Automatic Road Extraction using High Resolution Satellite Image Based on Texture Progressive Analysis and Normalized Cut Method

In this paper the approach for automatic road extraction for an urban region using structural, spectral and geometric characteristics of roads has been presented. Roads have been extracted based on two levels: Pre-processing and road extraction methods. Initially, the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, parking lots, vegetation regions and other open spaces). The road segments are then extracted using Texture Progressive Analysis (TPA) and Normalized cut algorithm. The TPA technique uses binary segmentation based on three levels of texture statistical evaluation to extract road segments where as, Normalizedcut method for road extraction is a graph based method that generates optimal partition of road segments. The performance evaluation (quality measures) for road extraction using TPA and normalized cut method is compared. Thus the experimental result show that normalized cut method is efficient in extracting road segments in urban region from high resolution satellite image.

Efficient content-based image retrieval based on multi-feature fusion

The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.

A model of social work classification in health care

The introduction of casemix funding for Australian acute health care services has challenged Social Work to demonstrate clear reporting mechanisms, demonstrate effective practice and to justify interventions provided. The term 'casemix' is used to describe the mix and type of patients treated by a hospital or other health care services. There is wide acknowledgement that the procedure-based system of Diagnosis Related Groupings (DRGs) is grounded in a medical/illness perspective and is unsatisfactory in describing and predicting the activity of Social Work and other allied health professions in health care service delivery. The National Allied Health Casemix Committee was established in 1991 as the peak body to represent allied health professions in matters related to casemix classification. This Committee has pioneered a nationally consistent, patient-centred information system for allied health. This paper describes the classification systems and codes developed for Social Work, which includes a minimum data set, a classification hierarchy, the set of activity (input) codes and 'indicator for intervention' codes. The advantages and limitations of the system are also discussed.

Charge density based classification of intermolecular interactions in molecular crystals

Evaluation of intermolecular interactions in terms of both experimental and theoretical charge density analyses has produced a unified picture with which to classify strong and weak hydrogen bonds, along with van der Waals interactions, into three regions.

The dynamics of solvation of an electron in the image potential state by a layer of polar adsorbates

Recently, ultrafast two-photon photoemission has been used to study electron solvation at a two-dimensional metal/polar adsorbate interfaces [A. Miller , Science 297, 1163 (2002)]. The electron is bound to the surface by the image interaction. Earlier we have suggested a theoretical description of the states of the electron interacting with a two-dimensional layer of the polar adsorbate [K. L. Sebastian , J. Chem. Phys. 119, 10350 (2003)]. In this paper we have analyzed the dynamics of electron solvation, assuming a trial wave function for the electron and the solvent polarization and then using the Dirac-Frenkel variational method to determine it. The electron is initially photoexcited to a delocalized state, which has a finite but large size, and causes the polar molecules to reorient. This reorientation acts back on the electron and causes its wave function to shrink, which will cause further reorientation of the polar molecules, and the process continues until the electron gets self-trapped. For reasonable values for the parameters, we are able to obtain fair agreement with the experimental observations. (c) 2005 American Institute of Physics.

Inhibitory activity of Image -asparaginase from Mycobcacterium tuberculosis on Yoshida ascites sarcoma in rats

The antitumor activity of Image -asparagine amidohydrolases (EC 3.5.1.1) from Mycobacterium tuberculosis H37Rv and H37Ra strains has been tested on Yoshida ascites sarcoma in rats. The enzyme specific to M. tuberculosis H37Ra but not to H37Rv has proved to be effective in inhibiting the growth of the sarcoma. Comparative studies on the activity of this enzyme with that of similar enzyme from Escherichia coli B, has shown that at the same levels the former is more effective than the latter. Long-lived immunity to this tumor in A/IISc Wistar rats following treatment of tumor bearing animals with M. tuberculosis H37Ra, pH 9.6 Image -asparaginase has been observed. Immunity in these rats was demonstrated by tumor rejection and detection of humoral antibodies in the sera to the antigen of the cell-free extract of the tumor. The enzyme was ineffective in inhibiting fibrosarcoma in mice at the dose levels tested.

Image -asparaginases from Mycobacterium tuberculosis strains H37Rv and H37Ra

M. tuberculosis H37Ra possesses two Image -asparaginases while the H37Rv strain possesses only a single enzyme. These enzymes have been purified and their properties studied. The two Image -asparaginases in H37Ra strain differ from each other in pH optima, heat inactivation, Michaelis constant and effects of inhibitors, while one of them resembles the single Image -asparaginase present in the H37Rv strain. Image -Cysteine inhibits both Image -asparaginases in an allosteric manner probably because it is one of the end-products in Image -asparagine metabolism. This is the first time that a qualitative difference has been reported in the enzyme pattern between the avirulent and virulent strains of M. tuberculosis.

A Framework for Classification of Prokaryotic Protein Kinases

Background:Overwhelming majority of the Serine/Threonine protein kinases identified by gleaning archaeal and eubacterial genomes could not be classified into any of the well known Hanks and Hunter subfamilies of protein kinases. This is owing to the development of Hanks and Hunter classification scheme based on eukaryotic protein kinases which are highly divergent from their prokaryotic homologues. A large dataset of prokaryotic Serine/Threonine protein kinases recognized from genomes of prokaryotes have been used to develop a classification framework for prokaryotic Ser/Thr protein kinases. Methodology/Principal Findings: We have used traditional sequence alignment and phylogenetic approaches and clustered the prokaryotic kinases which represent 72 subfamilies with at least 4 members in each. Such a clustering enables classification of prokaryotic Ser/Thr kinases and it can be used as a framework to classify newly identified prokaryotic Ser/Thr kinases. After series of searches in a comprehensive sequence database we recognized that 38 subfamilies of prokaryotic protein kinases are associated to a specific taxonomic level. For example 4, 6 and 3 subfamilies have been identified that are currently specific to phylum proteobacteria, cyanobacteria and actinobacteria respectively. Similarly subfamilies which are specific to an order, sub-order, class, family and genus have also been identified. In addition to these, we also identify organism-diverse subfamilies. Members of these clusters are from organisms of different taxonomic levels, such as archaea, bacteria, eukaryotes and viruses.Conclusion/Significance: Interestingly, occurrence of several taxonomic level specific subfamilies of prokaryotic kinases contrasts with classification of eukaryotic protein kinases in which most of the popular subfamilies of eukaryotic protein kinases occur diversely in several eukaryotes. Many prokaryotic Ser/Thr kinases exhibit a wide variety of modular organization which indicates a degree of complexity and protein-protein interactions in the signaling pathways in these microbes.

Thionucleotides in the transfer ribonucleic acid of Image Image

tRNA isolated from Image Image , grown in the presence of radioactive sulfur was analyzed for the occurrence of thionucleotides. The analysis revealed the presence of at least five thionucleotides, of which three were identified as 4-thiouridylic acid, 5-methylaminomethyl-2-thiouridylic acid and 2-thiocytidylic acid. Iodine-oxidation affected the acceptor ability of several amino acid specific tRNAs, those for lysine and serine being affected most. The tRNA of Image Image differs from that of Image . Image both in the number and the relative proportion of thionucleotides.

Comparison of Multiclass SVM Classification Methods to Use in a Supportive System for Distance Relay Coordination

This paper aims at evaluating the methods of multiclass support vector machines (SVMs) for effective use in distance relay coordination. Also, it describes a strategy of supportive systems to aid the conventional protection philosophy in combating situations where protection systems have maloperated and/or information is missing and provide selective and secure coordinations. SVMs have considerable potential as zone classifiers of distance relay coordination. This typically requires a multiclass SVM classifier to effectively analyze/build the underlying concept between reach of different zones and the apparent impedance trajectory during fault. Several methods have been proposed for multiclass classification where typically several binary SVM classifiers are combined together. Some authors have extended binary SVM classification to one-step single optimization operation considering all classes at once. In this paper, one-step multiclass classification, one-against-all, and one-against-one multiclass methods are compared for their performance with respect to accuracy, number of iterations, number of support vectors, training, and testing time. The performance analysis of these three methods is presented on three data sets belonging to training and testing patterns of three supportive systems for a region and part of a network, which is an equivalent 526-bus system of the practical Indian Western grid.

From cages to wedges and clefts : Design of some novel hosts based on Image , Image , Image -triquinane framework

Annulation of aromatic rings on the folded Image ,Image ,Image -triquinane backbone has led to the design of potential host systems Image and Image whose crystal structures have been determined.

Image Heritage - The Temporal Dimension in Consumers' Corporate Image Constructions

Images and brands have been topics of great interest in both academia and practice for a long time. The company’s image, which in this study is considered equivalent to the actual corporate brand, has become a strategic issue and one of the company’s most valuable assets. In contrast to mainstream corporate branding research focusing on consumerimages as steered and managed by the company, in the present study a genuine consumer-focus is taken. The question is asked: how do consumers perceive the company, and especially, how are their experiences of the company over time reflected in the corporate image? The findings indicate that consumers’ corporate images can be seen as being constructed through dynamic relational processes based on a multifaceted network of earlier images from multiple sources over time. The essential finding is that corporate images have a heritage. In the thesis, the concept of image heritage is introduced, which stands for the consumer’s earlier company-related experiences from multiple sources over time. In other words, consumers construct their images of the company based on earlier recalled images, perhaps dating back many years in time. Therefore, corporate images have roots - an image heritage – on which the images are constructed in the present. For companies, image heritage is a key for understanding consumers, and thereby also a key for consumer-focused branding strategies and activities. As image heritage is the consumer’s interpretation base and context for image constructions here and now, branding strategies and activities that meet this consumer-reality has a potential to become more effective. This thesis is positioned in the tradition of The Nordic School of Marketing Thought and introduces a relational dynamic perspective into branding through consumers’ image heritage. Anne Rindell is associated to CERS, the Center for Relationship Marketing and Service Management at the Swedish School of Economics and Business Administration.

Wavelet transform based error concealment approach for image denoising

Denoising of images in compressed wavelet domain has potential application in transmission technology such as mobile communication. In this paper, we present a new image denoising scheme based on restoration of bit-planes of wavelet coefficients in compressed domain. It exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each band. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with conventional unrestored scheme, in context of error reduction and has capability to adapt to situations where noise level in the image varies. The applicability of the proposed approach has implications in restoration of images due to noisy channels. This scheme, in addition, to being very flexible, tries to retain all the features, including edges of the image. The proposed scheme is computationally efficient.