• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1217-1230
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• 2021

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.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.455-463
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• 2022

The current study adds to the body of knowledge about the mediation in the causal link between students' perceptions of the utility of eLearning and their learning performance. The data was collected from 500 questionnaires that were delivered to the students at the Vietnam National University of Ho Chi Minh City. Only 422 finished questionnaires were usable for analyses, indicating a responding rate of 84.4%. Multiple regressions were used to investigate causal correlations, whereas Goodman's (1960) techniques were used to investigate mediating relationships. The major findings reveal that both the utility and adoption of eLearning have an impact on students' learning performance, with usefulness being a crucial determinant of eLearning adoption for study. More meaningfully, statistical evidence on the mediation of adopting eLearning for study in the causal linkage from the usefulness of eLearning perceived by students to their learning performance was provided. The relevance of using eLearning for study is stressed in this study, where it is not only one of the key antecedents of their learning performance, but also acts as a mediator between the usefulness of eLearning and learning performance in the research model.

• Genomics & Informatics
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• v.21 no.3
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• pp.28.1-28.13
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• 2023

Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer's disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer's Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.301-313
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• 2020

This study is a study on the interlocking method between emergency preparedness simulation model and military exercise war game model. The national emergency preparedness government exercises are being carried out by a message exercise and technology development for simulation models is being carried out to create a situation similar to the actual practice. In order to create a situation similar to the actual war, the military situation must be reflected and to do so, a link with the military exercise war game model is needed. The military exercise war game model applies HLA/RTI, which is a standardized interlocking method for various models such as Taegeuk JOS, and it is necessary to apply HLA/RTI linkage method to link with these military exercise war game models. In addition, since the emergency preparedness simulation model requires limited information such as enemy location and enemy attack situation on major facilities in the military exercise model, a method of interlocking that can select and link information is required. Therefore, in this study, the interlocking interface design plan is presented in order to selectively link the interlocking method and information between the emergency preparedness simulation model and the military exercise war game model. The main functions of interlocking interface include federation synchronization, storage and recovery, object management service, time management, and data filtering functions.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.1
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• pp.69-78
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• 2008

An integration study of watershed model(HSPF, Hydological Simulation program-Fortran) and reservoir water quality model (CE-QUAL-W2) was performed for the evaluation of turbid water management in Yongdam reservoir. The watershed model was calibrated and analyzed for flow and suspended solid concentration variation during rainy period, their results were inputted for reservoir water quality model as time-variable water temperature and turbidity. Results of the watershed model showed a good agreement with the field measurements of flow and suspended solid. Also, results of the reservoir water quality model showed a good agreement with the filed measurements of water balance, water temperature and turbidity using linkage of the watershed model results. Integration of watershed and reservoir model is an important in turbid water management because flow and turbidity in stream and high turbidity layer in reservoir could be predicted and analyzed. In this study, the integration of HSPF and CE-QUAL-W2 was applied for the turbid water management in Yongdam reservoir, where it is evaluated to be appliable and important.

• Atmosphere
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• v.16 no.4
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• pp.259-267
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• 2006

In the present study, the neural network (NN) model with cluster analysis method was developed to predict storm surge in the whole Korean coastal regions with special focuses on the regional extension. The model used in this study is NN model for each cluster (CL-NN) with the cluster analysis. In order to find the optimal clustering of the stations, agglomerative method among hierarchical clustering methods was used. Various stations were clustered each other according to the centroid-linkage criterion and the cluster analysis should stop when the distances between merged groups exceed any criterion. Finally the CL-NN can be constructed for predicting storm surge in the cluster regions. To validate model results, predicted sea level value from CL-NN model was compared with that of conventional harmonic analysis (HA) and of the NN model in each region. The forecast values from NN and CL-NN models show more accuracy with observed data than that of HA. Especially the statistics analysis such as RMSE and correlation coefficient shows little differences between CL-NN and NN model results. These results show that cluster analysis and CL-NN model can be applied in the regional storm surge prediction and developed forecast system.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.990-1001
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• 2015

This paper presents analysis of Switched Reluctance Machine (SRM) using Geometry Based Analytical Model (GBAM), Finite Element Analysis (FEA) and Fourier Series Model (FSM) with curve fitting technique. Further a Transient Analysis (TA) technique is proposed to corroborate the analysis. The main aim of this paper is to give in depth procedure in developing a Geometry Based Analytical Model of Switched Reluctance Machine which is very accurate and simple. The GBAM is developed for the specifications obtained from the manufacturer and magnetizing characteristic of the material used for the construction. Precise values of the parameters like Magneto Motive Force (MMF), flux linkage, inductance and torque are obtained for various rotor positions taking into account the Fringing Effect (FE). The FEA model is developed using MagNet7.1.1 for the same machine geometry used in GBAM and the results are compared with GBAM. Further another analytical model called Fourier Series Model is developed to justify the accuracy of the results obtained by the methods GBAM and FEA model. A prototype of microcontroller based SRM drive system is constructed for validating the analysis and the results are reported.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.4 no.2
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• pp.34-44
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• 1986

A data base system for a minicomputer, designed on the basis of the concept of Relational model, is proposed in this thesis. It is a module of reentrant programs, which can serve multi-users concurrently and interactivelv. Relational calculus is chosen as a data sublanguage. The inverted-list file structure is used for the physical storage structuse with the technique of seperating data and their relationships, while data model records, which contain the information of the logical data organization and linkage to a physical structure, con struct the data model. The retrieval is performed mainly with these.

• Journal of Biosystems Engineering
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• v.13 no.4
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• pp.1-8
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• 1988

A series of soil bin experiments was carried out on land to evaluate the soil physical properties whether they are pertinent to soil-wheel system and to investigate if true model theory u applicable to powered rigid wheel-soil system. Four different sized wheels having diameter of 45, 60, 75 and 90 em were wed for the experiment. The following conclusion was derived from the study. (1) True model theory can be sufficiently utilized to study the wheel traction and linkage on lands. (2) For both dry and wet sands, Cone Index(CI) and soil shear parameters (c, ${\phi}$) with bulk density (${\gamma}$) were found to be good measures of soil physical properties which are pertinent to predict the performance of the powered rigid wheel-soil system.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.89-96
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• 1997

A robust speed control scheme for a brushless DC(BLDC) motor using an adaptive input-output linearization technique is presented. By using this technique, the nonlinear motor model can be linearized in Brunovski canonical form, and the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory and positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative experiments.