Today, simulation of electrical drives with asynchronous motors based on systems of differential equations is regarded as one of the principal means of their research study. The difficulty of the simulation is determined by the need for accuracy of the results obtained and the complexity of the mathematical model’s differential equations. In this article, we present a study of the particularities of the simulation of electrical drives systems with asynchronous motors. We have studied models composed of three-phase and orthogonal coordinates systems and we have shown that qualitative and quantitative differences exist in the process of changing the angular speed of the rotor and electromagnetic torque. The result obtained is above all influenced by the non-linear character of the load opposing a fan-type or “dry friction”-type resistant torque. For dual-earthed electromagnetic actuation with the moments of the resistant torques indicated, integration of differential equation systems was carried out with various digital methods used in professional mathematical software for simulation.

PCNN has been widely used in image segmentation. However, satisfactory results are usually obtained at the expense of time-consuming selection of PCNN parameters and the number of iteration. A novel method, called grayscale iteration threshold pulse coupled neural network (GIT-PCNN) was proposed for image segmentation, which integrates grayscale iteration threshold with PCNN. In this method, traditional PCNN is simplified so that there is only one parameter to be determined. Furthermore, the PCNN threshold is determined iteratively by the grayscale of the original image so that the image is segmented through one time of firing process and no iteration or specific rule is needed as the iteration stop condition. The method demonstrates better performance and faster compared to those PCNN based segmentation algorithms which require the number of iterations and image entropy as iteration stop condition. Experimental results show the effectiveness of the proposed method on segmentation results and speed performance.

Han et.al have applied two SAOR splitting formats for solving the linear complementarity problem. We improve them by introducing a class of preconditioners based on the SAOR methods. The convergences of the modified methods have been analyzed. We also show the applicability of the methods by numerical example.

The main goal of present paper is to construct an efficient reduced order model (ROM) for aerodynamic system modeling. Proper Orthogonal Decomposition (POD) is presented to address the problem. First, the snapshots are collected to form the POD kernel, and then Singular Values Decomposition (SVD) is used to obtain POD modes, finally POD-ROM can be constructed by projecting full order aerodynamic system to POD modes subspace. Two problems are addressed: (1) aerodynamic data inverse design; (2) aeroelastic structure active control. For the second problem, POD method with balanced modification is introduced to improve the robustness of original POD method. Results in problem (1) suggest POD method works efficiently not only for interpolation inverse design but also for extrapolation problems. The results in problem (2) demonstrate POD method with balanced modification is efficient and accurate enough for aeroelastic system analysis.

This paper presents a new method for realistic real-time rendering of air pollutants based on image processing. The air pollutants’ variable density can create many shapes of mist what can add a realistic environment to virtual scene. In order to achieve a realistic effect, we further enhance thus obtained air pollution data getting from monitor in spatial domain. In the proposed method we map the densities of air pollutants to different gray levels, and visualize them by blending those gray levels with background images. The proposed method can also visualize large-scale air pollution data from different viewpoints in real-time and provide the resulting image with any resolution theoretically, which is very important and favorable for the Internet transmission.

Representation is a key concept for information systems (IS). IS is designated to provide information. However, the most available information systems such as databases using a computer are actually data storage and management systems because all they handle are data, which may be used to represent information. Therefore, a good understanding on the relationships between data, information and representation is vital for our study of information systems. And yet, it would seem that in the literature of information systems, the notion of representation has not been well studied, and in particular, how a possible representational relationship between two sets of data constructs may be systematically identified and how this representational relation may be explored for bearing on IS problems would seem worth looking at. The results of our investigation show that representation is a special type of signs created or being used by human agents to carry information about other states of affairs. Any representational relationship is realized and underpinned by information flow between components within an information channel. Moreover, representation can be quantitatively measured as long as certain conditions are met. The information content of representation reveals what you could possibly learn from it and the semantic content of representation is the proposition that a human originator intended to convey by using the representation. In addition, schema connections (i.e., connections between elements within a data schema) can be identified by examining the representational relationship between data entities.

A brushless DC(BLDC) motor with the characteristics of high speed and high power density has been more widely used in industrial area. The BLDC motor requires the position and speed sensors for control. However the position sensors are undesirable from standpoints of size, cost, maintenance and reliability. There are some different ways that can solve this problem, depending on the flux distribution. This paper describes a control system of sensorless BLDC motor. The back-EMF is adopted to detect the rotor position. The back-EMF is very small in the motor starting process, and it is difficult to obtain rotor position efficiently. A re-setting method of the rotor is proposed in the paper, and current closed loop is used for high-speed and safety in the motor starting process. A good speed and current double closed loops system is designed. The speed and current regulators are implemented by a digital signal processor(DSP). A simple algorithm is used to calculate motor speed indirectly by the software, which simplifies the system hardware structure. The hardware structure and software design of sensorless BLDC motor control system are described in details. The simulation and experimental results have shown the validity of the sensorless control system and the accuracy of the detective position signal obtained.

We model document summarization as a nonlinear 0-1 programming problem where an objective function is defined as Heronian mean of the objective functions enforcing the coverage and diversity. The proposed model implemented on a multi-document summarization task. Experiments on DUC2001 and DUC2002 datasets showed that the proposed model outperforms the other summarization methods.