Search Space Reduction in Exemplar Based Image Inpainting

This paper aims at developing accelerated exemplary inpaint method. The feature set is considered to be the pixels along with their 8-neighbors. A Multi Phase Search Space Reduction framework namely Systematic Reduction of Information System (SRIS) is employed. SRIS, basically is a roughest based approach which imputes the missing values in an adaptive manner. In this approach the order of inpainting pixels is determined by a simple but effective priority term. The best exemplar is determined based on a similarity metric which is derived by element wise difference of informative pixels of inpaint window and the corresponding pixels of the source region window

New similarity Measure for Exemplar Based in Painting

In this paper we intend to illustrate a utility and application of Kriging approximations in image processing problem designated by inpainting or filling in. We also review three state of the art infilling algorithms that deal with higher order PDE, Total Variation and exemplar-based approach. The computer model, a simple idea, we propose addresses this problem in deterministic way, and thus a response from a model lacks random error, i.e., repeated runs for the same input parameters gives the same response from the model. In its simple sense, Kriginng problem is related to the more general problem of predicting output from a computer model at untried inputs. Hence it lends it self for solving inpainting problem. Experimental results show that the proposed model yields qualitative results that are comparable to the existing complex approaches. The proposed method is very effective and simple to fill small gaps

Free leucine dissociates homo- and heterodimers formed between proteins containing leucine heptad repeats

AbstractA highly specific method for the dissociation of protein dimers has been developed. The method involves exposure of the dimers to free leucine at a concentration ranging between 3 and 10 mM. Using this method it has been possible to dissociate goat uterine oestrogen receptor homodimers, heterodimers formed between the non-activated oestrogen receptor (naER) and the oestrogen receptor activation factor (E-RAF) of the goat uterus, c-jun homodimers derived from bovine bone marrow and also glucocorticoid receptor homodimers isolated from rat liver cytosol. The pattern of dimer dissociation by leucine clearly differentiates two classes of proteins. The first is represented by steroid hormone receptors where dimerization is apparently contributed by both coiled-coil dimerization interfaces and the conserved heptad repeats of leucine. The second is represented by oncoproteins like c-fos and c-jun which dimerize through the exclusive involvement of leucine zippers. The patterns of dissociation of these two groups of proteins from the concerned affinity columns are distinctly different. This indicates a possibility that the elution pattern may be used as a yardstick to determine whether two proteins dimerize through the exclusive involvement of leucine zippers or whether coiled-coil interfaces are also involved in the dimerization process

Identification of DNA-binding proteins using support vector machines and evolutionary profiles

<p>Abstract</p> <p>Background</p> <p>Identification of DNA-binding proteins is one of the major challenges in the field of genome annotation, as these proteins play a crucial role in gene-regulation. In this paper, we developed various SVM modules for predicting DNA-binding domains and proteins. All models were trained and tested on multiple datasets of non-redundant proteins.</p> <p>Results</p> <p>SVM models have been developed on DNAaset, which consists of 1153 DNA-binding and equal number of non DNA-binding proteins, and achieved the maximum accuracy of 72.42% and 71.59% using amino acid and dipeptide compositions, respectively. The performance of SVM model improved from 72.42% to 74.22%, when evolutionary information in form of PSSM profiles was used as input instead of amino acid composition. In addition, SVM models have been developed on DNAset, which consists of 146 DNA-binding and 250 non-binding chains/domains, and achieved the maximum accuracy of 79.80% and 86.62% using amino acid composition and PSSM profiles. The SVM models developed in this study perform better than existing methods on a blind dataset.</p> <p>Conclusion</p> <p>A highly accurate method has been developed for predicting DNA-binding proteins using SVM and PSSM profiles. This is the first study in which evolutionary information in form of PSSM profiles has been used successfully for predicting DNA-binding proteins. A web-server DNAbinder has been developed for identifying DNA-binding proteins and domains from query amino acid sequences <url>http://www.imtech.res.in/raghava/dnabinder/</url>.</p

EASND: Energy Adaptive Secure Neighbour Discovery Scheme for Wireless Sensor Networks

Wireless Sensor Network (WSN) is defined as a distributed system of networking, which is enabled with set of resource constrained sensors, thus attempt to providing a large set of capabilities and connectivity interferences. After deployment nodes in the network must automatically affected heterogeneity of framework and design framework steps, including obtaining knowledge of neighbor nodes for relaying information. The primary goal of the neighbor discovery process is reducing power consumption and enhancing the lifespan of sensor devices. The sensor devices incorporate with advanced multi-purpose protocols, and specifically communication models with the pre-eminent objective of WSN applications. This paper introduces the power and security aware neighbor discovery for WSNs in symmetric and asymmetric scenarios. We have used different of neighbor discovery protocols and security models to make the network as a realistic application dependent model. Finally, we conduct simulation to analyze the performance of the proposed EASND in terms of energy efficiency, collisions, and security. The node channel utilization is exceptionally elevated, and the energy consumption to the discovery of neighbor nodes will also be significantly minimized. Experimental results show that the proposed model has valid accomplishment

Ethnomedicinal plants used by the tribals of Sudi Konda Forest, East Godavari District, Andhra Pradesh to cure women problems

The paper deals with 27 plant species belonging to 25 genera of 20 families to cure women problems prevalent among the tribals of Sudi konda forest area of East Godavari district, Andhra Pradesh are reported along with local name, methods of administration and prescribed doses

Criminal Identification Based on Androgenic Hair Pattern Using KNN-Clustering Method

This paper is implemented in order to identify the criminals in forensics based on the androgenic hair pattern of the criminal particularly in Low-resolution images. The Proposed paper is more dependable than the existing forensic techniques to identify criminals. The paper is implemented in five stages; in the first stage the input images and the database images are obtained after which the database images are trained through the algorithm to get the trained images. In the second stage pre-processing of the images is done in order to convert the image to grey scale and remove noise using thresholding method. The Third stage the image is passed through a Gabor filter to detect the edges in the image, this is followed by the Fourth phase where KNN clustering method is used to obtain the region of interest followed by the application of the bilateral filter in order to enhance the image. In the final stage the indifferent value calculated from the input image is matched with all the indifferent values of the trained images to identify the criminal

Yield behavior of unoriented and oriented polycarbonate and polypropylene as influenced by temperature

The yield behaviors of an amorphous polymer (polycarbonate) and a crystalline polymer (polypropylene) were investigated over certain ranges of temperature. Both polymers were used in an unoriented (isotropic) and an oriented (anisotropic) condition. By using proposed yield criteria for the two structural conditions various theoretical yield loci are predicted; these are then compared with experimental findings based on a number of uniaxial and biaxial stress states. With a few exceptions that seem amenable to rational explanation the comparison between theory and experiment is most promising. The onset of yielding is defined by two methods: using a 0.3% offset and using the concept of plastic work. Similar findings result. Finally, for the range of parameters used in this study it is possible to compare individual results for a given material condition with a single yield locus, regardless of the temperature at which the tests were conducted.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23251/1/0000184.pd