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Information Processing in Agriculture 2019年第1期6卷 116-131页

作者： Vi Nguyen thanh le Beniamin Apopei Kamal Alameh Edith Cowan University–Electron Science Research Institute Australia

Accurate crop and weed discrimination plays a critical role in addressing the challenges of weed management in *** use of herbicides is currently the most common approach to weed ***,herbicide resistant plants have long been recognised as a major concern due to the excessive use of *** weed detection techniques can reduce the cost of weed management and improve crop quality and yield.A computationally efficient and robust plant classification algorithm is developed and applied to the classification of three crops:Brassica napus(canola),Zea mays(maize/corn),and *** developed algorithm is based on the combination of Local Binary Pattern(LBP)operators,for the extraction of crop leaf textural features and Support vector machine(SVM)method,for multiclass plant *** paper presents the first investigation of the accuracy of the combined LBP algorithms,trained using a large dataset of canola,radish and barley leaf images captured by a testing facility under simulated field *** dataset has four subclasses,background,canola,corn,and radish,with 24,000 images used for training and 6000 images,for *** dataset is referred herein as "bccr-segset"and published *** each subclass,plant images are collected at four crop growth ***,the algorithm demonstrates plant classification accuracy as high as 91.85%,for the four classes.

关键词： Plant discrimination Classification LBP PCA and SVM

越南北江农林大学中文专业 ——教学现状调查及发展策略研究

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越南北江农林大学中文专业 ——教学现状调查及发展策略研究

作者：阮氏清水（NGUYEN THI thanh THUY）广西大学

学位级别：硕士

Electrochemical Immunosensor for Detection of Atrazine Based on Polyaniline/Graphene

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Journal of Materials Science & Technology 2016年第6期32卷 539-544页

作者： Nguyen van Chu Nguyen Hai Binh Cao Thi thanh Nguyen van Tu Nguyen le Huy Nguyen Tuan Dzung Phan Ngoc Minh Vu Thi Thu Tran Dai Lam Institute of Materials Science Vietnam Academy of Science and Technology18 Hoang Quoc VietCau Giay.HanoiViet Nam School of Chemical Engineering.Hanoi University of Science and Technology 1 Dai Co VietHanoiViet Ham Institute for Tropical Technology.Vietnam Academy of Science and Technology 18 Hoang Quoc VietHanoiViet Nam Center for High Technology Development Vietnam Academy of Science and Technology18 Hoang Quoc VietHanoiViet Nam University of Science and Technology of Hanoi.18 Hoang Quoc Viet HanoiViet Ham Graduate University of Science and Technology.Vietnam Academy of Science and Technology 18 Hoang Quoc Viet.HanoiViet Nam

In this study, a novel layer-by-layer polyaniline/graphene （PANi/Gr） structure for electrochemical detec- tion of atrazine was developed. Gr film was synthesized by thermal chemical vapor deposition （CVD） method and transferred onto the PANi-predeposited microelectrode. The properties of PANi/Gr film were thoroughly investigated by high-resolution transmission electron microscopy and Raman techniques. The most attractive feature of this system is a suitable microenvironment, which could provide an amplifi- cation of the conductive signal, thus may contribute to enhancing electron transfer and subsequently improve the sensitivity in electrochemical measurements. With low detection limit （- 43 × 10 -12 g/L）, ac-ceptable stability and good reproducibility, the proposed electrochemical immunosensor could be advantageously extended for multiplexed detection of other agents of environmental pollution.

关键词： Electrochemical immunosensor Polyaniline Graphene Atrazine

Designing Software to Analyze Sewing Process of Industrial Knitted Products

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Computer Systems Science & Engineering 2023年第2期44卷 1837-1852页

作者： Phan thanh Thao Nguyen thanh Hung Pham Thi le My Nguyen Xuan Hiep Duy-Nam Phan Hanoi University of Science and Technology Hanoi10000Vietnam

In the textile industry,garment manufacturing contains four major pro-cesses containing cutting,sewing,ﬁnishing,and *** is the most crucial and intricate section,dealing with a large number of varied operations.A successful sewing process needs to be optimized regarding different factors,including time,sewing equipment,and skilled *** lineﬂow is combined by a set of operations with a particular *** utmost impor-tance of all garment industry is to arrange the workstations to minimize the num-ber of employees in order to produce at the best productive rate with the most reasonable cost,shortest time,and satisfying *** most garment factories,the production lines are balanced using the empirical judgment of the line *** the whole process the data of production time at each step,labor pro-ductivity,proper choices of equipment were always needed to calculate line efﬁ*** far as the issue is concerned,there has not been an academically sewing process analyzing software providing adequate data of sewing motions and sewing time as the credible input for the line balancing *** this goal,this paper presents the results of research on optimizing academically self-built software to analyze the sewing process of knitted products applied to industrial production using Java programming language on Google *** results achieved by the software are not only to analyze sewing products and the technological sewing process,calculate the sewing time on the machine but also analyze the sewing activities of workers into manipulations,movements,and motions to calculate the preparation time for two typical knitted products,namely,Polo-Shirt and T-Shirt with the case studies at General Textile Garment Joint Stock Company Hanoi and Star Fashion Company Limited.

关键词： Sewing motion sewing time GSD MTM polo-shirt T-shirt sewing process sewing operation analyzing software

Blockchain for Education:Verification and Management of Lifelong learning Data

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Computer Systems Science & Engineering 2022年第11期43卷 591-604页

作者： Ba-Lam Do van-thanh Nguyen Hoang-Nam Dinh thanh-Chung Dao BinhMinh Nguyen School of Information and Communication Technology Hanoi University of Science and TechnologyHanoiVietnam

In recent years,blockchain technology has been applied in the educational domain because of its salient advantages,i.e.,transparency,decentralization,and *** systems typically use public blockchain networks such as Ethereum and Bitcoin to store learning ***,the cost of writing data on these networks is significant,making educational institutions limit data sent to the target network,typically containing only hash codes of the issued *** this paper,we present a system based on a private blockchain network for lifelong learning data authentication and management named B4E(Blockchain For Education).B4E stores not only certificates but also learners’training data such as transcripts and educational programs in order to create a complete record of the lifelong education of each user and verify certificates that they have *** a result,B4E can address two types of fake certificates,i.e.,certificates printed by unlawful organizations and certificates issued by educational institutions for learners who have not met the training *** addition,B4E is designed to allow all participants to easily deploy software packages to manage,share,and check stored information without depending on a single point of *** such,the system enhances the transparency and reliability of the stored *** experiments show that B4E meets expectations for deployment in reality.

关键词： Training data certificate verification and management private blockchain

Numerical investigation of the influence of casting techniques on fiber orientation distribution in ECC

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Frontiers of Structural and Civil Engineering 2022年第11期16卷 1424-1435页

作者： Chung Nguyen van Hai TRAN thanh Thuc Nhu NGUYEN Jianchun LI Faculty of Civil Engineering Ho Chi Minh City University of Technology and EducationHo Chi Minh 721400Vietnam School of Civil and Environmental Engineering University of Technology SydneySydneyNSW 2007Australia School of Civil Engineering Hue Industrial CollegeHue 49120Vietnam

Engineered cementitious composites(ECC),also known as bendable concrete,were developed based on engineering the interactions between fibers and cementitious *** orientation of fibers,in this regard,is one of the major factors influencing the ductile behavior of this *** this study,fiber orientation distributions in ECC beams influenced by different casting techniques are evaluated via numerical modeling of the casting *** casting directions and two casting positions of the funnel outlet with beam specimens are modeled using a particle-based smoothed particle hydrodynamics(SPH)*** this SPH approach,fresh mortar and fiber are discretized by separated mortar and fiber particles,which smoothly interact in the computational domain of *** movement of fiber particles is monitored during the casting ***,the fiber orientations at different sections of specimens are determined after the fresh ECC stops flowing in the *** simulation results show a significant impact of the casting direction on fiber orientation distributions along the longitudinal wall of beams,which eventually influence the flexural strength of *** addition,casting positions show negligible influences on the orientation distribution of fibers in the short ECC beam,except under the pouring position.

关键词： ECC fiber orientation distribution casting direction casting position

A Simple Approach to the Fabrication of Graphene-Carbon Nanotube Hybrid Films on Copper Substrate by Chemical Vapor Deposition

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Journal of Materials Science & Technology 2015年第5期31卷 479-483页

作者： Nguyen van Chuc Cao Thi thanh Nguyen van Tu Vuong T.Q Phuong Pham Viet Thang Ngo Thi thanh Tam Institute of Materials Science Vietnam Academy of Science and Technology Hanoi University of Science Vietnam National University

In this study,graphene-carbon nanotube（CNT） hybrid films were directly synthesized on polycrystalline copper（Cu） substrates by thermal chemical vapor deposition（CVD） *** films were synthesized on Cu substrate at 1000 ℃ in mixture of gases:argon（Ar）,hydrogen（H2）,and methane（CH4）.Then,carbon nanotubes（CNTs） were grown uniformly on the surface of graphene/Cu films at 750 ℃ in mixture of Ar,*** acetylene（C2H2） *** salt FeCl3solution deposited onto the surface of graphene/Cu substrate by spin coating method was used as precursor for the growth of the *** density and quality of the CNTs on the surface of graphene/Cu films can be controlled by varying the concentration of FeCl3salt catalyst.

关键词： Graphene Carbon nanotube(CNT) Hybrid films Copper

Viral co-infections among children with confirmed measles at hospitals in Hanoi,Vietnam,2014

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Asian Pacific Journal of Tropical Medicine 2017年第2期10卷 164-167页

作者： Hang le Khanh Nguyen Loan Phuong Do van thanh Thi Trieu Son Vu Nguyen Phuong Vu Mai Hoang Hien Thi Pham thanh Thi le Huong Thi Thu Tran Cuong Duc Vuong Mai Thi Quynh le National Institute of Hygiene and Epidemiology No 1-Yesrsin streetHanoiVietnam

Objective:To characterize viral co-infections among representative hospitalized measles cases during the 2014 Hanoi ***:Throat swabs were collected from 54 pediatric patients with confirmed measles,and molecular diagnostics performed for 10 additional viral respiratory pathogens(Influenza A/H1N1pdm09;A/H3N2 and influenza B;Parainfluenza 1,2,3;Respiratory Synctial Virus,RSV;human Metapneumovirus,hM PV;Adenovirus and Picornavirus).Results:Twenty-one cases(38.9%) showed evidence of infection with other respiratory viruses:15 samples contained measles plus one additional virus,and 6 samples contained measles plus 2 additional *** was detected as a predominant cause of co-infections(13 cases;24.1%),followed by RSV(6 cases;11.1%),A/H1N1pdm09(3 cases;5.6%),PIV3(3 cases;3.7%),Rhinovirus(3 cases;3.7%) and hM PV(1 case;1.96%).Conclusions:Viral co-infections identified from pediatric measles cases may have contributed to increased disease severity and high rate of fatal *** treatment of measles cases may require control of multiple viral respiratory pathogens.

关键词： Measles virus Respiratory viruses Co-infection

Free radical scavenging and anti-proliferative activities of avocado(Persea americana Mill.) seed extract

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Asian Pacific Journal of Tropical Biomedicine 2019年第3期9卷 91-97页

作者： thanh Sang Vo Phuong Uyen le Dai Hung Ngo NTT Institute of Hi-Technology Nguyen Tat Thanh University Faculty of Natural Sciences Thu Dau Mot University

Objective: To investigate the chemical components and biological activities of avocado seed extract and fractions in order to determine the nutritional and pharmaceutical values of avocado seed. Methods: Various organic solvents were applied for extraction and fractionation of avocado seed. 1,1-diphenyl-2-picryl-hydrazyl, 2,2-azinobis-3-ethyl benzothiazoline-6-sulfonic acid, and DNA oxidation assays were applied for investigation of free radical scavenging activity. Nitric oxide production was measured by Griess reaction assay. Moreover, MTT assay was used to measure cancer cell growth inhibition. Results: The result indicated that the avocado seed contains(7.14 ± 0.40) g lipid/100 g,(1.67 ± 0.03) g protein/100 g,(54.0 ± 1.2) g carbohydrate/100 g, and(62.0 ± 2.3) mg gallic acid equivalent/g dried weight extract. Moreover, dichloromethane and ethyl acetate were revealed to be the highest free radical scavenging fractions with IC_(50) values of(48.0 ± 3.4) μg/mL(1,1-diphenyl-2-picryl-hydrazyl assay) and(22.0 ± 1.8) μg/mL(2,2-azinobis-3-ethyl benzothiazoline-6-sulfonic acid assay), respectively. Additionally, the avocado seed extract and fractions were able to protect against H_2O_2-induced DNA damage at the concentration of 100 μg/mL. On the other hand, the ethanol extract was effective in reducing nitric oxide production from lipopolysaccharide-stimulated RAW 264.7 macrophage cells without cytotoxic effect. Notably, the avocado seed significantly inhibited the proliferation of human lung A549 and human gastric BGC823 cancer cells at the concentration of 200 μg/mL, especially hexane(81 ± 3)% and dichloromethane(75 ± 2)% fractions. Conclusions: The results of the present study supported the avocado seed as potential by-product source for further development of health beneficial products.

关键词： Avocado seed By-product DPPH Nitric oxide Cancer cells

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