Pub Date : 2020-12-16DOI: 10.1109/PuneCon50868.2020.9362442
Ans Maria Kuriakose, Denny Philip Kariyalil, Marymol Augusthy, S. Sarath, Joffie Jacob, N. Antony
Solar Photo voltaic (PV) system’s usage is increasing day by day as a substitute of energy considering about the environmental factors. But at the same time its performance have a huge impact. Due to the uncertainty of solar Photo voltaic (PV) power outputs, an accurate method of predicting the output power is required. Thus, a proper estimation of the solar power must be done. Predicting the solar power will help in optimal planning of PV units in generating or transmission, scheduling of other generators by considering the predicted values etc. This paper deals with a comparison between Machine Learning algorithms on Day-Ahead forecasting of the Solar Photo-voltaic output considering the weather parameters (which include wind speed, humidity, radiance and temperature). Artificial Neural Network, Linear Regression and Support Vector Machine have been considered and a conclusion is drawn based on the results obtained. The objective of the paper is to predict the Solar Power at Amal Jyothi College of Engineering, Kanjirapally, Kottayam. To provide real time values weather station has been used. The daily forecast results will help to improve the forecast accuracy which will eventually help in its proper utilization.
{"title":"Comparison of Artificial Neural Network, Linear Regression and Support Vector Machine for Prediction of Solar PV Power","authors":"Ans Maria Kuriakose, Denny Philip Kariyalil, Marymol Augusthy, S. Sarath, Joffie Jacob, N. Antony","doi":"10.1109/PuneCon50868.2020.9362442","DOIUrl":"https://doi.org/10.1109/PuneCon50868.2020.9362442","url":null,"abstract":"Solar Photo voltaic (PV) system’s usage is increasing day by day as a substitute of energy considering about the environmental factors. But at the same time its performance have a huge impact. Due to the uncertainty of solar Photo voltaic (PV) power outputs, an accurate method of predicting the output power is required. Thus, a proper estimation of the solar power must be done. Predicting the solar power will help in optimal planning of PV units in generating or transmission, scheduling of other generators by considering the predicted values etc. This paper deals with a comparison between Machine Learning algorithms on Day-Ahead forecasting of the Solar Photo-voltaic output considering the weather parameters (which include wind speed, humidity, radiance and temperature). Artificial Neural Network, Linear Regression and Support Vector Machine have been considered and a conclusion is drawn based on the results obtained. The objective of the paper is to predict the Solar Power at Amal Jyothi College of Engineering, Kanjirapally, Kottayam. To provide real time values weather station has been used. The daily forecast results will help to improve the forecast accuracy which will eventually help in its proper utilization.","PeriodicalId":368862,"journal":{"name":"2020 IEEE Pune Section International Conference (PuneCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129825434","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}
Pub Date : 2020-12-16DOI: 10.1109/punecon50868.2020.9362428
{"title":"PuneCon 2020 List of Reviewers","authors":"","doi":"10.1109/punecon50868.2020.9362428","DOIUrl":"https://doi.org/10.1109/punecon50868.2020.9362428","url":null,"abstract":"","PeriodicalId":368862,"journal":{"name":"2020 IEEE Pune Section International Conference (PuneCon)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122673840","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}
Pub Date : 2020-12-16DOI: 10.1109/PuneCon50868.2020.9362384
Yash Khivasara, Yash Khare, Tejas Bhadane
Internet is a supreme one-stop source of information that enables the sharing of news and curated user-content at a rapid, effortless, and in a routine manner. News is a global medium of daily events worldwide, offering absorption of quick information. With ample availability of news content online, these news articles has by-products in information generation in both ways -real and fake news. Considering the context and volume of information shared online, it is challenging to establish authenticity of news. This leads to the immense growth of fake news on various websites, which can lead to serious concerns in society, fading away the correct news content to reach the users creating misconceptions and deceived views of the readers. To ensure the readers have the credibility of the content, we propose a web-based extension enabling them to distinguish from the fake and real news content. The proposed web extension in the paper uses multiple deep learning models. The first is based on our model trained on LSTM, and the other uses OPEN AI’s well-developed AI-generated text classifier GPT-2. The devised web-extension displays both probabilities of news being either AI-generated or written by an individual.
{"title":"Fake News Detection System using Web-Extension","authors":"Yash Khivasara, Yash Khare, Tejas Bhadane","doi":"10.1109/PuneCon50868.2020.9362384","DOIUrl":"https://doi.org/10.1109/PuneCon50868.2020.9362384","url":null,"abstract":"Internet is a supreme one-stop source of information that enables the sharing of news and curated user-content at a rapid, effortless, and in a routine manner. News is a global medium of daily events worldwide, offering absorption of quick information. With ample availability of news content online, these news articles has by-products in information generation in both ways -real and fake news. Considering the context and volume of information shared online, it is challenging to establish authenticity of news. This leads to the immense growth of fake news on various websites, which can lead to serious concerns in society, fading away the correct news content to reach the users creating misconceptions and deceived views of the readers. To ensure the readers have the credibility of the content, we propose a web-based extension enabling them to distinguish from the fake and real news content. The proposed web extension in the paper uses multiple deep learning models. The first is based on our model trained on LSTM, and the other uses OPEN AI’s well-developed AI-generated text classifier GPT-2. The devised web-extension displays both probabilities of news being either AI-generated or written by an individual.","PeriodicalId":368862,"journal":{"name":"2020 IEEE Pune Section International Conference (PuneCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131316908","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}
Pub Date : 2020-12-16DOI: 10.1109/PuneCon50868.2020.9362408
A. Deshmukh, A. Odhekar
A circularly polarized antennas are required to reduce the signal loss resulting due to the multi-path propagation. The modified Ψ-shape microstrip antenna design is reported in the literature which gives axial ratio bandwidth of more than 19% in 5300 MHz frequency range, radiating away from the broadside direction. For the optimized design, resonant modes and the equivalent circuit model are mentioned in the reported paper without a comprehensive study to explain the antenna functioning attributed to effects of each of the modifications made in the Ψ-shape patch on the realized axial ratio bandwidth. Initially in this paper comprehensive study based on resonant mode explanation attributed to each modification is presented. Also paper gives a thorough study which brings out the resonant mode based description for the effects of every modifications made in the modified Ψ-shape geometry starting from the equivalent Eshape geometry. The modifications made in the Ψ-shape patch yields optimization of the resonance frequency and the input impedance at modified TM21 mode which yields circular polarized response. Further simpler design using different length of slots in the Ψ-shape geometry is presented which yields dual band circular polarized response with axial ratio bandwidth of 12.03% centered at 4500 MHz and 5% centered at 6100 MHz. The proposed design is simpler in optimization and can find its applications in the frequency agile systems.
{"title":"Modified Psi-shape Microstrip Antenna For Circularly Polarized Response","authors":"A. Deshmukh, A. Odhekar","doi":"10.1109/PuneCon50868.2020.9362408","DOIUrl":"https://doi.org/10.1109/PuneCon50868.2020.9362408","url":null,"abstract":"A circularly polarized antennas are required to reduce the signal loss resulting due to the multi-path propagation. The modified Ψ-shape microstrip antenna design is reported in the literature which gives axial ratio bandwidth of more than 19% in 5300 MHz frequency range, radiating away from the broadside direction. For the optimized design, resonant modes and the equivalent circuit model are mentioned in the reported paper without a comprehensive study to explain the antenna functioning attributed to effects of each of the modifications made in the Ψ-shape patch on the realized axial ratio bandwidth. Initially in this paper comprehensive study based on resonant mode explanation attributed to each modification is presented. Also paper gives a thorough study which brings out the resonant mode based description for the effects of every modifications made in the modified Ψ-shape geometry starting from the equivalent Eshape geometry. The modifications made in the Ψ-shape patch yields optimization of the resonance frequency and the input impedance at modified TM21 mode which yields circular polarized response. Further simpler design using different length of slots in the Ψ-shape geometry is presented which yields dual band circular polarized response with axial ratio bandwidth of 12.03% centered at 4500 MHz and 5% centered at 6100 MHz. The proposed design is simpler in optimization and can find its applications in the frequency agile systems.","PeriodicalId":368862,"journal":{"name":"2020 IEEE Pune Section International Conference (PuneCon)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125708718","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}
Pub Date : 2020-12-16DOI: 10.1109/PuneCon50868.2020.9362452
Shalini
In this paper, another approach is anticipated for examination of tie-line management of grid connected solar system. Anticipated method depends on the management of power in tie-line. Presented method gives low stress on operation of custom-made topology for control. The working principle of described method is that the grid is developed by the solar system for the distribution of energy and tie-line control is developed with the help of two parameters viz. frequency and power. Usage of a boost converter (BC) for controlling the power of photovoltaic (PV) by Maximum power point technique (MPPT) is presented is presented here. Firstly the PV network is evaluated through simulink for the principle point and then the BC is deployed next to a MPP control device. The Maximum power point technique is accountable for finding the utmost power from the PV and give it, by using BC, to the load which in turn increase the voltage to the desired level. The key factor is to track the utmost point of power of the PV module with the objective to obtain supreme plausible power. Solar cell as well as the BC are designed through SIM power system block.
{"title":"Simulation and Modelling of MPPT based PV System Connected with Boost Converter","authors":"Shalini","doi":"10.1109/PuneCon50868.2020.9362452","DOIUrl":"https://doi.org/10.1109/PuneCon50868.2020.9362452","url":null,"abstract":"In this paper, another approach is anticipated for examination of tie-line management of grid connected solar system. Anticipated method depends on the management of power in tie-line. Presented method gives low stress on operation of custom-made topology for control. The working principle of described method is that the grid is developed by the solar system for the distribution of energy and tie-line control is developed with the help of two parameters viz. frequency and power. Usage of a boost converter (BC) for controlling the power of photovoltaic (PV) by Maximum power point technique (MPPT) is presented is presented here. Firstly the PV network is evaluated through simulink for the principle point and then the BC is deployed next to a MPP control device. The Maximum power point technique is accountable for finding the utmost power from the PV and give it, by using BC, to the load which in turn increase the voltage to the desired level. The key factor is to track the utmost point of power of the PV module with the objective to obtain supreme plausible power. Solar cell as well as the BC are designed through SIM power system block.","PeriodicalId":368862,"journal":{"name":"2020 IEEE Pune Section International Conference (PuneCon)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122502671","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}
Pub Date : 2020-12-16DOI: 10.1109/PuneCon50868.2020.9362444
Vibha Oberoi
VANETs is Ad-Hoc network which is highly dynamic in behaviour and do not have any fixed infrastructure. Due to which it is more prone to insecurity and vulnerability which may arise from within or outside the network. In VANETs, “Routing” plays an important role in implementation of Intelligent Transport System(ITS).So, analysis has been conducted on Reactive Routing Protocol i.e. Ad hoc On-Demand Distance Vector. For network analysis and generation of real time traffic two simulators have been used i.e. Network Simulator-2 and Simulation of Urban MObility. The analysis has been conducted on varying number of vehicle (nodes) i.e. 20,50,100 and has also considered the speed of the vehicles. Enhanced Security to VANETs against Blackhole Attack using Flag Status based Technique (ESVBFST) has been proposed in order to enhance the Quality of service (QoS) Parameters thereby improving the performance of the network. In order to consider the performance of Routing Protocol i.e. AODV with attack and Enhanced Security to VANETs against Blackhole Attack using Flag Status based Technique (ESVBFST) scenario different QoS parameter like throughput,Packet Delivery Ratio,Packet Drop Ratio and Delay has been considered.
{"title":"Enhancement of QoS in Security Algorithm for Blackhole Attack in VANET","authors":"Vibha Oberoi","doi":"10.1109/PuneCon50868.2020.9362444","DOIUrl":"https://doi.org/10.1109/PuneCon50868.2020.9362444","url":null,"abstract":"VANETs is Ad-Hoc network which is highly dynamic in behaviour and do not have any fixed infrastructure. Due to which it is more prone to insecurity and vulnerability which may arise from within or outside the network. In VANETs, “Routing” plays an important role in implementation of Intelligent Transport System(ITS).So, analysis has been conducted on Reactive Routing Protocol i.e. Ad hoc On-Demand Distance Vector. For network analysis and generation of real time traffic two simulators have been used i.e. Network Simulator-2 and Simulation of Urban MObility. The analysis has been conducted on varying number of vehicle (nodes) i.e. 20,50,100 and has also considered the speed of the vehicles. Enhanced Security to VANETs against Blackhole Attack using Flag Status based Technique (ESVBFST) has been proposed in order to enhance the Quality of service (QoS) Parameters thereby improving the performance of the network. In order to consider the performance of Routing Protocol i.e. AODV with attack and Enhanced Security to VANETs against Blackhole Attack using Flag Status based Technique (ESVBFST) scenario different QoS parameter like throughput,Packet Delivery Ratio,Packet Drop Ratio and Delay has been considered.","PeriodicalId":368862,"journal":{"name":"2020 IEEE Pune Section International Conference (PuneCon)","volume":"44 26","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120816282","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}
Pub Date : 2020-12-16DOI: 10.1109/PuneCon50868.2020.9362416
Anupam Das, Mohammad Akour
Technology-enhanced learning provides various communication and information technologies for learning and teaching. The teachers also feel comfortable with the Open Educational Resources repositories that learn the existing learning materials when a new course is developed. Yet, this exists as a non-trivial problem because the learning environments should be flexible for the students to learn on the basis of their situations and characteristics. Hence, the main aim of this paper is to provide personalized dynamic and continuous recommendations for online learning systems. This paper plans to implement the novel recommendation system for online learning using intelligent techniques. The main steps of the proposed model are (a) Data collection, (b) Feature extraction, and (c) classification. Initially, the data are collected locally from the Ekhool learning application. Then the feature extraction techniques, such as t-Distributed Stochastic Neighbour Embedding (t-SNE) and Principle Component Analysis (PCA) are used for selecting the most relevant features. Further, the classifier termed as Fuzzy Logic Classifier is adopted as the recommendation system, where the improvement is made in the membership limits by optimizing it with the Rider Optimization Algorithm (ROA). The superiority of the proposed method is proved by the performance analysis in terms of various performance measures.
{"title":"Intelligent Recommendation System for E-Learning using Membership Optimized Fuzzy Logic Classifier","authors":"Anupam Das, Mohammad Akour","doi":"10.1109/PuneCon50868.2020.9362416","DOIUrl":"https://doi.org/10.1109/PuneCon50868.2020.9362416","url":null,"abstract":"Technology-enhanced learning provides various communication and information technologies for learning and teaching. The teachers also feel comfortable with the Open Educational Resources repositories that learn the existing learning materials when a new course is developed. Yet, this exists as a non-trivial problem because the learning environments should be flexible for the students to learn on the basis of their situations and characteristics. Hence, the main aim of this paper is to provide personalized dynamic and continuous recommendations for online learning systems. This paper plans to implement the novel recommendation system for online learning using intelligent techniques. The main steps of the proposed model are (a) Data collection, (b) Feature extraction, and (c) classification. Initially, the data are collected locally from the Ekhool learning application. Then the feature extraction techniques, such as t-Distributed Stochastic Neighbour Embedding (t-SNE) and Principle Component Analysis (PCA) are used for selecting the most relevant features. Further, the classifier termed as Fuzzy Logic Classifier is adopted as the recommendation system, where the improvement is made in the membership limits by optimizing it with the Rider Optimization Algorithm (ROA). The superiority of the proposed method is proved by the performance analysis in terms of various performance measures.","PeriodicalId":368862,"journal":{"name":"2020 IEEE Pune Section International Conference (PuneCon)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122314052","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}
Pub Date : 2020-12-16DOI: 10.1109/PuneCon50868.2020.9362355
Sanika Gaykar, Nilay Joshi, C. Swami, Saloni Shinde, T. Kharat, M. Chaudhari
The world of electronics, technology and the upcoming Industry 4.0 is set to transform the face of the world’s manufacturing and supply chain industry, but we are running short of the force that runs it-energy. Many have tried to find innovative, regenerative, reproductive and renewable sources of energy. Most succeeded but many failed as well. Generating electricity from rotating shafts of vehicles was one of the most innovative method of energy harvesting, but it didn't work every time. The Indian Railways had installed an alternator on the ICF coaches for self-generation, but it didn't work the same with the new LHB coaches. To find a solution to the bigger problem of energy harvesting and the particular problem of implementation on LHB coaches, this paper talks about a model which can provide them both by the design of a permanent magnet alternator.
{"title":"Permanent Magnet Alternator for Electricity Generation in LHB Railway Coaches","authors":"Sanika Gaykar, Nilay Joshi, C. Swami, Saloni Shinde, T. Kharat, M. Chaudhari","doi":"10.1109/PuneCon50868.2020.9362355","DOIUrl":"https://doi.org/10.1109/PuneCon50868.2020.9362355","url":null,"abstract":"The world of electronics, technology and the upcoming Industry 4.0 is set to transform the face of the world’s manufacturing and supply chain industry, but we are running short of the force that runs it-energy. Many have tried to find innovative, regenerative, reproductive and renewable sources of energy. Most succeeded but many failed as well. Generating electricity from rotating shafts of vehicles was one of the most innovative method of energy harvesting, but it didn't work every time. The Indian Railways had installed an alternator on the ICF coaches for self-generation, but it didn't work the same with the new LHB coaches. To find a solution to the bigger problem of energy harvesting and the particular problem of implementation on LHB coaches, this paper talks about a model which can provide them both by the design of a permanent magnet alternator.","PeriodicalId":368862,"journal":{"name":"2020 IEEE Pune Section International Conference (PuneCon)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133317258","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}
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