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Trajectory prediction is a prerequisite for missile and high-speed vehicle guidance interception. To address the trajectory problem for the near space hypersonic unpowered gliding vehicle. Firstly, the trajectory prediction mechanism is analyzed. Based on the existing NSHV trajectory prediction method, the key techniques of trajectory prediction are discussed from the perspectives of prediction parameter selection and prediction parameter description. Then, a trajectory prediction method based on Hough transform is proposed. The core of the method is to select the longitude latitude, and high direction positions as prediction parameters, and use the Hough transform to fit the prior basis functions. In the latitude and longitude direction, the rationality of predicting parameters is discussed from two aspects:position extreme point and lateral maneuverability. In the height direction, for the NSHV oscillation drop characteristic, two Hough transforms are used to separate the periodic term from the linear term. In addition, we give the approximate interval of the parameter values of the method, and design a parameter adaptive scheme. Finally, trajectory prediction is performed on two different control patterns. The error of the prediction time of 100s is within 25km, and the results show the effectiveness of the proposed method.

Aiming at the problem of gliding near space hypersonic vehicle (NSHV) trajectory prediction, a trajectory prediction method based on aerodynamic acceleration empirical mode decomposition (EMD) is proposed. The method analyzes the motion characteristics of the skipping gliding NSHV and verifies that the aerodynamic acceleration of the target has a relatively stable rule. On this basis, EMD is used to extract the trend of aerodynamic acceleration into multiple sub-items, and aggregate sub-items with similar attributes. Then, a prior basis function is set according to the aerodynamic acceleration stability rule, and the aggregated data are fitted by the basis function to predict its future state. After that, the prediction data of the aerodynamic acceleration are used to drive the system to predict the target trajectory. Finally, experiments verify the effectiveness of the method. In addition, the distribution of prediction errors in space is discussed, and the reasons are analyzed.

Objective: A meta-analysis of the screened data was performed to investigate the survival status of patients with second primary non-small cell lung cancer (SPNSCLC) after pulmonary lobectomy and partial pulmonary lobectomy, and assess the applicability of such option in the treatment of such disease. Methods: Based on the databases of PubMed, Ovid, and CNKI, relevant reports on postoperative survival of patients with SPNSCLC were obtained, and the information, including authors, publication year, research type, tumor staging, tumor diameter, surgical options, reasons for resection, and overall survival (OS), was extracted. The data were analyzed using Review Manager 5.3. Results: A total of 11 studies published from 2010 to 2017 were collected. Patients with SPNSCLC were mainly in stage Ia and Ib, 51.4% of whom underwent pulmonary lobectomy and 34.7% of whom underwent partial pulmonary lobectomy. The analysis results showed that after the second lobectomy, the mortality rate of the patients undergoing intensive surgery was 8%, the incidence of postoperative complications was 29%, and the 5-year OS rate was 53% after the second lobectomy for patients with SPNSCLC. Conclusion: The survival rate of patients with SPNSCLC is lower than that of patients with early lung cancer. In view of this, surgical resection is feasible. There are remarkable differences between pulmonary lobectomy and partial pulmonary lobectomy.

This paper studied on the clustering problem for intrusion detection with the theory of information entropy, it was put forward that the clustering problem for exact intrusion detection based on information entropy is NP-complete, therefore, the heuristic algorithm to solve the clustering problem for intrusion detection was designed, this algorithm has the characteristic of incremental development, it can deal with the database with large connection records from the internet.

The particle filter (PF) algorithm is one of the most commonly used algorithms for maneuvering target tracking. The traditional PF maps from multi-dimensional information to one-dimensional information during particle weight calculation, and the incorrect transmission of information leads to the fact that the particle prediction information does not match the weight information, and its essence is the reduction of the information entropy of the useful information. To solve this problem, a dual channel independent filtering method is proposed based on the idea of equalization mapping. Firstly, the particle prediction performance is described by particle manipulations of different dimensions, and the accuracy of particle prediction is improved. The improvement of particle degradation of this algorithm is analyzed in the aspects of particle weight and effective particle number. Secondly, according to the problem of lack of particle samples, the new particles are generated based on the filtering results, and the particle diversity is increased. Finally, the introduction of the graphics processing unit (GPU) parallel computing the platform, the “channel-level” and “particlelevel” parallel computing the program are designed to accelerate the algorithm. The simulation results show that the algorithm has the advantages of better filtering precision, higher particle efficiency and faster calculation speed compared with the traditional algorithm of the CPU platform.

Conventionally the international education circle for computer graphics education insists on that computer graphics is based on graphical standards for displaying graphics. This mainstream point of view entails quite a lot of difficulties in computer graphics education. To resolve these problems, this paper proposes a new method of teaching that the fundamental methodology for realizing 3D graphical displays is done by a combination of computer programming and computer simulation. The discipline connotation of computer graphics is distilled in three aspects of research area, methodology and theory architecture. The position and role of computer graphics is re-established in computer science. We expect the new paradigm could solve the problem in computer graphics education that puzzled the international computer graphics education world for so many years. At the same time, the connotation of computer education and the subject framework of computer science are distilled effectively.

The paper introduces a new simulation system for training EWA Combat Service Personnel ???EWACSP???, which uses data mining technology on the massive accumulation training information for knowledge discovery. In the system, the model of cluster analysis is established. Using this model, the system provides a higher level training program and arranges much more reasonable training for each Combat Service Personnel.

The paper introduces a new simulation system for training early warning air roster, which uses data mining technology on the massive accumulation training information for intelligence analysis. In the system, the model of association rules are established. Using this model, the system provide ability that arrange much more reasonable training plan for each early warning air roster. Furthermore, it can support an optimized decision of how to make up the team of rosters.

For solving information fusion problem of inequality important information in integrated target recognition the concept of evidence weight is introduced based on D-S reasoning. For transformation of each evidence according to its weight difference the evidence synthesis is completed using tradition method in integrated target recognition of different grade using this method the problem of target recognition of only same grade sensor using tradition evidence theory can be solved. An identification example using this method indicates that the precision and effectiveness of target recognition are raised.

In order to solve the problem of the blind region for radar netting in jamming, based on the analysis of anti-jamming capability; this paper uses the highly mobile radar to compensate the blind region to upgrade the anti-jamming capability holistically. It defines the conception of the blind compensation gain, constructs the decision-making model and designs the genetic algorithm. The result of simulation indicates the model is effective. The model provides the decision-making evidence for mobile blind compensation and lays a foundation for reserve and application of highly mobile radars.