scispace - formally typeset
Search or ask a question
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
More filters
Journal ArticleDOI
TL;DR: An author topic model-based collaborative filtering (ATCF) method is proposed to facilitate comprehensive points of interest (POIs) recommendations for social users and advantages and superior performance of this approach are demonstrated by extensive experiments on a large collection of data.
Abstract: From social media has emerged continuous needs for automatic travel recommendations. Collaborative filtering (CF) is the most well-known approach. However, existing approaches generally suffer from various weaknesses. For example , sparsity can significantly degrade the performance of traditional CF. If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information for effective inference. Moreover, existing recommendation approaches often ignore rich user information like textual descriptions of photos which can reflect users’ travel preferences. The topic model (TM) method is an effective way to solve the “sparsity problem,” but is still far from satisfactory. In this paper, an author topic model-based collaborative filtering (ATCF) method is proposed to facilitate comprehensive points of interest (POIs) recommendations for social users. In our approach, user preference topics, such as cultural, cityscape, or landmark, are extracted from the geo-tag constrained textual description of photos via the author topic model instead of only from the geo-tags (GPS locations). Advantages and superior performance of our approach are demonstrated by extensive experiments on a large collection of data.

215 citations

Journal ArticleDOI
TL;DR: In this article, a tunable magnetic-spring based electromagnetic energy harvester is presented to harvest vibration energy from human motions, which is modeled by Ansoft Maxwell software and the best way of magnetic stack is chosen according to the generated voltage from simulation.

215 citations

Journal ArticleDOI
TL;DR: In this article, the authors provide an integrated framework for examining effects of relationship stability and trust on relational risk and explore the moderating effects of guanxi on the relationships between trust and relational risk in marketing channels.

215 citations

Proceedings ArticleDOI
01 Dec 2013
TL;DR: A low-rank matrix factorization problem with a Mixture of Gaussians (MoG) noise, which is a universal approximator for any continuous distribution, and hence is able to model a wider range of real noise distributions.
Abstract: Many problems in computer vision can be posed as recovering a low-dimensional subspace from high-dimensional visual data. Factorization approaches to low-rank subspace estimation minimize a loss function between the observed measurement matrix and a bilinear factorization. Most popular loss functions include the L1 and L2 losses. While L1 is optimal for Laplacian distributed noise, L2 is optimal for Gaussian noise. However, real data is often corrupted by an unknown noise distribution, which is unlikely to be purely Gaussian or Laplacian. To address this problem, this paper proposes a low-rank matrix factorization problem with a Mixture of Gaussians (MoG) noise. The MoG model is a universal approximator for any continuous distribution, and hence is able to model a wider range of real noise distributions. The parameters of the MoG model can be estimated with a maximum likelihood method, while the subspace is computed with standard approaches. We illustrate the benefits of our approach in extensive synthetic, structure from motion, face modeling and background subtraction experiments.

215 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present multicentennial-length and near annually-resolved reconstructions of monsoon precipitation, inferred from absolute-dated and instrumentally calibrated speleothem oxygen isotope records from regions (central and northeast India) that have diametric responses to active-break monsoon circulation patterns.
Abstract: [1] The “internally” generated intraseasonal variability of the Indian Summer Monsoon is characterized by intermittent periods of enhanced (“active”) and deficient (“break”) precipitation, which produce a quasi east-west precipitation dipole over the Indian subcontinent. Here we present multicentennial-length and near annually-resolved reconstructions of monsoon precipitation, inferred from absolute-dated and instrumentally calibrated speleothem oxygen isotope records from regions (central and northeast India) that have diametric responses to active-break monsoon circulation patterns. On centennial timescales (AD 1400–2008), precipitation variability from these two regions exhibit opposing behavior, oscillating between periods with a persistently “active-dominated” (AD ∼1700 to 2007) and a “break-dominated” (AD 1400 to ∼1700) regime. The switch between these regimes occurs abruptly (within decades) at a time (AD ∼ 1650–1700) when a proxy record of upwelling intensity from the Arabian Sea suggest an abrupt increase in the monsoon winds. On the basis of these observations, we hypothesize that the frequency distribution of active-break periods varies on centennial timescales, implying a leading role of internal dynamics in governing the ISM response to slowly-evolving changes in the external boundary conditions.

215 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
Network Information
Related Institutions (5)
Shanghai Jiao Tong University
184.6K papers, 3.4M citations

96% related

Zhejiang University
183.2K papers, 3.4M citations

95% related

Tsinghua University
200.5K papers, 4.5M citations

93% related

Peking University
181K papers, 4.1M citations

92% related

Fudan University
117.9K papers, 2.6M citations

92% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023306
20221,655
202111,508
202011,183
201910,012
20188,215