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A New Framework for Software Vulnerability Detection Based on an Advanced Computing

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Computers, Materials & Continua 2024年第6期79卷 3699-3723页

作者： bui Van Cong Cho Do Xuan Department of Information Technology University of Economics and Technical IndustriesHanoi100000Vietnam Faculty of Information Security Posts and Telecommunications Institute of TechnologyHanoi100000Vietnam

The detection of software vulnerabilities written in C and C++languages takes a lot of attention and interest *** paper proposes a new framework called DrCSE to improve software vulnerability *** uses an intelligent computation technique based on the combination of two methods:Rebalancing data and representation learning to analyze and evaluate the code property graph(CPG)of the source code for detecting abnormal behavior of software *** do that,DrCSE performs a combination of 3 main processing techniques:(i)building the source code feature profiles,(ii)rebalancing data,and(iii)contrastive *** which,the method(i)extracts the source code’s features based on the vertices and edges of the *** method of rebalancing data has the function of supporting the training process by balancing the experimental ***,contrastive learning techniques learn the important features of the source code by finding and pulling similar ones together while pushing the outliers *** experiment part of this paper demonstrates the superiority of the DrCSE Framework for detecting source code security vulnerabilities using the Verum *** a result,the method proposed in the article has brought a pretty good performance in all metrics,especially the Precision and Recall scores of 39.35%and 69.07%,respectively,proving the efficiency of the DrCSE *** performs better than other approaches,with a 5%boost in Precision and a 5%boost in ***,this is considered the best research result for the software vulnerability detection problem using the Verum dataset according to our survey to date.

关键词： Source code vulnerability source code vulnerability detection code property graph feature profile contrastive learning data rebalancing

An Efficient Smoothing and Thresholding Image Segmentation Framework with Weighted Anisotropic-lsotropicTotalVariation

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Communications on Applied Mathematics and Computation 2024年第2期6卷 1369-1405页

作者： Kevin bui Yifei Lou Fredrick Park Jack Xin Department of Mathematics University of CaliforniaIrvineIrvineCA 92697-3875USA Department of Mathematics University of North CarolinaChapel HillChapel HillNC 27599.USA Department of Mathematics and Computer Science Whittier CollegeWhittierCA 90602USA

In this paper,we design an efficient,multi-stage image segmentation framework that incorporates a weighted difference of anisotropic and isotropic total variation(AITV).The segmentation framework generally consists of two stages:smoothing and thresholding,thus referred to as smoothing-and-thresholding(SaT).In the first stage,a smoothed image is obtained by an AITV-regularized Mumford-Shah(MS)model,which can be solved efficiently by the alternating direction method of multipliers(ADMMs)with a closed-form solution of a proximal operator of the l_(1)-αl_(2) *** convergence of the ADMM algorithm is *** the second stage,we threshold the smoothed image by K-means clustering to obtain the final segmentation *** experiments demonstrate that the proposed segmentation framework is versatile for both grayscale and color images,effcient in producing high-quality segmentation results within a few seconds,and robust to input images that are corrupted with noise,blur,or *** compare the AITV method with its original convex TV and nonconvex TVP(O

关键词： Image segmentation Non-convex optimization Mumford-Shah(MS)model Alternating direction method of multipliers(ADMMs) Proximal operator

Modeling Geometrically Nonlinear FG Plates: A Fast and Accurate Alternative to IGA Method Based on Deep learning

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2793-2808页

作者： Se Li Tiantang Yu Tinh Quoc bui College of Mechanics and Materials Hohai UniversityNanjing211100China Duy Tan Research Institute for Computational Engineering(DTRICE) Duy Tan UniversityHo Chi Minh CityVietnam

Isogeometric analysis (IGA) is known to showadvanced features compared to traditional finite element *** IGA one may accurately obtain the geometrically nonlinear bending behavior of plates with functionalgrading (FG). However, the procedure is usually complex and often is time-consuming. We thus put forward adeep learning method to model the geometrically nonlinear bending behavior of FG plates, bypassing the complexIGA simulation process. A long bidirectional short-term memory (BLSTM) recurrent neural network is trainedusing the load and gradient index as inputs and the displacement responses as outputs. The nonlinear relationshipbetween the outputs and the inputs is constructed usingmachine learning so that the displacements can be directlyestimated by the deep learning network. To provide enough training data, we use S-FSDT Von-Karman IGA andobtain the displacement responses for different loads and gradient indexes. Results show that the recognition erroris low, and demonstrate the feasibility of deep learning technique as a fast and accurate alternative to IGA formodeling the geometrically nonlinear bending behavior of FG plates.

关键词： FG plates geometric nonlinearity deep learning BLSTM IGA S-FSDT

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

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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Velocity equation for grenades while impacting on dry sand media

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Defence Technology（防务技术） 2024年第5期35卷 168-173页

作者： Martin Macko Xuan Son bui Kongsathit Phanthavong Duc Hung Pham Van Gion Do Van Minh Do Jiri Skala University of Defence BrnoCzech Republic le Quy Don Technical University Ha NoiViet Nam

This paper deals with the collision of sphere shape grenades with sand *** central issue of the article is the establishing of an empirical velocity equation of the grenade while impacting on sand that is used to solve motion equations of the mechanical mechanism inside the impact grenade *** paper focuses on impact velocities that are lower than 5 m s^(-1).An experiment was conducted to study the velocity of the grenade while impacting on dry sand.A high-speed camera video was used to capture the grenade *** grenade velocity in the impact process was generated from these video *** types of fitting curves are used to regress the velocity equation of the grenade while interacting with the sand media and the best-fitting model is *** result shows the regression curve has a high correlation with the experiment data for grenade velocities below 5 m s^(-1).The received regression equation is useful for analyzing the working ability of the inertial mechanism inside the impact grenade or analyzing and choosing the appropriate parameters of each part in the inertial mechanism to meet the required characteristics of the mechanism.

关键词： Dynamic response Impact velocity Impact grenade Low-velocity impact

Improvement of hepatic fibrosis after tenofovir disoproxil fumarate switching to tenofovir alafenamide for three years

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World Journal of Hepatology 2024年第7期16卷 1009-1017页

作者： Tung Huynh Delana MyAn bui Tina Xiwen Zhou Ke-Qin Hu Department of Pharmacy University of California Irvine Medical CenterOrangeCA 92868United States University of Houston HoustonTX 77204United States Chicago Medical School at Rosalind Franklin University North ChicagoIL 60064United States Division of Gastroenterology and Hepatology University of California IrvineSchool of MedicineOrangeCA 92868United States

BACKGROUND Both tenofovir alafenamide(TAF)and tenofovir disoproxil fumarate(TDF)are the first-line treatments for chronic hepatitis B(CHB).We have showed switching from TDF to TAF for 96 weeks resulted in further alanine aminotransferase(ALT)improvement,but data remain lacking on the long-term benefits of TDF switching to TAF on hepatic *** To assess the benefits of TDF switching to TAF for 3 years on ALT,aspartate aminotransferase(AST),and hepatic fibrosis improvement in patients with *** A single center retrospective study on 53 patients with CHB who were initially treated with TDF,then switched to TAF to determine dynamic patterns of ALT,AST,AST to platelet ratio index(APRI),fibrosis-4(FIB-4)scores,and shear wave elastography(SWE)reading improvement at switching week 144,and the associated *** The mean age was 55(28-80);45.3%,males;15.1%,clinical cirrhosis;mean baseline ALT,24.8;AST,25.7 U/L;APRI,0.37;and FIB-4,*** 144 weeks TDF switching to TAF,mean ALT and AST were reduced to 19.7 and 21,*** baseline to switching week 144,the rates of ALT and ASTle)/25(female)andle)/19(female)were persistently increased;hepatic fibrosis was also improved by APRIle and the frequency of patients with glomerular filtration rate>60 mL/min was increased from 86.5%at baseline to 88.2%at switching week *** Our data confirmed that switching from TDF to TAF for 3 years results in not only persistent ALT/AST improvement,but also hepatic fibrosis improvement by APRI,FIB-4 scores,as well as SWE reading,the important clinical benefits of long-term hepatitis B virus antiviral treatment with TAF.

关键词： Tenofovir alafenamide Tenofovir disoproxil fumarate Switching Hepatic fibrosis improvement Aspartate aminotransferase to platelet ratio index Fibrosis-4 Shear wave elastography

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

Buckling Analysis of FG Porous Truncated Conical Shells Resting on Elastic Foundations in the Framework of the Shear Deformation Theory

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Advances in Applied Mathematics and Mechanics 2022年第1期14卷 218-247页

作者： le Kha Hoa bui Gia Phi Do Quang Chan Dang Van Hieu Military Academy of Logistics HanoiVietnam Department of Technical Fundamental University of Transport Technology54 Trieu Khuc9 Thanh XuanHanoiVietnam Department of Mechanical Engineering and Mechatronics PHENIKAA UniversityHanoi 12116Vietnam PHENIKAA Research and Technology Institute(PRATI) A&A Green Phoenix Group JSCNo.167 Hoang NganTrung HoaCau GiayHanoi 11313Vietnam Thainguyen University of Technology ThainguyenVietnam

In this article,an analytical method is proposed to analyze of the linear buckling behavior of the FG porous truncated conical shells subjected to a uniform axial compressive load and resting on the Pasternak elastic *** material properties including Young’s modulus,shear modulus and density are assumed to vary in the thickness *** types of FG porous distributions including symmetric porosity distribution,non-symmetric porosity and uniform porosity distribution are *** governing equations of the FG porous truncated conical shells are obtained by using the first-order shear deformation theory(FSDT).With the help of the Galerkin method,the expressions for critical buckling loads are obtained in closed *** reliability of the obtained results is verified by comparing the present solutions with the published ***,the numerical results show the effects of shell characteristics,porosity distribution,porosity coefficient,and elastic foundation on the critical buckling load.

关键词： Buckling truncated conical shells first order shear deformation theory porous materials elastic foundations