检索结果-内蒙古大学图书馆

Optimizing Gene Expression Analysis Using Clustering Algorithms 1

5th International Conference on computer and Communication Technologies, IC3T 2023

作者： Bikku, Thulasi Ramu, J. Sekhar, J. Chandra Pratap, V. Krishna Pujari, Jeevana Jyothi Computer Science and Engineering Amrita School of Computing Amaravati Amrita Vishwa Vidyapeetham Andhra Pradesh Amaravati522503 India Department of Computer Science and Engineering NRI Institute of Technology Andhra Pradesh Guntur India Department of Database Systems School of Computer Science and Engineering Vellore Institute of Technology Tamilnadu Vellore632014 India

ISBN: (数字)9789819997077

ISBN: (纸本)9789819997060

Gene expression analysis plays a crucial role in understanding biological processes and diseases. However, the high-dimensional nature of gene expression data poses challenges for its analysis and interpretation. Clustering algorithms have been widely used for identifying patterns in gene expression data, but their effectiveness is limited by the choice of algorithm and parameters used. In this study, we propose an approach for optimizing gene expression analysis using clustering algorithms. Initially, a range of clustering techniques were assessed, encompassing K-means, hierarchical clustering, and DBSCAN. This assessment was conducted using gene expression information sourced from a publicly accessible database. Subsequently, various techniques for feature selection were employed. These techniques encompassed principal component analysis (PCA) as well as correlation-based feature selection (CFS). Their objective was twofold: to decrease the data's dimensionality and to enhance the effectiveness of the clustering process. From the study, we came to know that the combination of K-means clustering with PCA feature selection outperformed other methods in terms of clustering accuracy and stability. We also identified a set of genes that were consistently associated with different clusters, providing insights into the underlying biological processes. Overall, our study demonstrates the importance of careful algorithm and parameter selection for gene expression analysis and highlights the potential of clustering algorithms for identifying meaningful patterns in gene expression data. The suggested methodology entails merging DBSCAN with K-means clustering, which could be extended to diverse high-dimensional datasets for the enhancement of their analysis and comprehension. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Submodular Participatory Budgeting 1

引用

18th International Conference on Algorithmic Aspects in Information and Management, AAIM 2024

作者： Yuan, Jing Tang, Shaojie Department of Computer Science and Engineering University of North Texas Denton United States Department of Management Science and Systems School of Management University at Buffalo Buffalo United States

ISBN: (数字)9789819777983

ISBN: (纸本)9789819777976

Participatory budgeting refers to the practice of allocating public resources by collecting and aggregating individual preferences. Most existing studies in this field often assume an additive utility function, where each individual holds a private utility for each candidate project, and the total utility of a set of funded projects is simply the sum of the utilities of all projects. We argue that this assumption does not always hold in reality. For example, building two playgrounds in the same neighborhood does not necessarily lead to twice the utility of building a single playground. To address this, we extend the existing study by proposing a submodular participatory budgeting problem, assuming that the utility function of each individual is a monotone and submodular function over funded projects. We propose and examine three preference elicitation methods and analyze their performances in terms of distortion. Notably, if the utility function is additive, our aggregation rule designed for threshold approval votes achieves a better distortion than the state-of-the-art approach. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Budget control

来源：评论

学校读者我要写书评

暂无评论

Shortest Job First with Gateway-based Resource Management Strategy for Fog Enabled Cloud Computing 4

Shortest Job First with Gateway-based Resource Management St...

引用

4th IEEE International Conference on Data engineering and Communication systems, ICDECS 2024

作者： Anbazhagan, K. Kumar, Rotash Thilagavathy, R. Anuradha, D. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Government Engineering College Department of Electronics and Communication Engineering Rajasthan Jhalawar India College of Engineering and Technology Srm Institute of Science and Technology Kattankulathur Department of Computing Technologies Chennai India Panimalar Engineering College Department of Computer Science and Business Systems Chennai India

ISBN: (纸本)9798350393354

In recent years, fog computing has extended cloud services to the network edge, lowering network latency and congestion and overcoming cloud computing restrictions. Many hurdles, however, must be overcome before the benefits of the fog-IoT paradigm for low-latency applications can be completely realized. The most challenging difficulty in IoT applications is developing efficient resource management strategies that maximize throughput while minimizing delay. IoT and fog computing, rather than simply utilizing cloud computing technology, have brought intriguing new data management solutions. Fog computing makes real-time analytics applications conceivable. After combining fog computing technologies with Internet of Things (IoT) applications, the system can reply in milliseconds. Existing fog resource managers focus on a subset of fog resource management parameters such as system response time, network bandwidth, energy consumption, and latency. No Fog resource management takes multiple factors into account at the same time for decision-making, which will become increasingly crucial in intelligent homes. Gateway-based Fog Computing pioneered the introduction of the shortest job (SJFGFC) to address these difficulties. The technique is validated in an IoT-based imaginative house automation scenario before being evaluated in a small-scale bright home experiment using the iFogSim toolbox and empirical models. © 2024 IEEE.

关键词： Fog computing

来源：评论

学校读者我要写书评

暂无评论

System of System Architecture for Cybersecurity of Power systems Operations 11

System of System Architecture for Cybersecurity of Power Sys...

引用

11th International Conference on Electrical and Electronics engineering, ICEEE 2024

作者： Ur Rahman, Ehab Ashiku, Lirim Dagli, Cihan Bo, Rui Missouri University of Science and Technology Department of Electrical and Computer Engineering RollaMO United States Missouri Universtity of Science and Technology Engineering Management and Systems Engineering RollaMO United States

ISBN: (纸本)9798350362541

Smart grids are at risk of cyber-attacks due to more connected devices being introduced. Different kinds of attacks may incur different consequences in the operation of smart grids. Attackers have identified different vulnerable points in smart grid operations and have developed malicious stealthy attacks to disrupt the operation of physical systems. In this paper we have formulated the power system cyber security problem as a five-dimensional optimization problem. A general framework is developed using the system of system explorer tool providing a defensive solution to the vulnerable points of a smart grid prone to malicious attacks. An optimal meta-architecture composed of defensive system constituents is achieved using Genetic algorithm (GA) and fuzzy inference system providing a solution to ensure cybersecurity of power system operations. © 2024 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

A New Approach for Quantum Phase Estimation Based Algorithms for Machine Learning 8th

A New Approach for Quantum Phase Estimation Based Algorithm...

引用

8th International Conference on Smart City Applications, SCA 2023

作者： Ouedrhiri, Oumayma Banouar, Oumayma El Hadaj, Salah Raghay, Said Department of Computer Science and Mathematics University of Quebec at Trois-Riviéres Trois-Riviéres Canada Faculty of Sciences and Techniques Laboratory of Computer Science Engineering and Systems Marrakesh Morocco

ISBN: (纸本)9783031543753

One of the greatest developments in computer science is undoubtedly quantum computing. It has demonstrated to give various benefits over the classical algorithms, particularly in the significant reduction of processing time, due to the parallelism and entanglement properties. One of the most crucial quantum computing algorithms is quantum phase estimation (QPE). It is called the eigenvalue finding module for unitary operators. It has helped to solve the order finding and the factoring problem, and to calculate the eigenvalues of unitary matrices and quantum sampling methods. In this paper, we study recent improved versions for the QPE procedure, their advantages and experimentation. We also propose a new approach for QPE based algorithms for machine learning (ML). These algorithms are the Harrow-Hassidim-Lloyd (HHL) algorithm for solving linear systems, the quantum singular value thresholding (QSVT) algorithm for matrix completion in recommender systems, and the quantum principal components analysis (QPCA) for data visualization. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Security model to identify block withholding attack in blockchain

Security model to identify block withholding attack in block...

引用

International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Keshta, Ismail Reegu, Faheem Ahmad Ahmad, Adeel Saxena, Archana Chandan, Radha Raman Mahalakshmi, V. Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia College of Computer Science and Information Technology Jazan University Jazan Saudi Arabia Department of Computer Applications Invertis University UP Bareilly India Department of Computer Science and Engineering Shambhunath Institute of Engineering and Technology College Jhalwa Prayagraj India Department of Computer Science College of Computer Science and Information Technology Jazan University Jazan Saudi Arabia

ISBN: (纸本)9781032669663

Block interception attack, also known as block withholding attack, is an attack method in the blockchain. The attacker penetrates the target mining pool for passive mining to destroy the target mining pool. This paper briefly introduces the mining mechanism and the working principle of block interception attack, summarizes several models of block interception attack, studies the attack methods and benefits of the existing block interception attack models, and analyses their attack effects. A block interception attack model is constructed to increase the rate of return while increasing the rate of return. The completed model is verified through simulated mining experiments. The typical and made models are compared and analyzed based on the rate of return. Finally, the applicable environments of different attack models are given based on the experimental results. © 2024 The Author(s).

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Coupling Mobile Brain Imaging and Virtual Reality Omnidirectional Treadmill to Explore Attenuated Situational Awareness during Distracted Walking

引用

IEEE Transactions on Cognitive and Developmental systems 2024年第3期16卷 1063-1076页

作者： Chuang, Chun-Hsiang Chiu, Tsai-Feng Hsu, Hao-Che Lin, Shih-Syun National Tsing Hua University Research Center for Education and Mind Sciences College of Education The Institute of Information Systems and Applications College of Electrical Engineering and Computer Science Hsinchu300 Taiwan National Tsing Hua University Research Center for Education and Mind Sciences Hsinchu300 Taiwan National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300193 Taiwan National Taiwan Ocean University Department of Computer Science and Engineering Keelung20224 Taiwan

Walking while engaging in distracting activities affects our perception of changes happening on the road, leading to exposure to hazardous conditions. This study aimed to evidence that pedestrians who become distracted when absorbed in their smartphones fail to maintain situational awareness. Thirty-six recruited participants performed a psychomotor vigilance task and a wayfinding task designed to simulate a multitasking scenario;meanwhile, an auditory oddball paradigm presented to participants tested their situational awareness of an external stimulus. The experiment was conducted in virtual reality (VR) environment with an omnidirectional treadmill. Participant's behavioral and electroencephalographic (EEG) responses were measured and analyzed using a newly proposed brain network measure, phase locking distance (PLD), to capture multitasking-associated couplings between brain regions. The current study supports the notion that multitasking can lead to diminished behavioral performance and changes in walking patterns. Despite the increased interregional brain connectivity, which may be an adaptive response to heightened cognitive demands, the associated reduction in event-related EEG activity suggests competition for neural resources during multitasking. Moreover, the observed EEG activities could indicate additional information processing capacity limitations and provide evidence of decreased situational awareness during multitasking, thereby increasing susceptibility to potentially hazardous situations. © 2016 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

引用

computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami Khafaga Faten Khalid Karim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

来源：评论

学校读者我要写书评

暂无评论

A Novel Parallel Computing Confidentiality Scheme Based on Hindmarsh-Rose Model

引用

computers, Materials & Continua 2023年第8期76卷 1325-1341页

作者： Jawad Ahmad Mimonah Al Qathrady Mohammed SAlshehri Yazeed Yasin Ghadi Mujeeb Ur Rehman Syed Aziz Shah School of Computing Engineering and the Built EnvironmentEdinburgh Napier UniversityEdinburghEH105DTUK Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi112612United Arab Emirates School of Science Technology and HealthYork St John UniversityYorkYO317EXUK Research Centre for Intelligent Healthcare Coventry UniversityCoventryCV15FBUK

Due to the inherent insecure nature of the Internet,it is crucial to ensure the secure transmission of image data over this ***,given the limitations of computers,it becomes evenmore important to employ efficient and fast image encryption *** 1D chaotic maps offer a practical approach to real-time image encryption,their limited flexibility and increased vulnerability restrict their practical *** this research,we have utilized a 3DHindmarsh-Rosemodel to construct a secure *** randomness of the chaotic map is assessed through standard *** proposed system enhances security by incorporating an increased number of system parameters and a wide range of chaotic parameters,as well as ensuring a uniformdistribution of chaotic signals across the entire value ***,a fast image encryption technique utilizing the new chaotic system is *** novelty of the approach is confirmed through time complexity *** further strengthen the resistance against cryptanalysis attacks and differential attacks,the SHA-256 algorithm is employed for secure key *** results through a number of parameters demonstrate the strong cryptographic performance of the proposed image encryption approach,highlighting its exceptional suitability for secure ***,the security of the proposed scheme has been compared with stateof-the-art image encryption schemes,and all comparison metrics indicate the superior performance of the proposed scheme.

关键词： Hindmarsh-rose model image encryption SHA-256 parallel computing

来源：评论

学校读者我要写书评

暂无评论

Robust Authentication: Leveraging Hardware Fingerprints and AI to Enhance Security Against Spoofing

引用

IEEE Access 2025年 13卷 86912-86926页

作者： Nimmy, K. Jain, Kurunandan Sachin, S.M. Abekaesh, P.A. Venkitasubramaniam, Parv Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri690525 India Center for Cybersecurity Systems and Networks Amrita Vishwa Vidyapeetham Amritapuri Campus Kerala Amritapuri690525 India Lehigh University Department of Electrical and Computer Engineering BethlehemPA18015 United States

Fingerprint authentication blends biometric precision with user convenience, leveraging unique ridge patterns for fast, reliable, and tamper-resistant identity verification. However, it remains vulnerable to spoofing attacks, where adversaries create synthetic fingerprints using materials like gelatin. To mitigate this, multi-factor authentication (MFA) enhances security by verifying both the fingerprint and the user’s device, restricting access to authorized hardware and complicating attacks. Although Photo Response Non-Uniformity (PRNU) has been explored for device authentication, its reliability diminishes under varying lighting conditions. To address this, we propose an AI-driven approach to generate robust hardware fingerprints from fingerprint scanners, enabling high-accuracy device identification. Our method, trained on 2,000 fingerprint images from 10 scanners, achieves an impressive 98% accuracy in identifying the source scanner. By integrating fingerprint biometrics, hardware fingerprints, and passwords, our novel MFA protocol significantly enhances security against spoofing and forgery attacks. Through security analysis, we demonstrate its effectiveness in preventing unauthorized access. Finally, we validate our authentication framework using an AI-powered binary classifier model, showcasing its practicality for real-world security applications. © 2013 IEEE.

关键词： Authentication Protocol

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：