2023 World Conference on Communication & Computing (WCONF)最新文献_第5页

Smart Shoes for Women Safety with Implicit Triggers 智能鞋为女性安全与隐性触发

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235229

M. Dhore, Himanshu Bhatia, Shraddha Bagav, Prajwal Kadam, Amey Dhuri

{"title":"Smart Shoes for Women Safety with Implicit Triggers","authors":"M. Dhore, Himanshu Bhatia, Shraddha Bagav, Prajwal Kadam, Amey Dhuri","doi":"10.1109/WCONF58270.2023.10235229","DOIUrl":"https://doi.org/10.1109/WCONF58270.2023.10235229","url":null,"abstract":"The high incidence of assault and harassment faced by women in public places has been a persistent issue in various regions around the globe. Despite the existence of laws aimed at protecting women from such misbehavior, incidents of stalking, sexual harassment, and assault continue to occur. Considering this, various smartphone apps have been developed to provide women with a means of protection through their mobile devices. In an effort to address this problem, this study proposes the development of a smart shoe, referred to as Step Safe. This design utilizes IoT-based hardware embedded in a shoe which consists implicit trigger and circuitry present in a shoe which can be triggered by the user in emergency situations to send alerts in the form of SMS to all emergency contacts including parents, friends and relatives. The shoe incorporates a triggering mechanism, GPS module, and emergency calling feature to provide women with a means of quickly and effectively alerting authorities of their location in emergency situations. The system also includes an accompanying Android application and website, which further enhance its functionality. Also, a unique part of the system is a website which is synchronized with the Firebase database and was created especially for law enforcement organizations. When a user registers on the Step Safe app, her information is transferred to a database that the police may access. In the event of an abduction or missing person, this enables quick and simple access to vital information such the user’s last known location, contact information, and guardian information. It is anticipated that this proposed technology will address a significant percentage of the fundamental concerns faced by women in regard to personal safety and assist them in remaining protected in potentially dangerous situations.","PeriodicalId":202864,"journal":{"name":"2023 World Conference on Communication & Computing (WCONF)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126382862","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

YouTube Universe of Comments: A Machine Learning approach for systematic classification of YouTube Comments on custom prepared dataset YouTube评论宇宙:一种机器学习方法，用于在自定义准备数据集上对YouTube评论进行系统分类

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235049

Sankalp Naik, Ashay Katre

{"title":"YouTube Universe of Comments: A Machine Learning approach for systematic classification of YouTube Comments on custom prepared dataset","authors":"Sankalp Naik, Ashay Katre","doi":"10.1109/WCONF58270.2023.10235049","DOIUrl":"https://doi.org/10.1109/WCONF58270.2023.10235049","url":null,"abstract":"At present, YouTube can be regarded as a cloud service owing to the amount of data it adds every second and the enormous data it stores in its data farms. It doesn’t delete old content, it uses redundant storage. The platform can be more sustainable and cost efficient, if they were to discard redundancies of which major portion is constituted by the spam comments or comments that are offensive/abusive. In this paper several machine learning models are used in order to reduce those comments and eventually towards a more efficient storage model. We first address the task of dataset preparation by designing a comprehensive annotation scheme, considering various dimensions such as sentiment, topic, toxicity, and engagement. Leveraging this annotated dataset, we develop a robust machine learning framework that combines state-of-the-art natural language processing techniques with advanced classification algorithms. Our methodology involves several stages, including preprocessing, feature extraction, and model training. We also employ techniques like sentiment analysis and toxicity detection to capture the sentiment and abusive nature of comments, respectively. We also introduced gravity to the comments which would act as a reward mechanism to the comments. To evaluate the performance of our approach, we conduct extensive experiments on a large-scale YouTube comments dataset. We compare the effectiveness of various classification algorithms, including support vector machines, random forests, and deep learning models, in accurately categorizing comments based on our predefined annotation scheme. Additionally, we assess the generalizability of our model by conducting cross-domain experiments on different genres of YouTube videos. Overall, our work contributes to the understanding and management of the YouTube comment ecosystem, showcasing the power of machine learning techniques in systematically classifying and analyzing comments on this popular platform.","PeriodicalId":202864,"journal":{"name":"2023 World Conference on Communication & Computing (WCONF)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123117353","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 Common Source Amplifier Circuit Using Gate All Around Junctionless Dopingless Nanowire TFET 采用栅极无结无掺杂纳米线TFET的共源放大电路的设计与实现

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235094

Mayank Trehan, Pradeep Kumar

{"title":"Design And Implementation Of Common Source Amplifier Circuit Using Gate All Around Junctionless Dopingless Nanowire TFET","authors":"Mayank Trehan, Pradeep Kumar","doi":"10.1109/WCONF58270.2023.10235094","DOIUrl":"https://doi.org/10.1109/WCONF58270.2023.10235094","url":null,"abstract":"The practical utilization of analog common source amplifier circuit, implemented using Gate All Around Junction Less Dopingless Nanowire Tunnel Field Effect Transistor (GAA JL DL NW TFET) device is proposed herein. The integration of Tunnelling, GAA architectures, dopingless and Junction-Less technique in the proposed Nanowire TFET structure led to exceptional electrostatic control over the channel. That is due to the enhanced individual properties of each technique which has resulted in the refinement of the transfer characteristics of the conventional MOSFET, HD TMG TFET Structure which were analyzed and compared with GAA JL DL NW TFET using analog parametric analysis, improvements such as, a reduced $mathrm{I}_{mathrm{O}mathrm{F}mathrm{F}}$ of $4.79 times 10^{-16}$ (A), an improved $mathrm{I}_{mathrm{O}mathrm{N}}$ of 1.17 $(mu mathrm{A})$, and an enhanced $mathrm{I}_{mathrm{O}mathrm{N}}/mathrm{I}_{mathrm{O}mathrm{F}mathrm{F}}$ of $2.44 times 10^{15}$. Look up table approach has been used to study CS amplifier circuit application using proposed device, it was determined that the proposed design achieved higher gain of 10.23 dB for the same configuration of the CS Amplifier circuit and draws lower current while delivering the same voltage gain as the existing design.","PeriodicalId":202864,"journal":{"name":"2023 World Conference on Communication & Computing (WCONF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126306720","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

Exploring the Impact of Regularization to Improve Bankruptcy Prediction for Corporations 探讨规范化对提高公司破产预测的影响

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235083

Shaun Almeida

{"title":"Exploring the Impact of Regularization to Improve Bankruptcy Prediction for Corporations","authors":"Shaun Almeida","doi":"10.1109/WCONF58270.2023.10235083","DOIUrl":"https://doi.org/10.1109/WCONF58270.2023.10235083","url":null,"abstract":"Bankruptcy prediction for corporations is highly essential in today’s fast growing global economy for various reasons, including risk management and financial sustainability. For several years, credit agencies have used statistical methods like regression and discriminant analysis to assess the probability of bankruptcy. However, as Deep Learning and Neural Networks are gaining more momentum to solve more challenging problems, we are turning our attention towards them to address our immediate problems. In this paper, we attempt to explore and apply the working of various neural network methodologies, including the basic architecture, application of regularization techniques, such as L1, L2, Dropout and Early Stopping, to observe the difference in performance for predicting bankruptcy. Other machine learning algorithms such as SVM, Random Forest and XGBoost have also been implemented to compare their performance with neural networks. The results achieved in terms of accuracy were as follows; 82%, 49%, 89%, 90% and 94% for ordinary neural network model, L1, L2, Dropout and Early Stopping methods respectively. Other models, SVM, RF and XGBoost showed an accuracy of 87%, 86% and 85% respectively.","PeriodicalId":202864,"journal":{"name":"2023 World Conference on Communication & Computing (WCONF)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123747827","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

An Extensive Review on Recognition of Antique Tamil characters for Information Repossession from Epigraphic Inscriptions 碑文信息回收中古泰米尔文字识别问题综述

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235212

S. Bhuvaneswari, Kathiravan Kannan

{"title":"An Extensive Review on Recognition of Antique Tamil characters for Information Repossession from Epigraphic Inscriptions","authors":"S. Bhuvaneswari, Kathiravan Kannan","doi":"10.1109/WCONF58270.2023.10235212","DOIUrl":"https://doi.org/10.1109/WCONF58270.2023.10235212","url":null,"abstract":"The ancient script recognition is one of the most demanding areas for the researches due to numerous variations in writing styles. All-embracing research work is reported on recognition of various ancient scripts such as Brahmi, Grantha. However the work accounted on Tamil scripts is still in its infancy so momentous research is required in this field. The Tamil scripts which contain loop, curves, circle, dots, etc are the complex issues for identifying the characters present in the image or the input data. The Tamil script has many characters with many features in which those features should be extracted in an efficient way to envisage the character with higher accuracy. There is no proper technology to convert the ancient inscriptions to human readable form in digitised format. Several scripts and inscriptions are examined, which indicates some future research prospects. Based on study demeanour it has been found that there is a need of an automated system for ancient character recognition with hybrid feature extraction and classification techniques for attained the accurate results. This paper aims to provide the insights of types of scripts, inscriptions, various methods, techniques of feature extraction, classification reported over the last few years in the field of epigraphy. So, a novel framework has been proposed to recognize the ancient Tamil character with higher classification accuracy with an aim to surpass the workflow of existing systems.","PeriodicalId":202864,"journal":{"name":"2023 World Conference on Communication & Computing (WCONF)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125644624","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

Predicting Severity from Electronic Health Records of Leprosy Patients using Ensemble Learning 利用集成学习预测麻风病患者电子健康记录的严重程度

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235056

Jalpa Mehta, M. Kalla

引用次数: 0

Revolutionizing Rice Disease Diagnosis: A Fusionof Convolutional Neural Networks and Support Vector Machines 革命性的水稻病害诊断:卷积神经网络和支持向量机的融合

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235197

Arshleen Kaur, V. Kukreja, D. Banerjee, D. Bordoloi

{"title":"Revolutionizing Rice Disease Diagnosis: A Fusionof Convolutional Neural Networks and Support Vector Machines","authors":"Arshleen Kaur, V. Kukreja, D. Banerjee, D. Bordoloi","doi":"10.1109/WCONF58270.2023.10235197","DOIUrl":"https://doi.org/10.1109/WCONF58270.2023.10235197","url":null,"abstract":"This study uses a CNN architecture to provide a deep learning strategy for the detection and categorization of eight common rice illnesses. Three layers of convolution, three maximum pooling layers, including two fully linked layers make up the proposed model. The photos of numerous rice diseases were gathered from various sources and included in the dataset for this study. A 2,830 picture-labeled dataset with an 80/20 split between both the testing and training sets is used to train the model. The model that was trained is then assessed using Fl-score metrics for precision, recall, and recall. The evaluation’s findings are shown in a graph where each disease class’s effectiveness is gauged by the percentage of assistance given to each class. According to the experimental findings, the model that was suggested achieves a precision of 81.23%, so it’s comparable to the most recent models. The accuracy of each class is greater than 77%, demonstrating the model’s ability to distinguish between various rice illnesses. showing that the model is capable of recognizing the majority of the instances for each disease class, the accuracy of the recall of every category is also over 55%. Each class’s F1 score is higher than 67%, indicating a decent overall performance for the model. In conclusion, the suggested model has a good level of accuracy, recall, and Fl-score for accurately classifying various rice illnesses. The detection and treatment of rice diseases may benefit from the findings of this research, which will help rice production continue to grow sustainably. It is possible to do additional research to enhance the performance of the model by expanding the dataset and utilizing transfer learning strategies.","PeriodicalId":202864,"journal":{"name":"2023 World Conference on Communication & Computing (WCONF)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133259636","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

Hybrid Islanding Identification Strategy for PV Fed Distributed Generators Using Rate of Frequency Variation and Even Harmonic Perturbation 基于频率变化率和均匀谐波摄动的PV - Fed分布式发电机混合孤岛辨识策略

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235025

Praveen Raj, J. S. Savier

{"title":"Hybrid Islanding Identification Strategy for PV Fed Distributed Generators Using Rate of Frequency Variation and Even Harmonic Perturbation","authors":"Praveen Raj, J. S. Savier","doi":"10.1109/WCONF58270.2023.10235025","DOIUrl":"https://doi.org/10.1109/WCONF58270.2023.10235025","url":null,"abstract":"The power sector has benefitted from Renewable Energy Source (RES) dependent distributed Generation (DG) to a large extent, as there could be a substantial reduction in the investment in large transmission system, especially in remote areas. The environment owes the renewable energy source dependent DG due to the reduction in the emission. Due to the introduction of RES fed DGs, the dependability of the power supply has been improved. The Synchronization of DGs with the grid is inevitable as the surplus power in one can meet the deficiency in the other. However, Synchronization of DG with the grid poses certain concerns as well. One of the major concerns is the islanding state of the DGs. Islanding is the scenario in which a DG keeps a site powered despite the absence of exterior bulk Electric Power Systems (EPS). It is mandatory to identify involuntary islanding as quickly as possible and to isolate the DG, due to serious hazards to equipment and working personnel. In this paper a robust hybrid Islanding Identification Strategy (IIS), with Rate of frequency variation (ROFV) as passive method and Even Harmonic Perturbation (EHP) as active method is presented and their performances are assessed. MATLAB/SIMULINK 2023a software is used to simulate the proposed algorithm.The obtained results show that the hybridized methods outperforms well when compared with the conventional methods.","PeriodicalId":202864,"journal":{"name":"2023 World Conference on Communication & Computing (WCONF)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133939729","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 Review of Cloud Microservices Architecture for Modern Applications 现代应用的云微服务架构综述

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235199

Gunjan Pathak, Monika Singh

{"title":"A Review of Cloud Microservices Architecture for Modern Applications","authors":"Gunjan Pathak, Monika Singh","doi":"10.1109/WCONF58270.2023.10235199","DOIUrl":"https://doi.org/10.1109/WCONF58270.2023.10235199","url":null,"abstract":"As a potent architectural paradigm for creating and deploying contemporary applications in the cloud computing environment, cloud microservices have been developed. This review paper offers a thorough examination of the ideas, advantages, problems, and developments related to cloud microservices. We start by outlining the core ideas and traits of the microservices architecture and highlighting its benefits over more conventional monolithic ones. The advantages of using cloud microservices, such as scalability, robustness, and flexibility, are then discussed, along with the difficulties in implementing and managing them. The article compares the features and constraints of several cloud platforms and tools for deploying and orchestrating microservices, such as AWS, Azure, Google Cloud Platform, and Kubernetes. Real-world case studies highlight effective cloud microservices implementations and offer helpful insights and best practices. We also examine current trends in the field and recent research papers to determine where future research should be focused. Additionally, cloud microservice-specific security and governance issues are covered, with an emphasis on methods for encrypting communication, controlling access, and guaranteeing data privacy. This review paper seeks to increase the comprehension of this revolutionary architectural paradigm by providing a thorough examination of cloud microservices for modern applications.","PeriodicalId":202864,"journal":{"name":"2023 World Conference on Communication & Computing (WCONF)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134128034","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

MPPT Controller for Efficiency Enhancement of Solar Power Plant Using Neural Network 基于神经网络的太阳能电站效率提升MPPT控制器

2023 World Conference on Communication & Computing (WCONF) Pub Date : 2023-07-14 DOI: 10.1109/WCONF58270.2023.10235090

Shubham Soni, R. Bindal, M. S. Manna

引用次数: 0