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Controllers Design for the Multi-Shuttle and Multi-Station Transportation System

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Open Journal of Applied Sciences 2021年第8期11卷 946-965页

作者： Tien Dong Ha Minh Tien Trinh Tran Thanh Cong Vu tuong quan vo Faculty of Mechanical Engineering Ho Chi Minh City University of Technology VNU-HCM Viet Nam

Nowadays, the Multi-Shuttle and Multi-Station Transportation System (MMTS) is one of the most interesting research topics in many fields of industries. It is an effective solution to reduce unexpected accidents that occur during transportation as well as increase productivity in manufacturing. The aim of this paper is to introduce the controller design for the MMTS which is built in our BK-Recme BioMech Lab at Ho Chi Minh City University of Technology (VNU-HCM), Viet Nam. Based on the design of this system, the control algorithms will be conducted to check the operation of the whole system. To evaluate the feasibility and effectiveness of this model, we design a series of random instances for different quantities of nodes as well as the different quantities of shuttles. Our system includes 4 stations and 6 shuttles which are assembled in the serial chain system. However, the number of stations and number of shuttles can be expanded to any desired ones which are based on the requirement of the industries. In this paper, we mainly focus on the controller design of this system to make it operate in an effective way that the goods will be transported and delivered to the target station as fast as possible. In order to solve the large-scale instances and realistic transport problems, we propose three algorithms for three progresses as shuttles calling, path reading and shuttles communicating. The shuttles calling is to decide which shuttle should be called to the start-node. Path reading to determine the shortest way to go from start-node to end-node. Finally, shuttles co

关键词： Multi-Station Multi-Shuttle Transportation Shuttle Calling RFID Communicating Start-Node End-Node

A Study on Optimizing the Double-Spine Type Flow Path Design for the Overhead Transportation System Using Tabu Search Algorithm

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Intelligent Automation & Soft Computing 2024年第2期39卷 255-279页

作者： Nguyen Huu Loc Khuu Thuy Duy Truong Quoc Dien Le Tran Thanh Cong Vu Hoa Binh Tran tuong quan vo Department of Mechatronics Faculty of Mechanical EngineeringHo Chi Minh City University of Technology(HCMUT)Ho Chi Minh CityVietnam Bach Khoa Research Center for Manufacturing Engineering Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh CityVietnam VietnamNational University Ho ChiMinh City Ho ChiMinh CityVietnam

Optimizing Flow Path Design(FPD)is a popular research area in transportation system design,but its application to Overhead Transportation Systems(OTSs)has been *** study focuses on optimizing a double-spine flow path design for OTSs with 10 stations by minimizing the total travel distance for both loaded and empty *** employ transportation methods,specifically the North-West Corner and Stepping-Stone methods,to determine empty vehicle travel ***,the Tabu Search(TS)algorithm is applied to branch the 10 stations into two main layout *** results obtained from our proposed method demonstrate a reduction in the objective function value compared to the initial feasible ***,we explore howchanges in the parameters of the TS algorithm affect the optimal *** validate the feasibility of our approach by comparing it with relevant literature and conducting additional tests on layouts with 20 and 30 stations.

关键词： Overhead transportation systems tabu search double-spine layout transportationmethod empty travel flow path design

OPT-BAG Model for Predicting Student Employability

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Computers, Materials & Continua 2023年第8期76卷 1555-1568页

作者： Minh-Thanh vo Trang Nguyen tuong Le Faculty of Information Technology HUTECH UniversityHo Chi Minh CityVietnam Faculty of Information Technology Ho Chi Minh City Open UniversityHo Chi Minh CityVietnam Laboratory for Artificial Intelligence Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh CityVietnam Faculty of Information Technology School of TechnologyVan Lang UniversityHo Chi Minh CityVietnam

The use of machine learning to predict student employability is important in order to analyse a student’s capability to get a *** on the results of this type of analysis,university managers can improve the employability of their students,which can help in attracting students in the *** addition,learners can focus on the essential skills identified through this analysis during their studies,to increase their *** effectivemethod calledOPT-BAG(OPTimisation of BAGging classifiers)was therefore developed to model the problem of predicting the employability of *** model can help predict the employability of students based on their competencies and can reveal weaknesses that need to be ***,we analyse the relationships between several variables and the outcome variable using a correlation heatmap for a student employability ***,a standard scaler function is applied in the preprocessing module to normalise the variables in the student employability *** training set is then input to our model to identify the optimal parameters for the bagging classifier using a grid search cross-validation ***,the OPT-BAG model,based on a bagging classifier with optimal parameters found in the previous step,is trained on the training dataset to predict student *** empirical outcomes in terms of accuracy,precision,recall,and F1 indicate that the OPT-BAG approach outperforms other cutting-edge machine learning models in terms of predicting student *** this study,we also analyse the factors affecting the recruitment process of employers,and find that general appearance,mental alertness,and communication skills are the most *** indicates that educational institutions should focus on these factors during the learning process to improve student employability.

关键词： Ensemble classifier grid search cross-validation OPT-BAG student employability

Dealing with the Class Imbalance Problem in the Detection of Fake Job Descriptions

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Computers, Materials & Continua 2021年第7期68卷 521-535页

作者： Minh Thanh vo Anh H.vo Trang Nguyen Rohit Sharma tuong Le Faculty of Information Technology Ho Chi Minh City University of Technology(HUTECH)Ho Chi Minh CityVietnam Faculty of Information Technology Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Information Technology Ho Chi Minh City Open UniversityHo Chi Minh CityVietnam Department of Electronics&Communication Engineering SRM Institute of Science and TechnologyNCR CampusGhaziabadIndia Informetrics Research Group Ton Duc Thang UniversityHo Chi Minh CityVietnam

In recent years,the detection of fake job descriptions has become increasingly necessary because social networking has changed the way people access burgeoning information in the internet *** fraud in job descriptions can help jobseekers to avoid many of the risks of job ***,the problem of detecting fake job descriptions comes up against the problem of class imbalance when the number of genuine jobs exceeds the number of fake *** causes a reduction in the predictability and performance of traditional machine learning *** therefore present an efficient framework that uses an oversampling technique called FJD-OT(Fake Job Description Detection Using Oversampling Techniques)to improve the predictability of detecting fake job *** the proposed framework,we apply several techniques including the removal of stop words and the use of a tokenizer to preprocess the text data in the first *** then use a bag of words in combination with the term frequency-inverse document frequency(TF-IDF)approach to extract the features from the text data to create the feature dataset in the second ***,our framework applies k-fold cross-validation,a commonly used technique to test the effectiveness of machine learning models,that splits the experimental dataset[the Employment Scam Aegean(ESA)dataset in our study]into training and test sets for *** training set is passed through the third module,an oversampling module in which the SVMSMOTE method is used to balance data before training the classifiers in the last *** experimental results indicate that the proposed approach significantly improves the predictability of fake job description detection on the ESA dataset based on several popular performance metrics.

关键词： Fake job description detection class imbalance problem oversampling techniques

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

Enrichment of hydrogen in product gas from a pilot-scale rice husk updraft gasification system

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Carbon Resources Conversion 2022年第3期5卷 231-239页

作者： Phan Dinh Tuan Le Minh quan vo Trang Nhi Hoang Minh Huong Le Thi Kim Phung Daolun Feng Hochiminh City University of Natural Resources and Environment 236B Le Van Sy St.Tan Binh Dist.Ho Chi Minh City 70.000Viet Nam Applied Research Institute for Natural Resources Materialand Environment58/4 Tran Van Du St.Tan Binh Dist.Ho Chi Minh City 70.000Viet Nam Hochiminh City University of Technology 268 Ly Thuong Kiet St.Dist.10Ho Chi Minh City 70.000Viet Nam Vietnam National University-Ho Chi Minh(VNU-HCM) Linh Trung WardThu Duc CityHo Chi Minh CityViet Nam College of Marine Science and Engineering Shanghai Maritime UniversityShanghai 200135PR China

An updraft gasifier was employed to treat 3 kg of dried rice husk per batch with different types of gasifying agents such as air,steam/air,and air with dolomite catalyst addition at various operating *** H2 content,low heating value,and H2/CO ratio in syngas were compared to determine the most effective solution to enhance the H2 production from rice husk *** presence of dolomite in air gasification produced the highest H2 content in the product gas,up to 15.4 mol%,followed by 7.08 and 3.6 mol%when steam/air and air standalone were used as gasifying agents,*** higher low heating value of syngas 5.1 MJ/Nm3 was observed in catalytic air gasification compared to 3.6 MJ/Nm3 when steam was *** optimal operation condition was reported at an airflow rate of 3 m3/h and a catalyst mixing ratio of 15%.

关键词： Rice husk Enriched hydrogen syngas Dolomite Updraft gasifier

Shell Model for Elastic and Thermodynamic Properties of Gallium Nitride with Hexagonal Wurtzite Structure

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Communications in Theoretical Physics 2008年第12期50卷 1443-1448页

作者： CHENG Yan TU Ya-Jing ZENG Zhao-Yi GOU Qing-quan College of Physical Science and Technology Sichuan University Chengdu 610064 China Institute of Atomic and Molecular Physics Sichuan University Chengdu 610065 China School of Computer Science and Engineering Beijing University of Aeronautics and Astronautics Beijing 100083 China

Shell model molecular dynamic simulation with interatomic pair potential is utilized to investigate the elastic and thermodynamic properties of gallium nitride with hexagonal wurtzite structure （w-GaN） at high pressure. The calculated elastic constants Cij at zero pressure and 300 K agree well with the experimental data and other calculated values. Meanwhile, the dependences of the relative volume V/vo, elastic constants Cij, entropy S, enthalpy H, and heat capacities Cv and Up on pressure are successfully obtained. From the elastic constants obtained, we also calculate the shear modulus G, bulk modulus B, Young＇s modulus E, Poisson＇s ratio v, Debye temperature ΘD, and shear anisotropic factor Ashear on pressures.

关键词： shell model molecular dynamics elastic properties thermodynamic properties GaN

Synergetic effect of Fevo_4 andα-Fe_2O_3 in Fe-V-O catalysts for liquid phase oxidation of toluene to benzaldehyde

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Chinese Chemical Letters 2012年第2期23卷 145-148页

作者： Gui quan Zhang Xin Zhang Tao Lin Ting Gong Min Qi School of Chemical Engineering Northwest UniversityXi'an 710069China

Synergistic effect of Fevo_4 withα-Fe_2O_3 was found in Fe-V-O catalyst,which was responsible for the high apparent formation rate（A.F.R.） of benzaldehyde in liquid phase oxidation of toluene by hydrogen *** synergistic effect might create vo_πspecies as active sites;moreover,it improved the reducibility and the reactivity of Fe-V-O *** order to gain the high A.F.R. of benzaldehyde,the catalyst should have the moderate reducibihty.

关键词： Liquid oxidation Synergistic effect Toluene Benzaldehyde Fevo_4 α-Fe_2O_3

Defect-mediated reactivity of Pt/TiO2 catalysts:the different role of titanium and oxygen vacancies

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Science China Chemistry 2020年第9期63卷 1323-1330页

作者： quan Xiao Yanan Wang Zhi-Jian Zhao Chunlei Pei Sai Chen Lijun Gao Rentao Mu Qiang Fu Jinlong Gong Key Laboratory for Green Chemical Technology of Ministry of Education School of Chemical Engineering and TechnologyTianjin UniversityCollaborative Innovation Center of Chemical Science and EngineeringTianjin 300072China State Key Laboratory of Catalysis iChEMDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023China Joint School of National University of Singapore and Tianjin University International Campus of Tianjin UniversityBinhai New CityFuzhou 350207China

Defects are ubiquitous in oxide supports and can often tune the catalytic property of supported metal *** work describes the distinct role of titanium and oxygen vacancies of TiO2 supports in the catalytic performance of supported Pt catalysts for CO *** was loaded on the TiO2 supports with oxygen vacancies(vo-TiO2)and titanium vacancies(VTiTiO2).It was found that different defects of TiO2 could distinctively modify the electron property of Pt and thereby CO adsorption *** strength of CO adsorption on Pt/VTi-TiO2 is enhanced,while that of Pt/vo-TiO2 becomes ***,the presence of defects would also promote the reducibility of *** the account of the superior redox ability,both Pt/VTi-TiO2 and Pt/vo-TiO2 exhibit a higher activity than Pt supported on normal TiO2 for CO oxidation.

关键词： defects electronic metal-support interaction titanium vacancies oxygen vacancies CO oxidation