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Machine learning based models for predicting compressive strength of geopolymer concrete

Frontiers of Structural and Civil Engineering 2024年第7期18卷 1028-1049页

作者： Quang-Huy LE Duy-Hung nguyen thanh SANG-TO Samir KHATIR Hoang LE-MINH Amir H.GANDOMI thanh CUONG-LE Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(SVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMSE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MSE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

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Effect of Land Use Change on Runoff and Sediment Yield in Da River Basin of Hoa Binh province, Northwest Vietnam

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Journal of Mountain Science 2015年第4期12卷 1051-1064页

作者： NGO thanh Son nguyen Duy Binh Rajendra Prasad SHRESTHA Asian Institute of Technology Faculty of Land Resources Management Vietnam National University of Agriculture Faculty of Information Technology Vietnam National University of Agriculture

The objective of this study was to assess runoff discharge and sediment yield from Da River Basin in the Northwest of Vietnam using Soil and Water Assessment Tools(SWAT) *** SWAT model was calibrated and validated using the observed monthly stream flows and sediment yield at selected gauging *** results indicated that SWAT generally performs well in simulating runoff and sediment yield according to Nash-Sutcliffe efficiency(NSE), Observation's standard deviation ratio(RSR), and percent bias(PBIAS) *** runoff, the values of NSE, RSR, and PBIAS were 0.98,0.02, and 3.69 during calibration period and 0.99,0.01, and 1.56 during validation period, *** sediment yield, the efficiency was lower than the value of NSE, RSR, and PBIAS during calibration period were 0.81, 0.19, and-4.14 and 0.84, 0.16, and-2.56 during validation period, *** results of the study indicated that the vegetation status has a significant impact on runoff and sediment *** in land use type between 1995 and2005 from forest to field crop and urban strongly contributed to increasing the average annual runoff from 182.5 to 342.7 mm and sediment yield from101.3 to 148.1 ton-1 *** 2005 and 2010, adecrease of both runoff(from 342.7 to 167.6 mm) and sediment yield(from 148.1 to 74.0 ton-1 ha) was due to the expansion of forested area and application of soil conservation *** results of this study are important for developing soil and water conservation programs, extending future SWAT modelling studies and disseminating these results to other regions in Vietnam.

关键词： Land use change Hydrology Soil erosion Soil and Water Assessment Tools(SWAT) Da River Basin

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A comparative analysis of weight-based machine learning methods for landslide susceptibility mapping in Ha Giang area

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Big Earth Data 2023年第4期7卷 1005-1034页

作者： thanh Trinh Binh thanh Luu Trang Ha Thi Le Duong Huy nguyen Trong Van Tran Thi Hai Van nguyen Khanh Quoc nguyen Lien Thi nguyen Faculty of Computer Science Phenikaa UniversityYen NghiaHa DongHanoi 12116Vietnam Phenikaa Research and Technology Institute(PRATI) A&A Green Phoenix Group JSCNo.167 Hoang NganTrung HoaCau GiayHanoi 11313Vietnam Northwestern Geological Division General Department of Geology and Minerals of VietnamHanoiVietnam Youth union office Thuyloi University175 Tay SonDong DaHanoiVietnam Center of Remote Sensing and Geohazards Vietnam Institute of Geosciences and Mineral ResourcesHanoiVietnam

Landslide susceptibility maps (LSMs) are very crucial for planningpolicies in hazardous areas. However, the accuracy and reliability ofLSMs depend on available data and the selection of suitable *** study is conducted to produce LSMs by combinations of machinelearning methods and weighting techniques for Ha Giang province,Vietnam, where has limited data. In study area, we gather 11 landslideconditioning factors and establish a landslide inventory *** the weights of classes (or factors) is very important toprepare data for machine learning methods to generate LSMs. Wefrst use frequency ratio (FR) and analytic hierarchy process (AHP)techniques to generate the weights. Then, random forest (RF), supportvector machine (SVM), logistic regression (LR), and AHP methods arecombined with FR and AHP weights to yield accurate and reliableLSMs. Finally, the performance of these methods is evaluated by fivestatistical metrics, ROC and R-index. The empirical results have shownthat RF is the best method in terms of R-index and the five metrics, *** rate (0.9661), FP rate (0.0), ACC (0.9835), MAE (0.0046), and RMSE(0.0350) for this study area. This study opens the perspective of weightbasedmachine learning methods for landslide susceptibility mapping.

关键词： Landslide logistic regression random forest SvM Vietnam

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Cimicifuga heracleifolia is therapeutically similar to black cohosh in relieving menopausal symptoms: evidence from pharmacological and metabolomics studies

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Chinese Journal of Natural Medicines 2019年第6期17卷 435-445页

作者： MIAO Lan-Yun CHU Thi thanh huyen LI Ping JIANG Yan LI Hui-Jun State Key Laboratory of Natural Medicines China Pharmaceutical UniversityNanjing 210009China College of Chemical Engineering Nanjing Forestry UniversityNanjing 210037China

In the market of botanical dietary supplements, Cimicifuga heracleifolia(CH) has always been considered as an adulterated species of Cimicifuga racemosa(CR), a conventional American herb with promising benefits to counteract troubles arising from the menopause. However, the detailed comparison of their therapeutic effects is lacking. In present study, the pharmacological and metabolomics studies were comparatively conducted between CH and CR in ovariectomized(OVX) female rats. Specifically, estrogen-like, anti-hyperlipidemia and anti-osteoporosis effects were evaluated through measuring serum biochemical parameters, histopathological examination and micro computed tomography(Micro-CT) scanning. At the same time, a gas chromatography-mass spectrometry(GC-MS)-based serum metabolomics method was employed to profile the metabolite compositional changes. As a result, both CR and CH displayed anti-osteoporosis and anti-hyperlipemia on menopause syndrome. Meanwhile, their potentials in improving the OVX-induced metabolic disorders were discovered. In conclusion, these results demonstrated that CH is therapeutically similar to CR in relieving menopausal symptoms and CH could be considered as a promising alternative to CR instead of an adulterant in the market of botanical dietary supplements.

关键词： Cimicifuga heracleifolia Black cohosh Menopausal symptoms Metabolomics Substitute

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Enhancing Fire Detection Performance Based on Fine-Tuned YOLOv10

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Computers, Materials & Continua 2024年第11期81卷 2281-2298页

作者： Trong Thua Huynh Hoang thanh nguyen Du Thang Phu Faculty of Information Technology 2 Posts and Telecommunications Institute of Technology(PTIT)Ho Chi Minh City700000Vietnam

In recent years,early detection and warning of fires have posed a significant challenge to environmental protection and human *** learning models such as Faster R-CNN(Faster Region based Convolutional Neural Network),YOLO(You Only Look Once),and their variants have demonstrated superiority in quickly detecting objects from images and videos,creating new opportunities to enhance automatic and efficient fire *** YOLO model,especially newer versions like YOLOv10,stands out for its fast processing capability,making it suitable for low-latency ***,when applied to real-world datasets,the accuracy of fire prediction is still not *** study improves the accuracy of YOLOv10 for real-time applications through model fine-tuning techniques and data *** core work of the research involves creating a diverse fire image dataset specifically suited for fire detection applications in buildings and factories,freezing the initial layers of the model to retain general features learned from the dataset by applying the Squeeze and Excitation attention mechanism and employing the Stochastic Gradient Descent(SGD)with a momentum optimization algorithm to enhance accuracy while ensuring real-time fire *** results demonstrate the effectiveness of the proposed fire prediction approach,where the YOLOv10 small model exhibits the best balance compared to other YOLO family models such as nano,medium,and ***,the study provides an experimental evaluation to highlight the effectiveness of model fine-tuning compared to the YOLOv10 baseline,YOLOv8 and Faster R-CNN based on two criteria:accuracy and prediction time.

关键词： Fire detection accuracy prediction time fine-tuning real-time YOLOv10 Faster R-CNN

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Spatiotemporal Trend Analysis of Precipitation Extremes in Ho Chi Minh City, Vietnam During 1980–2017

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International Journal of Disaster Risk Science 2021年第1期12卷 131-146页

作者： nguyen Trong Quan Dao nguyen Khoi nguyen Xuan Hoan nguyen Ky Phung thanh Duc Dang Faculty of Environmental and Food Engineering Nguyen Tat Thanh UniversityHo Chi Minh City 700000Vietnam Faculty of Environment University of ScienceHo Chi Minh City 700000Vietnam Vietnam National University Ho Chi Minh City 700000Vietnam Ho Chi Minh City University of Food Industry Ho Chi Minh City 700000Vietnam Institute for Computational Science and Technology Ho Chi Minh City 700000Vietnam Engineering Systems and Design Pillar Singapore University of Technology and DesignTampines 487372Singapore

In this study,the spatiotemporal variability of trends in extreme precipitation events in Ho Chi Minh City during the period 1980–2017 was analyzed based on several core extreme precipitation indices(Rx1 day,Rx5 day,CDD,CWD,R20 mm,R25 mm,R95 p,and SDII).The nonparametric Mann–Kendall and Sen’s slope methods were used to compute the statistical strength,stability,and magnitude of trends in annual rainfall,as well as the extreme precipitation *** found that 64%of the stations had statistically significant upward trends in yearly rainfall,with high magnitudes frequently observed in the northern and southern regions of the *** the extreme precipitation indices,only SDII and R25 mm showed dominantly significant ***,there were increasing trends in the frequency and duration at the southern and central regions of the city during the study ***,El Ni?o-Southern Oscillation and Pacific Decadal Oscillation positively correlated with the duration and negatively correlated with the intensity and frequency of extreme ***,water management plans should be adjusted appropriately to reduce the severe impacts of precipitation extremes on communities and ecosystems.

关键词： Spatiotemporal trend Extreme precipitation Extreme precipitation indices Ho Chi Minh City

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Simulation of cohesive crack growth by a variable-node XFEM

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Frontiers of Structural and Civil Engineering 2020年第1期14卷 215-228页

作者： Weihua FANG Jiangfei WU Tiantang YU thanh-Tung nguyen Tinh Quoc BUI Nanjing Automation Institute of Water Conservancy and Hydrology Nanjing 210012China Department of Engineering Mechanics Hohai UniversityNanjing 211100China Laboratory of Solid Structures University of LuxembourgLuxembourg L-1359Luxembourg Institute for Research and Development Duy Tan UniversityDa Nang City 550000Vietnam Department of Civil and Environmental Engineering Tokyo Institute of TechnologyTokyo 152-8552Japan

A new computational approach that combines the extended finite element method associated with variable-node elements and cohesive zone model is *** using a new enriched technique based on sign function,the proposed model using 4-node quadrilateral elements can eliminate the blending element *** also allows modeling the equal stresses at both sides of the crack in the crack-tip as assumed in the cohesive model,and is able to simulate the arbitrary crack-tip *** multiscale mesh technique associated with variable-node elements and the arc-length method further improve the efficiency of the developed *** performance and accuracy of the present approach are illustrated through numerical experiments considering both mode-I and mixed-mode fracture in concrete.

关键词： extended finite element method cohesive zone model sign function crack propagation

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Spherical Fuzzy WASPAS-based Entropy Objective Weighting for International Payment Method Selection

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Computers, Materials & Continua 2022年第7期72卷 2055-2075页

作者： Phi-Hung nguyen thanh-Tuan Dang Kim-Anh nguyen Hong-Anh Pham Faculty of Business FPT UniversityHanoi100000Vietnam Department of Business Management National Taipei University of TechnologyTaipei1068Taiwan Department of Industrial Engineering and Management National Kaohsiung University of Science and TechnologyKaohsiung80778Taiwan

In international trade,exporters prefer to receive payments as quickly as possible,and importers want to make payments as late as *** this respect,the payment field,an essential condition for trade transactions,also represents the positions of exporters and importers *** addition,there are many cases in which various variables must be considered rather than only one specific variable representatively affecting payment,particularly in the case of import-export Small and Medium-Sized Enterprises(SMEs)from emerging countries.A selection of proper payment methods can be categorized as a Multi-Criteria Decision-Making(MCDM)***,this study aims to propose a novel and efficient Spherical Fuzzy Weighted Aggregated Sum Product Assessment based Entropy Objective Weighting method(SF-EW and WASPAS-SF)to evaluate international payment methods with uncertain ***,SF-EW model is applied to determine the relative weights of critical ***,international payment method alternatives are prioritized by the WASPAS-SF *** essential factors for four international payment methods are proposed based on experts’opinions and the existing literature.A real-world case study from Vietnamese import-export SMEs is presented to validate the applicability of the proposed *** results indicated that“Characteristics of payment method(PA)”had the most significant impact on international payment method *** comparison,“Letters of Credit(L/C)”was the most reliable payment method with the highest ranking available to international ***,a sensitivity analysis was performed to examine the validity and robustness of the proposed decision support ***,this study could contribute to international payment services and in the context of globalization and international trade.

关键词： International payment Vietnam MCDM spherical fuzzy theory entropy WASPAS

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Fuzzy Decision Model: Evaluating and Selecting Open Banking Business Partners

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Computers, Materials & Continua 2022年第9期72卷 4557-4570页

作者： Ngo Quang Trung nguyen Van thanh nguyen Viet Tinh Syed Tam Husain Faculty of Commerce Van Lang UniversityHo Chi Minh City70000Vietnam

The finance supply chain has always been a different supply chain compared to product supply chain being a service supply *** Banking(OB)is one of the most important milestones since the beginning of financial technology innovation and service supply *** these are activities provided by traditional banks,non-bank financial institutions also provide financial service with access to consumer banking,transactional and other financial data to develop financial applications and services tailored to their *** development of financial technology,“Open banking”,promotes financial services to begin this ***,evaluating and selecting open banking business partners from multiple perspectives for banks are ***,the authors in this research proposed a hybrid multicriteria decision-making model which includes a Spherical Fuzzy Analytical Hierarchy Process(SF-AHP)model and a Multi-Attributive Ideal-Real Comparative Analysis(MAIRCA)model with supports from seasoned domain *** contribution of this research is a proposition of a fuzzy decision model for evaluating and selecting open banking business *** model successfully determined a suitable open bank provider in order to assist decision makers decide objectively.

关键词： Open banking MCDM SF-AHP MAIRCA fuzzy theory

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Moving Least Squares Interpolation Based A-Posteriori Error Technique in Finite Element Elastic Analysis

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Computer Modeling in Engineering & Sciences 2021年第10期129卷 167-189页

作者： Mohd Ahmed Devender Singh Saeed Al Qadhi nguyen Viet thanh Civil Engineering Department College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia Ministry of Information Soochna BhavanCGO ComplexDelhi110003India Urban Transport&Coastal Engineering Department University of Transport and CommunicationsHanoi100000Vietnam

The performance of a-posteriori error methodology based on moving least squares(MLS)interpolation is explored in this paper by varying the finite element error recovery parameters,namely recovery points and field variable derivatives *** MLS interpolation based recovery technique uses the weighted least squares method on top of the finite element method’s field variable derivatives solution to build a continuous field variable derivatives *** boundary of the node support(mesh free patch of influenced nodes within a determined distance)is taken as circular,i.e.,circular support domain constructed using radial weights is *** field variable derivatives(stress and strains)are recovered at two kinds of points in the support domain,i.e.,Gauss points(super-convergent stress locations)and nodal *** errors are computed as the difference between the stress from the finite element results and projected stress from the post-processed energy norm at both elemental and global *** benchmark numerical tests using quadrilateral and triangular meshes measure the finite element errors in strain and stress *** numerical examples showed the support domain-based recovery technique’s capabilities for effective and efficient error estimation in the finite element analysis of elastic *** MLS interpolation based recovery technique performs better for stress extraction at Gauss points with the quadrilateral discretization of the problem *** is also shown that the behavior of the MLS interpolation based a-posteriori error technique in stress extraction is comparable to classical Zienkiewicz-Zhu(ZZ)a-posteriori error technique.

关键词： Recovery points field variable derivatives effectivity error recovery support domain error convergence

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