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Forecasting measured responses of structures using temporal deep learning and dual attention

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 832-850页

作者： Viet-Hung DANG trong-Phu nguyen Thi-Lien PHAM Huan X.nguyen Department of Structural Mechanics Hanoi University of Civil EngineeringHanoi 11600Vietnam Faculty of Applied Science University of Economics-Technology for IndustriesHanoi 11600Vietnam London Digital Twin Research Centre Faculty of Science and TechnologyMiddlesex UniversityLondon NW44BTUK International School Vietnam National UniversityHanoi 11600Vietnam

The objective of this study is to develop a novel and efficient model for forecasting the nonlinear behavior of structures in response to time-varying random *** key idea is to design a deep learning architecture to leverage the relationships,between external excitations and structure's vibration signals,and between historical values and future values,within multiple time-series *** proposed method consists of two main steps:the first step applies a global attention mechanism to combine multiple-measured time series and time-varying excitation into a weighted time series before feeding it to a temporal architecture;the second step utilizes a self-attention mechanism followed by a fully connected layer to predict multi-step future *** viability of the proposed method is demonstrated via two case studies involving synthetic data from a three-dimensional(3D)reinforced concrete structure and experimental data from an 18-story steel ***,comparison and robustness studies are carried out,showing that the proposed method outperforms conventional methods and maintains high performance in the presence of noise with an amplitude of less than 10%.

关键词： structural dynamic time-varying excitation deep learning signal processing response forecasting

An Optimal Node Localization in WSN Based on Siege Whale Optimization Algorithm

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2201-2237页

作者： Thi-Kien Dao trong-The nguyen Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhou350118China Multimedia Communication Lab University of Information TechnologyHo Chi Minh CityVietnam

Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging andfundamental operations in various monitoring or tracking applications because the network deploys a large areaand allocates the acquired location information to unknown devices. The metaheuristic approach is one of themost advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditionalmethods that often suffer from computational time problems and small network deployment scale. This studyproposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on thesiege mechanism (SWOA) for node localization inWSN. The objective function is modeled while communicatingon localized nodes, considering variables like delay, path loss, energy, and received signal strength. The localizationapproach also assigns the discovered location data to unidentified devices with the modeled objective functionby applying the SWOA algorithm. The experimental analysis is carried out to demonstrate the efficiency of thedesigned localization scheme in terms of various metrics, e.g., localization errors rate, converges rate, and executedtime. Compared experimental-result shows that theSWOA offers the applicability of the developed model forWSNto perform the localization scheme with excellent quality. Significantly, the error and convergence values achievedby the SWOA are less location error, faster in convergence and executed time than the others compared to at least areduced 1.5% to 4.7% error rate, and quicker by at least 4%and 2% in convergence and executed time, respectivelyfor the experimental scenarios.

关键词： Node localization whale optimization algorithm wireless sensor networks siege whale optimization algorithm optimization

Influence of different land-use types on selected soil properties related to soil fertility in A Luoi District,Thua Thien Hue,Vietnam

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Soil Ecology Letters 2024年第1期6卷 131-140页

作者： Khoa Phuc nguyen Tan trong Tran Huy Dinh Le Phuong Thuy nguyen Hien Thao Thi Pham Dien Thanh nguyen Ngu Huu nguyen University of Agriculture and Forestry Hue UniversityHue CityThua Thien Hue 52000Vietnam School of Biotechnology Tan Tao UniversityTan Duc ECityDuc HoaLong An850000Vietnam

Land use type affects the physicochemical properties of *** value of OM and TN is high in acacia *** acidity of soil is considered a serious constraint for *** cash crops are acacia,cassava,banana,rice and *** fertility is affected by land-use types and land management,which exacerbates soil erosion and various other forms of soil degradation in the mountainous regions of *** study was conducted in A Luoi District,Thua Thien Hue,Vietnam to identify the effects of land-use types on specific soil physicochemical characteristics related to soil *** physicochemical properties,such as organic matter(OM),total nitrogen(TN),total phosphorous(TP),and K+were significantly affected by land-use *** results showed that the soils were sandy in rice but clay loam for acacia and *** mean bulk density value of acacia soil was significantly greater than that of other *** were higher in the acacia soils than those in the rice,maize,and banana *** OM content was significantly higher in the acacia,cassava,and banana soils than those in the rice and maize *** mean of exchangeable K+in the rice soil was higher compared to those in other soils and was affected by land-use *** high exchangeable acidity content in the soils was probably due to intensive ***,both land use type and management did not affect the CEC ***,the inappropriate land use caused the disturbance of soil physicochemical properties,indicating that the conditions of rice and maize soils are becoming worse than acacia ***,lowering the intensity of cultivation,adopting incorporated soil fertility management,and applying organic fertilizer should preserve the existing conditions and enhance soil properties.

关键词： Land-use types soil characteristics soil frility suitable crop Vietnam

Oxygen functionalization-assisted anionic exchange toward unique construction of flower-like transition metal chalcogenide embedded carbon fabric for ultra-long life flexible energy storage and conversion

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Carbon Energy 2024年第1期6卷 72-93页

作者： Roshan M.Bhattarai Kisan Chhetri nghia Le Debendra Acharya Shirjana Saud Mai Cao Hoang Phuong Lan nguyen Sang Jae Kim Young Sun Mok Department of Chemical Engineering Jeju National UniversityJejuRepublic of Korea Department of Nano Convergence Engineering Jeonbuk National UniversityJeonjuRepublic of Korea Regional Leading Research Center(RLRC)for Nanocarbon-based Energy Materials and Application Technology Jeonbuk National UniversityJeonjuRepublic of Korea Department of Chemistry Mississippi State UniversityStarkvilleMississippiUSA Nanomaterials and System Laboratory Department of Mechatronics EngineeringJeju National UniversityJejuRepublic of Korea

The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion *** NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside *** obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode ***,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed ***,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and ***,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.

关键词： carbon cloth energy conversion energy storage flexible metal embedding ultra-stable

Assessment of Agricultural Soil Quality Indices Using Mechanistic Models

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Open Journal of Soil Science 2024年第6期14卷 333-352页

作者： Mohammadali Nikpey Javad Robatjazi Shahabeddin Garmehei Hendra Gonsalve W. Lasar nguyen Khoi nghia Benjamin Kwadwo Agyei Department of Soil Science Faculty of Agriculture Tarbiat Modarres University Tehran Iran Texas A&M AgriLife Research Department of Soil and Crop Sciences Texas A&M University College Station TX USA Faculty of Soil Sciences College of Agriculture Can Tho University Can Tho Vietnam Department of Plant Soil and Microbial Sciences Michigan State University East Lansing MI USA

Assessing soil quality is a critical strategy for diagnosing soil status and anticipating concerns in land use systems for agricultural sustainability. In this study, two soil quality assessment indices, the Integrated Quality Index (IQI) and Nemoro Quality Index (NQI), were employed using two indicator selection methods: Total Data Set (TDS) and Minimum Data Set (MDS), focusing on agricultural fields in Golestan province, Iran. A total of 89 soil samples were collected and analyzed for particle size distribution, organic carbon, calcium carbonate equivalent (CCE), electrical conductivity (EC), pH, and plant-essential nutrients, including nitrogen, phosphorus, potassium, zinc, copper, manganese, and iron. Principal component analysis (PCA) was used to extract MDS from TDS, and geostatistical adaptation and correlation analyses were performed to determine the optimal soil quality evaluation index. Our results show that the exponential model better suits the spatial structure of soil quality indicators (IQIMDS: 0.955). Conformity and correlation analyses indicate that the IQI index outperformed the NQI index in estimating soil quality. The superiority of the TDS technique over the MDS technique in terms of accuracy (IQITDSs kappa: 0.155). Linear relationships between different methods showed a higher correlation coefficient (R2 = 0.43) through the application of IQI. This study suggests the use of IQIMDS to provide a reliable measurement that is particularly useful in assessing the quality of agricultural soil.

关键词： Soil Quality Geographic Information System Integrated Quality Index Nemoro Quality Index

Tuberculosis Diagnosis and Visualization with a Large Vietnamese X-Ray Image Dataset

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Intelligent Automation & Soft Computing 2024年第2期39卷 281-299页

作者： nguyen trong Vinh Lam Thanh Hien Ha Manh Toan Ngo Duc Vinh Do Nang Toan Faculty of Information Technology Lac Hong UniversityBien HoaDong Nai76120Vietnam Institute of Information Technology Vietnam Academy of Science and TechnologyHanoi10072Vietnam Faculty of Information Technology Hanoi University of IndustryHanoi11915Vietnam

Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse ***,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very *** late detection of tuberculosis could lead to danger to patient health,even *** one of the countries heavily affected by the COVID-19 pandemic,andmany residential areas as well as hospitals have to be isolated for a long *** demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessingmedical services,such as an automatic tuberculosis diagnosis *** our study,aiming to build that system,we were interested in the tuberculosis diagnosis problem from the chest X-ray images of Vietnamese *** chest X-ray image is an important data type to diagnose tuberculosis,and it has also received a lot of attention from deep learning *** paper proposed a novel method for tuberculosis diagnosis and visualization using the deeplearning approach with a large Vietnamese X-ray image *** detail,we designed our custom convolutional neural network for the X-ray image classification task and then analyzed the predicted result to provide visualization as a *** prove the performance of our network model,we conducted several experiments to compare it to another study and also to evaluate it with the dataset of this *** support the implementation,we built a specific annotation system for tuberculosis under the requirements of radiologists in the Vietnam National Lung Hospital.A large experiment dataset was also from this hospital,and most of this data was for training the convolutional neural network *** experiment results were evaluated regarding sensitivity,specificity,and *** achieved high scores with a training accuracy score of 0.99,and the testing specificity and sensitivity scores were over *** on the X-ray image classification result,we visualize pr

关键词： Tuberculosis classification Vietnamese chest X-ray deep learning

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

Data-driven approach to solve vertical drain under time-dependent loading

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Frontiers of Structural and Civil Engineering 2021年第3期15卷 696-711页

作者： trong nghia-nguyen Mamoru KIKUMOTO Samir KHATIR Salisa CHAIYAPUT Hnguyen-XUAN Thanh CUONG-LE Department of Civil Engineering Yokohama National UniversityYokohama 240-8501Japan Faculty of Civil Engineering Ho Chi Minh City Open UniversityHo Chi Minh City 70000Vietnam Department of Electrical Energy MetalsMechanical Constructions and SystemsFaculty of Engineering and ArchitectureGhent UniversityGhent 9000Belgium Department of Civil Engineering School of EngineeringKing Mongkut’s Institute of Technology LadkrabangBangkok 10520Thailand CIRTECH Institute Ho Chi Minh City University of Technology(HUTECH)Ho Chi Minh City 708300Vietnam

Currently,the vertical drain consolidation problem is solved by numerous analytical solutions,such as time-dependent solutions and linear or parabolic radial drainage in the smear zone,and no artificial intelligence(AI)approach has been ***,in this study,a new hybrid model based on deep neural networks(DNNs),particle swarm optimization(PSO),and genetic algorithms(GAs)is proposed to solve this *** DNN can effectively simulate any sophisticated equation,and the PSO and GA can optimize the selected DNN and improve the performance of the prediction *** the present study,analytical solutions to vertical drains in the literature are incorporated into the DNN–PSO and DNN–GA prediction models with three different radial drainage patterns in the smear zone under timedependent *** verification performed with analytical solutions and measurements from three full-scale embankment tests revealed promising applications of the proposed approach.

关键词： vertical drain artificial neural network time-dependent loading deep learning network genetic algorithm particle swarm optimization

Fresh and hardened properties of high-performance fiber-reinforced concrete containing fly ash and rice husk ash:Influence of fiber type and content

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Frontiers of Structural and Civil Engineering 2022年第12期16卷 1621-1632页

作者： nguyen-trong HO Viet Quoc DANG Minh-Hieu nguyen Chao-Lung HWANG trong-Phuoc HUYNH Faculty of Civil Engineering VSB-Technical University of OstravaOstrava-Poruba 70800Czech Republic Faculty of Bridge and Road Construction Mientrung University of Civil Engineering(MUCE)Tuy Hoa City 56100Vietnam Vinh Long Department of Construction Vinh Long City 85000Vietnam Taiwan Building Technology Center Taiwan University of Science and TechnologyTaipei 10607China Faculty of Civil Engineering College of EngineeringCan Tho UniversityCan Tho City 94000Vietnam

Although fibers are used only infrequently as an additive in concrete in the construction industry,fiberenhanced concrete is known to provide a wide range of advantages over conventional *** main objective of this study was to investigate the influences of fiber type and content on the mechanical properties and durability of highperformance fiber-reinforced concrete(HPFRC)designed using a novel densified mixture design algorithm with fly ash and rice husk *** types of fiber,including polypropylene(PP)fiber,steel fiber(SF),and hybrid fiber(HF),were *** on the results,the inclusion of fibers decreased HPFRC flowability,regardless of fiber *** the compressive strength of HPFRC with 1.6%PP fiber content was 11.2%below that of the reference HPFRC specimen at 91 d of curing age,the 91-d compressive strengths of both SF and HF-enhanced HPFRC specimens were significantly better than that of the reference HPFRC ***,the HPFRC specimens incorporating SF and HF both exhibited better splitting tensile and flexural strengths as well as less drying shrinkage than the HPFRC specimens incorporating PP ***,the fiber-enhanced specimens,especially those with added SF,registered less surface electrical resistivity and greater vulnerability to chloride ion penetration than the reference HPFRC specimen.

关键词： high-performance fiber-reinforced concrete fly ash rice husk ash durability mechanical strength