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Adaptive Multi-strategy Rabbit Optimizer for Large-scale Optimization

Journal of Bionic engineering 2025年第1期22卷 398-416页

作者： Baowei Xiang Yixin Xiang Department of Computing School of Electronic and Information Engineering Taizhou UniversityTaizhou318000China Department of Software Engineering College of Software Nankai UniversityTianjin300350China

As optimization problems continue to grow in complexity,the need for effective metaheuristic algorithms becomes increasingly ***,the challenge lies in identifying the right parameters and strategies for these *** this paper,we introduce the adaptive multi-strategy Rabbit Algorithm(RA).RA is inspired by the social interactions of rabbits,incorporating elements such as exploration,exploitation,and adaptation to address optimization *** employs three distinct subgroups,comprising male,female,and child rabbits,to execute a multi-strategy *** parameters,including distance factor,balance factor,and learning factor,strike a balance between precision and computational *** offer practical recommendations for fine-tuning five essential RA parameters,making them versatile and *** is capable of autonomously selecting adaptive parameter settings and mutation strategies,enabling it to successfully tackle a range of 17 CEC05 benchmark functions with dimensions scaling up to *** results underscore RA’s superior performance in large-scale optimization tasks,surpassing other state-of-the-art metaheuristics in convergence speed,computational precision,and ***,RA has demonstrated its proficiency in solving complicated optimization problems in real-world engineering by completing 10 problems in CEC2020.

关键词： Adaptive parameter Large scale optimization Rabbit algorithm Swarm intelligence engineering optimization

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Joint contrastive learning and belief rule base for named entity recognition in cybersecurity

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Cybersecurity 2025年第2期8卷 174-187页

作者： Chenxi Hu Tao Wu Chunsheng Liu Chao Chang College of Electronic Engineering National University of Defense TechnologyHefeiChina Department of Computing The Hong Kong Polytechnic UniversityHong KongChina

Named Entity Recognition(NER)in cybersecurity is crucial for mining information during cybersecurity *** methods rely on pre-trained models for rich semantic text embeddings,but the challenge of anisotropy may affect subsequent encoding ***,existing models may struggle with noise *** address these issues,we propose JCLB,a novel model that Joins Contrastive Learning and Belief rule base for NER in *** utilizes contrastive learning to enhance similarity in the vector space between token sequence representations of entities in the same category.A Belief Rule Base(BRB)is developed using regexes to ensure accurate entity identification,particularly for fixed-format phrases lacking ***,a Distributed Constraint Covariance Matrix Adaptation Evolution Strategy(D-CMA-ES)algorithm is introduced for BRB parameter *** results demonstrate that JCLB,with the D-CMA-ES algorithm,significantly improves NER accuracy in cybersecurity.

关键词： Named entity recognition Cybersecurity Contrastive learning Belief rule base

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More Than Lightening:A Self-Supervised Low-Light Image Enhancement Method Capable for Multiple Degradations

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 622-637页

作者： Han Xu Jiayi Ma Yixuan Yuan Hao Zhang Xin Tian Xiaojie Guo the Electronic Information School Wuhan UniversityWuhan 430072China IEEE the Department of Electronic Engineering Chinese University of Hong KongHong Kong 999077China the College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of *** enhance low-light images,most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is *** contrast,a self-supervised method breaks free from the reliance on normal-light data,resulting in more convenience and better *** self-supervised methods primarily focus on illumination adjustment and design pixel-based adjustment methods,resulting in remnants of other degradations,uneven brightness and *** response,this paper proposes a self-supervised enhancement method,termed as *** can handle multiple degradations including illumination attenuation,noise pollution,and color shift,all in a self-supervised *** attenuation is estimated based on physical principles and local neighborhood *** removal and correction of noise and color shift removal are solely realized with noisy images and images with color ***,the comprehensive and fully self-supervised approach can achieve better adaptability and *** is applicable to various low light conditions,and can reproduce the original color of scenes in natural *** experiments conducted on four public datasets demonstrate the superiority of SLIE to thirteen state-of-the-art *** code is available at https://***/hanna-xu/SLIE.

关键词： Color correction low-light image enhancement self-supervised learning.

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Model Predictive Current Control for Low-Cost Shunt Active Power Filter

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1589-1598页

作者： Ali A.Abdel-Aziz Mohamed A.Elgenedy Barry W.Williams the Electronic and Electrical Engineering Department Strathclyde UniversityGlasgowG11XQUK School of Computing Engineering and the Built Environment(SCEBE)Glasgow Caledonian UniversityGlasgowG40BAUK

Performance of a three-phase shunt active power filter(SAPF)relies on the capability of the controller to track the reference ***,designing an accurate current controller is crucial to guarantee satisfactory SAPF *** paper presents a model predictive current controller(MPCC)for a low-cost,four-switch,shunt active power filter for power quality improvement.A four-switch,B4,converter topology is adopted as an SAPF,hence offering a simple,robust,and low-cost *** addition,to further reduce overall cost,only two interfacing filter inductors,instead of three,are used to eliminate switching current *** proposed SAPF model MPCC is detailed for implementation,where simulation and experimental results validate effectiveness of the proposed control algorithm showing a 20%improvement in total harmonic distortion compared with a conventional hysteresis band current controller.

关键词： Four-switch converter harmonic distortion model predictive current control power quality shunt active power filter

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Robot-Oriented 6G Satellite-UAV Networks: Requirements, Paradigm Shifts, and Case Studies

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China Communications 2024年第2期21卷 74-84页

作者： Peng Wei Wei Feng Yunfei Chen Ning Ge Wei Xiang Department of Electronic Engineering Tsinghua UniversityBeijing 100084China Department of Engineering University of DurhamDH13LEDurhamUK School of Computing Engineering and Mathematical SciencesLa Trobe UniversityMelbourneVIC 3086Australia

Networked robots can perceive their surroundings, interact with each other or humans,and make decisions to accomplish specified tasks in remote/hazardous/complex environments. Satelliteunmanned aerial vehicle(UAV) networks can support such robots by providing on-demand communication services. However, under traditional open-loop communication paradigm, the network resources are usually divided into user-wise mostly-independent links,via ignoring the task-level dependency of robot collaboration. Thus, it is imperative to develop a new communication paradigm, taking into account the highlevel content and values behind, to facilitate multirobot operation. Inspired by Wiener’s Cybernetics theory, this article explores a closed-loop communication paradigm for the robot-oriented satellite-UAV network. This paradigm turns to handle group-wise structured links, so as to allocate resources in a taskoriented manner. It could also exploit the mobility of robots to liberate the network from full coverage,enabling new orchestration between network serving and positive mobility control of robots. Moreover,the integration of sensing, communications, computing and control would enlarge the benefit of this new paradigm. We present a case study for joint mobile edge computing(MEC) offloading and mobility control of robots, and finally outline potential challenges and open issues.

关键词： closed-loop communication mobility control satellite-UAV network structured resource allocation

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Optimisation and Performance Computation of a Phase Frequency Detector Module for IoT Devices

Annals of Emerging Technologies in Computing

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Annals of Emerging Technologies in computing 2024年第1期8卷 13-21页

作者： Hemel, Md. Shahriar Khan Reaz, Mamun Bin Ibne Ali, Sawal Hamid Bin Md Bhuiyan, Mohammad Arif Sobhan Miraz, Mahdi H. Department of Electrical Electronic and Systems Engineering Universiti Kebangsaan Malaysia Malaysia Department of Electrical and Electronic Engineering Independent University Bangladesh School of Electrical Engineering and Artificial Intelligence Xiamen University Malaysia Malaysia School of Computing and Data Science Xiamen University Malaysia Malaysia Faculty of Arts Science and Technology Wrexham University United Kingdom Faculty of Computing Engineering and Science University of South Wales United Kingdom

The Internet of Things (IoT) is pivotal in transforming the way we live and interact with our surroundings. To cope with the advancement in technologies, it is vital to acquire accuracy with the speed. A phase frequency detector (PFD) is a critical device to regulate and provide accurate frequency in IoT devices. Designing a PFD poses challenges in achieving precise phase detection, minimising dead zones, optimising power consumption, and ensuring robust performance across various operational frequencies, necessitating complex engineering and innovative solutions. This study delves into optimising a PFD circuit, designed using 90 nm standard CMOS technology, aiming to achieve superior operational frequencies. An efficient and high-frequency PFD design is crafted and analysed using cadence virtuoso. The study focused on investigating the impact of optimising PFD design. With the optimised PFD, an operational frequency of 5 GHz has been achieved, along with a power consumption of only 29 µW. The dead zone of the PFD was only 25 ps. © 2024 by the author(s).

关键词： Phase locked loops

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Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

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Computer Modeling in engineering & Sciences 2024年第3期138卷 2103-2127页

作者： Othman S.Al-Heety Zahriladha Zakaria Ahmed Abu-Khadrah Mahamod Ismail Sarmad Nozad Mahmood Mohammed Mudhafar Shakir Hussein Alsariera Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka(UTeM)Durian TunggalMalaysia College of Computing&Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Department of Electrical Electronic and System EngineeringUniversiti Kebangsaan MalaysiaUKM BangiSelangorMalaysia Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityKirkukIraq Faculty of Engineering and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Batu PahatMalaysia 6Research Center DepartmentThe University of MashreqBaghdadIraq

Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the *** this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things *** framework integrates Kalman filtering and *** smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction *** traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction *** evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art ***,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.

关键词： Q-learning intelligent transportation system(ITS) traffic control vehicular communication kalman filtering smart city Internet of Things

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Optimal aeration management strategy for a small-scale food waste composting

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Carbon Resources Conversion 2024年第1期7卷 79-88页

作者： Jia Chi Lai Yi Lung Then Siaw San Hwang Chung Sien Lee School of Engineering and Science Faculty of EngineeringComputing and ScienceSwinburne University of Technology93350 KuchingSarawakMalaysia Department of Electrical and Electronic Engineering Faculty of EngineeringUniversiti Malaysia Sarawak94300 Kota SamarahanSarawakMalaysia

Food waste is a significant contributor to greenhouse gas emissions when it ends up in *** turns out to be a sustainable solution to this problem,but it requires controlled and continuous airflow for optimal *** study focused on the effect of aeration rates and airflow directions on food waste composting using a closed system with forced *** was entered into the composting vessel in three directions,which were upward,downward,and a combination of both *** direction was run at aeration rates of 0.1,0.4,and 0.7 L/*** findings showed that the compost pile aerated at 0.4 L/min by using two-directional airflow can reach the thermophilic temperature within half of the *** compost pile achieved temperature of 40.94℃ after 10.5 *** the compost experienced slightly high in moisture loss(4.3%),the compost still attained the standard values for *** compost produced from food waste could be applied in soil to improve its fertility.

关键词： Small-scale composting Two-directional airflow Intermittent aeration Food waste

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Optimization of Real-Time Dynamic Gesture Recognition Based on Multi-Scale Spatio-Temporal Residual Graph Convolutional Neural Networks 5

Optimization of Real-Time Dynamic Gesture Recognition Based ...

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5th IEEE International Conference on Power, electronics and Computer Applications, ICPECA 2025

作者： Zhou, Meixiu Chen, Hanying Zhao, Shancheng Wu, Xia Jinan University Department of Electronic Engineering Guangzhou China Computing Center Jinan University Guangzhou China

ISBN: (纸本)9798331533694

The challenge of real-time dynamic gesture recognition is how to accurately locate the gestures in the video and take into account the real-time and accuracy in the recognition process. Aiming at the problem of dynamic gesture recognition in video, this paper proposes a dynamic gesture recognition method based on the multi-scale spatio-temporal residual graph convolution. The convolution module based on spatio-temporal residual graph is used to capture the motion information at different time and spatial scales, expand the receptive field of spatio-temporal dimension, and use the residual structure system to process hierarchically. The dynamic gesture recognition algorithm is designed by using the characteristics of time series, gesture category, gesture coordinates and gesture area to complete the dynamic gesture recognition. The gesture recognition performance of the model is tested under simple and complex background. Under the same level model, the performance of this model has certain advantages. © 2025 IEEE.

关键词： Convolutional neural networks

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A Novel Proactive AI-Based Agents Framework for an IoE-Based Smart Things Monitoring System with Applications for Smart Vehicles

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Computers, Materials & Continua 2025年第2期82卷 1839-1855页

作者： Meng-Hua Yen Nilamadhab Mishra Win-Jet Luo Chu-En Lin Department of Electronic Engineering National Chin-Yi University of TechnologyTaichung411030Taiwan School of Computing Science&Engineering VIT Bhopal UniversityBhopal466114India Department of Refrigeration Air-Conditioning and Energy EngineeringNational Chin-Yi University of TechnologyTaichung411030Taiwan

The Internet of Everything(IoE)coupled with Proactive Artificial Intelligence(AI)-Based Learning Agents(PLAs)through a cloud processing system is an idea that connects all computing resources to the Internet,making it possible for these devices to communicate with one *** featured in the IoE include embedding,networking,and sensing *** achieve the intended results of the IoE and ease life for everyone involved,sensing devices and monitoring systems are linked *** IoE is used in several contexts,including intelligent cars’protection,navigation,security,and fuel *** Smart Things Monitoring System(STMS)framework,which has been proposed for early occurrence identification and theft prevention,is discussed in this *** STMS uses technologies based on the IoE and PLAs to continuously and remotely observe,control,and monitor *** STMS is familiar with the platform used by the global positioning system;as a result,the STMS can maintain a real-time record of current vehicle *** information is utilized to locate the vehicle in an accident or *** findings of the STMS system are promising for precisely identifying crashes,evaluating incident severity,and locating vehicles after collisions have ***,we formulate an ad hoc STMS network communication scenario to evaluate the efficacy of data communication by utilizing various network parameters,such as round-trip time(RTT),data packet transmission,data packet reception,and *** our experimentation,we obtained an improved communication efficiency for STMS across multiple PLAs compared to the standard greedy routing and traditional AODV *** framework facilitates adaptable solutions with communication competence by deploying Proactive PLAs in a cloud-connected smart vehicular environment.

关键词： Artificial intelligence(AI) proactive AI-based learning agents(PLA) internet of everything(IoE) smart things monitoring system(STMS) cloud processing system driving monitoring assistance system(MAS) smart vehicles

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