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Shenyang, China

Neusoft Corporation is a Chinese multinational provider of software engineering services, Information Technology services, product engineering services, IT education and medical equipment headquartered in Shenyang, China. It was founded in 1991 and, as of 2012, is the largest China-based software company measured by revenues.Neusoft has established overseas subsidiaries in Japan, USA, Germany, Romania, Finland, Switzerland, Dubai and Peru. Service center offices spread across the Middle East, Europe, and South Asia. Wikipedia.

Wang X.,Shenyang Aerospace University | Wangx W.,Shenyang Aerospace University | bao M.,Neusoft Group
Applied Mechanics and Materials | Year: 2013

Modern enterprises have established many information management systems based on management of enterprise information. But any of the systems can only manage information of a department, and even on different task directions in the same department there are many information management systems. Between these systems, it is hard to realize mutual contact or data sharing, not even coordinated work. How to establish an information integration mechanism to make these systems share data for coordinated work and values as 1+1>2 becomes the problem to be solved by modern enterprises in an earnest status. As an effective method to reach mutual communication between data of the isomeric systems, the data integration system can shield off the isomerism of systems it covers and unify the data modes of these systems. Then, mode shifting is made between different systems to make these systems have the same mode on the data integration layer, to provide convenience for mutual communication between these systems, to reduce the coupling of the whole system and to provide operation function of the enterprise. © (2013) Trans Tech Publications, Switzerland.

Xiong J.,Anyang University, China | Liu Y.,Anyang University, China | Liu W.,Neusoft Group
Proceedings - 11th Web Information System and Application Conference, WISA 2014 | Year: 2014

In the era of big data, massive educational resources are stored on the internet and mobile networks. However, most of these resources are heterogeneous and decentralized, they have different format. The resources are designed for humans to read and not understandable to the machine. Their low level sharing and reuse make them difficult to acquire. How to access the resources the users need quickly and efficiently and take advantage of them is a serious problem. In order to solve the problem, an ontology-based integration educational resources framework and sharing strategies are proposed. Using the advantages of ontological semantics these educational resources can be annotated semantically, so that the computer can understand and deal with the marked information. The ontology-based integration and sharing strategies can improve the recall and precision of the educational resources retrieval. © 2014 IEEE.

Yang J.,Northeastern University China | Feng C.,Northeastern University China | Zhao D.,Northeastern University China | Zhao D.,Neusoft Group
Magnetic Resonance Imaging | Year: 2013

MR raw data collected using non-Cartesian method can be transformed on Cartesian grids by traditional gridding algorithm (GA) and reconstructed by Fourier transform. However, its runtime complexity is O(K×N2), where resolution of raw data is N×N and size of convolution window (CW) is K. And it involves a large number of matrix calculation including modulus, addition, multiplication and convolution. Therefore, a Compute Unified Device Architecture (CUDA)-based algorithm is proposed to improve the reconstruction efficiency of PROPELLER (a globally recognized non-Cartesian sampling method). Experiment shows a write-write conflict among multiple CUDA threads. This induces an inconsistent result when synchronously convoluting multiple k-space data onto the same grid. To overcome this problem, a reverse gridding algorithm (RGA) was developed. Different from the method of generating a grid window for each trajectory as in traditional GA, RGA calculates a trajectory window for each grid. This is what "reverse" means. For each k-space point in the CW, contribution is cumulated to this grid. Although this algorithm can be easily extended to reconstruct other non-Cartesian sampled raw data, we only implement it based on PROPELLER. Experiment illustrates that this CUDA-based RGA has successfully solved the write-write conflict and its reconstruction speed is 7.5 times higher than that of traditional GA. © 2013 Elsevier Inc.

Kou Y.,Northeastern University China | Li D.,Neusoft Group | Shen D.,Northeastern University China | Yu G.,Northeastern University China | Nie T.,Northeastern University China
Jisuanji Yanjiu yu Fazhan/Computer Research and Development | Year: 2010

With the increase of Web databases, accessing Deep Web is becoming the main method to acquire information. Because of the large-scale unstructured content, heterogeneous result and dynamic data in Deep Web, there are some new challenges for entity extraction. Thus it is important to solve the problem of extracting the entities from Deep Web result pages effectively. By analyzing the characteristics of result pages, a DOM-tree based entity extraction mechanism for Deep Web (called D-EEM) is presented to solve the problem of entity extraction for Deep Web. D-EEM is modeled as three levels: expression level, extraction level, collection level. Therein the components of region location and semantic annotation are the core parts to be researched in this paper. A DOM-tree based automatic entity extraction strategy is performed in D-EEM to determine the data regions and entity regions respectively, which can improve the accuracy of extraction by considering both the textual content and the hierarchical structure in DOM-trees. Also based on the Web context and co-occurrence, a semantic annotation method is proposed to benefit the process of data integration effectively. An experimental study is proposed to determine the feasibility and effectiveness of the key techniques of D-EEM. Compared with various entity extraction strategies, D-EEM is superior in the accuracy and efficiency of extraction.

Su X.,Shenyang Ligong University | Li Y.,Neusoft Group
Proceedings of 2011 International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2011 | Year: 2011

A uniform model for Direct Volume Render is described in this paper. A rendering pipeline is described by introducing intermediate rendering buffer. To construct the intermediate rendering buffer, the Contribution Number and Visibility Number of 3D volume dataset. By join with advantage of both image order and object order DVR model, the uniform model is more efficient and suitable to parallel computing. © 2011 IEEE.

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