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To evaluate the application of Traditional Chinese Medicine (TCM) Four-diagnostic Auxiliary Apparatus in disease diagnosis.The liver cancer patients and healthy controls were recruited from Shanghai Integrated Chinese and Western Medicine Hospital and Beijing University of Traditional Chinese Medicine, respectively. Then, the included subjects were diagnosed by the Four-diagnostic auxiliary apparatus.Thirty liver cancer patients and 30 paired healthy controls were enrolled in this study. Based on the apparatus, the pulse wave velocity was significantly higher in patients compared with controls (P0.05). The number of patients with purple tongue and ecchymosis were more than controls (P0.05). The number of patients (10%) with yellow tongue coating were higher than the controls (0%). Patients were inclined to be with water type and fire type constitution.TCM Four-diagnostic auxiliary apparatus can be applied in clinical diagnosis of body constitution and health status of subjects. It promotes the accuracy and speed for disease diagnosis and TCM standardization.

In this paper, a kind of intelligent LED lighting system was designed, and intelligent processing and control technology were obtained based on STC89C52 MCU minimum system, which combining with the LED lighting technology, infrared sensing technology, photoelectric detection technology. The system can intelligently test the design of LED lighting system, realize the intensity of light control, infrared detection and the measurement of light intensity, reflecting the intelligence and humanity of LED lights, and further to achieve energy-saving green lighting.

Ocean current energy harvester is a promising infrastructure to achieve self-powered marine wireless sensing system. This study proposes and investigates an underwater flag-like Triboelectric Nanogenerator (UF-TENG) based on the flow-induced vibration. The UF-TENG consists of two conductive ink-coated polyethylene terephthalate membranes and one strip of poly tetra fluoroethylene membrane with their edges sealed up by a waterproof PTFE tape. In this way, the triboelectric layers are prevented from contacting water. It is verified that the vortex street induced by a cylinder enhances the vibration of the UF-TENG. The low velocity startup enables the UF-TENG to harvest extremely low-velocity ocean current energy, e.g., presently achieving 0.133 m/s as the critical startup velocity. The proposed UF-TENG has a simpler structure and better low velocity performance when comparing with electromagnetic generators and piezoelectric generators. Parametric studies are conducted to evaluate the influence of geometrical parameters of the UF-TENG on the vibration behavior and output performance. It is demonstrated that the underwater electrical appliance can be powered by parallel UF-TENG units. The present UF-TENG is a more cost-effective and more accessible hydroelectric technology to utilize the renewable ocean current for powering sensors or micro electric appliances in Internet of Things.

We present a new method for detection of abnormal behaviors in crowded scenes. Based on statistics of low-level feature—optical flow, which describes human movement efficiently, the motion energy model is proposed to represent the local motion pattern in the crowd. The model stresses the difference between normal and abnormal behaviors by considering sum of square differences (SSD) metric of motion information in the center block and its neighboring blocks. Meanwhile, data increasing rate is introduced to filter outliers to achieve boundary values between abnormal and normal motion patterns. In this model, an abnormal behavior is detected if the occurrence probability of anomaly is higher than a preset threshold, namely the motion energy value of its corresponding block is higher than that of the normal one. We evaluate the proposed method on two public available datasets, showing competitive performance with respect to state-of-the-art approaches not only in detection accuracy, but also in computational efficiency.

s Wind energy harvesting from ambient environment by TENG is highly desirable for powering the wireless sensing system. However, humid environment and variable wind direction deteriorate the output performance of the most demonstrated TENG-based wind energy harvesters. In this work, a humidity resisting and wind direction adapting flag-type TENG is to be proposed and investigated. The flag-type TENG consists of two carbon-coated polyethylene terephthalate membranes and one strip of poly tetra fluoroethylene membrane with their edges sealed up. Thus, the triboelectric layers are isolated from the air and the electrical performance is independent of the relative humidity. Parametric studies are conducted to evaluate the influence of geometrical parameters of the flag-type TENG on the flutter behavior and the resulting energy output. It is interesting to find that a pair of flag type TENGs with a certain gap distance can contact with each other due to the wind speed variation and pressure difference between the internal and external flow areas. The power density is increased by 40 times compared with the only one flag-type TENG. In addition, the flag-type TENG can harvest wind energy from arbitrary directions without equipping other extra mechanisms. It can also serve as a self-powered wind speed and direction sensor. Therefore, the present flag-type TENG has a great potential to apply for ambient wind energy harvesting, self-powered wind speed and direction sensing in harsh natural conditions.

Due to the risk of failure of LED luminaries induced by the driver power, performance testing is especially important to driver power in some critical industries production and acceptance of work. A test system of LED driver based on LabVIEW is proposed to detect multiple physical parameters, including input voltage, output current, driver power efficiency, peak factor of current ripple and total harmonic distortion etc. The component selection of the system was investigated and the framework of the proposed system was presented. The hardware of this system mainly consists of signal conditioning modules, data acquisition card, test cables and computer. The software is designed by LabVIEW to realize the calculation, display and analysis of the collected data. The experimental results show that the system can realize the test of LED driver, and real-time grade determination of the test results according to relevant standards or the exact level specified by client. In addition, the system has simple structure and high expansibility, which is convenient for early use and later maintenance. The stability and bias was carried out to evaluate the proposed system by Minitab software, which ensured the measurement accuracy.

Abnormal event detection is a rapid development task in video analysis, which is aimed to distinguish abnormal and normal events in surveillance videos. As the normal and abnormal events have some similarities, more discriminating methods or motion information need to be explored. In this paper, to detect escaping people in different scenes, a global abnormal event detection method is proposed based on motion information entropy. To be specific, the proposed method utilizes the directions and magnitudes of motion vectors extracted from optical flow field to calculate the motion information entropy which represents the uncertainty of motion information. The normal samples are distributed around the center of a Gaussian distribution while the abnormal ones are distributed on the side. Experimental result shows that the proposed method has better detection performance than most of other classic methods with much lower computational complexity.