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Effect of Temperature Dependence on Electrical Characterization of <i>p-n</i>GaN Diode Fabricated by RF Magnetron Sputtering

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Materials Sciences and Applications 2015年第9期6卷 809-817页

作者： thi tran anh tuan Dong-Hau Kuo Cheng-Che Li Guan-Zhang Li Department of Materials Science and Engineering National Taiwan University of Science and Technology Taiwan School of Basic Sciences Tra Vinh University Tra Vinh Vietnam

The p-n junction GaN diodes were all fabricated by sputtering technique with cermet targets for p- and n-type GaN and metal targets for electrodes. The interface of these p-n junction GaN diodes examined by high-resolution transition electron microscopy was clear and distinguishable. Lattice images identified the complete dissolution of Mg into the Ga site. At the room temperature, the diode had the turn-on voltage of 2.2 V, the leakage current of 2.2 × 10–7 A, the breakdown voltage of –6 V, the barrier height of 0.56 eV, ideality factor of 5.0 by I (current)-V (voltage) test and 5.2 derived from the Cheungs’ method, and series resistance of 560 Ω. These electrical properties were investigated at different testing temperatures from room temperature to 200°C. The temperature dependence in the I-V characteristics of the p-n diodes can be successfully explained on the basis of thermionic-emission mode.

关键词： p-n GaN Diode I-V Measurement Barrier Height Leakage Current Cheungs’ Method

Material and Device Developments of p/n Ⅲ-Nitrde thin Films made by Low-Temperature Sputtering

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Material and Device Developments of p/n Ⅲ-Nitrde Thin Films...

An Efficient Differential Evolution for Truss Sizing Optimization Using AdaBoost Classifier

第二届海峡两岸功能材料科技与产业峰会（2015）

作者： Dong-Hau Kuo thi tran anh tuan Cheng-Che Li Wei-Chun Yen Department of Materials Science and Engineering "National Taiwan University of Science and Technology"

GaN and In GaN layers have been deposited by metal-organic vapor deposition(MOCVD)and molecular beam *** MOCVD,In GaN films grown at 550-900 oC use trimethylindium(TMIn),trimethylgallium(TMGa),and NH as reaction precursors and N as carrier *** high capital cost and process temperature and the utilization of dangerous precursors are the major concerns of MOCVD process.p-Ga N films grown at 1000

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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

Object Detection in Remote Sensing Images Using Picture Fuzzy Clustering and MapReduce

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Computer Systems Science & Engineering 2022年第12期43卷 1241-1253页

作者： tran Manh tuan tran thi Ngan Nguyen Tu Trung Faculty of Computer Science and Engineering Thuyloi University175 Tay SonDong DaHanoi010000Vietnam

In image processing, one of the most important steps is image segmentation. The objects in remote sensing images often have to be detected in order toperform next steps in image processing. Remote sensing images usually havelarge size and various spatial resolutions. Thus, detecting objects in remote sensing images is very complicated. In this paper, we develop a model to detectobjects in remote sensing images based on the combination of picture fuzzy clustering and MapReduce method (denoted as MPFC). Firstly, picture fuzzy clustering is applied to segment the input images. Then, MapReduce is used to reducethe runtime with the guarantee of quality. To convert data for MapReduce processing, two new procedures are introduced, including Map_PFC and Reduce_*** formal representation and details of two these procedures are presented in thispaper. The experiments on satellite image and remote sensing image datasets aregiven to evaluate proposed model. Validity indices and time consuming are usedto compare proposed model to picture fuzzy clustering model. The values ofvalidity indices show that picture fuzzy clustering integrated to MapReduce getsbetter quality of segmentation than using picture fuzzy clustering only. Moreover,on two selected image datasets, the run time of MPFC model is much less thanthat of picture fuzzy clustering.

关键词： Remote sensing images picture fuzzy clustering image segmentation object detection MapReduce

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

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

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Frontiers of Structural and Civil Engineering 2022年第7期16卷 928-945页

作者： Van Quan tran Hai-Van thi MAI Thuy-anh NGUYEN Hai-Bang LY Faculty of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam

The compressive strength of self-compacting concrete(SCC)needs to be determined during the construction design *** paper shows that the compressive strength of SCC(CS of SCC)can be successfully predicted from mix design and curing age by a machine learning(ML)technique named the Extreme Gradient Boosting(XGB)algorithm,including non-hybrid and hybrid *** ML techniques,such as Linear regression(LR),K-Nearest Neighbors(KNN),Support Vector Machine(SVM),Decision Trees(DTR),Random Forest(RF),Gradient Boosting(GB),and Artificial Neural Network using two training algorithms LBFGS and SGD(denoted as ANN_LBFGS and ANN_SGD),are also compared with the XGB ***,the hybrid models of eight ML techniques and Particle Swarm Optimization(PSO)are constructed to highlight the reliability and accuracy of SCC compressive strength prediction by the XGB_PSO hybrid *** highest number of SCC samples available in the literature is collected for building the ML *** with previously published works’performance,the proposed XGB method,both hybrid and non-hybrid models,is the most reliable and robust of the examined techniques,and is more accurate than existing ML methods(R2=0.9644,RMSE=4.7801,and MAE=3.4832).Therefore,the XGB model can be used as a practical tool for engineers in predicting the CS of SCC.

关键词： compressive strength self-compacting concrete machine learning techniques particle swarm optimization extreme gradient boosting

Profiling of Urban Noise Using Artificial Intelligence

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Computer Systems Science & Engineering 2023年第5期45卷 1309-1321页

作者： Le Quang Thao Duong Duc Cuong tran thi Tuong anh tran Duc Luong Ph.D.Faculty of Physics VNU University of ScienceHanoi100000Vietnam University of Science Vietnam National UniversityHanoi100000Vietnam The International School of Penang(Uplands) PenangMalaysia Alpha School Hanoi100000Vietnam

Noise pollution tends to receive less awareness compared to other types of pollution,however,it greatly impacts the quality of life for humans such as causing sleep disruption,stress or hearing *** urban sound through the identification of noise sources in cities could help to benefit livability by reducing exposure to noise pollution through methods such as noise control,planning of the soundscape environment,or selection of safe living *** this paper,we proposed a self-attention long short-term memory(LSTM)method that can improve sound classification compared to previous *** attention mechanism will be designed solely to capture the key section of an audio data *** is practical as we only need to process important parts of the data and can ignore the rest,making it applicable when gathering information with long-term *** dataset used is the Urbansound8k dataset which specifically pertains to urban environments and data augmentation was applied to overcome imbalanced data and dataset *** audio sources in the dataset were normalized to mono *** the dataset above,an experiment was conducted to confirm the suitability of the proposed model when applied to the mel-spectrogram and MFCC(Mel-Frequency Cepstral Coefficients)datasets transformed from the original *** the classification accuracy depends on the machine learning models as well as the input data,therefore we have evaluated different class models and extraction methods to find the best *** combining data augmentation techniques and various extraction methods,our classification model has achieved state-of-the-art performance,each class accuracy is up to 98%.

关键词： Urban noise noise classification mel-spectrogram MFCC LSTM self-attention

Hydrogen roles approaching ideal electrical and optical properties for undoped and Al doped ZnO thin films

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Journal of Materiomics 2022年第1期8卷 123-135页

作者： Dung Van Hoang Nam Hoang Vu Nga thi Do anh tuan Thanh Pham Truong Huu Nguyen Jer-Lai Kuo Thang Bach Phan Vinh Cao tran Laboratory of Advanced Materials University of ScienceHoChiMinh City700000Viet Nam Vietnam National University HoChiMinh City700000Viet Nam HoChiMinh City Institute of Physics HoChiMinh City700000Viet Nam Institute of Atomic and Molecular Sciences Academia SinicaTaipei10617Taiwan Center for Innovative Materials and Architectures(INOMAR) HoChiMinh City700000Viet Nam Faculty of Materials Science&Technology University of ScienceHoChiMinh City700000Viet Nam

this paper distinguished hydrogen roles to improve electron mobility and carrier concentration in ZnO and Al doped ZnO sputtered *** combining experimental evidences and theoretical results,we find out that hydrogen located at oxygen vacancy sites(H_(O))is the main factor gives rise to increase simultaneously mobility and carrier concentration which has not been mentioned *** appropriate hydrogen content during sputtering not only results in crystalline relaxation but also supports doping Al into ZnO,increasing carrier concentration and electron mobility in the *** principles calculations confirmed hydrogen substitutional stability for oxygen vacancy,significantly reducing electron conductivity effective mass and hence increasing electron *** particular,0.8%hydrogen partial pressure ratio achieved 61 cm^(2)V^(-1)s^(-1)maximum electron mobility,optical transmittance above 82%in visible and near-infrared regions,and 2×10^(20) cm^(-3)carrier concentrations for H-Al co-doped ZnO *** values approach ideal electrical and optical properties for transparent conducting oxide *** presence of one maximum electron mobility was attributed to competition between increasing mobility due to restoring effective electron mass and hydrogen passivation of native defects,and decreased electron mobility due to electron-phonon scattering.

关键词： High electron mobility Hydrogen roles Passivation effects Effective electron mass DFT calculations Doped ZnO thin Film

Conflict management styles of nurse managers and influencing factors in children’s hospital, Vietnam

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Journal of Integrative Nursing 2023年第4期5卷 266-272页

作者： Ha Manh tuan tran thi Hong HUONG Le Viet TUNG Postgraduate Department University of Medicine and Pharmacy at Ho Chi Minh CityHo Chi Minh CityVietnam Head of Branch 2 University Medical Center Ho Chi Minh CityHo Chi Minh CityVietnam Department of Ophthalmology Children’s Hospital 1Ho Chi Minh CityVietnam Faculty of Public Health University of Medicine and Pharmacy at Ho Chi Minh CityHo Chi Minh CityVietnam Training and Scientific Research Department University Medical Center Ho Chi Minh CityHo Chi Minh CityVietnam

Objective:this study aimed to describe the conflict management styles and identify factors affecting the conflict management styles of nurse *** and Methods:A cross-sectional study was conducted by interviewing nurse managers with a questionnaire,including the Rahim Organizational Conflict Inventory-II Form B,used to assess an individual’s approach to conflict management across five styles:cooperating,competing,compromising,obliging,and ***:A total of 30 nurse managers participated in this *** mean scores of the cooperating style were the highest at 4.3±0.4,followed by a compromising style at 3.4±0.5,an avoiding style at 3.1±0.6,an accommodating style at 2.9±0.7,and a competing style at 2.8±0.8(χ^(2)=66.624,P<0.001).The mean scores for avoiding style among bachelor’s degree nurse managers(3.2±0.6)were higher than those of master’s degree nurse managers(2.7±0.6)(P=0.036).Nurse managers over 40 years old,holding a managerial position for≥10 years,and frequent conflict handling rated higher mean scores for the cooperating style than their counterparts(P<0.05).Conclusion:The cooperating style was the most commonly used conflict management style among nurse *** affecting the conflict management style were age,education level,and experience in management and conflict *** findings are useful for developing interventions that enhance the competencies of nurse managers in conflict management.

关键词： Conflict conflict management nurse nurse manager