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Institution

Xi'an Jiaotong University

EducationXi'an, China
About: Xi'an Jiaotong University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Heat transfer & Dielectric. The organization has 85440 authors who have published 99682 publications receiving 1579683 citations. The organization is also known as: '''Xi'an Jiaotong University''' & Xi'an Jiao Tong University.


Papers
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Journal ArticleDOI
TL;DR: In this article, a comprehensive review of key issues related to achieving a successful elastocaloric cooling system is presented, where the basic and advanced thermodynamic cycles are presented based on analogy from other solid-state cooling technologies.
Abstract: Elastocaloric cooling is a new alternative solid-state cooling technology undergoing early stage research and development. This study presents a comprehensive review of key issues related to achieving a successful elastocaloric cooling system. Fundamentals in elastocaloric materials are reviewed. The basic and advanced thermodynamic cycles are presented based on analogy from other solid-state cooling technologies. System integration issues are discussed to characterize the next generation elastocaloric cooling prototype. Knowledge acquired from the elastocaloric heat engines is provided as the basis for the design of cooling system configuration. Commercially available drivers enabling proper compression and tension are also presented. A few performance assessment indices are proposed and discussed as guidelines for design and evaluation of future elastocaloric cooling system. A brief summary of the up-to-date elastocaloric cooling prototypes is presented as well.

229 citations

Journal ArticleDOI
TL;DR: In this paper, the formation of AlN thin films successfully deposited on Si(111) substrates by using the direct current magnetron sputtering method was studied, and the effects of the sputtering pressure, sputtering power and distance from the target to the substrate on the preferential orientation of the AlN films were also studied.

228 citations

Journal ArticleDOI
TL;DR: The uncertainty analyses reveal that the epidemics is still uncertain and it is important to continue enhancing the quarantine and isolation strategy and improving the detection rate in mainland China.

228 citations

Journal ArticleDOI
TL;DR: In this paper, β-catenin and Yap1 were found to interact physically and are activated in most human hepatoblastoma tissues; overexpression of constitutively active forms of these proteins in livers of mice leads to rapid tumor development.

228 citations

Journal ArticleDOI
01 Mar 2011
TL;DR: This investigation presents a SVR model with chaotic genetic algorithm (CGA), namely SVRCGA, to forecast the tourism demands, and empirical results that involve tourism demands data from existed paper reveal the proposed SVRC GA model outperforms other approaches in the literature.
Abstract: Accurate tourist demand forecasting systems are essential in tourism planning, particularly in tourism-based countries. Artificial neural networks are attracting attention to forecast tourism demands due to their general non-linear mapping capabilities. Unlike most conventional neural network models, which are based on the empirical risk minimization principle, support vector regression (SVR) applies the structural risk minimization principle to minimize an upper bound of the generalization error, rather than minimizing the training error. This investigation presents a SVR model with chaotic genetic algorithm (CGA), namely SVRCGA, to forecast the tourism demands. With the increase of the complexity and the larger problem scale of tourism demands, genetic algorithms (GAs) are often faced with the problems of premature convergence, slowly reaching the global optimal solution or trapping into a local optimum. The proposed CGA based on the chaos optimization algorithm and GAs, which employs internal randomness of chaos iterations, is used to overcome premature local optimum in determining three parameters of a SVR model. Empirical results that involve tourism demands data from existed paper reveal the proposed SVRCGA model outperforms other approaches in the literature.

227 citations


Authors

Showing all 86109 results

NameH-indexPapersCitations
Feng Zhang1721278181865
Yang Yang1642704144071
Jian Yang1421818111166
Lei Zhang130231286950
Yang Liu1292506122380
Jian Zhou128300791402
Chao Zhang127311984711
Bin Wang126222674364
Xin Wang121150364930
Bo Wang119290584863
Xuan Zhang119153065398
Jian Liu117209073156
Andrey L. Rogach11757646820
Yadong Yin11543164401
Xin Li114277871389
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023306
20221,655
202111,508
202011,183
201910,012
20188,215