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With the large scale accessing of wind power to the grid, the power system will withstand different types of active disturbances. In other words, in addition to the traditional step change of the active power caused by the generator outages or sudden change of load, the random fluctuation of the wind power will also cause a distinct deviation of the system frequency. Since different types of disturbances will cause different frequency response characteristics, it inevitably puts forward higher requirements for the optimal configuration of the primary frequency modulation capacity and governor parameters to synchronous generators in the system. For this reason, based on the electromechanical dynamic model which equivalent to the single machine, this paper analyzes the different characteristics of the primary frequency modulation under the step type likes generator outages or sudden change of load and the sinusoidal form likes wind power fluctuation. At the same time, the simulation results of the IEEE 3-machine 9-bus system based on the DIgSILENT further show that the governor aimed at single type active disturbance can not better adapt to other types. This paper will lay the foundation for the primary frequency optimizing configuration of the power system which considering multiple types of active disturbances.

In this paper, the reliability evaluation of distribution network is studied by using the sequential Monte Carlo simulation based on dual sampling. A reliability evaluation model of distribution network is established. The range influenced by fault is determined by the analysis method of node fault. And then, all kinds of reliability index are calculated. With Matlab programming, IEEE RBTS Bus 6 test system is evaluated to prove that the method in this paper is effective. Then the simulation analysis is carried out for the cases that whether there is a standby transformer in power distribution network, whether the circuit breaker is reliable and whether there is a contact switch between the two feeders. The results show that the reliability of distribution network system can be enhanced by adding the standby transformer and the contact switch and improving the reliability of the circuit breaker.

Some potential danger, such as robbery, steal, and drug-dealing activity, can be avoided effectively by detecting loitering behavior in advance. In this paper, we propose a loitering detection algorithm by analyzing the trajectory of pedestrian. Firstly, we propose a trajectory extraction method combined with motion estimation and object detection to adapt to the tracking under a static camera scene. Then we judge the loitering behavior by analyzing the trajectory of object through the duration time and angles variation between the initial point and remaining points on the trajectory. The experiments were performed using several surveillance cameras. And experimental results show that the proposed method provides superior performance in terms of accuracy, robustness, and speed.

In general, some abnormal crowd behaviors are associated, for example, fight causes tumble or panic and tumble causes stampede. And those abnormal behaviors often happened at the same time. However, most researchers consider those mixed abnormal behaviors as only one behavior and ignore the other behaviors appearing in the video. To analyze those behaviors better, this paper proposes a method using label distribution learning to detect the crowd abnormal behavior such as stampede, fight, panic and tumble. We consider that every behavior sequence associated with some behavior labels, and the behavior label distribution covers a series of behavior labels, representing the describe degree that each behavior labels describe the behavior sequence. Then a label distribution learning algorithm named BFGS can be used to learn the behavior label distribution. Through this way, we not only can obtain which behavior happened, but also all behaviors are taken into account for each behavior sequence. The experimental results show that our approach achieves better performance for crowd abnormal behaviors detection.

Space-ground integrative network is an important development direction for sustainable communication networks especially to the information system which contains the data acquiring in multiple ways including space and ground, data processing by amalgamation and so on. As a new satellite technology, ORS (Operationally Responsive Space) will provide a fast and flexible solution for emergency response such as aim tracking, dense earth-observation, communication relay and so on, which can be fast deployed or awoken and play an important role on-demand. However, most existing satellite communication follows a designated and static scheme that can't meet the dynamic networking requirements of ORS. In order to build a reliable ORS satellite network whose communication parameters can be reconfigured such as task region, work time, cooperation satellites, QoS and so on, a new satellite network architecture should be studied. Firstly, based on software defined network (SDN) technology, a networking scheme for ORS satellites was proposed in literally, named SDN-Sat Arc, which adopted a light-structure. It can also receive and process the instructions of ground center. Then ORS satellite network model was designed according to network meta-model defined by us to allow describing current ORS satellite states, and compute the necessary multi-hop route in the future.

This study found a positive correlation between dual commitment and positive industrial relations climate while a negative correlation between dual commitment and negative industrial relations climate according to a questionnaire survey with 610 samples in several Wuhan's private enterprises. With a further research by using the Logistic regression model, the affective commitment, normative commitment in organization commitment as well as the member's affection and member's benefits have a remarkable positive impact on positive industrial relations climate, while economic commitment and choice commitment in organization commitment as well as member's affection and member's benefits have a remarkable negative impact on negative industrial relations climate. This essay is conducive to both a correct understanding of unions for the managers of private enterprises and the creation of a harmonious industrial relations climate for the unions.

This study represents a watershed-scale study of C fluxes from land change in the Jiulong River watershed, a subtropical watershed in Southeast China. Land-cover maps of woodland, cropland, orchard, built-up, water, and barren from 1986, 1996, 2002, 2007, 2010 were produced using a combination of unsupervised classification and spatial reclassification based on manual on-screen digitizing. Intensity analysis was then used to identify the dominant and systematic transitions. C fluxes from land change over three decades of imagery were estimated from the transitions among woodland, cropland, built and orchard for each time period. C accumulation and losses from terrestrial biomass are derived from observed changes in land cover. The ecological method used in this study considered that the amount of C emitted to the atmosphere is a function of the amount of C stored in terrestrial vegetation and the areal extent of each land-use category, combined with key terms of biomass, annual carbon gain, and burning efficiency. The results indicate that the trend of LUCC in Jiulong River watershed can produce a considerable potential of function as an important Carbon sink in south-eastern China, the net amount of carbon stored can be 4.50×104 t, 1.86×105 t, 9.21×105 t, 1.35×105 t for 1986–1996, 1996–2002, 2002–2007, and 2007–2010, respectively. The findings of this study enable us to gain a broad understanding of watershed-scale C fluxes from land change in a subtropical watershed of China.

Software configuration management (SCM) controls and maintains the revision, integrity and traceability of software systems throughout the entire software life cycle. In order to solve the efficiency problems in construction, management and maintenance of software configuration component library, a component classification method based on priority-facet (PF-CCM) was proposed. Unifying the three kinds of component retrieval mechanisms, i.e., index, key word and facet, an optimized matching algorithm with pruning (POMA) was introduced, which sorts the query results according to the priority of facets. The experiments show that these works can improve the query efficiency.

GML, a geographic information coding standard, has been widely used in WebGIS, heterogeneous GIS data sharing, integration, and interoperation. However, its features of large amount of redundancy inherited from XML file structure and geographic information system make a serious obstacle in WebGIS applications. According to the characteristics of GML, a data stream-based compression algorithm GDSC ( GML data stream compression ) was given, which separated the GML into structure data and value data using “Draw Pattern”, replaced the structure data with dictionary table during the separation process, and compressed the structure data and value data respectively to increase compression rate. In order to reduce compression time, GDSC uses two sub-threads for compression, decompression and network transmission.

We propose and demonstrate a direct method to observe higher-order whispering-gallery modes in vertical cavity surface emitting lasers (VCSELs) at room temperature by embedding a defect-free a surface micro-structure. Up to the 23rd azimuthal order whispering-gallery mode confined laterally by the native oxide layers is observed in experiments and identified by the spectrum in experiments as well as numerical simulations.

In this paper, a progressive audio coding algorithm is presented. Distinctive from existing transform-based perceptual audio coding schemes, which allow either constant bit rate or multiple fixed bit rates, our proposed algorithm achieves a fully embedded audio coding scheme whose bit rate can be controlled depending on the user's requirement. This feature makes it extremely useful in audio networking applications, such as audio on-demand and audio broadcasting over the Internet. In the proposed audio coding scheme, efficient successive quantization and bit layer coding are applied to the compact audio signal representation obtained from traditional subband decomposition. Our research focuses on the improved successive approximation quantisation (ISAQ), which performs bit allocation for quantization based on psychoacoustic analysis of the input audio signal. Thus the progressive audio coding is achieved, while perceptually transparent audio coding is also maintained to the allowance of bit rate constraint. The performance measurement of our presented algorithm is demonstrated.

To deal with a small sample problem which appears in estimating the prevalence rate of hypertension, this paper presents an unlimited information diffusion method with a special kind of function, which is called the "normal structural information diffusion function with parameters". Based on the supposition that the variation of the prevalence rate with age and body mass index (BMI) - which are the two main risk factors - should be smooth and have no great fluctuations, this paper introduces a new method to optimize the parameters according to the "minimal fluctuation principle".

A progressive approach to perceptual audio coding is presented in this paper. In contrast with existing perceptual audio coding schemes where the digital audio signal is encoded at a fixed bit rate, the progressive approach achieves fully embedded audio coding whose bit rate can be controlled dynamically, making it useful in audio networking applications. In the proposed scheme, efficient successive quantization and bit layer coding are applied for the compression of an audio signal representation obtained from traditional subband decomposition. An improved successive approximation quantization (ISAQ) is introduced to perform bit allocation and quantization based on the psychoacoustic analysis of input audio signals.