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Accuracy assessment of mine walls＇ surface models derived from terrestrial laser scanning

International Journal of Coal Science & Technology 2018年第3期5卷 328-338页

作者： Nguyen Quoc Long Michal M. Buczek La Phu Hien Sylwia A. Szlapinska bui xuan nam Nguyen Viet Nghia Cao xuan Cuong Department of Mine Surveying Hanoi University of Mining and Geology Hanoi Vietnam Department of Mine Surveying AGH University of Science and Technology Kxakow Poland Department of Surveying and Spatial Data Analysis Hanoi University of Mining and Geology Hanoi Vietnam Department of Surface Mining Hanoi University of Mining and Geology Hanoi Vietnam

The monitoring of highwall slopes at open-pit mines is an important task to ensure safe mining. For this reason, several techniques such as total station, radar, terrestrial Light Detection and Ranging （LIDAR） can be employed for surface measurement. The objective of this study is to investigate mesh algorithms, which can be used to interpolate 3D models of pit walls. Experiments were carried out at Coc Sau open-pit mine at Quang Ninh province of Vietnam, and at experimental mine of Akademia Gtrniczo-Hutnicza University of Science and Technology in Cracow, Poland. First, 3D point cloud data for the study area was acquired by using terrestrial LIDAR, then was used to generate mesh surfaces using three algorithms--Delaunay 2.5D XY Plane, Delaunay 2.5D Best Fitting Plane, and Mesh from Points. After that, the results were rectified and optimized. Subsequently, the optimized meshes were used for generation of non-uniform rational basis spline （NURBS） surfaces. Then, the NURBS surface accuracy was assessed. The results showed that the average distance between surface and point cloud was within range of 5.6-5.8 mm with deviation of 6.2-6.8 mm, depending on the used mesh. Additionally, the quality of surfaces depends on the quality of input data set and the algorithm used to generate mesh network, and the accuracy of computed NURBS surfaces fitting into pointset was 4-5 times lower than that of optimized mesh fitting. However, the accuracy of the final product allows determining displacements on the level of centimeters.

关键词： Polygon mesh network NURBS surface LIDAR - Open-pit mine Highwall slope

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基于基因表达编程和粒子群优化鲁棒混合计算模型的深部地下矿井岩爆分类

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土木与环境工程学报（中英文） 2023年第2期45卷 21-38页

作者： TRAN Quang-Hieu bui xuan-nam NGUYEN Hoang Department of Surface Mining Mining Faculty/Innovations for Sustainable and Responsible Mining(ISRM)Research GroupHanoi University of Mining and GeologyHanoi 100000Vietnam

在深部地下采矿中,岩爆因具有许多不利影响(如对人员、设备、隧道/地下矿山工作面和开采周期等的影响)而被视为不确定性风险。由于其不确定性的特征,对岩爆趋势的准确预测和分类具有一定难度,且已有研究成果较少。提出一种基于基因表达... 详细信息

在深部地下采矿中,岩爆因具有许多不利影响(如对人员、设备、隧道/地下矿山工作面和开采周期等的影响)而被视为不确定性风险。由于其不确定性的特征,对岩爆趋势的准确预测和分类具有一定难度,且已有研究成果较少。提出一种基于基因表达编程(GEP)和粒子群优化(PSO)的鲁棒混合计算模型GEP-PSO,用于预测和分类深部开口的岩爆趋势,提高了预测和分类的准确性。在建立GEP-PSO模型的过程中,评估GEP模型中不同数量的基因(1~4)和连接功能(例如,加法、提取、乘法和除法)。收集246次岩爆发生的地质和施工因素,用于建立岩爆分类的GEP-PSO模型;应用处理数据集缺失值的技术改进数据集的属性;用相关矩阵选取潜在输入参数的特征;建立13个混合GEP-PSO模型,得到各模型的精度。结果表明:在GEP结构中具有3个基因和乘法连接函数的GEP-PSO模型具有最高的准确度(80.49%)。将获得的最佳GEP-PSO模型的结果与基于相同数据集开发的各种已有模型进行比较,结果表明,选择的GEP-PSO模型结果优于已有模型,表明提出的GEP-PSO模型在岩爆等级的预测和分类方面的准确性显著提高,可以应用于深开挖工程中,以准确预测和评估岩爆敏感性。

关键词：岩爆 GEP-PSO模型地下采矿深开挖风险评估

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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

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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

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Photocatalytic degradation of antibiotic sulfamethizole by visible light activated perovskite LaZnO_(3)

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Journal of Environmental Sciences 2024年第10期144卷 212-224页

作者： bui The Huy XCuong Nguyen Vu Khac Hoang bui Nguyen Ngoc Tri Iqra Rabani Nhu Hoa Thi Tran Quang Viet Ly Hai Bang Truong Major of Biomedical Engineering Division of Smart HealthcareCollege of Information Technology and ConvergencePukyong National UniversityBusan 48513Korea Center for Advanced Chemistry Institute of Research and DevelopmentDuy Tan UniversityDa Nang 550000Viet Nam Faculty of Environmental and Chemical Engineering Duy Tan UniversityDa Nang 550000Viet Nam Department of Environment and Energy Sejong UniversitySeoul 05006Korea Lab of Computational Chemistry and Modelling Department of ChemistryFaculty of Natural SciencesQuy Nhon UniversityQuy NhonViet Nam Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Korea Faculty of Materials Science and Technology University of ScienceHo Chi Minh City 700000Viet Nam Vietnam National University Ho Chi Minh City 700000Viet Nam Department of Environmental Engineering Seoul National University of Science and TechnologySeoul 01811Korea Optical Materials Research Group Science and Technology Advanced InstituteVan Lang UniversityHo Chi Minh CityViet Nam Faculty of Applied Technology School of TechnologyVan Lang UniversityHo Chi Minh CityViet Nam

In thiswork,the perovskite LaZnO_(3) was synthesized via sol-gel method and applied for photocatalytic treatment of sulfamethizole(SMZ)antibiotics under visible light *** was almost completely degraded(99.2%±0.3%)within 4 hr by photocatalyst LaZnO3 at the optimal dosage of 1.1 g/L,with amineralization proportion of 58.7%±0.4%.The efficient performance of LaZnO_(3) can be attributed to itswide-range light absorption and the appropriate energy band edge levels,which facilitate the formation of active agents such as·O_(2)^(−),h^(+),and·*** integration of RP-HPLC/Q-TOF-MS and DFT-based computational techniques revealed three degradation pathways of SMZ,which were initiated by the deamination reaction at the aniline ring,the breakdown of the sulfonamidemoieties,and a process known as Smile-type rearrangement and SO2 *** toxicity of SMZ and the intermediateswere analyzed by quantitative structure activity relationship(QSAR),indicating the effectiveness of LaZnO_(3)-based photocatalysis in preventing secondary pollution of the intermediates to the ecosystem during the degradation *** visible-light-activated photocatalyst LaZnO_(3) exhibited efficient performance in the occurrence of inorganic anions and maintained high durability across multiple recycling tests,making it a promising candidate for practical antibiotic treatment.

关键词： Perovskite Antibiotics Photocatalysis Density functional theory Toxicity

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Novel Soft ComputingModel for Predicting Blast-Induced Ground Vibration in Open-Pit Mines Based on the Bagging and Sibling of Extra Trees Models

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Computer Modeling in Engineering & Sciences 2023年第3期134卷 2227-2246页

作者： Quang-Hieu Tran Hoang Nguyen xuan-nam bui Department of Surface Mining Mining FacultyHanoi University of Mining and GeologyHanoi100000Vietnam Innovations for Sustainable and Responsible Mining(ISRM)Research Group Hanoi University of Mining and GeologyHanoi100000Vietnam

This study considered and predicted blast-induced ground vibration(PPV)in open-pit mines using bagging and sibling techniques under the rigorous combination of machine learning ***,four machine learning algorithms,including support vector regression(SVR),extra trees(ExTree),K-nearest neighbors(KNN),and decision tree regression(DTR),were used as the base models for the purposes of combination and PPV initial *** bagging regressor(BA)was then applied to combine these base models with the efforts of variance reduction,overfitting elimination,and generating more robust predictive models,abbreviated as BA-ExTree,BAKNN,BA-SVR,and *** is emphasized that the ExTree model has not been considered for predicting blastinduced ground vibration before,and the bagging of ExTree is an innovation aiming to improve the accuracy of the inherently ExTree model,as *** addition,two empirical models(i.e.,USBM and Ambraseys)were also treated and compared with the bagging models to gain a comprehensive *** this aim,we collected 300 blasting events with different parameters at the Sin Quyen copper mine(Vietnam),and the produced PPV values were also *** were then compiled as the dataset to develop the PPV predictive *** results revealed that the bagging models provided better performance than the empirical models,except for the BA-DTR *** those,the BA-ExTree is the best model with the highest accuracy(i.e.,88.8%).Whereas,the empirical models only provided the accuracy from 73.6%–76%.The details of comparisons and assessments were also presented in this study.

关键词： Mine blasting blast-induced ground vibration environmentally friendly blasting peak particle velocity bagging extra trees

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Predicting roof displacement of roadways in underground coal mines using adaptive neuro-fuzzy inference system optimized by various physics-based optimization algorithms

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Journal of Rock Mechanics and Geotechnical Engineering 2021年第6期13卷 1452-1465页

作者： Chengyu Xie Hoang Nguyen xuan-nam bui Van-Thieu Nguyen Jian Zhou School of Environment and Resources Xiangtan UniversityXiangtan411105China Mining Faculty Hanoi University of Mining and GeologyHanoi100000Viet Nam Innovations for Sustainable and Responsible Mining(ISRM)Group Hanoi University of Mining and GeologyHanoi100000Viet Nam Artificial Intelligence Independent Research Group Hanoi100000Viet Nam School of Resources and Safety Engineering Central South UniversityChangsha410083China

Due to the rapid industrialization and the development of the economy in each country,the demand for energy is increasing *** coal mines have to pace up the mining operations with large production to meet the energy *** requirement has led underground coal mines to go deeper with more difficult conditions,especially the mining hazards,such as large deformations,rockburst,coal burst,roof collapse,to name a ***,this study aims at investigating and predicting the stability of the roadways in underground coal mines exploited by longwall mining method,using various novel intelligent techniques based on physics-based optimization algorithms(***-verse optimizer(MVO),equilibrium optimizer(EO),simulated annealing(SA),and Henry gas solubility optimization(HGSO)) and adaptive neuro-fuzzy inference system(ANFIS),named as MVO-ANFIS,EO-ANFIS,SA-ANFIS and HGSOANFIS ***,162 roof displacement events were investigated based on the characteristics of surrounding rocks,such as cohesion,Young’s modulus,density,shear strength,angle of internal friction,uniaxial compressive strength,quench durability index,rock mass rating,and tensile *** MVO-ANFIS,EO-ANFIS,SA-ANFIS and HGSO-ANFIS models were then developed and evaluated based on this dataset for predicting roof displacements in roadways of underground *** results indicated that the proposed intelligent techniques could accurately predict the roof displacements in roadways of underground mines with an accuracy in the range of 83%-92%.Remarkably,the SA-ANFIS model yielded the most dominant accuracy(i.e.92%).Based on the accurate predictions from the proposed techniques,the reinforced solutions can be timely suggested to ensure the stability of roadways during exploiting coal,especially in the underground coal mines exploited by the longwall mining.

关键词： Roof displacement Longwall mining Underground mine Physics-based optimization Risk assessment Mining hazards

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Advancing Wound Filling Extraction on 3D Faces:An Auto-Segmentation and Wound Face Regeneration Approach

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2197-2214页

作者： Duong Q.Nguyen Thinh D.Le Phuong D.Nguyen Nga T.K.Le H.Nguyen-xuan Department of Mathematics and Statistics Quy Nhon UniversityQuy Nhon City55100Viet Nam Applied Research Institute for Science and Technology Quy Nhon UniversityQuy Nhon City55100Viet Nam CIRTECH Institute HUTECH UniversityHo Chi Minh City72308Viet Nam

Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical *** this paper,we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional *** method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss *** achieve accurate segmentation,we conducted thorough experiments and selected a high-performing model from the *** selectedmodel demonstrates exceptional segmentation performance for complex 3D facial ***,based on the segmentation model,we propose an improved approach for extracting 3D facial wound fillers and compare it to the results of the previous *** method achieved a remarkable accuracy of 0.9999993% on the test suite,surpassing the performance of the previous *** this result,we use 3D printing technology to illustrate the shape of the wound *** outcomes of this study have significant implications for physicians involved in preoperative planning and intervention *** automating facial wound segmentation and improving the accuracy ofwound-filling extraction,our approach can assist in carefully assessing and optimizing interventions,leading to enhanced patient ***,it contributes to advancing facial reconstruction techniques by utilizing machine learning and 3D bioprinting for printing skin tissue *** source code is available at https://***/SIMOGroup/WoundFilling3D.

关键词： 3D printing technology face reconstruction 3D segmentation 3D printed model

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Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

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Geoscience Frontiers 2021年第3期12卷 458-472页

作者： Chengyu Xie Hoang Nguyen xuan-nam bui Yosoon Choi Jian Zhou Thao Nguyen-Trang School of Environment and Resources Xiangtan UniversityXiangtan 411105China Institute of Research and Development Duy Tan UniversityDa Nang 550000Viet Nam Department of Surface Mining Mining FacultyHanoi University of Mining and Geology18 Pho VienDuc Thang wardBac Tu Liem districtHanoi 100000Viet Nam Center for Mining Electro-Mechanical researchHanoi University of Mining and Geology18 Pho VienDuc Thang wardBac Tu Liem districtHanoi 100000Viet Nam Department of Energy Resources Engineering Pukyong National UniversityBusan 48513Republic of Korea School of Resources and Safety Engineering Central South UniversityChangsha 410083HunanChina Division of Computational Mathematics and Engineering Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh City 700000Viet Nam Faculty of Mathematics and Statistics Ton Duc Thang UniversityHo Chi Minh City 700000Viet Nam

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit *** evaluate the quality of blasting,the size of rock distribution is used as a critical criterion in blasting operations.A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental ***,this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters,as well as the efficiency of blasting operation in open ***,a nature-inspired algorithm(i.e.,firefly algorithm-FFA)and different machine learning algorithms(i.e.,gradient boosting machine(GBM),support vector machine(SVM),Gaussian process(GP),and artificial neural network(ANN))were combined for this aim,abbreviated as FFA-GBM,FFA-SVM,FFA-GP,and FFA-ANN,***,predicted results from the abovementioned models were compared with each other using three statistical indicators(e.g.,mean absolute error,root-mean-squared error,and correlation coefficient)and color intensity *** developing and simulating the size of rock in blasting operations,136 blasting events with their images were collected and analyzed by the Split-Desktop *** which,111 events were randomly selected for the development and optimization of the ***,the remaining 25 blasting events were applied to confirm the accuracy of the proposed ***,blast design parameters were regarded as input variables to predict the size of rock in blasting ***,the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench *** the models developed in this study,FFA-GBM provided the highest accuracy in predicting the size of fragmented *** other techniques(i.e.,FFA-SVM,FFA-GP,and FFA-ANN)yielded lower computational stability and ***,the FFA-GBM model can be used as a powerful

关键词： Mine blasting Rock fragmentation Artificial intelligence Hybrid model Gradient boosting machine Meta-heuristic algorithm

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Comparative Chemical Research in Essential Oils from Six Apiaceae Species Growing in the Northern Region of Vietnam

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Phyton-International Journal of Experimental Botany 2024年第7期93卷 1677-1687页

作者： Nguyen Quang Hung Nguyen Thanh Tung Nguyen Phuong Hanh Chu Thi Thu Ha Nguyen Thi Nhung Nguyen Thai An Vu xuan Giang Luong Van Hao Oleh Koshovyi Ain Raal Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology(VAST)Cau GiayHa Noi100000Viet Nam Graduate University of Science and Technology Vietnam Academy of Science and Technology(VAST)Cau GiayHa Noi100000Viet Nam Department of Pharmacognosy Faculty of Pharmacognosy and Traditional MedicineHanoi University of PharmacyHoan KiemHa Noi100000Viet Nam Sa Pa Research Center of Medicinal Materials National Institute of Medicinal MaterialsDien Bien PhuSa PaLao Cai330000Viet Nam Institute of Pharmacy Faculty of MedicineUniversity of TartuTartu50411Estonia

Our study aimed to compare the essential oil(EO)concentration and composition of several Apiaceae species growing in the Northern region of *** yields of EOs from materials ranged from 0.03%(root EO of Angelica acutiloba and aerial parts EO of Heracleum bivittatum)-0.27%(leaf EO of Xyloselinum vietnamense).Gas chromatography-mass spectrometry(GC-MS)allowed the identiﬁcation of 74 components in the EOs of six Apiaceae species,making up 94.4%–100.0%of the *** EO from Angelica acutiloba,(Z)-ligustilide accounted for an extremely large proportion(94.9%).EO of Angelica pubescens was dominated by six character-istic components includingα-pinene(21.5%),β-phellandrene(18.1%),p-cymene(12.2%),3-methylnonane(8.7%),o-cymene(8.1%),and D-sylvestrene(6.2%).The EO from Cryptotaenia japonica was characterized by high amounts ofα-selinene(48.7%),β-selinene(23.7%),and trans-β-farnesene(5.4%).The EOs from leaves and stems of Xyloselinum vietnamense were characterized by high concentrations of sabinene(69.8%and 33.8%),4-terpineol(8.7%and 7.4%)andβ-pinene(4.0%and 6.5%)while EOs from aerial parts and root of Xylo-selinum leonidii comprise four characteristic monoterpenes includingα-pinene(28.2%and 52.8%),β-pinene(7.9%and 10.3%),β-phellandrene(7.6%and 15.3%),and sabinene(3.0%and 4.1%).Additionally,cryptone is also one of the major components in the EO of Xyloselinum leonidii(13.2%in the aerial parts oil and 2.8%in the root oil).In the EOs isolated from the aerial parts and root of Heracleum bivittatum,α-pinene(22.5%and 70.2%)andβ-pinene(43.2%and 20.0%)were the predominant *** appeared in the EO from aerial parts of Heracleum bivittatum with a relatively high concentration(13.5%)while bornyl acetate(5.1%)was also one of the main components in the EO from its aerial parts but was not detected in other Apiaceae species in the present *** databases help identify and control the quality of plant material studied from the family Apiaceae growing in Vietnam.

关键词： Apiaceae essential oil terpenoids gaschromatography-mass spectrometry

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