检索结果-内蒙古大学图书馆

Resource allocation strategy in fog computing

International Journal of Industrial and Systems engineering 2025年第2期50卷 234-252页

作者： Patil-Karpe, Sharmila Brahmananda, S.H. Department of Computer Science and Engineering GITAM School of Technology GITAM University Bangalore Campus Karnataka India Department of Information Technology Walchand Institute of Technology Maharashtra Solapur India

The idea of fog computing enables the delivery of computational services and resources closer to the endpoints and users, at the network’s edge. Due to the large number of devices, determining the best resource allocation in this situation is challenging. Accordingly, a unique resource allocation strategy for fog computing is suggested in this work. The resource allocation of fog computing is made possible by the modelling of a nonlinear functionality under the objective function comprising metrics like service response rate, execution time, make span, resource consumption, and reboot rate. The proposed approach also takes consideration for the allocation of resources in urgent scenarios that allow for quick resource distribution. Considering this as the optimisation problem, a new optimisation model termed as hybrid coati insisted beluga whale optimisation (HCIBWO) is introduced in this work. The performance of proposed work is evaluated over the conventional models in terms of different measures. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

Gannet Optimization Algorithm Enhanced by Quasi-Affine Transformation Algorithm and Its Application in 3D Coverage of Wireless Sensor Network

Journal of Network Intelligence

引用

Journal of Network Intelligence 2024年第1期9卷 69-87页

作者： Peng, Yun-Feng Chu, Shu-Chuan Wang, Ru-Yu Zhao, Jia Pan, Jeng-Shyang School of Computer Science Northeast Electric Power University Jilin132012 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China School of Information Engineering Nanchang Institute of Technology Nanchang330099 China Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan

The gannet optimization algorithm (GOA) is an effective group intelligence algorithm inspired by the foraging behavior of gannets. Despite its merits, considerable potential exists for enhancing its exploration and convergence capabilities. A gannet optimization algorithm improved by the quasi-affine transformation evolutionary algorithm, restart strategy, and elite selection strategy (QRE-GOA) is proposed in this paper. The algorithm employs the quasi-affine transformation evolutionary algorithm (QUATRE) to matrix the gannet optimization algorithm to search for optimal solutions more accurately. The use of a restart strategy and elite selection can be more effective in preventing the algorithm from falling into local optimal solutions. Comparative experiments were conducted using the CEC2017 benchmark series. A detailed analysis was conducted, we per-formed a detailed analysis to check the accuracy and convergence speed of the algorithm search in different dimensions. Subsequently, a comprehensive analysis was undertaken to assess the accuracy and convergence speed of the algorithm’s search process across various dimensions. The experimental statistical results show that the new algorithm has stronger exploration ability and better convergence ability than the original algorithm. In addition, this paper focuses on process justification so that the experimental results are reliable, trustworthy, and interpretable. Finally, the newly proposed QRE-GOA algorithm is deployed to address the 3D Coverage challenge in Wireless Sensor Networks. Experimental findings unequivocally demonstrate the superior performance of QRE-GOA. These results, underscore its potential for addressing existing limitations in optimization methods. © 2024, Taiwan Ubiquitous information CO LTD. All rights reserved.

关键词： Evolutionary algorithms

来源：评论

学校读者我要写书评

暂无评论

Enhancing Medical Image Classification with BSDA-Mamba:Integrating Bayesian Random Semantic Data Augmentation and Residual Connections

引用

computers, Materials & Continua 2025年第6期83卷 4999-5018页

作者： Honglin Wang Yaohua Xu Cheng Zhu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210044China School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Electrical&Computer Engineering University of Illinois at Urbana ChampaignUrbanaIL 61801USA

Medical image classification is crucial in disease diagnosis,treatment planning,and clinical *** introduced a novel medical image classification approach that integrates Bayesian Random Semantic Data Augmentation(BSDA)with a Vision Mamba-based model for medical image classification(MedMamba),enhanced by residual connection blocks,we named the model *** augments medical image data semantically,enhancing the model’s generalization ability and classification ***,a deep learning-based state space model,excels in capturing long-range dependencies in medical *** incorporating residual connections,BSDA-Mamba further improves feature extraction *** comprehensive experiments on eight medical image datasets,we demonstrate that BSDA-Mamba outperforms existing models in accuracy,area under the curve,and *** results highlight BSDA-Mamba’s potential as a reliable tool for medical image analysis,particularly in handling diverse imaging modalities from X-rays to *** open-sourcing of our model’s code and datasets,will facilitate the reproduction and extension of our work.

关键词： Deep learning medical image classification data augmentation visual state space model

来源：评论

学校读者我要写书评

暂无评论

VivID: A Visually Improved GIF Encoding Network Design

引用

IEEE Transactions on Circuits and Systems for Video technology 2025年第6期35卷 6101-6113页

作者： Wang, Yifei Liu, Gaozhi Zhu, Zhiying Zhang, Xinpeng Qian, Zhenxing Fudan University School of Computer Science Shanghai200433 China East China University of Science and Technology School of Information Science and Engineering Shanghai200237 China

Graphics Interchange Format (GIF) encoding is the art of reproducing an image with limited colors. Existing GIF encoding schemes often introduce unpleasant visual artifacts such as banding artifact, dotted-pattern noise and color shift, especially when the palette size is small. To address the issues above, we propose VivID, a Visually Improved GIF Encoding Network Design, which is compatible with exiting GIF decoders. VivID consists of three modules and two of them provide the functionality within the GIF encoding pipeline. Firstly, in order to reduce the color shift introduced by color quantization, we design the multi-palette extractor to create a GIF image with minimal distortion by extracting a near-optimal palette. This module can significantly improve the image fidelity and gains adaptability to multiple palette sizes after only one-time training. Furthermore, to reduce banding artifact and the dotted-pattern noise caused by dithering process, we propose banding remover which can randomize quantization error to neighbourhood by utilizing a learnable dithering pattern. Moreover, to further eliminate the banding artifacts, we design the banding scorer module, which is a novel metric for evaluating banding artifact and it correlates well with subjective perception. We adopt it as a customized loss for training dithering module. Extensive experiments across various aspects demonstrate that VivID produces visually pleasing results even when the palette size is extremely small, outperforming both traditional and existing learning based GIF encoding methods. © 1991-2012 IEEE.

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

Propagation-Based Code Clone Analysis for Detecting Smart Contract Vulnerability

引用

IEICE Transactions on information and Systems 2025年第6期E108.D卷 634-639页

作者： Zhang, Zhuo Li, Donghui Jiang, Kun Li, Ya Wang, Junhu Meng, Xiankai School of Electrical and Information Engineering Tianjin University Tianjin30072 China School of Computer Science and Engineering Xian University of Technolog Xian710000 China Ningbo Artificial Intelligence Institute Shanghai Jiaotong University Ningbo315000 China School of Information Technology and Engineering Guangzhou College of Commerce Guangzhou510000 China College of Computer and Information Engineering Polytechnic University Shanghai200127 China

Smart contracts are self-executing programs that operate on a blockchain. Once deployed, they cannot be altered, which introduces distinct maintenance challenges unlike those found in traditional software systems. Bugs and vulnerabilities in smart contracts have led to significant economic losses, drawing increased attention to their security. The immutability of smart contracts has made thorough security checks prior to deployment a priority. In this paper, we introduce a smart contract timestamp vulnerability detection technique PropaDT with propagation-based code clone analysis. The core idea of this technique involves using dataflow analysis based on an Abstract Syntax Tree (AST) to extract propagation chains that reveal how variables interact, potentially leading to vulnerabilities. Next, we extract code snippets based on the propagation chains and compare them with known vulnerability patterns in a database. This allows us to determine whether the tested smart contract contains a timestamp vulnerability, facilitating the detection of potential timestamp vulnerabilities in the code. Copyright © 2025 The Institute of Electronics, information and Communication Engineers.

关键词： Data flow analysis

来源：评论

学校读者我要写书评

暂无评论

On Designs of Decentralized Reputation Management for Permissioned Blockchain Networks

引用

computer Modeling in engineering & Sciences 2024年第5期139卷 1755-1773页

作者： Jinyu Chen Long Shi Qisheng Huang Taotao Wang Daojing He School of Electronic and Optical Engineering Nanjing University of Science and TechnologyNanjing210094China School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen518055China College of Electronics and Information Engineering Shenzhen UniversityShenzhen518060China School of Computer Science and Technology Harbin Institute of TechnologyShenzhen518055China

In permissioned blockchain networks,the Proof of Authority(PoA)consensus,which uses the election of authorized nodes to validate transactions and blocks,has beenwidely advocated thanks to its high transaction throughput and fault ***,PoA suffers from the drawback of centralization dominated by a limited number of authorized nodes and the lack of anonymity due to the round-robin block proposal *** a result,traditional PoA is vulnerable to a single point of failure that compromises the security of the blockchain *** address these issues,we propose a novel decentralized reputation management mechanism for permissioned blockchain networks to enhance security,promote liveness,and mitigate centralization while retaining the same throughput as traditional *** paper aims to design an off-chain reputation evaluation and an on-chain reputation-aided ***,we evaluate the nodes’reputation in the context of the blockchain networks and make the reputation globally verifiable through smart ***,building upon traditional PoA,we propose a reputation-aided PoA(rPoA)consensus to enhance securitywithout sacrificing *** particular,rPoA can incentivize nodes to autonomously form committees based on reputation authority,which prevents block generation from being tracked through the randomness of reputation ***,we develop a reputation-aided fork-choice rule for rPoA to promote the network’s ***,experimental results show that the proposed rPoA achieves higher security performance while retaining transaction throughput compared to traditional PoA.

关键词： Blockchain reputation management PoA throughput security decentralization

来源：评论

学校读者我要写书评

暂无评论

Feature selection for determining input parameters in antenna modeling

引用

Journal of Systems engineering and Electronics 2025年第1期36卷 15-23页

作者： LIU Zhixian SHAO Wei CHENG Xi OU Haiyan DING Xiao School of Physics University of Electronic Science and Technology of ChinaChengdu 611731China School of Computer and Information Engineering Xinjiang Agricultural UniversityUrumqi 830052China

In this paper,a feature selection method for determining input parameters in antenna modeling is *** antenna modeling,the input feature of artificial neural network(ANN)is geometric *** selection criteria contain correlation and sensitivity between the geometric parameter and the electromagnetic(EM)*** information coefficient(MIC),an exploratory data mining tool,is introduced to evaluate both linear and nonlinear *** EM response range is utilized to evaluate the *** wide response range corresponding to varying values of a parameter implies the parameter is highly sensitive and the narrow response range suggests the parameter is *** the parameter which is highly correlative and sensitive is selected as the input of ANN,and the sampling space of the model is highly *** modeling of a wideband and circularly polarized antenna is studied as an example to verify the effectiveness of the proposed *** number of input parameters decreases from8 to *** testing errors of|S_(11)|and axis ratio are reduced by8.74%and 8.95%,respectively,compared with the ANN with no feature selection.

关键词： antenna modeling artificial neural network(ANN) feature selection maximal information coefficient(MIC)

来源：评论

学校读者我要写书评

暂无评论

Cat Swarm Algorithm Generated Based on Genetic Programming Framework Applied in Digital Watermarking

引用

computers, Materials & Continua 2025年第5期83卷 3135-3163页

作者： Shu-Chuan Chu Libin Fu Jeng-Shyang Pan Xingsi Xue Min Liu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210000China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266000China Department of Information Management Chaoyang University of TechnologyTaichung40601TaiwanChina School of Information Science and Engineering Fujian University of TechnologyFuzhou350000China Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resource Nanjing University of Information Science and TechnologyNanjing210000China

Evolutionary algorithms have been extensively utilized in practical ***,manually designed population updating formulas are inherently prone to the subjective influence of the *** programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world *** paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human *** modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the *** designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update *** Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the *** validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark ***,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking *** experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.

关键词： Cat swarm algorithm genetic programming digital watermarking update mode mode generation framework

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Based Diabetes Detection Model for False Negative Reduction

引用

Biomedical Materials and Devices 2024年第1期2卷 427-443页

作者： Uddin, Md. Ashraf Islam, Md. Manowarul Talukder, Md. Alamin Hossain, Md. Al Amin Akhter, Arnisha Aryal, Sunil Muntaha, Maisha School of Information Technology Deakin University Department of Computer Science and Engineering Jagannath University

Diabetes is a chronic disease characterized by the inability of the pancreas to produce enough insulin or the body’s inability to use insulin efficiently. This disease is becoming increasingly prevalent worldwide and can result in severe complications such as blindness, kidney failure, and stroke. Early detection of diabetes can potentially save millions of lives globally, making it a crucial focus of research. In this study, we propose a machine learning model to aid in predicting diabetes. The model comprises several machine learning methods: Linear Regression (LnR), Logistic Regression (LR), k-nearest neighbor (KNN), Naive Bayes (NB), Random Forest (RF), Support Vector Machine (SVM), and Decision Tree (DT). Prior to feeding the pre-processed data into the machine learning model for evaluation, we conducted several pre-processing steps, such as removing null values, standardizing data using normalization, and labeling data using the label encoding process. Imbalanced datasets can adversely affect the accuracy of machine learning algorithms, and we address this problem by balancing the datasets using the Synthetic Minority Oversampling Technique (SMOTE) method. We assessed the model’s performance on two datasets and found that the random forest algorithm produced optimal results, with 97% accuracy on the diabetes dataset 2019 and 80% accuracy on the Pima Indian dataset. However, using a balanced dataset, we can significantly reduce the number of false-negative detections. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC 2023.

关键词： Balance data Features selection Machine learning Pre-processed data Random forest SMOTE

来源：评论

学校读者我要写书评

暂无评论

A Frog-Shaped UWB MIMO Antenna Design for 5G

引用

Progress in Electromagnetics Research C 2025年 151卷 101-112页

作者： Yao, Shanhua Yang, Tianchu Qiu, Xiaorong Li, Xiang School of Electrical and Information Engineering Anhui University of Science and Technology Huainan232001 China School of Computer Science Huainan Normal University Huainan232001 China

In this paper, a frog-shaped ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna is proposed for 5G applications in the n77, n78, n79, and 6 GHz bands with a compact antenna structure of 31 × 55 × 1.5 mm3. The designed antenna consists of two frog-shaped monopole antennas and a floor from which a part has been removed, and the operating bandwidths range from 3.05 to 13.38 GHz, which meets the design criteria for UWB. The T-shaped floor with two T-shaped slots impedes the flow of coupling currents and improves the isolation of the antenna. This results in an isolation of less than −17 dB over the entire operating bandwidth and less than −20 dB in the 5G band. In addition, the envelope correlation coefficient (ECC) is less than 0.007, the diversity gain (DG) more than 9.96, the total active reflection coefficient (TARC) less than −30 dB, and the channel capacity loss (CCL) less than 0.34 bit/s/Hz. The measured and simulated results agree with each other, demonstrating the antenna’s potential application in 5G communication systems. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Bandwidth

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：