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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

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

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(Ovantages of our proposed method.

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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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 AST60 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

Shear strength model of the reinforced concrete beams with embedded through-section strengthening bars

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Frontiers of Structural and Civil Engineering 2022年第7期16卷 843-857页

作者： Linh van Hong bui Phuoc Trong NGUYEN Faculty of Civil Engineering Ho Chi Minh City Open UniversityHo Chi Minh City 700000Vietnam

In this study,finite element(FE)analysis is utilized to investigate the shear capacity of reinforced concrete(RC)beams strengthened with embedded through-section(ETS)*** of critical variables on the beam shear strength,including the compressive strength of concrete,stiffness ratio between ETS bars and steel stirrups,and use of ETS strengthening system alone,are parametrically investigated.A promising method based on the bond mechanism between ETS strengthening and concrete is then proposed for predicting the shear resistance forces of the strengthened *** expression for the maximum bond stress of the ETS bars to concrete is *** new expression eliminates the difficulty in the search and selection of appropriate bond parameters from adhesion *** results obtained from the FE models and analytical models are validated by comparison with those measured from the ***,the model proposed in this study demonstrates better performance and more accuracy for prediction of the beam shear-carrying capacity than those of existing *** results obtained from this study can also serve researchers and engineers in selection of the proper shear strength models for design of ETS-strengthened RC beams.

关键词： embedded through-section strengthening fiber-reinforced polymer finite element shear strength model bond mechanism

Combining SnO_(2-x)and g-C_(3)N_(4)nanosheets toward S-scheme heterojunction for high selectivity into green products of NO degradation reaction under visible light

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Journal of Materiomics 2022年第1期8卷 1-8页

作者： Pham van Viet Thanh-Dat Nguyen Dai-Phat bui Cao Minh Thi Faculty of Materials Science and Technology University of ScienceVNU-HCM227 Nguyen Van Cu StreetDistrict 5Ho Chi Minh City700000Viet Nam Vietnam National University-Ho Chi Minh City Thu Duc DistrictHo Chi Minh City700000Viet Nam Ho Chi Minh City University of Technology(HUTECH) 475A Dien Bien Phu StreetBinh Thanh DistrictHo Chi Minh City700000Viet Nam

NOx emissions cause many negative impacts on the living *** photocatalysis of semiconductors is superior for nitric oxide(NO)degradation due to their low redox *** this report,we combine SnO_(2-x)/g-C_(3)N_(4)heterojunction photocatalyst toward the high selectivity into green products under visible light *** show that SnO_(2-x)/g-C_(3)N_(4)heterojunction degraded 40.8%of NO,which is 1.6 times higher than that of g-C_(3)N_(4).In addition,the selectivity coefficient of SnO_(2-x)/g-C_(3)N_(4)is higher 3 times than both pure SnO_(2-x)and g-C_(3)N_(4).Furthermore,SnO_(2-x)/g-C_(3)N_(4)expresses a superior stability for NO photocatalytic-degradation after five *** scavenger trapping test results,and electron spin resonance(ESR)analysis also provide more understanding of the charge transfer mechanism of ***_(2-x)/g-C_(3)N_(4)heterojunction shows a high removal efficiency of NO gas,making it an up-and-coming environmental treatment candidate.

关键词： G-C_(3)N_(4) NO removal Oxygen vacancies Photocatalysis S-scheme