Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00033
Hargobind Singh, Amritpal Singh
As we know that Social media has become an important part of today's generation. People try to post their daily routine on social media (Facebook, twitter etc.). Thus, results produced from mining the social media data are very effective in understanding current trends. As we all know these trends are very helpful for different kind of business, launching new products etc. But there is one another field where social media plays a big role that is in understanding social and political dynamic. This proposal paper is based on understanding this political dynamic through mining the social media data and producing trends which can even be used for future plans.
{"title":"Proposed Methodology for Sentiment Analysis of Social Media Data Focusing on the Sentiment Analysis in Political Domain","authors":"Hargobind Singh, Amritpal Singh","doi":"10.1109/ICCS54944.2021.00033","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00033","url":null,"abstract":"As we know that Social media has become an important part of today's generation. People try to post their daily routine on social media (Facebook, twitter etc.). Thus, results produced from mining the social media data are very effective in understanding current trends. As we all know these trends are very helpful for different kind of business, launching new products etc. But there is one another field where social media plays a big role that is in understanding social and political dynamic. This proposal paper is based on understanding this political dynamic through mining the social media data and producing trends which can even be used for future plans.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125469540","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 : 2021-12-01DOI: 10.1109/ICCS54944.2021.00048
Parminder Kaur, Anshu Parashar, Kavisha Duggal, S. Sunita
Blockchain technology, because of its widespread usage in research, and its multifarious and superior properties has also reached the education sector. While most of the work is related to the record-keeping of students' data, the work proposed in this paper is teacher-centric. In this paper, a framework for educators has been created that will facilitate their future employability. A supervisory entity has been established to provide feedback to educators as they carry out various teaching activities. The feedback and performance of educators would be uploaded to the blockchain ledger through a smart contract by the supervisor, who would create a work profile for the prospective employer to access. A token system for reward has also been introduced in the framework. Because blockchain data is immutable, secure, and distributed, this research could give educators, educational institutions, and employers an advantage in managing faculty and employee records.
{"title":"A Blockchain-based Approach for Educators' Profile Management and Reward system","authors":"Parminder Kaur, Anshu Parashar, Kavisha Duggal, S. Sunita","doi":"10.1109/ICCS54944.2021.00048","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00048","url":null,"abstract":"Blockchain technology, because of its widespread usage in research, and its multifarious and superior properties has also reached the education sector. While most of the work is related to the record-keeping of students' data, the work proposed in this paper is teacher-centric. In this paper, a framework for educators has been created that will facilitate their future employability. A supervisory entity has been established to provide feedback to educators as they carry out various teaching activities. The feedback and performance of educators would be uploaded to the blockchain ledger through a smart contract by the supervisor, who would create a work profile for the prospective employer to access. A token system for reward has also been introduced in the framework. Because blockchain data is immutable, secure, and distributed, this research could give educators, educational institutions, and employers an advantage in managing faculty and employee records.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127570627","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 : 2021-12-01DOI: 10.1109/ICCS54944.2021.00018
Jagdeep Singh, Jatinder Warraich, Parminder Singh
Fog Computing has developed as a domain that gives an adequate platform for computing, networking and storage to promote innovative development. The foremost goal of fog computing is to minimize load of different jobs requests on the cloud due to an excessive amount of Internet of Things (IoT) nodes and devices raised within the last decade. The load balancing on the Fog-IoT network environment is an auspicious problem in fog computing frameworks that can reduce latency, energy and bandwidth consumption. In this article, the analysis is done on load balancing techniques implemented by several authors in Fog-IoT computing to discover deficiencies for the further enhancement of overall frameworks. The research gaps and future directions are also addressed, so the researchers can quickly decide the process to do the future investigation.
{"title":"A Survey on Load Balancing Techniques in Fog Computing","authors":"Jagdeep Singh, Jatinder Warraich, Parminder Singh","doi":"10.1109/ICCS54944.2021.00018","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00018","url":null,"abstract":"Fog Computing has developed as a domain that gives an adequate platform for computing, networking and storage to promote innovative development. The foremost goal of fog computing is to minimize load of different jobs requests on the cloud due to an excessive amount of Internet of Things (IoT) nodes and devices raised within the last decade. The load balancing on the Fog-IoT network environment is an auspicious problem in fog computing frameworks that can reduce latency, energy and bandwidth consumption. In this article, the analysis is done on load balancing techniques implemented by several authors in Fog-IoT computing to discover deficiencies for the further enhancement of overall frameworks. The research gaps and future directions are also addressed, so the researchers can quickly decide the process to do the future investigation.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123228712","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}
Machine learning works primarily at teaching computers how to solve issues using data or prior experience. There are already a variety of common machine learning applications. Machine learning can be used in three ways to assess correlations: supervised learning, unattended learning and improved learning. In this analysis, however, the strengths and the drawbacks of the supervised classification algorithms will be emphasized. The primary point of supervised education is to build a concise class brand distribution model with regards to predictor characteristics. When the value of the predictor function is known but the value of the target class is unknown, the resultant coder is used to add class labels to trials. We anticipate that our research will assist new scientists in leading new initiatives and comparing the utility of svms.
{"title":"A Review Paper on A Comparative Study of Supervised Learning Approaches","authors":"Saksham Trivedi, Balwinder Kaur Dhaliwal, Gurpreet Singh","doi":"10.1109/ICCS54944.2021.00027","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00027","url":null,"abstract":"Machine learning works primarily at teaching computers how to solve issues using data or prior experience. There are already a variety of common machine learning applications. Machine learning can be used in three ways to assess correlations: supervised learning, unattended learning and improved learning. In this analysis, however, the strengths and the drawbacks of the supervised classification algorithms will be emphasized. The primary point of supervised education is to build a concise class brand distribution model with regards to predictor characteristics. When the value of the predictor function is known but the value of the target class is unknown, the resultant coder is used to add class labels to trials. We anticipate that our research will assist new scientists in leading new initiatives and comparing the utility of svms.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129306912","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 : 2021-12-01DOI: 10.1109/ICCS54944.2021.00063
Vivek Kumar, Gursharan Singh, Balraj Singh
Data transaction is increasing day by day over internet which is resulting into a great challenge of their security. Data security had been a great matter of concern for which different technique like steganography, cryptography came into picture. These techniques are used to convert the data into unreadable format so that it can be protected from any kind of attack. However, the attackers are also updating themselves. Thus, the combination of various compression techniques has been implemented for higher security. In this paper, a study of various stenographic compression technique and combination of steganography and cryptography methods are reviewed and discussed in detail. The result of the analysis of various ideas helps in proposing a more complex and secure method. We come to a solution that, the combination of Huffman compression technique along with other compression technique and Cryptography is best suited for higher secrecy of data and less distortion in stegno image. Elliptical curve cryptography or public-key cryptography is also proposed for the better encryption of data and secrecy of key as well.
{"title":"A Comparative Study of Various Lossless Compression Techniques of Steganography and Cryptography","authors":"Vivek Kumar, Gursharan Singh, Balraj Singh","doi":"10.1109/ICCS54944.2021.00063","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00063","url":null,"abstract":"Data transaction is increasing day by day over internet which is resulting into a great challenge of their security. Data security had been a great matter of concern for which different technique like steganography, cryptography came into picture. These techniques are used to convert the data into unreadable format so that it can be protected from any kind of attack. However, the attackers are also updating themselves. Thus, the combination of various compression techniques has been implemented for higher security. In this paper, a study of various stenographic compression technique and combination of steganography and cryptography methods are reviewed and discussed in detail. The result of the analysis of various ideas helps in proposing a more complex and secure method. We come to a solution that, the combination of Huffman compression technique along with other compression technique and Cryptography is best suited for higher secrecy of data and less distortion in stegno image. Elliptical curve cryptography or public-key cryptography is also proposed for the better encryption of data and secrecy of key as well.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129483118","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 : 2021-12-01DOI: 10.1109/ICCS54944.2021.00016
A. Ramya, K. Rohini
Datamining is very important in modern world. Collection of many types of data we find (knowledge discovery process) the essential information from hidden things. So, data mining is very important to extract the essential hidden data. Data mining with machine learning algorithmsis effective to mine the essential data and it is very fast-growing technology. Few ML algorithms are compared using BMI based. Obesity is BMI level is equal to 30 or above 30, so this disease is very complex. Obesity will affect the quality of life like depression, lower work achievement, disability. In this paper we applied classification machine learning algorithms like KNN, XGB, Logistic Regression, DT and compared those algorithms in obesity data.
{"title":"Comparative evaluation of machine learning classifiers with Obesity dataset","authors":"A. Ramya, K. Rohini","doi":"10.1109/ICCS54944.2021.00016","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00016","url":null,"abstract":"Datamining is very important in modern world. Collection of many types of data we find (knowledge discovery process) the essential information from hidden things. So, data mining is very important to extract the essential hidden data. Data mining with machine learning algorithmsis effective to mine the essential data and it is very fast-growing technology. Few ML algorithms are compared using BMI based. Obesity is BMI level is equal to 30 or above 30, so this disease is very complex. Obesity will affect the quality of life like depression, lower work achievement, disability. In this paper we applied classification machine learning algorithms like KNN, XGB, Logistic Regression, DT and compared those algorithms in obesity data.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116017105","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 : 2021-12-01DOI: 10.1109/ICCS54944.2021.00053
Sandhya N. Dhage, V. Garg
Weather conditions are affected by climate change due to global warming which ultimately cause the impact on crop production. Change in environmental factors is the cause of occurrence of different diseases of cotton crop results into low cotton yield. Severity of diseases varies according to weekly weather conditions in that region. Hence survey is conducted yearly to record intensity of diseases of cotton plant based on metrological data in north, south and central zone of India by ICAR, India. The main goal and contribution of this paper is to summarize the impact of environmental factors on cotton plant fungal diseases and analyze the correlation of these diseases with different environmental factors. The paper also discuss the CNN based deep learning approach needed for accurate detection of diseases to control the spreading of fungal diseases of cotton plant so that cotton yield loss can be controlled.
{"title":"Analysis of Impact of Environmental Factors on Cotton Plant Diseases and Detection using CNN","authors":"Sandhya N. Dhage, V. Garg","doi":"10.1109/ICCS54944.2021.00053","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00053","url":null,"abstract":"Weather conditions are affected by climate change due to global warming which ultimately cause the impact on crop production. Change in environmental factors is the cause of occurrence of different diseases of cotton crop results into low cotton yield. Severity of diseases varies according to weekly weather conditions in that region. Hence survey is conducted yearly to record intensity of diseases of cotton plant based on metrological data in north, south and central zone of India by ICAR, India. The main goal and contribution of this paper is to summarize the impact of environmental factors on cotton plant fungal diseases and analyze the correlation of these diseases with different environmental factors. The paper also discuss the CNN based deep learning approach needed for accurate detection of diseases to control the spreading of fungal diseases of cotton plant so that cotton yield loss can be controlled.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"35S 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122703105","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 : 2021-12-01DOI: 10.1109/ICCS54944.2021.00058
Vishu Madaan, Subrath Das, Prateek Agrawal, C. Gupta, Dhruv Goel
With the increase in number of sexual harassment cases, there is a need to give quick response to any personal story of a victim. This research work is replacing the manual categorization to automatic analysis of online shared sexual harassment cases. To train a model, machine learning techniques are used on the data available on Safecity. It is a platform that empowers individuals, communities, police and city government to create safer public and private spaces.
{"title":"Fusion of ML models to Identify Sexual Harassment Cases","authors":"Vishu Madaan, Subrath Das, Prateek Agrawal, C. Gupta, Dhruv Goel","doi":"10.1109/ICCS54944.2021.00058","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00058","url":null,"abstract":"With the increase in number of sexual harassment cases, there is a need to give quick response to any personal story of a victim. This research work is replacing the manual categorization to automatic analysis of online shared sexual harassment cases. To train a model, machine learning techniques are used on the data available on Safecity. It is a platform that empowers individuals, communities, police and city government to create safer public and private spaces.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121471738","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 : 2021-12-01DOI: 10.1109/ICCS54944.2021.00012
Komal Mishra, Pooja Sharma
Due to the advancement of technologies, Wireless Sensor Network (WSN) is applied in every field due to its huge advantages. A thousand sensors are connected to provide better quality information based on application. In this proposal, the author examines the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol for efficient information transmission. It is an energy-efficient protocol designed to prolong the lifetime of the network by reduction of energy consumption. The Particle Swarm Optimization Algorithm with Artificial Neural Network is introduced to optimize the LEACH routing protocol, and is used to identify the optimal route under two different scenarios; with Particle Swarm Optimization (PSO) plus Artificial Neural Network (ANN), and without PSO+ANN. The performance of the presented approach is evaluated in terms of comparative analysis of throughput (kbps), Energy Consumption (joules), delay (ms), Packet Delivery Ratio (PDR), and Number of alive nodes. The simulation results evaluation describes that PSO + ANN provides better results as compared to without PSO +ANN approach.
{"title":"Improved Cluster Head Selection Using Particle Swarm Optimization and Neural Network in WSN","authors":"Komal Mishra, Pooja Sharma","doi":"10.1109/ICCS54944.2021.00012","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00012","url":null,"abstract":"Due to the advancement of technologies, Wireless Sensor Network (WSN) is applied in every field due to its huge advantages. A thousand sensors are connected to provide better quality information based on application. In this proposal, the author examines the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol for efficient information transmission. It is an energy-efficient protocol designed to prolong the lifetime of the network by reduction of energy consumption. The Particle Swarm Optimization Algorithm with Artificial Neural Network is introduced to optimize the LEACH routing protocol, and is used to identify the optimal route under two different scenarios; with Particle Swarm Optimization (PSO) plus Artificial Neural Network (ANN), and without PSO+ANN. The performance of the presented approach is evaluated in terms of comparative analysis of throughput (kbps), Energy Consumption (joules), delay (ms), Packet Delivery Ratio (PDR), and Number of alive nodes. The simulation results evaluation describes that PSO + ANN provides better results as compared to without PSO +ANN approach.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131652354","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 : 2021-12-01DOI: 10.1109/ICCS54944.2021.00047
S. Tiwari, Gurbakash Phonsa, Parminder Singh
This paper is a comparative study depicting the difference between our model of a donation website and the websites that are currently functioning in this field. We firstly introduce the technologies used in the model along with their benefits and shortcomings. The donation site model created uses Bootstrap, MaterialUI, Font-awesome for its styling. They can be used by including their import link from their website in their code. Javascript, JSON HTML for its creating its skeletal base. Firebase and its API for database. NodeJS and Npm to manage its packages and dependencies. Then we move towards how this website is different from its counterparts and conclude the paper with what future additions are possible to make it better. All the features can be obtained by using React with other web tools and create an efficient product for any platform without creating multiple applications. Since React can also create mobile applications it helps increase the reach of donation organisations. This is also cheaper and proves efficient for developers who maintain the website. The model created has a lot of potential to grow.
{"title":"Study and Comparative analysis of Donation based websites","authors":"S. Tiwari, Gurbakash Phonsa, Parminder Singh","doi":"10.1109/ICCS54944.2021.00047","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00047","url":null,"abstract":"This paper is a comparative study depicting the difference between our model of a donation website and the websites that are currently functioning in this field. We firstly introduce the technologies used in the model along with their benefits and shortcomings. The donation site model created uses Bootstrap, MaterialUI, Font-awesome for its styling. They can be used by including their import link from their website in their code. Javascript, JSON HTML for its creating its skeletal base. Firebase and its API for database. NodeJS and Npm to manage its packages and dependencies. Then we move towards how this website is different from its counterparts and conclude the paper with what future additions are possible to make it better. All the features can be obtained by using React with other web tools and create an efficient product for any platform without creating multiple applications. Since React can also create mobile applications it helps increase the reach of donation organisations. This is also cheaper and proves efficient for developers who maintain the website. The model created has a lot of potential to grow.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129268030","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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