Pub Date : 2023-01-01DOI: 10.12720/jait.14.1.145-152
P. Gawade, Sarang A. Joshi
For safety decisions in social media applications, it is necessary to classify personification patterns. The paper proposes using video material to apply machine learning to select, and extract significant feature qualities and grasp the semantics of feature space connection to comprehend the personification of a certain user. The feature traits are based on a computer vision-based approach and a natural language-based approach. A strong belief is calculated from language descriptions and persona traits. These traits are then used to determine the overlap of feature space using various ML algorithms to deduce the intrinsic relationships. The proposed goal is validated by this algorithm and user personification is an important aspect that can be captured through video analytics. Using this personification-based method, better decisions can be made in the given domain space.
{"title":"Algorithm for Safety Decisions in Social Media Feeds Using Personification Patterns","authors":"P. Gawade, Sarang A. Joshi","doi":"10.12720/jait.14.1.145-152","DOIUrl":"https://doi.org/10.12720/jait.14.1.145-152","url":null,"abstract":"For safety decisions in social media applications, it is necessary to classify personification patterns. The paper proposes using video material to apply machine learning to select, and extract significant feature qualities and grasp the semantics of feature space connection to comprehend the personification of a certain user. The feature traits are based on a computer vision-based approach and a natural language-based approach. A strong belief is calculated from language descriptions and persona traits. These traits are then used to determine the overlap of feature space using various ML algorithms to deduce the intrinsic relationships. The proposed goal is validated by this algorithm and user personification is an important aspect that can be captured through video analytics. Using this personification-based method, better decisions can be made in the given domain space.","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66329438","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 : 2023-01-01DOI: 10.12720/jait.14.2.257-263
Y. Matanga, Yanxia Sun, Zenghui Wang
—Optimal control is a high-quality and challenging control approach that requires very explorative metaheuristic optimisation techniques to find the most efficient control profile for the performance index function, especially in the case of highly nonlinear dynamic processes. Considering the success of differential evolution in nonlinear optimal control problems, the current research proposes the use of sequential niching differential evolution to boost further the solution accuracy of the solver owing to its globally convergent feature. Also, because sequential niching bans previously discovered solutions, it can propose several competing optimal control profiles relevant for control practitioners. Simulation experiments of the proposed algorithm have been first conducted on IEEE CEC2017/2019 datasets and n-dimensional classical test sets, yielding improved solution accuracy and robust performances on optimal control case studies
{"title":"Nonlinear Optimal Control Using Sequential Niching Differential Evolution and Parallel Workers","authors":"Y. Matanga, Yanxia Sun, Zenghui Wang","doi":"10.12720/jait.14.2.257-263","DOIUrl":"https://doi.org/10.12720/jait.14.2.257-263","url":null,"abstract":"—Optimal control is a high-quality and challenging control approach that requires very explorative metaheuristic optimisation techniques to find the most efficient control profile for the performance index function, especially in the case of highly nonlinear dynamic processes. Considering the success of differential evolution in nonlinear optimal control problems, the current research proposes the use of sequential niching differential evolution to boost further the solution accuracy of the solver owing to its globally convergent feature. Also, because sequential niching bans previously discovered solutions, it can propose several competing optimal control profiles relevant for control practitioners. Simulation experiments of the proposed algorithm have been first conducted on IEEE CEC2017/2019 datasets and n-dimensional classical test sets, yielding improved solution accuracy and robust performances on optimal control case studies","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66330169","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 : 2023-01-01DOI: 10.12720/jait.14.2.311-318
Shahid Akbar, T. Saba, Saeed Ali Omer Bahaj, Muhammad Inshal, Amjad Rehman Khan
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{"title":"Forecasting Volatility in Generalized Autoregressive Conditional Heteroscedastic (GARCH) Model with Outliers","authors":"Shahid Akbar, T. Saba, Saeed Ali Omer Bahaj, Muhammad Inshal, Amjad Rehman Khan","doi":"10.12720/jait.14.2.311-318","DOIUrl":"https://doi.org/10.12720/jait.14.2.311-318","url":null,"abstract":".","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66330266","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 : 2023-01-01DOI: 10.12720/jait.14.2.295-301
A. S. Girsang, Fransisco Junius Amadeus
—The act of simplifying a text from its original source is known as text summarization. Instead of capturing the substance of the original content, an effective summary should be able to convey the information. Recent research on this form of extractive summarization has produced encouraging findings. A graphical model and a modified ant system method will be combined in this literature to provide a solution. The pheromone modification will decide which pertinent phrases will be selected to be a decent summary structure, while the modification process will focus on the point at which the graph construction will be built to represent an article. Additionally, a dataset (Indosum) including news stories that are often utilized in relevant research will be used in accordance to the summary in Indonesian. In addition, the ROUGE approach will be utilized as a tool for evaluation to rate the summary’s quality. Finally, this paper concludes with the challenges and future directions of text summarization.
{"title":"Extractive Text Summarization for Indonesian News Article Using Ant System Algorithm","authors":"A. S. Girsang, Fransisco Junius Amadeus","doi":"10.12720/jait.14.2.295-301","DOIUrl":"https://doi.org/10.12720/jait.14.2.295-301","url":null,"abstract":"—The act of simplifying a text from its original source is known as text summarization. Instead of capturing the substance of the original content, an effective summary should be able to convey the information. Recent research on this form of extractive summarization has produced encouraging findings. A graphical model and a modified ant system method will be combined in this literature to provide a solution. The pheromone modification will decide which pertinent phrases will be selected to be a decent summary structure, while the modification process will focus on the point at which the graph construction will be built to represent an article. Additionally, a dataset (Indosum) including news stories that are often utilized in relevant research will be used in accordance to the summary in Indonesian. In addition, the ROUGE approach will be utilized as a tool for evaluation to rate the summary’s quality. Finally, this paper concludes with the challenges and future directions of text summarization.","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66330443","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 : 2023-01-01DOI: 10.12720/jait.14.3.411-417
Srikanth Bethu, M. Neelakantappa, A. S. Goud, B. H. Krishna, P. Rao M
—The best biometric information processes is a face recognition device, its applicability is simpler and its working range is broader than other methods like fingerprinting, iris scanning and signature. Face Detection is one of the kinds of bio-metric strategies that immediately apply to facial recognition by computerized devices through staring at the facial. It is a common feature used in bio analytics, digital cameras, and social labeling. Main applications of facial recognition algorithms that concentrate on recognition of face include environments, artifacts, and other parts of humans. Face-detection systems uses learning algorithms which are part of machine learning that can be used to identify subject faces inside big size pictures in order to function.
{"title":"An Approach for Person Detection along with Object Using Machine Learning","authors":"Srikanth Bethu, M. Neelakantappa, A. S. Goud, B. H. Krishna, P. Rao M","doi":"10.12720/jait.14.3.411-417","DOIUrl":"https://doi.org/10.12720/jait.14.3.411-417","url":null,"abstract":"—The best biometric information processes is a face recognition device, its applicability is simpler and its working range is broader than other methods like fingerprinting, iris scanning and signature. Face Detection is one of the kinds of bio-metric strategies that immediately apply to facial recognition by computerized devices through staring at the facial. It is a common feature used in bio analytics, digital cameras, and social labeling. Main applications of facial recognition algorithms that concentrate on recognition of face include environments, artifacts, and other parts of humans. Face-detection systems uses learning algorithms which are part of machine learning that can be used to identify subject faces inside big size pictures in order to function.","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66330799","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 : 2023-01-01DOI: 10.12720/jait.14.4.769-776
Nidal Al Said
—The problem under the study of this work is investigating data mining algorithms for intelligent analysis of data written in Arabic. The study comprised instead involves several stages, including Data Collection and Pre-Processing; Data Mining Algorithms (Multinomial Naïve Bayes Classifier, Naïve Bayes Classifier, Support Vector Machine and Modified K-Means); Study Results Processing and Software Implementation. A total of 16,732 Facebook posts written exclusively in Arabic were downloaded. Almost two-thirds of them (namely 11,155 items) were used to train algorithms, while the rest (5577 items) were subject to research. The training data were categorized into five groups based on subjects (politics, entertainment, medicine, science, and religion) with five keywords used for testing in each group. Most posts (4736 items) were related to politics. The most accurate algorithm proved to be the multinomial Naïve Bayesian classifier for the maximum number of test data, while the minimum values of this feature were recorded for the Support vector machine. The effectiveness of the multinomial Naïve Bayesian classifier algorithm was most remarkable for the maximum amount of data, while the Support Vector Machine was most effective for the minimum amount. The argument’s fit score is maximum at 5577 data points for the multinomial Naïve Bayesian classifier and 1394 data points for K-means. To improve and refine the results of data mining, the sample must be expanded, adding more data classes and keywords. Other machine learning models, such as deep learning algorithms, could also be used. The significance of investigation is very important because it expands our knowledge about the use of Machine Learning Algorithms to mine Arabic texts on social media platforms.
{"title":"Data Mining for Managing and Using Online Information on Facebook","authors":"Nidal Al Said","doi":"10.12720/jait.14.4.769-776","DOIUrl":"https://doi.org/10.12720/jait.14.4.769-776","url":null,"abstract":"—The problem under the study of this work is investigating data mining algorithms for intelligent analysis of data written in Arabic. The study comprised instead involves several stages, including Data Collection and Pre-Processing; Data Mining Algorithms (Multinomial Naïve Bayes Classifier, Naïve Bayes Classifier, Support Vector Machine and Modified K-Means); Study Results Processing and Software Implementation. A total of 16,732 Facebook posts written exclusively in Arabic were downloaded. Almost two-thirds of them (namely 11,155 items) were used to train algorithms, while the rest (5577 items) were subject to research. The training data were categorized into five groups based on subjects (politics, entertainment, medicine, science, and religion) with five keywords used for testing in each group. Most posts (4736 items) were related to politics. The most accurate algorithm proved to be the multinomial Naïve Bayesian classifier for the maximum number of test data, while the minimum values of this feature were recorded for the Support vector machine. The effectiveness of the multinomial Naïve Bayesian classifier algorithm was most remarkable for the maximum amount of data, while the Support Vector Machine was most effective for the minimum amount. The argument’s fit score is maximum at 5577 data points for the multinomial Naïve Bayesian classifier and 1394 data points for K-means. To improve and refine the results of data mining, the sample must be expanded, adding more data classes and keywords. Other machine learning models, such as deep learning algorithms, could also be used. The significance of investigation is very important because it expands our knowledge about the use of Machine Learning Algorithms to mine Arabic texts on social media platforms.","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66333539","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 : 2023-01-01DOI: 10.12720/jait.14.3.594-600
J. P. Tomas, Kevin I. Lucero, Christian Jose P. Ajero, Renz Justin V. Thomas
.
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{"title":"Comparative Study on Model Skill of ERT and LSTM in Classifying Proper or Improper Execution of Free Throw, Jump Shot, and Layup Basketball Maneuvers","authors":"J. P. Tomas, Kevin I. Lucero, Christian Jose P. Ajero, Renz Justin V. Thomas","doi":"10.12720/jait.14.3.594-600","DOIUrl":"https://doi.org/10.12720/jait.14.3.594-600","url":null,"abstract":".","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66332557","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}
—Potassium nitrite or saltpeter is used as a food additive and preservative. It confers a fresh and appetizing appearance to food when used in moderation. However, when used in excess, it may lead to cancer. In the present study, an image-processing mobile application was developed for quality control and ensure the hygiene of food products. The developed application is a user-friendly innovation that would raise the quality standards of processed foods, allowing for a competitive edge in the market. The main objectives of the present study were to identify the representatives of each class of suitable color tones and then develop a model-based application for estimating the content of nitrite in processed meat products. The study was conducted in six steps: (1) image layer separation of RGB to three layers comprising the R-G-B layers; (2) identification of the representatives of each class of suitable color tones using the k-means clustering technique; (3) deciphering the linear equations representing the linear relationship between the color tone and the content of nitrite; (4) designing of a mobile application for estimating the amount of nitrite based on an image; (5) development of the model-based mobile application for estimating the nitrite content; (6) evaluation of the developed mobile application using the testing dataset. The results revealed that the mean and median of the green color’s layer were appropriate representatives of the image dataset and could also be associated with the concentration of the nitrite standard solution. In addition, the efficiency of estimating the concentration of nitrite in meat products using the paper analytical apparatus was 88.25%.
{"title":"Applying an Image Technology to Estimates Values of Nitrite in Processed Meat Products","authors":"Tippaya Thinsungnoen, Jessada Rattanasuporn, Manoch Thinsungnoen, Thanakorn Pluangklang, Vanida Choomuenwai, Chareonsak Lao-ngam, Panadda Phansamdaeng, Chutima Pluangklang, Maliwan Subsadsana","doi":"10.12720/jait.14.5.1088-1095","DOIUrl":"https://doi.org/10.12720/jait.14.5.1088-1095","url":null,"abstract":"—Potassium nitrite or saltpeter is used as a food additive and preservative. It confers a fresh and appetizing appearance to food when used in moderation. However, when used in excess, it may lead to cancer. In the present study, an image-processing mobile application was developed for quality control and ensure the hygiene of food products. The developed application is a user-friendly innovation that would raise the quality standards of processed foods, allowing for a competitive edge in the market. The main objectives of the present study were to identify the representatives of each class of suitable color tones and then develop a model-based application for estimating the content of nitrite in processed meat products. The study was conducted in six steps: (1) image layer separation of RGB to three layers comprising the R-G-B layers; (2) identification of the representatives of each class of suitable color tones using the k-means clustering technique; (3) deciphering the linear equations representing the linear relationship between the color tone and the content of nitrite; (4) designing of a mobile application for estimating the amount of nitrite based on an image; (5) development of the model-based mobile application for estimating the nitrite content; (6) evaluation of the developed mobile application using the testing dataset. The results revealed that the mean and median of the green color’s layer were appropriate representatives of the image dataset and could also be associated with the concentration of the nitrite standard solution. In addition, the efficiency of estimating the concentration of nitrite in meat products using the paper analytical apparatus was 88.25%.","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135212024","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 : 2023-01-01DOI: 10.12720/jait.14.1.138-144
Kanjana Boonim
This research aimed to use clustered heatmap positioning analytical techniques in tennis in order to be able to analyze the positions of tennis players. A heatmap represents the cumulative frequency of tennis players’ movements in each zone of the tennis court. The performance testing of centroid clustering heatmap position analysis was achieved on selected men’s doubles tennis matches during the SINGHA CLASSIC 2019 competition. The research was done by collecting the cumulative frequency data and replacing it with intensity of color space. The process started with, firstly, cutting videos for each match based on the area of the court that could be seen clearly by the cameras in the field. Secondly, the video was converted into binary images. Thirdly, noise reduction was performed using morphological techniques. Fourthly, the centroid position was identified using a connected component and blob analysis. Fifthly, clustering data with k-mine was used to predict new tracks by Kalman filter. Finally, the percentage of player position in the three zones of the tennis court was calculated with the percent yield formula. The experimental results clearly showed the cumulative frequency of the players’ movement with the intensity of color space, allowing coaches and players to easily understand and use the data in planning for the next practice or competition.
{"title":"Analysis of Playing Positions in Tennis Match Videos to Assess Competition Using a Centroid Clustering Heatmap Prediction Technique","authors":"Kanjana Boonim","doi":"10.12720/jait.14.1.138-144","DOIUrl":"https://doi.org/10.12720/jait.14.1.138-144","url":null,"abstract":"This research aimed to use clustered heatmap positioning analytical techniques in tennis in order to be able to analyze the positions of tennis players. A heatmap represents the cumulative frequency of tennis players’ movements in each zone of the tennis court. The performance testing of centroid clustering heatmap position analysis was achieved on selected men’s doubles tennis matches during the SINGHA CLASSIC 2019 competition. The research was done by collecting the cumulative frequency data and replacing it with intensity of color space. The process started with, firstly, cutting videos for each match based on the area of the court that could be seen clearly by the cameras in the field. Secondly, the video was converted into binary images. Thirdly, noise reduction was performed using morphological techniques. Fourthly, the centroid position was identified using a connected component and blob analysis. Fifthly, clustering data with k-mine was used to predict new tracks by Kalman filter. Finally, the percentage of player position in the three zones of the tennis court was calculated with the percent yield formula. The experimental results clearly showed the cumulative frequency of the players’ movement with the intensity of color space, allowing coaches and players to easily understand and use the data in planning for the next practice or competition.","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66329291","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}
Ahsanul Akib, Prof. Dr. Kamruddin Nur, Suman Saha, Jannatul Ferdous Srabonee, M. F. Mridha
—The COVID-19 pandemic has wreaked havoc on people all across the world. Even though the number of verified COVID-19 cases is steadily decreasing, the danger persists. Only societal awareness and preventative measures can assist to minimize the number of impacted patients in the work environment. People often forget to wear masks before entering the work premises or are not careful enough to wear masks correctly. Keeping this in mind, this paper proposes an IoT-based architecture for taking all essential steps to combat the COVID-19 pandemic. The proposed low-cost architecture is divided into three components: one to detect face masks by using deep learning technologies, another to monitor contactless body temperature and the other to dispense disinfectants to the visitors. At first, we review all the existing state-of-the-art technologies, then we design and develop a working prototype. Here, we present our results with the accuracy of 97.43% using a deep Convolutional Neural Network (CNN) and 99.88% accuracy using MobileNetV2 deep learning architecture for automatic face mask detection.
{"title":"Computer Vision-Based IoT Architecture for Post COVID-19 Preventive Measures","authors":"Ahsanul Akib, Prof. Dr. Kamruddin Nur, Suman Saha, Jannatul Ferdous Srabonee, M. F. Mridha","doi":"10.12720/jait.14.1.7-19","DOIUrl":"https://doi.org/10.12720/jait.14.1.7-19","url":null,"abstract":"—The COVID-19 pandemic has wreaked havoc on people all across the world. Even though the number of verified COVID-19 cases is steadily decreasing, the danger persists. Only societal awareness and preventative measures can assist to minimize the number of impacted patients in the work environment. People often forget to wear masks before entering the work premises or are not careful enough to wear masks correctly. Keeping this in mind, this paper proposes an IoT-based architecture for taking all essential steps to combat the COVID-19 pandemic. The proposed low-cost architecture is divided into three components: one to detect face masks by using deep learning technologies, another to monitor contactless body temperature and the other to dispense disinfectants to the visitors. At first, we review all the existing state-of-the-art technologies, then we design and develop a working prototype. Here, we present our results with the accuracy of 97.43% using a deep Convolutional Neural Network (CNN) and 99.88% accuracy using MobileNetV2 deep learning architecture for automatic face mask detection.","PeriodicalId":36452,"journal":{"name":"Journal of Advances in Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66329937","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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