Xuhui Chen

Frequency-specific alterations of functional hub in generalized tonic-clonic seizure

Resting-state functional magnetic resonance imaging (fMRI) has revealed aberrant brain functional networks in individuals with generalized tonic-clonic seizure (GTCS). Little is known, however, about these changes in functional hubs across different frequency bands. In this study, we applied a data-driven method named complementary ensemble empirical mode decomposition (CEEMD) to decompose the whole brain BOLD time series into five frequency-specific bands. Then, we compared alterations of frequency-specific functional hub across five different frequency bands in 21 GTCS patients to 22 normal control (NC) subjects. CTCS patients showed aberrant functional hubs predominately at some particular frequency bands and primary in the default mode network (DMN) and the somatomotor network (SMN). Furthermore, we found these hub located in the DMN at a higher frequency band was associated with disease severity. These findings provide an overview of frequency-specific hub, and may be helpful in uncovering abnormal neuronal activity in patients with GTCS at specific frequency bands.

Exposing library data with big data technology: A review

Libraries play an important role at the intersections of government, universities, research institutes, and the public since they are storing and managing digital assets. The large amount of data and those data in library need to be transformed into information or knowledge which then be used by researchers or users. Librarians might need to understand how to transform, analyze, and present data in order to facilitate knowledge creation. For example, they should know how to make big datasets more useful, visible and accessible. With new and powerful analytics of big data, such as information visualization tools, researchers/users can look at data in new ways and mine it for information they intend to have. In this work, we discussed the characteristics of datasets in library, conducted a review for the research work on library big data and then summarized the applications in this field. The issues associated with it were also discussed and explored.

A communication method between IPv4 server and IPv6 network in virtual machine environment

This paper presents an IPv4/IPv6 communication method in virtual machine environment called Virtual IVI. The purpose is to find an easy way to translate IPv4 service into IPv6 service in datacenter with less hardware change and less applications modification in IPv4 servers. The proposed new mechanism is based on IVI technology which is a stateless IPv4/IPv6 translation technique developed by China Education and Research Network. And the key idea is to migrate IVI hardware to virtual server and modify neutron network system in virtual network in data center. Eventually the mechanism can be applied in our OpenStack environment.

STM32-based vehicle data acquisition system for Internet-of-Vehicles

As the new era of the Internet of Things(IoT) is driving the evolution of conventional Vehicle Ad-hoc Networks into the Internet of Vehicles(IoV), vehicles are equipped with different kinds of sensor and become a sensing node themselves in IoV. Consequently, complexity of the automotive electronic system inside the vehicles are daily increasing. To guarantee the safe operation of vehicles, it is of great significance to acquire vehicle data in real-time to realize the on-line diagnosis, cyber-security attacking detection and et al. In this paper, we propose to realize a STM32-based data acquisition system(DAS), where the vehicle data transferred on CAN networks are acquired through the OBD2(On-Broad Diagnosis) interface. And then, the acquired vehicle data are parsed and analyzed preliminarily according to the OBD2 protocol, and then shown on a LED displayer. Through the implementation of a prototype system, the feasibility and effectiveness of the proposed design of DAS is verified.

Cloud-assisted home health monitoring system

A new generation of home healthcare monitoring system strives to have such characteristics as low-cost, low-power and low-volume etc., and furthermore, it needs to quickly adapt to the development of national medical information based Cloud computing in China. In response to this trend, a Cloud-assisted home health monitoring system was designed in this paper. Sensors can be selectively configured to monitor the respective physiological signal depending on the diagnostic demands of a patients disease. This system uses smart phones to receive physiological signals and cloud platforms (such as Xiamen Health Cloud) to storage physiological monitoring data. Combined with these data, health cloud provides risk assessment of chronic disease. Clinical application of the system shows that it has positive significance for patients with hypertension and diabetes who can enjoy health monitoring and the services of health could at home.

Robustness of community structure algorithm of complex network in the task state brain function

We used the seed-voxel method to construct a brain function network and divided the community structure by greedy algorithm based on the n-back task. And then, we explored brain function network community structure robustness based on improved perturbation model. The results showed that random disturbance has little effect on the community structure, brain function network showed strong robustness. However, the brain function network showed vulnerability in the case of deliberate disturbance. Finally, we found that community connection strength was negatively correlated with robustness, community structure in the best divided state not mean the community robustness reach best, and no synchronization between them.

Study on Complex Network Stability Based on the Structure Parameters

According to several attributes of network structure, firstly, we give a summary about some related works of network stability. And then, through the simulation experiments, we explored the influence of network density and network size on the stability of complex networks and got some interesting conclusions. Finally, we defined a factor η for the connection strength of community, and we speculate that there is a threshold ηc, it led to the network stability decreased and then increased with the increase of η, and eventually reached a peak.