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2nd International Conference on Automation, Computing and Renewable systems, ICACRS 2023

作者： Gunavathie, M.A. Jacophine Susmi, S. Sivasankari, S.S. Venkatesh, M. Information Technology Panimalar Engineering College Chennai India Information Technology University College of Engineering Tindivanam India Electronics and Communication Engineering Dayananda Sagar University Bangalore India Computer Science and Business Systems Thiagarajar College of Engineering Madurai India

ISBN: (纸本)9798350340235

The placement of controllers is a critical issue that can significantly impact network performance and efficiency in Software DefinedNetworking (SDN). The optimal placement of controllers should take into account various factors such as network topology, resource requirements, and potential failures. For the purpose of determining the optimal placement of controllers, various approaches have been proposed in the literature, including mathematical optimization models, game theory, and simulation-based methods. These approaches aim to minimize latency, maximize network capacity, and improve network reliability in the face of failures. Overall, the optimal placement of controllers in SDNs remains an active area of research, and there is a need for continued exploration of new and innovative approaches to this problem. By taking into account the various factors that influence network performance and efficiency, researchers can continue to develop solutions that improve the design and operation of SDN networks. © 2023 IEEE.

关键词： Controller placement Software Defined Networking

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Simultaneous Speech Extraction for Multiple Target Speakers Under Meeting Scenarios

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Journal of Shanghai Jiaotong University (science) 2024年 1-7页

作者： Zeng, Bang Suo, Hongbin Wan, Yulong Li, Ming School of Computer Science Wuhan University Wuhan430027 China Suzhou Municipal Key Laboratory of Multimodal Intelligent Systems Duke Kunshan University Kunshan Jiangsu215316 China Data & amp AI Engineering System OPPO Beijing100125 China

The common target speech separation directly estimates the target source, ignoring the interrelationship between different speakers at each frame. We propose a multiple-target speech separation (MTSS) model to simultaneously extract each speaker’s voice from the mixed speech rather than just optimally estimating the target source. Moreover, we propose a speaker diarization (SD) aware MTSS system (SD-MTSS). By exploiting the target speaker voice activity detection (TSVAD) and the estimated mask, our SD-MTSS model can extract the speech signal of each speaker concurrently in a conversational recording without additional enrollment audio in advance. Experimental results show that our MTSS model achieves improvements of 1.38 dB signal-to-distortion ratio (SDR), 1.34 dB scale-invariant signal-to-distortion ratio (SISDR), and 0.13 perceptual evaluation of speech quality (PESQ) over the baseline on the WSJ0-2mix-extr dataset, separately. The SD-MTSS system makes a 19.2% relative speaker dependent character error rate reduction on the Alimeeting dataset. © Shanghai Jiao Tong University 2024.

关键词： Speech analysis

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Automation 5.0: The Key to systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-Hop Routing Protocol

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computer systems science & engineering 2023年第5期45卷 1759-1773页

作者： Manar Ahmed Hamza Haya Mesfer Alshahrani Sami Dhahbi Mohamed K Nour Mesfer Al Duhayyim ElSayed M.Tag El Din Ishfaq Yaseen Abdelwahed Motwakel Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11845Egypt

Wireless Sensor Networks(WSN)has evolved into a key technology for ubiquitous living and the domain of interest has remained active in research owing to its extensive range of *** spite of this,it is challenging to design energy-efficient *** routing approaches are leveraged to reduce the utilization of energy and prolonging the lifespan of *** order to solve the restricted energy problem,it is essential to reduce the energy utilization of data,transmitted from the routing protocol and improve network *** this background,the current study proposes a novel Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-hop Routing Protocol(DEAOA-MHRP)for *** aim of the proposed DEAOA-MHRP model is select the optimal routes to reach the destination in *** accomplish this,DEAOA-MHRP model initially integrates the concepts of Different Evolution(DE)and Arithmetic Optimization Algorithms(AOA)to improve convergence rate and solution ***,the inclusion of DE in traditional AOA helps in overcoming local optima *** addition,the proposed DEAOA-MRP technique derives a fitness function comprising two input variables such as residual energy and *** order to ensure the energy efficient performance of DEAOA-MHRP model,a detailed comparative study was conducted and the results established its superior performance over recent approaches.

关键词： Wireless sensor network routing multihop communication arithmetic optimization algorithm fitness function

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Feature selection using modified chaotic satin bowerbird algorithm with deep transfer learning for Multispectral Image Classification

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International Journal of information Technology (Singapore) 2024年 1-13页

作者： Rajakani, M. Kavitha, R.J. Rajesh, S. Department of Data Science and Business Systems School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology SRM Nagar Kattankulathur Chennai India Department of Electronics and Communication Engineering University College of Engineering Panruti Panruti 607106 India Department of Information Technology Mepco Schlenk Engineering College Sivakasi India

Multispectral image classification has received significant attention among research communities and academicians. Recently, several artificial intelligence (AI) models can be used for the extraction of prominent features. Besides, deep learning (DL) methods become more familiar and gained interest in the remote sensing community for the classification of multispectral and hyperspectral images. With this motivation, this paper presents an optimized feature learning with deep transfer learning enabled multispectral image classification (OFLDTL-MSIC) technique. The proposed OFLDTL-MSIC technique aims to categorize the different class labels of the multispectral images. Besides, the OFLDTL-MSIC technique applies multi-level discrete wavelet transform (DWT) based image decomposition technique. Moreover, the EfficientNet technique is applied as a feature extractor to generate a collection of features. Furthermore, selecting optimal features extracted by a EfficientNet involves identifying and retaining the most relevant and informative features The improved chaotic satin bowerbird optimization (CSBO) algorithm which uses dynamic population size is proposed for feature selection and kernel extreme learning machine (KELM) model is applied for the classification process. In order to ensure the enhanced performance of the OFLTDL-MSIC technique, a wide range of simulations take place using the Madurai LISS IV multispectral images and the results are examined under several aspects. The extensive comparative study highlighted the better performance of the OFLTDL-MSIC technique over the recent methods. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Deep learning Image classification Multispectral images Parameter tuning Remote sensing

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Combinational Backdoor Attack against Customized Text-to-Image Models

arXiv

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arXiv 2024年

作者： Jiang, Wenbo He, Jiaming Li, Hongwei Xu, Guowen Zhang, Rui Chen, Hanxiao Hao, Meng Yang, Haomiao The School of Computer Science and Engineering University of Electronic Science and Technology of China China The School of Computing and Information Systems Singapore Management University Singapore

Recently, Text-to-Image (T2I) synthesis technology has made tremendous strides. Numerous representative T2I models have emerged and achieved promising application outcomes, such as DALL-E, Stable Diffusion, Imagen, etc. In practice, it has become increasingly popular for model developers to selectively adopt various pre-trained text encoders and conditional diffusion models from third-party platforms, integrating them to build customized (personalized) T2I models. However, such an adoption approach is vulnerable to backdoor attacks. In this work, we propose a Combinational Backdoor Attack against Customized T2I models (CBACT2I) targeting this application scenario. Different from previous backdoor attacks against T2I models, CBACT2I embeds the backdoor into the text encoder and the conditional diffusion model separately. The customized T2I model exhibits backdoor behaviors only when the backdoor text encoder is used in combination with the backdoor conditional diffusion model. These properties make CBACT2I more stealthy and flexible than prior backdoor attacks against T2I models. Extensive experiments demonstrate the effectiveness of CBACT2I with different backdoor triggers and different backdoor targets on the open-sourced Stable Diffusion model. This work reveals the backdoor vulnerabilities of customized T2I models and urges countermeasures to mitigate backdoor threats in this scenario. Copyright © 2024, The Authors. All rights reserved.

关键词： Encoding (symbols)

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Movement Impacts on Eyeblink Detection Using FMCW Radar 9

Movement Impacts on Eyeblink Detection Using FMCW Radar

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9th IEEE Smart World Congress, SWC 2023

作者： Zhang, Xinze Brahim, Walid Ma, Jianhua Apduhan, Bernady O. Hosei University Graduate School of Computer and Information Sciences Tokyo184-8584 Japan Kyushu Sangyo University Faculty of Science and Engineering Department of Information Science Fukuoka813-0004 Japan

ISBN: (纸本)9798350319804

Eyeblink detection is essential for assessing physiological and psychological states in various applications. Radar technology offers a promising solution for non-intrusive and reliable eyeblink detection. This ongoing work investigates the effects of movements on eyeblink detectability using FMCW radar. The proposed methodology relies on the use of Adaptive Variational Mode Decomposition algorithm (AVMD) for blink signal extraction. Extensive experiments were performed to assess the performance under challenging conditions, analyzing the influence of body, head, and mouth movements on blink detectability. An in-depth analysis of movement impacts, identification of underlying reasons, and potential mitigation strategies is presented. This research provides a comprehensive evaluation, useful for the next step of research to provide a more reliable radar-based blink detection solution. © 2023 IEEE.

关键词： AVMD body Eyeblink FMCW radar head mouth movement impact

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Evaluation of Different Network Coding Algorithm Strategies for Wireless systems 5th

Evaluation of Different Network Coding Algorithm Strategies ...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Parameswaran, Murali Savita Kannagi, A. Panwar, Rahul School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Electrical Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

These research objectives are to evaluate and compare distinct community coding algorithms that can be applied in wireless networks to maximize network efficiency, throughput, and facts switch velocity. Special procedures are taken, such as coding in any respect of nodes within the community or sure nodes, which includes area nodes or routers. One-of-a-kind coding algorithm techniques might be tested in this study, including threshold coding and coded pooling. The chosen method will depend on the type of community, the scale, the traffic charge, and the favored performance goals, which include latency or bandwidth. Through leveraging network coding, packets can be transmitted and retransmitted without re-encoding. Studies have been carried out to evaluate the overall performance of diverse network coding algorithms for wireless networks inclusive of flooding, random linear network coding (RLNC), most distance separable codes (MDSC), directional network coding (DANC) and layered community coding (LNC). At the same time, MDSC and directional network coding have been proven more potent in factor-to-factor conversation eventualities. LNC is the most efficient average in many instances because of its ability to modify in real-time to changing link conditions. All of those algorithms provide a couple of advantages for wireless networks. This abstract affords an overview of the unique algorithm techniques, evaluates their effectiveness in numerous scenarios, and highlights their blessings for wireless networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network coding

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Optimizing Fabric Welding Using Image Processed Laser Inspection 5th

Optimizing Fabric Welding Using Image Processed Laser Inspec...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Ansari, Tabish Sekhar, Malepati Chandra Alam, Intekhab Bargavi, Manju Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India

ISBN: (纸本)9789819780426

Material welding is used in expanding industrial and industrial applications and depends on accuracy and precision to ensure satisfaction and protection. Laser inspection technology has been developed to help enhance the procedure's accuracy and performance by presenting rapid, reliable imaging that may be processed to decide where changes are wished. Through photograph processing, particular modifications to cloth welding can be recognized quickly and effectively. Additionally, photograph-processed laser inspection can hit upon any irregularities or defects in the welding method that can cause premature failure or decreased functionality. With this generation, designers and manufacturers can also develop higher control structures for his or her tasks, making more accurate and price-effective use of their assets. Sooner or later, the laser inspection era can offer actual-time remarks for automatic tactics, allowing changes to be made quickly with minimal disruption. Using this image processing technology, fabric welding groups can improve exceptional accuracy and value across merchandise. Optimizing material welding through image-processed laser inspection is a valuable method for controlling the pleasantness of welds. This technique uses a laser scanner, mild source, and a digital camera to seize detailed photos of the welds before and after welding. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Inspection

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Cryptanalysis of 2D-SCMCI Hyperchaotic Map Based Image Encryption Algorithm

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computer systems science & engineering 2023年第8期46卷 2401-2414页

作者： Mohammed S.Alshehri Sultan Almakdi Mimonah Al Qathrady Jawad Ahmad Department of Computer Science Najran UniversityNajran55461Saudi Arabia Department of Information Systems Najran UniversityNajran55461Saudi Arabia School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK

Chaos-based cryptosystems are considered a secure mode of communication due to their *** maps are associated with the other domains to construct robust encryption *** exist numerous encryption schemes in the literature based on chaotic *** work aims to propose an attack on a recently proposed hyper-chaotic map-based *** core notion of the original algorithm was based on permutation and diffusion.A bitlevel permutation approach was used to do the permutation row-and *** diffusion was executed in the forward and backward *** statistical strength of the cryptosystem has been demonstrated by extensive testing conducted by the author of the *** cryptanalysis article investigates the robustness of this cryptosystem against a chosen-plaintext *** secret keys of the cryptosystem were retrieved by the proposed attack with 258 chosen-plain *** results in this manuscript suggest that,in addition to standard statistical evaluations,thorough cryptanalysis of each newly suggested cryptosystem is necessary before it can be used in practical ***,the data retrieved is also passed through some statistical analysis to compare the quality of the original and retrieved *** results of the performance analysis indicate the exact recovery of the original *** make the cryptosystem useful for applications requiring secure data exchange,a few further improvement recommendations are also suggested.

关键词： Cryptanalysis hyperchaotic map image encryption chosen-plaintext attack cryptosystem

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