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In order to achieve the unified measurement of the air velocity from subsonic to supersonic circumstance, an analytical method referred to as the equivalent acoustic source, which was only suitable for the analysis of supersonic air current before, is extended to the subsonic case. Systematic analysis demonstrates the essential difference of the air current property between subsonic and supersonic scenario. Finally, a unified measurement model of acoustic particle-velocity vector is introduced. It provides a mathematical basis for us to measure the transonic air velocity via the use of an acoustic particle-velocity sensor, i.e., Acoustic vector-sensor.

In this paper, the transonic measurement of air velocity is addressed based on an acoustic vector sensor. According to the measurement model of acoustic particle-velocity vector field developed by the analytical method of the equivalent acoustic source, we establish the relationship between the observation data of the acoustic vector sensor and the transonic air velocity to be estimated. A two-dimensional Generalized Multiple Signal Classification algorithm for Air Velocity Estimation (GMUSIC-AVE) is proposed. The GMUSIC-AVE algorithm can not only make the correct judgment between the subsonic and supersonic air velocity, but also yield high estimation accuracy of the current air velocity. Simulations are implemented to illustrate the effectiveness of the proposed algorithm.

In order to realize high-precision position tracking control for (Medium Density Fiberboard, MDF) continuous hot press hydraulic position servo system in the presence of interior parameter perturbations and external load disturbance, an adaptive backstepping sliding mode control strategy with fuzzy disturbance observer (FDO) is presented. Firstly, a modified FDO is designed to estimate and compensate the interior parameter perturbations and external load disturbance of the system. Secondly, the backstepping sliding mode controller is designed and adaptive algorithm is used to online estimate the uncertainty of the system. Thirdly, the convergence of tracking error and the asymptotic stability of system are strictly proved according to Lyapunov stability theory. The results of simulation experiments indicate that the controller has strong robustness against the interior parameter perturbations and external load disturbance. Moreover, the controller has good performance including fast response, high tracking accuracy and small steady-state error.

The scale of Logistics Park in all regions affected by the level of local economic development and various factors, so it must be scientifically and rationally calculated and planned. But the reality is that the blind construction of Logistics Parks began to emerge, which can't decrease the cost, or stop the loss of state assets. Therefore, we must sum up the experience all over the Logistics Parks and the scientific methods of academic research; determine reasonable Logistics Parks' scale to avoid the problem of blind construction and expansion. This paper describes and comments in recent years, domestic methods for determining the scale of Logistics Parks, hoping to determine the size of the Logistics Park has a guiding role.

Label placement is very important when we display the electronic map. It will affect the beauty of electronic map. Furthermore, in order to display label placement in real-time, the computational complexity can not be too high. A novel algorithm of label placement is expounded based on the thinking of grid. It first divides the screen simply, then those three objects of points, arcs and polygons will be dealt with. The label configuration is reasonable, and does not result in any overlap. The experimental result indicates this algorithm is simple and effective. It can meet the demand of high quality map dynamic label placement and is successfully applied in commercial GIS.

Based on the advantages of both wavelet analysis and artificial neural network, the wavelet neural network (WNN) model is established through coupling wavelet transform with BP neural network for forecasting the basin sediment yield. The time sequence of the annual sediment yield is decomposed and reconstructed into the low-frequency and high-frequency components by wavelet transform; then these components are predicted by optimized BP neural network respectively. Finally, the sum of the predicting values is the forecasting result of the sediment yield. The result shows that the hybrid model, compared with the traditional BP (TB) model, has high accuracy in the simulation and test of basin sediment yield, which can provide a scientific basis for ecological environment protection and water resource management in a basin.

This paper addresses the pricing decisions of the decentralized assemble-to-order system. We consider an assemble-to-order system consisting of two substitute products and three components manufactured by different suppliers. Demand for the products is price-sensitive. The final selling prices for the products are jointly determined by firms in the system. We study the system under both centralized and decentralized decision making situations. For the centralized system, we demonstrate that there exists a unique optimal pricing solution. For the decentralized system, we show that there exists a unique Nash equilibrium in the players' pricing game. We show that the decentralized system can be effectively coordinated and the system performance can be improved with a simple profit-sharing contract. Finally, numerical examples are provided.

A Hinfin filter based on GPS dynamic locating method is put forward in this paper. The proposed method is able to decrease the current acceleration model error. Some examples show that the method can perform better in GPS dynamic locating than EKF for less computation consumption and higher locating accuracy.

Optimal system performance requires the close cooperation among all members in the system. We investigate a decentralized two-stage assemble-to-order system with price-dependent demand. The assembler assembles products with complementary components from multiple suppliers. Each customer has an individual reservation price, which is uniformly distributed. Customers place orders when the product price is below their reservation prices. We compare the price and system profit in the decentralized system with those in the centralized system. The product price is higher and the system profit is lower in the decentralized system and the system profit loss is associated with the number of suppliers in the system. We propose a profit-sharing contract and show that it can effectively coordinate the system and achieve the same optimal system profit as that in the centralized system.

In this paper we improve the performance of tensor voting over large contour gaps by extending the naive tensor voting techniques. We propose an iterative optimization procedure together with three extensions such as orientation estimation modification, saliency measure revision and edge thinning. As the experimental result shows, the extended tensor voting is more efficient to complete large contour gaps.