2022 IEEE International Conference on Data Science and Information System (ICDSIS)最新文献_第6页

Accident Detection and Warning Systems in VANET VANET中的事故检测和预警系统

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915806

Polisetty Swetha V Padmavathi, U. Srilakshmi, D. Venkatesulu

{"title":"Accident Detection and Warning Systems in VANET","authors":"Polisetty Swetha V Padmavathi, U. Srilakshmi, D. Venkatesulu","doi":"10.1109/ICDSIS55133.2022.9915806","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915806","url":null,"abstract":"Accidents pose a grave danger to human life. The frequency with which accidents occur on our roads has risen to such frightening levels that immediate action is required. Reporting an accident as soon as possible to the nearest rescue station can help prevent road traffic collisions. Wireless technology-aided solutions are the primary way of reporting a traffic collision. In the reporting of traffic accidents, wireless technology techniques such as Vehicular Ad-hoc Network (VANET) and the Global System for Mobile Communication (GSM) are often used. As long as vehicles are within range of one another, an ad-hoc network known as a VANET may connect them. Instead, GSM is a wireless communication standard that allows users to send and receive text messages, pictures, and multimedia messaging (MMS) across mobile phone networks. Invariably, fewer people will die, and less property will be damaged if the rescue crew receives accurate information about an accident as soon as possible. The two separate wireless accident reporting methods are discussed in this study. Compare the method’s efficacy against that of other approaches already in use.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125067076","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: 1

Power Quality Enhancement in Utility with Photovoltaic Renewable Energy Penetration Using Active Power Filter 利用有源滤波器提高光伏可再生能源渗透公用事业电能质量

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915995

Mahesh R. Pawar, V. D. Bavdhane

{"title":"Power Quality Enhancement in Utility with Photovoltaic Renewable Energy Penetration Using Active Power Filter","authors":"Mahesh R. Pawar, V. D. Bavdhane","doi":"10.1109/ICDSIS55133.2022.9915995","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915995","url":null,"abstract":"In recent era, the efforts for harnessing electrical power from renewable sources increased significantly. Application of power electronics to harness electrical power from renewable energy sources are posing serious power quality issues in grid. When power from such generation units integrated in utility grid it’s power quality, stability, and reliability is getting compromised due to nature of generation and it’s dependency on various factors like irradiance, wind speed etc. The main objective of any electric power utility company shall be providing its end user reliable and quality of power at all time. Strict laws shall be made for power quality parameter compliances to avoid detrimental effects of power quality issues. This paper addresses control of current harmonics using shunt active power filter in utility grid generated by non-linear load. The solar PV energy penetration is used to mitigate harmonics distortion and bring it down to acceptable limits as per international standards. The harmonics mitigation using shunt active power filter with hysteresis current control is presented.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126457259","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

Methodology for Determining Optimal Model and Training Data in Deep Learning 确定深度学习中最优模型和训练数据的方法

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9916009

V. K. Kodavalla

{"title":"Methodology for Determining Optimal Model and Training Data in Deep Learning","authors":"V. K. Kodavalla","doi":"10.1109/ICDSIS55133.2022.9916009","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9916009","url":null,"abstract":"Deep Learning has numerous applications in various market segments including consumer, industrial, energy & utilities, oil & gas, surveillance, autonomous vehicles and medical and so on. And within each dataset, the deep learning inference precision achieved with a trained model may be meeting the precision goals. But that does not mean the same trained model may perform equally well on some other test dataset. In practical applications, such drop in precision on test data variations is highly undesired. Hence, it is critical to train the deep learning model with adequate and augmented training data. Also, it is important to deploy an optimal deep learning model for a given application. This is to utilize optimum compute resources, when such deep learning trained model is deployed in inferencing. This becomes even more important for resource constrained and battery-operated embedded edge applications. Hence, determining the amount of training data needed and deep learning model to be used should not be on trial-and-error basis. There are no known structured methodologies available, for optimal model selection and training data. In this paper, a methodology has been proposed for determining optimal deep learning model and training data to be used, for achieving target precision levels.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116570373","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

Smart Vehicle Document Verification System Using IoT 使用物联网的智能车辆证件验证系统

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915875

N. Pavithra, C. Manasa, Preethi, R. Sapna.

{"title":"Smart Vehicle Document Verification System Using IoT","authors":"N. Pavithra, C. Manasa, Preethi, R. Sapna.","doi":"10.1109/ICDSIS55133.2022.9915875","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915875","url":null,"abstract":"The verification of vehicle documents is a significant role of the transportation department that is becoming more important as the number of vehicles registered grows. This process can be made more efficient by using an automated vehicle document verification system. IoT-based vehicle document verification system based on RFID technology in proposed this paper. As a result, the manual vehicle inspection that is currently performed can be replaced by automation. When normal vehicle checks are performed manually, a significant amount of time is lost. The proposed system will automate this process. The current verification method employs inductive loops installed in a roadbed to detect vehicles as they pass through the magnetic field loop. Similarly, sensing devices installed along the road can detect passing vehicles using the Bluetooth mechanism. Fixed audio detection devices that can identify the type of vehicle on the road. Other measurements include fixed cameras installed at strategic points along roads to categorize vehicles. However, none of these mechanisms can verify the vehicles’ documents and certificates. In this work, algorithm is proposed that uses RFID technology to automate the document verification process of vehicles with the help of an RFID reader and alcohol sensor to detect alcohol consumption by drivers to avoid road accidents.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129719485","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 Modalities of Dyslexic Students using Neuro-Linguistic Programming to Enhance Learning Method 用神经语言程序设计来预测失读症学生的学习方法

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915905

Gaurav J. Choube, Gauri Rahul Dudhmande, Jagalingam Pushparaj, Christopher Anand, Shilpa Suresh

{"title":"Predicting Modalities of Dyslexic Students using Neuro-Linguistic Programming to Enhance Learning Method","authors":"Gaurav J. Choube, Gauri Rahul Dudhmande, Jagalingam Pushparaj, Christopher Anand, Shilpa Suresh","doi":"10.1109/ICDSIS55133.2022.9915905","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915905","url":null,"abstract":"Dyslexia causes difficulty in reading, writing and learning. The children at a tender age have always suffered due to dyslexia. Dyslexia deceives student’s perception and makes it difficult in the process of learning. In this paper, machine learning techniques like multi-layer perceptron, Decision tree and Gaussian NB approaches were implemented for the prediction of modalities. To enhance the learning approach for the students suffering from dyslexia, the predicted modalities can be adopted. The sampled data was trained, and the target labels were classified into three classes as visual, auditory, and kinesthetic. The data was processed and fed into multi-layer perceptron, decision tree and naive bayes machine learning algorithms using scikit-learn. Confusion matrix was used to evaluate the performance measure of the algorithms. It was observed that models achieved accuracy of 81.41% for MLP Classifier, 63.82% for Decision tree and 79.25% for Naive bayes. The best result was achieved by MLP Classifier.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132927653","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: 1

Detection of a Facemask Using Convolution Neural Network 基于卷积神经网络的面罩检测

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915869

R. Chandana, S. Ranganatha, Sanjay

引用次数: 1

Comparison of SVR Techniques for Stock Market Predictions 股票市场预测的SVR技术比较

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915990

S. Sricharan, Vinay Joshi

{"title":"Comparison of SVR Techniques for Stock Market Predictions","authors":"S. Sricharan, Vinay Joshi","doi":"10.1109/ICDSIS55133.2022.9915990","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915990","url":null,"abstract":"Here we build and test the Support Vector Regression (SVR) model for Indian stock market prediction. The SVR is the regression model based on the primitive Machine Learning (ML) technique called Support Vector Machines (SVM) wherein the sparsity and the parameters of the decision process can be effectively controlled by selecting the desired kernel functions. The conventional ML based prediction and regression models face regularization issues leading to overfitting, unstable learning for nonlinear and multi-dimensional data. We used a strong feature extractor to extricate the parameters indicating the trend of the multi-dimensional financial data. The SVR then correlates the features on a GPU based execution environment for faster predictions. Though our goal is to build a standalone application for the Indian Stock market prediction, as a first step we choose to build and compare SVR models with various kernels to decide whether to buy stocks or not based of the regression model built upon the 20 years of stock market data. The results indicate that the SVR is a very efficient and powerful tool for handling the financial data and can be used in building the stock market predictions.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130846120","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

Implementation of a Low-power N-bit Hybrid Carry Select Adder with Sum-Carry Selection 具有和进位选择的低功耗n位混合进位选择加法器的实现

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915807

Kaja Naga Venkata Akhil, P. S. Kumar

{"title":"Implementation of a Low-power N-bit Hybrid Carry Select Adder with Sum-Carry Selection","authors":"Kaja Naga Venkata Akhil, P. S. Kumar","doi":"10.1109/ICDSIS55133.2022.9915807","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915807","url":null,"abstract":"Recently, the digital circuitry requires a reduction in space and power by optimizing the time with an increase in performance. Adders serve as the building blocks of the basic components of digital circuits. So, the performance of adders must be improved to enhance the performance of real-world integrated circuits. This article is focused on implementation of novel architecture of hybrid carry select adder (CSLA) utilizing full carry generation (FCG), full sum generation (FSG), half carry generation (HCG), and half sum generation (HSG) blocks, which is named as Hybrid CSLA. Further, the N-bit Hybrid-CSLA is implemented using reconfigurable properties with square root additions through modified sum carry selection (MSCS). Further, the Carry and Sum output generation consumes less propagation time by utilizing multiplexer switching logic, which selects the full sum bits and carry bits in high-speed manner. The simulation results show that the proposed Hybrid CSLA resulted in improved area, delay and power consumptions as compared to the basics adders and state-of-art approaches.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132126973","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

IoT Based Automated Elevator Emergency Alert System Using Android Mobile Application 基于物联网的自动电梯紧急警报系统

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915909

Akshat Sharma, A. Chatterjee, Pooja K. Thakur, Swapnil Jha, K. Sriharipriya

{"title":"IoT Based Automated Elevator Emergency Alert System Using Android Mobile Application","authors":"Akshat Sharma, A. Chatterjee, Pooja K. Thakur, Swapnil Jha, K. Sriharipriya","doi":"10.1109/ICDSIS55133.2022.9915909","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915909","url":null,"abstract":"Elevators have found use almost everywhere in the modern society. They are used in residential buildings, commercial buildings, hospitals, malls, industries, et cetera. In fact, almost every building with more than 5 floors employs the use of elevators. This extensive use of elevators is also accompanied by instances of failure of the machine. Often, people are stuck in elevators for hours, and in severe cases, such failures may also cause loss of life. Thus, entailing the need for a system deployable in the time of an emergency. This paper thus focuses on the creation of an Internet of Things application that allows the maintenance business and technician to monitor the elevator’s status in real time and get information about emergencies or scheduled repairs. The elevator communication module, the IoT platform, and the front-end software application make up the system. The data taken from the elevator’s vital systems is sent to the IoT platform through the communication module, where it is stored, viewed, and analysed. The data is then sent from the IoT platform to the mobile application. The technician and the maintenance firm are notified of any emergency or planned maintenance period through the front-end mobile application. In the event of an emergency, this program also has a map feature that will instantly provide the shortest way from the technician’s position to the elevator. The project’s major goal is to make elevator rides safer for passengers by providing timely maintenance and prompt emergency response.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131826396","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 Impact of YOLOv5 on Text Detection and Recognition System using TesseractOCR in Images/Video Frames YOLOv5对基于TesseractOCR的图像/视频帧文本检测与识别系统的影响

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915927

Y. Chaitra, R. Dinesh, M. Jeevan, M. Arpitha, V. Aishwarya, K. Akshitha

{"title":"An Impact of YOLOv5 on Text Detection and Recognition System using TesseractOCR in Images/Video Frames","authors":"Y. Chaitra, R. Dinesh, M. Jeevan, M. Arpitha, V. Aishwarya, K. Akshitha","doi":"10.1109/ICDSIS55133.2022.9915927","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915927","url":null,"abstract":"Text detection and recognition in images and videos are significant research areas in computer vision. A computer vision technology is used for smart city real-time traffic monitoring, and a security camera can simultaneously record the license plate information of suspected vehicles. The challenging task here is detecting the text images that are arbitrary oriented, such as aerial photographs and scene texts. Most complementary text detection and recognition methods are designed to identify text in images that are clear in the background and near-horizontal text. However, those methods will not be effective in detecting text in complex images and video streams. To address this issue, we propose a system that detects the text images using the YOLOv5s model, which effectively trains small-scale images and YOLOv5x for largescale images. TesseractOCR recognizes the detected text by converting the image to a string and storing it in CSV format. The experiment was carried out for ICDAR2013, ICDAR2015, and YVT images/frames. The results indicate that the proposed method using YOLOv5x effectively detects images/video frames with reasonably good accuracy, and the recognition rate is suitable for a near-horizontal image using TesseractOCR.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128094090","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