Xi'an Jiaotong University

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.

Optimal linear estimation fusion .I. Unified fusion rules

Abstract: This paper deals with data (or information) fusion for the purpose of estimation. Three estimation fusion architectures are considered: centralized, distributed, and hybrid. A unified linear model and a general framework for these three architectures are established. Optimal fusion rules based on the best linear unbiased estimation (BLUE), the weighted least squares (WLS), and their generalized versions are presented for cases with complete, incomplete, or no prior information. These rules are more general and flexible, and have wider applicability than previous results. For example, they are in a unified form that is optimal for all of the three fusion architectures with arbitrary correlation of local estimates or observation errors across sensors or across time. They are also in explicit forms convenient for implementation. The optimal fusion rules presented are not limited to linear data models. Illustrative numerical results are provided to verify the fusion rules and demonstrate how these fusion rules can be used in cases with complete, incomplete, or no prior information.

Review of catalytic supercritical water gasification for hydrogen production from biomass

Abstract: Hydrogen is defined as an attractive energy carrier due to its potentially higher energy efficiency and low generation of pollutants, which can replace conventional fossil fuels in the future. The governments have invested huge funds and made great efforts on the research of hydrogen production. Among the various options, supercritical water gasification (SCWG) is a most promising method of hydrogen production from biomass. Supercritical water (SCW) has received a great deal of attention as a most suitable reaction medium for biomass gasification because it is safe, non-toxic, readily available, inexpensive and environmentally benign. However, high temperature and pressure are required to meet the minimum reaction condition. Therefore, the high operating cost has become the biggest obstacle to the development of this technology. To overcome this bottleneck, many researchers have carried out intensive research work on the catalytic supercritical water gasification (CSCWG). Based on the previous studies stated in the literature, the authors try to give an overview (but not an exhaustive review) on the recent investigations of CSCWG. Besides, the physicochemical properties of SCW and its contributions in subcritical and supercritical water reaction are also summarized.

Motion texture: a two-level statistical model for character motion synthesis

Abstract: In this paper, we describe a novel technique, called motion texture, for synthesizing complex human-figure motion (e.g., dancing) that is statistically similar to the original motion captured data. We define motion texture as a set of motion textons and their distribution, which characterize the stochastic and dynamic nature of the captured motion. Specifically, a motion texton is modeled by a linear dynamic system (LDS) while the texton distribution is represented by a transition matrix indicating how likely each texton is switched to another. We have designed a maximum likelihood algorithm to learn the motion textons and their relationship from the captured dance motion. The learnt motion texture can then be used to generate new animations automatically and/or edit animation sequences interactively. Most interestingly, motion texture can be manipulated at different levels, either by changing the fine details of a specific motion at the texton level or by designing a new choreography at the distribution level. Our approach is demonstrated by many synthesized sequences of visually compelling dance motion.