Prediction of protein folding rates from primary sequence by fusing multiple sequential features

We have developed a web-server for predicting the folding rate of a protein based on its amino acid sequence information alone. The web- server is called Pred-PFR (Predicting Protein Folding Rate). Pred-PFR is featured by fusing multiple individual predictors, each of which is established based on one special feature derived from the protein sequence. The ensemble pre-dictor thus formed is superior to the individual ones, as demonstrated by achieving higher correlation coefficient and lower root mean square deviation between the predicted and observed results when examined by the jack-knife cross-validation on a benchmark dataset constructed recently. As a user-friendly web- server, Pred-PFR is freely accessible to the public at www.csbio.sjtu.edu.cn/bioinf/Folding Rate/.

A two-step rectification algorithm for airborne linear images with POS data

Rectification for airborne linear images is an indispensable preprocessing step. This paper presents in detail a two-step rectification algorithm. The first step is to establish the model of direct georeference position using the data provided by the Po- sitioning and Orientation System (POS) and obtain the mathematical relationships between the image points and ground reference points. The second step is to apply polynomial distortion model and Bilinear Interpolation to get the final precise rectified images. In this step, a reference image is required and some ground control points (GCPs) are selected. Experiments showed that the final rectified images are satisfactory, and that our two-step rectification algorithm is very effective.

Hardware Implementation and System Control Strategy of Videoconference System Based on Rec. H. 261

The design and realization of a videoconference system based on international recommendation are introduced in this paper, and the hardware implementation of video codec based on ITU-T H. 261 is briefly discussed. Furthermore, the buffer control method and the adaptive control strategy for quantization are proposed, which are adaptive and robust. This system can be operated under the transmission rate ranging from 128kb/s to 2Mb/s. With these strategies for the videoconference system, the high quality image is obtained. The time delay of the system is about half a second.

Edge location in the automatic track system of NGW with small slope angle

Based on the analysis of the groove images in gas metal arc welding with small slope angle, a new algorithm of the groove edge location is presented. The groove edge was effectively detected by combining Roberts Detector with the general non linear gradient operator. In addition, using Norton Quadratic Polynomial Interpolation, the edge location precision reached sub pixel level. The experimental results show that the edge detection system works well under the condition of short transfer arc welding.

CMAC Based Color Separation in Printing Images

To over come the drawbacks existing in current measurement methods for detecting and controlling colors in printing process, a new medal for color separation and dot recognition is proposed from a view of digital image processing and patter recognition. In this model, firstly data samples are collected from some color patches by the Fuzzy C-Means （FCM） method; then a classifier based on the Cerebellar Model Articulation Controller （CMAC） is constructed which is used to recognize color pattern of each pixel in a microscopic halftone image. The principle of color separation and the algorithm model are introduced and the experiments show the effectiveness of the CMAC-based classifier as opposed to the BP network.

A New Approach for Lossless Image Compression Based on Fuzzy Adaptive Prediction

This paper proposes a novel approach for image lossless compression based on fuzzy logic and adaptive prediction. By a flexible strategy, the method can acquire a set of original predictors describing the more detail characteristic. Using a neural network, the proposed method can more efficiently organize the training of original predictors and implement adaptive prediction in fuzzy style. In entropy coding phase, the context-based conditional adaptive arithmetic encoding is adopted. The experiments demonstrate the characteristics make the approach achieve good tradeoff between computational complexity and efficiency of prediction and good performance for lossless compression.

Microscopic Halftone Image Segmentation

Microscopic halftone image recognition and analysis can provide quantitative evidence for printing quality control and fault diagnosis of printing devices, while halftone image segmentation is one of the significant steps during the procedure. Automatic segmentation on microscopic dots by the aid of the Fuzzy C-Means (FCM) method that takes account of the fuzziness of halftone image and utilizes its color information adequately is realized. Then some examples show the technique effective and simple with better performance of noise immunity than some usual methods. In addition, the segmentation results obtained by the FCM in different color spaces are compared, which indicates that the method using the FCM in the f 1f 2f 3 color space is superior to the rest.

机器人手眼标定的仿真分析(英文)

研究了一种新的机器人手眼标定的方法。在实际中,手-双目系统有着广泛的应用。传统方法主要集中在手-单目系统中。直接将传统方法应用到手-双目系统中将会很容易受到噪声的干扰。与传统方法相比,文章充分利用了双目摄像机之间以及摄像机与机器人手爪之间的约束关系进行机器人手眼标定,大大提高了抗干扰的能力。最后仿真结果证明了新方法的精确性与有效性。

Blind source separation based on generalized gaussian model

Since in most blind source separation(BSS)algorithms the estimations of probability density function(pdf)of sources are fixed or can only switch between one sup-Gaussian and other sub-Gaussian model,they may not be efficient to separate sources with different distributions.So to solve the problem of pdf mismatch and the separation of hybrid mixture in BSS,the generalized Gaussian model(GGM)is introduced to model the pdf of the sources since it can provide a general structure of univariate distributions.Its great advantage is that only one parameter needs to be determined in modeling the pdf of different sources,so it is less complex than Gaussian mixture model.By using maximum likelihood(ML)approach,the convergence of the proposed algorithm is improved.The computer simulations show that it is more efficient and valid than conventional methods with fixed pdf estimation.

A bidirectional feature selection method based on mutual information and redundancy-synergy coefficient

Feature subset selection is a fundamental problem of data mining. The mutual information of feature subset is a measure for feature subset containing class feature information. A hashing mechanism is proposed to calculate the mutual information of feature subset. The feature relevancy is defined by mutual information. Redundancy-synergy coefficient, a novel redundancy and synergy measure for features to describe the class feature, is defined. In terms of information maximization rule, a bidirectional heuristic feature subset selection method based on mutual information and redundancy-synergy coefficient is presented. This study’s experiments show the good performance of the new method.

A Hybrid Motion Compensation De-interlacing Approach

Motion compensation de interlacing is expected to be better than linear techniques; but all the block based motion compensation de interlacing methods cause block artifacts. The algorithm proposed in this paper is concerned with reducing the deficiency of motion compensated interpolation by using adaptive hybrid de interlacing methods. A spatio temporal tensor based approach is used to get more accurate motion field for de interlacing. Motion vector is assigned for each position with pixel precision; the block artifact is reduced significantly. To deal with the artifacts introduced by motion compensation when the motion estimation is incorrect, linear techniques are considered by adaptive weighting. Furthermore, directional filter is adapted to preserve details and the edge discontinuity could be eliminated greatly. Our approach is robust to incorrect motion vector estimation.

Humanoid Robot 3-D Motion Simulation for Hardware Realization

In this paper,three dimensions kinematics and kinetics simulation are discussed for hardware realization of a physical biped walking-chair robot.The direct and inverse close-form kinematics solution of the biped walking-chair robot is deduced.Several gaits are realized with the kinematics solution,including walking straight on level floor,going up stair,squatting down and standing up.Zero Moment Point(ZMP)equation is analyzed considering the movement of the crew.The simulated biped walking-chair robot is used for mechanical design,gaits development and validation before they are tested on real robot.

High-quality multi-resolution volume rendering in medicine

In order to perform a high-quality interactive rendering of large medical data sets on a single off-the-shelf PC, a LOD selection algorithm for multi-resolution volume rendering using 3D texture mapping is presented, which uses an adaptive scheme that renders the volume in a region-of-interest at a high resolution and the volume away from this region at lower resolutions. The algorithm is based on several important criteria, and rendering is done adaptively by selecting high-resolution cells close to a center of attention and low-resolution cells away from this area. In addition, our hierarchical level-of-detail representation guarantees consistent interpolation between different resolution levels. Experiments have been applied to a number of large medical data and have produced high quality images at interactive frame rates using standard PC hardware.

Robust Watermarking Scheme with Side Information and Template Matching Mechanism

Digital watermarking has been proposed for the copyright protections of multimedia products. In this paper, a robust and blind watermarking scheme is presented. The concept of communication with side information is applied at the encoder to improve the probability of detection within acceptable fidelity, while the template matching technique is employed to estimate the undergone attacks in attacking channel. This scheme is optimized by the optimal design of the encoder to match with the media content and the decoder to adapt to the attack channel state. Experiments show that our method is robust against some common attacks such as filtering, compression, rotation, scaling, cropping and translation. It can be applied to both color and gray images.

Face recognition using improved-LDA with facial combined feature

Pace recognition subjected to various conditions is a challenging task. This paper presents a combined feature improved Fisher classifier method for face recognition. Both of the facial holistic information and local information are used for face representation. In addition, the improved linear discriminant analysis (I-LDA) is employed for good generalization capability. Experiments show that the method is not only robust to moderate changes of illumination, pose and facial expression but also superior to the traditional methods, such as eigenfaces and Fisherfaces.

Elliptical Splats Based Isosurface Visualization for Volume Data

Elliptical splats are used to represent and render the isosurface of volume data. The method consists of two steps. The first step is to extract points on the isosurface by looking up the case table. In the second step, properties of splats are computed based on local geometry. Rendering is achieved using surface splatting algorithm. The obtained results show that the extraction time of isosurfaces can be reduced by a factor of three. So our approach is more appropriate for interactive visualization of large medical data than the classical marching cubes (MC) technique.