Poland

ISBN: (纸本)9781665480468

In this paper, we propose a Secure Energy Management System (SEMS) with anomaly detection and Q-Learning decision modules for Automated Guided Vehicles (AGV). The anomaly detection module is a multi-task learning network to simultaneously classify suppliers and predict the real supply quantities. The Q-learning decision module can then determine operating reserve and subsidies to manage the energy grid. Experimental results illustrate that the proposed anomaly detection module has an excellent performance in classifying malicious suppliers, excels at shaping supply distribution, and outperforms the existing benchmark systems.

关键词： Q-learning Remotely guided vehicles Big Data Benchmark testing Multitasking Energy management systems Anomaly detection

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of Engineering & Technology 2023.

关键词： Machine learning

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