Determinants of Foreign Direct Investment: Evidence from Vietnam

NGO, Minh Ngoc,CAO, Huy Hoang,NGUYEN, Long Ngoc,NGUYEN, Thuc Ngoc Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.6

The paper investigates the determinants of foreign direct investment (FDI) in Vietnam in 2000-2019 period. This study uses difference Generalized Methods of Moments (GMM) and Pooled Mean Group (PMG) to analyse panel data officially provided by General Statistical Office of Vietnam. The results show that market size impacts positively significant on FDI attraction: 1% -1.45% (PMG) and 1% -1.25% (GMM). Besides, some other factors have positive influences as labor force, macroeconomic policy, macroeconomic stability and skilled labor. Meantime, the trade openness negatively affects FDI inflows in the short-term, while not being statistically significant in the long-term. Moreover, economic shocks often have a negative impact on FDI inflows. The findings of this study lead to the following recommendations. First, authorities should pay special attention to encourage economic growth rate in Vietnam to expand market size because this is the first priority of foreign investors. Second, authorities need to continue increasing the rate of skilled labor, especially highly qualified management force, engineers and well-skilled workers. Third, the authorities should adjust trade openness to boost the role of its determinant in attracting FDI inflows. Fourth, macroeconomic stability needs to be governed by international standards in order to secure the belief of foreign investors in the long-term.

Statistical approach for figurative sentiment analysis on Social Networking Services: a case study on Twitter

Nguyen, Hoang Long,Jung, Jai E. Springer-Verlag 2017 MULTIMEDIA TOOLS AND APPLICATIONS Vol.76 No.6

<P>This paper presents a system that analyzes the sentiment of figurative language contained in short texts collected from Social Networking Services (SNS). This case study sources information from tweets on Twitter and calculates the polarity of the figurative language with three different categories (i.e., sarcastic, ironic, and metaphorical tweets). As in Medhat et al. (Ain Shams Eng J 5(4):1093-1113, 2014), Nguyen and Jung (Mob Netw Appl 20(4):475-486, 2015), many related works have used a lexical-based approach (e.g., dictionary and corpus), and machine learning-based approach (e.g., decision tree, rule discovery, and probabilistic methods) to extract sentiment in a given text. This statistical approach makes use of two main features: i) Content-based, and ii) Emotion Pattern-based. We believe that this combination offers a general method to solve the current problem and easily extends for analyzing other types of figurative languages. The proposed algorithm is evaluated by using Cosine similarity to conduct an experiment over a Data set that contains about 5,000 tweets. The results show that the FIS Model (Figurative language Identification using Statistical-based Model) works well with figurative tweets with a highest achievement of 0.7813.</P>

Privacy-Aware Framework for Matching Online Social Identities in Multiple Social Networking Services

Hoang Long, Nguyen,Jung, Jason J. Taylor Francis 2015 Cybernetics and systems Vol.46 No.1

Effects of Media on the Callogenensis and Cell Mass Production in Cell Cultures of Panax vietnamensis

Hoang Van Luong,Nguyen Van Long,Vu Binh Duong,Nguyen Linh Toan,Nguyen Van Minh,Le Bach Quang,Nam Hyuck Kim,Sang Yo Byun 한국생물공학회 2009 KSBB Journal Vol.24 No.2

This study was initiated to investigate the impacts of media types and other components on the callogenensis and cell mass production of Panax vietnamensis in the first step of the cell biomass procedure. Four media were checked: Murashige-Skoog (MS), White, Gamborg and Nitch-All. All the four media were shown potential media for Panax vietnamensis callogenensis and cell mass production, in which the MS medium showed the best results: the successful callogenensis ratio and cell mass formation were 30% and 62,93 ± 3,63 mg (DW) respectively, the Nitch medium showed the lowest results: the successful callogenensis ratio and cell mass formation were 15% and 27,10 ± 2,24 mg (DW) respectively. The results showed that the MS medium is the most suitable medium for Panax vietnamensis callogenensis and cell mass production.

Modeling of the Temperature Dependence of the Dielectric Function of Biaxial α-SnS

Nguyen Hoang Tung,Le Van Long,Kim Tae Jung,Nguyen Xuan Au,Kim Young Dong 한국물리학회 2020 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.77 No.11

The dielectric functions of biaxial α-SnS at temperatures from 27 to 350 K are modeled with an analytic expression for Tauc-Lorentz oscillators. The temperature dependence of all the obtained parameters are fitted to third-order polynomial equations. The results provide a comprehensive database of the coefficients, which allows the construction of the dielectric function of biaxial α-SnS at arbitrary temperatures from 27 to 350 K and in the spectra range from 0.73 to 6.0 eV, which can be converted to optical constant values such as refractive indices and the absorption coefficients along the armchair-, zigzag-, and c-axes directions for designing optoelectronic devices based on the SnS material.

A systematic review on metabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer

Long, Nguyen Phuoc,Yoon, Sang Jun,Anh, Nguyen Hoang,Nghi, Tran Diem,Lim, Dong Kyu,Hong, Yu Jin,Hong, Soon-Sun,Kwon, Sung Won Springer-Verlag 2018 METABOLOMICS Vol.14 No.8

High-Throughput Omics and Statistical Learning Integration for the Discovery and Validation of Novel Diagnostic Signatures in Colorectal Cancer

Long, Nguyen Phuoc,Park, Seongoh,Anh, Nguyen Hoang,Nghi, Tran Diem,Yoon, Sang Jun,Park, Jeong Hill,Lim, Johan,Kwon, Sung Won MDPI 2019 INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES Vol.20 No.2

<P>The advancement of bioinformatics and machine learning has facilitated the discovery and validation of omics-based biomarkers. This study employed a novel approach combining multi-platform transcriptomics and cutting-edge algorithms to introduce novel signatures for accurate diagnosis of colorectal cancer (CRC). Different random forests (RF)-based feature selection methods including the area under the curve (AUC)-RF, Boruta, and Vita were used and the diagnostic performance of the proposed biosignatures was benchmarked using RF, logistic regression, naïve Bayes, and k-nearest neighbors models. All models showed satisfactory performance in which RF appeared to be the best. For instance, regarding the RF model, the following were observed: mean accuracy 0.998 (standard deviation (SD) < 0.003), mean specificity 0.999 (SD < 0.003), and mean sensitivity 0.998 (SD < 0.004). Moreover, proposed biomarker signatures were highly associated with multifaceted hallmarks in cancer. Some biomarkers were found to be enriched in epithelial cell signaling in <I>Helicobacter pylori</I> infection and inflammatory processes. The overexpression of <I>TGFBI</I> and <I>S100A2</I> was associated with poor disease-free survival while the down-regulation of <I>NR5A2</I>, <I>SLC4A4</I>, and <I>CD177</I> was linked to worse overall survival of the patients. In conclusion, novel transcriptome signatures to improve the diagnostic accuracy in CRC are introduced for further validations in various clinical settings.</P>

Equivalent Convective Heat Transfer Coefficient for Boundary Conditions in Temperature Prediction of Early-Age Concrete Elements Using FD and PSO

Long Nguyen-Ngoc,Tu Anh Do,Viet Hai Hoang,Tuyet Thi Hoang,Tam Duc Tran 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.6

Engineering infrastructure includes a large number of concrete structures. The main binder used in concrete is Portland cement, which reacts with water when mixing. During the chemical reaction (cement hydration) heat is released causing non-uniform temperature distribution and subsequent internal stresses that may crack the concrete. Therefore, accurate prediction of concrete temperature evolution in design and control of concrete temperature in construction are crucial tasks for engineers. This paper presents the development of a finite difference (FD) model for predicting thermal behavior of concrete structures during cement hydration. A formwork or insulation layer that covers the outer of the concrete was accounted for in the model. The temperature profiles calculated by the proposed model show close agreement with those measured from a concrete bridge footing and a concrete cube. The Particle Swarm Optimization (PSO) algorithm was adopted to compute an “equivalent convection coefficient” for the convection boundary condition in the simplified model for several common insulation materials. The results show that using the simplified model along with an equivalent convection coefficient can give a significant reduction in the computation time while the accuracy is still maintained. In addition, an equation for estimating an equivalent convection coefficient for a given insulation material was developed for design and practical purposes. The proposed method can be used in the design of concrete structures and control of concrete temperature to prevent early-age thermal cracking thus ensuring the expected durability and service life. From the obtained results, varying equivalent convection values are also recommended to be used for different insulation materials.

The Development of Accurate GPS Module Using Discrete-Time H<SUB>∞</SUB> Filter

Nguyen Hoang(윈황휴),Nguyen Phi Long(윈필롱),Lee Sang-Hoon(이상훈),Park Ok-Deuk(박옥득),Kim Hyun-Su(김현서),Kim Han-Sil(김한실) 대한전기학회 2006 대한전기학회 학술대회 논문집 Vol.2006 No.10

In this paper, we present the traditional CPS Position-Velocity (PV) model to apply for both Discrete-Time Kalman Filter and Discrete-Time H<SUB>∞</SUB> Filter. The positioning algorithms of both filters are proposed for a stand-alone low-cost CPS module to increase its accuracy. For disturbance cancellation, the Kalman Filter requires the statistical information about process and measurement noises while the H<SUB>∞</SUB> Filter only requires that these noises are bounded. Experiments show that with the same measurement data, H<SUB>∞</SUB> Filter gives us better positioning results compared with Least-Squared method and Kalman Filter.

Global ginseng research

Nguyen, Phuoc Long,Nguyen, Hoang Anh,Park, Jeong Hill The Korean Society of Ginseng 2020 인삼문화 Vol.2 No.-

지금까지 Web of Science의 core collection에 나타난 인삼 관련 연구논문의 수를 분석하였다. 인삼논문이 처음 나타난 1905년부터 2019년까지 전세계에서 총 8,090편의 SCI(E) 논문이 출판된 것으로 나타났다. 그중 최근 24년, 즉, 1996년부터 2019년까지의 논문이 7,385편이었다. 1980년 18편에 불과했던 인삼 논문이 1990년에는 53편, 2000년에는 97편, 2010년에는 369편, 2019년에는 678편으로 비약적으로 증가하였다. Web of Science의 core collection에 수재된 전체 학술논문에서 인삼 논문이 차지하는 비중도 1970년 0.0008%, 1980년 0.0044%, 1990년 0.101%, 2000년 0.0141%에서 2019년에는 0.0422%로 비약적으로 증가하였다. 지난 24년간 출판된 인삼 연구논문 중 원보(노트 포함)는 7,099편, 리뷰는 286편이었다. 총 78개국 3,286개 기관에서 연구가 이루어졌으며, 1,274개 학술잡지에 논문이 수재되었다. 전체 논문 중 중국에서 연구된 논문이 40.3%로 가장 높았고, 대한민국에서 연구된 논문이 34.7%로 한국과 중국의 연구가 전체의 75%를 차지하였다. 그 다음은 미국(6.0%), 일본(4.1%), 캐나다(2.9%) 순이었다. 2013년까지는 한국에서 연구된 논문이 가장 많았으나 2014년부터 중국에서 연구된 논문의 수가 더 많아졌다. 지난 24년간 인삼은 전세계에서 가장 많이 연구된 약용식물로 인삼 다음으로는 차(6,499편), 마늘(3,641편), 은행(2,590편), 생강(1,945편) 순이었다. We conducted a comprehensive analysis of research papers on ginseng to provide an overview of global ginseng research. The qualitative and quantitative interpretation was carried out using collected data of Panax species and six other herbal plants from the Web of Science^TM Core Collection. We summarized and classified them by country/territory and institutions based on the corresponding author's institution. The first ginseng paper appeared in 1905 and since then, 8,090 papers have been published until 2019. Among them 7,385 papers were published in recent 24 years from 1996 to 2019. It was 18 papers in 1980, 53 in 1990, 97 in 2000, 369 in 2010, and increased to 678 in 2019. Proportion of ginseng papers in total number of scientific papers were also greatly increased, namely, 0.0008% in 1970, 0.0044% in 1980, 0.101% in 1990, 0.0141% in 2000, and 0.0422% in 2019. 7,099 original research papers including notes and 286 review papers were published during last 24 years. Total 3,286 institutions in 78 countries and 1,274 journals contributed to the publication of ginseng papers. Korea was the leading country in ginseng papers up to 2013, however, China took over the top from 2014. Chinese institutions contributed 40.3% of total papers followed by Korea (34.7%), USA (6.0%), Japan (4.1%), and Canada (2.9%). Ginseng was the most studied medicinal plant during last 24 years followed by tea, garlic, ginkgo, and ginger whose number of papers were 6,499, 3,641, 2,590, and 1,945, respectively.