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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

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

A Data Collection on Secondary School Students’STEM Performance and Reading Practices in an Emerging Country

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Data Intelligence 2021年第2期3卷 336-356页

作者： Quan-hoang Vuong Viet-Phuong La Manh-Toan Ho Thanh-Hang Pham Thu-trang Vuong Ha-My Vuong minh-hoang Nguyen Centre for Interdisciplinary Social Research Phenikaa UniversityYen Nghia WardHa Dong DistrictHanoi 100803Vietnam A.I.for Social Data Lab Vuong&AssociatesDong Da DistrictHanoi 100000Vietnam School of Business and Management RMIT Vietnam UniversityHanoi 100000Vietnam

Science,technology,engineering,and mathematics(STEM)education has become a critical factor in promoting sustainable ***,book reading is still an essential method for cognitive development and knowledge *** developing countries where STEM teaching and learning resources are limited,book reading is an important educational tool to promote ***,public data sets about STEM education and book reading behaviors in emerging countries are *** article,therefore,aims to present a data set of 4,966 secondary school students from a school-based data collection in *** data set comprises of five major categories:1)students’personal information(including STEM performance),2)family-related information,3)book reading preferences,4)book reading frequency/habits,and 5)classroom *** introducing the designing principles,the data collection method,and the variables in the data set,we aim to provide researchers,policymakers,and educators with well-validated resources and guidelines to conduct low-cost research,pedagogical programs in emerging countries.

关键词： STEM education Socio-economic status Book reading Emerging country Students

Properties of poly（1-naphthylamine）/Fe3O4 composites and arsenic adsorption capacity in wastewater

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Frontiers of Materials Science 2016年第1期10卷 56-65页

作者： minh Thi TRAN Thi Huyen trang NGUYEN Quoc Trung VU minh Vuong NGUYEN Faculty of Physics Hanoi National University of Education 136-Xuanthuy Street Caugiay District Hanoi Vietnam Faculty of Chemistry Hanoi National University of Education 136-Xuanthuy Street Caugiay District Hanoi Vietnam Department of Physics Quynhon University 170 An Duong Vuong Quynhon Vietnam

The research results of poly（1-naphthylamine）lFe3O4 （PNA/Fe3O4） nanocomposites synthesized by a chemical method for As（Ⅲ） wastewater treatment are presented in this paper. XRD patterns and TEM images showed that the Fe3O4 grain size varied from 13 to 20 nm. The results of Raman spectral analysis showed that PNA participated in part of the PNA/Fe3O4 composite samples. The grain size of PNA/Fe3O4 composite samples is about 25-30 nm measured by SEM. The results of vibrating sample magnetometer measurements at room temperature showed that the saturation magnetic moment of PNA/Fe3O4 samples decreased from 63.13 to 43.43 emu/g, while the PNA concentration increased from 5% to 15%. The nitrogen adsorption-desorption isotherm of samples at 77 K at a relative pressure PIPo of about 1 was studied in order to investigate the surface and porous structure of nanoparticles by the BET method. Although the saturation magnetic moments of samples decreased with the polymer concentration increase, the arsenic adsorption capacity of the PNA/Fe3O4 sample with the PNA concentration of 5% is better than that of Fe3O4 in a solution with pH = 7. In the solution with pH 〉 14, the arsenic adsorption of magnetic nanoparticles is insignificant.

关键词： poly(1-naphthylamin)/Fe3O4 nanocomposite magnetization arsenic adsorption

Mechanism of Japanese encephalitis virus genotypes replacement based on human,porcine and mosquito-originated cell lines model

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Asian Pacific Journal of Tropical Medicine 2016年第4期9卷 325-328页

作者： Loan Phuong Do trang minh Bui Nga Thi Phan National Institute of Hygiene and Epidemiology

Objective:To examine the multiplication efficiency Japanese encephalitis virus(JEV)genotype Ⅰ(G Ⅰ) and genotype Ⅲ(GⅢ) of different cell lines which originated from human,porcine,mosquitoes in order to prove mechanism of JEV G Ⅰ replacement JEV GⅢ since it emerging in nature recent ***:The mixture of Gi and GⅢ JEV isolates was inoculated on human rhabdomyosarcoma(RD).pig kidney epithelial(PS) and Aedes albopictus C6/36 clone(C6/36) which originated from human,porcine and mosquitoes,*** assays were performed to calculate virus titer and real-time RT-PCR with GⅠand GⅢspecific primer sets to quantify the number of GⅠ and GUI RNA ***:The highest virus titer reached at the 3rd day of post infection when G Ⅰand GⅢ mixture was inoculated on RD and PS and that of C636 was at the 4^(th)*** were amplified and maintained by C6/36 cells after 10 passages whereas that by RD and PS only limited within 8 and 6 passages,respectively.GⅠ strain amplified and maintained more efficiently on C6/36 and PS but not *** GⅢ strain amplified and maintained more efficiently on ***:There is a correlation between the multiplication efficiency of GⅠ and GⅢ JEV strains when these two genotype strains co-infected on different cell lines with the predominance of GⅠstrains in C6/36 and PS and the limited detection of G 1 strains in RD cells proving a possible mechanism of shift JEV genotypes in nature recent decades since GⅠ emerging.

关键词： Japanese encephalitis virus Genotype I Genotype Ⅲ Multiplication Shift genotype

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

Prevalence and risk factors associated with long COVID symptoms in children and adolescents in a southern province of Vietnam

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Asian Pacific Journal of Tropical Medicine 2024年第3期17卷 119-128,I0001,I0002页

作者： Huynh Ngoc Linh Nguyen The Tan Le Thi minh Thu Nguyen Tu Loan Nguyen Thi To Uyen Le Thanh Thao trang Truong Thanh Nam Doan hoang Phu Faculty of Medicine Ca Mau Medical CollegeCa Mau 98000Vietnam Ca Mau Obstetrics and Pediatrics Hospital Ca Mau 98000Vietnam Faculty of Basic Science and Public Health Dong Thap Medical CollegeDong Thap 81000Vietnam Graduate University of Sciences and Technology Vietnam Academy of Science and TechnologyHa Noi 10000Vietnam Community Public Health Research Program School of Public HealthWalailak UniversityNakhon Si Thammarat 80160Thailand Faculty Public Health Can Tho University of Medicine and PharmacyCan Tho City 94000Vietnam Doctoral Program in Health Sciences College of Graduate StudiesWalailak UniversityNakhon Si Thammarat 80160Thailand

Objective:To investigate the prevalence and risk factors associated with long COVID symptoms among children and adolescents who have recovered from ***:This study applied a cross-sectional approach within community settings in a southern province of Vietnam.A structured questionnaire featuring socio-demographic information and common long COVID symptoms was *** correlation coefficients assessed associations among pairs of long COVID ***,multivariable logistic regression models were performed to investigate the risk factors of long COVID in recovered COVID-19 children and ***:Among 422 participants,39.3%reported long COVID symptoms,with a prevalence of 45.2%(SD=0.5)in children and 22.2%(SD=0.4)in *** symptoms reported were cough 34.6%(SD=0.5),fatigue 20.6%(SD=0.4),shortness of breath 10.9%(SD=0.3),and lack of appetite 6.6%(SD=0.3).Concerning risk factors of long COVID,a higher risk was observed among demographic groups,including girls(OR 1.25,95%CI 1.15-1.37;P<0.001,reference:boys),children compared to adolescents(OR 1.24,95%CI 1.12-1.37;P<0.001),overweight individuals(OR 1.14,95%CI 1.02-1.27;P=0.018,reference:healthy weight),and participants without any COVID-19 vaccination(OR 1.36,95%CI 1.20-1.54;P<0.001),or have received only one single dose(OR 1.35,95%CI 1.10-1.64;P=0.004)compared to those who have received two ***,patients with a COVID-19 treatment duration exceeding two weeks also had a higher risk of long COVID(OR 1.32,95%CI 1.09-1.60;P=0.003)than those who recovered less than seven ***:The insights from this study provide crucial guidance for predicting the factors associated with the occurrence of long COVID in pediatric patients,contributing to strategic interventions aimed at mitigating the long COVID risks among children and adolescents in Vietnam.

关键词： Long COVID Prevalence Risk factors Children Adolescent Vietnam

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

Stochastic Systems Arising from Markov Modulated Empirical Measures

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Journal of Systems Science & Complexity 2017年第5期30卷 999-1011页

作者： YIN Gang BUI trang Department of Mathematics Wayne State UniversityDetroitMI 48202USA

This work is devoted to stochastic systems arising from empirical measures of random sequences(termed primary sequences) that are modulated by another Markov chain. The Markov chain is used to model random discrete events that are not represented in the primary sequences. One novel feature is that in lieu of the usual scaling in empirical measure sequences, the authors consider scaling in both space and time, which leads to new limit results. Under broad conditions, it is shown that a scaled sequence of the empirical measure converges weakly to a number of Brownian bridges modulated by a continuous-time Markov chain. Ramifications and special cases are also considered.

关键词： Brownian bridge limit empirical measure multi-scale modeling regime-switching model,weak convergence