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2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)最新文献

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Buck and Boost DC-DC Converters for industrial application with different load 降压和升压DC-DC转换器适用于不同负载的工业应用
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787657
Arpit Nema, Siddrath Shukla
{"title":"Buck and Boost DC-DC Converters for industrial application with different load","authors":"Arpit Nema, Siddrath Shukla","doi":"10.1109/CSNT54456.2022.9787657","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787657","url":null,"abstract":"In this paper Boost converter has been design using impedance matching network, high mobility transistor and active capacitor. The impedance matching network is used in form of high and low pass filter. This converter is a good boosting factor with resistive and inductive load compare to past decade work. The π and T matching filters are used to enhance the boosting rate. This circuit is applicable in industry application for boosting purpose. The designing of the circuits are low cost. LT-Spice simulation is used to design and simulate the Boost dc to dc converter. Studied boosting characteristics with different load.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127437653","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
Color Adaptive Robust DWT-SVD Watermarking Algorithm and Limitations : Color Space Comparisons 颜色自适应鲁棒DWT-SVD水印算法及其局限性:色彩空间比较
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787610
Arun Patel, Prabhat Patel
{"title":"Color Adaptive Robust DWT-SVD Watermarking Algorithm and Limitations : Color Space Comparisons","authors":"Arun Patel, Prabhat Patel","doi":"10.1109/CSNT54456.2022.9787610","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787610","url":null,"abstract":"Color image watermarking is a technique for digital data authentication and security. Because of the substantial differences in colour aspects, watermarking a colour image is a time-consuming and challenging problem. Noval algorithm DWT-SVD oriented colour image watermarking based on entropy, adapting colour components is proposed to designed in this paper. The algorithim is expected to improve invisibility, of the colour component with the least amount of information is chosen for watermark insertion. For watermark embedding, the is proposed algorithm takes advantage of dual-level security by employing the SVD of logo and wavelet coefficients. The performance of the proposed technique was also examined for three distinct colour spaces: RGB, YCbCr, and LAB. The comparison of watermarking and logo extraction is used to assess qualitative performance. Peak Signal-to-Noise ratio (PSNR) and Normalize cross Correlation (NC) is used in the parametric analysis under the exposure of the various attacks.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131944779","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
A Hybrid Convolutional Recurrent (CNN-GRU) Model for Stock Price Prediction 股票价格预测的混合卷积循环(CNN-GRU)模型
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787651
Rashi Jaiswal, B. Singh
{"title":"A Hybrid Convolutional Recurrent (CNN-GRU) Model for Stock Price Prediction","authors":"Rashi Jaiswal, B. Singh","doi":"10.1109/CSNT54456.2022.9787651","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787651","url":null,"abstract":"Stock price forecasting systems are on-demand that used for prediction in the financial world. The deep learning models are used for handling large data and making predictions more accurately than the traditional methods. This paper proposed a hybrid convolutional recurrent model architecture for stock price prediction based on exploitation of two different deep learning models properties into a single model. Hybrid Convolutional Recurrent Model consists of 1D-CNN and GRU where 1D-CNN is leveraged as feature extraction task and GRU for temporal regression. The proposed CNN-GRU Model outperform for stock price prediction. The performance evaluation and comparison analysis between the existing hybrid models and proposed hybrid model have also been done with experiments to justify.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132010910","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: 9
Resource Aware Energy Efficiency Optimization by Using 6G Technology Based Advanced Virtual Multi-Purpose Embedding Algorithm 基于6G技术的先进虚拟多用途嵌入算法的资源感知能效优化
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787614
G. Saidivya, V. Sridhar, K. V. R. Rao, C. Ashwini
{"title":"Resource Aware Energy Efficiency Optimization by Using 6G Technology Based Advanced Virtual Multi-Purpose Embedding Algorithm","authors":"G. Saidivya, V. Sridhar, K. V. R. Rao, C. Ashwini","doi":"10.1109/CSNT54456.2022.9787614","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787614","url":null,"abstract":"Now a days, Network Technology is the one of the most important technology, which is used to resolve the shortcomings including network ossification of the current design of the internet. Because of adopted digital business growth Internet becomes success and it increased the competition for bandwidth in the communication. Ultra-high-definition videos and vehicle systems require more bandwidth rates and increase the network connection capacity respectively. The rapid advancement of network visualization and 6G technologies is driven by high bandwidth and high speed parallel communication. This often introduces a new link allocation problems to existing substrate networks in a network visualization environment. In order to solve this far reaching network effects, this paper proposes a new model called Advanced Virtual Multi-Purpose Network Embedding Algorithm (AVMPNEA). In this AVMPNEA model uses clustering method. Clustering is a learning algorithm. The clustering is a process which integrally evaluates the topological node structure, the latency and the related bandwidth between the nodes. The nodes the longevity which are used for selected mapping. Here, the result shows that the proposed AVMPNEA model is better in comparison with other models. In which throughput is high, latency is low and reduction of energy consumption. Hence, this model improves the throughput and the long-term application support.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129178664","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
Estimation of Inductance and Capacitance Parameters of Single Phase Dual Winding Converter Transformer with FEM 单相双绕组换流变压器电感和电容参数的有限元估计
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787659
S. S. Mopari, D. More, P. K. Murthy, M. Chawla
{"title":"Estimation of Inductance and Capacitance Parameters of Single Phase Dual Winding Converter Transformer with FEM","authors":"S. S. Mopari, D. More, P. K. Murthy, M. Chawla","doi":"10.1109/CSNT54456.2022.9787659","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787659","url":null,"abstract":"The converter transformers are key equipment in DC power transmission systems. The power system security is greatly influenced by converter transformer insulation. As compared to conventional transformers, electric field distribution is more complex in converter transformers. Hence electric field and its distribution play a crucial role for optimal design and manufacturing process of converter transformer. In this paper a single phase converter transformer equivalent circuit model with dual winding has been established. The electric field simulation is carried out with the help of 2D finite element method (FEM). The insulation strength can be tested by conducting a DC test on valve side winding. Also, ANSYS Maxwell simulation platform is used for calculating converter transformer winding parameters. The present approach permits a faster and more precious method for modeling of converter transformer winding.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"239 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126814355","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: 2
Optimized Dual-mode Security Encryption Chip Design Based on Hash Algorithm 基于哈希算法的优化双模安全加密芯片设计
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787655
Weihan Xu, Yongkang Xu, Guanting Huo, Yang Yang, Yufeng Jin
{"title":"Optimized Dual-mode Security Encryption Chip Design Based on Hash Algorithm","authors":"Weihan Xu, Yongkang Xu, Guanting Huo, Yang Yang, Yufeng Jin","doi":"10.1109/CSNT54456.2022.9787655","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787655","url":null,"abstract":"With the arrival of the 5G era, IoT develops and promotes rapidly and the security issues of IoT are concerned increasingly. SHA256 and SM3 are significant hash encryption algorithms that can improve the security of IoT systems. This paper proves the equivalence between partial Boolean functions of these two encryption algorithms and designs a shared security encryption circuit that can support SM3 and SHA256 modes. Compared with the traditional design, the area of this design decreases by 17.3%. To improve the speed and reduce power consumption, this design is optimized by precomputation and reducing the signal update frequency. The precomputation part shortens the critical path and increases the maximum frequency and throughput successfully. The power optimization part also improves energy efficiency. After function verification, this design can encrypt the original message correctly and efficiently and is synthesized based on the 65nm LVt process library of SMIC.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"85 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123066992","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
The Adoption of IoMT in Disease Prediction using Machine Learning: A benefit to Healthcare system 使用机器学习在疾病预测中采用IoMT:对医疗保健系统的好处
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787563
Md. Ramish, Ankit Pankaj, Ankit Lakra
{"title":"The Adoption of IoMT in Disease Prediction using Machine Learning: A benefit to Healthcare system","authors":"Md. Ramish, Ankit Pankaj, Ankit Lakra","doi":"10.1109/CSNT54456.2022.9787563","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787563","url":null,"abstract":"Health information needs are also changing the information-fetching behavior, and that is observed around the globe. In this paper author has suggested the possibility of combining edge computing and machine learning algorithms into an Internet of medical things architecture focused on distributed computing. The paper is divided in two parts, First, the author proposed a model for collecting data usually produced by the front-end sensor frameworks on Internet of medical things devices using Edge computing and protocols such as Message Queuing Telemetry Transport (MQTT). Secondly, the author attempted to predict a disease correctly by looking at the patient's symptoms. Four diverse Machine learning algorithms K-Nearest Neighbor (KNN), Naïve Bayes, Decision tree, Random forest tree, were tested. The data set was collected from 2537 patients from the Apollo hospitals of India. To measure the performance, various performances metric is involved, and random forest gives the accuracy of 91%.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"363 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122835796","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
A Novel approach for Data mining Classification using J48DT Classifier for Intrusion Detection System 基于J48DT分类器的入侵检测系统数据挖掘分类新方法
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787632
T. Manimegalai, T. Ravishankar, L. Kannagi, K. Kannan, G. Anitha
{"title":"A Novel approach for Data mining Classification using J48DT Classifier for Intrusion Detection System","authors":"T. Manimegalai, T. Ravishankar, L. Kannagi, K. Kannan, G. Anitha","doi":"10.1109/CSNT54456.2022.9787632","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787632","url":null,"abstract":"Because of the growing quantity of network traffic that is being transmitted across the network in today's modern era, network attack detection has become a necessity. The technique of data mining is extremely important in the hunt for network assaults and anomalies. These strategies aid in the selection and refinement of meaningful and relevant knowledge from enormous data sets, which is beneficial in many situations. The process of data mining aids in the categorisation of important information for Intrusion Detection Systems (IDS). The IDS provides warnings for the network traffic informing it of any foreign intrusions into the network. We show how different data mining methods may be used for intrusion detection to offer a safe network environment in the research article. The J48DT Classifier is utilised for classification in this case. Comparisons based on characteristics such as data accuracy, the discovery of valuable patterns, and the extraction of useful information between approaches are made.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128044669","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: 6
Design Pattern Detection by Using Correlation Feature Selection Technique 基于相关特征选择技术的设计模式检测
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787569
Seema Dewangan, Rajwant Singh Rao
{"title":"Design Pattern Detection by Using Correlation Feature Selection Technique","authors":"Seema Dewangan, Rajwant Singh Rao","doi":"10.1109/CSNT54456.2022.9787569","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787569","url":null,"abstract":"Design pattern detection is a popular re-engineering job in software development. It provides essential information to the developers to recognize, sustain, and recycle the software. This article proposes a graph matching algorithm using a correlation-based feature selection technique to discover the design pattern (DP) instances from the software or system design. Usually, the feature selection method is used to choose the best instances from the dataset, which mostly matches the target feature. However, this paper has applied a correlation feature selection method to match the system design to the design pattern. We have taken three DPs comparing examples for this intention:•the first example for an entire match•the second example for a partial match•the third example of a not matchIn this experiment, we took the Abstract factory DP as a model graph, and the remaining twenty-two DPs are system or DPs. Software instances groups lots of classes and objects we converted into a graph. We observed that three of the 22 DPs are completely matched to the model DP, one pattern is not matched, and the remaining 18 patterns are only partially matched.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133262998","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
Comparative Analysis of Machine Learning Techniques for Disease Prediction in Crops 作物病害预测的机器学习技术比较分析
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2022-04-23 DOI: 10.1109/CSNT54456.2022.9787661
V. Choudhary, Archana Thakur
{"title":"Comparative Analysis of Machine Learning Techniques for Disease Prediction in Crops","authors":"V. Choudhary, Archana Thakur","doi":"10.1109/CSNT54456.2022.9787661","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787661","url":null,"abstract":"Agriculture can be considered as backbone of India. It is not only a matter of food, but agricultural crop production has an impact on the entire economy of the country, as all enterprises rely on agricultural results, whether directly or indirectly. Crop pests and diseases are the leading causes of crop loss in India. In order to control disease and pests in agriculture, early disease identification is critical. Technology can be quite useful in completing this work. Machine learning has shown to be an important technique in the prediction of crop diseases in recent years. It solves many of the challenges associated with manual crop disease diagnosis while also providing high accuracy. We compare and contrast various machine learning algorithms for disease prediction in agriculture crops in this research.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134561178","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
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