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Stoichiometric Ti3C2Tx Coating for Inhibiting Dendrite Growth in Anode-Free Lithium Metal Batteries

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Energy & Environmental Materials 2024年第4期7卷 153-162页

作者： Xiangrong Zeng Manmatha Mahato Woong Oh Hyunjoon Yoo van hiep Nguyen Saewoong Oh Geetha Valurouthu Soon-Ki Jeong Chi Won Ahn Yury Gogotsi Il-Kwon Oh National Creative Research Initiative for Functionally Antagonistic Nano-Engineering Department of Mechanical Engineering Korea Advanced Institute of Science and Technology (KAIST) Department of Materials Science & Engineering and A. J. Drexel Nanomaterials Institute Drexel University Department of Energy Engineering Soonchunhyang University National Nanofab Center (NNFC) Korea Advanced Institute of Science and Technology (KAIST)

Lithium metal batteries (LMBs) and anode-free LMBs (AFLMBs) present a solution to the need for batteries with a significantly superior theoretical energy ***,their adoption is hindered by low Coulombic efficiency (CE) and rapid capacity fading,primarily due to the formation of unstable solid electrolyte interphase (SEI) layer and Li dendrite growth as a result of uneven Li plating.

关键词： anode-free lithium metal batteries stoichiometric MXene solid electrolyte interphase surface terminations

Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques

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Geoscience Frontiers 2021年第3期12卷 333-342页

作者： Binh Thai Pham Abolfazl Jaafari Tran van Phong hoang Phan Hai Yen Tran Thi Tuyen Vu van Luong Huu Duy Nguyen hiep van Le Loke Kok Foong University of Transport Technology Ha Noi 100000Viet Nam Research Institute of Forests and Rangelands Agricultural ResearchEducation and Extension Organization(AREEO)TehranIran Institute of Geological Sciences Vietnam Academy of Sciences and Technology84 Chua Lang StreetDong daHa NoiViet Nam Department of Geography School of Social EducationVinh UniversityViet Nam Department of Resource and Environment Management School of Agriculture and ResourcesVinh UniversityViet Nam Faculty of Geography VNU University of Science334 Nguyen TraiHa NoiViet Nam Institute of Research and Development Duy Tan UniversityDa Nang 550000Viet Nam Department for Management of Science and Technology Development Ton Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityViet Nam

Improving the accuracy of flood prediction and mapping is crucial for reducing damage resulting from flood *** this study,we proposed and validated three ensemble models based on the Best First Decision Tree(BFT)and the Bagging(Bagging-BFT),Decorate(Bagging-BFT),and Random Subspace(RSS-BFT)ensemble learning techniques for an improved prediction of flood susceptibility in a spatially-explicit manner.A total number of 126 historical flood events from the Nghe An Province(Vietnam)were connected to a set of 10 flood influencing factors(slope,elevation,aspect,curvature,river density,distance from rivers,flow direction,geology,soil,and land use)for generating the training and validation *** models were validated via several performance metrics that demonstrated the capability of all three ensemble models in elucidating the underlying pattern of flood occurrences within the research area and predicting the probability of future flood *** on the Area Under the receiver operating characteristic Curve(AUC),the ensemble Decorate-BFT model that achieved an AUC value of 0.989 was identified as the superior model over the RSS-BFT(AUC=0.982)and Bagging-BFT(AUC=0.967)models.A comparison between the performance of the models and the models previously reported in the literature confirmed that our ensemble models provided a reliable estimate of flood susceptibilities and their resulting susceptibility maps are trustful for flood early warning systems as well as development of mitigation plans.

关键词： Machine learning Ensemble learners Hybrid modeling

Prediction of falling weight deflectometer parameters using hybrid model of genetic algorithm and adaptive neuro-fuzzy inference system

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Frontiers of Structural and Civil Engineering 2023年第5期17卷 812-826页

作者： Long hoang NGUYEN Dung Quang VU Duc Dam NGUYEN Fazal E.JALAL Mudassir IQBAL Vinh The DANG hiep van LE Indra PRAKASH Binh Thai PHAM Faculty of Civil Engineering University of Transport TechnologyHanoi 10000Vietnam Department of Civil Engineering State Key Laboratory of Ocean EngineeringShanghai Jiao Tong UniversityShanghai 200025China Department of Civil Engineering University of Engineering and TechnologyPeshawar 25120Pakistan DDG(R)Geological Survey of India Gandhinagar 382010India

A falling weight deflectometer is a testing device used in civil engineering to measure and evaluate the physical properties of pavements,such as the modulus of the subgrade reaction(Y1)and the elastic modulus of the slab(Y2),which are crucial for assessing the structural strength of *** this study,we developed a novel hybrid artificial intelligence model,i.e.,a genetic algorithm(GA)-optimized adaptive neuro-fuzzy inference system(ANFIS-GA),to predict Y1 and Y2 based on easily determined 13 parameters of rigid *** performance of the novel ANFIS-GA model was compared to that of other benchmark models,namely logistic regression(LR)and radial basis function regression(RBFR)*** models were validated using standard statistical measures,namely,the coefficient of correlation(R),mean absolute error(MAE),and root mean square error(RMSE).The results indicated that the ANFIS-GA model was the best at predicting Y1(R=0.945)and Y2(R=0.887)compared to the LR and RBFR ***,the ANFIS-GA model can be used to accurately predict Y1 and Y2 based on easily measured parameters for the appropriate and rapid assessment of the quality and strength of pavements.

关键词： falling weight deflectometer modulus of subgrade reaction elastic modulus metaheuristic algorithms

Locally weighted learning based hybrid intelligence models for groundwater potential mapping and modeling: A case study at Gia Lai province, Vietnam

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Geoscience Frontiers 2021年第5期12卷 54-68页

作者： hoang Phan Hai Yen Binh Thai Pham Tran van Phong Duong Hai Ha Romulus Costache hiep van Le Huu Duy Nguyen Mahdis Amiri Nguyen van Tao Indra Prakash Department of Geography School of Social Sciences EducationVinh University182 Le DuanVinhNghe AnVietnam University of Transport Technology Hanoi 100000Viet Nam Institute of Geological Sciences Vietnam Academy of Science and Technology(VAST)84 Chua LangDong DaHanoiViet Nam Institute for Water and Environment Hanoi 100000Viet Nam Research Institute of the University of Bucharest 90-92 Sos.Panduri5th DistrictBucharestRomania National Institute of Hydrology and Water Management București-Ploiești Road97E1st District013686 BucharestRomania Faculty of Geography VNU University of ScienceVietnam National University334 Nguyen TraiHanoi 100000Viet Nam Department of Watershed&Arid Zone Management Gorgan University of Agricultural Sciences&Natural ResourcesGorgan ***Iran DDG(R)Geological Survey of India Gandhinagar 382010India

The groundwater potential map is an important tool for a sustainable water management and land use planning,particularly for agricultural countries like *** this article,we proposed new machine learning ensemble techniques namely AdaBoost ensemble(ABLWL),Bagging ensemble(BLWL),Multi Boost ensemble(MBLWL),Rotation Forest ensemble(RFLWL)with Locally Weighted Learning(LWL)algorithm as a base classifier to build the groundwater potential map of Gia Lai province in *** this study,eleven conditioning factors(aspect,altitude,curvature,slope,Stream Transport Index(STI),Topographic Wetness Index(TWI),soil,geology,river density,rainfall,land-use)and 134 wells yield data was used to create training(70%)and testing(30%)datasets for the development and validation of the *** statistical indices were used namely Positive Predictive Value(PPV),Negative Predictive Value(NPV),Sensitivity(SST),Specificity(SPF),Accuracy(ACC),Kappa,and Receiver Operating Characteristics(ROC)curve to validate and compare performance of *** show that performance of all the models is good to very good(AUC:0.75 to 0.829)but the ABLWL model with AUC=0.89 is the *** the models applied in this study can support decision-makers to streamline the management of the groundwater and to develop economy not only of specific territories but also in other regions across the world with minor changes of the input parameters.

关键词： Locally weighted learning Hybrid models Groundwater potential GIS Vietnam

Using Susceptible-Exposed-Infectious-Recovered Model to Forecast Coronavirus Outbreak

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Computers, Materials & Continua 2021年第5期67卷 1595-1612页

作者： Debabrata Dansana Raghvendra Kumar Arupa Parida Rohit Sharma Janmejoy Das Adhikari hiep van Le Binh Thai Pham Krishna Kant Singh Biswajeet Pradhan Department of Computer Science and Engineering GIET UniversityGunupurOdishaIndia Department of Electronics&Communication Engineering Faculty of Engineering and TechnologySRM Institute of Science and TechnologyNCR CampusDelhi-NCR CampusModinagarGhaziabadIndia Institute of Research and Development Duy Tan UniversityDa Nang550000Viet Nam University of Transport Technology Hanoi100000Viet Nam Department of ECE KIET Group of InstitutionsGhaziabadIndia Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS) University of Technology SydneySydneyNSW2007Australia Department of Energy and Mineral Resources Engineering Sejong UniversitySeoul05006Korea Center of Excellence for Climate Change Research King Abdulaziz UniversityJeddah21589Saudi Arabia Earth Observation Center Institute of Climate ChangeUniversiti Kebangsaan Malaysia43600SelangorMalaysia

The Coronavirus disease 2019(COVID-19)outbreak was rst discovered in Wuhan,China,and it has since spread to more than 200 *** World Health Organization proclaimed COVID-19 a public health emergency of international concern on January 30,***,a quickly spreading infection that could jeopardize the well-being of countless individuals requires prompt action to forestall the malady in a timely ***19 is a major threat worldwide due to its ability to rapidly *** vaccines are yet available for *** objective of this paper is to examine the worldwide COVID-19 pandemic,specically studying Hubei Province,China;Taiwan;South Korea;Japan;and Italy,in terms of exposed,infected,recovered/deceased,original conrmed cases,and predict conrmed cases in specic countries by using the susceptible-exposed-infectious-recovered model to predict the future outbreak of *** applied four differential equations to calculate the number of conrmed cases in each country,plotted them on a graph,and then applied polynomial regression with the logic of multiple linear regression to predict the further spread of the *** also compared the calculated and predicted cases of conrmed population and plotted them in the graph,where we could see that the lines of calculated and predicted cases do intersect with each other to give the perfect true results for the future spread of the *** study considered the cases from 22 January 2020 to 25 April 2020.

关键词： COVID-19 SEIR forecasting global pandemic predict conrmed case

Ensemble machine learning models based on Reduced Error Pruning Tree for prediction of rainfall-induced landslides

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International Journal of Digital Earth 2021年第5期14卷 575-596页

作者： Binh Thai Pham Abolfazl Jaafari Trung Nguyen-Thoi Tran van Phong Huu Duy Nguyen Neelima Satyam Md Masroor Sufia Rehman Haroon Sajjad Mehebub Sahana hiep van Le Indra Prakash Division of Computational Mathematics and Engineering Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityViet Nam Research Institute of Forests and Rangelands Agricultural ResearchEducationand Extension Organization(AREEO)TehranIran Institute of Geological Sciences Vietnam Academy of Sciences and TechnologyHanoiViet Nam Faculty of Geography V.N.U.University of ScienceVietnam National UniversityHanoiViet Nam Discipline of Civil Engineering Indian Institute of Technology IndoreMadhya PradheshIndia Department of Geography Jamia Millia IslamiaNew DelhiIndia School of Environment Education and DevelopmentUniversity of ManchesterManchesterUK Institute of Research and Development Duy Tan UniversityDa NangViet Nam DDG(R)Geological Survey of India GujaratIndia

In this paper,we developed highly accurate ensemble machine learning models integrating Reduced Error Pruning Tree(REPT)as a base classifier with the Bagging(B),Decorate(D),and Random Subspace(RSS)ensemble learning techniques for spatial prediction of rainfallinduced landslides in the Uttarkashi district,located in the Himalayan range,*** do so,a total of 103 historical landslide events were linked to twelve conditioning factors for generating training and validation *** Mean Square Error(RMSE)and Area Under the receiver operating characteristic Curve(AUC)were used to evaluate the training and validation performances of the *** results showed that the single REPT model and its derived ensembles provided a satisfactory accuracy for the prediction of *** D-REPT model with RMSE=0.351 and AUC=0.907 was identified as the most accurate model,followed by RSS-REPT(RMSE=0.353 and AUC=0.898),B-REPT(RMSE=0.396 and AUC=0.876),and the single REPT model(RMSE=0.398 and AUC=0.836),*** prominent ensemble models proposed and verified in this study provide engineers and modelers with insights for development of more advanced predictive models for different landslide-susceptible areas around the world.

关键词： Machine learning ensemble modeling Bagging Decorate Random Subspace

Groundwater Level Prediction Using Artificial Neural Networks: A Case Study in Tra Noc Industrial Zone, Can Tho City, Vietnam

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Journal of Water Resource and Protection 2018年第9期10卷 870-883页

作者： Tran van Ty Le van Phat Huynh van hiep College of Engineering Technology Can Tho University Can Tho Vietnam Department of Natural Resources and Environment of Can Tho City Can Tho City Vietnam Tra Vinh University Tra Vinh Vietnam

The objective of this study is to predict groundwater levels (GWLs) under different impact factors using Artificial Neural Network (ANN) for a case study in Tra Noc Industrial Zone, Can Tho City, Vietnam. This can be achieved by evaluating the current state of groundwater resources (GWR) exploitation, use and dynamics;setting-up, calibrating and validating the ANN;and then predicting GWLs at different lead times. The results show that GWLs in the study area have been found to reduce rapidly from 2000 to 2015, especially in the Middle-upper Pleistocene (qp2-3) and upper Pleistocene (qp3) due to the over-withdrawals from the enterprises for production purposes. Concerning this problem, an Official Letter of the People’s Committee of Can Tho City was issued and taken into enforcement in 2012 resulting in the reduction of exploitation. The calibrated ANN structures have successfully demonstrated that the GWLs can be predicted considering different impact factors. The predicted results will help to raise awareness and to draw an attention of the local/central government for a clear GWR management policy for the Mekong delta, especially the industrial zones in the urban areas such as Can Tho city.

关键词： Groundwater Resources (GWR) Groundwater Levels (GWLs) Artificial Neural Network (ANN) Prediction Tra Noc Industrial Zone

Gravitationally lensed extended sources: the case of QSO RXJ0911

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Research in Astronomy and Astrophysics 2013年第7期13卷 803-814页

作者： Do Thi Hoai Pham Tuyet Nhung Pham Tuan Anh Frederic Boone Pierre Darriulat Pham Ngoc Diep Pham Ngoc Dong Nguyen van hiep Nguyen Thi Thao VATLY INST179Hoang Quoc VietCau GiayHanoiVietnam IRAP 14avenue Edouard BelinF31400 ToulouseFrance

After a brief reminder of the mechanism of gravitational lensing of ex- tended sources, the particular case of the host galaxy of QSO RXJ0911, a high red-shift （z - 2.8） quadruply imaged quasar, is explored. The non linearity of the problem, together with the proximity of the source to a cusp of the lens inner caustic, has impor-tant consequences on the dependence of the image appearance on the size and shape of the source. Their expected main features and their interpretation in terms of source extension and shape are investigated in a spirit of simplicity and in preparation for the analysis of high sensitivity and spatial resolution images that will soon be within reach with the completion of the Atacama Large Millimeter/submillimeter Array （ALMA）. In particular, the information on source size carded by relative image brightness is dis-cussed. Extension of the results to other types of quadruply imaged quasars is briefly considered.

关键词： gravitational lensing - galaxies: high-redshift

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旅越中国游客目的地体验质量评价研究

旅越中国游客目的地体验质量评价研究

作者： NGUYEN van hiep 陕西师范大学

学位级别：硕士

自古以来,中越两国有着友好的邻国关系。近年来,选择赴越旅游的中国游客日益增多,并成为了赴越旅游的主要游客来源。随着中国游客给越南带来巨大经济利益的同时,一些疑问也随之产生。越南的旅游市场对中国游客是否具有吸引力?中国游客... 详细信息

自古以来,中越两国有着友好的邻国关系。近年来,选择赴越旅游的中国游客日益增多,并成为了赴越旅游的主要游客来源。随着中国游客给越南带来巨大经济利益的同时,一些疑问也随之产生。越南的旅游市场对中国游客是否具有吸引力?中国游客是否愿意进行二次消费?都在一定程度上影响着消费者的游玩体验。因此,越南旅游业要想抓住中国这个大市场,提升游客的体验质量是其亟需解决的问题。故笔者以《旅越中国游客体验质量评价研究》为题目撰写了本论文。本论文采用“问卷调查”与“实地考察”的方法进行资料收集,并对回收的问卷资料进行了定量分析。然后又通过统计学的相关研究方法,分析了游客差异对旅游体验质量的影响,并通过游客的反馈,为如何提升旅越中国游客的体验质量提出了相应的对策。具体分为八章。第一章是绪论部分,主要阐述本论文的研究理由及意义、越南国内外研究现状以及研究方法及过程。第二章和第三章分别是介绍中国国内外研究进展以及对越南旅游行业现状的分析。第四章是旅越中国游客体验质量调查设计。本章首先介绍了调查问卷的构成,然后说明数据的回收、具体的研究方法以及回收数据的质量,最后提出游客的总体评价与各主因子线性回归分析。第五章和第六章笔者通过SPSS软件对数据进行假设性检验,对不同类型游客的旅游体验质量影响进行了分析。第七章中根据调查问卷中所反映出来的具体影响旅越中国游客体验质量的因素,针对性的提出了一些提升游客体验质量的建议与措施。第八章总结了本研究的核心成果与收获。本次调查实施于2017年9月15日至11月15日,在越南河内市、芽庄市及胡志明市主要旅游景区进行发放问卷调查。总体发放问卷250份,回收有效问卷205份,有效率为82%。对影响游客的体验指标进行了因子分析,通过对影响游客体验的各因子进行分析之后,利用SPSS建立了影响游客体验的线性回归方程模型,发现影响游客体验的最主要因素是服务及价格因子。说明越南的旅游城市的服务质量会直接影响到游客们的体验,并且性价比高的旅游方案更容易被游客所接受。本文的主要研究结论包括以下几个方面:(1)确定了旅越中国游客体验质量影响因素的结构以及维度名称。通过数据分析,我们确定了针对旅越中国游客体验质量的影响因素由三个维度构成,三个维度的名称分别为“旅游环境”、“旅游服务”和“旅游活动”;影响游客体验的线性回归方程模型显示,价格及其他服务因子对游客总体体验最为显著。(2)不同的人口统计学特征下,旅越中国游客对三个维度的感知影响差异。研究结果显示,旅越中国游客受年龄阶段/居住地/职业的影响,对“旅游环境”维度的认知评价存在显著差异;不同月收入/性别的受访中国游客对“旅游活动”的感知评价存在显著差异;不同月收入/居住地/职业的受访中国游客对“旅游服务”维度的感知评价有显著差异。(3)旅越中国游客主要是通过旅行社的途径来获取与越南有关的旅游信息;在交通方式的选择上,绝大多数游客选择乘坐飞机的方式去越南进行游玩;中国游客喜欢到具有海岛特色的城市进行旅游,比如芽庄、岘港、下龙湾等。本文尝试的创新在于:(1)中国游客群体行为模式研究案例地的创新性选择。出境旅游研究一直是中国旅游研究的重点,前期成果丰硕,但该研究成果多数限制于中国国境以内,即对入境中国游客的行为进行调查与分析。而对出境中国游客的行为调查分析则较少。本文创新性的对旅越的中国游客进行调查分析,调查问卷是在越南境内进行的,使旅游研究走出国门迈向国际。(2)游客行为调查主客位视角的融合创新。笔者作为客位并没有与作为主位的游客相分割开来。笔者前往越南,在体验越南的风光的基础上,对中国游客进行问卷调查,在案例地和调查人员之间选择了一种融合的角度。同时也存在一定的缺陷:由于本人只是一名越南留学生,在论文的编写过程中存在一定的不足之处:(1)由于越南方面的相关文献查询较为困难,本文搜集的文献可能不够全面,所以不能够更深层次的探讨影响游客体验的因素。(2)本人的中文水平有限,书写上也存在一定的问题,会使阅读起来没有那么生动直观,在一定程度上会影响本文的质量。可能会在表达上放一些常识性错,使读者不能很好地理解本人的内容。

关键词：越南旅游中国游客服务质量体验质量回归分析