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Ilizarov胫骨横向骨搬移血管再生技术对下肢慢性缺血性疾病临床疗效的初步研究

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Ilizarov胫骨横向骨搬移血管再生技术对下肢慢性缺血性疾病临床疗...

作者：武黎黄英（vu le Hoang anh）广西医科大学

学位级别：硕士

目的：初步探讨Ilizarov胫骨横向骨搬移血管再生技术对下肢慢性缺血性疾病的临床疗效。方法：回顾分析2012年4月至2012年7月在我院住院行Ilizarov胫骨横向骨搬移血管再生技术对下肢慢性缺血性疾病的4例病人,共有5个患肢;用Fontaine分... 详细信息

目的：初步探讨Ilizarov胫骨横向骨搬移血管再生技术对下肢慢性缺血性疾病的临床疗效。方法：回顾分析2012年4月至2012年7月在我院住院行Ilizarov胫骨横向骨搬移血管再生技术对下肢慢性缺血性疾病的4例病人,共有5个患肢;用Fontaine分期法进行分期诊断治疗;其中临床诊断为“下肢血栓闭塞性脉管炎,TAO" Fontaine IV期女性1例;“下肢动脉硬化闭塞症,ASO" Fontaine IV期男性3例;其中4例病人均发生足趾缺血性坏死,渗出伴有恶嗅,溃疡、疼痛;3例病人有动脉粥样硬化,无糖尿病、高血压、肝肾功能不全;1例病人有高血压病3级级高危组、小脑梗死。术前行患肢CT扫描+血管三维重建(Computed Tomography Artery,CTA)动脉粥样硬化狭窄1个患肢、显示胭动脉闭塞2个患肢、胫前动脉栓塞1个患肢和足背动脉及足底内外侧动脉栓塞1个患肢、4例病人的股深动脉和(或)者股浅动脉通畅、远端流出道不良。术中在病人的胫骨内侧嵴上开一小块胫骨窗2x12cm,术后第3天开始以每天缓慢横向外搬移1mm的游离胫骨窗,分4次完成,20天后停止。通过刺激骨膜和胫骨骨髓再生,以及刺激新鲜微小动脉再生,并形成新生毛细血管网。新生毛细血管网与原来的毛细血管网相连通,改善患肢缺血供。结果：5个患肢中4个患肢获得满意疗效。3例病人术后随访时间3-7个月,平均4.7个月,1例失访。下肢缺血症状明显改善,溃疡创面愈合,无并发症。1例病人术后2个月仍有患肢严重血供不良,病人放弃治疗要求下肢截肢术。结论：Ilizarov骨搬移血管再生技术对下肢慢性缺血性疾病有较好的临床疗效,能促进骨膜、骨髓再生和外周新生血管网形成,改善患肢局部血供,以及促进创面愈合。本手术方法简便,易操作;创面小,术后病情改善快,有利于避免截肢,减轻患者痛苦,提高患者的生活质量;手术费药物用低;病情不易复发。

关键词： Ilizarov 骨搬移血管再生技术血栓闭塞性脉管炎动脉硬化闭塞症

Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine learning Models and Grid Search Optimization Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-anh Thi Bui Dam Duc Nguyen Hiep Van le Indra Prakash Binh Thai Pham Civil Engineering Department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine learning Models

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine learning Models Duc-Dam Nguyen Nguyen Viet Tiep Quynh-anh Thi Bui Hiep Van le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of Civil Engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic Engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania Department of Civil Engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India Department of Civil Engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Fabrication and characterization of YVO_4:Eu^(3+) nanomaterials by the microwave technique

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Journal of Rare Earths 2011年第12期29卷 1137-1141页

作者： Tran Thu Huong vu Duc Tu Tran Kim anh le Thi Vinh le Quoc Minh Institute of Materials Science Vietnamese Academy of Science and Technology University of Engineering and Technology National University Hanoi Departments of Chemistry Hanoi University of Mining and Geology

Fabrication and characterization of YVO4：Eu^3＋ nanophosphors prepared by microwave （MW） irradiation assisted soft template synthesis were reported. The effects of synthesis conditions such as different powers of MW irradiation, pH values and concentration of reac- tion materials on properties of nanophosphor were also investigated to obtain the controllable size, morphology and high luminescence efficiency. Morphology, crystalline structure, and optical properties were characterized by field emission scanning electron microscopy （FE-SEM）, X-ray diffraction （XRD） and fluorescence spectroscopy, respectively. The results showed that YVOa：Eu^3＋ nanophosphors were obtained by using diethyleneglycol （DEG） as soft template, with pH values in the range of 4 to 12, upon microwave irradiation from 300 to 900 W, at temperature of 80 ℃. The high fluorescent YVOa：Eu^3＋ nanocrystals obtained with size from 15 nm down to 8 nm are more effective to develop an ultrahigh sensitive fluorescent label for biomolecule, cell and tissue.

关键词： microwave synthesis method DEG soft template YVO4:Eu^3+ nanophosphor luminescence rare earths

A fully automated framework for helicopter rotor blades design and analysis including aerodynamics,structure, and manufacturing

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Chinese Journal of Aeronautics 2016年第6期29卷 1602-1617页

作者： Ngoc anh vu Jae Woo lee Tuan Phuong Nam le Song Thanh Thao Nguyen Division of Computational Mechatronics Institute for Computational Science Ton Duc Thang University Faculty of Electrical & Electronics Engineering Ton Duc Thang University Department of Aerospace Information Engineering Konkuk University Faculty of Mechanical Engineering Industrial University of Ho Chi Minh City Department of Aerospace Engineering Ho Chi Minh City University of Technology Vietnam National University-Ho Chi Minh City

This study describes an integrated framework in which basic aerospace engineering aspects(performance, aerodynamics, and structure) and practical aspects(configuration visualization and manufacturing) are coupled and considered in one fully automated design optimization of rotor blades. A number of codes are developed to robustly perform estimation of helicopter configuration from sizing, performance analysis, trim analysis, to rotor blades configuration representation. These codes are then integrated with a two-dimensional airfoil analysis tool to fully design rotor blades configuration including rotor planform and airfoil shape for optimal aerodynamics in both hover and forward flights. A modular structure design methodology is developed for realistic composite rotor blades with a sophisticated cross-sectional geometry. A D-spar cross-sectional structure is chosen as a baseline. The framework is able to analyze all realistic inner configurations including thicknesses of D-spar, skin, web, number and ply angles of layers of each composite part,and materials. A number of codes and commercial software(ANSYS, Gridgen, VABS, Pre VABS,etc.) are implemented to automate the structural analysis from aerodynamic data processing to sectional properties and stress analysis. An integrated model for manufacturing cost estimation ofcomposite rotor blades developed at the Aerodynamic Analysis and Design Laboratory(AADL),Aerospace Information Engineering Department, Konkuk University is integrated into the framework to provide a rapid and dynamic feedback to configuration design. The integration of three modules has constructed a framework where the size of a helicopter, aerodynamic performance analysis, structure analysis, and manufacturing cost estimation could be quickly investigated. All aspects of a rotor blade including planform, airfoil shape, and inner structure are considered in a multidisciplinary design optimization without an exception of critical configuration.

关键词： Design optimization Helicopter rotor blades Integrated framework Modular structure design methodology Perform estimation

Study of vertically ascending flight of a hawkmoth model

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Acta Mechanica Sinica 2020年第5期36卷 1031-1045,I0002页

作者： anh Tuan Nguyen vu Dan Thanh le The Hung Tran V.N.Due Van Binh Phung Faculty of Aerospace Engineering Le Quy Don Technical UniversityHanoiVietnam Institute of Theoretical and Applied Research.Duy Tan University HanoiVietnam Division of Construction Computation Institute for Computational ScienceTon Due Thang UniversityHo Chi Minh CityVietnam Faculty of Civil Engineering Ton Due Thang UniversityHo Chi Minh CityVietnam

This paper provides insight into the wing kinematics,the power requirement and the dynamic stability characteristics of a hawkmoth model in vertically ascending *** wing kinematics of the hawkmoth model is obtained based on the minimum required power *** optimization process is conducted using genetic and simplex algorithms that are coupled with an artificial neural network to rapidly predict the aerodynamic force and required *** training data for the neural network are generated from an unsteady vortex-lattice *** to hover,the results in this study show the larger flapping frequency and the smaller rotation amplitude of the hawkmoth wing kinematics in ascending ***,more power is required when the ascending speed *** conducting a dynamic modal analysis based on a cycle-average approach,the certain effect of the ascending speed on the modal structures of the hawkmoth model was observed.

关键词： Hawkmoth Ascending flapping flight-Genetic algorithm Artificial neural network Flight dynamic stability

An Efficient Differential Evolution for Truss Sizing Optimization Using AdaBoost Classifier

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Computer Modeling in Engineering & Sciences 2023年第1期134卷 429-458页

作者： Tran-Hieu Nguyen anh-Tuan vu Hanoi University of Civil Engineering Hanoi100000Vietnam

Design constraints verification is the most computationally expensive task in evolutionary structural optimization due to a large number of structural analyses thatmust be *** a surrogatemodel to approximate the behavior of structures instead of the exact structural analyses is a possible solution to tackle this ***,most existing surrogate models have been designed based on regression *** paper proposes a novel method,called CaDE,which adopts a machine learning classification technique for enhancing the performance of the Differential Evolution(DE)*** proposed method is separated into two *** the first optimization stage,the original DE is implemented as usual,but all individuals produced in this phase are stored as inputs of the training *** on design constraints verification,these individuals are labeled as“safe”or“unsafe”and their labels are saved as outputs of the training *** collecting enough data,an AdaBoost model is trained to evaluate the safety state of *** model is then used in the second stage to preliminarily assess new individuals,and unpromising ones are rejected without checking design *** method reduces unnecessary structural analyses,thereby shortens the optimization *** benchmark truss sizing optimization problems are solved using the proposed method to demonstrate its *** obtained results show that the CaDE finds good optimal designs with less structural analyses in comparison with the original DE and four other DE *** reduction rate of five examples ranges from 18 to over 50%.Moreover,the proposed method is applied to a real-size transmission tower design problem to exhibit its applicability in practice.

关键词： Structural optimization machine learning surrogate model differential evolution AdaBoost classifier

An improved CRNN for Vietnamese Identity Card Information Recognition

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Computer Systems Science & Engineering 2022年第2期40卷 539-555页

作者： Trinh Tan Dat le Tran anh Dang Nguyen Nhat Truong Pham Cung le Thien vu vu Ngoc Thanh Sang Pham Thi vuong Pham The Bao Information Science Faculty Sai Gon UniversityHCM City700000Vietnam Faculty of Electrical&Electronics Engineering University of TechnologyHCM City700000Vietnam

This paper proposes an enhancement of an automatic text recognition system for extracting information from the front side of the Vietnamese citizen identity(CID)***,we apply Mask-RCNN to segment and align the CID card from the ***,we present two approaches to detect the CID card’s text lines using traditional image processing techniques compared to the EAST ***,we introduce a new end-to-end Convolutional Recurrent Neural Network(CRNN)model based on a combination of Connectionist Temporal Classification(CTC)and attention mechanism for Vietnamese text recognition by jointly train the CTC and attention objective functions *** length of the CTC’s output label sequence is applied to the attention-based decoder prediction to make the final label *** process helps to decrease irregular alignments and speed up the label sequence estimation during training and inference,instead of only relying on a data-driven attention-based encoder-decoder to estimate the label sequence in long *** may directly learn the proposed model from a sequence of words without detailed *** evaluate the proposed system using a real collected Vietnamese CID card dataset and find that our method provides a 4.28%in WER and outperforms the common techniques.

关键词： Vietnamese text recognition OCR CRNN BLSTM attention mechanism joint CTC-Attention

Feature mapping and state estimation for highly automated vehicles

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Journal of Control and Decision 2015年第1期2卷 1-25页

作者： anh vu Jay A.Farrell Department of Electrical and Computer Engineering University of California-RiversideRiversideCAUSA

The past decade has witnessed an acceleration of autonomous vehicle research and development,with technological advances contributed by academia,government,and the industrial and consumer *** advancements hold the potential to improve society by enhancing transportation safety and throughput,where decreased congestion saves time and reduces vehicle *** of the key technologies to enable vehicle infrastructure interaction,advanced traffic management,and automated vehicles are automated roadway mapping and reliable vehicle state *** this paper,we present an overview and new methods for the problems automated roadway mapping plus a discussion of the extension of these methods to the problem of vehicle state *** from the application of these methods to feature mapping and state estimation are presented.

关键词： automated precise mapping vehicle state estimation Bayesian estimation vehicle infrastructure interaction advanced driver assistance systems autonomous driving