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In order to solve the problem of optimal scheduling caused by the coordinated operation of multi-microgrid and distribution network in the region, a cooperative optimization scheduling method for multi-microgrid and distribution network is proposed based on taking into account the participation of electric vehicles. This method can fully utilize the distributed energy in the microgrid and improve the power quality of distribution network and the economic benefits of the microgrid. The satisfaction degree of electric vehicle users is also considered. Coordination between multi-microgrid and distribution network using two-layer model hierarchical coordination method. The upper layer is the distribution network system, and the lower layer is the Multi-microgrid system. Based on the prediction of power supply and load, the optimal objective function of each layer is established. The effectiveness of the two-layer model is verified by simulation, compared with other methods, the advantages of this method in multi-microgrid economic model and distribution network stability are proved.

System in Package (SiP) plays an important role in Consumer Electronics, Military and Aerospace Electronics with the superiority of microminiaturization, weight reduction, high density, and high reliability. Nevertheless, SiP module test has encountered the problem on malfunction location with the system scale and system complexity exponentially increasing. An interconnect test detects, identifies and locates intra-die assembly defects, which is systematically performed in conventional board testing. Built on the JTAG test technology which has been responsibly used on board testing, this paper proposed a testing method, testing flow and testing platform for SiP module interconnection testing, and discussed the discrepancy between the testing for board and the testing for SiP. In the interconnection testing of the certain SiP module, the test coverage of the interconnection network is provided.

To visualize and analysis the multidimensional integer dataset, we present a visualization method named segmental offset-mapping parallel coordinates. The method first counted and calculated the proportion of each integer value in each dimension. The stacked coordinate axis was adopted to express the distribution of data in each dimension. The offset-mapping technology was introduced to obtain corresponding points in axes. The position of corresponding points could be different even the same integer value in different record using offset-mapping. The corresponding points was scattered over segment in the stacked coordinate axis using the offset-mapping technology. The offset-mapping technology can improve the capability of expressing the correlativity between the adjacent dimensions effectively for the multidimensional integer dataset. Road scene data in the unmanned driving field was selected as the experimental dataset in this paper. The experimental results prove the method presented in the paper can achieve obvious expression to the correlativity between the adjacent dimension data. The method can effectively improve the matching and analysis efficiency of road scene data in the unmanned driving field.

In the analysis of plastic packaging SiP product failure, we should not only consider the plastic material and techniques inherent problems, but also the problem that SiP products have a lot of materials, complex structure, and small surface bonding. A type of plastic packaging SiP module function failure after reflow soldering, through appearance inspection, pin electrical characteristic test, X-ray analysis, Scanning Acoustic Microscope(SAM) examination and longitudinal section inspection and so on. We found that due to the compact structure, the design refers to the bonding finger with a small distance from the bare die, resulting in a small amount of adhesive film and forming a hole. In addition to improper selection of adhesive, the conductive adhesive after curing is relatively brittle and hard. It is not conducive to large chip resistance stress, resulting in plastic devices after moisture absorption during reflow soldering. The internal Vapor thermal expansion leads to delamination and failure.

Along with the construction and development of Global Navigation Satellite System (GNSS) technology, GNSS has been widely and increasingly used in the ocean field, such as offshore wind retrieval, sea ice observation, sea state monitoring et al. Researchers from National Ocean Technology Center take advantage of GNSS satellites signal Doppler shift to measure the buoy state, then inverse the wave spectrum, and calculate the wave characteristic values; Furthermore, GNSS receiver and GNSS Ground-based Augmentation System (GBAS) is used to measure the real-time height of the buoy, then the tide data is extracted through a low-pass filter and a tide revised. Presently, both of the inversion algorithms have passed the laboratory and field test, the results are summarized as follows: the measured wave data is in good consistency with the reference instruments and the tide accuracy of measurement can arrive at centimeter-level. Recently, researchers are concentrating on further improvement of simultaneous inversion algorithm.

Measuring the spurious free dynamic range (SFDR) of analog-to-digital converters (ADCs) by the fast Fourier transformation (FFT) has difficulties in performing coherent sampling and integral period truncation. The non-coherent sampling is inevitable, and the SFDR measurement results may be disturbed by the spectral leakage and the picket fence effect (PFE). We propose a triple-spectrum-line interpolated FFT algorithm based on a five-item cosine window with the maximum side lobe decay speed to reduce the errors caused by the spectral leakage and PFE. The verification platform is constructed based on MATLAB, and the behavior-level dynamic models of typical high-speed ADCs are employed for simulation and verification. Results show that the proposed method can achieve the similar measurement accuracy as the standard coherent sampling FFT method with significantly reduced test cost.

Data analysis reflecting the social politics, economy, public opinion and the management of public sentiment, especially those in such areas based on questionnaire survey, often need to study the main factors affecting a problem. The traditional statistical analysis method is to count the factor which is selected most frequently among those influencing a question, which is dee me d as the most principal factors. But the principal factors are not necessarily sensitive factors, that is, a sensitive factor is not necessarily often highest selected factors. An entropy based method is proposed to determine the sensitive factors, and the analysis of multiple choices in questionnaire survey is selected for the empirical study, the calculation method of sensitive factors and its significance is discussed.

Leaf color has been commonly used as an index for crop stress status diagnosis. We have developed a low-cost and non-destructive method that is easy to use to assess the health status of plants, based on the estimation of chlorophyll content of leaves using a portable digital camera. Relationships between chlorophyll content and leaf image color indices in the RGB and Lab* space with the comparison of SPAD are examined. The RGB color indices of R, G and R+G+B, R-B, R+B, R+G and The Lab* space parameters L*, a* and b* had the significant relationship with chlorophyll content. Although the determination coefficient and prediction confidence intervals of color indices regression were not good than SPAD, the leave imaged tools had the profit of easy operation, found everywhere and no much money cost. The indices from leaf color image analysis maybe used to estimate chlorophyll content.

This paper presents an automatic procedure for constructing a compact synthesized collage from a video sequence. The synthesized image called video collage, is a kind of static video summary - to select most representative images from video, to extract salient regions of interest (ROI) from these images and resize them according to their saliency, and to seamlessly arrange ROI on a given canvas with the temporal structure of video content preserved. We formulate the generation of video collage as an energy minimization problem in which each of above desirability is represented by an energy term. Unlike most existing video presentation schemes, video collage is more compact and visually appealing. We have applied video collage on several home videos and report superior performance in a user study compared with key existing approaches to video presentation.

Fast and accurate segmentation of moving objects in video sequences is a basic task in many computer vision and video analysis applications. This paper presents a novel method for background modeling based on the unscented Kalman filter (UKF) algorithm. In addition, shadow detection is conducted during motion segmentation. Experiments are performed under different conditions indoor and outdoor. The results show that the proposed algorithm is effective and efficient in background modeling and motion segmentation

Video is an information-intensive media with much redundancy. Therefore, it is desirable to be able to mine structure or semantics of video data for efficient browsing, summarization and highlight extraction. In this paper, we propose a generic approach to key-event as well as structure mining for sports video analysis. Mosaic is generated for each shot as the representative image of shot content. Based on mosaic, sports video is mined by the method with prior knowledge and without prior knowledge. Without prior knowledge, our system may locate plays by discriminating those segments without essential content, such as breaks. If prior knowledge is available, the key-events in plays are detected using robust features extracted from mosaic. Experimental results have demonstrated the effectiveness and robustness of this sports video mining approach.

In the process that MR signal is quadrature demodulated, the initial phases of sinusoid and cosinusoid used as demodulation reference signal exist errors, which results in artifacts in the image. It is typically overcome through precise control of the initial phases with the help of the special hardware, but the errors are not reduced completely. In this work, a method based on reference scan is proposed. Reference scan without frequency encoding gradient and phase encoding gradient is executed before FSE sequence, and an echo train is acquired. The phase errors of sinusoid and cosinusoid that are used to demodulate each echo in the reference echo train are calculated. Then the k-space data of image is corrected by these errors and artifacts are removed. The experiments using 0.35T MRI system demonstrate the effectiveness of this method.

Presenting more comprehensive information than key frame and any subset of frames, mosaic has attracted a growing attention in recent years as a useful element for a variety of vision tasks. In this paper, we present an efficient approach to video mosaicing based on motion analysis with investigating two important issues that significantly affect the performance of mosaicing. First, given a video shot, a method based on motion entropy analysis is introduced to determine whether the visual content in a shot or video segment is suited to be represented by a mosaic. The second is to decide which subset of frames in the shot is the best to be selected for efficient and effective mosaicing by constructing a global motion path. Experimental comparisons with typical mosaicing method approve that with this approach, the visual quality of mosaic is significantly improved, as well as the computation time is remarkably reduced.

Pictures have become increasingly common and popular in mobile communications. In our previous work, an attention model based scheme has been proposed to facilitate the browsing of large images on small displays. However, the image analysis components involved are quite costly in terms of power consumption and time, especially for thin clients. To deal with this problem, in this paper, we introduce our experience in using a proxy-based system for deploying image adaptation procedures. The images are processed while delivering from the server to the mobile clients and the adaptation results are stored as metadata in the image header. Experimental evaluations indicate that our approach is efficient and practical.

Images have become more and more common in mobile communications. People now can easily take and exchange pictures on the move using their mobile devices and digital cameras. However, a crucial challenge is to provide a better user experience for browsing large images on limited and heterogeneous screen sizes of mobile devices. In this paper, we propose a novel image viewing technique based on an adaptive attention shifting model. A presentation technique named rapid serial visual presentation (RSVP), borrowed from the UI community, is used to simulate the attention shifting process. We show a prototype image viewer developed for pocket PC and conduct some evaluations to demonstrate the effectiveness of our approach.

This paper presents an algorithm for classifying moving objects in real-world traffic scenes. Spatial and Temporal information provided by region segmenting and tracking is used for moving object classification. In order to achieve real-time requirement, the proposed approach uses the classification metrics that are computationally inexpensive and makes use of simplifying assumption that there are two kinds of objects: vehicle(including motorcycle, car, bus, and truck) and human (including the pedestrian and bicycler). Using the classification statistics, we successfully reduces the occlusion effect. The experiment results show that the object classification algorithm can obviously improve the performance of urban traffic monitoring system, such as, the accuracy of vehicles counting and average speed measuring, and rarely degrades the system processing speed.