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The Effectiveness of the Cultural Differences on HRM Practices of MNCs Operating in Vietnam

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The Effectiveness of the Cultural Differences on HRM Practic...

A Chemical Reactor Network for Oxides of Nitrogen Emission Prediction in Gas Turbine Combustor

The 4th International Conference on Engineering and Business Management

作者： nguyen Thi thanh dan Liangmou Gao School of Business administration Dongbei University of Finance and Economics

This study examines the effect of cultural differences on the performance of human resource management （HRM） practices in the multinational corporations （MNCs） operating in Vietnam. It will explore how cultural differences lead to the management differences;the relationship between critical HRM practices and Vietnamese employees. The research sought to find the key to more effectively coordinate the relations between the labor and the capital, help the MNCs’ top management when managing their workforce in Vietnam in order to enhance the performance of human resource management.

关键词： Cultural Differences Human Resource Management Practices Performance Multinational Corporations Vietnam

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Journal of Thermal Science 2014年第3期23卷 279-284页

作者： nguyen thanh Hao Industrial University of HoChiMinh City

This study presents the use of a new chemical reactor network(CRN) model and non-uniform injectors to predict the NOx emission pollutant in gas turbine combustor. The CRN uses information from Computational Fluid Dynamics(CFD) combustion analysis with two injectors of CH4-air mixture. The injectors of CH4-air mixture have different lean equivalence ratio, and they control fuel flow to stabilize combustion and adjust combustor's equivalence ratio. Non-uniform injector is applied to improve the burning process of the turbine combustor. The results of the new CRN for NOx prediction in the gas turbine combustor show very good agreement with the experimental data from Korea Electric Power Research Institute.

关键词： Chemical Reactor Networks (CRN) Computational Fluid Dynamics (CFD) Perfectly Stirred Reactor (PSR) Plug Flow Reactor (PFR) Gas Turbine Combustor Oxides of Nitrogen Emission (NOx).

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Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam nguyen nguyen Viet Tiep Quynh-Anh Thi Bui Hiep Van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of Civil Engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic Engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania Department of Civil Engineering Transilvania University of BrasovBrasov500152Romania danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India Department of Civil Engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Hyperstatic reaction method for calculations of tunnels with horseshoe-shaped cross-section under the impact of earthquakes

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Earthquake Engineering and Engineering Vibration 2020年第1期19卷 179-188页

作者： thanh nguyen Chi Gospodarikov Alexandr Saint Petersburg Mining University Saint PetersburgRussia Federation Hanoi University of Mining and Geology HanoiVietnam

Tunnels are now an integral part of the infrastructure in major cities around the world. For many reasons, these tunnels have horseshoe-shaped cross-sections with round top and flat bottom. This paper presents some improvements to the use of the Hyperstatic Reaction Method-HRM for analysing tunnels with horseshoe-shaped cross-sections when these tunnels operate under the influence of earthquakes, particularly in cases when the tunnel lining is a continuous lining. The analysis used parameters of a tunnel from the Hanoi metro system, as well as parameters of the strongest earthquake that may occur in the central Hanoi area in the improved HRM and 2 D numerical methods using the ABAQUS software. On the basis of the results obtained, the paper gives conclusions about the HRM methodology when it is used to calculate tunnels that have horseshoe cross-sections operating under the influence of earthquakes.

关键词： hyperstatic reaction method earthquake horseshoe cross-section impact tunnel

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Multilevel Threshold Based Image Denoising in Curvelet Domain

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Journal of Computer Science & Technology 2010年第3期25卷 632-640页

作者： nguyen thanh Binh Ashish Khare Department of Electronics and Communication University of Allahabad

In this paper, we propose a multilevel thresholding technique for noise removal in curvelet transform domain which uses cycle-spinning. Most of uncorrelated noise gets removed by thresholding curvelet coefficients at lowest level, while correlated noise gets removed by only a fraction at lower levels, so we used multilevel thresholding on curvelet coefficients. The threshold in the proposed method depends on the variance of curvelet coefficients, the mean and the median of absolute curvelet coefficients at a particular level which makes it adaptive in nature. Results obtained for 2-D images demonstrate an improved performance over other recent related methods available in literature.

关键词： curvelet transform denoising multilevel thresholding cycle-spinning

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Schistosomal appendicitis:A serious and often misdiagnosed condition

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World Journal of Clinical Cases 2025年第10期13卷 62-64页

作者： Phi Duong nguyen thanh Kien Lam Orthopaedic-Burn-Plastic Surgery City Children’s HospitalHo Chi Minh City 71815Viet Nam The Faculty of Medical Technology Van Lang UniversityHo Chi Minh City 700000Viet Nam

Schistosomal appendicitis(SA)is a rare but serious complication of schistosomiasis,a parasitic disease affecting over 250 million people worldwide.A recent retrospective study by Wang et al provides important insights into the clinicopathological characteristics of *** study compared 136 cases of SA to 5418 cases of non-SA over a ten-year *** findings include a higher average age of SA patients(61.73 years vs 35.8 years for non-SA),a higher proportion of acute on chronic appendicitis(33.1%vs 16%),and a significantly higher incidence of colorectal cancer(11.7%vs 2.2%).Despite these differences,SA remains a diagnostic challenge due to its nonspecific clinical presentation and lack of specific laboratory *** study also highlights the persistent prevalence of SA,accounting for 1.6%-3.4%of all appendicitis cases each year from 2013 to *** findings underscore the need for enhanced awareness,early detection,and prompt treatment of SA in endemic *** the association with colorectal cancer,patients with SA require thorough screening and *** research into the pathogenesis and diagnostic markers of SA is *** the global battle against schistosomiasis continues,targeted efforts to diagnose and manage SA can significantly improve patient outcomes.

关键词： Schistosomal appendicitis Schistosomiasis Colorectal cancer Misdiagnosis Clinicopathological characteristics

Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh Thi Bui Dam Duc nguyen Hiep Van Le Indra Prakash Binh Thai Pham Civil Engineering Department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

Bubble entrapment during the recoil of an impacting droplet

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Microsystems & Nanoengineering 2020年第1期6卷 768-774页

作者： thanh-Vinh nguyen Masaaki Ichiki Sensing System Research Center National Institute of Advanced Industrial Science and Technology(AIST)Japan1-2-1 NamikiTsukuba-shiIbaraki 305-8564Japan

When a droplet impacts a(super-)hydrophobic surface,there is a range of Weber numbers within which bubble entrapment will occur during droplet recoil due to closure of the air cavity developed when the droplet spreads out during the *** this study,we studied bubble entrapment using a microelectromechanical system(MEMS)-based acoustic sensor fabricated on a *** found that bubble entrapment is followed by an acoustic vibration that can be detected by the ***,the frequency of the vibration is inversely proportional to the radius of the droplet,which indicates that this vibration is the resonant oscillation of the ***,the MEMS-based acoustic sensor can be used not only to detect but also to measure the size of the entrapped ***,we demonstrated that it is possible to prevent bubble formation by allowing the air to escape to the underside of the droplet contact *** can be done by creating through-holes on the substrate or decorating the substrate with sufficiently large textures.

关键词： bubble radius resonant

Study of vertically ascending flight of a hawkmoth model

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Acta Mechanica Sinica 2020年第5期36卷 1031-1045,I0002页

作者： Anh Tuan nguyen Vu dan thanh Le The Hung Tran V.N.Due Van Binh Phung Faculty of Aerospace Engineering Le Quy Don Technical UniversityHanoiVietnam Institute of Theoretical and Applied Research.Duy Tan University HanoiVietnam Division of Construction Computation Institute for Computational ScienceTon Due Thang UniversityHo Chi Minh CityVietnam Faculty of Civil Engineering Ton Due Thang UniversityHo Chi Minh CityVietnam

This paper provides insight into the wing kinematics,the power requirement and the dynamic stability characteristics of a hawkmoth model in vertically ascending *** wing kinematics of the hawkmoth model is obtained based on the minimum required power *** optimization process is conducted using genetic and simplex algorithms that are coupled with an artificial neural network to rapidly predict the aerodynamic force and required *** training data for the neural network are generated from an unsteady vortex-lattice *** to hover,the results in this study show the larger flapping frequency and the smaller rotation amplitude of the hawkmoth wing kinematics in ascending ***,more power is required when the ascending speed *** conducting a dynamic modal analysis based on a cycle-average approach,the certain effect of the ascending speed on the modal structures of the hawkmoth model was observed.

关键词： Hawkmoth Ascending flapping flight-Genetic algorithm Artificial neural network Flight dynamic stability