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African Bison Optimization Algorithm:A New Bio-Inspired Optimizer with Engineering Applications

computers, Materials & Continua 2024年第10期81卷 603-623页

作者： Jian Zhao Kang Wang Jiacun Wang Xiwang Guo Liang Qi School of Science University of Science and Technology LiaoningAnshan114051China Team of Artificial Intelligence Theory and Application University of Science and Technology LiaoningAnshan114051China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Information and Control Engineering College Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China

This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological *** is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and *** foraging behavior prompts the bison to seek a richer food source for *** bison find a food source,they stick around for a while by bathing *** jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating *** eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent *** above behaviors are translated into ABO by mathematical *** assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with *** findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.

关键词： Optimization metaheuristics African bison optimization engineering problems

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Fake News Encoder Classifier (FNEC) for Online Published News Related to COVID-19 Vaccines

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Intelligent Automation & Soft Computing 2023年第7期37卷 73-90页

作者： Asma Qaiser Saman Hina Abdul Karim Kazi Saad Ahmed Raheela Asif Department of Computer Science and Information Technology NED University of Engineering and TechnologyKarachi75270Pakistan Department of Computer Science Iqra UniversityKarachi76400Pakistan Department of Software Engineering NED University of Engineering and TechnologyKarachi75270Pakistan

In the past few years,social media and online news platforms have played an essential role in distributing news content *** of the authenticity of news has become a major *** the COVID-19 outbreak,misinformation and fake news were major sources of confusion and insecurity among the general *** the first quarter of the year 2020,around 800 people died due to fake news relevant to *** major goal of this research was to discover the best learning model for achieving high accuracy and performance.A novel case study of the Fake News Classification using ELECTRA model,which achieved 85.11%accuracy score,is thus reported in this *** addition to that,a new novel dataset called COVAX-Reality containing COVID-19 vaccine-related news has been *** the COVAX-Reality dataset,the performance of FNEC is compared to several traditional learning models i.e.,Support Vector Machine(SVM),Naive Bayes(NB),Passive Aggressive Classifier(PAC),Long Short-Term Memory(LSTM),Bi-directional LSTM(Bi-LSTM)and Bi-directional Encoder Representations from Transformers(BERT).For the evaluation of FNEC,standard metrics(Precision,Recall,Accuracy,and F1-Score)were utilized.

关键词： Deep learning fake news detection machine learning transformer model classification

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A decision model for decentralized autonomous organization platform selection: Three industry case studies

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Blockchain(Research and Applications) 2023年第2期4卷 82-100页

作者： E.Baninemeh S.Farshidi S.Jansen Department of Information and Computer Science Utrecht UniversityUtrechtthe Netherlands Department of Software Engineering Lappeenranta University of TechnologyLappeenrantaFinland

Context:Decentralized autonomous organizations are a new form of smart contract-based *** autonomous organization platforms,which support the creation of such organizations,are becoming increasingly popular,such as Aragon and *** the best fitting platform is challenging for organizations,as a significant number of decision criteria,such as popularity,developer availability,governance issues and consistent documentation of such platforms,should be ***,decision-makers at the organizations are not experts in every domain,so they must continuously acquire volatile knowledge regarding such ***:Supporting decision-makers in selecting the right decentralized autonomous organization platforms by designing an effective decision model is the main objective of this *** aim to provide more insight into their selection process and reduce time and effort significantly by designing a decision ***:This study presents a decision model for the decentralized autonomous organization platform selection *** decision model captures knowledge regarding such platforms and concepts *** model is based on an existing theoretical framework that assists software engineers with a set of multi-criteria decision-making problems in software ***:We conducted three industry case studies in the context of three decentralized autonomous organizations to evaluate the effectiveness and efficiency of the decision model in assisting *** case study participants declared that the decision model provides significantly more insight into their selection process and reduces time and ***:We observe in the empirical evidence from the case studies that decision-makers can make more rational,efficient,and effective decisions with the decision ***,the reusable form of the captured knowledge regarding decentralized autonomous organization platforms can be

关键词： Decentralized autonomous organization Decision model Multi-criteria decision making Decision support system Decentralized autonomous organization platform Case study research

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LQG Problem of Descriptor Systems and Separation Principle 63

LQG Problem of Descriptor Systems and Separation Principle

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Nosrati, Komeil Belikov, Juri Tepljakov, Aleksei Petlenkov, Eduard Tallinn University of Technology Department of Computer Systems Estonia Tallinn University of Technology Department of Software Science Estonia

ISBN: (纸本)9798350316339

The performance of linear-quadratic regulators (LQRs), which possess robustness with guaranteed levels of gain and phase margin, will be affected by incomplete state information. By furnishing this regulator with a linear-quadratic estimator (LQE), a recursive algorithm with an optimal feedback law can be obtained. Notwithstanding this, the optimal operation of this so-called linear-quadratic Gaussian (LQG) algorithm might be compromised in transformed stochastic descriptor systems if constraints are violated. Inspired by recent results in stochastic control, we deal with the LQG problem using a direct strategy without any transformations and regularity assumptions. First, an expected quadratic cost function using a regularized least-squares is formulated. Using the estimated states with a designed LQE, we then connect the formulation to a constrained recursive minimization problem under Bellman's principle. To accomplish this, a dynamic programming approach is used in a backward policy within a finite horizon to develop an LQG algorithm for the original system. We conclude the study by stating the separation principle of optimal control and state estimation and verifying the results, where despite noisy measurements, the controller effectively track the reference position while stabilizing the DC motor. © 2024 IEEE.

关键词： Cost functions

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Introduction to the Special Issue on Formal Methods and Models for System Design

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ACM Transactions on Embedded Computing Systems 2025年第3期24卷 1-3页

作者： Brandt, Jens Saha, Indranil Zhang, Lijun Hochschule Niederrhein Krefeld Germany Department of Computer Science and Engineering Indian Institute of Technology Kanpur Kanpur India State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

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An Advanced Bald Eagle Search Algorithm for Image Enhancement

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computers, Materials & Continua 2025年第3期82卷 4485-4501页

作者： Pei Hu Yibo Han Jeng-Shyang Pan School of Computer and Software Nanyang Institute of TechnologyNanyang473004China College of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210044China Department of Information Management Chaoyang University of TechnologyTaichung413310Taiwan

Image enhancement utilizes intensity transformation functions to maximize the information content of enhanced *** paper approaches the topic as an optimization problem and uses the bald eagle search(BES)algorithm to achieve optimal *** our proposed model,gamma correction and Retinex address color cast issues and enhance image edges and *** final enhanced image is obtained through color *** BES algorithm seeks the optimal solution through the selection,search,and swooping ***,it is prone to getting stuck in local optima and converges *** overcome these limitations,we propose an improved BES algorithm(ABES)with enhanced population learning,position updates,and control *** is employed to optimize the core parameters of gamma correction and Retinex to improve image quality,and the maximization of information entropy is utilized as the objective *** benchmark images are collected to validate its *** results demonstrate that ABES outperforms the existing image enhancement methods,including the flower pollination algorithm,the chimp optimization algorithm,particle swarm optimization,and BES,in terms of information entropy,peak signal-to-noise ratio(PSNR),structural similarity index(SSIM),and patch-based contrast quality index(PCQI).ABES demonstrates superior performance both qualitatively and quantitatively,and it helps enhance prominent features and contrast in the images while maintaining the natural appearance of the original images.

关键词： Image enhancement gamma correction retinex bald eagle search algorithm

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The Design of Continuous Surgical Robotic Arms with Variable Stiffness Material and Magnetic Guidance 5

The Design of Continuous Surgical Robotic Arms with Variable...

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5th International Conference on Signal Processing and Machine Learning, CONF SPML 2025

作者： Zhang, Yixin Department of Computer Science and Software Engineering Hebei University of Technology Hebei Langfang065000 China

ISBN: (纸本)9781837243235

In recent years, with the aging population and the increasing incidence of natural cavity diseases and cancer tumors, the demand for minimally invasive surgery has risen. This, in turn, requires robotic arms with greater flexibility and precision. However, traditional rigid surgical robotic arms make it difficult to meet these needs. This paper includes an illustration of the invention related to a continuous surgical robotic arm which is combined with magnetic guidance and a variable stiffness material. This paper aims to explore the advantages of continuum robots based on Phase Change Materials (PCMs) in surgical applications, especially through the stiffness adjustability of the material and the combination of magnetic materials to improve positioning accuracy. In this study, low-melting-point alloys were chosen as the variable stiffness material. This paper analyzed a flexible and precise surgical robotic arm by summarizing and combining previous experiments on the properties of low-melting alloys under different conditions and simulating magnetic navigation in complex environments. Through this design, the robots can enhance the safety, versatility and collaboration ability among the continuous robots, opening up new ways for endocavitary robotic surgery. © The Institution of Engineering & technology 2025.

关键词： Robotic arms

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Path Selection Optimization Algorithms for Mobile Agent Based on Push-All-Data Strategy

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2025年第10期19卷 112-128页

作者： Alzyoud, Faisal Tarawneh, Monther Al-Shrouf, Faiz Almaghthawi, Ahmed Alrehaili, Meaad Kanaker, Hasan Department of Computer Science Isra University Amman Jordan Department of Information Technology College of Information Technology and Communications Tafila Technical University Tafila Jordan Department of Software Engineering Faculty of Information Technology Isra University Amman Jordan Department of Computer Science College of Science & Art at Mahayil King Khalid University Abha62529 Saudi Arabia Department of Computer Sciences and Artificial Intelligence Collège of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Department of Information Security Faculty of Information Technology Petra University Amman Jordan

With the advent of 5G and 6G technologies and the growing ubiquity of the Internet, the Mobile Agent (MA) paradigm is increasingly seen as a promising alternative to the conventional client-server model. MAs, which are software entities capable of moving and processing data across different systems, offer potential efficiencies in data management. However, their operation in dynamic and mobile environments can lead to challenges, such as incomplete or delayed tasks. This study addresses these issues by focusing on reducing the relocation time of MAs. A numerical procedure and a streamlining strategy were developed to expedite the transfer of an agent from the source to the target hub. Utilizing the itinerary design pattern and the Ant Colony Optimization (ACO) algorithm, implemented via the Java Agent Development Framework (JADE), this study sought the most efficient path for the MA. The proposed algorithm demonstrated a significant improvement, selecting the optimal path in just 271.511 seconds. This performance represents a substantial enhancement over previous approaches using the master-slave design pattern with either the Genetic Algorithm (GA) or the Node Compression Algorithm (NCA). The implications of this improvement are far-reaching, potentially enhancing the efficiency and reliability of data management systems in a variety of applications. © 2025 by the authors of this article. Published under CC-BY.

关键词： Information management

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A Survey of Edge Caching:Key Issues and Challenges

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Tsinghua science and technology 2024年第3期29卷 818-842页

作者： Hanwen Li Mingtao Sun Fan Xia Xiaolong Xu Muhammad Bilal School of Computer Science Nanjing University of Information Science and TechnologyNanjing 210044China Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 262700China Reading Academy Nanjing University of Information Science and TechnologyNanjing 210044China School of Software Nanjing University of Information Science and TechnologyNanjing 210044China Department of Computer Engineering Hankuk University of Foreign StudiesYongin-si 17035Republic of Korea

With the rapid development of mobile communication technology and intelligent applications,the quantity of mobile devices and data traffic in networks have been growing exponentially,which poses a great burden to networks and brings huge challenge to servicing user *** caching,which utilizes the storage and computation resources of the edge to bring resources closer to end users,is a promising way to relieve network burden and enhance user *** this paper,we aim to survey the edge caching techniques from a comprehensive and systematic *** first present an overview of edge caching,summarizing the three key issues regarding edge caching,i.e.,where,what,and how to cache,and then introducing several significant caching *** then carry out a detailed and in-depth elaboration on these three issues,which correspond to caching locations,caching objects,and caching strategies,*** particular,we innovate on the issue“what to cache”,interpreting it as the classification of the“caching objects”,which can be further classified into content cache,data cache,and service ***,we discuss several open issues and challenges of edge caching to inspire future investigations in this research area.

关键词： edge caching edge computing caching location caching object caching strategy 5G networkarchitecture Internet of Things(IoT)

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GliomaCNN: An Effective Lightweight CNN Model in Assessment of Classifying Brain Tumor from Magnetic Resonance Images Using Explainable AI

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computer Modeling in Engineering & sciences 2024年第9期140卷 2425-2448页

作者： Md.Atiqur Rahman Mustavi Ibne Masum Khan Md Hasib M.F.Mridha Sultan Alfarhood Mejdl Safran Dunren Che Department of Computer Science and Engineering Ahsanullah University of Science and TechnologyDhaka1208Bangladesh Department of Computer Science and Software Engineering The University of Western AustraliaPerthWA 6009Australia Department of Computer Science American International University-BangladeshDhaka1229Bangladesh Department of Computer Science College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia School of Computing Southern Illinois UniversityCarbondale62901USA

Brain tumors pose a significant threat to human lives and have gained increasing attention as the tenth leading cause of global *** study addresses the pressing issue of brain tumor classification using Magnetic resonance imaging(MRI).It focuses on distinguishing between Low-Grade Gliomas(LGG)and High-Grade Gliomas(HGG).LGGs are benign and typically manageable with surgical resection,while HGGs are malignant and more *** research introduces an innovative custom convolutional neural network(CNN)model,*** stands out as a lightweight CNN model compared to its *** research utilized the BraTS 2020 dataset for its *** with the gradient-boosting algorithm,GliomaCNN has achieved an impressive accuracy of 99.1569%.The model’s interpretability is ensured through SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation Mapping(Grad-CAM++).They provide insights into critical decision-making regions for classification *** challenges in identifying tumors in images without visible signs,the model demonstrates remarkable performance in this critical medical application,offering a promising tool for accurate brain tumor diagnosis which paves the way for enhanced early detection and treatment of brain tumors.

关键词： Deep learning magnetic resonance imaging convolutional neural networks explainable AI boosting algorithm ablation

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