检索结果-内蒙古大学图书馆

A Novel Hybrid Approach-Based on Heartbeat and Accelerometer Signals for Enhanced Security in WBSNs

IEEE Sensors Journal 2025年第6期25卷 10295-10308页

作者： Yan, Guixiang Zhang, Guanghe Liu, Fanghua Williams Samuel, Oluwarotimi Aborokbah, Majed Guo, Jiquan Zhu, Liqing Wei, Sikang Jiangxi Normal University School of Computer and Information Engineering Nanchang330022 China University of Derby School of Computing and Data Science Research Centre DerbyDE22 3AW United Kingdom INTI International University Faculty of Data Science and Information Technology Nilai71800 Malaysia University of Tabuk Faculty of Computers and Information Technology Tabuk71491 Saudi Arabia Jiangxi Normal University School of Digital Industry Shangrao334000 China

In wireless body sensor networks (WBSNs), ensuring secure and efficient key distribution is critical, particularly given the limited computational and energy resources of the sensors. Existing methods often struggle to balance security with these resource constraints, especially in environments involving physiological data such as acceleration (ACC) and electrocardiogram (ECG) signals. For the first time, this study proposes a novel hybrid approach that integrates fuzzy commitment with ACC signal noise and ECG features for efficient key generation and distribution in WBSNs. By employing a low-pass filter to process ACC signal noise, we generated highly random binary sequences (BSs), leveraging the inherent randomness of the signal for secure key generation. Concurrently, an optimized coding scheme was built for ECG feature construction to ensure secure key distribution between devices. Extensive experiments, including entropy analysis and National Institute of Standards and Technology (NIST) statistical tests, confirm the robustness and security of our method. The proposed scheme achieves a false acceptance rate (FAR) of 5.23%, demonstrating superior performance across multiple databases in comparison to benchmark approaches. This novel dual-key generation strategy that combines the unpredictability of ACC noise with the individual-specific traits of ECG signals can significantly enhance the security, applicability, and versatility of WBSNs. © 2001-2012 IEEE.

关键词： Acceptance tests

来源：评论

学校读者我要写书评

暂无评论

Energy Theft Detection in Smart Grids with Genetic Algorithm-Based Feature Selection

引用

Computers, Materials & Continua 2023年第3期74卷 5431-5446页

作者： Muhammad Umair Zafar Saeed Faisal Saeed Hiba Ishtiaq Muhammad Zubair Hala Abdel Hameed Faculty of Information Technology University of Central PunjabLahore54590Pakistan DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirmingham B47XGUK Faculty of Computer and Information Systems Fayoum University63514Egypt Khaybar Applied College Taibah UniversitySaudi Arabia

As big data,its technologies,and application continue to advance,the Smart Grid(SG)has become one of the most successful pervasive and fixed computing platforms that efficiently uses a data-driven approach and employs efficient information and communication technology(ICT)and cloud *** a result of the complicated architecture of cloud computing,the distinctive working of advanced metering infrastructures(AMI),and the use of sensitive data,it has become challenging tomake the SG *** of the SG are categorized into two main categories,Technical Losses(TLs)and Non-Technical Losses(NTLs).Hardware failure,communication issues,ohmic losses,and energy burnout during transmission and propagation of energy are ***’s are human-induced errors for malicious purposes such as attacking sensitive data and electricity theft,along with tampering with AMI for bill reduction by fraudulent *** research proposes a data-driven methodology based on principles of computational intelligence as well as big data analysis to identify fraudulent customers based on their load *** our proposed methodology,a hybrid Genetic Algorithm and Support Vector Machine(GA-SVM)model has been used to extract the relevant subset of feature data from a large and unsupervised public smart grid project dataset in London,UK,for theft detection.A subset of 26 out of 71 features is obtained with a classification accuracy of 96.6%,compared to studies conducted on small and limited datasets.

关键词： Big data data analysis feature engineering genetic algorithm machine learning

来源：评论

学校读者我要写书评

暂无评论

Job Generator for Evaluating and Comparing Scheduling Algorithms for Modern GPU Clouds 15

Job Generator for Evaluating and Comparing Scheduling Algori...

引用

15th International Conference on Cloud computing and Services science, CLOSER 2025

作者： Konopa, Michal Fesl, Jan Beránek, Ladislav Department of Data Science and Computing Systems Faculty of Agriculture and Technology University of South Bohemia České Budějovice Czech Republic

ISBN: (纸本)9789897587474

The steep technological and performance advances in GPU cards have led to their increasing use in data centers in the recent years, especially in machine learning jobs. However, high hardware performance alone does not guarantee (sub) optimal utilization of computing resources, especially when the cost associated with power consumption also needs to be increasingly considered. As consequence of these realities, various job scheduling algorithms have been and are being developed to optimize the power consumption in data centers with respect to defined constraints. Unfortunately, there is still no known, widely used, parametrizable dataset that serves as a de facto standard for simulating scheduling algorithms and the resulting ability to compare their performance against each other. The goal of this paper is to describe a simple job set generator designed to run on modern GPU architectures and to introduce the newly created data set suitable for evaluation the scheduling algorithms. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Multi-View Dynamic Kernelized Evidential Clustering

引用

IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2435-2450页

作者： Jinyi Xu Zuowei Zhang Ze Lin Yixiang Chen Weiping Ding the Software Engineering Institute East China Normal UniversityShanghai 200062 Shanghai Key Laboratory of Trustworthy Computing East China Normal UniversityShanghai 200062China IEEE the School of Automation Northwestern Polytechnical UniversityXi’an 710072China the School of Artificial Intelligence and Computer Science Nantong UniversityNantong 226019 the Faculty of Data Science City University of MacaoMacao 999078China

It is challenging to cluster multi-view data in which the clusters have overlapping *** multi-view clustering methods often misclassify the indistinguishable objects in overlapping areas by forcing them into single clusters,increasing clustering *** solution,the multi-view dynamic kernelized evidential clustering method(MvDKE),addresses this by assigning these objects to meta-clusters,a union of several related singleton clusters,effectively capturing the local imprecision in overlapping *** offers two main advantages:firstly,it significantly reduces computational complexity through a dynamic framework for evidential clustering,and secondly,it adeptly handles non-spherical data using kernel techniques within its objective *** on various datasets confirm MvDKE's superior ability to accurately characterize the local imprecision in multi-view non-spherical data,achieving better efficiency and outperforming existing methods in overall performance.

关键词： Evidential clustering imprecision characterizing kernel technique multi-view clustering

来源：评论

学校读者我要写书评

暂无评论

Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications

引用

Digital Communications and Networks 2023年第2期9卷 367-382页

作者： Qusay M.Salih Md Arafatur Rahman A.Taufiq Asyhari Muhammad Kamran Naeem Mohammad Patwary Ryan Alturki Mohammed Abdulaziz Ikram Faculty of Computing Universiti Malaysia Pahang26300GambangPahangMalaysia School of Engineering Computing and Mathematical SciencesUniversity of WolverhamptonUK Data Science Program Monash UniversityIndonesiaand Birmingham City UniversityB47XGUK Department of Information Science College of Computer and Information SystemsUmm Al-Qura UniversitySaudi Arabia Computer Science Department Al Jumoum University CollegeUmm Al-Qura UniversitySaudi Arabia

Cognitive Radio Networks(CRNs)have become a successful platform in recent years for a diverse range of future systems,in particularly,industrial internet of things(IIoT)*** order to provide an efficient connection among IIoT devices,CRNs enhance spectrum utilization by using licensed ***,the routing protocol in these networks is considered one of the main problems due to node mobility and time-variant channel ***,the channel selection for routing protocol is indispensable in CRNs to provide an adequate adaptation to the Primary User(PU)activity and create a robust routing *** study aims to construct a robust routing path by minimizing PU interference and routing delay to maximize throughput within the IIoT ***,a generic routing framework from a cross-layer perspective is investigated that intends to share the information resources by exploiting a recently proposed method,namely,Channel Availability ***,a novel cross-layer-oriented routing protocol is proposed by using a time-variant channel estimation *** protocol combines lower layer(Physical layer and data Link layer)sensing that is derived from the channel estimation ***,it periodically updates and stores the routing table for optimal route ***,in order to achieve higher throughput and lower delay,a new routing metric is *** evaluate the performance of the proposed protocol,network simulations have been conducted and also compared to the widely used routing protocols,as a *** simulation results of different routing scenarios demonstrate that our proposed solution outperforms the existing protocols in terms of the standard network performance metrics involving packet delivery ratio(with an improved margin of around 5–20%approximately)under varying numbers of PUs and cognitive users in Mobile Cognitive Radio Networks(MCRNs).Moreover,the cross-layer routing protocol successfully achiev

关键词： Channel selection Cross-layer design Mobile cognitive radio networks Routing protocol IIoT applications

来源：评论

学校读者我要写书评

暂无评论

Improving the Cost of Updates in Virtual Knowledge Graphs

Improving the Cost of Updates in Virtual Knowledge Graphs

引用

2024 Joint Ontology Workshops - Episode X: The Tukker Zomer of Ontology, and Satellite Events, JOWO 2024

作者： Wandji, Romuald Esdras Calvanese, Diego Department of Computing Science Umeå Universitet Umeå Sweden Research Centre for Knowledge and Data Faculty of Engineering Free University of Bozen-Bolzano Bolzano Italy

Virtual Knowledge Graph (VKG) is known as a data integration paradigm used to efficiently manage the heterogeneity of richly structured data that is common inside several organizations, in inter-organizational settings, and more openly on the Web. Although such a paradigm continues to gain importance in both foundational and applied research, updates in VKG systems remain an open challenge that has received less attention. Yet, a solution to such a problem would be of great importance, as it would allow VKG systems to be full-fledged, thus allowing end-users to fully manage source data through the lens of the ontology they are exposed to. This research aims to propose a comprehensive framework for instance-level updates in VKGs, where updates posed over the ontology have to be translated into source-level updates and, more importantly, how the side effects related to the propagation of ontology-based updates to the underlying data source can be minimized. © 2024 Copyright for this paper by its authors.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

The optimal scaling factor based on Secant Method for image watermarking using the hybrid DTCWT-DCT domain.

Iraqi Journal for Computer Science and Mathematics

引用

Iraqi Journal for Computer science and Mathematics 2024年第1期5卷 237-262页

作者： Lebcir, Mohamed Awang, Suryanti Benziane, Ali Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Pekan26600 Malaysia Center of Excellence for Artificial Intelligence & Data Science Universiti Malaysia Pahang Al-Sultan Abdullah Lebuh Persiaran Tun Khalil Yaakob Pahang Kuantan26300 Malaysia Faculty of Science and Technology University of Djelfa Algeria

This paper proposes an implementation of the secant optimization method on the watermark embedding in DTCWT domain. An objective function combining PSNR and NC (The Normalized Correlation) values calculated for a set of common attacks is used in the optimization process. The aim is to enhance the tradeoff between robustness and imperceptibility against the various image processing attacks via an automatic and careful selection of the scaling factor using optimization. The watermark is inserted in the high energy bands of DCT-transformed sub-vectors, which were generated from the DTCWT coefficient decomposition of the host image. Experimental results performed on a set of 512×512 greyscale images, show better results than the existing schemes for most common image attacks such as compression, low-pass filtering and noise addition. © 2024 College of Education, Al-Iraqia university. All rights reserved.

关键词： Image watermarking

来源：评论

学校读者我要写书评

暂无评论

A Survey on Usage of Multimedia databases for Emotion Elicitation: A Quantitative Report on How Content Diversity Can Improve Performance 46

A Survey on Usage of Multimedia Databases for Emotion Elicit...

引用

46th ICT and Electronics Convention, MIPRO 2023

作者： Horvat, M. Jercic, P. University of Zagreb Faculty of Electrical Engineering and Computing Department of Applied Computing Zagreb Croatia Graz University of Technology Institute of Interactive Systems and Data Science Graz Austria

ISBN: (纸本)9789532331042

Affective picture databases provide a standardized set of images to elicit controlled and consistent emotional responses in research participants. They are a valuable tool for studying various emotion-related phenomena across several research domains. These domains include emotion perception, emotion regulation, and the neural basis of emotion. However, affective picture databases have diverse schemas, structures, and content, making them difficult to use. Searching and retrieving optimal pictures relevant to affective stimulation may be challenging and time-consuming. In this context, we surveyed domain experts about their practices and experiences working with affective multimedia databases such as IAPS, NAPS, OASIS, GAPED, and others. The survey identified a need for novel data observatory software. This finding motivates the authors' intention to develop and validate such software platform that relies on AI. Such a platform would describe better, retrieve, and integrate various semi-structured affective multimedia datasets. The results prominently indicate the overwhelming dissatisfaction regarding stimuli content diversity and cultural bias, specifically regarding emotional and semantic context. The main driver of satisfaction from users of existing automated retrieval software is the quality of semantic descriptors available. This points to the direction AI should take in novel data observatory software. This survey follows up on a similar survey conducted ten years ago and explores the differences in researchers' opinions and experiences during that time. The complete aggregated results are publicly available at https://***/mhorvat/stimdbsurvey. © 2023 MIPRO Croatian Society.

关键词： database systems

来源：评论

学校读者我要写书评

暂无评论

Intelligent Predictive Model for Hepatitis C 3

Intelligent Predictive Model for Hepatitis C

引用

3rd IEEE International Conference on Artificial Intelligence, ICAI 2023

作者： Shahzadi, Mehreen Bukhari, Faisal Shafi, Numan University of the Punjab Faculty of Computing & Information Technology Department of Data Science Lahore Pakistan University of Engineering and Technology Department of Computer Science Lahore Pakistan

ISBN: (纸本)9798350322125

Hepatitis C is the liver's festering that can lead to severe liver damage, usually caused by the hepatitis C virus. Hepatitis C has different stages. It is tough to cure in it's last stages;at the same time, it is expensive and painful process. The current research, however, is an alternative precaution to this issue. Hepatitis C can be predicted early by using multiple factors. The dataset related to hepatitis C was not publicly available. To overcome this challenge, the healthy and HCV effected samples were collected from different hospitals in Punjab. A questionnaire based survey was taken including different HCV related factor i.e. gender, weight loss, hives/ rashes, swelling, jaundice, drug addiction history, hepatic encephalopa-thy (drowsiness, slurred speech), Ascites (fluid buildup in belly/ abdomen), spider angiomas (Spiderlike blood vessels), shared syringe usage, medical history, and severeness. Different cleaning, scaling, and feature selection techniques were applied to collect the best feature data. After selection, various machine learning algorithms were applied. Random forest, KNN, Decision Tree, SVC, and MLP were used, but MLP yielded optimal results in all classification algorithms. We have gained 95.9 % accuracy when tested on unknown data based on the MLP model. As the predictions' results were satisfactory, it would be helpful for the people and act as a critical awareness. © 2023 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

EQCNN: Enhanced Remote Sensing Imagery Classification with Circuit-Based Error-Corrected Quantum Convolutional Neural Networks 25

EQCNN: Enhanced Remote Sensing Imagery Classification with C...

引用

25th International Conference on Digital Image computing: Techniques and Applications, DICTA 2024

作者： Zaman, Muhammad Kehkashan, Tanzila Akhunzada, Adnan Alaidaros, Hashem Uddin, Mueen Azeem, Muhammad University of Lahore Faculty of Computer Science Punjab Sargodha40100 Pakistan Universiti Teknologi Malaysia Faculty of Computing Johor Bahru Malaysia College of Computing & It University of Doha for Science & Technology Department of Data and Cybersecurity Doha Qatar Dar Al-Hekma University Department of Cybersecurity Jeddah Saudi Arabia

ISBN: (纸本)9798350379037

Quantum information processing is more complex than classical counterpart because of the No-Cloning theorem, decoherence, and issues detecting quantum states. Building a quantum computer without error detection and correction module is challenging. To overcome this challenge, qubit error correction codes are implemented. Inadequate error detection and correction codes have been the downfall of earlier attempts to encode quantum information, leading to disrupted qubit transmission. Qubit information is decohered by circuit noise. Unfortunately, the principal qubit error, phase flip error is not corrected by existing qubit error correction methods. In this study, we proposed Quantum Error Detection and Correction scheme (QEDC) to keep qubit in a coherent state. Used S gates, unitary gates, 10 CNOT gates, and Hadamard gates spanning on 4 physical and 1 logical qubits over the IBM Quantum Experience Machine. We found that the error probability is reduced to 7.91% owing to the efficiency of the quantum information encoding and phase flip control. Furthermore, we proposed Error Corrected Quantum Convolution Neural Network (EQCNN) for Image Classification. EQCNN combat and correct qubit errors that occur during the image processing. EQCNN outperformed over Earth Observatory (EO) dataset, EuroSAT and achieved an impressive results of 99.3% accuracy, 98.9% F1-score, 96.73% precision, and 98.4% recall. © 2024 IEEE.

关键词： Qubits

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：