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) & Synthetic aperture radar. 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.

HCPP: Cryptography Based Secure EHR System for Patient Privacy and Emergency Healthcare

Abstract: Privacy concern is arguably the major barrier that hinders the deployment of electronic health record (EHR) systems which are considered more efficient, less error-prone, and of higher availability compared to traditional paper record systems. Patients are unwilling to accept the EHR system unless their protected health information (PHI) containing highly confidential data is guaranteed proper use and disclosure, which cannot be easily achieved without patients' control over their own PHI. However, cautions must be taken to handle emergencies in which the patient may be physically incompetent to retrieve the controlled PHI for emergency treatment. In this paper, we propose a secure EHR system, HCPP (Healthcaresystem for Patient Privacy), based on cryptographic constructions and existing wireless network infrastructures, to provide privacy protection to patients under any circumstances while enabling timelyPHI retrieval for life-saving treatment in emergency situations. Furthermore, our HCPP system restricts PHI access to authorized (not arbitrary) physicians, who can be traced and held accountable if the accessed PHI is found improperly disclosed. Last but not least, HCPP leverages wireless network access to support efficient and private storage/retrieval of PHI, which underlies a secure and feasible EHR system.

Frontostriatal circuits, resting state functional connectivity and cognitive control in internet gaming disorder.

Abstract: Converging evidence has identified cognitive control deficits in internet gaming disorder (IGD). Recently, mounting evidence had revealed that resting state functional connectivity (RSFC) and structural connectivity of frontostriatal circuits could modulate cognitive control in healthy individuals. Unfortunately, relatively little is known about the thoroughly circuit-level characterization of the frontostriatal pathways (both the dorsal and ventral striatum) during resting-state and their association with cognitive control in IGD. In the current study, the differences of striatum volume and RSFC networks were investigated between 43 young IGD individuals and 44 healthy controls. Meanwhile, cognitive control deficits were assessed by Stroop task performances. The neuroimaging findings were then correlated with the Stroop task behaviors. In IGD subjects, we demonstrated an increased volume of right caudate and nucleus accumbens (NAc) as well as reduced RSFC strength of dorsal prefrontal cortex (DLPFC)-caudate and orbitofrontal cortex (OFC)-NAc. NAc volumes were positively correlated with internet addiction test scores in IGD. The caudate volume and DLPFC-caudate RSFC was correlated with the impaired cognitive control (more incongruent errors in Stroop task) in IGD. Consistent with substance use disorder (SUD) findings, we detected striatum volume and frontostriatal circuits RSFC differences between IGD and healthy controls, which provided evidence of some degree of the similarity between IGD and SUD. More importantly, the cognitive control deficits in IGD were correlated with the reduced frontostrital RSFC strength. It is hoped that our results could shed insight on the neurobiological mechanisms of IGD and suggest potential novel therapeutic targets for treatment.

SHRINK: a structural clustering algorithm for detecting hierarchical communities in networks

Abstract: Community detection is an important task for mining the structure and function of complex networks. Generally, there are several different kinds of nodes in a network which are cluster nodes densely connected within communities, as well as some special nodes like hubs bridging multiple communities and outliers marginally connected with a community. In addition, it has been shown that there is a hierarchical structure in complex networks with communities embedded within other communities. Therefore, a good algorithm is desirable to be able to not only detect hierarchical communities, but also identify hubs and outliers. In this paper, we propose a parameter-free hierarchical network clustering algorithm SHRINK by combining the advantages of density-based clustering and modularity optimization methods. Based on the structural connectivity information, the proposed algorithm can effectively reveal the embedded hierarchical community structure with multiresolution in large-scale weighted undirected networks, and identify hubs and outliers as well. Moreover, it overcomes the sensitive threshold problem of density-based clustering algorithms and the resolution limit possessed by other modularity-based methods. To illustrate our methodology, we conduct experiments with both real-world and synthetic datasets for community detection, and compare with many other baseline methods. Experimental results demonstrate that SHRINK achieves the best performance with consistent improvements.

The fit between technological innovation and business model design for firm growth: evidence from China

Abstract: How does technological innovation fit with business model design to jointly impact firm growth? Given the increasingly salient role of business model, extant literature provides little answer to this question. This study builds a theoretical model based on technological innovation literature, business ecosystem theory, and business model literature to investigate this issue. This study finds that exploitative innovation and exploratory innovation fit with different business model designs to promote firm growth. Six hypotheses are proposed and examined by a database from 176 Chinese firms. This research finds that exploitative innovation has a negative whereas exploratory innovation has a positive effect on firm growth. More importantly, we find that efficiency-centered business model design enhances the negative effect of exploitative innovation and weakens the positive effect of exploratory innovation. We also find that novelty-centered business model design weakens the negative effect of exploitative innovation. This research contributes to both technological innovation and business model design literature.