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Graphical method based on modified maximum force criterion to indicate forming limit curves of 22MnB5 boron steel sheets at elevated temperatures

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Journal of Iron and Steel Research International 2021年第8期28卷 1009-1018页

作者： Thanh Luyen quoc-Tuan pham Thi-Bich Mac Tien-Long Banh Duc-Toan Nguyen Faculty of Mechanical Engineering Hungyen University of Technology and EducationHungyen 160000Vietnam Division of Computational Mathematics and Engineering Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh City 70000Vietnam School of Mechanical Engineering Hanoi University of Science and TechnologyHanoi City 100000Vietnam

A new approach for predicting forming limit curves(FLCs)at elevated temperatures was proposed *** are often used to predict failure and determine the optimal forming parameters of automotive ***,a graphical method based on a modified maximum force criterion was applied to estimate the FLCs of 22MnB5 boron steel sheets at room temperature using various hardening ***,the predicted FLC data at room temperature were compared with corresponding data obtained from Nakazima's tests to obtain the best *** estimate the FLC at elevated temperatures,tensile tests were conducted at various temperatures to determine the ratios of equivalent fracture strains between the corresponding elevated temperatures and room *** at elevated temperatures could be established based on obtained ***,the predicted FLCs at elevated temperatures did not agree well with the corresponding FLC experimental data of Zhou et al.A new method was proposed herein to improve the prediction of FLCs at elevated *** FLC calculated at room tem-perature was utilized to predict the failure of Nakazima's samples via finite element *** on the simulation results at room temperature,the mathematical relationships between the equivalent ductile fracture strain versus stress triaxiality and strain ratio were established and then combined with ratios between elevated and room temperatures to calculate the FLCs at different *** predicted FLCs at elevated temperatures agree well with the corresponding experimental FLC data.

关键词： Forming limit curve Modified maximum force criterion Graphical method Hardening law Finite element method Boron steel sheet Elevated temperature

Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization:a case study in Central Vietnam

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International Journal of Digital Earth 2016年第11期9卷 1077-1097页

作者： Dieu Tien Bui Binh Thai pham quoc Phi Nguyen Nhat-Duc hoang Geographic Information System Group Department of Business Administration and Computer ScienceUniversity College of Southeast NorwayBøi TelemarkNorway Faculty of Geomatics and Land Administration Hanoi University of Mining and GeologyHanoiVietnam Department of Civil Engineering Gujarat Technological UniversityAhmedabadGujaratIndia Department of Geotechnical Engineering University of Transport TechnologyHa NoiVietNam Department of Environmental Sciences Hanoi University of Mining and GeologyHanoiVietnam Faculty of Civil Engineering Institute of Research and DevelopmentDuy Tan UniversityDanangVietnam

This study represents a hybrid intelligence approach based on the differential evolution optimization and Least-Squares Support Vector Machines for shallow landslide prediction,named as *** LSSVM is used to establish a landslide prediction model whereas the DE is adopted to search the optimal tuning parameters of the LSSVM *** this research,a GIS database with 129 historical landslide records in the Quy Hop area(Central Vietnam)has been collected to establish the hybrid *** receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to assess the performance of the newly constructed *** results show that the proposed model has high performances with approximately 82%of AUCs on both training and validating *** model’s results were compared with those obtained from other methods,Support Vector Machines,Multilayer Perceptron Neural Networks,and J48 Decision *** result comparison demonstrates that the DE-LSSVMSLP deems best suited for the dataset at hand;therefore,the proposed model can be a promising tool for spatial prediction of rainfall-induced shallow landslides for the study area.

关键词： Shallow landslide Least-Squares Support Vector Machines differential evolution GIS Vietnam

Is convenience really king? Comparative evaluation of catastrophic costs due to tuberculosis in the public and private healthcare sectors of Viet Nam: a longitudinal patient cost study

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贫困所致传染病(英文) 2024年第2期13卷 17-28页

作者： Nguyen hoa Binh Quang Vo Luan Nguyen Forse Rachel Jeanette Wiemers Anja Maria Christine Huynh Huy Ba Dong Thuy Thi Thu Phan Yen Thi hoang Creswell Jacob Dang Thi Minh Ha Nguyen Lan Huu Shedrawy Jad L?nnroth Knut Nguyen Tuan Dinh Van Dinh Luong Annerstedt Kristi Sidney Codlin Andrew James National Lung Hospital Ha Noi Viet Nam Friends for International TB Relief Ha Noi Viet Nam Department of Global Public Health WHO Collaboration Centre On Tuberculosis and Social Medicine Karolinska Institute Stockholm Sweden Stop TB Partnership Geneva Switzerland pham Ngoc Thach Hospital Ho Chi Minh City Viet Nam

Background In Viet Nam, tuberculosis (TB) represents a devastating life-event with an exorbitant price tag, partly due to lost income from daily directly observed therapy in public sector care. Thus, persons with TB may seek care in the private sector for its flexibility, convenience, and privacy. Our study aimed to measure income changes, costs and catastrophic cost incurrence among TB-affected households in the public and private *** Between October 2020 and March 2022, we conducted 110 longitudinal patient cost interviews, among 50 patients privately treated for TB and 60 TB patients treated by the National TB Program (NTP) in Ha Noi, Hai Phong and Ho Chi Minh City, Viet Nam. Using a local adaptation of the WHO TB patient cost survey tool, participants were interviewed during the intensive phase, continuation phase and post-treatment. We compared income levels, direct and indirect treatment costs, catastrophic costs using Wilcoxon rank-sum and chi-squared tests and associated risk factors between the two cohorts using multivariate *** The pre-treatment median monthly household income was significantly higher in the private sector versus NTP cohort (USD 868 vs USD 578;P=0.010). However, private sector treatment was also significantly costlier (USD 2075 vs USD 1313;P=0.005), driven by direct medical costs which were 4.6 times higher than costs reported by NTP participants (USD 754 vs USD 164;P<0.001). This resulted in no significant difference in catastrophic costs between the two cohorts (Private: 55% vs NTP: 52%;P=0.675). Factors associated with catastrophic cost included being a single-person household [adjusted odds ratio [(aOR=13.71; 95% confidence interval (CI): 1.36–138.14;P=0.026], unemployment during treatment (aOR=10.86; 95%CI: 2.64–44.60;P<0.001) and experiencing TB-related stigma (aOR=37.90; 95%CI: 1.72–831.73;P=0.021).Conclusions Persons with TB in Viet Nam face similarly high risk of catastrophic costs whether treated in the

关键词： Tuberculosis Patient cost Catastrophic cost Private sector Comparative analysis Viet Nam

A New Species of Rhacophorus(Amphibia:Anura:Rhacophoridae)from Vietnam

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Asian Herpetological Research 2017年第4期18卷 221-234页

作者： Tao Thien NGUYEN Cuong The pham Truong Quang NGUYEN hoa Thi NINH Thomas ZIEGLER Vietnam National Museum of Nature Vietnam Academy of Science and Technology18 Hoang Quoc Viet RoadHanoiVietnam Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology18 Hoang Quoc VietHanoiVietnam Graduate University of Science and Technology Vietnam Academy of Science and Technology18 Hoang Quoc VietCau GiayHanoiVietnam The Kyoto University Museum Kyoto UniversityYoshida HonmachiSakyokuKyoto 606-8501Japan Hanoi National University of Education 136 Xuan ThuyCau GiayHanoiVietnam AG Zoologischer Garten K6ln Riehler Strasse 173D-50735 CologneGermany Institute of Zoology University of CologneZiilpicherStrafle 47bD-50674 CologneGermany

We describe a new species of Rhacophorus based on two adult specimens collected from hoa Binh Province, northern Vietnam. Rhacophorus hoabinhensis sp. nov. is distinguishable from its congeners on the basis of a combination of the following morphological characters： size small （SVL 31.1-32.5 mm in males）; head slightly longer than wide; vomerine teeth absent; snout short （SNL/SVL 0.16）; dorsal skin smooth; forearm and tarsus with dermal fringes; dermal appendage at vent present; webbing formula on fingers I12/3-12/3II1-2III1-1IV and on toes I3/4-1II1/2- IIII1/2-1IVI-1/2V; dorsal surface grey yellow with brown spots; lower jaw region dark grey, throat, chest and belly cream; anterior and posterior thighs, as well as ventral surface of tibia orange. The interspecific uncorrected genetic distances （16S rRNA gene） between the new species from hoa Binh and other analyzed congeners varied from 9.8% to 17.4%. In the phylogenetic analyses, the new species revealed to be a representative of Rhacophorus and was nested within the R. hoanglienensis-orlovi species group.

关键词： Rhacophorus hoabinhensis sp.nov karst forest molecular phylogeny taxonomy hoa Binh Province

Building 3D CityGML models of mining industrial structures using integrated UAV and TLS point clouds

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International Journal of Coal Science & Technology 2023年第5期10卷 158-177页

作者： Canh Le Van Cuong Xuan Cao Anh Ngoc Nguyen Chung Van pham Long quoc Nguyen Department of Mine Surveying Hanoi University of Mining and GeologyHanoiVietnam Viettel Group Viettel Cyberspace CenterHanoiVietnam

Mining industrial areas with anthropogenic engineering structures are one of the most distinctive features of the real world.3D models of the real world have been increasingly popular with numerous applications,such as digital twins and smart factory *** this study,3D models of mining engineering structures were built based on the CityGML *** collecting spatial data,the two most popular geospatial technologies,namely UAV-SfM and TLS were *** accuracy of the UAV survey was at the centimeter level,and it satisfied the absolute positional accuracy requirement of creat-ing all levels of detail(LoD)according to the CityGML ***,the UAV-SfM point cloud dataset was used to build LoD 2 *** addition,the comparison between the UAV-SfM and TLS sub-clouds of facades and roofs indicates that the UAV-SfM and TLS point clouds of these objects are highly consistent,therefore,point clouds with a higher level of detail and accuracy provided by the integration of UAV-SfM and TLS were used to build LoD 3 *** resulting 3D CityGML models include 39 buildings at LoD 2,and two mine shafts with hoistrooms,headframes,and sheave wheels at LoD3.

关键词： 3D modelling CityGML-Mining industry UAV Terrestrial laser scanning Point cloud

Predicting 3D Radiotherapy Dose-Volume Based on Deep Learning

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Intelligent Automation & Soft Computing 2024年第2期39卷 319-335页

作者： Do Nang Toan Lam Thanh Hien Ha Manh Toan Nguyen Trong Vinh pham Trung Hieu Institute of Information Technology Vietnam Academy of Science and TechnologyHanoi10072Vietnam Faculty of Information Technology Lac Hong UniversityBien HoaDong Nai76120Vietnam

Cancer is one of the most dangerous diseaseswith *** of the principal treatments is radiotherapy by using radiation beams to destroy cancer cells and this workflow requires a lot of experience and skill from doctors and *** our study,we focused on the 3D dose prediction problem in radiotherapy by applying the deeplearning approach to computed tomography(CT)images of cancer *** image data has more complex characteristics than normal image data,and this research aims to explore the effectiveness of data preprocessing and augmentation in the context of the 3D dose prediction *** proposed four strategies to clarify our hypothesis in different aspects of applying data preprocessing and *** strategies,we trained our custom convolutional neural network model which has a structure inspired by the U-net,and residual blocks were also applied to the *** output of the network is added with a rectified linear unit(Re-Lu)function for each pixel to ensure there are no negative values,which are absurd with radiation *** experiments were conducted on the dataset of the Open Knowledge-Based Planning Challenge which was collected from head and neck cancer patients treatedwith radiation *** results of four strategies showthat our hypothesis is rational by evaluating metrics in terms of the Dose-score and the Dose-volume histogram score(DVH-score).In the best training cases,the Dose-score is 3.08 and the DVH-score is *** addition,we also conducted a comparison with the results of another study in the same context of using the loss function.

关键词： CT image 3D dose prediction data preprocessing augmentation

Deep learning long short-term memory combined with discrete element method for porosity prediction in gravel-bed rivers

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International Journal of Sediment Research 2023年第1期38卷 128-140页

作者： Duong Tran Anh Ahad Hasan Tanim Daniel Prakash Kushwaha quoc Bao pham Van Hieu Bui HUTECH University Center for River Harbor and Landslide Research Chittagong University of Engineering & Technology Govind Ballabh Pant University of Agriculture and Technology Institute of Applied Technology Thu Dau Mot University Faculty of Mechanical Engineering Thuyloi University

The porosity of gravel riverbed material often is an essential parameter to estimate the sediment transport rate, groundwater-river flow interaction, river ecosystem, and fluvial geomorphology. Current methods of porosity estimation are time-consuming in simulation. To evaluate the relation between porosity and grain size distribution(GSD), this study proposed a hybrid model of deep learning Long Short-Term Memory(LSTM) combined with the Discrete Element Method(DEM). The DEM is applied to model the packing pattern of gravel-bed structure and fine sediment infiltration processes in threedimensional(3D) space. The combined approaches for porosity calculation enable the porosity to be determined through real time images, fast labeling to be applied, and validation to be done. DEM outputs based on the porosity dataset were utilized to develop the deep learning LSTM model for predicting bed porosity based on the GSD. The simulation results validated with the experimental data then segregated into 800 cross sections along the vertical direction of gravel pack. Two DEM packing cases, i.e., clogging and penetration are tested to predict the porosity. The LSTM model performance measures for porosity estimation along the z-direction are the coefficient of determination(R~2), root mean squared error(RMSE), and mean absolute error(MAE) with values of 0.99, 0.01, and 0.01 respectively, which is better than the values obtained for the Clogging case which are 0.71, 0.14, and 0.03, respectively. The use of the LSTM in combination with the DEM model yields satisfactory results in a less complex gravel pack DEM setup, suggesting that it could be a viable alternative to minimize the simulation time and provide a robust tool for gravel riverbed porosity prediction. The simulated results showed that the hybrid model of the LSTM combined with the DEM is reliable and accurate in porosity prediction in gravel-bed river test samples.

关键词： Numerical modeling Discrete element method LSTM Bed porosity Gravel-bed river

Hybrid model to optimize object-based land cover classification by meta-heuristic algorithm:an example for supporting urban management in Ha Noi,Viet Nam

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International Journal of Digital Earth 2019年第10期12卷 1118-1132页

作者： Quang-Thanh Bui Manh pham Van Nguyen Thi Thuy Hang quoc-Huy Nguyen Nguyen Xuan Linh pham Minh Hai Tran Anh Tuan pham Van Cu Center for Applied Research in Remote sensing and GIS(CARGIS) VNU University of ScienceHa NoiViet Nam VNU University of Science Ha NoiViet Nam Vietnam Institute of Geodesy and Cartography Ha NoiViet Nam Ministry of Education and Training Ha NoiViet Nam

This study proposed a novel object-based hybrid classification model named GMNN that combines Grasshopper Optimization Algorithm(GOA)and the multiple-class Neural network(MNN)for urban pattern detection in Hanoi,*** bands of SPOT 7 image and derivable NDVI,NDWI were used to generate image segments with associated attributes by PCI Geomatics *** segments were classified into four urban surface types(namely water,impervious surface,vegetation and bare soil)by the proposed ***,three training and validation datasets of different sizes were used to verify the robustness of this *** all tests,the overall accuracies of the classification were approximately 87%,and the Area under Receiver Operating Characteristic curves for each land cover type was ***,the performance of this model was examined by comparing several statistical indicators with common benchmark *** results showed that GMNN out-performed established methods in all comparable *** results suggested that our hybrid model was successfully deployed in the study area and could be used as an alternative classification method for urban land cover *** a broader sense,classification methods will be enriched with the active and fast-growing contribution of metaheuristic algorithms.

关键词： Urban remote sensing object-based classification neural network grasshopper optimization algorithm

A Neural-network-based Approach to Study the Energy-optimal Hovering Wing Kinematics of a Bionic Hawkmoth Model

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Journal of Bionic Engineering 2019年第5期16卷 904-915页

作者： Anh Tuan Nguyen Ngoc Doan Tran Thanh Trung Vu Thanh Dong pham quoc Tru Vu Jae-Hung Han Faculty of Aerospace Engineering Le Quy Don Technical University236 Hoang Quoc VietVietnam Office of International Cooperation Le Quy Don Technical University236 Hoang Quoc VietVietnam Department ofAerospace Engineerings Korea Advanced Institute of Science and Technology Daejeon 34141Republic ofKorea

This paper presents the application of an artificial neural network to develop an approach to determine and study the energy-optimal wing kinematics of a hovering bionic hawkmoth model.A three-layered artificial neural network is used for the rapid prediction of the unsteady aerodynamic force acting on the wings and the required *** this artificial network is integrated into genetic and simplex algorithms,the running time of the optimization process is reduced *** validity of this new approach is confirmed in a comparison with a conventional method using an aerodynamic model based on an extended unsteady vortex-lattice method for a sinu soidal wing kinematics *** studying the obtained results,it is found that actual hawkmoths do not hover under an energy-optimal ***,by tilting the stroke plane and lowering the wing positions,they can compromise and expend some energy to enhance their maneuverability and the stability of their flight.

关键词： optimal hovering wing kinematics artificial neural network insect flight genetic algorithm unsteady vortex-lattice method bionics