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A Study on Effects of Blade Pitch on the Hydrodynamic Performances of a Propeller by Using CFD

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Journal of Shipping and Ocean Engineering 2018年第1期8卷 36-42页

作者： nguyen chi cong LUONG Ngoc Loi NGO Van He Vietnam Marine University Haiphong 180000 Vietnam Hanoi University of Science and Technology Hanoi 10000 Vietnam

The main objective of this work is to use the CFD （Computational Fluid Dynamics） technique to study the effects of pitch ratio on the controllable pitch propeller＇s thrust characteristic. The propeller analyzed is at the following design condition： diameter of 3.65 m, speed of 200 rpm, blade number of 4, average pitch of 2.459 m, pitch ratio at 0.7 of 0.6737. The first stage involves the mesh generation and refinement on domain of the designed propeller. The second stage deals with the identification of initial and boundary conditions of the mesh-equipped module. In the final stage, various results are calculated and analyzed for pitch ratio affecting on the propeller＇s thrust characteristic. The achieved results are the basis design and improving efficiency of the controllable pitch propeller.

关键词： Controllable pitch propeller propeller blade pitch ship CFD thrust.

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中越改革（革新）开放以来党建工作比较研究

中越改革（革新）开放以来党建工作比较研究

作者：阮志功（nguyen chi cong）西安石油大学

学位级别：硕士

在长期执政的历史条件下,建设什么样的党、怎样建设党和怎么加强党的执政能力建设对于执政党来说是一个具有重大意义的问题,这也直接关系到党、国家和社会的前途命运。中越两国同为共产党执政的社会主义国家,中越两党都是在经历了长期... 详细信息

在长期执政的历史条件下,建设什么样的党、怎样建设党和怎么加强党的执政能力建设对于执政党来说是一个具有重大意义的问题,这也直接关系到党、国家和社会的前途命运。中越两国同为共产党执政的社会主义国家,中越两党都是在经历了长期的革命斗争后才最终成为执政党。从政党制度层面来看,两国的政党体制非常相似,从两国发展的历史背景来看,两党都是在不断地革命斗争当中最终取得执政权,稳固了其在本国的执政地位,中越两党在党的建设和探索过程当中遇到了很多挑战和机遇,并且很多方面都存在一定的共性与差异。本文旨在研究改革(革新)开放以来中越两国在党建方面的机遇与挑战、在多个方面进行的探索和取得的发展以及两国探索发展过程中的异同点,最后作总结。本文由六个章节组成,第一章介绍了本文的选题背景及意义、国内外研究现状、研究方法、研究思路和难点以及创新点等。第二章相关概念马克思主义经典作家关于党建问题的相关论述、改革(革新)开放以来中越党建理论等理论问题;第三章为中越改革(革新)开放以来党建工作面临的机遇和挑战,分别对中越两国所面临的机遇和挑战进行梳理总结。第四章中越改革(革新)开放以来党建工作的探索与发展,从政治建设、思想建设、组织建设、作风建设、纪律建设、制度建设六大方面分别对中越改革(革新)开放以来党建工作的探索和发展进行论述。第五章为中越改革(革新)开放以来党建工作探索与发展的异同分析,分别从党内法规制度建设、党内监督机构、党内反腐败措施、党内基层民主制度建设四个方面对两党的党建探索与发展中的异同点展开论述。第六章为启示,经过前文对中越党建的探索和发展以及实践经验,总结几点启示,为加强中越两党提供值得借鉴的经验。

关键词：中国共产党越南共产党改革开放革新开放党建工作

Privacy-preserving explainable AI: a survey

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Science china(Information Sciences) 2025年第1期68卷 23-56页

作者： Thanh Tam nguyen Thanh Trung HUYNH Zhao REN Thanh Toan nguyen Phi Le nguyen Hongzhi YIN Quoc Viet Hung nguyen School of Information and Communication Technology Griffith University School of Computer and Communication Sciences Ecole Polytechnique Federale de Lausanne Faculty of Mathematics and Computer Science University of Bremen Faculty of Information Technology HUTECH University Department of Computer Science Hanoi University of Science and Technology School of Electrical Engineering and Computer Science The University of Queensland

As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.

关键词： privacy-preserving explainable AI privacy attacks privacy defences PrivEx PPXAI

Cellular models of stress resistance may pave ways to fight neurodegenerative diseases

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Neural Regeneration Research 2025年第9期20卷 2579-2580页

作者： Thu nguyen Minh Pham Christian Behl Institute of Pathobiochemistry University Medical Center of the Johannes Gutenberg UniversityMainzGermany

Alzheimer's disease(AD),the most common form of neurodegeneration,is characterized by selective neuronal vulnerability and brain regionselective neuron *** entorhinal cortex and hippoc,ampal CA1 projection neurons are at greater risk in AD whereas other regions display resistance to ***,the cerebellum,a phylogenetically very old region,is affected only very late in the disease progression.

关键词： cortex resistance Alzheimer

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)

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

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

Electronic Band Structure of Carbon Nanotubes with Kekule Structure

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chinese Physics Letters 2013年第9期30卷 97-100页

作者： nguyen Ngoc Hieu Le cong Nhan Center of Research and Development Duy Tan UniversityK7/25 Quang TrungDa NangViet Nam Department of Environmental Science Saigon University273 An Duong VuongHo Chi Minh cityViet Nam

Electronic band structure of carbon nanotubes with the Kekule structure is studied by the tight-binding *** give a complete geometrical approach to structural properties of carbon nanotubes with bond alternation,including chiral and achiral *** the Kekule is introduced,all carbon nanotubes become semiconducting with a small band gap at the Fermi *** band gap of the carbon nanotubes depends only on the difference between C–C bond lengths or the resonance integrals.

关键词： carbon structure Fermi

Heat Transfer and Fluid Flow of Nanofluids in Laminar Radial Flow Cooling Systems

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Journal of Thermal Science 2005年第4期14卷 362-367页

作者： Gilles ROY Samy Joseph PALM cong Tam nguyen Faculty of Engineering Universite de MonctonMonctonNBCanadaElA 3E9

Nanofluids are considered as interesting alternatives to conventional coolants. It is well known that traditional fluids have limited heat transfer capabilities when compared to common metals. It is therefore quite conceivable that a small amount of extremely fine metallic particles placed in suspension in traditional fluids will considerably increase their heat transfer performances. A numerical investigation into the heat transfer enhancement capabilities of coolants with suspended metallic nanoparticles inside a radial, laminar flow cooling configuration is presented. Temperature dependant nanofluid properties are evaluated from experimental data available in recent literature. Results indicate that considerable heat transfer increases are possible with the use of relatively small volume fractions of nanoparticles. Generally, however, these are accompanied by considerable increases in wall shear-stress. Results also show that predictions obtained with temperature variable nanofluid properties yield greater heat transfer capabilities and lower wall shear stresses when compared to predictions using constant properties.

关键词： nanofluids nanoparticles heat transfer laminar flow confined radial flow.