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The regional energy Internet is coupled with natural gas, hot and cold, transportation and other technologies complement with the power system as the core. That helps multi-energy advantages complement each other and makes the entire system green and efficient. It is of great significance to promote the transformation of energy structure and promote China's energy revolution. The extraction of key indicators of different aspects of regional energy Internet, and the research of comprehensive benefit evaluation is an important issue that needs to be solved urgently. Firstly, considering the regional energy Internet economic benefits, environmental benefits, social benefits, the indicators with universal adaptability are extracted from the energy link, equipment link, distribution network link and user link. Then the analytic hierarchy process is used to determine the weight of the indictors, and the comprehensive state of the regional energy Internet is obtained by the fuzzy mathematics theory and the improved evidence reasoning. Finally, the effectiveness and practicability of the proposed method are verified by practical examples, and the development level of regional energy Internet in the example is accurately evaluated. Corresponding suggestions for the development of China's regional energy Internet are provided.

Based on the findings from reviewing most Unix textbooks in Chinese universities, we have identified common problems and analyzed their inadequacies, such as the bias of operation system, too many technical terms and inadequate treatment of programming-related content. The discussion about each problem is substantiated with examples, and suggestions are made on possible improvement. This analysis would be helpful to construct a more reasonable Unix course system scheme.

In this paper, we proposed a method to fuse data from radar and IR sensor in Extend Kalman probability hypothesis density (EK-GMPHD) filter. Firstly the multi-target is estimated with infrared (IR) sensor using EK-GMPHD filter, and then the filtering results are fused with measurements from radar through sequential filter, in this way, the multi-target state is updated at the tracking system. Under false alarms, missed detections and dense targets environment, this method has a high reliability when tracking multi-target. Simulation experiments are presented to demonstrate the performance of the proposed method.

This paper presents a novel SINS/GPS tightly integrated navigation algorithm based on Adaptive Extended Kalman Filtering. This algorithm is mainly used in vehicle SINS/GPS integrated navigation system to deal with time varied noise statistic in different working conditions. First, measurement noise covariance is estimated through innovation sequence online, then the covariance matching algorithm is used to track the process noise real-time based on the system equation. More, scale factor is introduced to reduce truncation error caused by Taylor formulation and thus improve estimation accuracy. The Simulations results show that, compared with the traditional extended kalman filter algorithm and unscented kalman filter algorithm, the proposed algorithm is able to estimate the changes of both process and observation noise statistics simultaneous, and have higher precision and more robustness.

Multi-target tracking is an important component of a surveillance, guidance, and obstacle avoidance system. The probability hypothesis density (PHD) filter is an attractive approach to tracking an unknown, and time varying number of targets in the presence of data association uncertainty, clutter, noise, and miss-detection. But there is no closed-form solution to the PHD recursion. Another approach to solve the problem, a closed-form solution for the PHD, named Gaussian mixture PHD (GMPHD) filter. This method can avoid the data association problem in multi-target tracking. Moreover, it is more reliable and less computational than particle PHD filter for multi-target tracking. Experiments show the GMPHD filter to be able to estimate both the number of tracked targets, as well as the states of the targets, robustly from noisy observations, the simulation results show that the method is simple and effective.

Aerial target under the daytime condition shows complex imaging characteristics, like misshapen and blurred edges, even flickering and discontinuous imaging, which becomes a bottleneck of target detection and tracking in imaging tracking system. This paper presents a novel algorithm for detecting and tracking aerial targets with blurred and flickering imagery. Firstly, point spread function (PSF) is determined combining with the feedback information of tracking process and we use a new model of image restoration proposed by Ben-Ezra to deblur the moving target. Secondly, association network model with linking mechanism is established in terms of their similarity based on accompanying values of the target features to handle the situation of flickering imaging and feature losing for target. Simulations are conducted using the proposed method for image sequences, which can obtain the good results.

This paper presents a new strategy to speed up the encoding process for fractal image compression. First, the range blocks are obtained by partitioning the image using adaptive quadtrees. Then we extract the high-order spectrum based on nonparametric double-spectrum estimation to constitute the eigenvector for the image block which size is larger than 4times4. The lower dimension kd-tree structure is to be created while orthogonal projecting these eigenvectors of high-order spectrum for the image block. The fractal code is quickly obtained by using nearest neighbor searching algorithm and quantizing the transform parameters. The experimental results show that, in comparison with conventional methods, the proposed algorithm can provide better speed-up and image quality under the same compression ratio.

A composite contact materials Ag-SnO2 have been used in low current switching devices for its good anti-welding properties and resistance to arc erosion. But the mass material transfer occurred at large surge current in DC switching now and then. Mass material transfer have an increased probability of early failures because the effective contact gap reduces or two contacts lock together. In this research, the shape and distribution of crystals at the contacts surfaces were observed to analyse the reason of mass transfer. It was found that the shape and distribution of the crystals are like sunflower at the contact surfaces. The equal axes crystals distributed over the surfaces center, and the radial club-shaped crystals distributed around the center. One test showed that the melting phenomena at the interface of crystals had precedence over that in other sections at large surge current for the composite contact materials Ag-SnO2, it result in individual crystal transfer or several crystals transfer together.