Pub Date : 1900-01-01DOI: 10.32604/cmc.2022.028241
Woo Hyun Park, Isma Farah Siddiqui, Dong Ryeol Shin, Nawab Muhammad Faseeh Qureshi
For the last couple years, governments and health authorities worldwide have been focused on addressing the Covid-19 pandemic;for example, governments have implemented countermeasures, such as quarantining, pushing vaccine shots to minimize local spread, investigating and analyzing the virus??? characteristics, and conducting epidemiological investigations through patient management and tracers. Therefore, researchers worldwide require funding to achieve these goals. Furthermore, there is a need for documentation to investigate and trace disease characteristics. However, it is time consuming and resource intensive to work with documents comprising many types of unstructured data. Therefore, in this study, natural language processing technology is used to automatically classify these documents. Currently used statistical methods include data cleansing, query modification, sentiment analysis, and clustering. However, owing to limitations with respect to the data, it is necessary to understand how to perform data analysis suitable for medical documents. To solve this problem, this study proposes a robust in-depth mixed with subject and emotion model comprising three modules. The first is a subject and non-linear emotional module, which extracts topics from the data and supplements them with emotional figures. The second is a subject with singular value decomposition in the emotion model, which is a dimensional decomposition module that uses subject analysis and an emotion model. The third involves embedding with singular value decomposition using an emotion module, which is a dimensional decomposition method that uses emotion learning. The accuracy and other model measurements, such as the F1, area under the curve, and recall are evaluated based on an article on Middle East respiratory syndrome. A high F1 score of approximately 91% is achieved. The proposed joint analysis method is expected to provide a better synergistic effect in the dataset.
{"title":"NLP-Based Subject with Emotions Joint Analytics for Epidemic Articles","authors":"Woo Hyun Park, Isma Farah Siddiqui, Dong Ryeol Shin, Nawab Muhammad Faseeh Qureshi","doi":"10.32604/cmc.2022.028241","DOIUrl":"https://doi.org/10.32604/cmc.2022.028241","url":null,"abstract":"For the last couple years, governments and health authorities worldwide have been focused on addressing the Covid-19 pandemic;for example, governments have implemented countermeasures, such as quarantining, pushing vaccine shots to minimize local spread, investigating and analyzing the virus??? characteristics, and conducting epidemiological investigations through patient management and tracers. Therefore, researchers worldwide require funding to achieve these goals. Furthermore, there is a need for documentation to investigate and trace disease characteristics. However, it is time consuming and resource intensive to work with documents comprising many types of unstructured data. Therefore, in this study, natural language processing technology is used to automatically classify these documents. Currently used statistical methods include data cleansing, query modification, sentiment analysis, and clustering. However, owing to limitations with respect to the data, it is necessary to understand how to perform data analysis suitable for medical documents. To solve this problem, this study proposes a robust in-depth mixed with subject and emotion model comprising three modules. The first is a subject and non-linear emotional module, which extracts topics from the data and supplements them with emotional figures. The second is a subject with singular value decomposition in the emotion model, which is a dimensional decomposition module that uses subject analysis and an emotion model. The third involves embedding with singular value decomposition using an emotion module, which is a dimensional decomposition method that uses emotion learning. The accuracy and other model measurements, such as the F1, area under the curve, and recall are evaluated based on an article on Middle East respiratory syndrome. A high F1 score of approximately 91% is achieved. The proposed joint analysis method is expected to provide a better synergistic effect in the dataset.","PeriodicalId":329824,"journal":{"name":"Computers, Materials & Continua","volume":"30 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":"127677150","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: 10.32604/cmc.2023.032740
Mesfer Al Duhayyim, Mohammed Maray, Ayman Qahmash, Fatma S. Alrayes, Nuha Alshuqayran, Jaber S. Alzahrani, Mohammed Alghamdi, Abdullah Mohamed
{"title":"Improved Multileader Optimization with Shadow Encryption for Medical Images in IoT Environment","authors":"Mesfer Al Duhayyim, Mohammed Maray, Ayman Qahmash, Fatma S. Alrayes, Nuha Alshuqayran, Jaber S. Alzahrani, Mohammed Alghamdi, Abdullah Mohamed","doi":"10.32604/cmc.2023.032740","DOIUrl":"https://doi.org/10.32604/cmc.2023.032740","url":null,"abstract":"","PeriodicalId":329824,"journal":{"name":"Computers, Materials & Continua","volume":"40 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":"127887513","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: 10.32604/cmc.2022.029438
Fadwa M. Alrowais, Saud S. Alotaibi, S. Dhahbi, Radwa Marzouk, Abdullah Mohamed, Anwer Mustafa Hilal
{"title":"Sign Language Recognition and Classification Model to Enhance Quality of Disabled People","authors":"Fadwa M. Alrowais, Saud S. Alotaibi, S. Dhahbi, Radwa Marzouk, Abdullah Mohamed, Anwer Mustafa Hilal","doi":"10.32604/cmc.2022.029438","DOIUrl":"https://doi.org/10.32604/cmc.2022.029438","url":null,"abstract":"","PeriodicalId":329824,"journal":{"name":"Computers, Materials & Continua","volume":"23 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":"126503434","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: 10.32604/cmc.2023.032950
W. Weera, Chantapish Zamart, Z. Sabir, M. Asif Zahoor Raja, Afaf S. Alwabli, S. R. Mahmoud, Supreecha Wongaree, T. Botmart
{"title":"Fractional Order Environmental and Economic Model Investigations Using Artificial Neural Network","authors":"W. Weera, Chantapish Zamart, Z. Sabir, M. Asif Zahoor Raja, Afaf S. Alwabli, S. R. Mahmoud, Supreecha Wongaree, T. Botmart","doi":"10.32604/cmc.2023.032950","DOIUrl":"https://doi.org/10.32604/cmc.2023.032950","url":null,"abstract":"","PeriodicalId":329824,"journal":{"name":"Computers, Materials & Continua","volume":"5 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":"128112296","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: 10.32604/cmc.2023.036093
Muhammad Usman Sana, Zhanli Li, Tayybah Kiren, Hannan Bin Liaqat, Shahid Naseem, Atif Saeed
{"title":"A Secure Method for Data Storage and Transmission in Sustainable Cloud Computing","authors":"Muhammad Usman Sana, Zhanli Li, Tayybah Kiren, Hannan Bin Liaqat, Shahid Naseem, Atif Saeed","doi":"10.32604/cmc.2023.036093","DOIUrl":"https://doi.org/10.32604/cmc.2023.036093","url":null,"abstract":"","PeriodicalId":329824,"journal":{"name":"Computers, Materials & Continua","volume":"175 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":"128153813","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: 10.32604/cmc.2022.027629
Prem Junswang, Z. Sabir, M. Asif Zahoor Raja, S. Salahshour, T. Botmart, W. Weera
{"title":"An Advanced Stochastic Numerical Approach for Host-Vector-Predator Nonlinear Model","authors":"Prem Junswang, Z. Sabir, M. Asif Zahoor Raja, S. Salahshour, T. Botmart, W. Weera","doi":"10.32604/cmc.2022.027629","DOIUrl":"https://doi.org/10.32604/cmc.2022.027629","url":null,"abstract":"","PeriodicalId":329824,"journal":{"name":"Computers, Materials & Continua","volume":"33 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":"125712516","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: 10.32604/cmc.2023.037293
Runguo Xu, Xuehan Yu, Xiaoxue Zhao
{"title":"Regional Economic Development Trend Prediction Method Based on Digital Twins and Time Series Network","authors":"Runguo Xu, Xuehan Yu, Xiaoxue Zhao","doi":"10.32604/cmc.2023.037293","DOIUrl":"https://doi.org/10.32604/cmc.2023.037293","url":null,"abstract":"","PeriodicalId":329824,"journal":{"name":"Computers, Materials & Continua","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":"125845206","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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