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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

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Frontiers of Structural and Civil Engineering 2024年第3期18卷 393-410页

作者： Tram bui-ngoc Duy-Khuong LY Tam T TRUONG Chanachai THONGCHOM T.NGUYEN-THOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Department of Computer Science Aarhus UniversityAarhus 8000Denmark Thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Thammasat School of Engineering Thammasat UniversityPathumthani 12120Thailand

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming *** surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement *** proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential *** achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training *** approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical *** study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured ***,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally *** approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data

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A Compromise Programming to Task Assignment Problem in Software Development Project

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Computers, Materials & Continua 2021年第12期69卷 3429-3444页

作者： Ngo Tung Son Jafreezal Jaafar Izzatdin Abdul Aziz bui ngoc anh Hoang Duc Binh Muhammad Umar Aftab Department of Computer and Information Sciences Universiti Teknologi PetronasSeri Iskandar32610Malaysia Department of Information and Communication Technology FPT UniversityHanoi100000Vietnam Department of Computer Science National University of Computer and Emerging SciencesChiniot-Faisalabad CampusChiniot35400Pakistan.

The scheduling process that aims to assign tasks to members is a difficult job in project *** plays a prerequisite role in determining the project’s quality and sometimes winning the bidding *** study aims to propose an approach based on multi-objective combinatorial optimization to do this *** generated schedule directs the project to be completed with the shortest critical path,at the minimum cost,while maintaining its *** are several real-world business constraints related to human resources,the similarity of the tasks added to the optimization model,and the literature’s traditional *** support the decision-maker to evaluate different decision strategies,we use compromise programming to transform multiobjective optimization(MOP)into a single-objective *** designed a genetic algorithm scheme to solve the transformed *** proposed method allows the incorporation of the model as a navigator for search agents in the optimal solution search process by transferring the objective function to the agents’fitness *** optimizer can effectively find compromise solutions even if the user may or may not assign a priority to particular *** are achieved through a combination of nonpreference and preference *** experimental results show that the proposed method worked well on the tested dataset.

关键词： Makespan RCPSP scheduling MOP combinatorial optimization compromise programming genetic algorithm

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Weighted estimates for generalised conical square functions and applications

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Acta Mathematica Sinica,English Series 2024年

作者： The anh bui Xuan Thinh DUONG Ji LI Department of Mathematics Macquarie University

Let{At}t>0be a family of bounded linear operator on L2(X) where (X,d,μ) is a metric space with metric d and doubling measureμ.Assume that the family{At}t>0satisfies suitable offdiagonal estimates from Lp0to L2for some p0*** applications such as weighted bounds for bilinear estimates associated to certain differential operators are also obtained.

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EP Aquarii:A New Picture of the Circumstellar Envelope

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Research in Astronomy and Astrophysics 2024年第3期24卷 83-105页

作者： Pham T.Nhung Do T.Hoai Pierre Darriulat Pham Tuan-anh Pham N.Diep Nguyen B.ngoc Tran T.Thai Department of Astrophysics Vietnam National Space CenterVietnam Academy of Science and Technology18Hoang Quoc VietNghia DoCau GiayHa Noivietnam

New analyses of earlier ALMA observations of oxygen-rich AGB star EP Aquarii are presented,which complete a previously published analysis and offer a different interpretation of the morpho-kinematics of the circumstellar *** birth of the equatorial density enhancement(EDE)is shown to occur very close to the star where evidence for rotation has been *** to the star and where outflows have been observed:their interaction with the gas of the nascent EDE is seen to play an important role in the development of the wind and the evolution of its radial velocity from 8 to 10 km s^(-1) on the polar symmetry axis to~2 km s^(-1) at the *** implies complex morpho-kinematics:making reliable interpretations with reasonable confidence is *** particular,it questions an earlier interpretation implying the presence of a white dwarf companion orbiting the star at an angular distance of -0″4 from its *** proposes instead an interpretation in terms of a standard mass ejection associated with a shock wave leaving a void of emission in its *** Doppler velocity wings are seen to consist of two components,the upper velocity end of the global wind,reaching above±12 km s^(-1),and an effective line broadening,confined within 200 mas from the center of the star,reaching above±20 km s^(-1) and interpreted as caused by the pattern of shock waves resulting from the interaction between stellar pulsation and convective cell partition.

关键词： stars AGB and post-AGB-(stars) circumstellar matter-radio lines stars

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不同薏苡品种光合特性及其与氮素利用效率的关系

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中国农业大学学报 2018年第11期23卷 31-39页

作者： Nghiem Tien Chung 江立庚孔飞扬 bui ngoc anh 广西大学农学院南宁530004 药材研究院越南河内10000 山罗高等学校越南山罗27000

为明确薏苡品种的光合特性及与氮素利用效率间的关系。2015年早季和晚季,分别以从大田试验中筛选出来的氮素利用效率较高和较低品种各2个为材料进行盆栽试验,在分蘖期、抽穗期和成熟期测定功能叶片光合速率及叶绿素荧光参数,抽穗期测定... 详细信息

为明确薏苡品种的光合特性及与氮素利用效率间的关系。2015年早季和晚季,分别以从大田试验中筛选出来的氮素利用效率较高和较低品种各2个为材料进行盆栽试验,在分蘖期、抽穗期和成熟期测定功能叶片光合速率及叶绿素荧光参数,抽穗期测定顶部4片功能叶的光合速率,成熟期测定氮素积累量和氮素利用效率。结果表明,氮高效品种西林1号(XL)与黔饮1号(QL)早季和晚季成熟期单株氮素吸收量平均分别比氮低效品种隆林1号(LL)与品种10号(CU)高125.5%和96.0%,其氮素利用效率平均比品种LL与CU分别高出17.7%和18.0%,品种间差异显著。氮高效品种在分蘖期、抽穗期和成熟期功能叶片的光合速率和叶绿素含量均明显高于氮低效品种。同时,氮高效品种在分蘖期后的光合速率、叶绿素含量衰减速率比氮低效品种小。不同品种在分蘖期、抽穗期和成熟期功能叶片的叶绿素荧光参数及抽穗期顶部4片功能叶光合速率也存在一定的差异,但品种间的变化规律不明显。综上所述,氮高效薏苡品种各生育期功能叶片的光合速率和叶绿素含量较高,其中后期光合速率及叶绿素含量衰减较慢。薏苡品种氮素利用效率与功能叶片的叶绿素荧光参数及顶部4片功能叶光合速率的变化没有显著的相关关系。

关键词：薏苡氮素利用率光合特性光合速率叶绿素含量叶绿素荧光

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Prevalence, risk factors, and BRAF mutation of colorectal sessile serrated lesions among Vietnamese patients

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World Journal of Clinical Oncology 2024年第2期15卷 290-301页

作者： Nhu Thi Hanh Vu Huy Minh Le Diem Thi-ngoc Vo Hoang anh Vu Nhan Quang Le Dung Dang Quy Ho Duc Trong Quach Department of Internal Medicine University of Medicine and Pharmacy at Ho Chi Minh CityHo Chi Minh 700000Viet Nam GI Endoscopy Department University Medical Center at Ho Chi Minh CityHo Chi Minh 700000Viet Nam Department of Histology-Embryology and Pathology University of Medicine and Pharmacy at Ho Chi Minh CityHo Chi Minh 700000Viet Nam Center for Molecular Biomedicine University of Medicine and Pharmacy at Ho Chi Minh CityHo Chi Minh 700000Viet Nam Department of Endoscopy Cho Ray HospitalHo Chi Minh 700000Viet Nam

BACKGROUND Sessile serrated lesions(SSLs)are considered precancerous colorectal lesions that should be detected and removed to prevent colorectal *** studies in Vietnam mainly investigated the adenoma pathway,with limited data on the serrated *** To evaluate the prevalence,risk factors,and BRAF mutations of SSLs in the Vietnamese *** This is a cross-sectional study conducted on patients with lower gastrointestinal symptoms who underwent colonoscopy at a tertiary hospital in *** were diagnosed on histopathology according to the 2019 World Health Organi-zation *** mutation analysis was performed using the Sanger DNA sequencing *** multivariate logistic regression model was used to determine SSL-associated *** There were 2489 patients,with a mean age of 52.1±13.1 and a female-to-male ratio of 1:*** prevalence of SSLs was 4.2%[95%confidence interval(CI):3.5-5.1].In the multivariate analysis,factors significantly associated with SSLs were age≥40[odds ratio(OR):3.303;95%CI:1.607-6.790],male sex(OR:2.032;95%CI:1.204-3.429),diabetes mellitus(OR:2.721;95%CI:1.551-4.772),and hypertension(OR:1.650,95%CI:1.045-2.605).The rate of BRAF mutations in SSLs was 35.5%.CONCLUSION The prevalence of SSLs was 4.2%.BRAF mutations were present in one-third of *** risk factors for SSLs included age≥40,male sex,diabetes mellitus,and hypertension.

关键词： Colorectal cancer Sessile serrated lesion BRAF mutation Risk factors Diabetes mellitus Hypertension

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A Hybrid Deep Learning Approach for PM2.5 Concentration Prediction in Smart Environmental Monitoring

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Intelligent Automation & Soft Computing 2023年第6期36卷 3029-3041页

作者： Minh Thanh Vo anh HVo Huong bui Tuong Le Faculty of Information Technology HUTECH UniversityHo Chi Minh CityVietnam Natural Language Processing and Knowledge Discovery Laboratory Faculty of Information TechnologyTon Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Computing Fundamentals FPT UniversityHo Chi Minh CityVietnam Laboratory for Artificial Intelligence Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh CityVietnam Faculty of Information Technology Van Lang UniversityHo Chi Minh CityVietnam

Nowadays,air pollution is a big environmental problem in develop-ing *** this problem,particulate matter 2.5(PM2.5)in the air is an air *** its concentration in the air is high in developing countries like Vietnam,it will harm everyone’s *** prediction of PM2.5 concentrations can help to make the correct decision in protecting the health of the *** study develops a hybrid deep learning approach named PM25-CBL model for PM2.5 concentration prediction in Ho Chi Minh City,***,this study analyzes the effects of variables on PM2.5 concentrations in Air Quality HCMC *** variables that affect the results will be selected for PM2.5 concentration ***,an efficient PM25-CBL model that integrates a convolutional neural network(CNN)andBidirectionalLongShort-TermMemory(Bi-LSTM)*** model consists of three following modules:CNN,Bi-LSTM,and Fully connected ***,this study conducts the experiment to compare the performance of our approach and several state-of-the-art deep learning models for time series prediction such as LSTM,Bi-LSTM,the combination of CNN and LSTM(CNN-LSTM),and *** empirical results confirm that PM25-CBL model outperforms other methods for Air Quality HCMC dataset in terms of several metrics including Mean Squared Error(MSE),Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),and Mean Absolute Percentage Error(MAPE).

关键词： Time series prediction PM2.5 concentration prediction CNN Bi-LSTM network

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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

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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

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An Ontology-Based Question Answering System for University Admissions Advising

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Intelligent Automation & Soft Computing 2023年第4期36卷 601-616页

作者： Thi Thanh Sang Nguyen Dang Huu Trong Ho ngoc Tram anh Nguyen School of Computer Science and Engineering International UniversityVNU-HCMCVietnam National UniversityHo Chi Minh CityVietnam

Question-Answer systems are now very popular and crucial to support human in automatically responding frequent questions in manyﬁ***,these systems depend on learning methods and training ***,it is necessary to prepare such a good dataset,but it is not an easy *** ontol-ogy-based domain knowledge base is able to help to reason semantic information and make effective answers given user *** study proposes a novel chatbot model involving ontology to generate efﬁcient responses automatically.A case study of admissions advising at the International University–VNU HCMC is taken into account in the proposed chatbot.A domain ontology is designed and built based on the domain knowledge of university admissions using Protégé.The Web user interface of the proposed chatbot system is developed as a prototype using *** includes a search engine reasoning the ontology and generat-ing answers to users’*** experiments are carried out to test how the system reacts to different ***ﬁrst experiment examines questions made from some templates,and the second one examines normal questions taken from frequent *** results have shown that the ontology-based chatbot can release meaningful and long *** results are analysed to prove the proposed chatbot is usable and promising.

关键词： Ontology chatbots answer-question systems domain knowledge base admissions advising

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