检索结果-内蒙古大学图书馆

Design of Six Element MIMO Antenna with Enhanced Gain for 28/38 GHz mm-Wave 5G Wireless Application

computer Systems science & engineering 2023年第8期46卷 1689-1705页

作者： K.Jayanthi A.M.Kalpana Department of Electronics and Communication Engineering Government College of EngineeringSalemIndia Department of Computer Science and Engineering Government College of EngineeringSalemIndia

The fifth-generation(5G)wireless technology is the most recent standardization in communication services of interest across the *** concept of Multiple-Input-Multiple-Output antenna(MIMO)systems has recently been incorporated to operate at higher frequencies without *** paper addresses,design of a high-gain MIMO antenna that offers a bandwidth of 400 MHz and 2.58 GHz by resonating at 28 and 38 GHz,respectively for 5G millimeter(mm)-wave *** proposed design is developed on a RT Duroid 5880 substrate with a single elemental dimension of 9.53×7.85×0.8 mm^(3).The patch antenna is fully grounded and is fed with a 50-ohm stepped impedance microstrip *** also has an I-shaped slot and two electromagnetically coupled parasitic slotted *** design is initially constructed as a single-element structure and proceeded to a six-element MIMO antenna configuration with overall dimensions of 50×35×0.8 mm^(3).The simulated prototype is fabricated and measured for analyzing its performance characteristics,along with MIMO antenna diversity performance factors making the proposed antenna suitable for 5G mm-wave and 5G-operated handheld devices.

关键词： MIMO antenna parasitic elements 5G mm-wave dual band frequency diversity factors

来源：评论

学校读者我要写书评

暂无评论

Integrating the Internet of Things to Protect Electric Vehicle Control Systems from Cyber Attacks

引用

IAENG International Journal of Applied Mathematics 2024年第3期54卷 433-440页

作者： Bhukya, Baddu Naik Venkataiah, V. Kuchibhatla, S. Mani Koteswari, S. Kumari, R.V.S. Lakshmi Raju, Yallapragada Ravi Department of Electrical and Electronics Engineering Prasad V. Potluri Siddhartha Institute of Technology Andhra Pradesh Vijayawada India Department of Computer Science Engineering CMR College of Engineering & Technology Telangana Hyderabad India Department of Electrical and Electronics Engineering ACE Engineering College Telangana Hyderabad India Department of Electronics and Communication Engineering Pragati Engineering College Kakinada India Andhra Pradesh Surampalem India Department of Electrical and Electronics Engineering Gayatri Vidya Parishad College of Engineering for Women Andhra Pradesh Visakhapatnam India Department of Computer Science and Technology Madanapalle Institute of Technology and Science Andhra Pradesh India

The Internet of Things (IoT) facilitates the delivery of intelligent services by sensing, gathering, processing, and exchanging data from millions of linked smart devices. The Internet of Things (IoT), which is based on communication infrastructure, provides real-time cyber-physical device monitoring, control, and sensing, such as electric autos. Traditional communication infrastructure's vulnerability to cyberattacks hampered IoT's capacity to investigate these potential applications. This study proposes an algorithm for monitoring and controlling electric vehicles through the Internet of Things communication network to prevent fake data injection attacks. A state-space model depicts a fully autonomous electric car equipped with a vision system. Intelligent sensors and actuators from the Internet of Things are utilized to monitor and change system conditions, compensating for the large distance between the electric car and the control center. Sensing data is delivered from the vehicle to the central command center via an insecure, attack-prone communication path. The mean square error approach is used to derive states in the most effective state estimation system for comprehending and showing autos. A semi-definite programming approach is used to create an optimal control algorithm to manage the vehicle states. The simulation results show how precisely and successfully the proposed algorithms can foresee and regulate a vehicle's state. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

From Perception to Action: Building a Robust AI System for Safe and Adaptive Autonomous Driving 15

From Perception to Action: Building a Robust AI System for S...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Taha, Adnan Sabith Hossain, Md Rafat Esha, Sheikh Aysha Khatun Pantha, Iffat Mahmud Riya, Aparna Sarker Uddin, Md.Jamil Shakur, Md. Abdus Computer Science and Engineering Bangladesh Pace University Data Science United States North South University Computer Science and Engineering Bangladesh Brac University Computer Science and Engineering Bangladesh Eastern University Electrical and Electronics Engineering Bangladesh Electrical and Electronics Engineering Bangladesh

ISBN: (纸本)9798350370249

This study explores the development of a self-driving car using a combination of deep learning (DL), machine learning (ML), computer vision (CV), and convolutional neural networks (CNN). The proposed system aims to simulate human-like decision making in response to external conditions encountered during autonomous driving. The approach involves real-time on-road testing and a self-training mechanism to enable the car to continuously learn and adapt. Furthermore, the text suggests an investigation into the fundamental principles of artificial intelligence (AI) and their role in the autonomous car's functionality. © 2024 IEEE.

关键词： Control Perception Planning Self-driving car

来源：评论

学校读者我要写书评

暂无评论

An Electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

引用

Tsinghua science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar Ayman Amer Mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap Electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

来源：评论

学校读者我要写书评

暂无评论

SMART DRIVING LICENSING SYSTEM AND AUTHORIZATION OF AUTONOMOUS VEHICLE INTEGRATING WIRELESS SENSOR NETWORKS AND IoT

引用

Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2024年第9期83卷 69-85页

作者： Santhakumar, D. Sudhan, M.B. Prasanna, R. Manikandan, S.P. Prathaban, Banu Priya Kanna, Rajesh R. Saravanan, G. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai Ramapuram India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering Sree Sastha Institute of Engineering and Technology Chennai India Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering Sri Sairam Institute of Technology Tamil Nadu Chennai India

The advent of autonomous vehicles has revolutionized the automotive industry, offering promising advancements in safety, efficiency, and mobility. To integrate these autonomous vehicles into our society seamlessly, it is imperative to establish a robust licensing system that ensures the safe operation of automated vehicles on public roads. This article presents an effective smart Driving Licensing System (SDLS), a digital framework designed to regulate the existing licensing system and authorize licensing for autonomous vehicles. Through a comprehensive assessment process, the system assesses the drivers and the autonomous vehicle’s ability to navigate various road conditions, respond to dynamic environments, and prioritize safety for passengers and other road users. SDLS integrates high-level security through facial and fingerprint verification for identity verification to preserve licensing data. Hacking and unauthorized access to autonomous vehicles is prevented by robust cybersecurity protocols. The key benefits of SDLS include automated data collection, integration of wireless sensor networks (WSN) and Internet of Things (IoT), smart application processing, real-time license checks, cybersecurity measures, automated testing, and digital certification. The proposed system offers a comprehensive approach to safely integrating autonomous vehicles into our transportation ecosystem. The autonomous vehicles are integrated with antennas at rooftops or into bumpers, depending upon the vehicle design which can be connected with the SDLS for signal communication. Furthermore, the SDLS establishes a framework for continuous monitoring and updates, enabling ongoing assessments to keep pace with evolving technology and safety standards. © 2024 by Begell House, Inc.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Classroom Engagement with Face Recognition and Attention-Based Attendance 3

Revolutionizing Classroom Engagement with Face Recognition a...

引用

3rd International Conference on Disruptive Technologies, ICDT 2025

作者： Thakur, Anushka Pande, Aayush Pande, Naincy Khandelwal, Richa Dwibedy, Prashant Ramdeobaba University Department of Electronics and Computer Science Engineering Nagpur India Ycce Department of Computer Science Engineering Nagpur India Ramdeobaba University Department of Electronics Engineering Nagpur India

ISBN: (纸本)9798331519582

Modern educational environments require effective and efficient systems to track attendance and participation to ensure better learning outcomes and increased productivity. Traditional systems often mark attendance automatically, regardless of the level of student engagement. This paper introduces a novel system, 'Revolutionizing Classroom Engagement with Face Recognition and Attention-Based Attendance,' designed to detect multiple faces in real time and automate the process of attendance marking based on students' attention levels. In contrast to traditional methods, attendance is only recorded when students surpass a predefined attention threshold (e.g. 75%) based on their focus during the lecture. This approach fosters a more dynamic, interactive, and focused learning environment. The proposed system leverages advanced face detection and recognition techniques, integrating Haar Cascade Classifiers, Deep Learning-based Face Detection, and K-Nearest Neighbors (KNN) to offer robust and accurate identification even in large, diverse classrooms. Real-time video processing is handled by OpenCV, which captures and analyzes classroom footage, while NumPy processes complex numerical computations for image data. Pandas is utilized for efficient attendance logging, storing data in easily accessible CSV files. The system's attention-tracking feature is another key innovation, as it analyzes students' gaze and behavioral cues to assess their level of engagement. This ensures that attendance is only recorded when students are genuinely focused and attentive. Designed to be scalable and non-intrusive the system can be adapted to classrooms of varying sizes and is easily incorporated into existing educational frameworks. By providing accurate attendance tracking and engagement analysis, the system not only simplifies administrative tasks but also contributes to fostering a smarter, more engaging, and more productive classroom environment. © 2025 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Abusive adversarial agents and attack strategies in cyber-physical systems

引用

CAAI Transactions on Intelligence Technology 2023年第1期8卷 149-165页

作者： Viraj Singh Gaur Vishal Sharma John McAllister School of Electronics Electrical Engineering and Computer ScienceQueen's University BelfastBelfastUK

The exponential increase in IoT device usage has spawned numerous cyberspace *** devices,sensors,and actuators bridge the gap between physical processes and the cyber network in a cyber-physical system(CPS).Cyber-physical system is a complex system from a security perspective due to the heterogeneous nature of its components and the fact that IoT devices can serve as an entry point for *** adversaries design their attack strategies on systems to gain an advantage at a relatively lower cost,whereas abusive adversaries initiate an attack to inflict maximum damage without regard to cost or *** this paper,a sensor spoofing attack is modelled as a malicious adversary attempting to cause system failure by interfering with the feedback control *** is accomplished by feeding spoofed sensor values to the controller and issuing erroneous commands to the *** on a Simulink-simulated linear CPS support the proof of concept for the proposed abusive ideology,demonstrating three attack *** impact of the evaluations stresses the importance of testing the CPS security against adversaries with abusive settings for preventing ***,the research concludes by highlighting the limitations of the proposed work,followed by recommendations for the future.

关键词： intelligent systems security security evaluation

来源：评论

学校读者我要写书评

暂无评论

WiFo: wireless foundation model for channel prediction

引用

science China(Information sciences) 2025年第6期68卷 372-384页

作者： Boxun LIU Shijian GAO Xuanyu LIU Xiang CHENG Liuqing YANG State Key Laboratory of Photonics and Communications School of Electronics Peking University Internet of Things Thrust The Hong Kong University of Science and Technology (Guangzhou) Department of Electronic and Computer Engineering and Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology

Channel prediction permits to acquire channel state information(CSI) without signaling overhead. However,almost all existing channel prediction methods necessitate the deployment of a dedicated model to accommodate a specific configuration. Leveraging the powerful modeling and multi-task learning capabilities of foundation models, we propose the first space-time-frequency(STF) wireless foundation model(WiFo) to address time-frequency channel prediction tasks in a unified manner. Specifically, WiFo is initially pre-trained over massive and extensive diverse CSI datasets. Then, the model will be instantly used for channel prediction under various CSI configurations without any fine-tuning. We propose a masked autoencoder(MAE)-based network structure for WiFo to handle heterogeneous STF CSI data, and design several mask reconstruction tasks for self-supervised pre-training to capture the inherent 3D variations of CSI. To fully unleash its predictive power, we build a large-scale heterogeneous simulated CSI dataset consisting of 160k CSI samples for *** validate its superior unified learning performance across multiple datasets and demonstrate its state-of-the-art(SOTA) zero-shot generalization performance via comparisons with other full-shot baselines.

关键词： channel prediction channel state information foundation model self-supervised pre-training zero-shot learning

来源：评论

学校读者我要写书评

暂无评论

FusionEXNet: an interpretable fused deep learning model for skin cancer detection

引用

International Journal of computers and Applications 2024年第9期46卷 743-753页

作者： Gautam, Yuvika Gupta, Piyush Kumar, Deepika Kalra, Bhavya Kumar, Abhinav Hemanth, Jude D. Department of Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering New Delhi India Department of Electronics & Communication Engineering Karunya Institute of Technology and Sciences Coimbatore India

Skin cancer poses a significant burden on mankind and healthcare systems globally, necessitating the development of effective diagnostic and treatment strategies. This paper introduces FusionEXNet, an innovative and interpretable fused deep-learning model for skin cancer detection. FusionEXNet leverages the strengths of EfficientNetV2S and XceptionNet architectures to extract robust features from dermoscopic images, achieving superior performance compared to individual models. While XceptionNet and EfficientNetV2S attained accuracies of 88.82% and 88.01%, respectively, FusionEXNet surpassed them with an impressive accuracy of 90.83%. To enhance model interpretability, Explainable Artificial Intelligence (XAI) techniques, such as SmoothGrad and Faster Score-CAM, are integrated, providing valuable insights into the decision-making process. The model was trained and evaluated using the extensive HAM10000 dataset, consisting of over 10,000 high-resolution images across seven skin lesion categories. The proposed FusionEXNet model offers a reliable, accurate, and interpretable system for skin cancer detection, contributing to improved patient outcomes and more efficient diagnostic processes. This study underscores the potential of combining advanced CNN architectures with XAI methods to create powerful tools for dermatological diagnostics. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR)in WSNs

引用

computer Systems science & engineering 2023年第1期44卷 99-112页

作者： D.Loganathan M.Balasubramani R.Sabitha S.Karthik Department of Electronics and Communication Engineering Info Institute of EngineeringCoimbatore641107India Department of Computer Science and Engineering SNS College of TechnologyCoimbatore641035India

Sensors are considered as important elements of electronic *** many applications and service,Wireless Sensor Networks(WSNs)are involved in significant data sharing that are delivered to the sink node in energy efficient man-ner using multi-hop ***,the major challenge in WSN is the nodes are having limited battery resources,it is important to monitor the consumption rate of energy is very much ***,reducing energy con-sumption can increase the network lifetime in effective *** that,clustering methods are widely used for optimizing the rate of energy consumption among the sensor *** that concern,this paper involves in deriving a novel model called Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR),which mainly concentrates on optimal energy utilization with load-balanced process among cluster heads and member *** providing equal rate of energy consumption among nodes,the dimensions of framed clusters are ***,the model develops a Finest Routing Scheme based on Load-Balanced Clustering to transmit the sensed information to the sink or base *** evaluation results depict that the derived energy aware model attains higher rate of life time than other works and also achieves balanced energy rate among head ***,the model also provides higher throughput and minimal delay in delivering data packets.

关键词： Wireless sensor networks energy consumption load balanced clustering finest routing

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：