Pub Date : 2021-08-31DOI: 10.4186/ej.2021.25.8.187
A. Kodaka, N. Leelawat, Yasushi Onda, Jing Tang, A. Laosunthara, Kumpol Saengtabtim, Piyaporn Sochoeiya, N. Kohtake
Various interventions were made by the Thai government to prevent the COVID-19 spread by controlling socioeconomic activities, but the effectiveness of these interventions and other factors have not yet been fully clarified. Thus, this study aims to provide further scientific evidence on those potential factors which affect the socioeconomic activities changes during the pandemic, by using spatial analysis on atmospheric composition. By taking Phra Nakhon Si Ayutthaya Province, Thailand as the case area. Results of the government's COVID-19 measures and statuses of industries were compared with changes in aerosols, including PM 2.5 which was analyzed by Google Earth Engine with nine open datasets including meteorological and hydrological factors. The analysis revealed that the aerosol index in ueban area of the province decreased at 28.03% in 2020 compared in 2019. Besides, PM 2.5 drastically decreased from March 2020, even without the influence of wind speed which as the highest causal relationship, and kept low level compared with previous years. The reason of the tendency would be explained that other than government interventions including national-level state of the emergency decree, reduction of factories' activities at Rojana Industrial Park and reduction of the number of tourists had significant influence to reduce the mean value of PM 2.5.
{"title":"Influential Factors on Aerosol Change During COVID-19 in Ayutthaya, Thailand","authors":"A. Kodaka, N. Leelawat, Yasushi Onda, Jing Tang, A. Laosunthara, Kumpol Saengtabtim, Piyaporn Sochoeiya, N. Kohtake","doi":"10.4186/ej.2021.25.8.187","DOIUrl":"https://doi.org/10.4186/ej.2021.25.8.187","url":null,"abstract":"Various interventions were made by the Thai government to prevent the COVID-19 spread by controlling socioeconomic activities, but the effectiveness of these interventions and other factors have not yet been fully clarified. Thus, this study aims to provide further scientific evidence on those potential factors which affect the socioeconomic activities changes during the pandemic, by using spatial analysis on atmospheric composition. By taking Phra Nakhon Si Ayutthaya Province, Thailand as the case area. Results of the government's COVID-19 measures and statuses of industries were compared with changes in aerosols, including PM 2.5 which was analyzed by Google Earth Engine with nine open datasets including meteorological and hydrological factors. The analysis revealed that the aerosol index in ueban area of the province decreased at 28.03% in 2020 compared in 2019. Besides, PM 2.5 drastically decreased from March 2020, even without the influence of wind speed which as the highest causal relationship, and kept low level compared with previous years. The reason of the tendency would be explained that other than government interventions including national-level state of the emergency decree, reduction of factories' activities at Rojana Industrial Park and reduction of the number of tourists had significant influence to reduce the mean value of PM 2.5.","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"83 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74184182","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 : 2021-07-31DOI: 10.4186/ej.2021.25.7.121
Dinh-Linh Le, The-Quan Nguyen, Khoa Do Huu
{"title":"Life Cycle Carbon Dioxide Emissions Assessment in the Design Phase: A Case of a Green Building in Vietnam","authors":"Dinh-Linh Le, The-Quan Nguyen, Khoa Do Huu","doi":"10.4186/ej.2021.25.7.121","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.121","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81516686","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 : 2021-07-31DOI: 10.4186/ej.2021.25.7.135
Ngoc-Tri Ngo, H. Le, V. Huynh, Thi-Phuong-Trang Pham
{"title":"Machine Learning Models for Inferring the Axial Strength in Short Concrete-Filled Steel Tube Columns Infilled with Various Strength Concrete","authors":"Ngoc-Tri Ngo, H. Le, V. Huynh, Thi-Phuong-Trang Pham","doi":"10.4186/ej.2021.25.7.135","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.135","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73591974","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":"A Fuzzy Credibility-Based Chance-Constrained Optimization Model for Multiple-Objective Aggregate Production Planning in a Supply Chain under an Uncertain Environment","authors":"Doan Hoang Tuan, N. Chiadamrong","doi":"10.4186/ej.2021.25.7.31","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.31","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84356840","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 : 2021-07-31DOI: 10.4186/ej.2021.25.7.157
V. Truong, H. Pham
. Thanks to the rapid development of computer science, direct analyses have been increasingly used in the design of structures in lieu of member-based design methods using the effective length factor. In a direct analysis, the ultimate strength of a whole structure can be sufficiently estimated, so that the need for member capacity checks is eliminated. However, in complicated structural design problems where many structural analyses are required, the use of direct analyses requires an excessive computation cost. In such cases, Machine Learning (ML) algorithms are used to build metamodels that can predict the structural responses without performing costly structural analysis. In this paper, the support vector machine (SVM) algorithm is employed for the first time to develop a metamodel for predicting the ultimate strength of trusses using direct analysis. Several kernel functions for the SVM model, including linear, sigmoid, polynomial, radial basis function (RBF), are considered. A planar 39-bar nonlinear inelastic steel truss is taken to study the performance of the kernel functions. The results confirm the applicability of the SVM-based metamodel for predicting the ultimate strength of trusses. In particular, the RBF appears to be the best kernel among others. This investigation also provides a deeper understanding of the effect of the parameters on the efficiency of the kernel functions.
{"title":"Support Vector Machine for Regression of Ultimate Strength of Trusses: A Comparative Study","authors":"V. Truong, H. Pham","doi":"10.4186/ej.2021.25.7.157","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.157","url":null,"abstract":". Thanks to the rapid development of computer science, direct analyses have been increasingly used in the design of structures in lieu of member-based design methods using the effective length factor. In a direct analysis, the ultimate strength of a whole structure can be sufficiently estimated, so that the need for member capacity checks is eliminated. However, in complicated structural design problems where many structural analyses are required, the use of direct analyses requires an excessive computation cost. In such cases, Machine Learning (ML) algorithms are used to build metamodels that can predict the structural responses without performing costly structural analysis. In this paper, the support vector machine (SVM) algorithm is employed for the first time to develop a metamodel for predicting the ultimate strength of trusses using direct analysis. Several kernel functions for the SVM model, including linear, sigmoid, polynomial, radial basis function (RBF), are considered. A planar 39-bar nonlinear inelastic steel truss is taken to study the performance of the kernel functions. The results confirm the applicability of the SVM-based metamodel for predicting the ultimate strength of trusses. In particular, the RBF appears to be the best kernel among others. This investigation also provides a deeper understanding of the effect of the parameters on the efficiency of the kernel functions.","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80133319","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":"Coastal Upwelling Investigation in the Gulf of Thailand Using Ekman Transport and Sea Surface Temperature Upwelling Indices","authors":"Pacharamon Sripoonpan, Suriyan Saramul","doi":"10.4186/ej.2021.25.7.1","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.1","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77621192","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}
K. Wongpatikaseree, Y. Kaewpitakkun, Sumeth Yuenyong, Siriwon Matsuo, P. Yomaboot
{"title":"EmoCNN: Encoding Emotional Expression from Text to Word Vector and Classifying Emotions—A Case Study in Thai Social Network Conversation","authors":"K. Wongpatikaseree, Y. Kaewpitakkun, Sumeth Yuenyong, Siriwon Matsuo, P. Yomaboot","doi":"10.4186/ej.2021.25.7.73","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.73","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73520044","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 : 2021-07-31DOI: 10.4186/ej.2021.25.7.167
Quynh To Thi Huong, E. Lou, Nam Le Thi Hoai
{"title":"Enhancing BIM Diffusion through Pilot Projects in Vietnam","authors":"Quynh To Thi Huong, E. Lou, Nam Le Thi Hoai","doi":"10.4186/ej.2021.25.7.167","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.167","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"94 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85472076","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 : 2021-07-31DOI: 10.4186/ej.2021.25.7.177
The-Quan Nguyen, Quoc Viet Dao
{"title":"A Case Study of BIM Application in a Public Construction Project Management Unit in Vietnam: Lessons Learned and Organizational Changes","authors":"The-Quan Nguyen, Quoc Viet Dao","doi":"10.4186/ej.2021.25.7.177","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.177","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75039638","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}
I. I. Safarov, M. Teshaev, A. Marasulov, B. Nuriddinov
{"title":"Propagation of Own Non- Axisymmetric Waves in Viscoelastic Three-Layered Cylindrical Shells","authors":"I. I. Safarov, M. Teshaev, A. Marasulov, B. Nuriddinov","doi":"10.4186/ej.2021.25.7.97","DOIUrl":"https://doi.org/10.4186/ej.2021.25.7.97","url":null,"abstract":"","PeriodicalId":32885,"journal":{"name":"AlKhawarizmi Engineering Journal","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83732600","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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