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检索条件"任意字段=Conference on Next-Generation Communication and Sensor Networks 2007"

共 1569 条记录，以下是181-190 订阅

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2nd International conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, ETAEERE 2020

2nd International Conference on Emerging Trends and Advances...

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2nd International conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, ETAEERE 2020

ISBN: (纸本)9789811575105

The proceedings contain 67 papers. The special focus in this conference is on Emerging Trends and Advances in Electrical Engineering and Renewable Energy. The topics include: Analysis and Prevention of Road Accidents;Brain Tumor Segmentation from 3D MRI Slices Using Cascading Convolutional Neural Network;Invoice Deduction Classification Using LGBM Prediction Model;enhancing Heart Disorders Prediction with Attribute Optimization;variable Optimization in Cervical Cancer Data Using Particle Swarm Optimization;A Hybrid DTNB Model for Heart Disorders Prediction;Comparative Study of AHP and Fuzzy AHP for Ranking of Medicinal Drugs;a Novel Privacy Preservation Mechanism for Wireless Medical sensor networks;IOT-Based Visitor Sensing Doormat: Future generation;analysis of t-distribution in Variable Step Size Firefly Algorithm in the Applications of Machine Learning;heart Disease Prediction Using Machine Learning Technique;a Smart Energy Meter-Based Home Recommender System;Performance of Solar PV Panel Under Higher Concentration of Carbon Dioxide;speech Enhancement Using a Novel Spectral Subtraction Method for Seashore Noise;optical Wave Guide: Fast and Secure communication for next-generation Technology;removal of Artifact from the Brain Signal Using Discrete Cosine Transform;a Comparison Study of Recurrent Neural networks in Recognition of Handwritten Odia Numerals;noise Suppression in Non-stationary Signals Using Adaptive Techniques;design of Circular Patch Antenna for Wireless communication in K-Band;automatic Event Detection in User-Generated Video Content: A Survey;detecting Vulnerabilities of Web Application Using Penetration Testing and Prevent Using Threat Modeling;a Comparative Analysis of Biomedical Data Mining Models for Cardiac Signal Classification;egocentric Vision for Dog Behavioral Analysis.

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2nd International conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, ETAEERE 2020

2nd International Conference on Emerging Trends and Advances...

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2nd International conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, ETAEERE 2020

ISBN: (纸本)9789811575037

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A study on the adoption of Wireless communication in Big Data Analytics Using Neural networks and Deep Learning

A study on the adoption of Wireless Communication in Big Dat...

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Advance Computing and Innovative Technologies in Engineering (ICACITE), International conference on

作者： P. Rohini Sachin Tripathi C M Preeti A. Renuka José Luis Arias Gonzales Durgaprasad Gangodkar Computer Science and Engineering Faculty of Science and Technology (ICFAI Foundation for Higher Education)HyderabadTelangana State Symbiosis International (Deemed) University Department of Computer Science and Engineering Institute of Aeronautical Engineering Hyderabad India JNTUH Department of CSE Department of Business University of British Columbia Department of Computer Science &#x0026 Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

The study explores about the Wireless communication which is one of the most rapidly evolving and active technology fields in the communication world. Wireless communication is a means of transmitting data from one point to another without the use of wires, cables, or another physical medium. As a result, commercial network operators have risen at an accelerating rate, bringing in the era of big data. Machine learning has been applied in a range of corporate and academic research contexts as one of the most promising artificial intelligences (AI) methods for deciphering this deluge of knowledge. This study presents a high-level introduction of big data handling and technological advances, as well as their potential applications in next-generation wireless networks (NG). Following that, we employ advanced analytics to estimate mobile users' demands and then use that knowledge to improve the efficacy of “community wireless communication channels.” In specifically, a unified, huge data-aided computer learning framework comprised of feature extraction, data modelling, and prediction/online refinement is provided. The primary benefits of the proposed framework are that we could create the logic, problem formulations, and method of powerful computational models inside the frame of wireless networks by depending on vast data that reflects the both spectrum and other hard demands of users. Via general, information is conveyed from sender to receiver across a certain distance in a communication system. The transmitter may be located anywhere within a few meters using Wireless communication… We examined currently known approaches and explored their benefits and drawbacks in order to identify new research avenues for future advancements in underwater sensor networks.

关键词： Underwater cables Wireless sensor networks Data analysis Transmitters Wireless networks Computational modeling Wires

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Semi-supervised Subject Recognition through Pseudo Label generation in Ubiquitous sensor Data

Semi-supervised Subject Recognition through Pseudo Label Gen...

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International conference on communication Systems and networks (COMSNETS)

作者： Dhekane, Sourish Gunesh Vajra, Krishnam Banerjee, Dip Sankar Indian Inst Informat Technol Guwahati Dept Comp Sci & Engn Gauhati 781015 Assam India

ISBN: (纸本)9781728131870

The task of gait-based subject recognition (SR) in ubiquitous sensor environments has become popular due to its wide range of applications in biometric authentication and smart home products. In recent times, a significant amount of work has been done in SR using supervised learning algorithms on datasets having high modality. However, the process of annotation for SR is difficult due to the challenges like privacy and high manual cost, which results in a scarcity of labeled data samples. Also, for the datasets having less modality, the task of SR in a semi-supervised domain is sparsely explored and challenging. In this work, we analyze the effect of these two factors (sparse labels and low modality) which are critical for SR in ubiquitous data. We select two datasets of ubiquitous data that are relatively unexplored in the context of SR. The datasets, namely OPPORTUNITY and Smartphone used to perform SR using conventional supervised learning algorithms to benchmark the results. Then we perform extensive experimentation to analyze the effect of the aforementioned factors over the task of SR by studying the variations in classification accuracies. next, we propose our semi-supervised framework for SR based on the concept of pseudo labels to counter the adverse effects of low modality and lack of labels. Experimental results show that our approach offers up to 77% and 98% accuracy on the Smartphone and OPPORTUNITY dataset respectively.

关键词： Subject Recognition Ubiquitous data analytics Pseudo Label generation Semi-Supervised learning

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Adaptive Addresses for next generation IP Protocol in Hierarchical networks 28

Adaptive Addresses for Next Generation IP Protocol in Hierar...

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28th IEEE International conference on Network Protocols (IEEE ICNP)

作者： Song, Haoyu Zhang, Zhaobo Qu, Yingzhen Guichard, James Futurewei Technol Santa Clara CA 95050 USA

ISBN: (数字)9781728169927

ISBN: (纸本)9781728169927

We propose the adaptive addresses under a hierarchical network structure, which can be realized in a newer generation of IP protocol (i.e., IPvn). It minimizes the communication overhead, enables arbitrary address space extension, simplifies both the network data-plane and control-plane, and supports better network security. More importantly, it supports incremental deployment from the network edge and gradual growth towards the core. A clear boundary between IPvn domain and the existing IPv4/IPv6 networks enables transparent cross-domain communication. The clear evolution path makes pre-standard deployment possible. We design both control plane and data plane, prototype the routers within and on the edge of an IPvn domain, and evaluate the performance. We open source the project to encourage further investigation and development.

关键词： IP networks Logic gates Internet of Things Adaptive systems Wireless sensor networks Wireless communication sensors

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Exploring the Integration of Wearable sensor Technologies in Professional Sports for Enhanced Athletic Performance and Injury Prevention

Exploring the Integration of Wearable Sensor Technologies in...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Kilaru Aswini Deepak Patidar Uma Reddy Amandeep Nagpal Mohamed I. Habelalmateen Praveen Institute of Aeronautical Engineering Dundigal Hyderabad Department of Electronics & Communication Engineering IES College Of Technology Bhopal M. P. India Department of Artificial Intelligence and Machine Learning New Horizon College of Engineering Bangalore Lovely Professional University Phagwara India The Islamic university Najaf Iraq Knowledge Park II Lloyd Institute of Engineering & Technology Greater Noida Uttar Pradesh

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

The escalating demand for wearable technologies coupled with the pressing need for environmentally conscious solutions has spurred innovative methodologies. This study delves into the symbiotic relationship between biomimetic designs and advanced deep learning, envisioning a paradigm shift in the landscape of next-generation wearables. This project meticulously integrates biomimetic design with cutting-edge deep learning. Biomimicry improves wearable technology by taking ideas from nature. Strong deep learning algorithms based on artificial neural networks provide predictive analytics and user adaptation. To explore biomimetic setups and user activities in a controlled setting, many datasets were collected. Across several success metrics, the proposed method performs better. The accuracy increases greatly, demonstrating how effectively biomimetic concepts and deep learning techniques work together to improve accuracy and reliability. As smart technology evolves, this study ensures that new technologies are cutting-edge and environmentally friendly. Biomimetic designs and deep learning have revolutionized sustainable technologies. It promotes a more compassionate and eco-friendly future.

关键词： Deep learning Training Technological innovation Accuracy Biomimetics Wearable devices Intelligent sensors

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Lightweight Wireless Sensing Through RIS and Inverse Semantic communications

Lightweight Wireless Sensing Through RIS and Inverse Semanti...

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IEEE conference on Wireless communications and Networking

作者： Hongyang Du Jiacheng Wang Dusit Niyato Jiawen Kang Zehui Xiong Junshan Zhang Xuemin Sherman Shen The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of California Davis USA The Department of Electrical and Computer Engineering University of Waterloo Canada

Thanks to the ubiquitous and easily accessible nature of wireless signals, wireless sensing is regarded as one of the promising techniques in the next-generation Internet of Things. In this paper, we propose the inverse semantic communications as a new paradigm to achieve lightweight wireless sensing using the reconfigurable intelligent surface (RIS). Instead of extracting semantic information from messages, we aim to encode the task-related source messages into a hyper-source message. Specifically, we first develop a novel RIS hardware for encoding several signal spectrums into one MetaSpectrum. We then propose a self-supervised learning method for decoding the MetaSpectrums to obtain the original signal spectrums. Using the sensing data collected from the real world, we show that our framework can reduce the data volume by 90% compared to that before encoding, without affecting the execution of various sensing tasks. Experiment results also demonstrate that the amplitude response matrix of the RIS enables the encryption of the sensing data.

关键词： Wireless communication Wireless sensor networks Semantics Self-supervised learning Encoding sensors Decoding

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Characterization of Secret Key generation in 5G+ Indoor Mobile LiFi networks

Characterization of Secret Key Generation in 5G+ Indoor Mobi...

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GLOBECOM 2022 - 2022 IEEE Global communications conference

作者： Elmahedi Mahalal Muhammad Ismail Zi–Yang Wu Mostafa M. Fouda Department of Computer Science Tennessee Technological University Cookeville TN USA College of Information Science and Engineering Northeastern University Shenyang China Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA Center for Advanced Energy Studies (CAES) Idaho Falls ID USA

ISBN: (纸本)9781665435413

This paper investigates wireless secret key generation in 5G+ indoor LiFi networks operating in the visible light band in the downlink and the infrared band in the uplink. Unlike the existing research, this paper aims to characterize the impact of indoor user mobility on the ability to generate identical secret keys between the user and the base station. Hence, we first generate mobility traces that reflect realistic human behavior in an indoor setup to capture the sensitivity of the optical channels to random blockage and transceiver-misorientation events associated with user mobility. next, we generate the corresponding channel impulse response and adopt guard band quantization and information reconciliation to extract identical uplink and downlink keys. Then, we examine a set of spatial and temporal features related to the channel probing rate, key disagreement rate, and key generation rate, along with their statistical distributions. Further, we study the randomness of the key following the NIST randomness tests. Our study demonstrated that the handover strategy significantly impacts the randomness of the key and its generation rate.

关键词： Wireless communication Wireless sensor networks Sensitivity Quantization (signal) Statistical distributions Light fidelity Downlink

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High-speed mobile communication network and wireless sensor network convergence service traffic prediction model and security mechanism design 9

High-speed mobile communication network and wireless sensor ...

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9th International conference on Computing and Pattern Recognition, ICCPR 2020

作者： Tang, Bin-Hui Zhou, Zhen-Xing Dept. of Computer Science and Technology Jincheng College of Sichuan University Chengdu610000 China Dept. of Representative Bureau of the Rocketing Military Chengdu610000 China

ISBN: (纸本)9781450387835

With the rapid development of 5G high-speed mobile communication technology, the deep integration of wireless sensor networks and high-speed mobile communication networks is an inevitable trend in the development of next-generation ubiquitous networks, and the development of the two networks convergence service is imminent, the service is not only the urgent needs of users in the context of new infrastructure but also the requirements of the development of the entire era. As mobile communication networks and wireless sensor networks have their own characteristics, and their respective network structures and protocol stacks are quite different, the multi-service data traffic generated by the heterogeneous convergence of the two networks will have local, periodic, random, bursty and other multiple characteristics, and a complex structure, which brings technical problems to network operation and security monitoring, and also brings new hidden problems and challenges to network security during the convergence process. The simulation results show that the prediction accuracy of the model algorithm is high and the security mechanism can effectively play an important role in the multi-service convergence of heterogeneous networks. © 2020 ACM.

关键词： Wireless sensor networks

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Towards a Novel and Efficient Public Key Management for Peer-Peer Security in Wireless Ad-Hoc/sensor networks 1

Towards a Novel and Efficient Public Key Management for Peer...

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International conference on Smart Technologies and Systems for next generation Computing (ICSTSN)

作者： Joseph, Abin John Sani, Nidhin Vineeth, M. V. Kumar, K. Suresh Kumar, T. Ananth Nishanth, R. Cochin Univ Coll Engn Kuttanad CUSAT Elect & Commun Engn Kuttanad Kerala India Cochin Univ Coll Engn Kuttanad CUSAT Informat Technol Kuttanad Kerala India IFET Coll Engn Elect & Commun Engn Villupuram Tamil Nadu India IFET Coll Engn Comp Sci & Engn Villupuram Tamil Nadu India

ISBN: (纸本)9781665421119;9781665421126

Key management for self-organized wireless adhoc networks using peer-to-peer (P2P) keys is the primary goal of this article (SOWANs). Currently, wireless networks have centralized security architectures, making them difficult to secure. In most cases, ad-hoc wireless networks are not connected to trusted authorities or central servers. They are more prone to fragmentation and disintegration as a result of node and link failures. Traditional security solutions that rely on online trusted authorities do not work together to protect networks that are not planned. With open wireless networks, anyone can join or leave at any time with the right equipment, and no third party is required to verify their identity. These networks are best suited for this proposed method. Each node can make, distribute, and revoke its keying material in this paper. A minimal amount of communication and computation is required to accomplish this task. So that they can authenticate one another and create shared keys, nodes in the self-organized version of the system must communicate via a secure side channel between the users' devices.

关键词： Authentication Network Security Ad Hoc networks Public key peer-peer

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