Because the request of automobile safety is higher and higher, drivers should clearly ensure the surrounding environment of the car, a kind of car surveying technology is proposed. Video mosaicing technology is the basis of surveying technology. In order to meet the requirement of vehicle instantaneity, this paper uses FPGA to achieve the video mosaicing. The system includes video capture module, video pre-processing module, video mosaicing module and video display module. The paper uses Cyclone IV development board of Altera company to complete the system and uses double DDR2 to complete Ping-Pong buffer. We use sift algorithm to match videos and linear fusion algorithm to mosaic videos. The system is verified by experiments and its feasibility is proved.

The fault estimation problem is investigated for a class of stochastic time-varying delayed systems subject to channel fadings. A sequence of variables which are mutually independent but obey the Bernoulli distribution is employed to describe the randomly occurring character of communication delays and the modified L-order Rice fading model is used to better reflect the phenomenon of channel fadings. Lyapunov stability theory, stochastic analysis techniques and LMI(Linear Matrix Inequality) techniques are utilized to derive the sufficient conditions for the designed fault estimator. The estimator gains are obtained by solving the feasible solution of the LMI. An illustrative example is provided to demonstrate the effectiveness of the proposed scheme.

In order to improve the tracking precision of radar to low altitude targets, we propose a novel real-time bias compensation algorithm based on the fading memory recursive algorithm of least squares estimation. Different devises are used to track the target simultaneously and different tracking results are obtained. The recursive algorithm of least squares estimation is used to give different weight to the different tracking results. The estimation of the angle measurement bias is obtained. By theoretical analysis, the multipath environment model is achieved, and the performance of the proposed algorithm is checked. The results show that estimation error of the proposed algorithm is relatively small. And it can also reduce the vibration of the angle measurements and give stable estimating results.

 To enharce the service quality of the internet catering industy, to better meet the needs of customers at ang time pointmed, the research is an intelligent ordering system based on Android Studio development environment, C/ S structure, and Gradle and Genymotion development tools. This paper introduces the principle of image loading and the interaction process between activities and the background. The system has realized its functions such as menu browsing, commodity collecting, food ordering, user center and food choosing by shaking. The result of tests show that the system has a good user interaction experience and can be operated easily. And it will have an extensive application prospect.

 Between higher and lower communication mode, the type of propaganda is required to transmit video in broadcasting way in emergency situations and military applications especially. We propose a MAC(Media Access Control) algorithm with novel slot allocation way to ensure video transmission which refers to the idea in NbIA(Neighbors Indirect Acknowledgement Algorithm). Both proposed algorithm and NbIA are simulated using OPNET. The results show that former performs better in convergence time and throughput of single point.

In order to solve the problem that the charging electric appliance safety testing, A test normal ac power detection circuit introduced in this paper, Analyzed the principle of the circuit and the circuit simulation test. And then to the test circuit hardware physical structures, and the test results are recorded. Analysis and data processing through the control chip of A/ D module, and then to determine whether a rechargeable electric complete charging process and the judgment result feedback to the user, To achieve the charging electric safety control. The main characteristics of this circuit is of simple structure design, debug, in the actual test has very high reliability and stability.

We study the concepts of ACA (Action Coverage Area) and AC (Action Core), and design a multiple-viewpoint action model based on the advanced object recogniton method Latent SVM ( Support Vector Machine). Multi-viewpoint ACA can succinctly describe the non-rigid change and appearance variation due to different viewpoints and multi-viewpoint AC, because the auxiliary of ACA can help to improve the efficiency and robustness of action recognition. We created an independent dataset of human action for model training and testing. Experiments showed that our model had high performance in classifying and detecting human action in still images.

o establish kinematics model D-H parameter method is employed and virtual joints is introduced, according to a variety of joint types of complex manipulator. There are many problems of multi-joint manipulator, such as multiple solution, accuracy and real-time performance. The solution of the inverse kinematics is obtained by using four different optimization algorithm: the particle swarm optimization algorithm with LPSO(Linear Decreasing Weight Particle Swarm Optimization), CBPSO (Crossbreed Particle Swarm Optimization) algorithm, SAPSO (Simulated Annealing Particle Swarm Optimization) algorithm and CPSO(Choas Particle Swarm Optimization) algorithm. These algorithms are tested for the validity of the solution of inverse kinematics. Through randomly selected workspace points, the four algorithms are compared according to the executing time, the end-effector position error and so on. The results show that the improved CBPSO algorithm can be effectively used for the inverse solution for complex multi-joint manipulator, and satisfy the requirement of real-time control in actual work.

Because short duration, randomness and zero point are hard to detect for transient power quality disturbance, a transient signal disturbance detection method based on dynamic window of improved wavelet modulus maxima is presented. For passing zero point disturbance, on the basis of dynamic detection window, through the coefficient of transformation, improve the unconspicuous problem of the passing zero point. Simulation results show that the method can accurately detect and locate the transient power quality disturbances, precision is high and easy to implement.

In order to solve the profile control problem for the cam grinding system on the basis of analyzing the contour error, the control scheme that combines tangential-contouring control with position tracking compensation was proposed. The tangential-contouring control was used between two motion axes, and contour error was transformed into tangential-contouring coordinate frame. With regard to error components obtained from coordinate transformation, two corresponding controllers were desgined reseparately. To make up the deficiency of tangential-contouring control, there were employed compensators outside the position loop by additionally compensating position tracking error to guarantee the system performance and enhance the tracking ability of input signal of each axis simultaneously. Several experiments have been conducted on Simulink platform to test the proposed control scheme. The results show that the proposed control scheme decreases tracking error and contour error, and presents excellent contouring and tracking performances.

 In order to aquire accurate and robust positioning results, a low cost monocular camera and an IMU(Inertial Measurement Unit) are combined by sensor fusion for the ego-positioning of MAVs (Micro Air Vehicles). In the visual positioning module, three of the most representative state-of-the-art monocular visual positioning approaches, which are originally designed for vehicles, are evaluated in different conditions. Based on the experiment results, the pros and cons of each method are analyzed and discussed. Considering the limitations of vision-2only approaches, an EKF (Extended Kalman Filter) is used to fuse the visual positioning with an inertial sensor based on a loosely-coupled framework, to compensate for the instability of vision. The experiment results demonstrate that the visual-inertial sensor fusion can effectively reduce the positioning errors in unstable visual cases.

 In order to analyze and design secure signature schemes under the standard model, and avoid the similar security issues in designing signature schemes, a new certificateless signature scheme and a forward- secure certificate-based signature scheme in the standard model are analyzed. The results show that this signature scheme can suffer from public key replacement attack and backdoors attack, the attacker can generate a valid signature on any message. These attacks are analyzed concretely, the methods about how to overcome these attacks are discussed. These attack methods are reference significance for the analysis and design of similar signature.

 To correct printing mistakes timely and improve print quality, a printing density detection system based on ARM ( Advanced RISC Machines) chips is provided. The system can make density detection digitization and automation, systematic in the printing process. IMAGERECEIVER is used as an image acquisition module, Embedded CMOS (Complementary Metal Oxide Semiconductor) image acquisition chips(OV511 and OV7620) are used as an image capture device, PPI-DMA (Pixel Per Inch-Direct Memory Access) is used as high-speed data transmission channel, LCD (Liquid Crystal Display) is used as an image display, keyboard is used as a human interface device. The images are transformed to grayscale images and digitized images, and then the dot area is calculated. Finally, the function of printing dot density detection is performed. The experiment results show that the system can achieve printing density detection.

To understand and research comparison algorithm of big trajectory data, an overall and systematical summarization of the trajectory comparison is given under the development and background of the big data research. With the problems of the big data application raised, the trajectory data need deeper research on the computation of the big data, the intelligence of the algorithms and the efficiency and the validity of the algorithm, etc.

To solve the construction of the evaluation index system of the employment quality of finance and economics college graduates, a new optimization method based on rough set theory for the evaluation index of Employment quality is proposed. Fourteen evaluation indexes are first established, the employment information of Jilin University of finance and economics graduates from 2012 to 2015 is taken as a sample data and the quantitative statistics is used to determine the weight of the indexes preliminary. The evaluation objects are evaluated and classified. The rough set theory is used to simplify the evaluation indexes, eliminate those do not affect the classification. The index system is reduced to 6 indexes from the original 14 indexes, and the weight of each index is re-determined. Finally the optimized evaluation index system of the finance and economics college graduates’employment quality is obtained. Using the optimized index system can reduce the workload of statistics and evaluation. This method provides a new direction and means for the construction and optimization of the evaluation index system of the employment quality of finance and economics college graduates.

in order to solve the problem of clustering center improper selection in the traditional K-means algorithm which leads to the clustering result into local optimum, the initial clustering center of K-means algorithm is searched by the bat algorithm. The simulated annealing and the niche technology based on crowding out is added into the bat algorithm, in order to overcome some problems such as slow-speed convergence in later and weak search capability, its validity is verified by test functions. Finally the initial clustering center of K-means algorithm is optimized by the improved bat algorithm. The improved algorithm is compared to the traditional K-means algorithm, and the experimental results show that the improved algorithm of clustering performance has improved greater than the traditional K-means algorithm.