In terms of the prokaryotic expression system Escherichia coli, it is well-known that incubation temperature, OD₆₀₀ value, isopropyl thiogalactoside concentration and time of induction are general factors which can directly affect the final protein's expression. The traditional method for this optimization is to study these factors which may influence the protein expression separately, thus, the interactions between factors are ignored. Design of experiment is a time-saving and cost-effective methodology for increasing the productivity and improving the quality of a product. In order to verify if design of experiment is suitable for the optimization of a protein expression and also to reveal if there is any interaction between the factors that have a significant influence on the protein's expression, the optimization of expression for the protein Bmlebocin3 was carried out using the design of experiment concept. Bmlebocin3 is an antimicrobial peptide in the silkworm, Bombyx mori. It has a unique precursor form which was suitable for this investigation. In this study, the Bmlebocin3 gene was cloned and expressed in Escherichia coli, and then this expression was optimized by design of experiment. The results revealed that through the use of design of experiment, in addition to quantifying the separate effects of the OD₆₀₀ value and the time of induction, it demonstrated that, their interaction can significantly affect the expression of Bmlebocin3. Furthermore, the best condition for the Bmlebocin3 's expression was identified through fewer experiments. This proved that design of experiment can be used as an efficient way to optimize the protein expression.

Evaporative resistance is an important parameter of clothing in its thermal comfort. The sweating thermal manikin developed for evaporative resistance test needs a textile skin covering its surface to simulate sweating. To investigate the effect of skin material on the measurement, three knitted fabrics (cotton, blend of cotton and polyester, polyester) were made into skins for the sweating thermal manikin Newton. The evaporative resistances of boundary air layer and four clothing ensembles were measured under an isothermal condition. It was found that the evaporative resistances measured with cotton skin were smaller than those measured with the other two skins. The large evaporative area and strong water absorbing ability of thick, dense and hydrophilic cotton skin result in more evaporative heat loss and consequently lower evaporative resistance values.

A new algorithm based on optimal Gabor filter and the basic Golden Image Subtraction (GIS) is presented for patterned fabric defect detection. Firstly, the defect-free patterned fabric images are processed to search optimal real Gabor filter parameters using traditional Genetic Algorithm (GA). Then test patterned fabric images are filtered according to the obtained optimal real Gabor filter. Furthermore, the basic GIS are adopted to perform subtractions between golden images from referenced fabric images and test images to get resultant images. Finally, thresholding is obtained by training a large amount of defect-free patterned fabric samples to segment defects from fabric background. Experiment results indicate that the average detection success rate is up to 96.31\% with ninety defective patterned images and ninety defect-free patterned images. It demonstrates that the proposed method is more efficient.

Traditionally dyed fabric color difference detection is based on the image color characteristics in textile industry. However, relying solely on the single image color features can't effectively identify dyed fabric color difference with rich texture characteristics. In order to solve this problem, a new efficient color difference detection method based on multi-dimensional characteristics of Morlet Wavelet Kernel Support Vector Machine (MWSVM) is proposed in this paper. Firstly the dyed fabric image to be detected is divided into some appropriate sub-blocks in the LAB color space. The LAB histograms of the image in those sub-blocks are extracted. In addition, the Local Binary Pattern (LBP) algorithm is applied to extract the image texture features in those different divided regions. Then the Grey Relational Grade (GRG) between the sample image and the detected image is calculated. Finally the LAB histograms, the LBP features and the GRG are used as the input image data for the MWSVM algorithm to detect color difference of dyed fabrics. The experimental results show that the proposed method can detect dyed fabric color difference more efficiently and accurately. The classification accuracy rate as high as 87.5\%.

Articulated pose estimation with mixtures-of-parts decomposes human body into several local component templates with springs connecting each other. Such a method fails in precisely estimating human pose especially due to the defects of tree models when human has the complicated pose of body. To address this problem, we propose pose estimation using local adjustment with mixtures-of-parts models. We can achieve the most suitable pose of body by the blending and selecting strategy based on the full score and the corresponding attributes of limbs and body. The experiments show that the estimation effect of human pose of our method is better than the previous method based on articulated pose estimation with mixtures-of-parts.

In order to inspect woven fabric density automatically, a method combining image processing and multi-scale wavelet transform is proposed in this paper. Firstly, fabric images are pre-processed by Bimodal Gaussian function histogram equalization to obtain more structure information. Secondly, fabric images are decomposed into horizontal and vertical sub-images by using wavelet filter. Thirdly, texture features are extracted from the sub-images through binarization and smooth processing. Finally, density of yarns is acquired accurately after analyzing features of warps and wefts of the fabric. The experiment results prove that the proposed algorithm is perfectly suitable for three principle weaves and the relative error of automatic inspection compared with manual inspection is less than 0.86\%.

The main content dealt with in the paper is to analyze effects of structural parameters on compression property of spacer fabrics. Based on compression stress and strain curves, four characteristic indices are featured, which include compression work, recovery ratio of compression work, maximum compression force when compression strain is 0.7 and secant modulus by fitting compression stress -- strain curve from strain 0 to 0.25. Experimental results show that structural parameters of spacer fabric, including thickness of spacer fabric and diameter, angle, arrangement shape and density of spacer filament, significantly influence compression behaviour. With the thickness of specimen increasing, compression work increased, while the compression secant modulus and maximum force decreased, and the recovery existed nonlinear relationship and showed a relatively optimal thickness. Compression work, recovery ratio, maximum force and secant modulus existed the same ascending trend when the diameter of spacer filament increased from, while they showed descending trend when spacer angles decreased. The whole structure of spacer fabric was more stable when the arrangement of spacer filament is X-shaped than V-shaped, and the compression work, recovery ratio, maximum force and secant modulus of sample X shape were all larger than those of sample V shape. As for the density of spacer filaments, the compression work, maximum force and secant modulus increased with density decreased, while the recovery ratio of spacer fabric with higher density was smaller than that of smaller density.

Ultrasound image segmentation is an important task for clinical diagnosis. In this study, a multi-threshhold segmentation approach was proposed to enhance ultrasound image segmentation accuracy. More specifically, the proposed multi-threshhold segmentation approach, combining an opening-closing morphological filter and potential function clustering theory, attempted to provide better ultrasound image segmentation visibility. This proposed approach was tested using computer-simulated images and in $\textit{vivo}$ images. Computer simulation results demonstrated that the method significantly improved the accuracy of image segmentation. From in $\textit{vivo}$ images investigation, we have found that, as compared with the original images, better segmentation visibility were obtained. Our initial results demonstrated that this method could be useful for improving the segmentation quality of ultrasound images as a post-processing tool.

The problems of reliability, stability and kinematics accuracy of domestic high-speed rapier loom are urgent to be solved. For the limitations of used methods of solving kinematics accuracy reliability, the mathematical solution model and index of kinematics accuracy reliability of beating-up mechanism were established based on the geometrical principle of reliability index. The particle swarm optimization was improved. Then using improved particle swarm optimization, the kinematics accuracy reliability of beating-up mechanism of high-speed rapier loom was optimized. The computational precision and effectiveness of solving are both improved. Thus a new valid method is provided for the solution of kinematics accuracy reliability of beating-up mechanism of high-speed rapier loom.

The quality of iris image is one of the key factors influences the performance of iris pattern recognition. Based on the existing quality assessment measures of iris image, and in consideration of the most prominent factors that lead recognition to fail, we firstly put forward iris rotation which is a new quality assessment measure. Then Iris Rotation, Iris Visibility, Iris Eccentricity and Iris Definition are together as quality assessment measures of iris image and the quality assessment of iris image is done by Support Vector Machine (SVM) classifier. The experiment results express that the method we propose can select the images with good quality and has strong predictability for the performance of iris pattern recognition.

This paper proposes a new scheme of interpolation subdivision curve and surface using Bezier curve to achieve more realistic surface design. Different from the previous interpolation subdivision schemes, the normal vectors are used to generate a circle from a triangle which results in only three vertices and three edges. This improvement not only makes a curve smooth, but also produces sharp angles during subdivision. Examples of subdivision surface by this scheme are illustrated and compared to show the advantages of this scheme.

To predict textile quality fluctuation from the perspective of uncertainty factors, first, the reasons and patterns of quality fluctuation in the industrial textile processing were analyzed, and knowledge representation of textile quality attributes was studied. Second, through the theories of human-machine-environment-system-engineering (HMESE), probability, and statistics, the uncertainty factors that affect textile production quality were extracted, and generation mechanism, interaction relationship and\linebreak behavioral characteristics of them was explored. Then, an improved human-machine-environment brittle model oriented to the textile processing was built. As verified by the experiment and simulation, the results have shown that the improved brittle model has achieved a full range analysis of quality uncertainty of the textile, which are from the reason and pattern of quality fluctuation to generation mechanism, mutual relations, and behavior identification of the uncertainty factors.

An environmental-friendly electroless copper plating process was employed in preparing copper-coated polyester fabric with excellent conductivity. The effects of bath temperature on the plating rate, compositions and crystal structure of the electroless copper deposits were studied. The results showed the deposition rate increased with the rise of the bath temperature. X-ray Diffraction (XRD) scan indicated that the copper coating deposited was well crystallized and Scanning Electron Microscopy (SEM) scan showed copper coating had good surface morphology. Surface resistance of copper plated polyester fabric was evaluated. The surface resistance was 16.5 m$\Omega$/sq as the temperatue was 65 $^{\circ}$C.

X-Ray Image Intensifier (XRII) suffers from serve distortion in C-arm CT imaging system. To overcome the challenging problem, this paper proposes a novel XRII correction based on the Biharmonic Spline Surface Interpolation (BSSI) framework. In our study, two functions \(X_2=$$f(X_1, Y_1)\) and \(Y_2=$$f(X_1, Y_1)\) are first developed to map the relation between pixels positions in the distorted XRII image and reference image. A bilinear interpolation can then be applied to estimate the corrected pixel intensities to achieve the final image. The proposed approach can well overcome the discontinuities problems in local algorithms and achieve improved accuracy in distortion correction. Experiment results demonstrate that the proposed algorithm is capable of providing XRII images with higher correction precision than classical algorithms.

This paper addresses the technical issues related to hand gestures generation and their real-time\linebreak recognition. The arbitrary 3D gestures are generated by the Leap-motion Controller which detects and tracks the hands and fingers to acquire position and motion information. We combine Leap-motion sensor and hardware based pattern engine to make gesture recognition easier and propose an efficient recognition solution involving a neuron chip (named CM1K). In our experiment, we used one-finger gesture cases to demonstrate the efficiency of our solution. Experimental results showed that our solution owns a high accuracy in gesture data acquiring and only costs a few milliseconds in recognizing speed. We also considered the situation of similar gestures recognition and analyzed the causes of low matching rate from specific data.

A B-spline Quasi-interpolation Empirical Mode Decomposition (BSQI-EMD) method is presented and applied to similarity analysis of DNA sequences. The B-spline quasi-interpolation is used to approximate the extrema envelopes during the Intrinsic Mode Function (IMF) sifting process. The BSQI-EMD method is simple, easy to implement, and does not require solving any linear system of equations. Then we implement the classic EMD method and our method respectively. This work verifies our method's suitability and better performance for similarity/dissimilarity analysis among the coding sequences of the first exon of $\beta$-globin gene of ten different species.

For the blood cell signal has the characteristics of nonlinear, non-stationary and M-morphous, an intelligent algorithm for blood cell recognition based on Hilbert-Huang Transformation and BP Neural Network (HHT-BPNN) is put forward, which convert the time domain features of the blood cell signal into energy features by combining empirical mode decomposition with Hilbert transform, and put the time domain features and the energy features together as the feature vector. Then, a model based on BP neural network is built by trainning and simulating that complete the work of effective identification and accurate count for M-morphous blood cells. Simulation results show that the algorithm proposed has high recognition accuracy with good recognition performance.

To improve robustness of Linear Regression (LR) for face recognition, a novel face recognition framework based on modular two-dimensional Principal Component Regression (2DPCR) is proposed in this paper. Firstly, all face images are partitioned into several blocks and the approach performs 2DPCA process to project the blocks onto the face spaces. Then, LR is used to obtain the residuals of every block by representing a test image as a linear combination of class-specific galleries. Lastly, three minimum residuals of every block and fuzzy similarity preferred ratio decision method are applied to make a classification. The proposed framework outperforms the state-of-the-art methods and demonstrates strong robustness under various illumination, pose and occlusion conditions on several face databases.

This paper introduces a method of lane detection based on recursive binary fitting method of the lane detection: First use canny edge detection algorithm to detect the edges on the basis of gray images, and then scan the edge image from the left to the right and from the bottom to the top, we can extract the inner side of the lane edge of the interested region and dilate the lane by connecting some breakup, and on this basis and through the connected domain filtering, to remove the one that does not conform to the characteristics of binary image of lane. At last, we can get the lane by the recursive binary fitting method. The results show that the algorithm has good robustness and real-time performance.

In order to improve the security of secret image transmission, using the property of the chaotic sequence in the encryption algorithm, a block image encryption scheme based on Logistic and Henon composite chaotic system is presented. The image encryption algorithm from two aspects that the pixel grayscale value and pixel position through two different chaotic sequences transform of the Logistic and Henon. At first, Logistic chaotic sequence is applied to the scrambling operation on the pixel position matrix. Then the pixel values of blocked images are scrambled based on Henon chaotic sequence. The experiments show that the algorithm has good encryption effect, and has better robustness to crop or noise attack. The cross correlation of encrypted image are decreased and the transport security is improved, the result shows that the project is effective.

Heart Rate Variability (HRV) analysis is based on variability between each heartbeat which is used as a diagnosis method for assessing the cardiovascular modulation of autonomic nerve system. Up to now, most HRV analysis has been done offline. However, in many relevant applications, HRV should be analyzed online such as the analysis of stress level and the detection of the drowsiness while driving. This paper proposes an online analysis method which can be used in platforms for human robot cooperation. This online analysis method based on a sliding Hurst window can be applied to estimate the heart status. By the sliding Hurst series, the two indices, cumulative mean of Hurst series (CMHurst) and cumulative standard deviation of Hurst series (CStdHurst) are introduced as indicators to distinguish heart health status. Using this method, the hardware requirement is significantly low, and the execution time is short. Some databases from the PhysioBank are used for test these indices. The results show this method can distinguish between the groups who have normal rhythm and abnormal rhythm.