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检索条件"任意字段=14th International Conference on COMmunication Systems and NETworkS, COMSNETS 2022"

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Fault Location Technology of Information System Across Isolation Devices

Fault Location Technology of Information System Across Isola...

引用

international conference on communication systems and Network Technologies (CSNT)

作者： Yao Wang Yunrui He Zhihong Li Yiying Yan Xinyi Le Information and Communication Branch of State Grid Corporation Limited Beijing China

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Fault location across isolated devices remains one of the most challenging tasks for modern information systems. Traditional linear regression fault location technology results in highly inaccurate and unproductive diagnoses due to the complex nature of the network environments and multiple layers of isolation. this paper aims at studying the fault location technology of information systems across isolated devices, specifying the improvement expected for diagnosis in both accuracy and speed. System logs and network traffic data are collected by data acquisition tools, which are then processed by feature extraction technology to individualize the key fault features. the convolutional neural networks (CNN) are then applied to identify and locate the patterns of fault. the experimental results indicate a maximum accuracy of 93% for this method in locating faults, with diagnosis time being reduced by 34% on average compared to the linear regression method. the CNN-based fault location technology appears to be capable of significantly improving the capability of fault diagnosis for information systems across isolated devices and providing a new solution for the fault management of complex network environments.

关键词： Location awareness Accuracy Linear regression Memory management Telecommunication traffic Fault location Feature extraction Real-time systems Convolutional neural networks Information systems

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DRO Design for Millimeter Wave Terminal communication System 14

DRO Design for Millimeter Wave Terminal Communication System

引用

14th international conference on Microwave and Millimeter Wave Technology (ICMMT)

作者： Huang, Shuojin Shi, Zhanqiang Zhang, Xianchao Yu, Xutao Chen, Peng Southeast Univ State Key Lab Millimeter Waves Nanjing 211189 Peoples R China Purple Mt Labs Nanjing 211111 Peoples R China Southeast Univ Sch Informat Sci & Engn Nanjing 210018 Peoples R China Jiaxing Univ Key Lab Med Elect & Digital Hlth Zhejiang Prov Jiaxing 314001 Peoples R China

ISBN: (纸本)9781665467520

In this paper, a parallel feedback dielectric resonator oscillator (DRO) with an operating frequency of 8.35GHz is designed. Using mechanical tuning structure, the frequency modulation bandwidth of the dielectric resonator can reach 1GHz. the phase noise can reach -133.921dBc/Hz@100KHz, and the output power can reach 6.687dBm. the dielectric oscillator works as a stable frequency source in the currently designed millimeter wave terminal communication system. the simulation results show that the frequency source has low phase noise.

关键词： phase noise DRO co-simulation parallel feedback

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Improving Target Detection Accuracy with OEERP in Wireless Sensor networks

Improving Target Detection Accuracy with OEERP in Wireless S...

引用

international conference on communication systems and Network Technologies (CSNT)

作者： J Elumalai K. Kumuthapriya R. Hema P. Sakthi Shunmuga Sundaram Department of Electronics and Communication Engineering SKR Engineering College Ponamallee Chennai Department of Electronics and Communication Engineering Tagore Engineering College Rathinamangalam Chennai Tamil Nadu

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

the energy consumption of Wireless Sensor networks (WSNs) is constrained by battery power. this paper presents a method aimed at reducing energy usage during network routing. An opportunistic energy-efficient routing protocol, often known as an OEERP, is a concept that comprises introduced to enhance the network’s performance, improve target location detection accuracy, Increase the network’s energy efficiency while simultaneously extending its existence. the approach that has been presented puts idle nodes into a sleep state, hence reducing the amount of energy that is consumed. When the network’s residual energy (RE) is taken into consideration, sleep states are dynamically regulated and flow rate (FR), optimizing energy conservation. Nodes in sleep mode are periodically activated through triggering mechanisms. Simulation results validate the effectiveness of the OEERP, showing enhanced target detection accuracy, energy efficiency, and overall network performance, and comparisons with existing protocols are provided through plotted results.

关键词： Wireless sensor networks Schedules Energy consumption Accuracy Simulation Energy conservation Object detection Routing Energy efficiency Routing protocols

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Lora-Enabled System for Smart Farming Management and Oversight, Utilizing Wireless Sensor networks

Lora-Enabled System for Smart Farming Management and Oversig...

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international conference on communication systems and Network Technologies (CSNT)

作者： J Elumalai K. Kumuthapriya R. Hema P. Sakthi Shunmuga Sundaram Department of Electronics and Communication Engineering S.K.R Engineering College Chennai Department of Electronics and Communication Engineering Tagore Engineering College Chennai Tamil Nadu

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

the purpose of this study is to create a LoRa-based smart farming management and surveillance system. Utilizing Wireless Sensor networks (WSNs) in rural settings, with the aim of replacing the existing technology in agricultural monitoring systems. A dedicated private network server is established and connected to a gateway, which gathers information or signals from the nodes at the end and sends this data to the cloud without the need for routers. this data can then be utilized for various applications by the end users. the system overcomes issues related to communication failures and energy-efficient data transmission. this advanced farming platform enhances the effectiveness of farming methods. the proposed methodology is the application of resources including as water, fertilizers, and pesticides should be optimized in order to achieve maximum efficiency while simultaneously minimizing waste. Farming productivity and sustainability are both significantly improved because of its contribution, notably in terms of the efficient management of resources. And intelligent cities used to improve agriculture—comparing the planned weather station and the numerous developed patents. the technique here is like a cutting-edge, reasonably priced choice for local weather monitoring.

关键词： Smart agriculture Productivity Wireless sensor networks Surveillance Urban areas Soil Sustainable development Water resources Farming Meteorology

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Design and Simulation of Metamaterial Microwave devices for High efficiency Wireless Applications

Design and Simulation of Metamaterial Microwave devices for ...

引用

international conference on communication systems and Network Technologies (CSNT)

作者： Amitabh Kumar Yogesh Kumar Department of Electrical Electronics & Communication Engineering Galgotias University Greater Noida U.P India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

In this research work, a novel approach in the design and modeling of metamaterial-based microwave devices for improved bandwidth and efficiency for the next generation wireless technology; 5G and all subsequent generations is presented. the design combines SRRs and CSRRs to realize a prototype that resonates at 5.85 GHz with -22.9 dB of return loss and 93% efficiency of transmission. the simulation results presented in this work demonstrated an operation bandwidth of 780 MHz, which was three times higher than conventional designs. Microwave design was performed using CST Microwave Studio and HFSS, while the experimental characteristics were obtained using a vector network analyzer. this paper describes the methodology, instruments, and control factors for obtaining this level of performance and indicates possible areas of using high-speed data transfers and signal quality in 5G and subsequent networks.

关键词： Wireless communication 5G mobile communication Simulation Resonant frequency Microwave devices Bandwidth Microwave communication Propagation losses Metamaterials Vectors

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A Bayesian Optimization Framework for Adaptive Node Deployment in Wireless Sensor networks

A Bayesian Optimization Framework for Adaptive Node Deployme...

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international conference on communication systems and Network Technologies (CSNT)

作者： Rahul Priyadarshi Jayant Kumar Rout Anish Kumar Vishwakarma Nikhil Dhengre Rakesh Ranjan Amit Verma Faculty of Engineering and Technology ITER SOA Bhubaneswar India School of Computer Application KIIT Bhubaneswar India School of Computer Science UPES Dehradun Uttarakhand India Department of ECE IIIT Nagpur Maharashtra India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Wireless Sensor networks (WSNs) require efficient node deployment strategies to optimize network longevity, energy consumption, and coverage. this paper introduces a novel approach for strategic node deployment in WSNs using Bayesian Optimization (BO). A BO-based framework that iteratively modifies node positions to maximize network performance metrics, such as energy efficiency and coverage ratio, while minimizing execution time is proposed. through extensive simulations across diverse deployment scenarios, the proposed method is evaluated and demonstrates superior performance compared to both traditional and machine learning (ML)-based techniques. the results indicate significant improvements in coverage and energy efficiency, alongside competitive execution times. these findings highlight the potential of BO to enhance WSN deployment strategies, offering a scalable and adaptive solution for real-world applications. Future research will focus on integrating BO with other optimization techniques and extending the approach to dynamic environments and varied network configurations.

关键词： Learning systems Wireless sensor networks Energy consumption Adaptive systems Machine learning Energy efficiency Real-time systems Bayes methods Reliability Optimization

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Energy-Based Maximum Likelihood Detector for GSSK in MIMO-ABC systems 14

Energy-Based Maximum Likelihood Detector for GSSK in MIMO-AB...

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14th IEEE international conference on Signal Processing and communications (SPCOM)

作者： Raghavendra, Ashwini H. Kowshik, Anagha K. Gurugopinath, Sanjeev Muhaidat, Sami Tellambura, Chintha PES Univ Dept Elect & Commun Engn Bengaluru 560085 India Khalifa Univ Dept Elect Engn & Comp Sci Abu Dhabi 127788 U Arab Emirates Univ Alberta Dept Elect & Comp Engn Edmonton AB Canada

ISBN: (数字)9781665482509

ISBN: (纸本)9781665482509

We propose a novel, low complexity energy-based maximum likelihood (EML) detector for a generalized space shift keying (GSSK)-enabled multiple-input multiple-output (MIMO) ambient backscatter communication (ABC) system. the proposed scheme exploits the multiple antenna structure of the system to achieve a lower error rate performance than the conventional single-antenna ABC systems. the proposed EML GSSK detector does not require the perfect knowledge of the ambient source signal. To gain insights into the performance of the proposed scheme, we derive the exact pairwise error probability (PEP) of the EML detector, and further obtain an upper bound on the probability of error. We also derive a simple asymptotic PEP expression, as the number of antennas of the reader becomes large. We validate our analysis through Monte Carlo simulations, and show that the performance loss due to the approximations employed in our analysis is small. the performance of EML detector is also compared with the conventional ML detector and the loss in performance is studied.

关键词： Radio frequency Maximum likelihood detection Monte Carlo methods Upper bound Detectors Receivers Signal processing

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Assessing the Impact of Deep End-to-End Architectures in Ensemble Learning for Histopathological Breast Cancer Classification 14

Assessing the Impact of Deep End-to-End Architectures in Ens...

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14th international conference on Knowledge Discovery and Information Retrieval, KDIR 2022 as part of 14th international Joint conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2022

作者： Zerouaoui, Hasnae Idri, Ali El Alaoui, Omar Modeling Simulation and Data Analysis Mohammed VI Polytechnic University Benguerir Morocco Software Project Management Research Team ENSIAS Mohammed V University Rabat Morocco

ISBN: (纸本)9789897586149

One of the most significant public health issues in the world and a major factor in women's mortality is breast cancer (BC). Early diagnosis and detection can significantly improve the likelihood of survival. therefore, this study suggests a deep end-to-end heterogeneous ensemble approach by using deep learning (DL) models for breast histological images classification tested on the BreakHis dataset. the proposed approach showed a significant increase of performances compared to their base learners. thus, seven DL architectures (VGG16, VGG19, ResNet50, Inception_V3, Inception_ResNet_V2, Xception, and MobileNet) were trained using 5-fold cross-validation. thereafter, deep end-to-end heterogeneous ensembles of two up to seven base learners were constructed based on accuracy using majority and weighted voting. Results showed the effectiveness of deep end-to-end ensemble learning techniques for breast cancer images classification into malignant or benign. the ensembles designed with weighted voting method exceeded the others with an accuracy value reaching 93.8%, 93.4%, 93.3%, and 91.8% through the BreakHis dataset's four magnification factors: 40X, 100X, 200X, and 400X respectively. Copyright © 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Learning systems

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Resource Allocation for Wireless-Powered Backscatter communication Network Based on Nash Bargaining Solution 22

Resource Allocation for Wireless-Powered Backscatter Communi...

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14th international conference on Computer Modeling and Simulation, ICCMS 2022

作者： Wang, Zhengqiang Wei, Xin Hong, Duan Fan, Zifu Wan, Xiaoyu Ding, Weiyi School of Communication and Information Engineering Chongqing University of Posts and Telecommunications China

ISBN: (纸本)9781450396547

this paper investigates the resource allocation problem for a wireless-powered backscatter communication network where the sensors can utilize the radio frequency (RF) signals from a hybrid access point (H-AP) to transmit data and store energy. We assume that the sensors receive RF signals from the H-AP and transmit data to the sensors' gateway by backscattering techniques. the sensors harvest energy from the RF signals, where a portion of the energy is harvested to transmit data to satisfy the gateway data demand, and the rest of the energy is stored in their batteries. In order to allocate the overall storage energy among sensors fairly, we propose a resource allocation problem based on the Nash bargaining solution (NBS) to maximize the product of the storage energy of each sensor. We prove that the energy allocation problem can be equivalent to a convex problem which can be solved by the interior-point method. Simulation results show that the proposed algorithm achieves a good balance between fairness and efficiency with other benchmark algorithms. © 2022 ACM.

关键词： Gateways (computer networks)

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Deep-Prenatal: A Deep Learning Approach for Detection and Analysis of Nuchal Translucency for Enhanced Prenatal Screening 14

Deep-Prenatal: A Deep Learning Approach for Detection and An...

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14th IEEE international conference on communication systems and Network Technologies, CSNT 2025

作者： Pawar, Smita S. Nikose, Mangesh D. Gupta, Anni U. Electrical and Electronics Engg. Dept School of Engg and Technology Sandip University Maharashtra Nashik India Electronics and Communication Engg. Dept. MET's IOE Maharashtrax Nashik India

ISBN: (纸本)9798331531935

Nuchal Translucency (NT) observed in ultrasound scans is widely utilized to identify genetic abnormalities in foetuses. However, NT measurements may be challenging to perform as a mainstay of prenatal screening. these challenges include operator dependency, which primarily relies on the technician’s expertise, and variations in imaging settings that can introduce data anomalies. thus, the precision of NT measurements is not always definitive, raising questions about their dependability in clinical practice. A Convolutional Neural Network (CNN) framework is proposed to address these constraints. this architecture comprises of Conv2D, Max Pooling, Dense, and Flatten layers and advanced components. Together, these elements enable the CNN to effectively identify and analyse NT measurements, thereby automating the process and reducing reliance on human involvement. the proposed CNN architecture performs well across critical criteria such as accuracy, precision, recall, and Intersection over Union (IoU). Furthermore, the framework has demonstrated stability when applied to diverse datasets, owing to its robustness and flexibility across various clinical databases. this proposed efficient and reliable preliminary screening method, based on the enhanced CNN architecture, addresses the inherent limitations of NT measurements. It establishes a new benchmark for accuracy in the field and introduces a transformative approach that enhances clinical outcomes. © 2025 IEEE.

关键词： Convolutional neural networks

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