检索结果-南通市图书馆

Defence Technology（防务技术） 2022年第3期18卷 490-508页

作者： Pham Van Vinh le quang huy Department of Solid Mechanics Le Quy Don Technical University236 Hoang Quoc VietHanoiViet Nam Institute of Techniques for Special Engineering Le Quy Don Technical University236 Hoang Quoc VietHanoiViet Nam

This study focusses on establishing the finite element model based on a new hyperbolic sheareformation theory to investigate the static bending,free vibration,and buckling of the functionally graded sandwich plates with *** novel sandwich plate consists of one homogenous ceramic core and two different functionally graded face sheets which can be widely applied in many fields of engineering and defence *** discrete governing equations of motion are carried out via Hamilton’s principle and finite element *** computation program is coded in MATLAB software and used to study the mechanical behavior of the functionally graded sandwich plate with *** present finite element algorithm can be employed to study the plates with arbitrary shape and boundary *** obtained results are compared with available results in the literature to confirm the reliability of the present ***,a comprehensive investigation of the effects of several parameters on the bending,free vibration,and buckling response of functionally graded sandwich plates is *** numerical results shows that the distribution of porosity plays significant role on the mechanical behavior of the functionally graded sandwich plates。

关键词： Functionally graded sandwich plates Porous plates Hyperbolic shear deformation theory Bending analysis Free vibration analysis Buckling analysis

维普期刊数据库

元江（中国）—红河（越南）跨境河流生态评价与生态目标管理研究

在线全文

学校读者我要写书评

暂无评论

元江（中国）—红河（越南）跨境河流生态评价与生态目标管理研究

作者：黎光辉（le quang huy）辽宁大学

学位级别：硕士

水作为生命不可或缺的重要元素,一直以来是国家安全的重要资源。而跨境河流由于其跨国性而具有了一定的地缘经济意义和政治内涵。因此跨境河流的共同合作与合理开发已不仅仅是一种环境科学问题,甚至还成为了一种国际关系问题,涉及到了... 详细信息

水作为生命不可或缺的重要元素,一直以来是国家安全的重要资源。而跨境河流由于其跨国性而具有了一定的地缘经济意义和政治内涵。因此跨境河流的共同合作与合理开发已不仅仅是一种环境科学问题,甚至还成为了一种国际关系问题,涉及到了国家政治稳定、地区安全、经济繁荣、环境保护、可持续发展等问题。2009年亚洲协会关于亚洲水资源报告中强调,水不会成为引发战争的唯一因素,而会成为威胁放大因素,加剧社会不稳定从而导致冲突。在跨境河流合作方面,Dinar认为各国在国际河流开发中的冲突引起了国际合作的需要,水资源既可能成为激化中印两国原有矛盾的催化剂,也可能成为加强两国战略合作的天然纽带,国际河流合作不但是解决国际河流争端的最佳途径,而且还可以成为通往全面合作的桥梁。本研究整理了元江-红河水系2016年到2017年各月中国元江出境口及越南红河入境口的各项水质指标,并通过数据对比,结合空间解译,基于监测点位置,在工农业等方面进行分析,同时通过分析结果提出相应措施,从而减少跨境河流水质污染,促进国家合作。研究结果显示,由于越南工农业的发展,红河流域的COD、NH-N含量相对于国内普遍较高,同时pH值及溶解氧含量相对较低,因此通过建立相关环境保护制度,推行生态补偿机制,并通过工程保护措施等多方面对红河流域进行保护,从而提高红河流域水质是及其必要的。

关键词：跨境河流元江—红河污染水质

Vietnamese State Budget Accounting With the Relationships Between the State Budget Law and International Public Sector Accounting Standards （IPSAS）＊ Pham quang huy University of Economics, Ho Chi Minh City, Vietnam

同方学位论文库评论

在线全文

同方学位论文库

学校读者我要写书评

暂无评论

Journal of Modern Accounting and Auditing 2013年第9期9卷 1194-1203页

作者： Pham quang huy University of Economics Ho Chi Minh City Vietnam

For a long time, Vietnam has modifications in all aspects in the society. For many years, Vietnam has improved features in administrative works as well as in different areas, such as public administration, finance, and accounting In the accounting content, budget accounting is an important thing which is worth noting. However, along with the achievements, Vietnam is also facing a number of limitations to be overcome for ensuring transparency in the state budget. Since then, the main purpose of the article is to provide a general picture of budget accounting in Vietnam and what has not been done through finding the relationships with budget regulations and international public sector accounting. The results showed that Vietnam will transform and issue the new law on budget and build up a new model for controlling information published by data accounting system in the future.

关键词： state budget public sector budget law international standards international public sector accountingstandards (IPSAS)

Machine learning based models for predicting compressive strength of geopolymer concrete

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Structural and Civil Engineering 2024年第7期18卷 1028-1049页

作者： quang-huy le Duy-Hung NGUYEN Thanh SANG-TO Samir KHATIR Hoang le-MINH Amir H.GANDOMI Thanh CUONG-le Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(SVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMSE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MSE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

CLS-Miner: efficient and effective closed high-utility itemset mining

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Computer Science 2019年第2期13卷 357-381页

作者： Thu-Lan DAM Kenli LI Philippe FOURNIER-VIGER quang-huy DUONG College of Computer Science and Electronic Engineering Hunan University Changsha 410082 China Faculty of Information Technology Hanoi University of Industry Hanoi Vietnam CIC of HPC National University of Defense Technology Changsha 410073 China National Supercomputing Center in Changsha Changsha 410082 China School of Natural Sciences and Humanities Harbin Institute of Technology Shenzhen Graduate School Shenzhen 518055 China Department of Computer Science Norwegian University of Science and Technology Trondheim Norway

High-utility itemset mining (HUIM) is a popular data mining task with applications in numerous domains. However, traditional HUIM algorithms often produce a very large set of high-utility itemsets (HUIs). As a result, analyzing HUIs can be very time consuming for users. Moreover, a large set of HUIs also makes HUIM algorithms less efficient in terms of execution time and memory consumption. To address this problem, closed high-utility itemsets (CHUIs), concise and lossless representations of all HUIs, were proposed recently. Although mining CHUIs is useful and desirable, it remains a computationally expensive task. This is because current algorithms often generate a huge number of candidate itemsets and are unable to prune the search space effectively. In this paper, we address these issues by proposing a novel algorithm called CLS-Miner. The proposed algorithm utilizes the utility-list structure to directly compute the utilities of itemsets without producing candidates. It also introduces three novel strategies to reduce the search space, namely chain-estimated utility co-occurrence pruning, lower branch pruning, and pruning by coverage. Moreover, an effective method for checking whether an itemset is a subset of another itemset is introduced to further reduce the time required for discovering CHUIs. To evaluate the performance of the proposed algorithm and its novel strategies, extensive experiments have been conducted on six benchmark datasets having various characteristics. Results show that the proposed strategies are highly efficient and effective, that the proposed CLS-Miner algorithm outperforms the current state-ofthe- art CHUD and CHUI-Miner algorithms, and that CLSMiner scales linearly.

关键词： utility mining high-utility itemset mining closed itemset mining closed high-utility itemset mining

An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第3期78卷 3585-3602页

作者： Duy quang Tran huy Q.Tran Minh Van Nguyen Faculty of Civil Engineering Nha Trang UniversityNha Trang650000Vietnam Robotics and Mechatronics Research Group Faculty of Engineering and TechnologyNguyen Tat Thanh UniversityHo Chi Minh City700000Vietnam Department of Civil Engineering Ho Chi Minh City University of Technology and EducationHo Chi Minh City700000Vietnam

With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service *** volume is an influential parameter for planning and operating traffic *** study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning *** fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal ***,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition *** second aspect involves predicting traffic volume using the long short-term memory ***,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent ***,the fusion of the obtained results leads to a final traffic volume *** experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and *** achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the *** findings highlight the accuracy of traffic pattern ***,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.

关键词： Ensemble empirical mode decomposition traffic volume prediction long short-term memory optimal hyperparameters deep learning

Determination of fuel burnup distribution of a research reactor based on measurements at subcritical conditions

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Nuclear Science and Techniques 2018年第12期29卷 30-38页

作者： quang Binh Do Hoai-Nam Tran quang huy Ngo Giang T. T. Phan Ho Chi Minh City University of Technology and Education 1 Vo Van Ngan Thu Duc HCMC Vietnam Institute of Fundamental and Applied Sciences Duy Tan University Ho Chi Minh city Vietnam

This paper presents the determination of the fuel burnup distribution of the Dalat nuclear research reactor(DNRR) using a method of measurements at subcritical conditions. The method is based on the assumption of linear dependence of the reactivity on the burnup of fuel bundles and the measurements at subcritical *** measurements were taken for seven selected fuel bundles in two different measuring sequences. The measured burnup values have also been compared with the calculations for verifying the method and the measurement procedure. The results obtained with the three detectors have a good agreement with each other with a discrepancy less than 1.0%. The errors of the measured burnup values are within 6%. Comparison between the calculated and measured burnup values shows that the discrepancy of the C/E ratio is within 9% compared to unity. The results indicate that the method of measurements at subcritical conditions could be well applied to determine the relative burnup distribution of the DNRR.

关键词：研究反应堆燃料分发测量过程验证方法方法论价值计算

维普期刊数据库

Facile synthesis of FeFe2O4 magnetic nanomaterial for removing methylene blue from aqueous solution

在线全文

学校读者我要写书评

暂无评论

Progress in Natural Science:Materials International 2019年第6期29卷 648-654页

作者： Van-Phuc Dinh Ngoc Quyen Tran Nguyen-Que-Tran le quang-huy Tran Trinh Duy Nguyen Gr EEN), Nguyen Tat Thanh University Van Tan le Future Materials and Devices Laboratory Institute of Fundamental and Applied Sciences Duy Tan University Institute of Applied Materials Science VAST Graduate University of Science and Technology VAST le Quy Don–LBT Highschool Bien Hoa City Dong Nai province Center of Excellence for Green Energy and Environmental Nanomaterials (CE Industrial University of Ho Chi Minh City

A facile and simple chemical precipitation method was utilized to synthesize FeFe2O4magnetic nanomaterial for removing methylene blue（MB） from aqueous solution. Characterizations of this material were examined by using XRD, SEM, FT-IR, TGA-DTG and BET methods. Factors affecting the uptake of methylene blue, including p H, adsorption time, and MB initial concentration were also studied. The measured data were fitted by using four isotherm models including Langmuir, Freundlich, Sips and Temkin. Results showed that the Sips model offers the best fit to the data. In addition, the monolayer MB adsorption capacity obtained from the Langmuir model was 42.35 mg g-1under the optimal conditions of p H = 10 and adsorption time = 80 min. In particular, the uptake of MB onto FeFe2O4magnetic nanomaterial obtained from the kinetic and mechanism studies of the adsorption was in good agreement with prediction of the pseudo-first-order model, whereas the electrostatic interaction was found to play a primary mechanism.

关键词： FeFe2O4 magnetic nanomaterial Adsorption Methylene blue Adsorption mechanism

Examining unobserved factors associated with red light running in Vietnam:A latent class model analysis

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Transportation Safety and Environment 2022年第1期4卷 110-122页

作者： Tien Dung Chu Tomio Miwa Tuan Anh Bui quang Phuc Nguyen quang huy Vu Department of Highway and Traffic Engineering University of Transport and CommunicationsNo.3 Cau Giay StreetLang Thuong WardDong Da DistrictHanoi 10001Vietnam Institute of Materials and Systems for Sustainability Nagoya UniversityFuro-choChikusa-kuNagoya cityAichi Prefecture464-8603Japan

Red-light running(RLR)is a crucial violation that causes traffic accidents and *** factors that affect RLR is very significant to reduce the potential of this *** studies have paid considerable attention to the observable factors,but not to unobservable *** study aims to examine the effects of observable and unobservable factors on *** study uses a latent class model(LCM)to assign individuals into two classes—red-light-respectful and red-light-disrespectful road users—by surveying 751 respondents who use private transportation *** study incorporates psychological determinants into the LCM to account for unobservable *** contribution of this study is the in-depth investigation into law-respectful and law-disrespectful behaviours and intentional and unintentional *** a study has not yet been conducted in the existing *** addition,a comprehensive comparison of the LCM and a traditional ordered probit model was ***,the results suggest that the LCM is superior to the model that does not consider latent *** estimation results are in alignment with previous studies on RLR:males,younger drivers/riders,less educated road users and motorcyclists are more likely to run red *** analysis of the latent variables shows that surrounding conditions—the behaviour of other violators,the absence of traffic police,and long waiting times—increase the possibility of *** on these results,we provide suggestions to policymakers and traffic engineers:the implementation of enforcement cameras and penalties for violators are critical countermeasures to minimize the potential of RLR.

关键词： red light running(RLR) developing country latent class model(LCM) multiple indicator multiple cause(MIMIC)model latent variables(LVs) motorcycles(MCs) traffic violation

维普期刊数据库

The impact of green finance,eco-innovation,renewable energy and carbon taxes on CO_(2) emissions in BRICS countries:Evidence from CS ARDL estimation

在线全文

学校读者我要写书评

暂无评论

Geoscience Frontiers 2024年第4期15卷 449-458页

作者： Muhammad Sadiq Ka Yin Chau Nguyen Tran Thai Ha Thi Thu Hien Phan Thanh quang Ngo Pham quang huy Carbon Economy Research Center Fuzhou University of International Studies and TradeFuzhou 350202China School of Accounting and Finance Faculty of Business and LawTaylor’s UniversityMalaysia Faculty of Business City University of MacaoTaipaMacaoChina Faculty of Finance and Banking Van Lang UniversityHo Chi Minh CityVietnam Zhejiang Shuren University No.8 Shuren streetHangzhou 310015China School of Government University of Economics Ho Chi Minh City(UEH)Ho Chi Minh City 72407Viet Nam Research Group Public Governance and Developmental Issues University of Economics Ho Chi Minh City(UEH)Ho Chi Minh City 72407Viet Nam Ho Chi Minh City University of Economics and Finance(UEF) Ho Chi Minh CityVietnam University of Economics and Human Sciences in Warsaw WarsawPoland

A sharp increase in economic and human development has multiplied the carbon intensity due to which there is a significant need of effective strategies in order to curb carbon ***,the present study aims to examine the effective of green finance,eco-innovation,renewable energy output(REO),renewable energy consumption(REC),and carbon taxes on carbon dioxide(CO_(2))emissions in BRICS countries in the time of ***-sectional autoregressive distributed lag(CS ARDL)is used to test the connection among the *** estimations of CS-ARDL approach validates the effectiveness of green finance,eco-innovation,REO,REC,carbon taxes,and industrialization as the relationship of these factors with carbon emissions is negative in nature in BRICS *** on the evidences,the study recommends the formulation of environmentally friendly practices and advancement in green finances to mitigate carbon emissions.

关键词： Green finance Eco-innovation Renewable energyoutput Carbon taxes Environmental degradation CO_(2)emissions