2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)最新文献_第3页

Research on Smart Contract Vulnerability Detection Method of Power Equipment Based on Deep Learning Algorithm 基于深度学习算法的电力设备智能合约漏洞检测方法研究

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470681

Liang Zhang, Yuan Fang, Yuexin Shen, Xiyin Wang

引用次数: 0

Analysis of Antenna-to-Antenna Spatial Correlation in Multi-User Millimeter-Wave Systems 多用户毫米波系统中的天线间空间相关性分析

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470477

Deepak Kumar, Febin Prakash, Gaurav Shukla

引用次数: 0

Impact of Antenna Beam Patterns on the Performance of Satellite Communication Links 天线波束模式对卫星通信链路性能的影响

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470666

G. D, Ramakant Upadhyay, Ashendra Kumar Saxena

{"title":"Impact of Antenna Beam Patterns on the Performance of Satellite Communication Links","authors":"G. D, Ramakant Upadhyay, Ashendra Kumar Saxena","doi":"10.1109/ICOCWC60930.2024.10470666","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470666","url":null,"abstract":"the overall performance of satellite communication links is extraordinarily established upon the spatial distribution of transmitted radiation. This distribution is managed by means of the antenna beam sample, which is a measure of the relative power emitted in one-of-a-kind directions from the antenna. The shape of the beam drastically impacts the efficiency of the hyperlink in addition to its robustness against fading. Numerous beam sample configurations are typically employed in satellite verbal exchange packages; every with it's set of advantages and disadvantages. By characterizing the variations among beam patterns, it is miles feasible to determine the most suitable design for a given utility. The most commonly used beam sample in satellite TV for PC communications is the pencil beam. This has a highly slim fundamental lobe width and presents exact gain traits inside the desired guidelines on the fee of extended aspect lobe power. This may cause better interference levels and fading outcomes, in particular in tremendously Asymmetric Circularly Polarized (HACP) structures. Then again, wider beam styles, which include fan or zone beams, provide decreased aspect lobe electricity on the fee of reduced gain. Broadening the sample will additionally increase the complexity of the link finances and antenna directivity calculations. Currently, extra complex antenna beam styles, including stepped-tapered, nested, and adaptive, have been hired so one can optimize the satellite TV for PC link overall performance.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"37 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and Implementation of Art Design System based on Image Processing Technology 基于图像处理技术的艺术设计系统的设计与实现

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470708

Zirui Feng

引用次数: 0

Research on Modulation Signal Detection Method based on Deep Learning 基于深度学习的调制信号检测方法研究

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470928

Bowei Xing, Yin He, Chi Xu, Yong Zhang

{"title":"Research on Modulation Signal Detection Method based on Deep Learning","authors":"Bowei Xing, Yin He, Chi Xu, Yong Zhang","doi":"10.1109/ICOCWC60930.2024.10470928","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470928","url":null,"abstract":"Facing the complex electromagnetic environment, the modulation mode of communication signal is becoming increasingly complex. The existing detection methods of modulation mode of communication signal can not detect the modulation mode of communication signal accurately and quickly. In order to facilitate the presentation, we represent the digital signal on the complex plane, form the constellation map according to the mapping formula, analyze the difference of the characteristics of the constellation map, and train and test the constellation map. It can be found that when the signal-to-noise ratio is lower than 20dB, the classification accuracy of the characteristics of the constellation map is greatly affected for the 64QAM signal with the largest number of points and the smallest radius. To solve this problem, A method of signal constellation de-noising using VMD is proposed. Compared with the pre-de-noising method, the average accuracy of VGGNet-16 classification is increased by 7.76%; The average accuracy rate of ResNet-18 classification increased by 9.77%; The average accuracy rate of ResNet-50 classification increased by 7.57%. This method improves the accuracy of constellation classification detection, which is difficult to improve, and lays a good foundation for the research of modulation signal detection methods.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"39 11","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Time Series Analysis for Low Energy Data Aggregation Using Extended Kalman Filtering 利用扩展卡尔曼滤波进行低能耗数据聚合的时间序列分析

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470537

Rakhi Gupta, Gaurav Kumar Rajput, M. N. Nachappa

{"title":"Time Series Analysis for Low Energy Data Aggregation Using Extended Kalman Filtering","authors":"Rakhi Gupta, Gaurav Kumar Rajput, M. N. Nachappa","doi":"10.1109/ICOCWC60930.2024.10470537","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470537","url":null,"abstract":"This paper provides a unique low electricity facts aggregation method utilizing the Extended Kalman Filtering (EKF) algorithm. Using time-collection evaluation on low energy facts streams, EKF can provide extra correct mixture values. This paper examines the system of characteristic extraction from low-strength records series streams and the underlying prolonged Kalman Filtering (EKF) model formula. The EKF version formula produces a correlated time-series representation of the low-strength records streams and estimates its parameters. Further, a case study of the real-world utility of this technique is supplied. The outcomes show that the proposed methodology can yield an advanced low-energy records aggregation method compared to standard strategies. The proposed EKF -based method holds the giant capacity for efficient strength, calling for forecasting in realistic settings. This paper examines prolonged Kalman Filtering (EKF) for low electricity information aggregation of time series evaluation. EKF is a recursive estimation technique primarily based on first principles and implements an optimally weighted linear aggregate of recursive estimates for nations and parameters. This look presents the analytical method of EKF implemented for the cause of time collection modeling and state estimation. A simulated case look at on-strength demand for a given length illustrates the gain of EKF for the low-strength data aggregation venture., a correct estimation is obtained from the time series information with a restrained range of samples and minimum computational attempt.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"14 6","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Statistical Methods for Performance Analysis of Data Processing Systems in High-Performance Computing Environments 高性能计算环境中数据处理系统性能分析的统计方法

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470613

Associate Professor A Kannagi, Neeraj Das, Meenakshi Dheer

{"title":"Statistical Methods for Performance Analysis of Data Processing Systems in High-Performance Computing Environments","authors":"Associate Professor A Kannagi, Neeraj Das, Meenakshi Dheer","doi":"10.1109/ICOCWC60930.2024.10470613","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470613","url":null,"abstract":"in excessive-performance computing environments, wherein huge amounts of data want to be processed quickly, the overall performance of statistics processing systems is crucial. Analyzing the performance of these structures is essential to become aware of bottlenecks and optimize their performance. This studies aims to increase statistical strategies for overall performance analysis of facts processing systems in high-performance computing environments. The evaluation technique is to gather overall performance facts from the goal device. This fact frequently consists of numerous measurements, making it challenging to draw meaningful insights. To cope with this difficulty, statistical strategies, transformation, outlier detection, and dimensionality discount can be implemented to clear out noise and pick out styles within the records. Regression evaluation may version the relationship among gadget parameters and overall performance metrics. It helps identify which device parameters have the most considerable effect on performance and may guide similarly optimization efforts. Moreover, cluster analysis can be used to institution systems with comparable performance traits, allowing comparison and identity of pinnacle-appearing systems.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"46 34","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging Self-Supervised Transfer Learning for Robust Medical Image Classification 利用自监督迁移学习进行稳健的医学图像分类

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470710

Surendra Yadav, Rakesh Kumar Dwivedi, Gobi N

引用次数: 0

Feature Extraction Using Canonical Correlation Analysis for Improved Recognition of Objects in Hyper Spectral Data 利用典型相关分析提取特征，提高超光谱数据中物体的识别率

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470883

Febin Prakash, Sachin Gupta, Garima Goswami

{"title":"Feature Extraction Using Canonical Correlation Analysis for Improved Recognition of Objects in Hyper Spectral Data","authors":"Febin Prakash, Sachin Gupta, Garima Goswami","doi":"10.1109/ICOCWC60930.2024.10470883","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470883","url":null,"abstract":"The objective of the modern-day work is to propose a characteristic extraction of the usage of canonical correlation analysis (CCA) mixed with different advanced strategies for the advanced recognition of items in hyperspectral data. CCA has come to be a famous tool for characteristic extraction as it permits nonlinear modeling of the information that's, in particular, helpful while we are exposing a hyperspectral photograph. CCA seeks to maximize the correlation between variable sets which is especially useful when the image consists of spurious noise, which might otherwise degrade the overall recognition performance. Additionally, CCA allows for retaining the spatial patterns inside the information. Other preprocessing and statistical techniques such as wavelet transforms, statistical covariance illustration, Kreskas-Wallis, and second Estimation strategies have been integrated into this work to improve the effects further. Experimental outcomes demonstrate that the proposed technique based totally on CCA, while combined with different techniques, improves the recognition rate of items and offers a better fitting of the information.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"56 52","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Developing Support Vector Machines for Accurate Medical Image Analysis 开发用于精确医学图像分析的支持向量机

2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC) Pub Date : 2024-01-29 DOI: 10.1109/ICOCWC60930.2024.10470551

Feon Jaison, Viiay Kumar Pandey, Ashish Bishnoi

{"title":"Developing Support Vector Machines for Accurate Medical Image Analysis","authors":"Feon Jaison, Viiay Kumar Pandey, Ashish Bishnoi","doi":"10.1109/ICOCWC60930.2024.10470551","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470551","url":null,"abstract":"help vector machines (SVMs) have become increasingly famous in scientific photo analysis because of their capacity to model complex relationships among inputs and outputs. SVMs are exceptionally high-quality because of their advanced overall performance in excessive-dimensional information units and their ability to address non-linear information. In clinical image evaluation, SVMs are used for various packages, including detecting tumors in Magnetic Resonance Imaging (MRI) and classifying lesions in Computed Tomography (CT) scans. No matter its benefits, growing dependable SVMs for scientific photograph evaluation remains a venture because of the uncertainty associated with scientific pics that regularly require information preprocessing and feature extraction before education. This paper surveys current work on developing robust SVMs for medical photo analysis, from preprocessing to publish-processing, and affords a comprehensive evaluation of the cutting-edge state of the art. mainly; we discuss diverse preprocessing and function extraction strategies that can be employed to improve performance, in addition to publish-processing strategies that can be used to enhance the general accuracy of the version. We also talk about ability directions for future research in this field.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"25 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0