检索结果-内蒙古大学图书馆

Probability Based Regression Analysis for the Prediction of Cardiovascular Diseases

computers, Materials & Continua 2023年第6期75卷 6269-6286页

作者： Wasif Akbar Adbul Mannan Qaisar Shaheen Mohammad Hijji Muhammad Anwar Muhammad Ayaz Department of Computer Science NFC Institute of Engineering and TechnologyMultanPakistan Faculty of Computer Science&Information Technology University of MalayaKuala LumpurMalaysia Department of Computer Science and Information Technology The Islamia University of BahawalpurRahim Yar Khan CampusPunjabPakistan Faculty of Computers and Information Technology University of TabukTabuk47512Saudi Arabia Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahorePakistan Sensor Networks and Cellular Systems(SNCS)research center University of TabukTabuk47512Saudi Arabia

Machine Learning(ML)has changed clinical diagnostic procedures *** in Cardiovascular Diseases(CVD),the use of ML is indispensable to reducing human *** studies focused on disease prediction but depending on multiple parameters,further investigations are required to upgrade the clinical ***-layered implementation of ML also called Deep Learning(DL)has unfolded new horizons in the field of clinical *** formulates reliable accuracy with big datasets but the reverse is the case with small *** paper proposed a novel method that deals with the issue of less data *** by the regression analysis,the proposed method classifies the data by going through three different *** the first stage,feature representation is converted into probabilities using multiple regression techniques,the second stage grasps the probability conclusions from the previous stage and the third stage fabricates the final *** experiments were carried out on the Cleveland heart disease *** results show significant improvement in classification *** is evident from the comparative results of the paper that the prevailing statistical ML methods are no more stagnant disease prediction techniques in demand in the future.

关键词： Machine learning heart disease cardiac disease deep regression regression learning

来源：评论

学校读者我要写书评

暂无评论

Examining the impact of link failures and network performance on a 6to4, 6rd, CHANC and D4across6 tunneling-based networks using various routing protocols

引用

International Journal of information technology (Singapore) 2024年 1-19页

作者： Hamarsheh, Ala Faculty of Information Technology/Department of Computer Science Arab American University Jenin 00970 Palestine

The article discusses the importance of failure recovery in communication networks to ensure smooth and dependable service. It states that the performance of real-time applications has been negatively affected for years due to failed links, and thus it is crucial to address the issue to prevent collapse and cascading failures for both users and service providers. The paper then goes on to analyze the performance of a network by simulating the failure and recovery of network links for different time periods using the 6rd, CHANC, D4across6 and 6to4 tunneling network. Different routing protocols and tunneling techniques are employed to evaluate the performance of the network for the specific type of applications (i.e. video streaming and real-time voice). It also looks at different metrics, including data transfer rate, dropped traffic, and network convergence. Furthermore, the study delves into the examination of the route table properties of various routers and the IPv4 backbone when links between them experience repeated failures and recoveries. The purpose of this analysis is to anticipate network performance and to ensure network availability and accessibility of traffic through forecasting the network's ability to survive and recover from link failures. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： IPv4 tunneling IPv6 IPV6 transition mechanisms IPv6 tunneling OPNET network performance

来源：评论

学校读者我要写书评

暂无评论

Multi-Agent Reinforcement Learning-Based Resource Sharing in Multi-UAV Wireless Networks

IEEE Journal on Miniaturization for Air and Space Systems

引用

IEEE Journal on Miniaturization for Air and Space Systems 2024年第2期6卷 103-112页

作者： Zhang, Yaxiu Luan, Mingan Chang, Zheng Hamalainen, Timo University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China University of Jyväskylä Faculty of Information Technology JyväskyläFIN-40014 Finland

This paper investigates the resource sharing problem in a multi-unmanned aerial vehicle (UAV) wireless network by utilizing the multi-agent reinforcement learning (MARL) method. Specifically, the considered multi-UAV system involves two transmission modes, i.e., UAV-to-Device (U2D) mode and UAV-to-Network (U2N) mode, in which the U2D mode is allowed to reuse the spectrum of U2N mode to improve the spectrum efficiency. Then, we formulate an optimization problem to maximize the throughput of U2D links by jointly optimizing the channel allocation, power level selection, and UAV trajectory, while ensuring the communication quality of U2N links. Due to the highly complex and dynamic nature, as well as the challenging non-convex objective function and constraints, the resulting problem is hard to address. Accordingly, we propose a novel Multi-Agent Deep Deterministic Policy Gradient (MADDPG)-based resource allocation and multi-UAV trajectory optimization policy. Simulation results illustrate the efficacy of our method in improving the system transmission rate. © 2019 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

De-Noising Brain MRI Images by Mixing Concatenation and Residual Learning(MCR)

引用

computer Systems science & Engineering 2023年第5期45卷 1167-1186页

作者： Kazim Ali Adnan N.Qureshi Muhammad Shahid Bhatti Abid Sohail Muhammad Hijji Atif Saeed Department of Computer Science Faculty of Information TechnologyUniversity of Central Punjab LahoreLahore54000Pakistan Department of Computer Science COMSAT University IslamabadLahore CampusLahore54000Pakistan Faculty of Computers and Information Technology Computer Science DepartmentUniversity of TabukTabuk47711Saudi Arabia

Brain magnetic resonance images(MRI)are used to diagnose the different diseases of the brain,such as swelling and tumor *** quality of the brain MR images is degraded by different noises,usually salt&pepper and Gaussian noises,which are added to the MR images during the acquisition *** the presence of these noises,medical experts are facing problems in diagnosing diseases from noisy brain MR ***,we have proposed a de-noising method by mixing concatenation,and residual deep learning techniques called the MCR de-noising *** proposed MCR method is to eliminate salt&pepper and gaussian noises as much as possible from the brain MRI *** MCR method has been trained and tested on the noise quantity levels 2%to 20%for both salt&pepper and gaussian *** experiments have been done on publically available brain MRI image datasets,which can easily be accessible in the experiments and result *** Structure Similarity Index Measure(SSIM)and Peak Signal-to-Noise Ratio(PSNR)calculate the similarity score between the denoised images by the proposed MCR method and the original clean ***,the Mean Squared Error(MSE)measures the error or difference between generated denoised and the original *** proposed MCR denoising method has a 0.9763 SSIM score,84.3182 PSNR,and 0.0004 MSE for salt&pepper noise;similarly,0.7402 SSIM score,72.7601 PSNR,and 0.0041 MSE for Gaussian noise at the highest level of 20%*** the end,we have compared the MCR method with the state-of-the-art de-noising filters such as median and wiener de-noising filters.

关键词： MR brain images median filter wiener filter concatenation learning residual learning MCR de-noising method

来源：评论

学校读者我要写书评

暂无评论

Mitigating Blackhole and Greyhole Routing Attacks in Vehicular Ad Hoc Networks Using Blockchain Based Smart Contracts

引用

computer Modeling in Engineering & sciences 2024年第2期138卷 2005-2021页

作者： Abdulatif Alabdulatif Mada Alharbi Abir Mchergui Tarek Moulahi Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science Higher Institute of Management of GabesGabes UniversityGabes6029Tunisia Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Faculty of Science and Technology of Sidi Bouzid Kairouan UniversityKairouan3131Tunisia

The rapid increase in vehicle traffic volume in modern societies has raised the need to develop innovative solutions to reduce traffic congestion and enhance traffic management *** advanced technology,such as Intelligent Transportation Systems(ITS),enables improved traffic management,helps eliminate congestion,and supports a safer *** provides real-time information on vehicle traffic and transportation systems that can improve decision-making for road ***,ITS suffers from routing issues at the network layer when utilising Vehicular Ad Hoc Networks(VANETs).This is because each vehicle plays the role of a router in this network,which leads to a complex vehicle communication network,causing issues such as repeated link breakages between vehicles resulting from the mobility of the network and rapid topological *** may lead to loss or delay in packet transmissions;this weakness can be exploited in routing attacks,such as black-hole and gray-hole attacks,that threaten the availability of ITS *** this paper,a Blockchain-based smart contracts model is proposed to offer convenient and comprehensive security mechanisms,enhancing the trustworthiness between ***-Classification Blockchain-Based Contracts(SCBC)and Voting-Classification Blockchain-Based Contracts(VCBC)are utilised in the proposed *** results show that VCBC succeeds in attaining better results in PDR and TP performance even in the presence of Blackhole and Grayhole attacks.

关键词： Blockchain data privacy machine learning routing attacks smart contract VANET

来源：评论

学校读者我要写书评

暂无评论

The Security of Using Large Language Models:A Survey With Emphasis on ChatGPT

引用

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 1-26页

作者： Wei Zhou Xiaogang Zhu Qing-Long Han Lin Li Xiao Chen Sheng Wen Yang Xiang the School of Science Computing and Engineering Technologies Swinburne University of Technology IEEE the School of Computer and Mathematical Sciences the University of Adelaide Adelaide the Faculty of Science and Engineering Southern Cross University the School of Information and Physical Sciences the University of Newcastle

ChatGPT is a powerful artificial intelligence(AI)language model that has demonstrated significant improvements in various natural language processing(NLP) tasks. However, like any technology, it presents potential security risks that need to be carefully evaluated and addressed. In this survey, we provide an overview of the current state of research on security of using ChatGPT, with aspects of bias, disinformation, ethics, misuse,attacks and privacy. We review and discuss the literature on these topics and highlight open research questions and future *** this survey, we aim to contribute to the academic discourse on AI security, enriching the understanding of potential risks and mitigations. We anticipate that this survey will be valuable for various stakeholders involved in AI development and usage, including AI researchers, developers, policy makers, and end-users.

关键词： Artificial intelligence (AI) ChatGPT large language models (LLMs) security

来源：评论

学校读者我要写书评

暂无评论

IRS-Enabled Interference Elimination and Fairness Enhancement in D2D Communication Networks

IRS-Enabled Interference Elimination and Fairness Enhancemen...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Dai, Xin Chen, Xin Jiao, Libo Han, Bingjie Pan, Yizheng Yin, Tong School of Computer Science Beijing Information Science & Technology University Beijing China Beijing University of Technology Faculty of Information Technology Beijing China

ISBN: (纸本)9781665410205

In order to cope with the increasing data traffic, we try to enable Intelligent Reflecting Surface (IRS) interference elimination in Device-to-Device (D2D) communication networks to improve the Signal Interference Noise Ratio (SINR). We build the system model and divide the original problem into two subproblems: IRS reflection parameter adjustment and IRS allocation. We use the the Cross Entropy Global Optimization Method (CEGOM) to solve the first subproblem. For the second subproblem, in order to ensure the fairness of user rates and avoid user starvation, we propose a heuristic algorithm based on the Max-Min Fairness Method (MMFM) to solve the problem. Simulation results demonstrate the superiority of the proposed algorithms, which improves Jain's fairness index by 70%, 72% and 13% and reduces the blocking probability by 92%, 90% and 82%, respectively, when compared to the random, shortest distance, and traditional MMFM strategies. © 2024 IEEE.

关键词： Heuristic algorithms

来源：评论

学校读者我要写书评

暂无评论

R3 - Rescale, Rotate, and Randomize: A Novel Image Cryptosystem Utilizing Chaotic and Hyper-Chaotic Systems

引用

IEEE Access 2023年 11卷 119284-119312页

作者： Gabr, Mohamed Korayem, Yousef Chen, Yen-Lin Yee, Por Lip Ku, Chin Soon Alexan, Wassim Faculty of Media Engineering and Technology Computer Science Department Cairo11835 Egypt National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia Faculty of Information Engineering and Technology Communications Department Cairo11835 Egypt New Administrative Capital Mathematics Department Cairo13507 Egypt

This work proposes a novel image encryption algorithm that integrates unique image transformation techniques with the principles of chaotic and hyper-chaotic systems. By harnessing the unpredictable behavior of the Chua system and the hyper-chaotic nature of the Chen system, the algorithm carries out rescaling, rotation, and randomization on the target image. The intrinsic unpredictability and sensitivity to initial conditions of these chaotic systems endow the encryption algorithm with an expansive key space of 25208. This feature not only bolsters its resilience against brute-force attacks but also magnifies its overall security profile. The algorithm's efficiency is evident in its rapid computational speed and lean resource consumption, making it suitable for real-time applications. To gauge its robustness, a battery of rigorous tests and analyses, spanning differential attacks, statistical attacks, and brute-force assaults, were employed. The results validate its ability to resist a diverse spectrum of threats. With its expansive key space, exceptional efficiency, and sturdy defenses, the proposed algorithm emerges as a potential cornerstone for safeguarding digital images in arenas like secure communication, data storage, and multimedia transmission. In sum, this research pushes the boundaries of high-security image encryption methodologies, catering to the burgeoning demands of the digital age. © 2013 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Enhanced MADM Strategy with Heptapartitioned Neutrosophic Distance Metrics

引用

Neutrosophic Sets and Systems 2025年 78卷 74-96页

作者： Eassa, Mohamed Myvizhi, M. Elkholy, Mohamed Abdelhafeez, Ahmed Elbehiery, Hussam Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Mathematics KPR Institute of Engineering and Technology Tamilnadu Coimbatore India Faculty of Computer Science& Engineering Alamein International University Egypt

In this work, a novel methodological approach to multi-attribute decision-making problems is developed and the notion of Heptapartitioned Neutrosophic Set Distance Measures (HNSDM) is introduced. By averaging the Penta-Partitioned Neutrosophic Distance Measures under particular conditional criteria, the suggested technique ranks the options. Additionally, we explore the fundamental characteristics of HNSDM and provide several illustrative theorems. The Heptapartitioned Neutrosophic Set Distance Measures are formulated based on the Hepta Neutrosophic Set. Lastly, a practical numerical example is provided to illustrate the efficacy of the suggested methodology. © 2025, University of New Mexico. All rights reserved.

关键词： Heptapartitioned Neutrosophic set Heptapartitioned Neutrosophic set and MADM strategy Heptapartitioned set Neutrosophic sine distance measure

来源：评论

学校读者我要写书评

暂无评论

A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

引用

computers, Materials & Continua 2024年第3期78卷 2967-3000页

作者： Usman Khan Muhammad Khalid Khan Muhammad Ayub Latif Muhammad Naveed Muhammad Mansoor Alam Salman A.Khan Mazliham Mohd Su’ud College of Computing and Information Sciences Karachi Institute of Economics and TechnologyKarachi75190Pakistan Faculty of Computing and Informatics(FCI) Multimedia UniversityCyberjaya63100Malaysia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyAustralia

Recently,there has been a notable surge of interest in scientific research regarding spectral *** potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable *** encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image *** a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent *** paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and *** meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical ***,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural *** findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in ***,we also shed light on the various issues and limitations of working with spectral *** comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

关键词： Machine learning deep learning unmanned aerial vehicles multi-spectral images image recognition object detection hyperspectral images aerial photography

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：