Advanced Materials Research Vols. 998-999

Abstract: In this paper, the local fractional Hilbert transform in fractal space is established. The characteristics of this local fractional transform are discussed in the following. Considering the basic properties of the local fractional Hilbert transforms, a kind of transform for local fractional is derived and analyzed.

Abstract: The solution of 2D parabolic equations based on the alternating direction implicit scheme is one of the important methods to solve high dimension problems.A alternating direction implicit scheme is presented in this paper, the stability and convergence of the alternating direction implicit scheme is to be proved, and the scheme of the errors are analyzed. Through the numerical experiment, the result shows that the method has good stability and high precision.

Abstract: The paper mainly research incremental sub-gradient method for the non-differentiable optimal problem in Hilbert space. And prove two conclusions about the sequence generated by this method.

Abstract: The rapid development and image processing technique to the computer is updated day by day, which lead the decorating pattern design to extend into the computer aided design from the original manual drawing.Decorative pattern is more huge miscellaneous from the contents with changeful graphics form, In this kind of advanced tool, with the help of computer of decorative pattern from figure element content changes to the graphics can carry on a processing and save in the form of digital data, can also make use of the computer to carry on the conventional image to it what processing technique falls through processing,thus form decorate pattern special manifestation and characteristics of the new era.

Abstract: Remote sensing image radiation correction is a key technique for quantitative remote sensing data processing is essential, especially in the surface undulating mountains, surface radiation affected by topography, the radiation correction of remote sensing inversion error can reduce the surface information, so as to maximize the accuracy of remote sensing investigation of mountain area. In this paper, the ETM image in mountain area of Western Beijing as an example, application of cosine correction model and Sandmeier correction model of image are topographic radiation correction, and then proposed an improved Sandmeier correction model, and carries on the precision analysis from the visual effect and quantitative parameters. Experiments show that, the improved Sandmeier correction model eliminates the influence of topography, greatly improving the accuracy of remote sensing image Topographic Radiation correction.

Abstract: Recent approaches for reconstructing 3D scenes from image collections only produce single scene models. To build a unified scene model that contains multiple subsets, we present a novel method for registration of 3D scene reconstructions in different scales. It first normalizes the scales of the models building on similarity reconstruction by the constraint of the 3D position of shared cameras. Then we use Cayley transform to fit the matrix of coordinates transformation for the models in normalization scales. The experimental results show the effectiveness and scalability of the proposed approach.

Abstract: The number of biomedical literatures is growing rapidly, and biomedical literature mining is becoming essential. A learning classifier based on maximum entropy (ME) for identifying abbreviations is proposed. Two innovative Web-based features for extracting additional semantic information are developed. The study shows the Web as a knowledge source can be incorporated effectively in the machine learning framework and significantly improves its performance. The ME classifier achieves 95% precision and 89% recall on the gold standard corpus “Medstract” and 91% precision and 84% recall on the larger test data that includes 128 full text literatures.

Abstract: Scene recognition is an important task for many computer vision and robotics applications. Recent progress in high-level object-based image representation has shown superior performance on scene classification tasks. In this work, we make an observation that groups of objects tend to co-occur frequently in a scene. We therefore propose to a novel framework that automatically learns object groups, and use them to build an image representation for scene recognition tasks. We model each object group as a template that explicitly encodes the spatial configurations of objects. To encourage the informativeness and discriminability, we learn the object group templates in a sparse filtering framework. Experiment results show that our object group representation could achieve state-of-the-art performance for both scene discovery and scene classification tasks.

Abstract: Diagnosis of engine fault is critical in reducing maintenance costs. A new method which incorporates hybrid relative vector machines and genetic algorithm (RVM-GA) was proposed to predict aero engine fault based on data of the spectrometric oil analysis. Experimental results show that it has a high accuracy and effective properties.

Abstract: Astronauts will suffer the orientation transformation problem without external force condition in spaceflight mission. Based on the establishment of human body system dynamics equation, the recommended control methods are put forward to guide the astronauts to make their orientation changed. The movement process is simulated through use of ADAMS to confirm the feasibility of method. Finally, simulated weightlessness environment is developed to demonstrate the advantages of the recommended control method compared with other control methods. The results show that using the control methods developed in this paper will make astronauts spend less time and smaller joint torques in performing body rotation about single axis in simulated weightlessness. There has certain reference significance for astronauts to conduct orientation transformation in spaceflight.