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Design of Chaos Induced Aquila Optimizer for Parameter Estimation of Electro-Hydraulic Control System

computer Modeling in engineering & sciences 2025年第5期143卷 1809-1841页

作者： Khizer Mehmood Naveed Ishtiaq Chaudhary Zeshan Aslam Khan Khalid Mehmood Cheema Muhammad Asif Zahoor Raja Sultan SAlshamrani Kaled MAlshmrany Department of Electrical and Computer Engineering International Islamic UniversityIslamabad44000Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan International Graduate School of Artificial Intlligence National Yunlin University of Science and TechnologyYunlin64002Taiwan Department of Electronic Engineering Fatima Jinnah Women UniversityRawalpindi46000Pakistan Department of Information Technology College of Computer and Information TechnologyTaif University.Taif21944Saudi Arabia Institute of Public Administration Jeddah21944Saudi Arabia

Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching *** is applied in various applications and its numerous variants were proposed in the ***,chaos theory has not been extensively investigated in ***,it is still not applied in the parameter estimation of electro-hydraulic *** this work,ten well-defined chaotic maps were integrated into a narrowed exploitation of AO for the development of a robust chaotic optimization *** extensive investigation of twenty-three mathematical benchmarks and ten IEEE Congress on Evolutionary Computation(CEC)functions shows that chaotic Aquila optimization techniques perform better than the baseline *** investigation is further conducted on parameter estimation of an electro-hydraulic control system,which is performed on various noise levels and shows that the proposed chaotic AO with Piecewise map(CAO6)achieves the best fitness values of and at noise levels and *** test 2.873E-05,1.014E-04,8.728E-031.300E-03,1.300E-02,1.300E-01,for repeated measures,computational analysis,and Taguchi test reflect the superiority of CAO6 against the state of the arts,demonstrating its potential for addressing various engineering optimization ***,the sensitivity to parameter tuning may limit its direct application to complex optimization scenarios.

关键词： Aquila optimizer electro-hydraulic control system chaos theory autoregressive model

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Interpretable foundation models as decryptors peering into the Earth system

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The Innovation 2024年第5期5卷 21-22页

作者： Chenyu Li Danfeng Hong Bing Zhang Tianjun Liao Naoto Yokoya Pedram Ghamisi Min Chen Lizhe Wang Jon Atli Benediktsson Jocelyn Chanussot Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China School of Electronic Electricaland Communication EngineeringUniversity of Chinese Academy of SciencesBeijing 100049China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China Academy of Military Sciences Beijing 100000China Graduate School of Frontier Sciences The University of TokyoChiba 277-8561Japan Helmholtz-Zentrum Dresden-Rossendorf Helmholtz Institute Freiberg for Resource Technology09599 FreibergGermany Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China School of Computer Science China University of GeosciencesWuhan 430078China Faculty of Electrical and Computer Engineering University of Iceland102 ReykjavikIceland University Grenoble Alpes InriaCNRSGrenoble INPLJK38000 GrenobleFrance

THE EARTH SYSTEM AMID THE BIG DATA *** processes of the Earth system drive interactions between energy,matter,and life,and a comprehensive understanding of their full evolutionary trajectory is critical for sustainable human *** modeling primarily relies on a set of theoretical equations to simulate dynamic process such as the carbon-nitrogen cycle,solar radiation dynamics,and terrestrial ecosystem dynamics.1 Despite the extensive modeling experience of Earth scientists,the rapid advancement of Earth observation techniques has led to a significant increase in the volume of databases,with data accumulating daily or even *** has exacerbated the conflict between the capacity for data collection and utilization for big Earth ***,there is an urgent need to enhance the intelligent processing and analysis of big Earth data.

关键词： dynamics. system foundation

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A Q-learning-based Multipath Scheduler for Data Transmission Optimization in Heterogeneous Wireless Networks

A Q-learning-based Multipath Scheduler for Data Transmission...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Thanh Trung Nguyen Minh Hai Vu Phi Le Nguyen Phan Thuan Do Kien Nguyen School of Information and Communication Technology Hanoi University of Science and Technology Hanoi Vietnam Faculty of Computer Science Phenikaa University Hanoi Vietnam Institute for Advanced Academic Research Chiba University Japan Graduate School of Engineering Chiba University Japan

In the era of 5G and beyond, mobile devices usually can access several heterogeneous wireless networks (e.g., Wi-Fi and 5G). To simultaneously and efficiently utilize the accessible network resources, muli path transport protocols, such as MPTCP and MPQUIC, have shown much potential. In these protocols, scheduling is one of the critical processes to ensure the performance of the multipath transmission. Although there have been many proposed multipath schedulers in the literature, they have not performed well in heterogeneous networks, especially when the network conditions vary (i.e., dynamicity). In this paper, we propose a novel Q-learning-based Multipath scheduler for data transmission optimization (Q-SAT), aiming to bypass the existing limitation. By leveraging the self-learning ability of reinforcement learning, Q-SAT can instantly observe environmental changes and deploy appropriate path selection to optimize data transmission time. As a result, Q-SAT efficiently schedules multipath communication in heterogeneous wireless networks with different dynamicity levels. We have implemented Q-SAT with MPQUIC and extensively evaluated Q-SAT in an emulated environment and a real network. The evaluation results show that Q-SAT improves the data transmission time by at least 10% in the emulation and 26% in the actual deployment compared to the state-of-the-art schedulers.

关键词： Transport protocols Schedules 5G mobile communication Wireless networks TCPIP Mobile handsets Heterogeneous networks

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Supplemental information

arXiv

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arXiv 2025年

作者： Sunada, Satoshi Niiyama, Tomoaki Kanno, Kazutaka Nogami, Rin Röhm, André Awano, Takato Uchida, Atsushi Faculty of Mechanical Engineering Institute of Science and Engineering Kanazawa University Kakuma-machi Kanazawa Ishikawa920-1192 Japan Department of Information and Computer Sciences Saitama University 255 Shimo-Okubo Sakura-ku Saitama338-8570 Japan Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan

The rapidly increasing computational demands for artificial intelligence (AI) have spurred the exploration of computing principles beyond conventional digital computers. Physical neural networks (PNNs) offer efficient neuromorphic information processing by harnessing the innate computational power of physical processes;however, training their weight parameters is computationally expensive. We propose a training approach for substantially reducing this training cost. Our training approach merges an optimal control method for continuous-time dynamical systems with a biologically plausible training method—direct feedback alignment. In addition to the reduction of training time, this approach achieves robust processing even under measurement errors and noise without requiring detailed system information. The effectiveness was numerically and experimentally verified in an optoelectronic delay system. Our approach significantly extends the range of physical systems practically usable as PNNs. Copyright © 2025, The Authors. All rights reserved.

关键词： Continuous time systems

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Part Aware Contrastive Learning for Self-Supervised Action Recognition

arXiv

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arXiv 2023年

作者： Hua, Yilei Wu, Wenhan Zheng, Ce Lu, Aidong Liu, Mengyuan Chen, Chen Wu, Shiqian School of Information Science and Engineering Wuhan University of Science and Technology China University of North Carolina at Charlotte United States Center for Research in Computer Vision University of Central Florida United States Peking University Shenzhen Graduate School China

In recent years, remarkable results have been achieved in self-supervised action recognition using skeleton sequences with contrastive learning. It has been observed that the semantic distinction of human action features is often represented by local body parts, such as legs or hands, which are advantageous for skeleton-based action recognition. This paper proposes an attention-based contrastive learning framework for skeleton representation learning, called SkeAttnCLR, which integrates local similarity and global features for skeleton-based action representations. To achieve this, a multi-head attention mask module is employed to learn the soft attention mask features from the skeletons, suppressing non-salient local features while accentuating local salient features, thereby bringing similar local features closer in the feature space. Additionally, ample contrastive pairs are generated by expanding contrastive pairs based on salient and non-salient features with global features, which guide the network to learn the semantic representations of the entire skeleton. Therefore, with the attention mask mechanism, SkeAttnCLR learns local features under different data augmentation views. The experiment results demonstrate that the inclusion of local feature similarity significantly enhances skeleton-based action representation. Our proposed SkeAttnCLR outperforms state-of-the-art methods on NTURGB+D, NTU120-RGB+D, and PKU-MMD *** code and settings are available at this repository: https://***/GitHubOfHyl97/SkeAttnCLR Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Preprocessing Techniques for Enhancing Vision-Based Detection System for Tire Sidewall Extraction

Preprocessing Techniques for Enhancing Vision-Based Detectio...

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International Seminar on Research of information Technology and Intelligent Systems (ISRITI)

作者： Jia Hao Loo Veronica Lestari Jauw Chin Seong Lim Khairul-Rijal Sarmin Nunung Nurul Qomariyah Ahmad Nurul Fajar Department of Mechanical Materials and Manufacturing Engineering University of Nottingham Malaysia Malaysia Continental Tyre Technology Centre Malaysia Petaling Jaya Malaysia Computer Science Department School of Computing and Creative Arts Bina Nusantara University Jakarta Indonesia Information System Management Department BINUS Graduate Program-Master Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

This study aims to develop a system for extracting crucial information from tire sidewalls using Optical Character Recognition (OCR). Initially, images of tire were captured manually by smartphone cameras, including Redmi 9T, iPhone 11, and Galaxy S23 Ultra. The captured images are then transferred to a computer for storage. Subsequently, these images were cropped according to the boundaries identified by Hough Circle Transform (HCT). The cropped images were then further pre-processed. During the pre-processing phase, geometrical transformation and image sharpening techniques are applied to enhance the clarity and readability of the text images. The text is then extracted using Google Vision, with the extracted text categorized by size, DOT, brand and pattern. The results indicated that the effectiveness of image pre-processing was constrained by the accuracy of circle detection, which reached a maximum rate of 87.1%. This causes parts of the text to be cut out inaccurately, leading to a suboptimal extraction accuracy of 55.65%. It is also observed that the Redmi 9T camera produced inconsistent results compared to other devices. Specifically, the iPhone 11 and Samsung Galaxy S23 Ultra demonstrated superior extraction accuracies of 69.71% and 66.37%, respectively, whereas the Redmi 9T achieved a lower extraction accuracy of 37.76%.

关键词： Accuracy Optical character recognition Text categorization Lighting Transforms US Department of Transportation Cameras Tires Internet Data mining

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Highly sensitive active-powering pressure sensor enabled by integration of double-rough surface hydrogel and flexible batteries

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npj Flexible Electronics 2022年第1期6卷 908-916页

作者： Yuan Huang Binbin Liu Wenyue Zhang Gangrui Qu Shunyu Jin Xianbo Li Zanxiang Nie Hang Zhou School of Microelectronics Science and Technology Sun Yat-Sen UniversityGuangzhouP.R.China School of Electronic and Computer Engineering Peking University Shenzhen Graduate SchoolShenzhen 518055P.R.China School of Electronics and Information Technology Sun Yat-Sen UniversityGuangzhouP.R.China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 23000P.R.China Zinergy Shenzhen Ltd. Floor 6Building HGangzhilong Science ParkLonghuaShenzhen 518109P.R.China

A conductive,elastic,and biocompatible hybrid network hydrogel was prepared by cross-linking of locust bean gum,polyvinyl alcohol,and carbon nanotubes,yielding a rough top surface and smooth bottom *** merging of the two pieces of hydrogel flat face to flat face forms a highly elastic hydrogel with double-rough surfaces.A piezoresistive sensor assembled with the double-rough surface hydrogel sandwiched between two carbon cloth electrodes exhibits a high sensitivity(20.5 kPa^(-1),0-1kPa),a broad detection range(0.1-100 kPa)and a reliable response for 1000 *** rough contact area between the hydrogels and the carbon cloth is found critical in achieving ultra-high sensitivities in the low-pressure ***,further monolithic integration of the sensor with a flexible solid-state zinc ion battery ensures the self-powering of the sensor for various human motions detection applications.

关键词： hydrogel double integration

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Time Series Forecasting for Coronavirus (COVID-19) 1

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3rd International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020

作者： Sobti, Priyal Nayyar, Anand Nagrath, Preeti Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering New Delhi110063 India Graduate School Faculty of Information Technology Duy Tan University Da Nang550000 Viet Nam

ISBN: (数字)9789811614804

ISBN: (纸本)9789811614798

The upsurge of the novel coronavirus has spread to many countries and has been declared a pandemic by WHO. It has shaken the most powerful countries across the world like the USA, UK, and has affected economies of various countries. The coronavirus or the 2019-nCoV causes the disease that has been named COVID-19. This disease transmits by inhaling droplets that are expelled by an infected person. It has been affecting people in different ways and has been found to be threatening for the older population or people with comorbidities. It has been seen that the virus 2019-nCoV spreads faster than the two of its antecedents namely severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). No cure or vaccine has been discovered as of now and taking precautions like staying at home are the only possible solutions. Our study analyzes the current trend of the disease in India and predicts future trends using time series forecasting. The official dataset provided by John Hopkins University through a GitHub repository has been used for the research for the time period of 22 January 2020 to 31 May 2020. The trend in cases, fatalities, and the people who have recovered until the date of 31 May 2020 has been discussed in the paper. It has been seen through the findings that the total number of cases is expected to rise to 2,15,000 by the end of May 2020 i.e. 31 May 2020 as per the AR (Autoregression) model. ARIMA (Autoregressive Integrated Moving Average) model predicts the number of cases to be 2,05,000 until the same date. Actual data has shown that the number of confirmed cases is 1,90,609 as on 31 May 2020 giving a percentage error of 7.57% and 12.85% for ARIMA and AR model respectively. Comparison between the findings of the two models has been shown later in the paper. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Coronavirus

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A Framework for Digital Twin-Based Deterministic Communication in Satellite Time Sensitive Networks

A Framework for Digital Twin-Based Deterministic Communicati...

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IEEE International Conference on Communications (ICC)

作者： Yinzhi Lu Guofeng Zhao Chuan Xu Muhammad Imran Keping Yu Joel J.P.C. Rodrigues School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China College of Applied Computer Science Saud University Riyadh Saudi Arabia Graduate School of Science and Engineering Hosei University Tokyo Japan College of Computer Science and Technology China University of Petroleum Qingdao China Instituto de Telecomunicações Covilhã Portugal

With the explosive growth of real-time applications in satellite systems, Time Sensitive Networking (TSN) is explored to be introduced to provide bounded low latency network services. Nevertheless, some efforts in delay ensuring techniques are ongoing, guaranteeing deterministic low latency communication in satellite networks is still a significant problem. In the article, we first present a Digital Twin-based TSN framework in which digital twin technology is introduced for the purpose of reducing the management cost and optimizing the performance of satellite networks. The virtual model of the scheduling method working in satellite systems is explored and created for the simulation and prediction of the forwarding delay results. Deep convolution generative adversarial network (DCGAN) is adopted to train the scheduling model. The simulation experiments verified that the digital twin could mirror the scheduling behavior and predict the delay in dynamic environments.

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ECG signals-based security and steganography approaches in WBANs: A comprehensive survey and taxonomy

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Sustainable Computing: Informatics and Systems 2024年 41卷

作者： Masdari, Mohammad Band, Shahab S. Qasem, Sultan Noman Sayed, Biju Theruvil Pai, Hao-Ting Department of Computer Engineering Urmia Branch Islamic Azad University Urmia Iran Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Taiwan Riyadh11432 Saudi Arabia Computer Science Department Faculty of Applied Science Taiz University Taiz6803 Yemen Department of Computer Science Dhofar University PO Box 2509 SalalahPCode 211 Oman Bachelor Program of Big Data Applications in Business National Pingtung University Pingtung Taiwan

Wireless Body Area Networks (WBANs) are integral components of e-healthcare systems, responsible for monitoring patients' physiological states through intelligent implantable or wearable sensor nodes. These nodes collect medical data, which is then transmitted to remote healthcare facilities for thorough evaluation. Securing medical data within WBANs is paramount due to its central role in preserving patient privacy and confidentiality. Notably, Electrocardiogram (ECG) signals have recently gained prominence as pivotal elements within diverse security frameworks. Incorporating ECG signals strategically enhances the security and reliability of WBANs and broader e-healthcare systems, instilling greater trustworthiness. This survey article provides an in-depth exploration of contemporary ECG-based security schemes, adding to the scholarly discourse. The imperative to categorize these security paradigms revolves around their use of ECG signals. This categorization identifies three key domains: the first involves schemes that utilize ECG signals for cryptographic operations, encompassing key generation, agreement, management, and authentication. The second category employs steganography-based techniques, using ECG signals to conceal patients' sensitive medical data. The third category focuses on enhancing ECG signal security during data transmission. Each category is meticulously elaborated, detailing architectural foundations, notable contributions, and intrinsic security services. Furthermore, each section presents a comprehensive overview of the attributes characterizing ECG-based security frameworks. This includes insights into employed datasets, simulation environments, evaluation metrics, and inherent advantages and limitations. Expanding on this, a thorough analysis of distinctive attributes underpinning these security frameworks concludes by shedding light on potential directions for future research. © 2023 Elsevier Inc.

关键词： Authentication

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