检索结果-内蒙古大学图书馆

International Conference on Energy, Power, Environment, Control and Computing (ICEPECC 2025)

作者： Rao Behram Umer Farhan Mushtaq Faisal Hammad Khan Muhammad Nouman Usman Hassan Amanullah Muhammad Adnan Photonics And Communication Lab Department of Electrical Engineering University of Engineering & Technology Taxila Pakistan Electronics and Communication Systems Lab Department of Telecommunication Engineering University of Engineering & Technology Taxila Pakistan School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan

ISBN: (数字)9781837243150

Li-Fi is another term for Visible light communication (VLC) which operates by transmitting data through free space by using eith er Light Emitting Diodes (LEDs) or Laser Diodes (LDs). The technique finds substantial applications in scientific research as we ll as military applications when used underwater. VLC technology helps eliminate radio interference alongside providing replacement solutions for traditional underwater communication systems. The research develops and models a visible light wireless communication system through ambient light testing with two 550 nm and 450 nm LD light sources and Pin photodetector over 10 meters using Opti System software. The system uses Non-Return-to-Zero On-Off Keying (NRZ OOK) also known as Amplitude Shift Keying (ASK) modulation through Mach-Zehnder Modulator with WDM technology in NLOS environment. A 10 Gbps data transmission occurs through the clear ocean environment along a 10-meter channel with 0.0405 1/m absorption and 0.0025 1/m scattering. The 550 nm transmitted source emits its maximum Quality factor as 8.35 when BER analyzers operate under ambient light conditions and produce its minimum BER as 4.89e-11 under the same conditions. Examining similar ambient light influences reveals the BER analyzers demonstrate a maximum Quality factor of 8.62 and minimum BER of 18.11e-12 when operating under 450 nm transmitted light.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Benchmarking Semantic communications for Image Transmission Over MIMO Interference Channels

arXiv

引用

arXiv 2024年

作者： Wang, Yanhu Guo, Shuaishuai Dong, Anming Zhao, Hui School of Control Science and Engineering Shandong Key Laboratory of Wireless Communication Technologies Shandong University Jinan250061 China The School of Computer Science and Technology Qilu University of Technology Jinan250353 China The Communication Systems Department EURECOM Sophia Antipolis 06410 France

Semantic communications offer promising prospects for enhancing data transmission efficiency. However, existing schemes have predominantly concentrated on point-to-point transmissions. In this paper, we aim to investigate the validity of this claim in interference scenarios compared to baseline approaches. Specifically, our focus is on general multiple-input multiple-output (MIMO) interference channels, where we propose an interference-robust semantic communication (IRSC) scheme. This scheme involves the development of transceivers based on neural networks (NNs), which integrate channel state information (CSI) either solely at the receiver or at both transmitter and receiver ends. Moreover, we establish a composite loss function for training IRSC transceivers, along with a dynamic mechanism for updating the weights of various components in the loss function to enhance system fairness among users. Experimental results demonstrate that the proposed IRSC scheme effectively learns to mitigate interference and outperforms baseline approaches, particularly in low signal-to-noise (SNR) regimes. © 2024, CC BY.

关键词： Channel state information

来源：评论

学校读者我要写书评

暂无评论

An effective approach for detecting deepfake videos using Long Short-Term Memory and ResNet

An effective approach for detecting deepfake videos using Lo...

引用

International Conference on communication, Computing and Internet of Things (IC3IoT)

作者： S Keerthana N Deepika E Pooja I Nandhini M Shanthalakshmi G R Khanaghavalle Department of Computer Science and Engineering Sri Venkateswara College of Engineering Pennalur Sriperumbudur Tamilnadu India Department of Computer Science and Business Systems Rajalakshmi Institute of Technology Kuthambakkam Tamilnadu India Department of ECE School of Electrical and Communication Vel Tech Rangarajan Dr. Sakunthala R&D Institute of Science and Technology Avadi

ISBN: (数字)9798350352689

ISBN: (纸本)9798350352696

Deep learning algorithms are becoming more potent and producing human-synthesized, undifferentiated footage is a simple process thanks to advances in computing power. A method of synthesizing human images called deep fakes is built on neural network techniques like GAN. These technologies use deep learning algorithms to overlay target pictures onto the source films, producing realistic-looking deep-fake photos and videos. In this work, we provide a novel deep-learning approach that can reliably discriminate between actual and AI-generated fake videos. In this work, we test our method on a large number of balanced and mixed datasets created by mixing various publicly available datasets, such as Face-Forensic++, Deepfake detection, Celeb DF, and other publicly available datasets as images and videos, to emulate real-time scenarios and improve model performance with real-time data by using LSTM and ResNet.

关键词： Deep learning Deepfakes Films Neural networks Generative adversarial networks Real-time systems Telecommunication computing

来源：评论

学校读者我要写书评

暂无评论

Analysis and Design of Mobile Model for DTN

引用

Chinese Journal of Electronics 2023年第4期18卷 635-638页

作者： Zhiting Lin Yugui Qu Yusheng Ji Baohua Zhao Department of Computer Science University of Science and Technology of China Hefei China Province Key Laboratory of Software in Computing and Communication Hefei China Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan

Delay tolerant networks may become unexpectedly partitioned due to node mobility or variation in signal strength. However, most widely used models in some relative works are generally very simplistic. In order to exploit intelligent forwarding algorithms, a novel nodal mobile model of delay tolerant networks is presented to map reality with more accuracy. And several approaches are introduced to analyze the network structure, such as n-cliques, n-clans, degree, closeness and betweenness. Our research results showed that the centralizations became smaller when the wireless connections were concerned. It meant that quite a number of nodes became potential relays because of the new structure of networks.

关键词： Wireless communication Analytical models Wireless sensor networks Protocols Social networking (online) Sensitivity analysis Social network theory

来源：评论

学校读者我要写书评

暂无评论

Near-Far Field Three-Stage Beam Training for RIS-Assisted Wideband OFDM communications

Near-Far Field Three-Stage Beam Training for RIS-Assisted Wi...

引用

IEEE Conference on Wireless communications and Networking

作者： Zhichao Cheng Shupei Zhang Shu Fu Boya Di School of Electronics Engineering and Computer Science Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China Department of Microelectronics and Communication Engineering Chongqing University Chongqing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Large-scale reconfigurable intelligent surfaces (RISs) have emerged as a promising technology for signal strength enhancement and coverage extension in 6G networks. However, as the antenna scale and the bandwidth increase, large-scale RIS-assisted wideband orthogonal frequency division multiplexing (OFDM) communication systems face new challenges due to the near-field range expansion and the beam split effect, complicating the acquisition of channel state information (CSI). To tackle these challenges, in this paper, we present a wideband beam training scheme by utilizing the beam split effect to bypass the CSI acquisition. Specifically, by analyzing the beam split effect in RIS-assisted OFDM communication systems, we propose a beam-split-aware codebook capable of covering both the near and far fields. The coverage of codewords in the proposed codebook is expanded benefiting from the beam split effect, leading to fewer codewords compared to conventional narrow-band codebooks. Utilizing such a codebook, a three-stage beam training mechanism is performed to obtain the optimal codeword with low time overhead, thereby facilitating the beamforming. Simulation results demonstrate that the proposed scheme outperforms existing codebook-based beam training schemes in terms of training overhead and sum rate in the hybrid near-far field.

关键词： Training Upper bound Array signal processing OFDM Simulation Reconfigurable intelligent surfaces Broadband antennas Wideband Faces Channel state information

来源：评论

学校读者我要写书评

暂无评论

Medical Insurance Premium Prediction Using Linear Support Vector Machine

Medical Insurance Premium Prediction Using Linear Support Ve...

引用

2023 Winter Summit on Smart Computing and Networks, WiSSCoN 2023

作者： Linija, K.P. Geetha, S. Mavaluru, Dinesh Ravali, Sahithya Mary, S Angel Latha Sri Sairam College of Engineering Department of Aiml Bangalore India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Bangalore India College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia Srm College of Pharmacy Department of Pharmacy Practice Chennai India Sri Eshwar College of Engineering Department of Computer Science and Business Systems Coimbatore India

ISBN: (纸本)9798350334050

In healthcare, data mining algorithms are utilized to make people's lives better by predicting diseases and trying to diagnose them faster than most doctors. When the middleman is eliminated, as it is with computerized medical insurance, there is an unbroken line of communication between the insurance company and the insured. Predicting the premium of medical insurance is a major source of worry. The only way for a health insurance provider to turn a profit is to receive more in premium payments than it pays out in claims. Linear Support Vector Machines (LSVM)are developed for Premium Prediction in the Well-beingAssurance Sector. Eleven different criteria were used to train and evaluate LSVM. Experimental results showed a 99% accuracy, and the researchers analysed the effectiveness of the algorithm using success metrics. © 2023 IEEE.

关键词： Health insurance

来源：评论

学校读者我要写书评

暂无评论

Allocation and Migration of Virtual Machines Using Machine Learning

引用

computers, Materials & Continua 2022年第2期70卷 3349-3364页

作者： Suruchi Talwani Khaled Alhazmi Jimmy Singla Hasan JAlyamani Ali Kashif Bashir School of Computer Science&Engg. Lovely Professional UniversityPunjabIndia National Center for Robotics and Internet of Things Technology Communication and Information Technology Research InstituteKing Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology in RabighKing Abdulaziz UniversityRabigh21911Saudi Arabia Department of Computing and Mathematics ManchesterMetropolitan UniversityManchesterM156BHUK

Cloud computing promises the advent of a new era of service boosted by means of virtualization *** process of virtualization means creation of virtual infrastructure,devices,servers and computing resources needed to deploy an application *** extensively practiced technology involves selecting an efficient Virtual Machine(VM)to complete the task by transferring applications from Physical Machines(PM)to VM or from VM to *** whole process is very challenging not only in terms of computation but also in terms of energy and *** research paper presents an energy aware VM allocation and migration approach to meet the challenges faced by the growing number of cloud data *** Learning(ML)based Artificial Bee Colony(ABC)is used to rank the VM with respect to the load while considering the energy efficiency as a crucial *** most efficient virtual machines are further selected and thus depending on the dynamics of the load and energy,applications are migrated fromoneVMto *** simulation analysis is performed inMatlab and it shows that this research work results in more reduction in energy consumption as compared to existing studies.

关键词： Cloud computing VM allocation VM migration machine learning

来源：评论

学校读者我要写书评

暂无评论

Optimal Extreme Learning Machine based Traffic Congestion Control System in Vehicular Network 6

Optimal Extreme Learning Machine based Traffic Congestion Co...

引用

6th International Conference on Electronics, communication and Aerospace Technology, ICECA 2022

作者： Bharti, Rajendra Kumar Suganthi, D. Abirami, S.K. Kumar, Relangi Anil Gayathri, B. Kayathri, S. Btkit Department of Cse Dwarahat Uttarakhand Almora India Saveetha College of Liberal Arts and Sciences Saveetha University Department of Computer Science Tamilnadu Chennai India Sri Eshwar College of Engineering Department of Computer Science and Business Systems Tamilnadu Coimbatore India Aditya College of Engineering and Technology Department of Electronics and Communication Engineering Surampalem India Bishop Heber College Bharathidasan University Department of Computer Science Tamilnadu Trichy India M. Kumarasamy College of Engineering Master of Computer Applications Tamilnadu Karur India

ISBN: (纸本)9781665482714

Over the past decade, Smart cities have been advanced and minimizing traffic congestion become the main concern in the progression of smart cities. The rapid growth in the number of road vehicles has raised the number of road accidents and traffic congestion. To Solve this problem, Vehicular Network (VN) formulated several novel concepts which include traffic control, vehicular communications, and navigation. Machine Learning (ML) will be an effective technique for identifying hidden insights into ITS without being programmed clearly by learning from data. This article develops an Optimal Extreme Learning Machine based Traffic Congestion Control System (OELM-TCCS) in vehicular networks. The presented OELM-TCCS technique mainly focuses on the identification and recognition of traffic congestion in VANET. To perform this, the presented OELM-TCCS technique primarily designs a new ELM model to carry out the classification process. In addition, the presented OELM-TCCS technique executes the satin bowerbird optimization (SBO) algorithm for parameter tuning of the ELM method. To demonstrate the boosted performance of the OELM-TCCS model, a series of experiments were executed. The experimental outcomes indicate the betterment of the OELM-TCCS method over recent methods with maximum accuracy of 99.17%. © 2022 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Near-Far Field Three-Stage Beam Training for RIS-Assisted Wideband OFDM communications

Near-Far Field Three-Stage Beam Training for RIS-Assisted Wi...

引用

2025 IEEE Wireless communications and Networking Conference, WCNC 2025

作者： Cheng, Zhichao Zhang, Shupei Fu, Shu Di, Boya School of Electronics Engineering and Computer Science Peking University Beijing China School of Electronics Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks Beijing China Chongqing University Department of Microelectronics and Communication Engineering Chongqing China

ISBN: (纸本)9798350368369

关键词： Signaling

来源：评论

学校读者我要写书评

暂无评论

Sustainable IoT-Based Data Logger System for Marine Applications Using Renewable Energy 8

Sustainable IoT-Based Data Logger System for Marine Applicat...

引用

8th IEEE International Conference on Engineering Technologies and Applied sciences, ICETAS 2023

作者： Faizabadi, Ahmed Rimaz Adnan, Khandakar Ameem Norazaruddin, Muhammad Aiman Mohd Zaki, Hasan Firdaus Haziq Bin Abang Akral, Abang Mohd Mohammed Shweesh, Osamah Ebrahim Kulliyyah of Engineering International Islamic University Malaysia Department of Mechatronics Engineering Kuala Lumpur Malaysia Kulliyyah of Information and Communication Technology International Islamic University Malaysia Department of Computer Science Malaysia Kulliyyah of Engineering International Islamic University Malaysia Department of Mechatronics Engineering Malaysia Hidrokinetik Technologies Sdn Bhd Autonomous Marine Systems Kuala Lumpur Malaysia

ISBN: (纸本)9798350327090

Navigational data is vital for various fields of applications. Satellite communications are costly while Automatic Identification System (AIS) data has considerable interval which can make crucial incidents during the voyage unrecoverable. The storage attached to the existing loggers are limited and the GSM900 communication link is slow. This paper presents the design and implementation of an Internet of Things (IoT) based data logging system tailored for marine applications that improves cost, power consumption and durability while providing efficient and reliable data logging capabilities in the harsh marine environment. A programmable multithreaded low-power UR32 industrial router from Milesight replaces the simple Microcontroller Unit (MCU), providing a dual-SIM 4G connectivity failsafe. The proposed design minimizes the required components and enables seamless data acquisition and remote monitoring. Using photovoltaic (PV) solar panels, our logger can run entirely on renewable energy giving an endurance of almost 24 hours on a single charge. It can log data from various sensors over serial communication ports with uninterrupted log intervals. The communication link is improved from 2kbps to more than 7 mbps while storage is improved by 32 times. The complete system is packaged into an IP68 rating enclosure. The proposed solution contributes to cost-effective and energy-efficient IoT-based data logging systems for marine applications, enabling better understanding and managing marine resources and ecosystems using renewable energy. © 2023 IEEE.

关键词： Internet of things

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：