Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India最新文献

{"title":"Investigation and Characterization of Soil for River Bank Filtration System","authors":"H. Kumar, N. Patil, S. Sangami","doi":"10.4108/EAI.16-5-2020.2304100","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2304100","url":null,"abstract":". Soil study has been done to check soil suitability for River Bank Filtration (RBF). A Somlapura village on the bank of Tungabhadra River is selected as study site. In study site 3 different soil samples were collected from 3 different locations to understand the characteristics of soils at a river bank (i.e. Soil texture and permeability). The report of grain size analysis of these 3 samples showed that the soil consists of gravel and sand, which are porous in nature. The permeability test results of soil samples 1, 2, and 3are 1.16×10-3cm/sec, 7.67×10-3cm/sec, and 3.87×10-3cm/sec respectively. The maximum permeability of soil sample 2 at site 1 is 7.67×10-3 cm/sec. The soil which has the maximum permeability is more likely to be suitable for the River Bank Filtration ap-plication.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"252 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122459513","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":"Analysis, Prediction and Maintenance of Teaching learning process by Empathize Students’ View","authors":"V. Ganesan, M. Kumar, Govi Govindarajan, Prof. Naren.J, yellamma pachipala","doi":"10.4108/EAI.16-5-2020.2304192","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2304192","url":null,"abstract":". Learning models have been widely used in predicting diseases, disorders, behaviour aspects in human beings etc. The current research gives an analytical study on predicting University students’ behaviour with various Machine Learning approaches. Research shows that Machine Learning approaches outwit the strategies especially in Student behaviour analysis. An analytical study on various learning approaches and its application in Behaviour Analysis is vividly presented in the paper. The study would give an understanding on how various learning approaches could be applied in Student Behaviour Analysis that includes academic performance, behavioural study with reference to courses, Online teaching modes etc. The paper also encompasses comparison with various Machine Learning approaches in student behavioural prediction.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120998198","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":"Stock Trend Prediction using Deep Neural Networks in Time Series and Social Sentiment Analysis","authors":"Dr. P. Ravichandran, Dr. J. Dafni Rose, K. Vijayakumar","doi":"10.4108/EAI.16-5-2020.2304210","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2304210","url":null,"abstract":"In this paper, we propose an approach towards predicting the trend of stock price values by analyzing the relevant words occurring in social media like Twitter and by performing a time series analysis of the performance of the stock over the years. We obtain training data and train them separately against normalized values of stock prices themselves using neural networks and obtain the desired results by using the outputs of these separate approaches as the training data for another separate neural network that predicts the trend in the stock’s future pricing along with the values with a certain degree of accuracy.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125723457","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":"Spectrum Sensing in Cognitive Radio using Energy Detection: Comprehensive Analysis","authors":"M. Chaitra, Somnath Sinha","doi":"10.4108/EAI.16-5-2020.2303966","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2303966","url":null,"abstract":"Cognitive radio networks manage spectrum effectively by capability of the usage of correct spectrum management techniques. This is taken in accordance on conformity allowing an unlicensed to use the spectrum channel properly by utilization of the underutilized spectrum. Spectrum sensing determines an agreement of a spectrum hole exists by the imitation of the truth of the unlicensed user. This paper analyse all the important spectrum sensing techniques such as, energy detection, minimum Eigen value detection and matched filter technique and describes the affectivity of the methods. It also represents the energy detection based spectrum sensing and represent their limits and efficiencies. Also the affectvity of additive white guassian method is tested against the noise using number of primary and secondary users.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134571544","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":"Audio Codec Using Legendre Functions for Simplified Digital Telephony","authors":"S. Ananthi, A. Arun, Sivakannan Subramani, K. Padmanabhan","doi":"10.4108/EAI.16-5-2020.2304205","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2304205","url":null,"abstract":". Speech signal is based on the more complex anatomy of the mouth, throat, and nasal bone. Such speech signals are controlled by digital signal processing for encoding and by compressing the same speech. Many speech signal processing methods and standards have been developed by many researchers for audio codec’s such as CELP. Advanced mathematical transformations such as Fourier, Lagrange, Hamilton, Legendre were developed for such applications. Signal processing using its equations through certain algorithms and methods to develop signals for various novel applications. Based on laryngeal pulses and oral cavity filter patterns, these techniques can be used to encode speech patterns more efficiently without losing signal clarity. In this paper a novel method of encoding speech with much simpler computations has been evolved. The famous spherical harmonic Legendre polynomials have been the key to the technique. Good compression, decent sound quality and above all, simplicity are the claimed advantages of the method. A new approach, using the spherical harmonic oscillator functions of Legendre is introduced here for this application. Thus, this paper describes this alternate scheme for speech compression and coding. Its usefulness lies in the simplicity relative to the more involved CELP techniques currently in use.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128086481","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":"Investigation of Grid Connected PV System with Electrial Appliances, Electric Vehicles and Battery Systems using PVsol Software","authors":"M. Pushpavalli, P. Abirami, P. Sivagami, V. Geetha","doi":"10.4108/EAI.16-5-2020.2304108","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2304108","url":null,"abstract":". Three different Modules areas considered for PV panels which is connected to grid, Electric appliances, Electric Vehicles and battery system in turn analyzed using PV sol simulation. The Main Objective of this paper is before implementing the PV panel in real time, examine the overview set-up of the system i.e. Module areas of the PV panel with different tracking methods along with Climate data for the particular location. This is Further investigated with number of PV modules needed for the required output. The overall system identified with the total number of inverters and battery systems. This system also analyzes the energy forecasting over a period of year and utilized for battery charging, Electric Vehicle Charging, Grid feeding and consumption for appliances. The system not only focus the technical aspects but also the emission of CO2 avoided, Financial analysis like investment costs and return on assets.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129193868","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":"Implementation of Intelligent Control Technique for Fly Back Converter Based Photovoltaic System","authors":"P. Sivagami, Sangramjith Mukherjee, S. Chakraborty, M. Pushpavalli, P. Abirami","doi":"10.4108/EAI.16-5-2020.2304190","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2304190","url":null,"abstract":"In this technological era the need for power increases rapidly and in order to meet the demand of power requirement of the population, voltage harnessed from various renewable energy sources has to be controlled. In order to increase and maintain stable output voltage many strategies are evolved with the help of many theories and approaches. But on increasing voltage, it leads to fluctuation and ripples at the output during the operation thereby increasing the cost of every equipment as well as maintenance. One of the non-conventional free sources available in abundant SOLAR is gaining popularity not only because of nondepleting nature but it is pollution free, clean green energy source. It helps in harnessing maximum energy by converting the light available into useful energy. For Photo voltaic (PV), the converter proposed is a modification of the existing boost converter with Fly back converter. It is like boost converter but has an additional advantage of isolation. The proffered model implemented with the intelligent control MPPT technique, in which the response time taken by the controller is faster. The controller helps in harnessing the maximum energy though influenced by the environmental factors. It uses a two-stage H-bridge inverter which is an open-loop circuit that converts the DC output of the converter into AC. Thus, the voltage harnessed from the model has waveform which is sinusoidal in nature with minimized harmonics which are obtained by using LC filters and are finally fed to the load. The approaches using boost converter has made satisfactory results in the past few decades but with recent theories, fly back converter can now be proved as a better way This approach thereby leads to a cost-effective technique of voltage boosting for high voltage applications. Experimental result obtained using hardware setup validates the proffered model.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124506392","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":"Save Here: Emergency Response Application","authors":"S. Rai, Hemangi Taraviya, D. Pawade, A. Dalvi, Irfan A. Siddavatam","doi":"10.4108/EAI.16-5-2020.2303954","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2303954","url":null,"abstract":". The current ratio of medical emergency services available in India is very limited in comparison to the actual population of our country India. Due to this, nearly 27% of the total deaths in India happen because of the absence of medical attention at the time of medical emergency. In this paper, we have proposed an application which provides quick medical emergency assistance for a patient, based on the patient’s real time location. The allocation of the closest Ambulance driver/Save Here Members and closest Hospital for the patient is also done based on the real time location of the patient, ambulance and Save Here Members. With just a click of a button present on our application, the patient can place a request for medical emergency assistance and then the allocated nearest Ambulance driver / Save Here Member would be notified about the patient’s details and location. The allocated Ambulance/Save Here Member providing medical emergency assistance to the patient, is shown the shortest route to the patients pick up location and then to the closest hospital with the help of our application.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123980903","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":"Comparative Analysis of Skyline Query Execution using Imputation Techniques on Partially Complete Data","authors":"S. Kanmani, E. Kirubakaran, E. Rajsingh","doi":"10.4108/EAI.16-5-2020.2303973","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2303973","url":null,"abstract":". In this era, the Database community depends on preference queries to satisfy user needs according to their given preferences. Skyline query is one of the preference-based queries. The skyline proceeds with contradictory preferences given by the user. Skyline query derived from the maximum vector problem which deals with Pareto dominance. Skyline query always leads to promising results in the complete data environment. Due to the dynamic data setup, this leads to unknown values or noisy data in the database. This type of data leads partially complete data environment and this affects the performance of skyline queries. This paper gives an analysis of complete and partially complete data using skyline queries with imputation techniques. Two different imputation techniques are used namely Random forest and Amelia to execute the Skyline query on partially complete data. The experimental study gives the solemnity of partially complete data using the skyline query and its influence on the result of the query.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125258285","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":"Comprehensive Analysis of Classifier to Identify Sentiment in Football Specific Tweets","authors":"Venkatesh U Venkatesh, C. Keerthi, Y. Nagaraj, S. Swetha","doi":"10.4108/EAI.16-5-2020.2304099","DOIUrl":"https://doi.org/10.4108/EAI.16-5-2020.2304099","url":null,"abstract":"The football fans' feelings get unfold during the different phases of the football match and they express their emotions, stance on Twitter. This research work focuses on identifying the stance expressed by the fans on Twitter. The changes in fans' opinions are reflected in a series of tweets written by fans. In this paper, various classification algorithms are used to analyze and categorize sentiments present in tweets posted during the 2018 FIFA World Cup. In this work, a football-specific dataset is created and labeled manually. From the dataset, a lexicon related to football-specific sentiment is created. We use domain-specific lexicons, the TF-IDF feature selection method, Count Vectorizer, and various sentiment classifiers to identify the sentiment expressed by football fans on Twitter. In this paper, the performance of different classifier algorithms is analyzed while determining the hidden sentiment. Our experiment results demonstrate that the Random Forest algorithm exhibits consistent and robust performance compared to other classifiers","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129343167","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}