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The characteristics clustering of electric loads are of great importance to the Measurement-Based Modeling method. In this paper, a new method based on Kohonen self-organization neural network is presented for the characteristics clustering of dynamic loads. At first, the model of every group of load disturbance data is established, and then the responses of the load models to the same voltage excitation and the pre-disturbance active power of the loads are incorporated into the feature vectors. At last, Kohonen neural network is introduced to cluster. Many sets of load data measured from North China Power System in three years (1996–1998) have been dealt with using the method. The results show load characteristics have rule though they are random and time-varying. The feasibility of the Measurement-Based Modeling approach is also proved.

For realizing accurate reliability allocation of complex system, a method based on inverse thinking is proposed in this paper. The important of every sub-system is determined by analyzing the inter-relationship between the changing of sub-system reliability and system reliability. The accurate reliability allocation model of the complex system is established based on the neural networks. The self-restriction conditions of every sub-system and the system reliability are taken as the input variables of the model, the bio-mutual ratio of sub-system reliability is taken as the output variables of the model. The important of every sub-system in the prophase reliability experiment is learned by the trained neural networks. Then, a positive reciprocal matrix can be formed by the output variables of the model. The reliability allocation coefficients of every sub-system can be achieved by solving the positive reciprocal matrix, and the expected reliability of every sub-system can also be achieved by substituting the reliability allocation coefficients into the reliability allocation formula. It is proved by the examples that the result of the model is completely according with the reliability allocation rules; the artificial factors in reliability allocation are avoided.

This paper proposes an improved scheme of using the inter-cluster distance in the feature space to choose the kernel parameters. First, the candidate vectors of the training set are selected. Then calculate the inter-cluster distance between classes to choose the proper kernel parameters. Finally the selected kernel parameters are used to train the Support Vector Machine (SVM) models. The basic principle is that the Support Vector (SV) set contains all information necessary to solve a given classification task. Experiment results show that our scheme costs much less computation time. Moreover, suitable kernel parameters can also be selected at the same time.

The deficiencies of existing load models and their implementations in power system simulation programs are addressed in this paper. To improve the load model for power system simulation, a Synthesis Load Model (SLM) with distribution network, which is consistent with the structure of power loads and distribution networks, is presented. The SLM is reasonable in structure and convenient to use. The SLM can simulate the load components and distribution systems including distribution network, reactive compensation and the generators connected to low voltage networks. The validity of SLM has been validated by four field tests of three-phase short circuit in Northeast China Power Grid in the years of 2004 and 2005 respectively.

This paper presents a novel image watermarking scheme for both tamper detection and tampered image recovery. The basic principle of this scheme is to compress per block of the original image using SPIHT (Set Partitioning in Hierarchical Trees), then scramble and embed the bit stream into LSBs (Least Significant Bit) of corresponding offset block. Experimental results show that the proposed scheme can detect and locate tamper accurately, and recover tampered block data with satisfied image visual quality.

Efficient algorithms for compressing three-dimensional (3D) triangle meshes have been widely developed in recent years, but most of them are designed to deal with manifold meshes. A progressive geometry-driven 3D triangle meshes algorithm is proposed in this work which can be easily extended to non-manifold mesh compression and polygon mesh compression. Different from connectivity-driven algorithms; our method starts with the geometry; it encodes the geometry data into a symbol sequence consisting of only three kinds of symbols. Edge collapse and vertex unification operator are used to encode the connectivity, and the symbol sequences can be further encoded by arithmetic coding.

A distributed spiders antitype was designed by Web Service based on Service-Oriented Architecture(SOA).This antitype is made up of a server and several clients. The clients are controlled to download a new web page by the server according to the crawled pages. Moreover, they must manage the To Crawl , Crawled URL queues and Noise URL queue after analyzing it by multi-threads. Furthermore, they keep connection with the server to pass the unknown URL and domain names. The server is made up of the front platform and the background. The front platform controls the clients including the design of load balance policy and real-time monitoring of clients by Microsoft Message Queue(MSMQ). Web service is deployed on the server background which contains the structure of persistent data connection. With the help of this structure, the front platform and the clients can access data by the normative interface. Finally, a lot of experiments were done which show that the distributed spiders system has good robust performance.

GVF snake model means gradient vector flow snake model. It is a representative of the active contour model and it has been used to solve image segmentation for some conglutinated images. GVF snake model is also a new accurate arithmetic to obtain the boundary of the object edge especially for those stomach epidermis tumors which have several conglutinated areas. As the first step of this arithmetic, many pretreatment processes are necessary such as the gauss blur and the edge mapping to get the clearer image boundary before starting the image segmentation. The next step after pretreatment processes is calculating the GVF outside force field which makes the snake move quicker to the object boundary after the initial points been selected. The experiments also show that as the key parameter of GVF snake model, mu must be set below 0.3 in order to get better segmentation results, otherwise the snake cannot move closer to the object boundary because the GVF outside force field dies down.

This paper presents a method of features extraction in speaker recognition. This method divides voice signal into two parts based on the MPEG Psychological Model I, and processes them respectively. And then we analyze the extracted MFCC parameters, and compare the partition of frequency-band between Mel-spaced filter group and wavelet packet decomposition. We extract the coefficients by wavelet package transform (called ldquoWPTCrdquo) as diagnostic parameters used in the speaker recognition. The results of experiments indicated that it perform well than MFCC while using the WPTC based on MPEG-I.

Genome research promises to promote continued and enhanced plant genetic improvement. As a world's leading crop and a model system for studies of many biological processes, genomics research of cottons has advanced rapidly in the past few years. This article presents a comprehensive review on the recent advances of cotton genomics research. The reviewed areas include DNA markers, genetic maps, mapped genes and QTLs, ESTs, microarrays, gene expression profiling, BAC and BIBAC libraries, physical mapping, genome sequencing, and applications of genomic tools in cotton breeding. Analysis of the current status of each of the genome research areas suggests that the areas of physical mapping, QTL fine mapping, genome sequencing, nonfiber and nonovule EST development, gene expression profiling, and association studies between gene expression and fiber trait performance should be emphasized currently and in near future to accelerate utilization of the genomics research achievements for enhancing cotton genetic improvement.

A new manifold learning algorithm is proposed in this paper. Our method is motivated by the unit covariance constraint problem of spectral embedding methods, where a unit covariance constraint is imposed to avoid degenerate solutions that map all manifold samples to one point. This constraint distorts the aspect ratio and introduces unwanted correlation between different components of embedding coordinates. Instead, our method uses boundary conditions to pull apart mapped points, and obtains the embedding by solving linear systems under boundary conditions. The mapping of boundary samples is decided by that of a coarse version of manifold, obtained by a graph simplification algorithm designed by us. Comparisons between our method and several other representative manifold learning methods are made, and the results demonstrate the effectiveness of the proposed method.

Vortex structures in a mesoscopic a superconducting ring, which is in the magnetic field generated by a circular electric current, are investigated based on the phenomenological Ginzburg-Landau (G-L) theory. Due to the axial symmetry of the system, the three-dimensional problem is reduced to a two-dimensional problem. We can mesh a two-dimensional sample into grids, and discretize the first G-L equation by using the finite-difference method. Then the eigenvalues and eigenfunctions will be evaluated numerically by solving the discrete equations. With the eigenvalues and eigenfunctions we further obtain the minimum free energy of the system and the corresponding superconducting wave function. We discuss the influences of the ring size and magnetic field distribution on two kinds of the vortex structures: giant vortex state (GVS) and multivortex state (MVS). Calculations show: 1) the GVS with axial symmetric wave function exists only in a small size superconducting ring, as the GVS is a state of single vortex line that only goes through the hole at the center of the superconducting ring and carries several magnetic flux quanta with it; 2) with the increase of the ring size, the diamagnetism of superconducting ring becomes stronger, and the critical magnetic field value of a giant vortex state increases, and the maximal number of giant vortexes that the superconducting ring can accommodate is also growing; furthermore, the entrance of a flux line will cause fluctuations of critical field values; 3) when the superconducting ring size is large enough, a GVS splits into a number of MVS. The MVS is an excited state and the GVS is mostly a ground state; 4) the free energy of the system changes with the magnetic field distribution, the magnetic field provided by a central small current loop can pass through the superconducting ring easily, and produce multivortices whose formations are diverse; if the magnetic field runs parallel to the plane of the superconducting ring, it is difficult to pass through the superconducting ring and form multivortices; 5) the vortex lines are naturally bent with the magnetic field lines and can pass through the same horizontal plane twice, so that one of the two vortex states seems to be an antivortex state; generally, the magnetic field lines can go through the hole of a superconducting ring easily but can hardly penetrate through the body of a superconducting ring, the structure of multivortices is similar to that of the magnetic field distribution in a superconducting ring. We also obtain a vortex structure with coexistences of giant vortex and multivortices. This study is of significance for the application of superconducting nanomaterials.

A novel approach of blind steganalysis is proposed, which is based on image texture energy-entropy features. Image complexity describes the difference of image's content and texture. Steg-image's texture is ordinarily more complicated than that of cover image. For analyzing image complexity, using image texture features to measure the statistical differences between cover image and steg-image. In the paper, we analyze image complexity based on image texture segmentation technique, and use Laws' image texture energy-entropy features to measure the statistical differences between cover image and steg-image. Applying these texture features, blind steganalysis is implemented. Support Vector Machine (SVM) is used as classifier to distinguish whether a given image is embedded into the convert message. Experiment results show that the proposed approach is greatly valuable and our blind steganalysis method attains a good testing accurate rate.

IT plays a strategic role in modern organizations, and IT strategy works as a guideline for IT investment, IT project selection and implementation, IT management and IT service. The alignment of business strategy and IT strategy is even more important than IT strategy itself. This study measured business strategy, IT strategy, strategic alignment, IT performance, and business performance. Analysis of data gathered in a mail survey of China's manufacturing SMEs indicated that: 1) IT strategy itself does not influence business performance and IT performance; 2) strategic alignment strongly correlated with business performance and the impacts are positive; 3) strategic alignment has no impact on IT performance; 4) There is positive relationship between IT performance and business performance; 5) The relationship between business strategy and business performance is not strong. The contribution of different IT systems to IT performance is also examined.

In this paper, we propose a new mesh editing method worked in the dual domain for ROI (region of interest). This method has intuitive user interface and efficient reconstruction process. The mesh detail is represented by dual Laplacian, and the reconstructed mesh is obtained by solving a quadratic minimization problem which preserves the mesh detail in least square sense. Preconditioned bi-conjugate gradient method (PBCG) is adopted to iteratively update the positions of the dual vertices and the dual Laplacian coordinates. The experiments demonstrate that our method can work effectively and give visually pleasing results.

In this paper, we present a technique for multi-resolution meshes deformation based on pyramid coordinates. Pyramid coordinates are rotation invariant, and can achieve low distortion editing for large deformations. Their drawback is that the reconstruction process is nonlinear and time consuming especially for large meshes. In order to decrease the computational cost, the proposed method reduces the number of vertices involved in the deformation. We first construct a simplified mesh using a modified CPM algorithm; then edit the simplified meshes by pyramid coordinates based mesh detail presentation; finally, series of details are added to the deformed simplified mesh. Our algorithm can generate natural looking deformations more efficiently than the original pyramid coordinates method.

In this paper, we propose a new energy-minimizing mesh parameterization method, which linearly combines two new energies EQ and EM. It not only avoids triangles overlap in the parameter domain, but also is invariant under rotation, translation and scale transformations. We first parameterize the original 3D mesh to the parameter plane by using the energy-minimizing parameterization, and get the optimal effect by optimizing the weights wij gradually. Experimental results indicate that this optimized energy-minimizing method has low distortion and good stability.

In this paper a novel and intuitive method for the interactive deformation of 3D meshes is proposed. This method is based on skeleton. After a region of the model to be deformed is selected and several reference points are specified, a skeleton is created implicitly and automatically through the reference points and the screen. Then the vertices in the region to be deformed are mapped onto the skeleton. Deformation of the region can be achieved by deforming the skeleton to the desired position constrained by the target points, which are specified by the user. To uniformly distributing the distortion brought by the deformation and preserving the details of the deformed region, the points on the skeleton are represented by the linear rotation- invariant coordinates. The deformed skeleton is reconstructed in the least-squares sense. At last, the mesh deformation is carried out by reverse mapping from points on the skeleton to the corresponding vertices in the region to be deformed. The skeleton are also can be used to twist the region of the mesh. We demonstrate the effectiveness and interactivity of our method by the detail-preserving editing of several models using little time.

Residual nuclide production is studied experimentally by bombarding a Cu target with a 250 MeV proton beam. The data are measured by the off-line gamma-spectroscopy method. Six nuclides are identified and their cross sections are determined. The corresponding calculated results by the MCNPX and GEANT4 codes are compared with the experimental data to check the validity of the codes. A comparison shows that the MCNPX simulation has a better agreement with the experiment. The energy dependence of residual nuclide production is studied with the aid of MCNPX simulation, and it is found that the mass yields for the nuclides in the light mass region increase significantly with the proton energy.

This paper proposes a new method to embed watermark in binary images. The given binary image is partitioned into two level blocks, and the watermark will be embedded into the sub-blocks based on the parity of characteristic values. The method is very efficient especially when applied to those binary images whose black and white pixels are distributed approximately uniformly. The experimental results show that the method only requires fewer operations and it can embed more watermarks. Embedding two bits information in a 4times4 block needs to change only one and a half pixels on average

During progressive transmission of 3D geometry models, the transmission order of details at different region has great effects on the quality of reconstructed models at low bit-rate. This work presents a ratedistortion (R-D) optimized progressive geometry compression scheme to improve the quality of reconstructed models by adjusting the transmission order of details. In this scheme, the input mesh is partitioned into parts, then each part is encoded into bit-stream independently, and the encoded bit-streams are truncated into segments while getting the R-D characteristics of every segment, at last all segments are assembled into a codestream based on R-D optimization, which ensure the region with rich detail will be transmitted early and make the reconstructed mesh achieve better quality as soon as possible. Experimental results show that, as compared with the well-known PGC method, the proposed one provides better R-D performance. Moreover, it provides a novel way to realize the region of interest (ROI) coding of 3D meshes.

In this paper, we investigate the trace of seamless splicing for blind image splicing. Image splicing is an essential operation for digital photomontage, which in turn is a technique for creating image forgery. Although good forgeries may leave no visual clues of having been tampered with, they may, nevertheless, alter the underlying statistics of an image. Through investigating the observation of the photomontages, we find the specific correlations in the image, which can be detected and used as evidence of digital tampering. The features derived from the proposal are useful and are proved by experimentation

Most-conventional registration algorithms use the distance sum between point pairs to estimate pose parameters. These algorithms have the problem of inexact point correspondences. This paper proposes a novel registration algorithm based on a distance metric of surface-to-surface. The integration calculation of the mean distance between surfaces is derived and reduced to a simple formula.

In order to describe mesh bit-streams which can be adapted to the heterogeneity of network bandwidth and terminals graphics capabilities, the concepts of quality scalability and resolution scalability are introduced. A triangle mesh compression scheme based on wavelet transform is proposed to generate bit-streams with both scalabilities. Each subband corresponds to a resolution level. Wavelet coefficients of each subband are bitplane encoded to enable quality refinement within this subband. The experimental results show the proposed coder has achieved better compression performance than that of PGC (progressive geometry compression).

In watermarking schemes an image is considered as a communication channel for transmitting messages. But because of the requirements of watermarking robustness and visibility, watermarking schemes have different characteristics from traditional communication. Watermarking capacity should be associated with the content of an image. A different image has a different watermarking capacity. In this paper, we present a content adaptive watermarking algorithm to embed the strongest watermark while maintaining the watermark's invisibility, and discuss watermarking capacity for this scenario. We also derive the relation between watermarking capacity and detection bit error rate (BER) for the first time.

Capacity is an important character of digital watermarking. Research of image watermarking capacity is to study how much information can be hidden in an image. Recently, wavelet transform has been applied widely in watermarking research as its excellent multi-resolution analysis property. According to watermarking methods in wavelet domain, watermark's embedding and extracting realized in wavelet domain, we think that watermarking capacity should be analyzed in wavelet domain also. This paper presents a watermarking capacity analysis method based on content of wavelet subbands by using Watson quantization matrix and Noise Visibility Function (NVF), and discusses watermarking capacity of blind watermarking and non-blind watermarking in this scenario.