In this report, address the problem of sentiment classi�cation on twitter dataset. used a number of machine learning and deep learning methods to perform sentiment analysis. In the end, used a majority vote ensemble method with 5 of our best models to achieve the classi�cation accuracy of 83.58% on kaggle public leaderboard.
{"title":"TWITTER SENTIMENT ANALYSIS","authors":"Vedurumudi Priyanka, June","doi":"10.26634/jcom.8.4.18269","DOIUrl":"https://doi.org/10.26634/jcom.8.4.18269","url":null,"abstract":"In this report, address the problem of sentiment classi�cation on twitter dataset. used a number of machine learning and deep learning methods to perform sentiment analysis. In the end, used a majority vote ensemble method with 5 of our best models to achieve the classi�cation accuracy of 83.58% on kaggle public leaderboard.","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120953615","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 : 1900-01-01DOI: 10.26634/jcom.10.3.19183
Kumar Vishwakarma Vijay, P. Narayan
This paper offers a concise analysis of the strategies currently in use for stock price prediction by retail investors. The price may increase or decrease according to the quarterly results, financial news flow, technical behavior, or market sentiment resulting from recent developments worldwide. This paper discussed the accuracy of many proposed approaches and methodologies for predicting stock price movement. The Support Vector Machine (SVM) is the foundation of the approaches, with additional parameters and variables.
{"title":"SVM-Based Stock Market Price Prediction Methods: An Advanced Review","authors":"Kumar Vishwakarma Vijay, P. Narayan","doi":"10.26634/jcom.10.3.19183","DOIUrl":"https://doi.org/10.26634/jcom.10.3.19183","url":null,"abstract":"This paper offers a concise analysis of the strategies currently in use for stock price prediction by retail investors. The price may increase or decrease according to the quarterly results, financial news flow, technical behavior, or market sentiment resulting from recent developments worldwide. This paper discussed the accuracy of many proposed approaches and methodologies for predicting stock price movement. The Support Vector Machine (SVM) is the foundation of the approaches, with additional parameters and variables.","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122662615","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 : 1900-01-01DOI: 10.26634/jcom.10.3.19111
S. Sharma, P. Malakar
Due to the Corona Virus Diseases (COVID-19) pandemic, education is completely dependent on digital platforms, so recent advances in technology have made a tremendous amount of video content available. Due to the huge amount of video content, content-based information retrieval has become more and more important. Video content retrieval, just like information retrieval, requires some pre-processing such as indexing, key frame selection, and, most importantly, accurate detection of video shots. This gives the way for video information to be stored in a manner that will allow easy access. Video processing plays a vital role in many large applications. The applications required to perform the various manipulations on video streams (as on frames or say shots). The high definition of video can take a lot of memory to store, so compression techniques are huge in demand. Also, object tracking or object identification is an area where much considerable research has taken place and it is in progress.
{"title":"Techniques for Detecting Video Shot Boundaries: A Review","authors":"S. Sharma, P. Malakar","doi":"10.26634/jcom.10.3.19111","DOIUrl":"https://doi.org/10.26634/jcom.10.3.19111","url":null,"abstract":"Due to the Corona Virus Diseases (COVID-19) pandemic, education is completely dependent on digital platforms, so recent advances in technology have made a tremendous amount of video content available. Due to the huge amount of video content, content-based information retrieval has become more and more important. Video content retrieval, just like information retrieval, requires some pre-processing such as indexing, key frame selection, and, most importantly, accurate detection of video shots. This gives the way for video information to be stored in a manner that will allow easy access. Video processing plays a vital role in many large applications. The applications required to perform the various manipulations on video streams (as on frames or say shots). The high definition of video can take a lot of memory to store, so compression techniques are huge in demand. Also, object tracking or object identification is an area where much considerable research has taken place and it is in progress.","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129875943","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":"SWITCHING AMONG DIFFERENT CLUSTER\u0000SIZES USING 'C' LANGUAGE","authors":"P. Rajesh","doi":"10.26634/jcom.9.2.14594","DOIUrl":"https://doi.org/10.26634/jcom.9.2.14594","url":null,"abstract":"","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129645606","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":"HYBRID CRYPTOSYSTEM USING HOMOMORPHIC ENCRYPTION\u0000 AND ELLIPTIC CURVE CRYPTOGRAPHY ALGORITHM","authors":"S. Prabakeran, K. Hemanth, T. Arvind, N. Bharath","doi":"10.26634/jcom.7.1.15667","DOIUrl":"https://doi.org/10.26634/jcom.7.1.15667","url":null,"abstract":"","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121578856","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 : 1900-01-01DOI: 10.26634/jcom.10.4.19273
Senthilkumar S. Poorana, B. Subramani
In the digital age, people may not be able to live without smart devices because they easily adopt them. IoT has made smart devices possible, which consist of sensors, connectivity, the cloud, and user interfaces. IoT research places sensors at the forefront of smart devices. IoT sensors are efficiently used in different IoT applications to develop smart environments in all fields. These sensors act like human sensing organs that collect real-time information from physical objects or the environment and convert it into electronic signals for processing in the IoT. Normally, two types of networks are applied in IoT: long-range low-power wide area networks and short-range networks. This review aims to assist researchers in understanding IoT applications and protocol classifications using short-range and long-range wireless technology that can communicate wirelessly within regions that facilitate IoT communication from a minimum distance of one millimeter to a few kilometers. This paper presents the types of sensors and various applications of IoT, as well as the energy requirements of different protocols and applications. Each network type has its own unique characteristics regarding energy consumption in the IoT network.
{"title":"Internet of things in low-power wide area network and short range network: A review","authors":"Senthilkumar S. Poorana, B. Subramani","doi":"10.26634/jcom.10.4.19273","DOIUrl":"https://doi.org/10.26634/jcom.10.4.19273","url":null,"abstract":"In the digital age, people may not be able to live without smart devices because they easily adopt them. IoT has made smart devices possible, which consist of sensors, connectivity, the cloud, and user interfaces. IoT research places sensors at the forefront of smart devices. IoT sensors are efficiently used in different IoT applications to develop smart environments in all fields. These sensors act like human sensing organs that collect real-time information from physical objects or the environment and convert it into electronic signals for processing in the IoT. Normally, two types of networks are applied in IoT: long-range low-power wide area networks and short-range networks. This review aims to assist researchers in understanding IoT applications and protocol classifications using short-range and long-range wireless technology that can communicate wirelessly within regions that facilitate IoT communication from a minimum distance of one millimeter to a few kilometers. This paper presents the types of sensors and various applications of IoT, as well as the energy requirements of different protocols and applications. Each network type has its own unique characteristics regarding energy consumption in the IoT network.","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114750821","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":"ON THE USE OF EXTREME LEARNING MACHINES FOR\u0000 DETECTING ANOMALIES IN STUDENTS' RESULTS","authors":"O. Hamza, O. Mohammed","doi":"10.26634/jcom.6.4.15724","DOIUrl":"https://doi.org/10.26634/jcom.6.4.15724","url":null,"abstract":"","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121947788","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}
R. Hemalatha, K. Pooja, P. Gayathri, K. SelvaBhuvaneswari, Kancheepuram Tamil Nadu India. Ucek
{"title":"ANALYSIS OF HARDWARE CRYPTOGRAPHY FOR SECURING INSTANT MESSAGING APPLICATIONS","authors":"R. Hemalatha, K. Pooja, P. Gayathri, K. SelvaBhuvaneswari, Kancheepuram Tamil Nadu India. Ucek","doi":"10.26634/jcom.8.4.18082","DOIUrl":"https://doi.org/10.26634/jcom.8.4.18082","url":null,"abstract":"","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133792350","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 : 1900-01-01DOI: 10.26634/jcom.10.4.19313
Ch. Swapnapriya, G. Josemoses, K. V. Ramana
Perceiving and interpreting color phenomena is a complex process for the human brain. Obtaining the true color of an object requires different experimental, physical, and theoretical results. By examining image features, color, and other aspects, individuals can study techniques for applying full-color images. In this context, color chemistry has been used in crime investigations to detect the time of death. It can be challenging for police to physically examine decomposed dead bodies, especially if they have been unknown for days, weeks, or even months. This makes the task much harder for law enforcement officials. An innovative approach has been developed to assist the police in investigating cases more efficiently. This approach enables them to solve crimes from the convenience of their offices, thereby enhancing their productivity.
{"title":"Colorization of images using soft colour capsule networks","authors":"Ch. Swapnapriya, G. Josemoses, K. V. Ramana","doi":"10.26634/jcom.10.4.19313","DOIUrl":"https://doi.org/10.26634/jcom.10.4.19313","url":null,"abstract":"Perceiving and interpreting color phenomena is a complex process for the human brain. Obtaining the true color of an object requires different experimental, physical, and theoretical results. By examining image features, color, and other aspects, individuals can study techniques for applying full-color images. In this context, color chemistry has been used in crime investigations to detect the time of death. It can be challenging for police to physically examine decomposed dead bodies, especially if they have been unknown for days, weeks, or even months. This makes the task much harder for law enforcement officials. An innovative approach has been developed to assist the police in investigating cases more efficiently. This approach enables them to solve crimes from the convenience of their offices, thereby enhancing their productivity.","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115578266","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 : 1900-01-01DOI: 10.26634/jcom.10.4.19307
Savad N. Muhammad, K. H. Hasna
The objective of the paper is to mitigate internet negativity by identifying and blocking toxic comments related to a particular topic or product. The detrimental effects of social media abuse and harassment can cause people to refrain from expressing themselves. Although some platforms disable user comments altogether, this method is not efficient. The presence of toxicity in comments can assist platforms in taking appropriate measures. The paper aims to classify comments according to their toxicity levels for future blockage. The dataset comprises comments classified into six types, toxic, severe toxic, threat, obscene, identity hate, and insult. Multiple classification techniques will be employed to determine the most accurate one for the data. The authors will employ four types of classification and select the most precise one for each dataset. This methodology enables the authors to choose various datasets for the problem and select the most accurate classifier for each dataset.
{"title":"Toxic comment classifier on social media platform","authors":"Savad N. Muhammad, K. H. Hasna","doi":"10.26634/jcom.10.4.19307","DOIUrl":"https://doi.org/10.26634/jcom.10.4.19307","url":null,"abstract":"The objective of the paper is to mitigate internet negativity by identifying and blocking toxic comments related to a particular topic or product. The detrimental effects of social media abuse and harassment can cause people to refrain from expressing themselves. Although some platforms disable user comments altogether, this method is not efficient. The presence of toxicity in comments can assist platforms in taking appropriate measures. The paper aims to classify comments according to their toxicity levels for future blockage. The dataset comprises comments classified into six types, toxic, severe toxic, threat, obscene, identity hate, and insult. Multiple classification techniques will be employed to determine the most accurate one for the data. The authors will employ four types of classification and select the most precise one for each dataset. This methodology enables the authors to choose various datasets for the problem and select the most accurate classifier for each dataset.","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"321 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116346162","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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