Applied Mechanics and Materials Vols. 241-244

Abstract: Automatic on-line signature verification is an intriguing intellectual challenge with wide attention and practical applications. We examined the validation of the new dynamic features for on-line signature verification, which extracted from 3-axis forces of pen-tip to writing tablet with application of discrete wavelet transform (DWT). The force signals were decomposed into sub-band signals by DWT and individual features were extracted as locations of modulus maximum in detail and the values of the wavelet transform at the corresponding location. Verification was achieved by using dynamic time warping (DTW) and total decision was done by combining multiple thresholds. Experimental results indicate the effectiveness of the dynamic features for on-line signature verification described in this paper.

Abstract: Informal learning is an important learning form in today’s knowledge society. This article introduced the concept of Digital Bloom, and discussed its great guiding significance for informal learning, then proposed an informal learning environment model based on the research of Digital Bloom, and illustrated the model detailedly from its composition, the learning model and the support system so as to provide some reference for improving informal learning quality.

Abstract: At present, our analysis of the aviation accident mainly limited to the methods of mathematical statistics, the analysis method means of a single, and in a passive state, so the accident prediction is poor. This paper, basis on the rough set theory in data mining and preferential information ,we improve the rough set attribute reduction algorithm, and applied to civil aviation accident analysis to indentify the potential law of accident.

Abstract: A modified Elman neural network model for the network system is proposed which is nonlinear, multivariable and time-varying. The learning method based on seasonal periodicity is introduced into the model training. And the output traffic of the backbone network at a certain university is selected for the test. Experimental results show this model has better accuracy of prediction. Compared with traditional linear model, BP neural network model and normal Elman neural network model, it has higher accuracy and better adaptability. Finally, abnormal behavior of network traffic can be found on time through the test of adaptive boundary value. And it shows that the model is feasible and effective.

Abstract: Real time 3D medical image registration method is key technology of medical image processing, especially in surgical operation navigation. However, current 3D medical image registration methods are time-consuming, which can’t meet the real time requirement of clinical application. To solve this problem, this paper presented a high performance computational method based on CUDA ( Compute Unified Device Architecture), which took full advantage of GPU parallel computing under CUDA architecture combined with image multiple scale and maximum mutual information to make fast registration of three dimensional medical image. Experiments showed that this algorithm can greatly accelerate the computational speed of registration of three dimensional medical image, and meet the real time requirement of clinical application.

Abstract: A new algorithm is proposed to adjust backlight luminance for local dimming of liquid crystal display (LCD) devices. PSNR (the peak signal-to-noise ratio) =30 is acted as the lowest standard to guarantee the quality of image in the algorithm. Based on the formula of PSNR=30, the square error value of the image distortion is gained. Then, luminance of backlight is gained dynamically by that the maximum gray level minus 1 into the formula proposed in the paper and decreases by one after each trial if the image quality requirement is not satisfied. In order to simplify the calculation, three important gray level values are selected to meet the requirements. The results show that the algorithm can greatly reduce the power consumption with guaranteeing the image quality and furthermore save much time in calculation and be better applied in hardware.

Abstract: Considerable attention has been devoted to prove the correctness of programs. Formal verification overcomes the incompleteness by applying mathematical methods to verify a design. SpaceWire is a well known communication standard. For safety-critical applications an approach is needed to validate the completeness of SpareWire design. This paper addresses formal verification of SpareWire error detection module. The system model was constructed by Kripke structure, and the properties were presented by linear temporal logic (LTL). Compared the verification of LTL with CTL (branch temporal logic), LTL properties could improve the verification efficiency due to its linear search. The error priority was checked using simulation guided by model checking. After some properties were modified, all possible behaviors of the module satisfied the specification. This method realizes complete validation of the error detection module.

Abstract: Most of the watermarking techniques based on DWT technique embed watermarks into the detail (or middle frequency) coefficients of the host image for a good-trade-off between robustness and fidelity. But, in order to obtain the most robustness, the DC area (LL sub-band) may be a most suitable region for watermark embedding, as the signal energy of DC components is much bigger than that of high frequency sub-bands. A blind novel watermarking algorithm based on fast lifting wavelet transform, a kind of second generation wavelet transform, is proposed. Firstly, a multi-level discrete lifting wavelet transform is employed, and then the watermark is embedded into DC area of last level lifting wavelet transform according to amplitude modulation method with a secret key, lastly a watermarked image is obtained after lifting wavelet reconstruction to be applied. The results of experiments show that this algorithm is still effective after applying high compression ratio JPEG.

Abstract: Values of surface roughness are usually unstable with conventional measurement methods because of the affection of measurement resolution and signal sampling, in order to make the measurement results reflect the practical engineering surface accurately, a new method of measuring surface roughness based on microscopic images and fractal theory is proposed. The microscopic images are acquired and pretreated, the structure function method is used to calculate the fractal dimension and fractal proportion coefficient, experiment results show that the fractal dimensions of tested samples with same making method are equal basically, while the fractal proportion coefficients are changed with different surface roughness, the two parameters can express the surface state preferably.

Abstract: To solve the problem of long time consuming in the fractal encoding process, a fast fractal encoding algorithm based on RMSE (Root mean square error) and DCT (Discrete Cosine Transform) classification is proposed. During the encoding process, firstly, the image is divided into range blocks and domain blocks by quadtree partition according to RMSE, then, according to DCT coefficients of image block, three classes of image blocks are defined, which are smooth class, horizontal/vertical edge class, diagonal/sub-diagonal class. At last, every range block is limited to search the best matched block in the corresponding domain block class, and the fractal coding are recorded until the process is completed. When searching the best matched block, the nearest neighbor block will be found in the sense of RMSE in the ordered codebook, and the best matched block will be further found in the vicinity of the nearest neighbor block. The experimental results show that the proposed algorithm can efficiently reduce the search space and shorten the encoding time, while achieving the same reconstructed image quality as that of the full search method.