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Predicting soil erosion hazard in Lattakia Governorate(W Syria)

International Journal of Sediment Research 2021年第2期36卷 207-220页

作者： Mohammed Safwan Khallouf Alaa Alshiehabi Omran Bao Pham Quoc thi thuy linh nguyen Nam Thai Van Tran Anh Duong Harsányi Endre Institution of Land Utilization Technology and Regional Planning Faculty of Agricultural and Food Sciences and Environmental Management University of Debrecen Administration of Natural Resources Management General Commission for Scientific Agricultural Research (GCSAR) 3. Department of Soil Sciences and Land Reclamation Faculty of Agriculture Al-Baath University Department of Soil and Environment Swedish University of Agricultural Sciences (SLU) Institute of Research and Development Duy Tan University Faculty of Environmental and Chemical Engineering Duy Tan University Faculty of Water Resource Engineering Thuyloi University Ho Chi Minh City University of Technology (HUTECH) Sustainable Management of Natural Resources and Environment Research Group Faculty of Environment and Labour Safety Ton Duc Thang University

The main objective of this study is to predict soil erosion in the Lattakia Governorate(W Syria) using the Water Erosion Prediction Project model(WEPP) and to compare the result with that of the RUSLE. Field survey and data collection were carried out, and 44 soil samples were analyzed. In addition, all the necessary input files were prepared for use in the WEPP model and RUSLE. Results show that more than of 80% of the locations studied experience slight to moderate erosion(less than 5 t/ha/y), whereas the rest of the locations experience severe soil erosion hazard. Moreover, the volume of runoff estimated by the WEPP model is in the range of 51 e321 mm, and the R~2 between the simulated soil erosion and the predicted runoff reached 0.68. Interestingly, the R~2 between the WEPP model and RUSLE is 0.56, which indicates a good correlation between the two models.

关键词： Soil erosion Run-off WEPP RUSLE Syria

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Transient response of doubly-curved bio-inspired composite shells resting on viscoelastic foundation subject to blast load using improved first-order shear theory and isogeometric approach

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Defence Technology（防务技术） 2024年第8期38卷 171-193页

作者： thuy Tran thi Thu Tu nguyen Anh Hue nguyen thi Hong nguyen thi School of Mechanical and Automotive Engineering Hanoi University of IndustryHanoiViet Nam Faculty of Technical Fundamental University of Transport TechnologyHanoiViet Nam Faculty of Mechanical Engineering Thuyloi University175 Tay SonDong DaHanoiViet Nam

Investigating natural-inspired applications is a perennially appealing subject for scientists. The current increase in the speed of natural-origin structure growth may be linked to their superior mechanical properties and environmental resilience. Biological composite structures with helicoidal schemes and designs have remarkable capacities to absorb impact energy and withstand damage. However, there is a dearth of extensive study on the influence of fiber redirection and reorientation inside the matrix of a helicoid structure on its mechanical performance and reactivity. The present study aimed to explore the static and transient responses of a bio-inspired helicoid laminated composite(B-iHLC) shell under the influence of an explosive load using an isomorphic method. The structural integrity of the shell is maintained by a viscoelastic basis known as the Pasternak foundation, which encompasses two coefficients of stiffness and one coefficient of damping. The equilibrium equations governing shell dynamics are obtained by using Hamilton's principle and including the modified first-order shear theory,therefore obviating the need to employ a shear correction factor. The paper's model and approach are validated by doing numerical comparisons with respected publications. The findings of this study may be used in the construction of military and civilian infrastructure in situations when the structure is subjected to severe stresses that might potentially result in catastrophic collapse. The findings of this paper serve as the foundation for several other issues, including geometric optimization and the dynamic response of similar mechanical structures.

关键词： Blast load Modified first-order shear theory Biological composite structures

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Green Synthesis of Silver Nanoparticles Using Plectranthus Amboinicus Leaf Extract for Preparation of CMC/PVA Nanocomposite Film

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Journal of Renewable Materials 2021年第8期9卷 1393-1411页

作者： nguyen thi Thanh thuy Le Hoang Huy Truong thuy Vy nguyen thi Thanh Tam Bien thiLan Thanh nguyen thi My Lan Nong Lam University Ho Chi Minh City Ho Chi Minh City700000Vietnam Industrial University of Ho Chi Minh City Ho Chi Minh City700000Vietnam University of Science Viet Nam National University Ho Chi Minh CityHo Chi Minh City700000Vietnam

In the present study,the biogenic silver nanoparticles have been synthesized using aqueous leaf extract of Plectranthus amboinicus(PA),which acted as both reducing and stabilizing *** PA synthesized silver nanoparticles were blended with carboxymethyl cellulose/polyvinyl alcohol(CMC/PVA)*** prepared AgNPs as well as the biogenic AgNPs incorporated CMC/PVA films were investigated using UV-visible spectrophotometry,Fourier-transform infrared spectroscopy(FT-IR),dynamic light scattering(DLS),scanning electron microscope(SEM),and X–ray diffraction(XRD).The DLS results showed that biogenic AgNPs had the average particle size of 65.70 nm with polydispersity index of *** surface plasmon resonance of AgNPs,which was determined by UV-vis spectrophotometry,showed the value of 410.00 *** results therefore confirmed the reduction Ag+into Ag°and the formation of AgNPs in the *** SEM imaging showed that AgNPs was quasi-spherical and *** XRD peaks at 33.07°,44.19°,64.58°and 77.47°confirmed the crystalline nature and presence of *** CMC/PVA films that incorporated with AgNPs displayed best mechanical strength and morphological properties than the pure CMC/PVA *** film of CMC/PVA-AgNPs exhibited significant antibacterial activities against Bacillus spizizenii,Staphylococcus aureus,Salmonella typhi and Escherichia Coli.

关键词： Carboxymethyl cellulose antibacterial green synthesis silver nanoparticles plectranthus amboinicus polyvinyl alcohol

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On the Laws of Large Numbers for Double Arrays of Independent Random Elements in Banach Spaces

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Acta Mathematica Sinica,English Series 2014年第8期30卷 1353-1364页

作者： Andrew ROSALSKY Le Van THANH nguyen thi thuy Department of Statistics University of FloridaGainesville Department of Mathematics Vinh University

For a double array of independent random elements {Vmn,m ≥ 1,n ≥ 1} in a real separable Banach space,conditions are provided under which the weak and strong laws of large numbers for the double sums mi=1 nj=1Vij,m ≥ 1,n ≥ 1 are *** the identically distributed and the nonidentically distributed cases are *** the main theorems,no assumptions are made concerning the geometry of the underlying Banach *** theorems are applied to obtain Kolmogorov,Brunk–Chung,and Marcinkiewicz–Zygmund type strong laws of large numbers for double sums in Rademacher type p（1 ≤ p ≤ 2） Banach spaces.

关键词： Real separable Banach space double array of independent random elements strong and weak laws of large numbers almost sure convergence convergence in probability Rademacher type p Banach space

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Some Mean Convergence Theorems for the Maximum of Normed Double Sums of Banach Space Valued Random Elements

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Acta Mathematica Sinica,English Series 2024年第7期40卷 1727-1740页

作者： Andrew ROSALSKY Le Van THANH nguyen thi thuy Department of Statistics University of FloridaGainesvilleFL 32611-8545USA Department of Mathematics Vinh UniversityVinhNghe AnViet Nam High School for Gifted Students Vinh UniversityVinhNghe AnViet Nam

In this correspondence,we establish mean convergence theorems for the maximum of normed double sums of Banach space valued random *** of the results pertain to random elements which are *** expand and improve a number of particular cases in the literature on mean convergence of random elements in Banach *** of the main contributions of the paper is to simplify and improve a recent result of Li,Presnell,and Rosalsky[Journal of Mathematical Inequalities,16,117–126(2022)].A new maximal inequality for double sums of M-dependent random elements is proved which may be of independent *** sharpness of the results is illustrated by four examples.

关键词： Double sum mean convergence Rademacher type p Banach space Banach space valued random element M-dependent random elements

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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

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Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

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Frontiers of Structural and Civil Engineering 2022年第7期16卷 928-945页

作者： Van Quan TRAN Hai-Van thi MAI thuy-Anh nguyen Hai-Bang LY Faculty of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam

The compressive strength of self-compacting concrete(SCC)needs to be determined during the construction design *** paper shows that the compressive strength of SCC(CS of SCC)can be successfully predicted from mix design and curing age by a machine learning(ML)technique named the Extreme Gradient Boosting(XGB)algorithm,including non-hybrid and hybrid *** ML techniques,such as Linear regression(LR),K-Nearest Neighbors(KNN),Support Vector Machine(SVM),Decision Trees(DTR),Random Forest(RF),Gradient Boosting(GB),and Artificial Neural Network using two training algorithms LBFGS and SGD(denoted as ANN_LBFGS and ANN_SGD),are also compared with the XGB ***,the hybrid models of eight ML techniques and Particle Swarm Optimization(PSO)are constructed to highlight the reliability and accuracy of SCC compressive strength prediction by the XGB_PSO hybrid *** highest number of SCC samples available in the literature is collected for building the ML *** with previously published works’performance,the proposed XGB method,both hybrid and non-hybrid models,is the most reliable and robust of the examined techniques,and is more accurate than existing ML methods(R2=0.9644,RMSE=4.7801,and MAE=3.4832).Therefore,the XGB model can be used as a practical tool for engineers in predicting the CS of SCC.

关键词： compressive strength self-compacting concrete machine learning techniques particle swarm optimization extreme gradient boosting

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Flood susceptibility modelling using advanced ensemble machine learning models

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Geoscience Frontiers 2021年第3期12卷 60-77页

作者： Abu Reza Md Towfiqul Islam Swapan Talukdar Susanta Mahato Sonali Kundu Kutub Uddin Eibek Quoc Bao Pham Alban Kuriqi nguyen thi thuy linh Department of Disaster Management Begum Rokeya UniversityRangpurBangladesh Department of Geography University of Gour BangaMaldaWest BengalIndia Environmental Quality Atmospheric Science and Climate Change Research GroupTon Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Environment and Labour Safety Ton Duc Thang UniversityHo Chi Minh CityVietnam CERIS Instituto Superior TécnicoUniversidade de LisboaLisbonPortugal Institute of Research and Development Duy Tan UniversityDanang 550000Vietnam Faculty of Environmental and Chemical Engineering Duy Tan UniversityDanang 550000Vietnam

Floods are one of nature's most destructive disasters because of the immense damage to land,buildings,and human *** is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash ***,earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood *** this study,we applied and assessed two new hybrid ensemble models,namely Dagging and Random Subspace(RS)coupled with Artificial Neural Network(ANN),Random Forest(RF),and Support Vector Machine(SVM)which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin,the northern region of *** application of these models includes twelve flood influencing factors with 413 current and former flooding points,which were transferred in a GIS *** information gain ratio,the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential *** the validation and the comparison of these models,for the ability to predict the statistical appraisal measures such as Freidman,Wilcoxon signed-rank,and t-paired tests and Receiver Operating Characteristic Curve(ROC)were *** value of the Area Under the Curve(AUC)of ROC was above 0.80 for all *** flood susceptibility modelling,the Dagging model performs superior,followed by RF,the ANN,the SVM,and the RS,then the several benchmark *** approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.

关键词： Flood hazard Flood vulnerability Flash floods Debris flow Teesta River basin Bangladesh

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Emotion Recognition with Capsule Neural Network

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Computer Systems Science & Engineering 2022年第6期41卷 1083-1098页

作者： Loan Trinh Van Quang H.nguyen thuy Dao thi Le School of Information and Communication Technology Hanoi University of Science and TechnologyHanoi10000Vietnam Faculty of Information Technology University of Transport and CommunicationsHanoi10000Vietnam

For human-machine communication to be as effective as human-tohuman communication, research on speech emotion recognition is *** the models and the classifiers used to recognize emotions, neural networks appear to be promising due to the network’s ability to learn and the diversity in configuration. Following the convolutional neural network, a capsuleneural network (CapsNet) with inputs and outputs that are not scalar quantitiesbut vectors allows the network to determine the part-whole relationships thatare specific 6 for an object. this paper performs speech emotion recognition basedon CapsNet. The corpora for speech emotion recognition have been augmented byadding white noise and changing voices. The feature parameters of the recognition system input are mel spectrum images along with the characteristics of thesound source, vocal tract and prosody. For the German emotional corpus EMODB, the average accuracy score for 4 emotions, neutral, boredom, anger and happiness, is 99.69%. For Vietnamese emotional corpus BKEmo, this score is94.23% for 4 emotions, neutral, sadness, anger and happiness. The accuracy scoreis highest when combining all the above feature parameters, and this scoreincreases significantly when combining mel spectrum images with the featuresdirectly related to the fundamental frequency.

关键词： Emotion recognition CapsNet data augmentation mel spectrum image fundamental frequency

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GIS-based landslide susceptibility modeling:A comparison between fuzzy multi-criteria and machine learning algorithms

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Geoscience Frontiers 2021年第2期12卷 857-876页

作者： Sk Ajim Ali Farhana Parvin Jana Vojteková Romulus Costache nguyen thi thuy linh Quoc Bao Pham Matej Vojtek Ljubomir Gigović Ateeque Ahmad Mohammad Ali Ghorbani Department of Geography Faculty of ScienceAligarh Muslim University(AMU)AligarhUP 202002India Department of Geography and Regional Development Faculty of Natural SciencesConstantine the Philosopher University in NitraTrieda A.Hlinku 194901 NitraSlovakia Research Institute of the University of Bucharest 90-92 Sos.Panduri5th DistrictBucharest 050663Romania National Institute of Hydrology and Water Management București-Ploiești Road97E1st DistrictBucharest 013686Romania thuyloi University 175 Tay SonDong DaHanoiViet Nam Institute of Research and Development Duy Tan UniversityDanang 550000Viet Nam Faculty of Environmental and Chemical Engineering Duy Tan UniversityDanang 550000Viet Nam Department of Geography University of Defence11000 BelgradeSerbia Sustainable Management of Natural Resources and Environment Research Group Faculty of Environment and Labour SafetyTon Duc Thang UniversityHo Chi Minh CityViet Nam

Hazards and disasters have always negative impacts on the way of *** is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout *** present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,*** this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Naïve Bayes(NB)classifier,and random forest(RF)classifier were ***,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,*** geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover *** ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model ***,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Naïve Bayes(NB)classifier,and random forest(RF)classifier ***,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and *** results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%).

关键词： Landslide susceptibility modeling Geographic information system Fuzzy DEMATEL Analytic network process Naïve Bayes classifier Random forest classifier

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