15014203
A VQ-based image-in-image data hiding scheme
Vector quantization (VQ)-based data hiding and watermarking techniques form a newly developed branch in the digital watermarking research field. We propose a novel watermarking scheme for image-in-image data hiding based on VQ. Unlike existing schemes in the literature for embedding a binary watermark into the original image with VQ, we present an efficient and secure algorithm for embedding a gray-level watermark into the original. The offered scheme is robust to attacks such as VQ compression and JPEG compression. Moreover, it greatly expands the capacity of the watermarking system. Experimental results demonstrate the superiority of our scheme in watermark robustness and watermark capacity. The results also prove the effectiveness of our proposed schemes in VQ-based image-in-image data hiding.
13572740
Image Texture Segmentation with Ant Colony Systems
A new scheme for texture segmentation based on ant colony systems (ACS) is proposed in this paper. Texture segmentation is one of the important branches in image pattern recognition, which provides usefulness in many applications. Until now, how to find an effective way for accomplishing texture segmentation in practical applications is still a major task. In this paper, we employ wavelet coefficients and characteristics of different subbands to serve as the basis of characteristic vectors, and we use three feature-extraction elements, namely, the extrema, entropy, and energy, to compose the characteristic vector. To alleviate segmentation fragments caused from the information in high frequency bands of texture images, we integrate the fourth element, the mean variance, into the characteristic vector. Finally, we use ACS to find a trade-off between texture segmentation and fragments. Simulation results demonstrate the effectiveness and practicability of the proposed algorithm
7106859
Vector quantization based on genetic simulated annealing
Genetic algorithm (GA) has been successfully applied to codebook design for vector quantization (VQ). However, most conventional GA-based codebook design methods need long runtime because candidate solutions must be "ne tuned by LBG. In this paper, a partition-based GA is applied to codebook design, which is referred to as genetic vector quantization (GVQ). In addition, simulated annealing (SA) algorithm is also used in GVQ to get more promising results and the corresponding method is referred to as GSAVQ. Both GVQ and GSAVQ use the linear scaling technique during the calculation of objective functions and use special crossover and mutation operations in order to obtain better codebooks in much shorter CPU time. Experimental results show that both of them save more than 71}87% CPU time compared to LBG. For di!erent codebook sizes, GVQ outperforms LBG by 1.1}2.1 dB in PSNR, and GSAVQ outperforms LBG by 1.2}2.2 dB in PSNR. In addition, GVQ and GSAVQ need a little longer CPU time than, the maximum decent (MD) algorithm, but they outperform MD by 0.2}0.5 dB in PSNR. 2001 Elsevier Science B.V. All rights reserved.
35266077
VQ-Based Gray Watermark Hiding Scheme and Genetic Index Assignment
A vector quantisation (VQ) based watermarking scheme for hiding the gray watermark is presented. It expands the watermark size, and employs VQ index assignment procedure with genetic algorithm, called genetic index assignment (GIA), for watermarking. The gray watermark is coded by VQ, and obtained indices are translated into a binary bitstream with a much smaller size. We partition the codebook into two sub-codebooks, and use either one of them based on the value of the bit for embedding. Next, GIA is employed to find better imperceptibility of watermarked image. Experimental results show that the proposed method possesses advantages over other related methods in literature.
16432489
Genetic watermarking based on transform-domain techniques
Abstract An innovative watermarking scheme based on genetic algorithms (GA) in the transform domain is proposed. It is robust against watermarking attacks, which are commonly employed in the literature. In addition, the watermarked image quality is also considered. In this paper, we employ GA for optimizing both the fundamentally conflicting requirements. Watermarking with GA is easy for implementation. We also examine the effectiveness of our scheme by checking the fitness function in GA, which includes both factors related to robustness and invisibility. Simulation results also show both the robustness under attacks, and the improvement in watermarked image quality with GA.
10859494
Adaptive watermarking using relationships between wavelet coefficients
We propose an approach that hides watermarks in relationships between wavelet coefficients. This approach minimizes the perceptual distortion of watermarked images, measured by PSNR or just noticeable distortion (JND). Therefore, the strength of watermarks can be enlarged to increase the robustness of the watermarks, while keeping the quality of watermarked images visually acceptable. Experimental results show that the watermark is still detectable after common image processing operations such as JPEG compression, Gaussian filtering and sharpening.
1841883
Mining putative regulatory elements in gene promoter regions of Saccharomyces cerevisiae
The availability of genome-wide gene expression data provides a unique set of genes from which we can decipher the mechanisms underlying the common transcriptional response. Transcription factors, which can bind to specific DNA sites, cooperatively regulate the transcription of genes. This study attempts to mine putative binding sites to investigate how combinations of the sites predicted from known sites and over-represented repetitive elements are distributed in the promoter regions of groups of functionally related genes. The over-represented repetitive elements appearing in the associations are possible transcription factor binding sites. The deduced association rules would facilitate to predict putative regulatory elements and to identify genes which are potentially co-regulated by the putative regulatory elements. Our proposed approach is applied to Saccharomyces cerevisiae and the promoter regions of yeast ORFs.
6014802
Identifying the combination of genetic factors that determine susceptibility to cervical cancer
Cervical cancer is common among women all over the world. Although infection with high-risk types of human papillomavirus (HPV) has been identified as the primary cause of cervical cancer, only some of those infected go on to develop cervical cancer. Obviously, the progression from HPV infection to cancer involves other environmental and host factors. Recent population-based twin and family studies have demonstrated the importance of the hereditary component of cervical cancer, associated with genetic susceptibility. Consequently, single-nucleotide polymorphism (SNP) markers and microsatellites should be considered genetic factors for determining what combinations of genetic factors are involved in precancerous changes to cervical cancer. This study employs a Bayesian network and four different decision tree algorithms, and compares the performance of these learning algorithms. The results of this study raise the possibility of investigations that could identify combinations of genetic factors, such as SNPs and microsatellites, that influence the risk associated with common complex multifactorial diseases, such as cervical cancer. The web site associated with this study is http://140.115.155.8/FactorAnalysis/.
6104187
Binary analysis and automated hot patching for Web-based applications
Patching technologies are commonly applied to improve the dependability of software after release. This paper reports the design of an automated hot patching (AHP) framework that fully automates reasoning for the causes of failures and patching the binary code of Web-based applications. AHP admits the hardness for rooting out all faults before product release, and autonomously patches problems of application programs. By directly operating on binary code, AHP is universal to virtually all applications. A promising application of AHP is to shortcut a function of the remote maintenance center (RMC) and hence to reduce the turn around time for patches.
7951451
A New Test System for Stability Measurement of Marker Gene Selection in DNA Microarray Data Analysis
Microarray gene expression data contains informative features that reflect the critical processes controlling prominent biological functions. Feature selection algorithms have been used in previous biomedical research to find the “marker” genes whose expression value change corresponds to the most eminent difference between specimen classes. One problem encountered in such analysis is the imbalance between very large numbers of genes versus relatively fewer specimen samples. A common concern, therefore, is “overfitting” the data and deriving a set of marker genes with low stability over the entire set of possible specimens. To address this problem, we propose a new test environment in which synthetic data is perturbed to simulate possible variations in gene expression values. The goal is for the generated data to have appropriate properties that match natural data, and that are appropriate for use in testing the sensitivity of feature selection algorithms and validating the robustness of selected marker genes. In this paper, we evaluate a statistically-based resampling approach and a Principal Components Analysis (PCA)-based linear noise distribution approach. Our results show that both methods generate reasonable synthetic data and that the signal/noise rate (with variation weights at 5%, 10%, 20% and 30%) measurably impacts the classification accuracy and the marker genes selected. Based on these results, we identify the most appropriate marker gene selection and classification techniques for each type and level of noise we modeled.
18616381
The Cost of Transparency: Grid-Based File Access on the Avaki Data Grid
Grid computing has been a hot topic for a decade. Several systems have been developed. Despite almost a decade of research and tens of millions of dollars spent, uptake of grid technology has been slow. Most deployed grids are based on a toolkit approach that requires significant software modification or development. An operating system technique used for over 30 years has been to reduce application complexity by providing transparency, e.g. file systems mask details of devices, virtual machines mask finite memory, etc. It has been argued that providing transparency in a grid environment is too costly in terms of performance. This paper examines that question in the context of data grids by measuring the performance of a commercially available data grid product – the Avaki Data Grid (ADG). We present the architecture of the ADG, describe our experimental setup, and provide performance results, comparing the ADG to a native NFS V3 implementation for both local and wide area access cases. The results were mixed, though encouraging. For single client local file operations, native NFS outperformed the ADG by 15% to 45% for smaller files, though for files larger than 32 MB ADG outperformed native NFS.