Xidian University

About: Xidian University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Antenna (radio) & Computer science. The organization has 32099 authors who have published 38961 publications receiving 431820 citations. The organization is also known as: University of Electronic Science and Technology at Xi'an & Xīān Diànzǐ Kējì Dàxué.

Relationship between knowledge sharing and performance: A survey in Xi’an, China

Abstract: This paper explores the quantitative relationship between knowledge sharing and performance, with contextual factors in consideration. First, we argue that both knowledge sharing and its contextual factors should be associated with performance. Then, we analyze the multi-dimensional characteristics of knowledge sharing and propose six measures for it. Next, we model the relationship between knowledge sharing and performance, integrating various contingent factors with the model framework, some of which have significant influences on the relationship between knowledge sharing and performance. After that, we propose four alternative models and corresponding propositions for knowledge sharing-contingent variables relationship, and present a quantitative formulation of the relationship between knowledge sharing and performance. Finally, we conduct a survey of 249 organizations in Xi’an, China, and show the empirical results. Our propositions about the knowledge sharing-performance relationship and contingent factors are supported by the survey. The empirical results suggest that managers have to pay attention to some contingent factors while they commit to knowledge sharing. This study adds to the understanding of the effects of knowledge sharing on performance, and gives implications to the practice of knowledge sharing.

Storing Shared Data on the Cloud via Security-Mediator

Abstract: Nowadays, many organizations outsource data storage to the cloud such that a member (owner) of an organization can easily share data with other members (users). Due to the existence of security concerns in the cloud, both owners and users are suggested to verify the integrity of cloud data with Provable Data Possession (PDP) before further utilization on data. However, previous methods either unnecessarily reveal the identity of a data owner to the untrusted cloud or any public verifiers, or introduce significant overheads on verification metadata to preserve anonymity. In this paper, we propose a simple and efficient publicly verifiable approach to ensure cloud data integrity without sacrificing the anonymity of data owners nor requiring significant verification metadata. Specifically, we introduce a security-mediator (SEM), which is able to generate verification metadata (i.e., signatures) on outsourced data for data owners. Our approach decouples the anonymity protection mechanism from the PDP. Thus, an organization can employ its own anonymous authentication mechanism, and the cloud is oblivious to that since it only deals with typical PDP-metadata, Consequently, there is no extra storage overhead when compared with existing non-anonymous PDP solutions. The distinctive features of our scheme also include data privacy, such that the SEM does not learn anything about the data to be uploaded to the cloud at all, which is able to minimize the requirement of trust on the SEM. In addition, we can also extend our scheme to work with the multi-SEM model, which can avoid the potential single point of failure existing in the single-SEM scenario. Security analyses prove our scheme is secure, and experiment results demonstrate our scheme is efficient.

Core-Shell Gold Nanorod@Metal-Organic Framework Nanoprobes for Multimodality Diagnosis of Glioma.

Abstract: One of the most significant challenges in the diagnosis of brain cancer is efficient in vivo imaging using nontoxic nanoprobes. Core-shell gold nanorod@MIL-88(Fe) nanostars are successfully constructed as triple-modality imaging (computed tomography/magnetic-resonance imaging/photoacoustic imaging) nanoprobes that show low cytotoxicity, high contrast, high penetration depth, and high spatial resolution for accurate and noninvasive imaging and diagnosis of gliomas.