Pub Date : 2021-06-12DOI: 10.48048/WJST.2021.10573
P. Vejjanugraha, K. Kotani, W. Kongprawechnon, T. Kondo, K. Tungpimolrut
Lung diseases are now the third leading cause of death worldwide because of the many risk factors we are exposed to daily, such as air pollution, tobacco use, viruses (such as COVID-19), and bacteria. This work introduces a new approach of the 3D Active Contour Model (3D ACM) to estimate an inhomogeneous motion of lungs, which can be used to analyze lung disease patterns using a hierarchical predictive model. The biophysical model of lungs consists of End Expiratory (EE) and End Inspiratory (EI) models, generated by high-resolution computed tomography images (HRCT). A proposed technique uses the 3D ACM to estimate the velocity vector by using the corresponding points on the parametric surface model of the EE model to the EI model. The external energy from the EI models is the external force that pushes the 3D parametric surface to reach the boundary. The external forces, such as the balloon force and Gradient Vector Flow (GVF), were adjusted adaptively based on the Zaratio which was calculated from the ratio of the maximum value of EI to EE on the Z axis. Next, the feature representation is studied and evaluated based on the lung structure, separated into five lobes. The stepwise regression, Support Vector Machine (SVM), and Artificial Neural Network (ANN) techniques are applied to classify the lung diseases into normal, obstructive lung, and restrictive lung diseases. In conclusion, the inhomogeneous motion pattern of lungs integrated with medical-based knowledge can be used to analyze lung diseases by differentiating normal and abnormal motion patterns and separating restrictive and obstructive lung diseases. [ABSTRACT FROM AUTHOR] Copyright of Walailak Journal of Science & Technology is the property of Walailak Journal of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
{"title":"Automatic Screening of Lung Diseases by 3D Active Contour Method for Inhomogeneous Motion Estimation in CT Image Pairs","authors":"P. Vejjanugraha, K. Kotani, W. Kongprawechnon, T. Kondo, K. Tungpimolrut","doi":"10.48048/WJST.2021.10573","DOIUrl":"https://doi.org/10.48048/WJST.2021.10573","url":null,"abstract":"Lung diseases are now the third leading cause of death worldwide because of the many risk factors we are exposed to daily, such as air pollution, tobacco use, viruses (such as COVID-19), and bacteria. This work introduces a new approach of the 3D Active Contour Model (3D ACM) to estimate an inhomogeneous motion of lungs, which can be used to analyze lung disease patterns using a hierarchical predictive model. The biophysical model of lungs consists of End Expiratory (EE) and End Inspiratory (EI) models, generated by high-resolution computed tomography images (HRCT). A proposed technique uses the 3D ACM to estimate the velocity vector by using the corresponding points on the parametric surface model of the EE model to the EI model. The external energy from the EI models is the external force that pushes the 3D parametric surface to reach the boundary. The external forces, such as the balloon force and Gradient Vector Flow (GVF), were adjusted adaptively based on the Zaratio which was calculated from the ratio of the maximum value of EI to EE on the Z axis. Next, the feature representation is studied and evaluated based on the lung structure, separated into five lobes. The stepwise regression, Support Vector Machine (SVM), and Artificial Neural Network (ANN) techniques are applied to classify the lung diseases into normal, obstructive lung, and restrictive lung diseases. In conclusion, the inhomogeneous motion pattern of lungs integrated with medical-based knowledge can be used to analyze lung diseases by differentiating normal and abnormal motion patterns and separating restrictive and obstructive lung diseases. [ABSTRACT FROM AUTHOR] Copyright of Walailak Journal of Science & Technology is the property of Walailak Journal of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)","PeriodicalId":38275,"journal":{"name":"Walailak Journal of Science and Technology","volume":"18 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46935755","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}
Background and Objectives: The advent of 2020 was eclipsed by an epidemic crisis of COVID-19 The swift spread of fatal viruses creates paralyzing apprehensions among all human beings and has produced a need to develop a sound psychometric scale to measure anxiety related to COVID-19
{"title":"Development and Validation of Corona Virus Anxiety Scale (CVAS)","authors":"Faiza Afreen","doi":"10.48048/wjst.2020.9878","DOIUrl":"https://doi.org/10.48048/wjst.2020.9878","url":null,"abstract":"Background and Objectives: The advent of 2020 was eclipsed by an epidemic crisis of COVID-19 The swift spread of fatal viruses creates paralyzing apprehensions among all human beings and has produced a need to develop a sound psychometric scale to measure anxiety related to COVID-19","PeriodicalId":38275,"journal":{"name":"Walailak Journal of Science and Technology","volume":"17 1","pages":"958-966"},"PeriodicalIF":0.0,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48702924","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}
Sirindhorn International Institute of Technology (SIIT) is an international institute of Thammasat University (TU), located in Pathum Thani, Thailand. The courses are offered in English, and many foreign students are studying at SIIT-TU. The classes have been suspended since 16 March 2020 to slow down the COVID-19 disease spread, and the students are suggested to study online at home. The present study intends to understand the at-home activities and well-being of foreign students. A web-based survey was conducted from 22 through 23 March 2020 to record the activities and well-being of the students on 20 and 21 March 2020. Happiness and stress levels with the seven-points Likert scales were considered as the two output variables (1 = lowest and 7 = highest). The ordered probit model was applied to develop the subjective well-being models, taking into account at-home activities. The results highlighted that students who were happier were more likely to study for longer at home, but that studying for longer increases stress levels. Students who were less happy and more stressed were more likely to speak on the phone for longer, while doing exercise at home for longer increased the likelihood of happiness. This paper contributes to a better understanding of at-home activities associated with well-being of foreign students in Thailand during the COVID-19 outbreak.
{"title":"At-Home Activities and Subjective Well-Being of Foreign College Students in Thailand during the COVID-19 Pandemic Outbreak","authors":"M. Rith, M. Piantanakulchai","doi":"10.48048/wjst.2020.9931","DOIUrl":"https://doi.org/10.48048/wjst.2020.9931","url":null,"abstract":"Sirindhorn International Institute of Technology (SIIT) is an international institute of Thammasat University (TU), located in Pathum Thani, Thailand. The courses are offered in English, and many foreign students are studying at SIIT-TU. The classes have been suspended since 16 March 2020 to slow down the COVID-19 disease spread, and the students are suggested to study online at home. The present study intends to understand the at-home activities and well-being of foreign students. A web-based survey was conducted from 22 through 23 March 2020 to record the activities and well-being of the students on 20 and 21 March 2020. Happiness and stress levels with the seven-points Likert scales were considered as the two output variables (1 = lowest and 7 = highest). The ordered probit model was applied to develop the subjective well-being models, taking into account at-home activities. The results highlighted that students who were happier were more likely to study for longer at home, but that studying for longer increases stress levels. Students who were less happy and more stressed were more likely to speak on the phone for longer, while doing exercise at home for longer increased the likelihood of happiness. This paper contributes to a better understanding of at-home activities associated with well-being of foreign students in Thailand during the COVID-19 outbreak.","PeriodicalId":38275,"journal":{"name":"Walailak Journal of Science and Technology","volume":"17 1","pages":"1024-1033"},"PeriodicalIF":0.0,"publicationDate":"2020-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44884850","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}
Tharin Phenwan, Weeratian Tawanwongsri, Phanit Koomhin, U. Saengow
To estimate the prevalence of dementia among Thai elderly in the upper Southern region of Thailand, we performed a cross-sectional screening of all Thai older people from 2 areas of Nakhon Si Thammarat province: Tambon Baan Thungchon, Tha Sala district, and Moo 6 and 7 from Sichon district, from December 2016 to November 2017. Trained health volunteers identified the participants in their communities and collected data including age, gender, comorbidities, Timed Up and Go Test (TUGT) results, and Montreal Cognitive Assessment (MoCA) scores. Our sample comprised 773 participants, of which 605 (78.3 %) were from Baan Thungchon area, while 168 were from Moo 6 and Moo 7 of Sichon district. The majority of participants were female (431, 55.7 %). The mean age of the participants was 79 ± 9.1 years, with a minimum age of 60, and a maximum age of 95. Their comorbidities were hypertension (42.9 %), type II diabetic mellitus (33.2 %), dyslipidemia (37.5 %), and osteoarthritis of the knees (35.8 %). 35.1 % of them also had positive TUGT. Sixty-seven participants (8.7 %) scored 7 or lower in the Abbreviated Mental Test (AMT). Five participants (7.5 %) had a positive screening for dementia.
{"title":"Dementia Community Screening Program in District Health Area 11: Phase 1","authors":"Tharin Phenwan, Weeratian Tawanwongsri, Phanit Koomhin, U. Saengow","doi":"10.48048/WJST.2020.5741","DOIUrl":"https://doi.org/10.48048/WJST.2020.5741","url":null,"abstract":"To estimate the prevalence of dementia among Thai elderly in the upper Southern region of Thailand, we performed a cross-sectional screening of all Thai older people from 2 areas of Nakhon Si Thammarat province: Tambon Baan Thungchon, Tha Sala district, and Moo 6 and 7 from Sichon district, from December 2016 to November 2017. Trained health volunteers identified the participants in their communities and collected data including age, gender, comorbidities, Timed Up and Go Test (TUGT) results, and Montreal Cognitive Assessment (MoCA) scores. Our sample comprised 773 participants, of which 605 (78.3 %) were from Baan Thungchon area, while 168 were from Moo 6 and Moo 7 of Sichon district. The majority of participants were female (431, 55.7 %). The mean age of the participants was 79 ± 9.1 years, with a minimum age of 60, and a maximum age of 95. Their comorbidities were hypertension (42.9 %), type II diabetic mellitus (33.2 %), dyslipidemia (37.5 %), and osteoarthritis of the knees (35.8 %). 35.1 % of them also had positive TUGT. Sixty-seven participants (8.7 %) scored 7 or lower in the Abbreviated Mental Test (AMT). Five participants (7.5 %) had a positive screening for dementia.","PeriodicalId":38275,"journal":{"name":"Walailak Journal of Science and Technology","volume":"17 1","pages":"1042-1047"},"PeriodicalIF":0.0,"publicationDate":"2020-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42430817","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}
The objectives of this cross-sectional research were to study university students' knowledge on COVID-19 transmission, their attitude toward the measures of COVID-19 prevention and control, social responsibility behaviors, and factors association with participants' social responsibility behaviors The population from 3 universities were 17,765 students, the sample size was at least 376 participants according to Krejcie and Morgan's formula Purposive sampling was employed to select the target participants Then, each student shared the questionnaire link with their friends The self-administered questionnaires were distributed by using Google Forms The content validity was evaluated by 3 experts;the Index of Item-Objective Congruence (IOC) of each item of all part was 1 and the coefficient of reliability knowledge and attitude were more than 0 70 The links of each Google Form was sent through Facebook and Line contact friends and asked them for distribution to others The were 416 students who completed the questionnaires Descriptive statistics were used to analyze the data, while for the association study, Chi-square and Binary logistic regression were used The results disclosed that the university students had the knowledge of Covid-19 transmission at Moderate level (50 72%), and had the attitude of the state measures for Covid-19 prevention and control in High level (81 01%) Additionally, their social responsibility behaviors for COVID-19 prevention and control were in High level (57 21%) The knowledge on Covid-19 transmission was significantly associated with social responsibility behaviors among university students (p-value < 0 05) as well as their attitude on the state measures for Covid-19 prevention and control that was significantly associated with university students' social responsibility behaviors (p-value < 0 01)
{"title":"Social Responsibility Behaviors among Universities Students in the 3 Southern Border Provinces of Thailand in the Period of Corona Virus 2019 (COVID-19) Pandemic","authors":"Awirut Singkun, Fatin Payodeuramae, Nuseeta Samae, Piriya Patiwikriwong, Khajornsak Chainapong, Phakkhanat Weerakhachon","doi":"10.48048/wjst.2020.10066","DOIUrl":"https://doi.org/10.48048/wjst.2020.10066","url":null,"abstract":"The objectives of this cross-sectional research were to study university students' knowledge on COVID-19 transmission, their attitude toward the measures of COVID-19 prevention and control, social responsibility behaviors, and factors association with participants' social responsibility behaviors The population from 3 universities were 17,765 students, the sample size was at least 376 participants according to Krejcie and Morgan's formula Purposive sampling was employed to select the target participants Then, each student shared the questionnaire link with their friends The self-administered questionnaires were distributed by using Google Forms The content validity was evaluated by 3 experts;the Index of Item-Objective Congruence (IOC) of each item of all part was 1 and the coefficient of reliability knowledge and attitude were more than 0 70 The links of each Google Form was sent through Facebook and Line contact friends and asked them for distribution to others The were 416 students who completed the questionnaires Descriptive statistics were used to analyze the data, while for the association study, Chi-square and Binary logistic regression were used The results disclosed that the university students had the knowledge of Covid-19 transmission at Moderate level (50 72%), and had the attitude of the state measures for Covid-19 prevention and control in High level (81 01%) Additionally, their social responsibility behaviors for COVID-19 prevention and control were in High level (57 21%) The knowledge on Covid-19 transmission was significantly associated with social responsibility behaviors among university students (p-value < 0 05) as well as their attitude on the state measures for Covid-19 prevention and control that was significantly associated with university students' social responsibility behaviors (p-value < 0 01)","PeriodicalId":38275,"journal":{"name":"Walailak Journal of Science and Technology","volume":"17 1","pages":"979-989"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70557803","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}
The objectives of this research were to study the knowledge on COVID-19 infection, satisfaction of the measures on disease prevention and control, and the association between factors and COVID-19 prevention behaviors among health sciences students Content validity and reliability of research tools were measured Ethical for human study was approved by Research Ethic Committee Self-administered questionnaires were used to collect the data of 184 health sciences students in April, 2020 First, a proportion by curriculum and year of study was made Then, simple random sampling was created based on student identification Data analysis involved descriptive statistics, Chi-square and Fisher's exact tests The results found that participants had correct answer for COVID-19 infection (70 65 - 99 46%) and had a good knowledge level on COVID-19 infection (90 22%) Their satisfaction of the institute's measures on COVID-19 prevention and control was at High level (50 54%) COVID-19 prevention behavior among participants was at moderate level (51 63%) Age, year level, payment per week, and satisfaction level of their organization's measures on COVID-19 prevention and control were closely associated with COVID-19 prevention behavior (p - value < 0 05) These results could be used as guidelines to arrange additional activities for students in lower age and integrate health concern into the curriculum in early year of study For further study, satisfaction theory can be applied to encourage students to have positive behaviors
{"title":"Factors Associated with Coronavirus 2019 (COVID-19) Prevention Behaviors among Health Sciences Students of a Higher Education Institution in Yala Province, Thailand","authors":"Awirut Singkun, Piriya Patiwikriwong, Khajornsak Chainapong, Phakkhanat Weerakhachon","doi":"10.48048/wjst.2020.10022","DOIUrl":"https://doi.org/10.48048/wjst.2020.10022","url":null,"abstract":"The objectives of this research were to study the knowledge on COVID-19 infection, satisfaction of the measures on disease prevention and control, and the association between factors and COVID-19 prevention behaviors among health sciences students Content validity and reliability of research tools were measured Ethical for human study was approved by Research Ethic Committee Self-administered questionnaires were used to collect the data of 184 health sciences students in April, 2020 First, a proportion by curriculum and year of study was made Then, simple random sampling was created based on student identification Data analysis involved descriptive statistics, Chi-square and Fisher's exact tests The results found that participants had correct answer for COVID-19 infection (70 65 - 99 46%) and had a good knowledge level on COVID-19 infection (90 22%) Their satisfaction of the institute's measures on COVID-19 prevention and control was at High level (50 54%) COVID-19 prevention behavior among participants was at moderate level (51 63%) Age, year level, payment per week, and satisfaction level of their organization's measures on COVID-19 prevention and control were closely associated with COVID-19 prevention behavior (p - value < 0 05) These results could be used as guidelines to arrange additional activities for students in lower age and integrate health concern into the curriculum in early year of study For further study, satisfaction theory can be applied to encourage students to have positive behaviors","PeriodicalId":38275,"journal":{"name":"Walailak Journal of Science and Technology","volume":"17 1","pages":"967-978"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70557723","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}
Big data is a collection of large volumes of data sets which are more complicated to analyze using standard data processing methods. It also emphasizes parameters like data variety and velocity data. Big data will play a most significant role in our daily life regarding applications like healthcare electronic commerce, agriculture, telecommunication, government, and financial trading. In the agriculture domain, big data is an optimal method to increase the productivity of farming by gathering and processing information like plant growth, farmland monitoring, greenhouse gases monitoring, climate change, soil monitoring and so forth. Virtualization is an emerging technique that can be combined with big data in agriculture. Virtualization has been used extensively in research for a long time, the term “virtual” entities affecting a real-life form. In agriculture, it has many more physical objects, sensors, and devices. This physical object is virtualized and has digital representation to store, communicate and process via the internet. The information from the virtual object has a large volume of data which helps meaningful data analysis or aspects to make application services like decision making, problem notification, and information handling. This paper provides a comprehensive review of big data virtualization in the agriculture domain. The virtualization methodology, and tools used by many researchers is surveyed.
{"title":"A Big Data Virtualization Role in Agriculture: A Comprehensive Review","authors":"S. Mathivanan, P. Jayagopal","doi":"10.14456/VOL16ISS2PP%P","DOIUrl":"https://doi.org/10.14456/VOL16ISS2PP%P","url":null,"abstract":"Big data is a collection of large volumes of data sets which are more complicated to analyze using standard data processing methods. It also emphasizes parameters like data variety and velocity data. Big data will play a most significant role in our daily life regarding applications like healthcare electronic commerce, agriculture, telecommunication, government, and financial trading. In the agriculture domain, big data is an optimal method to increase the productivity of farming by gathering and processing information like plant growth, farmland monitoring, greenhouse gases monitoring, climate change, soil monitoring and so forth. Virtualization is an emerging technique that can be combined with big data in agriculture. Virtualization has been used extensively in research for a long time, the term “virtual” entities affecting a real-life form. In agriculture, it has many more physical objects, sensors, and devices. This physical object is virtualized and has digital representation to store, communicate and process via the internet. The information from the virtual object has a large volume of data which helps meaningful data analysis or aspects to make application services like decision making, problem notification, and information handling. This paper provides a comprehensive review of big data virtualization in the agriculture domain. The virtualization methodology, and tools used by many researchers is surveyed.","PeriodicalId":38275,"journal":{"name":"Walailak Journal of Science and Technology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66681026","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}
The researchers observed and studied the business operations of 3 startup businesses in the export/import field. It was found that employees and their clients mostly communicate via email. Therefore, crucial business data are conveyed in email contents. Whenever employees need to find information, the first place they look for such data is email. The owners of businesses are concerned about this issue, so they proposed to buy a new workflow management system to help in managing their business transactions. The difficulty of implementing the new workflow management system is in migrating existing emails into the system. A new workflow management system should also be able to classify any incoming emails into categories. The researchers noticed that there were some keywords that frequently occurred in email contents in the same categories. Therefore, the researchers implemented a program to categorize the emails based on the words found in email messages. There are 2 parameters which affect the accuracy of the program. The first parameter is the number of words in a database compared to the sample emails. The second parameter is an acceptable percentage to classify emails. The results of this research demonstrated that the number of words in a database compared to the sample emails should be 9, and the acceptable percentage to categorize emails should be 30 %. When this rule was applied to categorize 8,751 emails, the accuracy of this experiment was approximately 73.6 %. The next phase is to order emails in each category based on their characteristics. Finally, the program extracts essential data from structured emails and prepares them for the new workflow management system.
{"title":"Email Classification Model for Workflow Management Systems","authors":"Takorn Prexawanprasut, Piyanuch Chaipornkaew","doi":"10.14456/VOL14ISS9PP%P","DOIUrl":"https://doi.org/10.14456/VOL14ISS9PP%P","url":null,"abstract":"The researchers observed and studied the business operations of 3 startup businesses in the export/import field. It was found that employees and their clients mostly communicate via email. Therefore, crucial business data are conveyed in email contents. Whenever employees need to find information, the first place they look for such data is email. The owners of businesses are concerned about this issue, so they proposed to buy a new workflow management system to help in managing their business transactions. The difficulty of implementing the new workflow management system is in migrating existing emails into the system. A new workflow management system should also be able to classify any incoming emails into categories. The researchers noticed that there were some keywords that frequently occurred in email contents in the same categories. Therefore, the researchers implemented a program to categorize the emails based on the words found in email messages. There are 2 parameters which affect the accuracy of the program. The first parameter is the number of words in a database compared to the sample emails. The second parameter is an acceptable percentage to classify emails. The results of this research demonstrated that the number of words in a database compared to the sample emails should be 9, and the acceptable percentage to categorize emails should be 30 %. When this rule was applied to categorize 8,751 emails, the accuracy of this experiment was approximately 73.6 %. The next phase is to order emails in each category based on their characteristics. Finally, the program extracts essential data from structured emails and prepares them for the new workflow management system.","PeriodicalId":38275,"journal":{"name":"Walailak Journal of Science and Technology","volume":"14 1","pages":"783-790"},"PeriodicalIF":0.0,"publicationDate":"2017-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66681005","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：