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

{"title":"Sentiment Analysis of Movie Reviews in Hindi Language Using Machine Learning","authors":"Tarun Jain, Payal Garg, Rimjhim Gupta, Priyanka Goyal, Namita Chalil","doi":"10.1109/ICDSIS55133.2022.9915961","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915961","url":null,"abstract":"Sentiment analysis has become an important field in the last few years. By performing sentiment analysis of user reviews, news, blogs, etc. we gain a deeper understanding of the general opinion towards a movie, product, etc. Sentiment Analysis is a very valuable tool for organizations to understand the opinion of the public towards their product, service movie, etc. Rather than reading an entire post, blog, or review, Sentiment Analysis allows companies to know the general opinion about their product or movie by deducing the emotion present in the piece of text. Sentiment analysis identifies the keywords in a piece of text and determines the emotion contained in it. Several works have been carried out in the subject area of sentiment analysis on English but hardly any work on Hindi. Hindi is a widely spoken language with a growing number of speakers. The social media platforms too see a large number of reviews, blogs in Hindi. Due to the rising amount of web content in Hindi, there was a requirement to perform sentiment analysis on the Hindi language. We propose a system for sentiment analysis on Hindi by using the Bag of Words model and applying four Machine Learning models.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"794 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":"116179702","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}

{"title":"Disease Classification in Citrus Leaf using Deep Learning","authors":"P. Sudharshan Duth, Shreeharsha Gopalkrishna Bhat","doi":"10.1109/ICDSIS55133.2022.9915847","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915847","url":null,"abstract":"India is an agricultural country. Its economy is largely based on crop production. The continuous improvement of India’s agriculture sector is required to maintain its competitive advantage in the global market. It is through proper monitoring that the crop is healthy and disease-free. Finding the most effective and appropriate one can be very challenging and time-consuming. Usually, finding the right one requires the help of experts and equipment such as Machine Vision Systems. Deep learning is a promising technology for pattern recognition in this research work, a detailed study of five different leaf diseases. They are Blackspot, Canker, Miner, and Healthy leaves are used for the detection and classification of citrus leaf diseases using various neural networks and a comparative outcome is the solution of this work.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"255 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":"116808525","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}

{"title":"Design of Virtual Assessment Application system based on Python GUI and Face Detection to Supervise Pupils during E-examination","authors":"Salma Itagi, P. Arpitha., Kari Keerthisri, Vihaa Harish Shetty","doi":"10.1109/ICDSIS55133.2022.9915988","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915988","url":null,"abstract":"Virtual Assessment is widely utilized in everyday life since it saves time and is the most accurate approach available, especially as the number of participants grows in today’s world. Students can take virtual tests that provide guidelines and tips to help them understand the material. Every technical student should have a fundamental understanding of the online examination system. Because of the rapid and precise grading system, all of the exams are held online. The flexibility of an online examination is greater than that of a written examination. It is primarily intended to encourage educational diversity. The integrity of the exam pattern is less likely to be compromised with online examination. For example, when compared to other examination systems, disposing of the online test setup is the most difficult. For the implementation in this exam platform technologies like Python GUI, Machine Learning, Image Processing, Firebase are used. Tkinter is used as python GUI toolkit(Frontend), Firebase as Backend application development, Spyder(Anaconda) is an IDE for python language, OpenCV for Image Processing and Haarcascade Classifier to detect the objects in the picture. The goal of this project is to provide the exam platform for students, so that the tests can be conducted in coordinated form without cheating and also to predict the accurate results of each student.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"7 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":"124694014","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}

{"title":"Effect of IoT Application and Smart Cities Using Deep Learning Techniques","authors":"V. Thirumurugan, R. Anandan, R. Vijayarangan","doi":"10.1109/ICDSIS55133.2022.9915856","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915856","url":null,"abstract":"This effort is an attempt to provide some insight into the future degree, possible plausible consequences, and challenges that may arise. The Internet of Things and how it may impact the life of the general public sooner rather than later in relation to the creation of smart urban areas in India are important questions to consider. The Internet of Things (IoT) can be defined as a network of physical or virtual articles or things that have been implanted with hardware, sensors, and programming projects that have scheduled availability, enabling these items to gather and exchange information, thereby providing availability to anything and everyone at any time, from any location, at any time. Articles may be recognized and controlled remotely using the Internet of Things (IoT), which makes use of an existing system foundation. The Internet of Things allows items to be detected and controlled remotely over an existing web-based network infrastructure, opening the door to more straightforward coordination between the genuine physical world and computer-based virtual environments, and resulting in increased productivity, accuracy, and financial advantage for businesses. Everyone and everything would be able to communicate with one another via the use of an implanted figuring structure that exists inside the Internet foundation, which would enable them to be easily distinguished. As a consequence of the growth of the 100 Smart urban community’s effort in India, the Internet of Things as a concept seems to be incredibly promising. The Internet of Things (IoT) has a particularly promising future in India, thanks to the government’s emphasis on, support of, and experimentation with efforts to develop a better framework. Even businesses are developing innovative products, and businesses are aware of the advantages that the Internet of Things brings to the table, which is why they are embracing it. In the event that research and assets are further developed, the Internet of Things might become significant on a global basis. If such a development becomes a reality, it is possible that the aspirations for IoT use in India would be realised as predicted, all things considered.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"12 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":"132467193","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}

{"title":"An Efficient 5-Transistor SRAM Cell Design using FNSBS-CNTFET for Improving Read and Write Stability","authors":"Gopavaram Suneel Kumar, Gannera Mamatha","doi":"10.1109/ICDSIS55133.2022.9915838","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915838","url":null,"abstract":"In this manuscript, 5-Transistor SRAM Read/Write Assist Techniques based on Fully Nonvolatile Spin-Based Synapse Carbon Nanotube Field-Effect Transistor (FNSBS-CNTFET) is designed for improving read and write stability. It uses two cross-coupled FNSBS-CNTFET for storing data, along with one access transistor connected with bit line (BL) and word line (WL) with minimum supply voltage therefore leakage current is reduced. By this, the proposed method reduces the delay of writing and reading cycles and to get better static noise margin (SNM) and controls precharge voltage. The proposed 5 FNSBS-CNTFET-SRAM is done in the HSPICE platform. Then the performance of the proposed 5T FNSBS-CNTFET-SRAM design is measured in terms of lower Read Delay by 24.97%, 18.04%, lower Write Delay by 20.83%, 19.06% and compared with existing methods like 10T CNTFET-SRAM, 8T CNTFET SRAM respectively.","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":"133000341","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}

{"title":"Banana Grading using Deep Learning Techniques","authors":"P. Sudharshan Duth, B. S. Shashidhara","doi":"10.1109/ICDSIS55133.2022.9915998","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915998","url":null,"abstract":"The horticulture sector in India accounts for around 33% of agriculture’s Gross Value Added (GVA), making it a substantial asset to the Indian economy. India is the second greatest producer of fruits and vegetables in the world, producing mango, banana, guava, papaya, sapota, pomegranate, and lime. Bananas are a popular fruit because of their inexpensive cost and great nutritional content. It is eaten as a ripe or raw fruit in both fresh and cooked form. Among many commercial varieties of banana, Nendran is very unique as it is the only variety that is consumed in many forms and at different stages of ripening. Major production and marketing in Tamilnadu and Kerala. This research work provides one of the most efficient ways for grading banana fruit using deep learning models like EfficientNetB7 and NasNetLarge, on a banana dataset with an accuracy of 97% and 95%, respectively.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"20 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120920866","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}

{"title":"Variant Mode Data Analytics in Predicting the Radiation Effect on Solar Power Generation using Machine Learning Algorithms","authors":"B. Kalaiselvi, B. Karthik, A. Kumaravel","doi":"10.1109/ICDSIS55133.2022.9915814","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915814","url":null,"abstract":"Power harvesting using solar power is the recent trend and innovations happening in deploying many types of equipment working with solar power. This is harmless and greatly reduces pollution and is eco-friendly. The government also provides more concessions for establishing these solar power harvesting methods. There are two subsystems in solar power generation like sensor management systems. The subsystems have to be managed by predicting the power generation and identifying the right time for panel cleaning, and maintenance. In solar power generation systems, it is necessary to identify the faulty equipment and replace it for robust power generation. In the proposed article we are predicting the effect of ambient temperature, and module temperature on radiation of the solar power generation system using the Weka machine learning tool using algorithms like SMOreg, Linear regression, KNN, and Multilayer Perceptron. The prediction model predicts the solar power radiation with Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of 0.0294 and 0.0558 of the Ambient and module temperature respectively. The prediction of radiation in the solar power plant will be helpful in grid maintenance, efficient use of accessories, identifying and servicing the sub-optimally performing unit to increase the daily yield, and reducing the operational cost.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"13 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":"123842176","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}

{"title":"An Overview on Detemining Fish Population using Image and Acoustic Approaches","authors":"B. B. Rao, J. Keerthana, C. Raghavendra, Kushi Sarangamath, Mallikarjuna","doi":"10.1109/ICDSIS55133.2022.9915953","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915953","url":null,"abstract":"India is indeed the world’s third largest producer of fish, with the aquaculture sector accounting for roughly 68 percent of the country’s total fish production. Aquaculture accounts for 1.07 percent of the country’s GDP. By 2025, India is anticipated to require 1.6 crore tonnes of fisheries. However, due to abrupt regional climatic conditions, aquatic productivity has reduced in recent situations. In intensive aquaculture, the quantity of fish in a shoal can provide useful information for the design of smart manufacturing management systems. Traditional artificial sampling and manual testing of aquatic life are not only difficult, arduous, and time - intensive, but they also put strain on the fish because it is a disruptive contact method that impacts fish well-being and health. This study reports on a review of an automatic fish counting system based on appropriate and dependable technology that can assist farmers in real-time, reliable and lossless fish population counts to address the aforementioned difficulties.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"351 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":"122649062","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}

{"title":"Visualization of Water Distribution System in Vijayawada City using Real Time Geospatial Data","authors":"Afrose Mohammad, Kavya Sharmila, C. Sravani, S. Vasavi, A. Rao","doi":"10.1109/ICDSIS55133.2022.9915925","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915925","url":null,"abstract":"Water supply system in India has never been a soft copy till now, we don’t even have the hard copy of the complete water supply system of a village, mandal, district or state combined in our hands. Hence, many are facing losses due to lack of clarity and sharing of information between departments. For example, during construction of a road, a water pipeline is broken accidentally as they do not have the map of water supply system, so the money of our people is being wasted by this. To avoid these problems, a map of water supply system with exact longitude and latitude is needed to be constructed. The solution to construct this map is our mobile application. The first task is to focus on getting the input data regarding the locations and properties of various water objects from major Overhead Tanks to minor locks and the pipelines as well. The second task focuses on getting the data represented on a map.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"56 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":"131621952","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}

{"title":"Categorization and Grading of Spices Using Deep Learning","authors":"S. Jana, P. Shanmukha Nagasai, K. Saravan Kumar, V. Mani Nageshwar","doi":"10.1109/ICDSIS55133.2022.9915893","DOIUrl":"https://doi.org/10.1109/ICDSIS55133.2022.9915893","url":null,"abstract":"Detection of spices from images and recognition based on image processing is a popular research topic. Food is the most vital aspect of human life. Every food consumed on a daily basis contains a variety of spices that make it delicious and flavorful. People are especially concerned about their health. The spices used in meals play a vital role in the prevention of dietary, obesity, and other such issues. The aim of this project is to create an automatic system for detecting and recognising Indian spices on different images, so that dieticians may properly analyze nutrition and other types of health dangers. Color and texture data were primarily used in the recognition method for a better categorization outcome. This approach has been evaluated on a variety of spices. The different spices were classified using a Convolution Neural Network (CNN). The proposed system involves the CNN model for categorization. The spices dataset is generated by collecting images from the internet and creating more images for training by using data augmentation for 4 categories. The spices images contain 640 as training data and another 128 images taken separately for testing data. For obtaining an optimum model with increased classification accuracy different combinations of number of hidden layers and epochs are analyzed. The overall network performance losses for various cases are also observed. Experimental results produced the best test accuracy of 91.14% and the best training accuracy of 97.19%.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"35 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":"132545425","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}