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Distribution of Factors Affecting Foreign Direct Investment in ASEAN Countries
Anh Thi Lan NGUYEN(Anh Thi Lan NGUYEN ),Chau Thi Minh PHAM(Chau Thi Minh PHAM ),Hanh Hong NGUYEN(Hanh Hong NGUYEN ),Dat Ngoc NGUYEN(Dat Ngoc NGUYEN ),Duy Van NGUYEN(Duy Van NGUYEN ) 한국유통과학회 2023 유통과학연구 Vol.21 No.2
Purpose: Research on attracting foreign direct investment plays an important role in ASEAN countries. ASEAN has needed FDI capital for development and integration with many developing countries. Research design, data and methodology: This study is conducted to assess the impact of factors: inflation (INF), economic growth (GDP), population (POP), and trade (TRADE) on attracting foreign direct investment (FDI) of ASEAN countries. The study will find out how factors distribution contributes to FDI attraction. The study collects data from 10 ASEAN countries from 2010 to 2020. With data collected for ten countries from 2010 to 2020, data analysis with panel data will be used in this study. The Regression with Driscoll-Kraay standard errors correction model will be used in the study. Results: Panel data analysis shows that economic growth and population positively impact FDI attraction in ASEAN countries. However, two factors: INF and TRADE, do not affect FDI. Conclusions: Countries need to focus on economic development, create many good conditions for people and domestic enterprises and create opportunities for foreign investors to pay more attention. improving the quality of domestic human resources will help to better improve the working quality factor when the demand for high-quality human resources increases.
Lan, Pham Thi,Son, Tong Si,Gunasekara, Kavinda,Nhan, Nguyen Thi,Hien, La Phu Korean Society of Surveying 2013 한국측량학회지 Vol.31 No.6
Coastline is the most dynamic part of seascape since its shape is affected by various factors. Coastal zone is an area with immense geological, geomorphological and ecological interest. Monitoring coastal change is very important for safe navigation, coastal resource management. This paper shows a result of monitoring coastal morphological changes using Remote Sensing and GIS. Study was carried out to obtain intensity of erosion, deposition and sand bar movement in the Red River Delta. Satellite images of ALOS/AVNIR-2 and Landsat were used for the monitoring of coastal morphological changes over the period of 1975 to 2009. Band rationing and threshold technique was used for the coastline extraction. Tidal levels at the time of image acquisition varied from -0.89m to 2.87m. Therefore, coastline from another image at a different tidal level in the same year was considered to get the corrected coastline by interpolation technique. A series of points were generated along the coastal line from 1975 image and were established as reference points to see the change in later periods. The changes were measured in Euclidean distances from these reference points. Positive values represented deposition to the sea and negative values are erosion. The result showed that the Red river delta area expanded to the sea 3500m in Red river mouth, and 2873m in Thai Binh river mouth from 1975 to 2009. The erosion process occurred continuously from 1975 up to now with the average magnitude 23.77m/year from 1975 to 1989 and 7.85m/year from 2001 to 2009 in Giao Thuy area. From 1975 to 2009, total 1095.2ha of settlement area was eroded by sea. On the other hand, land expanded to the sea in 4786.24ha of mangrove and 1673.98ha of aquaculture.
Lan, Nguyen Thi Thao,Phuong, Nguyen Pham Anh,Trang, Nguyen Thi My,Huong, Pham Thi My,An, Nguyen Thu,Le, Hoanh-Su Korea Multimedia Society 2021 The journal of multimedia information system Vol.8 No.1
The paper is based on data collected from the Amazon website (specific in the Handmade's Category) to understand and analyze Vietnamese artisans' business context. Data analysis is also applied to determine the factors that bring success Handmade products and compare products of the same industry among competitors to find out potential products. By collecting data from Amazon and analyzing the data, we extracted useful information for online business developers. Besides, the list of potential products in Handmade sector can be referred to improve the business and compete with competitors. This paper also proposes solutions to help Vietnamese products become more appealing to international customers on the Amazon website.
Pham Thi Lan,Tong Si Son,Kavinda Gunasekara,Nguyen Thi Nhan,La Phu Hien 한국측량학회 2013 한국측량학회지 Vol.31 No.6
Coastline is the most dynamic part of seascape since its shape is affected by various factors. Coastal zone isan area with immense geological, geomorphological and ecological interest. Monitoring coastal change is veryimportant for safe navigation, coastal resource management. This paper shows a result of monitoring coastalmorphological changes using Remote Sensing and GIS. Study was carried out to obtain intensity of erosion,deposition and sand bar movement in the Red River Delta. Satellite images of ALOS/AVNIR-2 and Landsatwere used for the monitoring of coastal morphological changes over the period of 1975 to 2009. Band rationingand threshold technique was used for the coastline extraction. Tidal levels at the time of image acquisitionvaried from -0.89m to 2.87m. Therefore, coastline from another image at a different tidal level in the same yearwas considered to get the corrected coastline by interpolation technique. A series of points were generated alongthe coastal line from 1975 image and were established as reference points to see the change in later periods. The changes were measured in Euclidean distances from these reference points. Positive values representeddeposition to the sea and negative values are erosion. The result showed that the Red river delta area expandedto the sea 3500m in Red river mouth, and 2873m in Thai Binh river mouth from 1975 to 2009. The erosionprocess occurred continuously from 1975 up to now with the average magnitude 23.77m/year from 1975 to 1989and 7.85m/year from 2001 to 2009 in Giao Thuy area. From 1975 to 2009, total 1095.2ha of settlement areawas eroded by sea. On the other hand, land expanded to the sea in 4786.24ha of mangrove and 1673.98ha ofaquaculture.
Rule set of object-oriented classification using Landsat imagery in Donganh, Hanoi, Vietnam
Trinh Thi Hoai Thu,Pham Thi Lan,Tong Thi Huyen Ai 한국측량학회 2013 한국측량학회지 Vol.31 No.6
Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imageryacquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond,residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristicsof features, but also indices of water, soil, vegetation, and urban. The study selected five indices, includinglargest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized differencevegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overallaccuracy of classification result is 0.84% as the rule set is used in classification process.
Han Thi Vo,Tien Duc Dao,Tuyen Van Duong,Tan Thanh Nguyen,Binh Nhu Do,Tinh Xuan Do,Khue Minh Pham,Vinh Hai Vu,Linh Van Pham,Lien Thi Hong Nguyen,Lan Thi Huong Le,Hoang Cong Nguyen,Nga Hoang Dang,Trung 질병관리청 2024 Osong Public Health and Research Persptectives Vol.15 No.1
Objectives: The incidence of posttraumatic stress disorder (PTSD) has increased, particularly among individuals who have recovered from coronavirus disease 2019 (COVID-19) infection. Health literacy is considered a “social vaccine” that helps people respond effectively to the pandemic. We aimed to investigate the association between long COVID-19 and PTSD, and to examine the modifying role of health literacy in this association.Methods: A cross-sectional study was conducted at 18 hospitals and health centers in Vietnam from December 2021 to October 2022. We recruited 4,463 individuals who had recovered from COVID-19 infection for at least 4 weeks. Participants provided information about their sociodemographics, clinical parameters, health-related behaviors, health literacy (using the 12-item short-form health literacy scale), long COVID-19 symptoms and PTSD (Impact Event Scale-Revised score of 33 or higher). Logistic regression models were used to examine associations and interactions.Results: Out of the study sample, 55.9% had long COVID-19 symptoms, and 49.6% had PTSD. Individuals with long COVID-19 symptoms had a higher likelihood of PTSD (odds ratio [OR], 1.68; 95% confidence interval [CI], 1.63–2.12; p<0.001). Higher health literacy was associated with a lower likelihood of PTSD (OR, 0.98; 95% CI, 0.97–0.99; p=0.001). Compared to those with long COVID-19 symptoms and the lowest health literacy score, those with long COVID-19 symptoms and a 1-point health literacy increment had a 3% lower likelihood of PTSD (OR, 0.97; 95% CI, 0.96–0.99; p=0.001).Conclusion: Health literacy was found to be a protective factor against PTSD and modified the negative impact of long COVID-19 symptoms on PTSD.
Rule set of object-oriented classification using Landsat imagery in Donganh, Hanoi, Vietnam
Thu, Trinh Thi Hoai,Lan, Pham Thi,Ai, Tong Thi Huyen Korean Society of Surveying 2013 한국측량학회지 Vol.31 No.6
Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.