检索结果-内蒙古大学图书馆

Game theory-based optimization for efficient IoT task offloading in 6G network base stations

Measurement: Sensors 2024年 33卷

作者： Keshta, Ismail Soni, Mukesh Deb, Nabamita singh, Shweta Saravanan, K. Raza Khan, Dr Ihtiram Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science & Technology Tathawade Pune India Assistant Professor Department of Information Technology Gauhati University India Department of Information Technology R.M.D. Engineering College Chennai India Computer Science Department Jamia Hamdard Delhi India Electronics and communication department IES college of technology Bhopal India

This study aims to optimise computing for intricate jobs within the overlapping coverage of 6G network base stations. A multi-access edge computing network model is created by solving the issues of task offloading. This model involves many base stations and IoT devices. It takes into account factors such as task delay, energy consumption, societal impacts, and economic incentives. The objective of joint optimization is to maximize the revenues of base stations and the utilities of IoT devices by considering base station price, IoT device base station selection, and job offloading mechanisms. The IoT device base station selection is addressed using a many-to-one matching game model, while pricing and task offloading interactions are managed by a two-stage approach based on Stackelberg game theory. The suggested Optimal Pricing and Best Response Algorithm (OBGT), which is based on Game Theory, successfully reaches equilibrium solutions. It demonstrates rapid convergence in simulations and improves both base station profits and IoT device utility. This study integrates data-driven mobile computing systems assurance for futuristic smart vertical networks, enhancing the efficiency of task offloading and optimization. © 2024 The Authors

关键词： Game theory

来源：评论

学校读者我要写书评

暂无评论

AI-Based Cybersecurity Frameworks for 7G-Enabled Virtual Therapy Platforms

Cyber Security and Applications

引用

Cyber Security and Applications 2025年

作者： A. Jayanthiladevi Jayapandian Natarajan KP Arjun L. Godlin Atlas M. Arvindhan Daniel Arockiam Professor Department of Computer Engineering Marwadi University Rajkot Gujarat India Associate Professor Department of Computer Science and Engineering School of Engineering and Technology Christ University Kengeri Campus Bangalore Karnataka India Department of Computer Science and Engineering GITAM University Bengaluru Campus Karnataka India Associate Professor Department of Computer Science and Engineering Bharath Institute of Higher Education and Research Chennai Tamil Nadu Assistant Professor Amity School of Engineering & Technology Computer Science and Engineering Gwalior Madhya Pradesh India Associate Professor CSE Amity University Madhya Pradesh Gwalior 474005 India

The modern technology network plays an important role. Artificial intelligence to provide a higher solution for network security. As 7G networks emerge, virtual therapy platforms have begun to take center stage, offering fast, real-time interaction and high-definition immersive experiences. While the convergence of security in health care and mobility is in many ways even more integrated into our lives, it is fraught with cybersecurity risks. This article proposes an AI-based cybersecurity framework for a 7 G-based virtual therapy platform. The framework employs advanced machine learning (ML) algorithms, predictive analytics, and adaptive threat intelligence to protect the confidentiality, integrity, and availability of data. The article covers the core building blocks like anomaly detection, secure 7 G-based virtual therapy platform authentication protocols, and privacy-preserving techniques. AI-GN gives an overview of attack mitigation using AI with a comparative analysis of existing 5G/6G frameworks and solutions and their unique aspects needed for 7G environments. This article mainly focuses on threat detection using a deep learning method, also it aims to provide a continuous authentication process. The proposed model response time is decreased by nearly 30 percent, at the same time detection rate is increased to 98.5 percent in a 7G network.

关键词： AI-based cyber security framework Adaptive threat intelligence Anomaly detection Predictive analytics Threat detection

来源：评论

学校读者我要写书评

暂无评论

Advanced skin lesion segmentation and classification using adaptive contextual GLCM and deep learning hybrid models

引用

Egyptian Informatics Journal 2025年 30卷

作者： Vinit Kumar D.L. Shanthi Tummala Ranga Babu Narendra Kumar Rakesh Kumar Godi Dr Arun G Professor Galgotias College of Engineering and Technology Greater Noida India Assistant Professor Department of Computer Science and Engineering BMS Institute of Technology and Management Bangalore Karnataka India Professor Electronics & Communication Engineering R.V.R. & J.C.College of Engineering India Associate Professor Department of CSE Amity University Jharkhand Ranchi Jharkhand India Department of Computer Science Central University of Karnataka Kalaburagi 585367 India Assistant Professor Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India

One of the most common and dangerous types of cancer, skin cancer, especially melanoma, is distinguished by its quick spread and high death rate if left untreated. It is impossible to overestimate the significance of early detection and precise diagnosis as they are essential for successful treatment and greatly raise patient survival rates. To improve skin lesion segmentation and classification, this work presents a state-of-the-art image analysis technique that uses hybrid deep learning models in conjunction with the Adaptive Contextual Gray Level Co-occurrence Matrix (GLCM). DeepLabV3 + is used to segment the skin lesion from pre-processed input images with high accuracy. A Long Short-Term Memory (LSTM) network trained on characteristics collected by the Adaptive Contextual GLCM is included to further evaluate the segmented images. Because of this special combination, the model can accurately capture contextual information and tiny texture differences, both of which are essential for differentiating between benign and malignant skin lesions. Our suggested approach performs very well in tasks involving both segmentation and classification. In particular, it attains a remarkable 98.34 % accuracy, 99.13 % specificity, 97.25 % sensitivity, 97.15 % Dice coefficient, and 98.6 % F1 score. These findings demonstrate the method’s stability and dependability, which makes it a potentially useful instrument for raising the detection accuracy of skin cancer. This approach has the potential to transform early detection procedures by providing improved diagnostic accuracy and resilience, eventually contributing to better patient outcomes and more effective management of skin cancer cases.

关键词： Skin cancer Machine Learning Deeplabv3 Adaptive Contextual Gray Level Co-occurrence Matrix Long Short-Term Memory

来源：评论

学校读者我要写书评

暂无评论

Survey on various DDoS attacks on firewall and study on emerging DoF attacks

引用

AIP Conference Proceedings 2023年第1期2773卷

作者： P. A. Jishiya Ajay James K. P. Swaraj M-Tech Student Computer Science and Engineering Govt. Engineering College Thrissur India Assistant Professor Computer Science and Engineering Govt. Engineering College Thrissur India Associate Professor Computer Science and Engineering Govt. Engineering College Thrissur India

A firewall is a network device that act as a security guard between a trusted network and an untrusted network. Firewall is the first line of defence against malicious traffic. Nowadays, attacking an organisation network for evil intentions has become a common thing. Distributed Denial of Service (DDoS) attack floods network traffic with illegitimate traffic and thereby preventing accessibility to legitimate users. However new type of attacks are being emerged targeting the network devices and their vulnerabilities. Attacker uses specially crafted packets to overload firewall with comparatively lesser effort, known as Denial of Firewalling (DoF) attack. This paper discusses about the attacks targeting the firewall and also about the newly emerged DoF attack. Moreover, a detection model for DDoS attack is also analysed.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comparative analysis of reduced feature set based ML models for IDS

引用

AIP Conference Proceedings 2023年第1期2773卷

作者： P. A. Jishiya K. P. Swaraj Ajay James M-Tech Student Computer Science and Engineering Govt. Engineering College Thrissur India Associate Professor Computer Science and Engineering Govt. Engineering College Thrissur India Assistant Professor Computer Science and Engineering Govt. Engineering College Thrissur India

Cyber-attacks targeting organisations and individuals are getting worse day by day. With the technological improve-ments, the principles used to launch attacks are also varied. Intrusion Detection System (IDS) is a network solution to detect attacks and anomalies in the network. Leveraging Machine Learning for developing an IDS can make it more powerful. This work aims at evaluating the performance of machine learning models for Intrusion Detection System built based on CART Algorithm, ID3Decision tree algorithm, Random forest algorithm with Convolutional Neural Network. The model is built using KDD Cup99 Dataset. In this work we perform Linear Correlation and Mutual Information feature selection algorithms for ML algorithms and for Convolutional Neural Network algorithm being a deep learning technique feature selection happens automatically. Analysing various parameters including F1-score, ID3 has shown better results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Introducing Service Learning To Under Graduate engineering Students Through EPICS

引用

Procedia computer science 2020年 172卷 688-695页

作者： Santosh Madeva Naik Surendra Bandi Hema Mahajan Assistant Professor Department of Mechanical Engineering HITAM Hyderabad Telangana 501401 India Associate Professor Department of Computer Science Engineering HITAM Hyderabad Telangana 501401 India Assistant Professor Department of Computer Science Engineering HITAM Hyderabad Telangana 501401 India

This paper describes the introduction of doing engineering through the "engineering Project in Community Service (EPICS)" and the impact of a community-based learning approach on student motivation. Students get practical hands-on experience while working with non-profit organizations. Now a day’s students find it difficult to learn in the traditional way of classroom teaching chalk and board. They want to work on real-time problems with community partners by applying engineering knowledge. EPICS program helps in grooming the students’ skills in design, communication, teamwork, and develop leadership skills, facing the challenges, social awareness, multidisciplinary knowledge, solution-driven approach towards a problem and maintaining social relationships. EPICS is one of the IUCEE (Indo Universal Collaboration for engineering Education) initiative where students are exposed to study the community needs and frame an engineering problem to work on further.

关键词： EPICS Community partner Design process Team work Products

来源：评论

学校读者我要写书评

暂无评论

Artificial super intelligence: Barriers and limitations

引用

AIP Conference Proceedings 2024年第1期3209卷

作者： Rahul Goyal Neha Sharma Amanpreet Kaur Student Department of Computer Science and Engineering Chitkara University Institute of Engineering & technology Chitkara University Punjab India. Assistant Professor Department of Computer Science and Engineering Chitkara University Institute of Engineering & Technology Chitkara University Punjab India Professor Department of Computer Science and Engineering Chitkara University Institute of Engineering & Technology Chitkara University Punjab India.

In urban studies, artificial intelligence systems are a widely recognized technology that provides an alternate approach to dealing with complicated and dynamic issues. Despite the risks of implementing more powerful artificial intelligence, many big tech companies are working towards it. So, this paper aims to show the barriers to artificial intelligence. Also, this paper illustrates barriers in machines that prevent artificial superintelligence from being achieved. Further, the paper discusses how machine neural networks differ from human neural networks and the existential threats posed by artificial intelligence and superintelligence.

关键词：

来源：评论

学校读者我要写书评

暂无评论

IoT for Smart City Planning and Development

IoT for Smart City Planning and Development

引用

International Conference on Computational and Characterization Techniques in engineering & sciences (CCTES)

作者： Raman Tirpude A. Vinitha Ahmed Kateb Jumaah Al-Nussairi Hawraa Ali Sabah Maki Mahdi Abdulhasan Manar Kareem Lafta Department of Management Research Scholar Ramdeobaba University and Assistant Professor at Maharashtra National Law University Nagpur Department of Computer Science Karpagam Academy of Higher Education Coimbatore Al-Manara College for Medical Sciences Amarah Iraq College of Technical Engineering National University of Science and Technology Dhi Qar Iraq Department of Technology Al-Nisour University College Baghdad Iraq Department of Pharmacy Mazaya University College Iraq

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

Urban planning and development have undergone a complete transformation with the advent of the Internet of Things (IoT), and groundbreaking technologies have been made available for smart city efforts. The inclusion of Internet of Things (IoT) technology in the design and development of smart cities is examined in this article. The significance that these technologies play in improving resource management, modernizing urban infrastructure, and elevating people's quality of life is given special consideration. This paper evaluates existing Internet of Things (IoT) applications, like intelligent transportation systems, smart grids, and environmental monitoring, to show how the Internet of Things (IoT) might address common urban issues like traffic congestion, energy consumption, and environmental pollution. Furthermore, the essay examines case studies submitted by well-known smart cities to show how the Internet of Things (IoT) may be successfully used and how it affects the sustainability and efficiency of metropolitan areas. The results suggest that the Internet of Things not only facilitates real-time data collection and analysis but also fosters the creation of creative urban development ideas. Thanks to the research that was done, this study shows how the Internet of Things has the potential to impact future cities and make them more resilient, adaptable, and effective in meeting the needs of growing populations.

关键词： Pollution Smart cities Urban planning Transportation Data collection Real-time systems Smart grids Internet of Things Environmental monitoring Sustainable development

来源：评论

学校读者我要写书评

暂无评论

Site reliability engineering for IOS mobile application in small-medium scale industries

Global Transitions Proceedings

引用

Global Transitions Proceedings 2021年第2期2卷 137-144页

作者： N Kavyashree Dr. Supriya M C Dr. Lokesh M R SSAHE Tumkur Assistant Professor Dr.AIT Bangalore Karnataka India Department of MCA SSIT Tumkur Karnataka India Department of computer Science and Engineering MITM Mandya Karnataka India

Software reliability is one and only the standard used to calculate the excellence of a software system. In this situation, we suggest a method to forecast software reliability in the primary creation of any process growth phases since from the designing stage only. Software mobile application has remained a significant tool in our lifetime, and several small-medium scale software progress companies capitalize the substantial resources to mark accessible prospects. The landscape of mobile atmospheres varies as of server environments owing to various issues, by means of the net, liveliness, battery-operated, and compatibility. Estimating and forecasting mobile application reliability remain the actual contests as of the variety of the mobile situations in which the applications are used, and the absence of widely available fault data. In addition, error information is optionally given in to the end-users. Hence, in what way to estimate reliability of mobile software application has remained more and more significant. In this paper, site reliability engineering (SRE) for mobile application is proposed for the reliability of software and is taken as a case study. Their failure is copied back to the exact features of mobile application is useful and powerful.

关键词： Fault report Mobile application Site reliability engineering Software forecast Software reliability SRGM Model

来源：评论

学校读者我要写书评

暂无评论

Reinforcement learning: A novel approach towards drug discovery

引用

AIP Conference Proceedings 2023年第1期2477卷

作者： Nishath Ansari Amjan Shaik Patluri Harika Boga Varasree K. Purnachand Saikumar Tara Assistant Professor Department of Computer Science and Engineering B V Raju Institute of Technology Narsapur Telangana India Professor Department of Computer Science and Engineering B V Raju Institute of Technology Narsapur Telangana India Assistant Professor Department of Computer Science and Engineering Institute of Aeronautical Engineering Dundigal Hyderabad Telangana India Assistant Professor Department of Information Technology Institute of Aeronautical Engineering Dundigal Hyderabad Telangana India Associate Professor Department of Computer Science and Engineering B V Raju Institute of Technology Narsapur Telangana India Associate Professor Department of Electronics and Communication Engineering CMR Technical campus Hyderabad Telangana India

Reinforcement learning has been giving new strategies to ad-lib in the fields of medication and the drug industry. It is probably the best strategy among all the AI strategies. Reinforcement learning has been compelling to discover strategies that could treat the immense number of deadly infections. In this paper, a detailed new methodology about what Reinforcement Leaning and what is drug revelation and what are various techniques utilized in Reinforcement learning, how Reinforcement learning could be utilized in different utilization of medication plan such as target identification, hit discovery, hit to lead, lead optimization. The consequence of the paper illustrates the summarized data of different approaches for the development and discovery of drugs. A clear illustration of various work done in the field of drug discovery, discuss different pros and cons of Reinforcement learning as well emphasize primary challenges need to handle and how to defeat them in the future.

关键词：

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：