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.

Improvement in carrier collection at the i/n interface of graded narrow-gap hydrogenated amorphous silicon germanium solar cells

Pham, Duy Phong,Kim, Sangho,Park, Jinjoo,Le, Anh Huy Tuan,Cho, Jaehyun,Yi, Junsin ELSEVIER SCIENCE 2017 JOURNAL OF ALLOYS AND COMPOUNDS Vol.724 No.-

<P><B>Abstract</B></P> <P>We examined different buffer layers at the i/n interface of narrow-gap amorphous silicon germanium alloy (a-SiGe:H)-based thin-film solar cells. These buffers included a conventional hydrogenated amorphous silicon (a-Si:H), an inversely graded hydrogenated amorphous silicon germanium, and a crystalline seed buffer (CSB). The solar cell with the CSB shows the highest performance, of 10%. The better carrier extraction at the rear side of the device is attributed to the role of the CSB layer. The effect of CSB thickness from 50 nm to 100 nm on cell performance was examined. Cell efficiency increased with the buffer thickness up to 80 nm and decreased with buffer thickness of 100 nm. This decrease can be attributed to increased defect densities of the buffer due to less efficient passivation of amorphous phase at the crystalline column boundaries.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Carrier extraction at the i/n interface is improved by crystalline seed buffer (CSB) layer. </LI> <LI> Role of crystalline seed buffer layer is discussed in detail. </LI> <LI> High efficiency of 10% of graded a-SiGe:H thin film solar cell is obtained with CSB buffer. </LI> </UL> </P>

Controlling a crystalline seed layer for mirocrystalline silicon oxide window layer in rear emitter silicon heterojunction cells

Pham, Duy Phong,Kim, Sangho,Lee, Sunhwa,Le, Anh Huy Tuan,Cho, Eun-Chel,Park, Jinjoo,Yi, Junsin Elsevier 2019 Infrared physics & technology Vol.102 No.-

<P><B>Abstract</B></P> <P>Remarkable progress has been made in the improvement of rear-emitter silicon heterojunction (RE-SHJ) solar cells with the use of very thin n-type front contact layers. However, further reducing the thickness of the front window layers while maintaining high conductivity for mitigating the parasitic absorption and carrier collection loss has proven challenging. In this study, we implement controlling a seed layer for achieving ultra-thin, high crystalline and conductivity of n-type hydrogenated microcrystalline silicon oxide (n-µc-SiO<SUB>x</SUB>:H) front window layer in RE-SHJ solar cells. By using a seed layer, the crystallinity confirmed by Raman and TEM measurements, and the conductivity of the n-µc-SiO<SUB>x</SUB>:H front layers are significantly enhanced compared with that without using the seed layer. This leads to a remarkable increase in the open-circuit voltage (<I>V</I> <SUB>oc</SUB>) by 6 mV and fill factor (<I>FF</I>) by 4.11% while maintaining a high short-circuit current density (<I>J</I> <SUB>sc</SUB>) in range of 38 mA/cm<SUP>2</SUP>. A high cell performance of 21.1% is obtained with the use of an optimised seed layer.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Effect of deposition power densities on seed-growth via TEM measurement was discussed. </LI> <LI> High crystallinity and conductivity of ultra-thin n-µc-SiOx:H front layer for RE-SHJ solar cells. </LI> <LI> V<SUB>oc</SUB> enhancement by 6 mV and fill factor by 4.11% due to optimization of seed layer. </LI> </UL> </P>

A Statistical Data-Filtering Method Proposed for Short-Term Load Forecasting Models

Duong Minh Bui,Phuc Duy Le,Tien Minh Cao,Hung Nguyen,Trang Thi Pham,Duy Anh Pham 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.5

Reliability assessment of the SCADA-system based load data is necessary for improving accuracy of short-term load forecasting (STLF) methods in a distribution network (DN). Specifi cally, the reliability evaluation of the load data is to properly eliminate noise/outliers caused by random power consumption behaviors or the sudden change in load demand from industrial and residential customers in the DN. Thus, this paper proposes a novel statistical data-fi ltering method, working at an input data pre-processing stage, which will evaluate the reliability of input load data by analyzing all possible data confi dence levels in order to fi lter-out the noise/outliers for accuracy improvement of diff erent short-term load forecasting models. The proposed statistical data-fi ltering method is also compared to other existing data-fi ltering methods (such as Kalman Filter, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Discrete Wavelet Transform (DWT) and Singular Spectrum Analysis (SSA)). Moreover, several case studies of short-term load forecasting for a typical 22 kV distribution network in Vietnam are conducted with an Artifi cial Neural Network (ANN) model, a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) model, a combined model of Long Short-Term Memory Network and Convolutional Neural Network (LSTM-CNN), and a conventional Autoregressive Integrated Moving Average (ARIMA) model to validate the statistical data-fi ltering method proposed. The achieved results demonstrate which the STLF using ANN, LSTM-RNN, LSTMCNN, and ARIMA models with the statistical data-fi ltering method can all outperform those with the existing data-fi ltering methods. Additionally, the numerical results also indicate that in case the SCADA-based load data is normally distributed, time-series forecasting models should be more preferred than neural network models; otherwise, when the SCADA-based load data contains multiple normally distributed sub-datasets, neural network-based prediction models are highly recommended.

3D-Brain MRI Segmentation Based on Improved Level Set by AI Rules and Medical Knowledge Combining 3 Classes-EM and Bayesian Method

Nguyen Ho Minh Duy,Tran Anh Tuan,Nguyen Hai Duong,Tran Anh Tuan,Nguyen Kim Dao,Atsuo Yoshitaka,Jin Young Kim,Seung Ho Choi,Pham The Bao 한국정보기술학회 2016 한국정보기술학회논문지 Vol.14 No.5

MRI and CT images are the most popular formats assisting a doctor in diagnosis and treatment, but highly accurate segmentation is a challenging problem due to intensity inhomogeneity and environmental noises. In this paper, we introduce an appropriate and effective automatic approach to facilitate this problem in two stages. In the first stage, skull region is removed from the brain by morphological active contour and level set process. Moreover, in level set process, some AI rules are defined on slice positions of brain to increase the accuracy. In the second stage, a modified EM method is performed on the resultant skull-stripping image to identify some candidate main regions of CSF (cerebro-spinal fluid), GM (gray matter), and WM (white matter). The candidate regions are then re-estimated into the proper CSF, GM, and WM through a Bayesian Estimation Process. The experimental results show that the proposed approach obtains a robust segmentation for IBSR, OASIS and Korean Hospital database. With the proposed AI-rules, the level set method gets good skull-stripping images regardless of MRI slice position in bran. Also, Bayesian postprocessing can improve the segmentation performance by 10~15% in CSF, GM and WM ratios compared the basic EM algorithm.

Electrical Conduction and Resistance Switching Mechanisms of Ag/ZnO/Ti Structure

Nguyen, Trung Do,Pham, Kim Ngoc,Tran, Vinh Cao,TuanNguyen, Duy Anh,Phan, Bach Thang Institute of Korean Electrical and Electronics Eng 2013 전기전자학회논문지 Vol.17 No.3

We investigated electrical conduction and resistance switching behavior of the Ag/ZnO/Ti structures for random access memory devices. These films were prepared on glass substrate by dc sputtering technique at room temperature. The resistance switching follows unipolar switching mode with small switching voltages (0.4 V - 0.6 V). Two electrical conduction mechanisms dominating the LRS and HRS are Ohmic and trap-controlled space charge limited current, respectively. These both conductions are consistent with the filamentary model. Based on the filamentary model, the switching mechanism was also interpreted.

Haidilao's Journey to Captivate Global Diners with the Most Traditional Chinese Food

정경화,Hien Thu Pham,Nghia Trong Phung,Phuong Ngoc Minh Tran,Quan Duy Anh Nguyen Academy of Asian Business (AAB) 2022 Academy of Asian Business Review Vol.8 No.1

Haidilao, which was established in 1994 in China, is a global hot pot chain. After going through several crises, Haidilao succeeded to attract global diners and became a world-renowned restaurant chain. This case introduces Haidilao’s globalization story which is unprecedentedly successful in the foodservice industry. Through continuous innovation, Haidilao has built a unique system in terms of foodservice operations. First, it set up a closely connected supply chain network that can stably and rapidly supply high-quality raw food materials to overseas restaurants. Secondly, it developed unique and diverse service practices that other firms cannot imitate. Thirdly, it established an effective human resources management system that can foster employees with good attitudes and high commitments. These success factors of Haidilao in the global market are analyzed in detail. Then, implications are discussed. Lastly, future challenges and recommendations are followed. This case serves as a valuable lesson for foodservice firms that want to enter and survive in the competitive global market.

Artocarpus nigrifolius: Cytotoxic and Antibacterial Constituents

Hoi, Tran Minh,Anh, Ha Van,Huong, Nguyen Thi Thanh,Tuyen, Nguyen Van,Anh, Le Thi Tu,Tra, Nguyen Thanh,Cham, Ba Thi,Ha, Nguyen Thi Thu,Linh, Pham Thuy,Tien, Doan Duy,Kiem, Phan Van,Ban, Ninh Khac,Kukha The Korean Society for Applied Biological Chemistr 2013 Applied Biological Chemistry (Appl Biol Chem) Vol.56 No.6

Six known compounds including ${\alpha}$-amyrin 3-acetate (1), ${\beta}$-sitosterol (2), betulinic acid (3), friedelan-3-one (4), artochamin B (5), and 2-C-methyl-D-erythritol 4-O-${\alpha}$-D-glucopyranoside (6) were isolated from the stem barks and leaves of Artocarpus nigrifolius (Moraceae) for the first time. Their structures were identified by spectroscopic methods as well as comparison with literatures. Cytotoxicity and antibacterial activity of 1-6 were evaluated. Results showed that artochamin B (5) possessed the highest cytotoxicity towards MCF7, Lu, HepG2, and KB cell lines with $IC_{50}$ values of 4.59, 20.00, 3.60, and $1.18{\mu}g/mL$, respectively. It also inhibited the growth of Gram-positive bacteria (Bacillus subtilis, Staphylococcus aureus), whereas inactive on the growth of both Gram-negative bacteria and yeast.

Multi-Strain Probiotics Enhance the Bioactivity of Cascara Kombucha during Microbial Composition-Controlled Fermentation

Thach Phan Van,Quang Khai Phan,Hoa Pham Quang,Gia Bao Pham,Ngoc Han Ngo Thi,Hong Tham Truong Thi,Anh Duy Do 한국식품영양과학회 2023 Preventive Nutrition and Food Science Vol.28 No.4

Kombucha is a widely consumed fermented tea beverage with diverse health benefits. In a previous study, we demonstrated that the use of cascara as a substrate results in a special kombucha beverage with high bioactivity. Traditional kombucha fermentation using a symbiotic culture of bacteria and yeast (SCOBY) can lead to inconsistent product quality because of the lack of control over microbial composition. We successfully isolated and identified yeast and bacteria, including Saccharomyces cerevisiae, Komagataeibacter rhaeticus, and Lactobacillus brevis that are appropriate starter cultures for cascara kombucha fermentation. We also demonstrated that a supplementation with lactic acid bacteria (LAB) and a mixture of S. cerevisiae and K. rhaeticus resulted in higher total polyphenol and flavonoid content of cascara kombucha compared with the traditionally fermented product using SCOBY as the inoculum. The free radical scavenging activity, inhibitory effects on α-amylase, tyrosinase activity, and antibacterial properties of cascara kombucha were also enhanced as a result of LAB supplement. These findings provide valuable insights into the controlled microbiological composition required for the fermentation of cascara kombucha, thereby ensuring consistent quality and enhanced bioactivity of the product. Further, the use of cascara as a substrate for kombucha production not only offers various health benefits and biological effects, but also repurposes by-products from the coffee industry, which contributes to sustainable development and is eco-friendly.

Understanding the COVID-19 Infodemic: Analyzing User-Generated Online Information During a COVID-19 Outbreak in Vietnam

Ha-Linh Quach,Thai Quang Pham,Ngoc-Anh Hoang,Dinh Cong Phung,Viet-Cuong Nguyen,Son Hong Le,Thanh Cong Le,Dang Hai Le,Anh Duc Dang,Duong Nhu Tran,Nghia Duy Ngu,Florian Vogt,Cong-Khanh Nguyen 대한의료정보학회 2022 Healthcare Informatics Research Vol.28 No.4

Objectives: Online misinformation has reached unprecedented levels during the coronavirus disease 2019 (COVID-19) pandemic. This study analyzed the magnitude and sentiment dynamics of misinformation and unverified information about public health interventions during a COVID-19 outbreak in Da Nang, Vietnam, between July and September 2020. Methods: We analyzed user-generated online information about five public health interventions during the Da Nang outbreak. We compared the volume, source, sentiment polarity, and engagements of online posts before, during, and after the outbreak using negative binomial and logistic regression, and assessed the content validity of the 500 most influential posts. Results: Most of the 54,528 online posts included were generated during the outbreak (n = 46,035; 84.42%) and by online newspapers (n = 32,034; 58.75%). Among the 500 most influential posts, 316 (63.20%) contained genuine information, 10 (2.00%) contained misinformation, 152 (30.40%) were non-factual opinions, and 22 (4.40%) contained unverifiable information. All misinformation posts were made during the outbreak, mostly on social media, and were predominantly negative. Higher levels of engagement were observed for information that was unverifiable (incidence relative risk [IRR] = 2.83; 95% confidence interval [CI], 1.33–0.62), posted during the outbreak (before: IRR = 0.15; 95% CI, 0.07–0.35; after: IRR = 0.46; 95% CI, 0.34-0.63), and with negative sentiment (IRR = 1.84; 95% CI, 1.23–2.75). Negatively toned posts were more likely to be misinformation (odds ratio [OR] = 9.59; 95% CI, 1.20–76.70) or unverified (OR = 5.03; 95% CI, 1.66–15.24). Conclusions: Misinformation and unverified information during the outbreak showed clustering, with social media being particularly affected. This indepth assessment demonstrates the value of analyzing online “infodemics” to inform public health responses.