检索结果-内蒙古大学图书馆

Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah Song Jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

来源：评论

学校读者我要写书评

暂无评论

An Initial Risk Assessment for Multimodal with LSTM-Based Trust Evaluation Framework for Autonomous Vehicle Security

引用

SN computer science 2025年第2期6卷 1-15页

作者： Renjith, P.N. Balasubramani, S. Ramesh, K. Patnala, Eswar School of Computer Science and Engineering Vellore Institute of Technology Chennai Campus Chennai India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore India

This research aims to develop a new approach to increase the safety and reliability of Autonomous Vehicle (AV) through the proposed risk assessment framework, supported by the trust evaluation approach derived from a machine learning algorithm. This work proposes a comprehensive risk assessment model with real-time sensor data, Vehicle-to-Vehicle (V2V), key communication reliability, environmental cognition, and Improved Long Short-Term Memory (I-LSTM). This framework is multidimensional compared to most conventional models, focusing primarily on assessing individual threat factors. Here, the machine learning portion is designed to evaluate and predict trust by quickly processing vast amounts of information from sensors, signals, and prior operation history. Such an approach to trust assessment enables the system to continuously evaluate the dependability of automated vehicle operation and identify threats to security with improved accuracy. The effectiveness of the performance of this method is substantiated by a number of stand-alone and live scenarios, where the model's performance is higher in perceiving possible risks, avoiding threats, and enhancing safety than the conventional approaches. The findings suggest that the safety regulations of the AVs will be improved by using a multi-dimensional risk assessment model and integrating the I-LSTM trust rating with 95.5% accuracy, 96.7% risk identification, and 180 ms response time. This will cause AV and its surrounding environment to be accepted by the public and used on the roads. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Autonomous vehicles LSTM model Machine learning Risk assessment Trust evaluation

来源：评论

学校读者我要写书评

暂无评论

Cyber Hacking Breaches Prediction and Detection Using Machine Learning 2

Cyber Hacking Breaches Prediction and Detection Using Machin...

引用

2nd IEEE International Conference on Innovations in High-Speed Communication and Signal Processing, IHCSP 2024

作者： Santha Sheela, K. Mrithula, M. Varshni Priya, A. Selvalakshmi, C.B. Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368949

Cyber hacks threaten organizations of every kind around the world;thus, they surely require stringent methodologies that would predict and detect them. In this paper, we discuss machine learning approaches to enhance identification and forecasting of a cyber attack by analyzing historical data. Several machine learning approaches such as decision trees, support vector machines, and neural networks are applied in sequence to extract patterns and anomalies related to potential breaches. It develops predictive models for identifying vulnerabilities and discovers features from network traffic, system logs, and user behavior up in near-real time. Metrics of performance such as accuracy, precision, and recall evaluate these algorithms to compare the effectiveness of established and emerging attack vectors. The findings suggest that machine learning significantly enhances the speed and accuracy of breach detection when compared with traditional methods. This advanced technique, applied in an organization's framework of cybersecurity, predicts cyber threats effectively and neutralizes them to increase resilience in overall security. © 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 Predictive and Adaptive Mobile/Web Application for Alzheimers Disease Using Machine Learning 9

A Predictive and Adaptive Mobile/Web Application for Alzheim...

引用

9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Balamuralikrishnan, G. Boomika, S. Sri Nandhini, R. Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377972

A neurodegenerative condition, Alzheimer's disease (AD) affects millions of individuals globally, that causes memory loss and cognitive impairment. Improving patient outcomes and delaying the course of disease need early detection and continuous treatment. The paper proposes a predictive and adaptive mobile/web application for Alzheimer's disease management, leveraging transfer learning. In this research, we utilize transfer learning techniques, specifically with pre-trained deep learning architectures like ResNet and VGG. These models, originally trained on large datasets, are fine-tuned with Alzheimer's disease-specific data to enhance diagnostic accuracy and efficiency within our mobile/web application. By offering cognitive activities, remote health tracking, and personalized care, the platform improves patient involvement and aids medical professionals in managing patient conditions. Transfer learning increases diagnostic precision while requiring less data. © 2024 IEEE.

关键词： Transfer learning

来源：评论

学校读者我要写书评

暂无评论

HOG-Based Feature Extraction for Accurate Modi Script Character Recognition 2

HOG-Based Feature Extraction for Accurate Modi Script Charac...

引用

2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Ingole, Ketki R. Tijare, Pritish Sipna College of Engineering and Technology Department of Computer Science and Engineering Amravati India

ISBN: (纸本)9798331528713

Modi is an old script used for documentation in Maharashtra that dates to the 17th century. With time the writing style of the script changes, and a lot of variation occurred till date. In the 20th century, due to a lack of awareness and understanding about the Modi-script, it disappeared and was replaced by the Devanagari. Manuscripts with Modi-script have not yet been explored, the information present in it remains unrevealed. To unfold the knowledge and develop a HOCR method for recognizing Modi characters, first need to understand the structural features of Modi characters. The main aim of this paper is to explore the structural features of the Modi characters that help in extracting the features. © 2024 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

System Sound Control Using Gesticulations 8th

System Sound Control Using Gesticulations

引用

8th International Conference on computers, Management and Mathematical sciences, ICCM 2022

作者： Uzair, Mohammed Department of Computer Science and Engineering Methodist College of Engineering and Technology Hyderabad India

ISBN: (纸本)9783031511660

Artificial intelligence is a field of computer science dedicated to solving reasonable problems mostly associated with human intelligence such as pattern recognition and problem solving. This chapter proposes a project controlling the sound (increasing or decreasing the volume) of a computer or a laptop using real-time hand gestures as input through a web camera, which is not necessarily a high-resolution camera, which makes it a cost-efficient project. Making use of gestures is one of the leading aspects contributing toward artificial intelligence and development in the field of technology. This project is implemented using the Python programming language. Here, we make use of the OpenCV library of Python to read the gestures from the user through the web camera. OpenCV is a widely used tool for processing images. To perform hand recognition and hand processing, we make use of the Hand Landmark Model of the MediaPipe Hands library of Python. To control the audio or volume of the system, we make use of the PyCaw Library of Python. Using these Python libraries makes it easy to implement complex projects as most of the required operations or functionalities can be done using a pre-defined function in the particular library. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Petoria-Your Pet's Ultimate Companion

Petoria-Your Pet's Ultimate Companion

引用

2024 MIT Art, Design and technology School of Computing International Conference, MITADTSoCiCon 2024

作者： Jiju, Anargh Ajayakumar, Adharsh P Paul, Edwin Shajan, John Sukumaran, Sruthy Sahrdaya College of Engineering and Technology Department of Computer Science and Engineering Thrissur India

ISBN: (纸本)9798350362879

Pet owners often face challenges in ensuring their pet's well-being, such as receiving timely advice on health and behavior and managing complex tasks like medication schedules and grooming appointments. The lack of personalized guidance and inconsistency in sourcing high-quality pet products can contribute to suboptimal choices. Our comprehensive solution aims to simplify and enhance the pet ownership experience by bridging the gaps in advice, management, and product sourcing. By providing personalized guidance, expert advice, and a curated selection of high-quality pet products, our solution creates a more rewarding and stress-free journey for pets and their devoted owners. © 2024 IEEE.

关键词： Artificial intelligence E-commerce Pet care management

来源：评论

学校读者我要写书评

暂无评论

TrackBot: Building an Intelligent Multipurpose Line Follower Robot 3

TrackBot: Building an Intelligent Multipurpose Line Follower...

引用

3rd International Conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Selva Lakshmi, C.B. Sandheep, S. Mani Ashwin Raaj, M. Harish Kumar, P. Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9798350396157

Robots are the solutions for replacing humans from dangerous and manual labour. Repetitive, non-creative manual tasks can be automated by using robots. One of the principal approaches to automate robots is by line sensing principle. We create a robot that acquires the front view using a camera mounted on the vehicle then applying few processes in order to detect the lines thereby steering the vehicle autonomously. © 2024 IEEE.

关键词： Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

NIDR: Network Interference Detection and Rectification 4

NIDR: Network Interference Detection and Rectification

引用

4th International Conference on Innovative Practices in technology and Management, ICIPTM 2024

作者： Rose Mary, K.A. Joy, Celestine Devis, Denin Fransisco, Irene Devassy, Deepa George, Livya Sahrdaya College of Engineering and Technology Department of Computer Science and Engineering Thrissur India

ISBN: (纸本)9798350307757

In the contemporary digital landscape, ensuring the continuous functionality of computer networks is vital for business and critical infrastructure success. This research project utilizes cutting-edge technologies like machine learning and anomaly detection to monitor network traffic and system logs. Through in-depth analysis of traffic patterns, identification of attack signatures, and prompt anomaly detection, the system provides accurate and timely identification of network attacks. Key components include real-time monitoring, comprehensive attack signature databases, and intelligent alerting for swift response, aiming to empower small-scale organizations in safeguarding their data and effectively responding to evolving cyber threats. © 2024 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive Networks and Archerfish Optimization

引用

computers, Materials & Continua 2024年第9期80卷 4791-4812页

作者： Ahmad Yahiya Ahmad Bani Ahmad Jafar Alzubi Sophers James Vincent Omollo Nyangaresi Chanthirasekaran Kutralakani Anguraju Krishnan Department of Accounting and Finance Faculty of BusinessMiddle East UniversityAmman11831Jordan Faculty of Engineering Al-Balqa Applied UniversitySalt19117Jordan Department of Mathematics Kongunadu College of Engineering and Technology(Autonomous)TholurpattiTrichy621215India Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo210-40601Kenya Department of Electronics and Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Department of Electronics and Communication Engineering Saveetha Engineering College(Autonomous)Chennai602105India Department of Computer Science and Engineering Kongunadu College of Engineering and Technology(Autonomous)TholurpattiTrichy621215India

In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant *** developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basic *** images captured by wearable sensors contain advanced features,allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human *** lighting and limited sensor capabilities can impact data quality,making the recognition of human actions a challenging *** unimodal-based HAR approaches are not suitable in a real-time ***,an updated HAR model is developed using multiple types of data and an advanced deep-learning ***,the required signals and sensor data are accumulated from the standard *** these signals,the wave features are *** the extracted wave features and sensor data are given as the input to recognize the human *** Adaptive Hybrid Deep Attentive Network(AHDAN)is developed by incorporating a“1D Convolutional Neural Network(1DCNN)”with a“Gated Recurrent Unit(GRU)”for the human activity recognition ***,the Enhanced Archerfish Hunting Optimizer(EAHO)is suggested to fine-tune the network parameters for enhancing the recognition *** experimental evaluation is performed on various deep learning networks and heuristic algorithms to confirm the effectiveness of the proposed HAR *** EAHO-based HAR model outperforms traditional deep learning networks with an accuracy of 95.36,95.25 for recall,95.48 for specificity,and 95.47 for precision,*** result proved that the developed model is effective in recognizing human action by taking less ***,it reduces the computation complexity and overfitting issue through using an optimization approach.

关键词： Human action recognition multi-modal sensor data and signals adaptive hybrid deep attentive network enhanced archerfish hunting optimizer 1D convolutional neural network gated recurrent units

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：