2022 IEEE International Conference on Data Science and Information System (ICDSIS)最新文献_第9页

Detection and Prevention of UDP Reflection Amplification Attack in WSN Using Cumulative Sum Algorithm 基于累积和算法的WSN中UDP反射放大攻击检测与防范

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915994

B. Santhosh Kumar, V.S Sanketh Gowda

引用次数: 1

Discharge Structure for Hazard and Vulnerability Analysis using GIS and Real Time Flood Data 基于GIS和实时洪水数据的泄洪结构危害与脆弱性分析

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915896

Gorijala Kusuma, Sahithi Tatineni, Suhitha Yalamanchili, S. Vasavi, C. Harikiran

{"title":"Discharge Structure for Hazard and Vulnerability Analysis using GIS and Real Time Flood Data","authors":"Gorijala Kusuma, Sahithi Tatineni, Suhitha Yalamanchili, S. Vasavi, C. Harikiran","doi":"10.1109/ICDSIS55133.2022.9915896","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915896","url":null,"abstract":"From pandemics to man-made disasters, all have impacted hundreds of thousands of humans worldwide. India is ranked as the 14th vulnerable country in the global because of severe weather-associated events. Out of thirty-six States and Union Territories in India, twenty-seven are disaster-prone. With GIS interactive maps, Government view essential statistics in layers and make knowledgeable decisions. GIS based information providing to the general public, how much area has to be evacuated, what are the alternative places for accommodation, food and medicine supply is important. This app is developed for the state of Andhra Pradesh as suggested by Andhra Pradesh Disaster Management Authority (APSDMA) which predicts the floods based on the runoff value given and identifies the disaster prone areas according to the runoff parameter. This web application also provides methods for flood change detection using image processing. The technology which is used here is ArcGIS. The database used for storing the runoff data is MongoDB. The accuracy of the Convolutional Neural Network (CNN) model that was built is 98.4%.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"10 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":"116051285","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

Optimized High Performance Concrete Mix Proportioning Through JAYA Algorithm 利用JAYA算法优化高性能混凝土配合比

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9916011

M. Jayaram

{"title":"Optimized High Performance Concrete Mix Proportioning Through JAYA Algorithm","authors":"M. Jayaram","doi":"10.1109/ICDSIS55133.2022.9916011","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9916011","url":null,"abstract":"In this paper an interdisciplinary research related to optimization of engineering design which is directed towards sustainability of materials is presented. The case in point is optimization of high performance concrete mixes. The recent bio-inspired algorithm, namely, Jaya algorithm has been implemented for the same. The development of models comprised of two steps, a sizable data of 500 mix designs gotten from standard publications and reported experimental results by researches were preprocessed and legitimate and befitting data sets numbering around 450 were retained for model development. Further, the data is partitioned in to five strength ranges. For each strength range, the lower limit and upper limits of variables and rational ratios of weights were mined from the data after its preprocessing. The algorithm performed very well just for 100-150 iterations. The mix proportions generated by this algorithm for assorted 28 day’s ranges of strength are highly acceptable and align closely with the practical values found in the data. This is reflected by the low mean square error. The mean square error was found to be 10 %-12% for cement, 7% - 9% for fly ash, and 2.1% - 4.0 % for water. Further, a comprehensive comparison of the results obtained in the previous studies of the author with other algorithms namely, Honey Bee Optimization (HBO), Ant Lion Algorithm(ALO), Particle swarm Optimization(PSO), and GA-Elitism Based models (EGA), is also made and presented. The quantities of ingredients of concrete generated by these algorithms are almost close. The differences in mean square errors noticed were marginal though. The output of Jaya algorithm is found to be very close to those generated by ALO.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"621 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":"116205915","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

Analyzing of Political Tweets in Hindi Language Using Machine Learning and Deep Learning 用机器学习和深度学习分析印度语的政治推文

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915864

Tarun Jain, S. Mathur, A. Ninnad, Bikkumalla Nikshep, Namita Chalil

引用次数: 2

Design of a Novel Encoder for Flash Analog to Digital Converter 一种新型Flash模数转换器编码器的设计

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915797

Arshiya Sadath, Deepa

{"title":"Design of a Novel Encoder for Flash Analog to Digital Converter","authors":"Arshiya Sadath, Deepa","doi":"10.1109/ICDSIS55133.2022.9915797","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915797","url":null,"abstract":"Analog to digital converters (ADC) are extensively used as a basic component in signal processing systems to convert the available analog signals to digital signals. Flash ADC, also called as parallel ADC offer high speed conversion than other ADCs. The major issues occurring in the Flash ADC are the response time of comparators and speed of thermometer to binary encoder. Therefore, different designs have been proposed previously for both comparators and encoders to overcome these issues. This work is centred on the encoder and reviews the different designs of encoders such as multiplexers, adders, adders with majority gates as its carry function and XOR-MAJ encoder. A novel encoder is proposed which is designed using full adders to reduce the number of transistors and eventually reducing number of capacitance nodes to reduce delay. The design is simulated at 130nm CMOS technology using Mentor Graphics EDA tool. The comparison of designs shows the worst-case delay, number of transistors and power consumption. The result analysis show that the novel encoder uses 92 transistors with the worst-case delay of 144.77 ns but the power dissipation is about 51.34 nW which is comparatively highest. Hence the analysis shows the novel encoder can be used when the constraints are number of transistors and delay but not for low power applications.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"301 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":"122796982","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

Secure Data Retrieval System using Biometric Identification 使用生物特征识别的安全数据检索系统

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915968

J. Anand Babu, H. Neha, K. S. Babu, Rishal Nishma Pinto

{"title":"Secure Data Retrieval System using Biometric Identification","authors":"J. Anand Babu, H. Neha, K. S. Babu, Rishal Nishma Pinto","doi":"10.1109/ICDSIS55133.2022.9915968","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915968","url":null,"abstract":"With the continuous dependence of using electronic media has drastically impacted our communications, with most of them currently taking place digitally. Users frequently have to logon to distant workstations, yet the adversarial Internet world can put users & service providers on risk. Biometric identification have grown in popularity in current times. With the rapid evolution of decentralized computation, data base owners are attempting to disperse the massive amount of biometric data as well as ID allocation to the cloud server in order to eliminate the high expenses of storage and computation. Biometric authentication technologies are becoming more popular as a method of verifying individual’s identity. Because of the many benefits that biometric credentials offer over traditional authenticating approaches, biometrics has become widely prominent as a way of verifying persons (e.g., password-based authentication). The inherent significant relation among the user with his/her biometric information is the main distinguishing aspect of such an authentication system. Yet, if the biometric feature is exploited, this very same favorable aspect creates major personal & safety problems. The major complex problems that must be considered while creating secure & privacy-preserving biometric authentication systems (PP-BAS) are discussed in this paper. Further we specifically outline the major challenges to secure & PP-BAS and provide recommendations for potential solutions in attempt to create S-PP BAS in cloud computing.","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":"128554143","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

Accident Detection using DenseNet 使用DenseNet进行事故检测

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915904

B. Mitleshwar Rao, Shrijith Devdas Nair, Shivasharvesh, R. Dhanalakshmi, Arulmozhi

引用次数: 0

IoT Based Biometric Supported Vehicle User Identification System 基于物联网的生物识别支持车辆用户识别系统

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915850

Nayana Hegde, Rani S Rashmi, Abdul Azeez, Jebran P Mohamed, J. Surendiran

引用次数: 3

Sentiment Analysis of Amazon Smartphone Reviews Using Machine Learning & Deep Learning 基于机器学习和深度学习的亚马逊智能手机评论情感分析

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915917

Neelesh Sharm, Tarun Jain, Saket S Narayan, Anurag C Kandakar

{"title":"Sentiment Analysis of Amazon Smartphone Reviews Using Machine Learning & Deep Learning","authors":"Neelesh Sharm, Tarun Jain, Saket S Narayan, Anurag C Kandakar","doi":"10.1109/ICDSIS55133.2022.9915917","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915917","url":null,"abstract":"The past few years have been marked by quite a few developments in e-commerce and online shopping with the biggest of them being in the smartphone segment. India is now the world’s largest market for smartphones with its share having increased to 45% in 2020 by registering a mammoth 7% growth during the pandemic year. Some of the major smartphone brands here are Xiaomi, Samsung, and OnePlus. These brands have often partnered exclusively with e-commerce platforms like Amazon and Flipkart with sweet deals and offers for buyers. For smartphones of all price segments, reviews on these sites can be an important indicator of how satisfied customers are with the product and can also be an important factor for decision making that helps customers choose whether a product is worth purchasing or not. In this paper, we will be exploring algorithms and techniques used for sentiment analysis and text classification of smartphone reviews on Amazon. The dataset we used for research is available on Kaggle and contains 6S,000 reviews of 720 smartphones of numerous brands. We have used a combination of machine learning and deep learning algorithms for the same, starting with baseline logistic regression and naive Bayes models and then moving on to complex support vector machines and Recurrent Neural Networks such as LSTM using the FastAI library.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"18 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":"122029747","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

Ewe Health Monitoring Using IoT simulator 使用物联网模拟器进行母羊健康监测

2022 IEEE International Conference on Data Science and Information System (ICDSIS) Pub Date : 2022-07-29 DOI: 10.1109/ICDSIS55133.2022.9915993

Tanveer Baig Z, C. Shastry

引用次数: 0