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Investigation of the temporal variability of resting-state brain networks informs our understanding of how neural connectivity aggregates and disassociates over time, further shedding light on the aberrant neural interactions that underlie symptomatology and psychosis development. In the current work, an electroencephalogram-based sliding window analysis was utilized for the first time to measure the nonlinear complexity of dynamic resting-state brain networks of schizophrenia (SZ) patients by applying fuzzy entropy. The results of this study demonstrated the attenuated temporal variability among multiple electrodes that were distributed in the frontal and right parietal lobes for SZ patients when compared with healthy controls (HCs). Meanwhile, a concomitant strengthening of the posterior and peripheral flexible connections that may be attributed to the excessive alertness or sensitivity of SZ patients to the external environment was also revealed. These temporal fluctuation distortions combined reflect an abnormality in the coordination of functional network switching in SZ, which is further the source of worse task performance (i.e., P300 amplitude) and the negative relationship between individual complexity metrics and P300 amplitude. Notably, when using the network metrics as features, multiple linear regressions of P300 amplitudes were also exactly achieved for both the SZ and HC groups. These findings shed light on the pathophysiological mechanisms of SZ from a temporal variability perspective and provide potential biomarkers for quantifying SZ's progressive neurophysiological deterioration.

Background: Although the electrophysiological event-related potential (ERP) in face processing (e.g., N170) is widely accepted as a face-sensitivity biomarker that is deficient in children with autism spectrum disorders (ASD), the time-varying brain networks during face recognition are still awaiting further investigation.Methods: To explore the social deficits in ASD, especially the time-varying brain networks during face recognition, the current study analyzed the N170, cortical activity, and time-varying networks under three tasks (face-upright, face-inverted, and house-upright) in ASD and typically developing (TD) children.Results: The results revealed a smaller N170 amplitude in ASD compared with TD, along with decreased cortical activity mainly in occipitotemporal areas. Concerning the time-varying networks, the atypically stronger information flow and brain network connections across frontal, parietal, and temporal regions in ASD were reported, which reveals greater effort was exerted by ASD to obtain comparable performance to the TD children, although the amplitude of N170 was still smaller than that of the TD children.Conclusion: Different brain activation states and interaction patterns of brain regions during face-processing were discovered between ASD and TD. These findings shed light on the face-processing mechanisms in children with ASD and provide new insight for understanding the social dysfunction of ASD.

Language is a remarkable cognitive ability that can be expressed through visual (written language) or auditory (spoken language) modalities. When visual characters and auditory speech convey conflicting information, individuals may selectively attend to either one of them. However, the dominant modality in such a competing situation and the neural mechanism underlying it are still unclear. Here, we presented participants with Chinese sentences in which the visual characters and auditory speech convey conflicting information, while behavioral and electroencephalographic (EEG) responses were recorded. Results showed a prominent auditory dominance when audio-visual competition occurred. Specifically, higher accuracy (ACC), larger N400 amplitudes and more linkages in the posterior occipital-parietal areas were demonstrated in the auditory mismatch condition compared to that in the visual mismatch condition. Our research illustrates the superiority of the auditory speech over the visual characters, extending our understanding of the neural mechanisms of audio-visual competition in Chinese.

To promote the rehabilitation of motor function in children with cerebral palsy (CP), we developed motor imagery (MI) based training system to assist their motor rehabilitation. Eighteen CP children, ten in short- and eight in long-term rehabilitation, participated in our study. In short-term rehabilitation, every 2 days, the MI datasets were collected; whereas the duration of two adjacency MI experiments was ten days in the long-term protocol. Meanwhile, within two adjacency experiments, CP children were requested to daily rehabilitate the motor function based on our system for 30 min. In both strategies, the promoted motor information processing was observed. In terms of the relative signal power spectra, a main effect of time was revealed, as the promoted power spectra were found for the last time of MI recording, compared to that of the first one, which first validated the effectiveness of our intervention. Moreover, as for network efficiency related to the motor information processing, compared to the first MI, the increased network properties were found for the last MI, especially in long-term rehabilitation in which CP children experienced a more obvious efficiency promotion. These findings did validate that our MI-based rehabilitation system has the potential for CP children to assist their motor rehabilitation.

TV White Spaces (hereinafter referred to as the "TVWS") is the radio spectrum has not been used, is assigned to using in broadcast television. TVWS has the advantages of high transmission distance, strong penetrating ability, not easy to be absorbed by water, large amount of transmission unit data, etc., low spectrum occupancy rate in maritime, is very suitable for maritime wireless network coverage. In this paper, the maritime communication system based on TVWS uses the wireless mesh network as the network architecture. Communication access point(hereinafter referred to as the "AP") based on the software router system (hereinafter referred to as the “ROS”). TVWS is used as the distance communication spectrum between APs. The AP implements the data exchange between WIFI and TVWS, and provides Ethernet wired access and WIFI wireless access for the terminal equipment. The communication system uses the Socket transmission protocol to set up the end to the end connection, realizes the functions of GPS, character communication, picture transmission, audio communication, video communication and camera monitoring, etc., using H264 video compression format to achieve smooth video communication.

This paper collects the measurement results of 470 MHZ-960MHZ spectrum in the coastal areas, and analyzes the characteristics of TV broadcast spectrum occupancy in the measurement region. Moreover, this article proposes construct the TD-LTE maritime trunking communication system using geolocation database, television database (TVDB) and cognitive radio (CR) technology.

After analyzing the occupancy and characteristics of television white space (TVWS), this paper proposes wireless broadband networking by using super Wi-Fi technology in maritime environment operating on TVWS. A sea surface channel model is developed for predicting maritime network coverage of super Wi-Fi technology. This channel model is based on Irregular Terrain Methodology (ITM) model with revised parameters and dual-path propagation effect. The simulations demonstrated that the sea surface channel model can accurately reflect the transmission loss of radio wave in TVWS.

As an application of Wireless Sensor Network (WSN), Smart Home obtained fast development in recent years, and the researches for the Media Access Control (MAC) protocol are mainly focused on energy efficiency and consumption, which pay little attention on the access control of urgent information about the security and guard. To introduce urgent information priorities and reduce the cost of independent security information overhead, this paper proposes a node-grouping superframe-division MAC protocol based on IEEE802.15.4 MAC protocol. This protocol is designed for Smart Home applications, and focused on priority facility in an emergency. This modified protocol has good network performance, especially to the node with transmission priority. The simulation result indicates that the new protocol is better than the traditional IEEE802.15.4 MAC protocol in terms of packet delivery ratio, transmission delay, network throughput, and energy efficiency.

Wireless Sensor Network, WSN to the exchange of data with each other must have the appropriate wireless network protocols, wireless protocols difficult to adapt to the traditional low-cost wireless sensors, low power, high fault tolerance requirements. In this case, ZigBee protocol came into being. ZigBee is an emerging short-range, low complexity, low-speed, low power, low-cost wireless networking technology, mainly for short-range wireless connection. It is based on IEEE 802.15.4/ZigBee protocol standards, in thousands of tiny sensors to achieve communication between the coordination. This background paper, based on ZigBee wireless meter reading system proposed routing algorithms and networking. In-depth analysis of several typical wireless sensor network routing protocols, through a network of some of the traditional routing algorithm feasibility, problems and improvement of, for the ZigBee standard in the meter reading system, designed for meter reading system Network routing algorithm, the test achieved the mesh point to point communication between modules[1].

Refrigerator transportation is an important part of cold chain. Aimming at monitoring the temperature and humidity inside the refrigerator trucks,and managing information of the the refrigerator trucks internal. At the paper, there is a design of an intelligent monitoring system based on the Internet of thing, realized monitoring temperature and humidity inside the refrigerator trucks and the intelligent cargo identification, and tracking the location of refrigerator trucks real-time in the entire transportation process by using advanced RFID technology, the sensor technology and the wireless communication technology.

With the continuous integration of information technology and traditional teaching methods, E-learning has gradually become a hot research topic. Our paper first introduces the background, E-learning behaviouri¼ˆELBi¼‰features and the necessities of ELB assessment. Then the research focuses on information collection and preservation of student ELB information using wireless Internet web services. The agent technology and statistical analysis methods are applied on student ELB to evaluate ELB findings within the context of behaviour theory and behavioural science. Finally, we conclude the value of this ELB study through correspondence analysis.

In order to effectively restrain the impact of network delays, a novel approach is proposed that new Smith predictor combined with nonlinear control in wireless networked control systems (WNCS). Because new Smith predictor hides predictor model of the network delay into real network data transmission process, further the network delay no longer need to be measured, identified or estimated on-line. It is applicable to some occasions that network delay is random, time-variant or uncertain. Based on IEEE 802.11b/g (WLAN), the results of simulation show that this approach is effective.

In order to effectively restrain the impact of network delays, a novel approach is proposed that new Smith predictor combined with the generalized predictive control (GPC) in the networked control systems (NCS). Because new Smith predictor hides predictor model of the network delay into real network data transmission process, further the network delay no longer need to be measured, identified or estimated on-line. Simultaneously this new Smith predictor doesn't include the prediction model of the controlled plant, thus it doesn't need to know the exact mathematical model of the controlled plant. It is applicable to some occasions that network delay is random, timevariant or uncertain. Based on CAN bus, the results of simulation show that this approach is effective.

Wireless network delay is the main factor that deteriorates the performance of the wireless networked control systems (WNCS). In order to effectively restrain the impact of network delay, a new approach is proposed that novel Smith predictor combined with generalized predictive control (GPC) for the WNCS. Because novel Smith predictor hides predictor models of the network delays into real network data transmission processes, further the network delay no longer need to be measured, identified or estimated on-line. Simultaneously this new Smith predictor doesn't include the prediction model of the controlled plant, thus it doesn't need to know the exact mathematical model of the controlled plant. It is applicable to some occasions that network delay is random, time-variant or uncertain, and there are some data dropouts in closed loop. Based on IEEE 802.11b/g (WLAN), the results of simulation show that this approach is effective.

Timely farming guidance is currently achieved via web-based e-learning as agricultural information technology develops. In this paper, we address the problem of timely farming guidance by integrating the advanced mobile learning technologies with the relevant pedagogic theories. Firstly, we discuss the limitations that general mobile learning may suffer from; then, we study the specific requirements both on techniques and learning theories in case of timely farming guidance; finally, we propose a peer-to-peer mobile learning model, which shapes the essential interface between the mobile terminals and the web applications. The proposed model is validated via effective tradeoff among timely response, individual learning oriented content management and multimedia streaming based peer-to-peer interactivity.