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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

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

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

Dry eye rate and its relationship with disease stage in patients with primary hypertension:a cross-sectional study in Vietnam

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International Journal of Ophthalmology(English edition) 2024年第4期17卷 653-658页

作者： Tran Tat Thang Pham Hong Phuong nguyen Sa Huynh nguyen Trung kien nguyenDuy Toan nguyen Thi Thu Ha Le Ha Khoa nguyen Huu Dung Thai Doan Thang Le Viet Thang Nghe An Eye Hospital Nghe An 43000Vietnam Nghe An Friendship General Hospital Nghe An 43000Vietnam Military Hospital 103 Ha Noi 100000Vietnam Vietnam Military Medical University Ha Noi 100000Vietnam Hanoi Medical University Ha Noi 100000Vietnam Bạch Mai Hospital Ha Noi 100000Vietnam TTH Vinh General Hospital Nghe An 100000Vietnam

AIM:To determine the dry eye(DE)rate and its relationship with disease stage in patients with primary ***:A cross-sectional study included 432 patients with primary hypertension(with an equal number of patients in each group:144 in stage Ⅰ,Ⅱ,and Ⅲ hypertension)and 144 healthy subjects as a control *** Ocular Surface Disease Index(OSDI)and Schirmer Ⅰ test without anesthetics were conducted on all 576 *** with OSDI scores<13 and Schirmer Ⅰ values equal to or under 10 mm were diagnosed with ***:The ratio of DE in hypertension patients was higher than in the control group(41.7%versus 18.8%;P<0.001).The proportion of patients with DE increased gradually according to the hypertension stage:27.1% in stage Ⅰ,40.3% in stage Ⅱ,and 57.6% in stage Ⅲ,P<***,duration of hypertension,plasma urea,creatinine,and high-sensitivity C-reactive protein(CRP-hs)levels in hypertension patients with DE were higher than those without DE,P<*** age,a long duration of hypertension,diabetes mellitus,elevated plasma creatinine,and CRP-hs levels were independent factors associated with DE in primary hypertension patients,P<***:DE is a common disorder associated with advanced age,a long duration of hypertension,diabetes mellitus,elevated plasma CRP-hs,and creatinine levels in patients with primary hypertension.

关键词： primary hypertension dry eye stage of hypertension plasma creatinine

Chebyshev polynomial-based Ritz method for thermal buckling and free vibration behaviors of metal foam beams

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 891-910页

作者： N.D.nguyen T.N.nguyen Faculty of Civil Engineering Ho Chi Minh City University of Technology and EducationHo Chi Minh City 71309Viet Nam Faculty of Engineering and Technology Kien Giang UniversityChau Thanh 92000Viet Nam

This study presents the Chebyshev polynomials-based Ritz method to examine the thermal buckling and free vibration characteristics of metal foam *** analyses include three models for porosity distribution and two scenarios for thermal *** material properties are assessed under two conditions,i.e.,temperature dependence and temperature *** theoretical framework for the beams is based on the higher-order shear deformation theory,which incorporates shear deformations with higher-order *** governing equations are established from the Lagrange equations,and the beam displacement fields are approximated by the Chebyshev *** simulations are performed to evaluate the effects of thermal load,slenderness,boundary condition(BC),and porosity distribution on the buckling and vibration behaviors of metal foam *** findings highlight the significant influence of temperature-dependent(TD)material properties on metal foam beams'buckling and vibration responses.

关键词： Ritz method Chebyshev function buckling vibration metal foam beam higher-order beam theory(HOBT)

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

A Sensor Network Coverage Planning Based on Adjusted Single Candidate Optimizer

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Intelligent Automation & Soft Computing 2023年第9期37卷 3213-3234页

作者： trong-The nguyen Thi-kien Dao Trinh-Dong nguyen Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhou350118China University of Information Technology Ho Chi Minh CityVietnam Vietnam National University Ho Chi Minh City700000Vietnam

Wireless sensor networks(WSNs)are widely used for various practical applications due to their simplicity and *** quality of service in WSNs is greatly influenced by the coverage,which directly affects the monitoring capacity of the target ***,low WSN coverage and uneven distribution of nodes in random deployments pose significant *** study proposes an optimal node planning strategy for net-work coverage based on an adjusted single candidate optimizer(ASCO)to address these *** single candidate optimizer(SCO)is a metaheuristic algorithm with stable implementation ***,it has limitations in avoiding local optimum traps in complex node coverage optimization *** ASCO overcomes these limitations by incorporating reverse learning and multi-direction strategies,resulting in updated *** performance of the ASCO algorithm is compared with other algorithms in the literature for optimal WSN node *** results demonstrate that the ASCO algorithm offers efficient performance,rapid convergence,and expanded coverage ***,the ASCO achieves an archival coverage rate of 88%,while other approaches achieve coverage rates below or equal to 85%under the same conditions.

关键词： Wireless sensor network coverage and connection adapted single candidate optimizer objective function optimization

Novel hybrid models of ANFIS and metaheuristic optimizations (SCE and ABC) for prediction of compressive strength of concrete using rebound hammer field test

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Frontiers of Structural and Civil Engineering 2022年第8期16卷 1003-1016页

作者： Dung Quang VU Fazal EJALAL Mudassir IQBAL Dam Duc nguyen Duong kien trong Indra PRAKASH Binh Thai PHAM University of Transport Technology Hanoi 100000Vietnam Department of Civil Engineering Shanghai Jiao Tong UniversityShanghai 200240China Department of Civil Engineering University of Engineering and TechnologyPeshawar 25120Pakistan DDG(R)Geological Survey of India Gandhinagar 382010India

In this study,we developed novel hybrid models namely Adaptive Neuro Fuzzy Inference System(ANFIS)optimized by Shuffled Complex Evolution(SCE)on the one hand and ANFIS with Artificial Bee Colony(ABC)on the other *** were used to predict compressive strength(Cs)of concrete relating to thirteen concrete-strength affecting parameters which are easy to determine in the *** and laboratory tests data of 108 structural elements of 18 concrete bridges of the Ha Long-Van Don Expressway,Vietnam were *** dataset was randomly divided into a 70:30 ratio,for training(70%)and testing(30%)of the hybrid *** of the developed fuzzy metaheuristic models was evaluated using standard statistical metrics:Correlation Coefficient(R),Root Mean Square Error(RMSE)and Mean Absolute Error(MAE).The results showed that both of the novel models depict close agreement between experimental and predicted ***,the ANFIS-ABC model reflected better convergence of the results and better performance compared to that of ANFIS-SCE in the prediction of the concrete ***,the ANFIS-ABC model can be used for the quick and accurate estimation of compressive strength of concrete based on easily determined parameters for the design of civil engineering structures including bridges.

关键词： shuffled complex evolution artificial bee colony ANFIS concrete compressive strength Vietnam