Foreign Direct Investment -Small and Medium Enterprises Linkages and Global Value Chain Participation: Evidence from Vietnam

NGUYEN, Thi Minh Thu,NGUYEN, Thi Tuong Anh,NGUYEN, Thi Thuy Vinh,PHAM, Huong Giang Korea Distribution Science Association 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.3

Using a multinomial logit model with the panel-data set of Vietnam manufacturing firms, this paper investigates the impacts of foreign direct investment (FDI) - small and medium enterprises (SMEs) linkages and other factors on SMEs' participation in the global value chain (GVC). We consider GVC firms are those engaging in any of the three modes including (i) using domestic inputs to export (D2E), (ii) using imported inputs to produce for the domestic market (I2P), (iii) using imported inputs to export (I2E). We discover that FDI-SME linkages statistically encourage Vietnamese SMEs to integrate into the GVC via I2P and I2E, while no statistical association between FDI-SME linkage and D2E participation is found. GVCs participation likelihood is also positively correlated with the introduction of new product introduction. The establishment of firms' production facilities in industrial zones and foreign ownership are both reported to be significantly decisive factors to SMEs' decisions on GVC participation. Besides, there is a strong association between firms' attributes, i.e. employment, capital intensity as well as financial access, and their participation in the GVC. Local governance quality (proxied by the Provincial Competitiveness Index) and the share of skilled labor at the province-level can facilitate firms' integration into GVCs, while greater market concentration may be a hurdle to such potential.

Compensating Background for Noise due to Camera Vibration in Uncalibrated-Camera-Based Vehicle Speed Measurement System

Thuy Tuong Nguyen,Xuan Dai Pham,Ji Ho Song,Seunghun Jin,Dongkyun Kim,Jae Wook Jeon IEEE 2011 IEEE Transactions on Vehicular Technology VT Vol.60 No.1

<P>Vision-based vehicle speed measurement (VSM) is one of the most convenient methods available in intelligent transportation systems. Existing methods use an uncalibrated camera to measure vehicle speed, but they do not consider the possibility of camera vibration that leads to poor measurement results. This paper considers the issue when the camera is tilted downward and mounted at a fixed location on a bridge crossing the target street. The camera may vibrate due to wind or bridge movement. A vision-based speed measurement system is described in this paper, along with the vertical-and-horizontal-histogram-based method, which is used to compensate the background of an incoming image. This novel method is utilized to eliminate noise coming from the displacement between an incoming image and a background image that is caused by camera vibration over time. Moreover, a method is presented to automatically detect the vanishing point based on the Hough transform and quadtree. Experimental comparisons of the system to those of the vehicle's own speedometer show that the proposed approach yields a satisfactory estimate of vehicle speed.</P>

Scaling-Translation Parameter Estimation using Genetic Hough Transform for Background Compensation

( Thuy Tuong Nguyen ),( Xuan Dai Pham ),( Jae Wook Jeon ) 한국인터넷정보학회 2011 KSII Transactions on Internet and Information Syst Vol.5 No.8

Background compensation plays an important role in detecting and isolating object motion in visual tracking. Here, we propose a Genetic Hough Transform, which combines the Hough Transform and Genetic Algorithm, as a method for eliminating background motion. Our method can handle cases in which the background may contain only a few, if any, feature points. These points can be used to estimate the motion between two successive frames. In addition to dealing with featureless backgrounds, our method can successfully handle motion blur. Experimental comparisons of the results obtained using the proposed method with other methods show that the proposed approach yields a satisfactory estimate of background motion.

A Pragmatic Analysis of Vietnamese EFL Textbooks: The Case of Disagreement

Lan Tuong Nguyen Bui,Minh Thi Thuy Nguyen 아시아테플 2023 The Journal of Asia TEFL Vol.20 No.4

The present study evaluates how upper-secondary school English language textbooks in Vietnam teach disagreement, a speech act that is central to classroom discourse but has received limited attention in textbook evaluation studies. The study employs an analytical framework derived from previous pragmatics research to analyse three textbooks and their accompanying audio files. The quantitative and qualitative analysis focused on the distribution of three key features: disagreement forms, contextual and metapragmatic information, and types of instructional activities aimed at enhancing students' pragmatic awareness. The study found a mismatch between the textbook input and authentic language use reported in previous pragmatics research, with textbooks featuring more instances of strong disagreement compared to disagreement prefaced with agreement. In addition, the textbooks presented a limited range of interactional resources for managing disagreement, thus restricting students' exposure to pragmatic input. Finally, while the textbooks exposed students to disagreement in interactive situations, they lacked explicit instruction to guide students to notice how disagreement is performed in context. The study highlights the need for more attention to be given to pragmatic competence in English language teaching materials, particularly with regard to the teaching of disagreement, and provides recommendations for improving the quality of EFL textbooks.

A Fast Evolutionary Algorithm for Real-Time Vehicle Detection

Vinh Dinh Nguyen,Thuy Tuong Nguyen,Dung Duc Nguyen,Sang Jun Lee,Jae Wook Jeon IEEE 2013 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY Vol.62 No.6

<P>The evolutionary algorithm (EA) is an effective method for solving various problems because it can search through very large search spaces and can quickly come to nearly optimal solutions. However, existing EA-based methods for vehicle detection cannot achieve high performance because their fitness functions depend on sensitive information, such as edge or color information on the preceding vehicle. This paper focuses on improving the performance of existing evolutionary-based methods for vehicle detection by introducing an effective fitness function that can more accurately capture a vehicle's information by combining a disparity map, edge information, and the position and motion of the preceding vehicle. The proposed method can detect multiple vehicles by using a turn-back genetic algorithm (GA) and can prevent false detection by using motion detection. Our fitness function is designed in a typical manner along with the fitness parameters. These parameters are usually selected using heuristic methods, making the choice of optimal parameters difficult. Therefore, this paper proposes a new approach to estimating optimal fitness parameters using EA and the least squares method. Robustness testing showed that the proposed method provides detection rate (DR) results close to those obtained using a state-of-the-art system and outperforms other dominant vehicle-detection-based EAs.</P>

Real-Time Vehicle Detection Design and Implementation on GPU

Vinh Dinh Nguyen,Thuy Tuong Nguyen,Dung Duc Nguyen,Jae Wook Jeon 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10

Vehicle detection and distance estimation system has become important due to their assistance in reducing vehicle accidents. Therefore, an efficient vehicle detection and distance estimation algorithm using a knowledge-based method and image segmentation technique has been developed. The proposed algorithm can detect and estimate the distance of the preceding vehicle under various road conditions using a single CCD camera of 16 mm and 25 mm focal lenghts mounted on a vehicle. A GPU implementation of this proposed algorithm is introduced to enable our proposed system to support real-time processing. Experimental results under various road and weather conditions prove that our proposed system is suitable for a real-time system.

Robot Supporting for Deaf and Less Hearing People

Nguyen Truong Thinh,Tuong Phuoc Tho,Tran Thi Thuy Nga 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10

This paper discusses the development of a service robot for translating spoken language text into signed languages and vice versa. The motivation for our study is the improvement of accessibility to public information announcements for deaf and less hearing people. The robot can translate Vietnamese sign language into speech and recognize Vietnamese/English speech to suitable gesture/sign language. The paper describes the use of service robot in a sign language machine translation system. Several sign language visualization methods were evaluated on the robot. In order to perform this study a machine translation service robot that uses display screen on robot as service-delivery device was developed as well as a 3D avatar. It was concluded that service robot are suitable service-delivery platforms for sign language machine translation systems.

An Improved Vision-basedWastewater Velocity Measurement System using Discontinuity-Preserving Smoothing and GPU Acceleration

Cuong Cao Pham,Thuy Tuong Nguyen,Jae Wook Jeon 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10

Automatic long-term measuring wastewater velocity is an important and challenging task in hydraulic systems. This paper proposed a vision-based wastewater velocity measurement method using Bilateral filter that is a discontinuitypreserving smoothing as a prior-processing step. Experimental results showed that using Bilateral filter can improve estimation accuracy over existing methods. An effective background creation algorithm and simple floating waste tracking algorithm based on binary blob properties are also discussed in this paper. Furthermore, by implementing the proposed method on massively parallel GPU (graphics processing units) using the CUDA (compute unified device architecture) programming model, we can achieve a satisfactory acceleration to apply in real-time applications. Memory usage optimization methods are discussed and analyzed for effective implementation in graphics hardware.

An FPGA-based Parallel Hardware Architecture for Real-time Eye Detection

Dongkyun Kim,Junhee Jung,Thuy Tuong Nguyen,Daijin Kim,Munsang Kim,Key Ho Kwon,Jae Wook Jeon 대한전자공학회 2012 Journal of semiconductor technology and science Vol.12 No.2

Eye detection is widely used in applications, such as face recognition, driver behavior analysis, and human-computer interaction. However, it is difficult to achieve real-time performance with software-based eye detection in an embedded environment. In this paper, we propose a parallel hardware architecture for real-time eye detection. We use the AdaBoost algorithm with modified census transform(MCT) to detect eyes on a face image. We parallelize part of the algorithm to speed up processing. Several downscaled pyramid images of the eye candidate region are generated in parallel using the input face image. We can detect the left and the right eye simultaneously using these downscaled images. The sequential data processing bottleneck caused by repetitive operation is removed by employing a pipelined parallel architecture. The proposed architecture is designed using Verilog HDL and implemented on a Virtex-5 FPGA for prototyping and evaluation. The proposed system can detect eyes within 0.15 ㎳ in a VGA image.

An FPGA-Based Vehicle Speed Measurement System Using an Uncalibrated Camera

JI HO SONG,Nguyen Tuong Thuy,Seunghun Jin,Dongkyun Kim,Jae Wook Jeon 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10

Measuring a vehicle’s speed using a video image is an important technique in an intelligent transportation system. This paper presents a hardware implemented vehicle speed measurement (VSM) system. The operation of the system consists of three steps. First, we remove vehicles from a series of captured images to create a background. To do this, we introduce a simplified exclusion algorithm optimized to the hardware. Second, we subtract the background from the incoming image and concurrently apply affine rectification. Finally, based on the rectified image, we track the vehicles and measure the velocity. The system uses two SRAMs and one FIFO to store images. At each step, we present a memory management method of two SRAMs to store multiple images in one SRAM. This enables our system to obtain two images in a single full memory scan. Our system obtained ± 7.5% velocity error using an experiment comparing the vehicle’s speedometer and the vision-based measured velocity.