Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741413
Annet John, Anice John, Reshma Sheik
Sentiment analysis refers to the study of attitudes or opinions. Sentiment mining is the drawing out of polarity of text, its features and the time at which the attitude was conveyed. Lexicon dependent techniques involve drawing out of polarities of term from the lexicon and aggravation of the obtained scores to determine the comprehensive sentiment of textual data. Lexicon based approaches plays vital role with respect to the large coverage of terms. The unsupervised machine learning methods rarely takes into account the appearance of emoticons, modifiers, negation terms, general purpose lexicon and domain specific lexicon while analyzing the polarity of text. In this paper, the lexicon based approaches plays an active role regarding the aforementioned aspects. Here we focus on handling of contextual polarity of text wherein which the prior polarity of the term expressed in the lexicon may be different from the polarity expressed in the text. Experimental results give evidence in the performance improvement of the proposed system in terms of accuracy, recall and precision when compared with the existing systems.
{"title":"Context Deployed Sentiment Analysis Using Hybrid Lexicon","authors":"Annet John, Anice John, Reshma Sheik","doi":"10.1109/ICIICT1.2019.8741413","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741413","url":null,"abstract":"Sentiment analysis refers to the study of attitudes or opinions. Sentiment mining is the drawing out of polarity of text, its features and the time at which the attitude was conveyed. Lexicon dependent techniques involve drawing out of polarities of term from the lexicon and aggravation of the obtained scores to determine the comprehensive sentiment of textual data. Lexicon based approaches plays vital role with respect to the large coverage of terms. The unsupervised machine learning methods rarely takes into account the appearance of emoticons, modifiers, negation terms, general purpose lexicon and domain specific lexicon while analyzing the polarity of text. In this paper, the lexicon based approaches plays an active role regarding the aforementioned aspects. Here we focus on handling of contextual polarity of text wherein which the prior polarity of the term expressed in the lexicon may be different from the polarity expressed in the text. Experimental results give evidence in the performance improvement of the proposed system in terms of accuracy, recall and precision when compared with the existing systems.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131571614","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 : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741355
A. K, S. UMADEVI YASODHEI
In recent days, as in repeatedly we notice that the ashbins are located at various places of the cities in which it is abundant because of addition within the waste on a daily basis. In this proposed project system there are several ashbins situated throughout the town or field, these ashbins are handled with least cost device which helps in monitoring the level of garbage bins Associate in Nursing an distinctive ID are provided for each ashbins so it's straightforward to spot that ashbins is full. When the sensor is placed over on the top of ashbins lid, it will maintain some weight age level as the threshold range; if the level reaches it will send the ashbins status to the centralized server based on the distinctive id. The details are collected from the server and the android application is developed to view those details and location, ashbins status are shown in the app with the help of GSM and GPS module.
{"title":"Multiview Garbage Collection Estimation Using IOT","authors":"A. K, S. UMADEVI YASODHEI","doi":"10.1109/ICIICT1.2019.8741355","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741355","url":null,"abstract":"In recent days, as in repeatedly we notice that the ashbins are located at various places of the cities in which it is abundant because of addition within the waste on a daily basis. In this proposed project system there are several ashbins situated throughout the town or field, these ashbins are handled with least cost device which helps in monitoring the level of garbage bins Associate in Nursing an distinctive ID are provided for each ashbins so it's straightforward to spot that ashbins is full. When the sensor is placed over on the top of ashbins lid, it will maintain some weight age level as the threshold range; if the level reaches it will send the ashbins status to the centralized server based on the distinctive id. The details are collected from the server and the android application is developed to view those details and location, ashbins status are shown in the app with the help of GSM and GPS module.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134176354","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 : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741360
R. B. Dhumale, N. D. Thombare, P. M. Bangare
The activities of computers with Artificial Intelligence are intended for Speech recognition, Learning, Planning, Problem solving, etc. Machine Learning is a division/subset of AI. Deep learning is a part of AI that is concerned with coping the learning approach to facilitate human beings applies to gain certain kind of knowledge. This paper presents the idea of Machine Learning. The different methods of learning like supervised learning, unsupervised learning and reinforcement learning are explained with the concepts of regression, classification, clustering and association are given. The terminologies used in machine learning like statistic fit and dimensionality reduction are given with suitable examples.
{"title":"Machine Learning: A Way of Dealing with Artificial Intelligence","authors":"R. B. Dhumale, N. D. Thombare, P. M. Bangare","doi":"10.1109/ICIICT1.2019.8741360","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741360","url":null,"abstract":"The activities of computers with Artificial Intelligence are intended for Speech recognition, Learning, Planning, Problem solving, etc. Machine Learning is a division/subset of AI. Deep learning is a part of AI that is concerned with coping the learning approach to facilitate human beings applies to gain certain kind of knowledge. This paper presents the idea of Machine Learning. The different methods of learning like supervised learning, unsupervised learning and reinforcement learning are explained with the concepts of regression, classification, clustering and association are given. The terminologies used in machine learning like statistic fit and dimensionality reduction are given with suitable examples.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115089629","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 : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741351
Piyush N. Dave, Aditya Amberkar, Lalit Gangurde, U. Chanderki
Call drop rate during Handoff in mobile communication degrade the performance of system. This paper describes a novel approach to increased reliability in mobile communication with reference to rate of change of reverse signal strength. Handoff available scheme which discussed in paper are inefficient to decrease call drop rate due to handoff. Call drop rate depend on channel availability and on rate of decrease of reverse signal strength. Channel availability problem can be solved by increasing frequency range in that particular cell or by dividing cell in to micro cell that’s why there very few effect of call drop rate due to channel availability. Call drop rate is more affect by approach to treat decease in reverse signal strength during handoff. In available approach Handoff decision are taken based on treating handoff call and new call in that particular cell as equal (No Priority) or starting Handoff procedure by monitoring RSS continuously (Delayed Handoff) or providing separate channel for Handoff call and new call (Guard Channel Approach) or Queuing the handoff call and proving channel to handoff call by LIFO manner (Queuing base handoff).
{"title":"A Novel Approach for Queuing based Handoff for Increasing Reliablity of Mobile Communication","authors":"Piyush N. Dave, Aditya Amberkar, Lalit Gangurde, U. Chanderki","doi":"10.1109/ICIICT1.2019.8741351","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741351","url":null,"abstract":"Call drop rate during Handoff in mobile communication degrade the performance of system. This paper describes a novel approach to increased reliability in mobile communication with reference to rate of change of reverse signal strength. Handoff available scheme which discussed in paper are inefficient to decrease call drop rate due to handoff. Call drop rate depend on channel availability and on rate of decrease of reverse signal strength. Channel availability problem can be solved by increasing frequency range in that particular cell or by dividing cell in to micro cell that’s why there very few effect of call drop rate due to channel availability. Call drop rate is more affect by approach to treat decease in reverse signal strength during handoff. In available approach Handoff decision are taken based on treating handoff call and new call in that particular cell as equal (No Priority) or starting Handoff procedure by monitoring RSS continuously (Delayed Handoff) or providing separate channel for Handoff call and new call (Guard Channel Approach) or Queuing the handoff call and proving channel to handoff call by LIFO manner (Queuing base handoff).","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123566387","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 : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741482
R. Ahilapriyadharshini, S. Arivazhagan, E. Francina, S. Supriya
Our country’s economy highly depends on agricultural productivity and thus disease detection plays a major role in agricultural field. The aim of this project is to support the farmers for detecting the type of disease in soybean culture. The idea is to identify whether the leaf is healthy or diseased and if it is affected, finding out the disease and to identify the percentage of infection. The segmentation phase is completed with the help of clustering algorithm and followed by classification using unsupervised learning algorithm. The system is trained using combinations of color and texture features. Using our idea it is possible to identify the soybean disease with 91% accuracy in average.
{"title":"Leaf Disease Detection And Classification System For Soybean Culture","authors":"R. Ahilapriyadharshini, S. Arivazhagan, E. Francina, S. Supriya","doi":"10.1109/ICIICT1.2019.8741482","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741482","url":null,"abstract":"Our country’s economy highly depends on agricultural productivity and thus disease detection plays a major role in agricultural field. The aim of this project is to support the farmers for detecting the type of disease in soybean culture. The idea is to identify whether the leaf is healthy or diseased and if it is affected, finding out the disease and to identify the percentage of infection. The segmentation phase is completed with the help of clustering algorithm and followed by classification using unsupervised learning algorithm. The system is trained using combinations of color and texture features. Using our idea it is possible to identify the soybean disease with 91% accuracy in average.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128442313","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 : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741503
S. Mestry, Hargun Singh, Roshan Chauhan, V. Bisht, Kaushik Tiwari
Social networking and online conversation platforms provide us with the power to share our views and ideas. However, nowadays on social media platforms, many people are taking these platforms for granted, they see it as an opportunity to harass and target others leading to cyber-attack and cyber-bullying which lead to traumatic experiences and suicidal attempts in extreme cases. Manually identifying and classifying such comments is a very long, tiresome and unreliable process. To solve this challenge, we have developed a deep learning system which will identify such negative content on online discussion platforms and successfully classify them into proper labels. Our proposed model aims to apply the text-based Convolution Neural Network (CNN) with word embedding, using fastText word embedding technique. fastText has shown efficient and more accurate results compared to Word2Vec and GLOVE model. Our model aims to improve detecting different types of toxicity to improve the social media experience. Our model classifies such comments in six classes which are Toxic, Severe Toxic, Obscene, Threat, Insult and Identity-hate. Multi-Label Classification helps us to provide an automated solution for dealing with the toxic comments problem we are facing.
{"title":"Automation in Social Networking Comments With the Help of Robust fastText and CNN","authors":"S. Mestry, Hargun Singh, Roshan Chauhan, V. Bisht, Kaushik Tiwari","doi":"10.1109/ICIICT1.2019.8741503","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741503","url":null,"abstract":"Social networking and online conversation platforms provide us with the power to share our views and ideas. However, nowadays on social media platforms, many people are taking these platforms for granted, they see it as an opportunity to harass and target others leading to cyber-attack and cyber-bullying which lead to traumatic experiences and suicidal attempts in extreme cases. Manually identifying and classifying such comments is a very long, tiresome and unreliable process. To solve this challenge, we have developed a deep learning system which will identify such negative content on online discussion platforms and successfully classify them into proper labels. Our proposed model aims to apply the text-based Convolution Neural Network (CNN) with word embedding, using fastText word embedding technique. fastText has shown efficient and more accurate results compared to Word2Vec and GLOVE model. Our model aims to improve detecting different types of toxicity to improve the social media experience. Our model classifies such comments in six classes which are Toxic, Severe Toxic, Obscene, Threat, Insult and Identity-hate. Multi-Label Classification helps us to provide an automated solution for dealing with the toxic comments problem we are facing.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114652992","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 : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741440
Afroos Sahana, Subee Krishna M. P.
A novel converter topology with a high-boost voltage gain for photovoltaic (PV) applications is proposed in this work. An unique converter-inverter drive system is used, where the topology is based on a switched-capacitor based dual switch (SCDS) dc-dc converter and a three phase voltage source inverter (VSI). The typical topology of SCDS converter has properties like high gain, reduced voltage stress and reduced loss on the power devices. The output of the converter system which is fed directly from PV energy, is given to the inverter system in which SPWM control is used. MPPT control is utilized to achieve utmost power output from a photovoltaic module. The validity of the presented system is verified by the MATLAB simulations. An output voltage of 200V is obtained from the SCDS converter for an input voltage of about 25V to 50V and is converted to an ac voltage of about 105V at the load side by the inverter.
{"title":"A Novel Converter for PV Applications","authors":"Afroos Sahana, Subee Krishna M. P.","doi":"10.1109/ICIICT1.2019.8741440","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741440","url":null,"abstract":"A novel converter topology with a high-boost voltage gain for photovoltaic (PV) applications is proposed in this work. An unique converter-inverter drive system is used, where the topology is based on a switched-capacitor based dual switch (SCDS) dc-dc converter and a three phase voltage source inverter (VSI). The typical topology of SCDS converter has properties like high gain, reduced voltage stress and reduced loss on the power devices. The output of the converter system which is fed directly from PV energy, is given to the inverter system in which SPWM control is used. MPPT control is utilized to achieve utmost power output from a photovoltaic module. The validity of the presented system is verified by the MATLAB simulations. An output voltage of 200V is obtained from the SCDS converter for an input voltage of about 25V to 50V and is converted to an ac voltage of about 105V at the load side by the inverter.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122112399","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 : 2019-04-01DOI: 10.1109/iciict1.2019.8741493
{"title":"ICIICT 2019 Author Index","authors":"","doi":"10.1109/iciict1.2019.8741493","DOIUrl":"https://doi.org/10.1109/iciict1.2019.8741493","url":null,"abstract":"","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128151439","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 : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741417
Lalit Gangurde, Aditya Gawande, Shubham Khanvilkar, Akshay Khochare, Piyush N. Dave
In this paper, The results of our project built in SIMULINK Model of an Electric Car’s Drive system. The main objective of this paper was to determine flow of power during the motoring & regeneration conditions in its powertrain. In this simulation, a BLDC motor, basic motor controller, PI controller and standard model of battery is modelled. This results are used to analyse the Powertrain’s flow and its efficiency for predefined Speed and Torque load conditions. The main system parameters and remaining are modelled ideally. The presented model in this paper can be used to represent the energy conversion in Electric Vehicles Powertrain.
{"title":"Modelling and Control of Electric Car Powertrain","authors":"Lalit Gangurde, Aditya Gawande, Shubham Khanvilkar, Akshay Khochare, Piyush N. Dave","doi":"10.1109/ICIICT1.2019.8741417","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741417","url":null,"abstract":"In this paper, The results of our project built in SIMULINK Model of an Electric Car’s Drive system. The main objective of this paper was to determine flow of power during the motoring & regeneration conditions in its powertrain. In this simulation, a BLDC motor, basic motor controller, PI controller and standard model of battery is modelled. This results are used to analyse the Powertrain’s flow and its efficiency for predefined Speed and Torque load conditions. The main system parameters and remaining are modelled ideally. The presented model in this paper can be used to represent the energy conversion in Electric Vehicles Powertrain.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128206011","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 : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741461
Priyanka Shakya, A. B. Bazil Raj
Inverse Synthetic Aperture Radar (ISAR) imaging techniques are used to estimate the target spatial image using target backscatter data. In the ISAR measurement environment, the target is often modeled as a collection of point scatterers to take advantage of the Fourier relationship between scatterer location and measured backscatter data. The technique is utilized for imaging a target based on employing scattering mechanism and Fourier Transform (FT). With Processing the backscattered data ISAR image, using the Inverse Fourier Transform (IFT), the target’s range and cross range are formed and imaging is formed accordingly.
{"title":"Inverse Synthetic Aperture Radar Imaging Using Fourier Transform Technique","authors":"Priyanka Shakya, A. B. Bazil Raj","doi":"10.1109/ICIICT1.2019.8741461","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741461","url":null,"abstract":"Inverse Synthetic Aperture Radar (ISAR) imaging techniques are used to estimate the target spatial image using target backscatter data. In the ISAR measurement environment, the target is often modeled as a collection of point scatterers to take advantage of the Fourier relationship between scatterer location and measured backscatter data. The technique is utilized for imaging a target based on employing scattering mechanism and Fourier Transform (FT). With Processing the backscattered data ISAR image, using the Inverse Fourier Transform (IFT), the target’s range and cross range are formed and imaging is formed accordingly.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126963236","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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