Gu Q.,Visual Computing and Virtual Reality Key Laboratory of Sichuan Province |
Gu Q.,Sichuan Normal University
Advanced Materials Research | Year: 2011
With emergence of online virtual reality applications, the 3D data of virtual scenes are available to heterogeneous end user devices with relatively limited computing power, resolution and transmission rate. Still, many virtual scenes created by expert developers are composed of complex 3D data models with huge number of geometry primitives and appearence elements. This complexity can cause a lot of problems when the scenes are deployed on the limited access devices. To address this issue, we propose a virtual scene adaptation framework which is able to perform the transformation of given complex 3D model into new forms with less geometric and appearance data Through the framework, complex virtual scenes are connected with real-world semantics and are preprocessed with selected optimization strategies based on the semantic features matching client devices' capabilities before deployment. © (2011) Trans Tech Publications, Switzerland.
Chen W.-L.,University of Sichuan |
Chen W.-L.,Sichuan Normal University |
Chen W.-L.,Visual Computing and Virtual Reality Key Laboratory of Sichuan Province |
He X.-H.,University of Sichuan |
And 2 more authors.
Journal of Information Science and Engineering | Year: 2012
A feature-based sequence-to-sequence alignment method was proposed by Caspi et al., which can align multiple sequences in space-time. But this method can not be very effective and precise in spatial alignment, due to a small number of moving objects in the scene, limited coverage of the trajectories and the short temporal duration of the trajectories. In order to solve this problem, we proposed a new sequence-to-sequence alignment method, combining the method proposed by Caspi et al. with a feature-based image registration method. In this paper, we made a comparison between our method and that of Caspi et al. Experimental results show that the presented method improves alignment precision both on X-axis orientation and on Y-axis orientation. The PSNR value is approximately improved by 13.5dB. At the same time, the time needed by Our-method will be slightly increased but can be ignored. When the results of the alignment are applied in space-time super-resolution reconstruction, the effect also proves the validity of our-method.
Ding J.L.,Sichuan Normal University |
Hou B.P.,Sichuan Normal University |
Hou B.P.,Visual Computing and Virtual Reality Key Laboratory of Sichuan Province
Optics Communications | Year: 2011
The interaction of a collection of N four-level tripod configuration atoms with two orthogonally polarized probe fields is investigated. Under the condition of electromagnetically induced transparency (EIT), we calculate the squeezing and entanglement spectra of the output probe fields. By analyzing the output spectrum, we find that the squeezing and entanglement of the probe fields can be well-preserved after passing through the optically thick medium. Additionally, the effects of the ground state dephasing rates of the atoms on the entanglement and squeezing of the output two-mode squeezed fields are investigated. It is shown that the dephasing rates will degrade the entanglement and squeezing, and these quantum properties can be lost when the dephasing rates increase up to a certain value. This will be useful in the quantum computation and quantum communication. © 2011 Elsevier B.V. All rights reserved.
Yang J.,Sichuan Normal University |
Yang J.,Visual Computing and Virtual Reality Key Laboratory of Sichuan Province |
Liu Y.L.,Sichuan Normal University |
Feng C.S.,Sichuan Normal University |
Zhu G.Q.,Sichuan Normal University
Genetics and Molecular Research | Year: 2016
Biologists and scientists can use the data from Alzheimer’s disease (AD) gene expression microarrays to mine AD disease-related genes. Because of disadvantages such as small sample sizes, high dimensionality, and a high level of noise, it is difficult to obtain accurate and meaningful biological information from gene expression profiles. In this paper, we present a novel approach for utilizing AD microarray data to identify the morbigenous genes. The Fisher score, a classical feature selection method, is utilized to evaluate the importance of each gene. Genes with a large between-classes variance and small within-class variance are selected as candidate morbigenous genes. The results using an AD dataset show that the proposed approach is effective for gene selection. Satisfactory accuracy can be achieved by using only a small number of selected genes. © FUNPEC-RP.
Li X.,Sichuan Normal University |
Li C.,Sichuan Normal University |
Li C.,Visual Computing and Virtual Reality Key Laboratory of Sichuan Province |
Ma L.,Sichuan Normal University
Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014 | Year: 2015
Online shopping has become an important and popular way of life. With the rapid C2C platform development, the credit problem in online shopping was being discussed. Serious loss of credit will leads to bad online business environment. However, till now lots of researchers just focus on seller reputation model to solve credit problem, thus buyer reputation model is seldom being considered. To solve the above problem, we proposed a Computational Buyer Reputation Model for C2C e-Commerce platform, i.e. CBRM. Five buyer reputation indicators, including transactions amount, seller ratings, buyer operations, chargeback ratio and real name authentication, were integrated into CBRM. By using AHP to distribute various indicator weights, we can obtain numeric value of buyer reputation. Therefore, these values can be used for sellers to choose appropriate buyers to deal with. Experiment results showed the efficiency and effectiveness of CBRM. © 2014 IEEE.