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Combining Entropy Optimization and Sobel Operator for Medical Image Fusion

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Computer Systems Science & Engineering 2023年第1期44卷 535-544页

作者： nguyen Tu trung Tran Thi Ngan Tran Manh Tuan To Huu nguyen Faculty of Computer Science and Engineering Thuyloi University175 Tay SonDong DaHanoi010000Vietnam University of Information and Communication Technology Thai Nguyen UniversityThai Nguyen240000Vietnam

Fusing medical images is a topic of interest in processing medical *** is achieved to through fusing information from multimodality images for the purpose of increasing the clinical diagnosis *** fusion aims to improve the image quality and preserve the specific *** methods of medical image fusion generally use knowledge in many differentfields such as clinical medicine,computer vision,digital imaging,machine learning,pattern recognition to fuse different medical *** are two main approaches in fusing image,including spatial domain approach and transform domain *** paper proposes a new algorithm to fusion multimodal *** algorithm is based on Entropy optimization and the Sobel *** transform is used to split the input images into components over the low and high frequency ***,two fusion rules are used for obtaining the fusing *** rule,based on the Sobel operator,is used for high frequency *** second rule,based on Entropy optimization by using Particle Swarm Optimization(PSO)algorithm,is used for low frequency *** algorithm is implemented on the images related to central nervous system *** experimental results of the paper show that the proposed algorithm is better than some recent methods in term of brightness level,the contrast,the entropy,the gradient and visual informationfidelity for fusion(VIFF),Feature Mutual Information(FMI)indices.

关键词： Medical image fusion wavelet entropy optimization PSO Sobel operator

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

The mechanism and effects of subgrade fluidisation under ballasted railway tracks

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Railway Engineering Science 2020年第2期28卷 113-128页

作者： Buddhima Indraratna Mandeep Singh Thanh trung nguyen Centre for Geomechanics and Railway Engineering University of WollongongWollongong CityNSW 2522Australia Australian Research Council(ARC)Industrial Transformation Training Centre ITTC-RailUniversity of WollongongWollongong CityNSW 2522Australia

The rapid growth in railway infrastructure and the construction of high-speed heavy-haul rail network,especially on ground that is basically unsuitable,poses challenges for geotechnical engineers because a large part of the money invested in the development of railway lines is often spent on track *** fact around the world,the mud pumping of subgrade fines is one of the common reasons why track performance deteriorates and track stability is *** article presents a series of laboratory tests to examine following aspects of mud pumping:(1)the mechanisms of subgrade fluidisation under undrained condition,(2)the effects of mud pumping on the engineering characteristics of ballast,and(3)the use of vertical drains to stabilize subgrade under cyclic *** undrained cyclic triaxial testing on vulnerable soft subgrade was performed by varying the cyclic stress ratio(CSR)from 0.2 to 1.0 and the loading frequency f from 1.0 to 5.0 *** is seen from the test results that for a specimen compacted at an initial dry density of 1790 kg/m3,the top portion of the specimen fluidises at CSR=0.5,irrespective of the applied loading *** cyclic railway loading,the internal redistribution of water at the top of the subgrade layer softens the soil and also reduces its *** response to these problems,this paper explains how the inclusion of vertical drains in soft subgrade will help to prevent mud pumping by alleviating the build-up of excess pore pressures under moving train loads.

关键词： Mud pumping Ballasted track Subgrade fluidisation Fouled ballast Prefabricated vertical drains

Orange G degradation by heterogeneous peroxymonosulfate activation based on magnetic MnFe_(2)O_(4)/α-MnO_(2) hybrid

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Journal of Environmental Sciences 2023年第2期124卷 379-396页

作者： Le Thi Thao To Van nguyen Van Quy nguyen Ngoc Man Phan Ki Jae Kim nguyen Nhat Huy nguyen trung Dung Faculty of Physical and Chemical Engineering Le Quy Don Technical UniversityHanoi 100000Vietnam Department of Energy Engineering Konkuk UniversitySeoul 05029Korea School of Chemical Engineering College of EngineeringSungkyunkwan UniversityJangan-guSuwon 16419Korea Faculty of Environment and Natural Resources Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh City 700000Vietnam Vietnam National University Ho Chi Minh City Linh Trung WardThu Duc CityHo Chi Minh City 700000Vietnam

Wastewater containing an azo dye Orange G(OG)causes massive environmental pollution,thus it is critical to develop a highly effective,environmental-friendly,and reusable catalyst in peroxymonosulfate(PMS)activation for OG *** this work,we successfully applied a magnetic MnFe_(2)O_(4)/α-MnO_(2) hybrid fabricated by a simple hydrothermal method for OG removal in *** characteristics of the hybrid were investigated by Xray diffraction,scanning electron microscopy,energy-dispersive X-ray spectroscopy,Fourier transform infrared spectroscopy,Brunauer–Emmett–Teller method,vibrating sample magnetometry,electron paramagnetic resonance,thermogravimetric analysis,and X-ray photoelectron *** effects of operational parameters(i.e.,catalytic system,catalytic dose,solution pH,and temperature)were *** results exhibited that 96.8% of OG degradation was obtained with MnFe_(2)O_(4)/α-MnO2(1:9)/PMS system in 30 min regardless of solution pH ***,the possible reaction mechanism of the coupling system was proposed,and the degradation intermediates of OG were identified by mass *** radical quenching experiments and EPR tests demonstrated that SO_(4)•̶,O_(2)•̶,and 1O2 were the primary reactive oxygen species responsible for the OG *** hybrid also displayed unusual stability with less than 30%loss in the OG removal after four sequential ***,magnetic MnFe2O4/α-MnO2 hybrid could be used as a high potential activator of PMS to remove orange G and maybe other dyes from wastewater.

关键词： MnFe_(2)O_(4)/α-MnO_(2) Peroxymonosulfate Orange G Catalytic degradation Reusability

A combination of damage locating vector method （DLV） and differential evolution algorithm （DE） for structural damage assessment

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Frontiers of Structural and Civil Engineering 2018年第1期12卷 92-108页

作者： T. nguyen-thoi A. TRAN-VIET N. nguyen-MINH T. VO-DUY V. HO-HUU Division of Computational Mathematics and Engineering Institute for Computational Science Ton Duc Thang University Hochiminh City Vietnam Division of Construction Computation Institute for Computational Science Ton Duc Thang University Hochiminh City Vietnam Faculty of Civil Engineering Ton Duc Thang University Hochiminh City Vietnam

In this study, a two-stage method is presented for identifying multiple damage scenarios. In the first stage, the damage locating vector （DLV） method using normalized cumulative energy （nce） is employed for damage localization in structures. In the second stage, the differential evolution algorithm （DE） is used for damage severity of the structures. In addition, in the second stage, a modification of an available objective function is made for handing the issue of symmetric structures. To verify the effectiveness of the present technique, numerical examples of a 72-bar space truss and a one-span steel portal frame are considered. In addition, the effect of noise on the performance of the identification results is also investigated. The numerical results show that the proposed combination gives good assessment of damage location and extent for multiple structural damage cases.

关键词： damage assessment damage locating vector method (DLV) differential evolution (DE) multiple damagelocation assurance criterion (MDLAC) mode shape error function

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

A deep feed-forward neural network for damage detection in functionally graded carbon nanotube-reinforced composite plates using modal kinetic energy

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Frontiers of Structural and Civil Engineering 2021年第6期15卷 1453-1479页

作者： Huy Q.LE Tam T.TRUONG D.DINH-CONG T.nguyen-thoi Division of Computational Mathematics and Engineering Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh City 700000Vietnam Faculty of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh City 700000Vietnam Division of Construction Computation Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh City 700000Vietnam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh City 700000Vietnam

This paper proposes a new Deep Feed-forward Neural Network(DFNN)approach for damage detection in functionally graded carbon nanotube-reinforced composite(FG-CNTRC)*** the proposed approach,the DFNN model is developed based on a data set containing 20000 samples of damage scenarios,obtained via finite element(FE)simulation,of the FG-CNTRC *** elemental modal kinetic energy(MKE)values,calculated from natural frequencies and translational nodal displacements of the structures,are utilized as input of the DFNN model while the damage locations and corresponding severities are considered as *** state-of-the art Exponential Linear Units(ELU)activation function and the Adamax algorithm are employed to train the DFNN ***,in order to enhance the performance of the DFNN model,the mini-batch and early-stopping techniques are applied to the training process.A trial-and-error procedure is implemented to determine suitable parameters of the network such as the number of hidden layers and the number of neurons in each *** accuracy and capability of the proposed DFNN model are illustrated through two distinct configurations of the CNT-fibers constituting the FG-CNTRC plates including uniform distribution(UD)and functionally graded-V distribution(FG-VD).Furthermore,the performance and stability of the DFNN model with the consideration of noise effects on the input data are also *** results indicate that the proposed DFNN model is able to give sufficiently accurate damage detection outcomes for the FG-CNTRC plates for both cases of noise-free and noise-influenced data.

关键词： damage detection deep feed-forward neural networks functionally graded carbon nanotube-reinforced composite plates modal kinetic energy

Discrete-time sliding mode control with power rate exponential reaching law of a pneumatic artificial muscle system

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Control Theory and Technology 2022年第4期20卷 514-524页

作者： Quy-Thinh Dao trung-Kien Le Tri Van-Anh nguyen Manh-Linh nguyen School of Electrical and Electronic Engineering Hanoi University of Science and TechnologyDai Co VietHanoi 11615Vietnam

This paper develops a discrete-time sliding mode controller with a power rate exponential reaching law approach to enhance the performance of a pneumatic artificial muscle system in both reaching time and chattering *** proposed method dynamically adapts to the variation of the switching function,which is based on an exponential term and a power rate term of the sliding ***,the controlled system can achieve high tracking performance while still obtain chattering-free ***,the effectiveness of the proposed method is validated through multiple experimental tests,focused on a dual pneumatic artificial muscle ***,experimental results show the effectiveness of the proposed approach in this paper.

关键词： Pneumatic artificial muscle Discrete-time sliding mode control Exponential reaching law Chattering

Properties of poly（1-naphthylamine）/Fe3O4 composites and arsenic adsorption capacity in wastewater

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Frontiers of Materials Science 2016年第1期10卷 56-65页

作者： Minh Thi TRAN Thi Huyen Trang nguyen Quoc trung VU Minh Vuong nguyen Faculty of Physics Hanoi National University of Education 136-Xuanthuy Street Caugiay District Hanoi Vietnam Faculty of Chemistry Hanoi National University of Education 136-Xuanthuy Street Caugiay District Hanoi Vietnam Department of Physics Quynhon University 170 An Duong Vuong Quynhon Vietnam

The research results of poly（1-naphthylamine）lFe3O4 （PNA/Fe3O4） nanocomposites synthesized by a chemical method for As（Ⅲ） wastewater treatment are presented in this paper. XRD patterns and TEM images showed that the Fe3O4 grain size varied from 13 to 20 nm. The results of Raman spectral analysis showed that PNA participated in part of the PNA/Fe3O4 composite samples. The grain size of PNA/Fe3O4 composite samples is about 25-30 nm measured by SEM. The results of vibrating sample magnetometer measurements at room temperature showed that the saturation magnetic moment of PNA/Fe3O4 samples decreased from 63.13 to 43.43 emu/g, while the PNA concentration increased from 5% to 15%. The nitrogen adsorption-desorption isotherm of samples at 77 K at a relative pressure PIPo of about 1 was studied in order to investigate the surface and porous structure of nanoparticles by the BET method. Although the saturation magnetic moments of samples decreased with the polymer concentration increase, the arsenic adsorption capacity of the PNA/Fe3O4 sample with the PNA concentration of 5% is better than that of Fe3O4 in a solution with pH = 7. In the solution with pH 〉 14, the arsenic adsorption of magnetic nanoparticles is insignificant.

关键词： poly(1-naphthylamin)/Fe3O4 nanocomposite magnetization arsenic adsorption