Abstract: In this study, six bacterial isolates of a slightly
thermophilic organism from the Sg. Klah hot spring, Malaysia were
successfully isolated and designated as M7T55D1, M7T55D2,
M7T55D3, M7T53D1, M7T53D2 and M7T53D3 respectively. The
bacterial isolates were screened for their cellulose hydrolytic ability
on Carboxymethlycellulose agar medium. The isolated bacterial
strains were identified morphologically, biochemically and
molecularly with the aid of 16S rDNA sequencing. All of the bacteria
showed their optimum growth at a slightly alkaline pH of 7.5 with a
temperature of 55°C. All strains were Gram-negative, non-spore
forming type, strictly aerobic, catalase-positive and oxidase-positive
with the ability to produce thermostable cellulase. Based on BLASTn
results, bacterial isolates of M7T55D2 and M7T53D1 gave the
highest homology (97%) with similarity to Tepidimonas ignava while
isolates M7T55D1, M7T55D3, M7T53D2 and M7T53D3 showed
their closest homology (97%-98%) with Tepidimonas thermarum.
These cellulolytic thermophiles might have a commercial potential to
produce valuable thermostable cellulase.
Abstract: ‘Steganalysis’ is one of the challenging and attractive interests for the researchers with the development of information hiding techniques. It is the procedure to detect the hidden information from the stego created by known steganographic algorithm. In this paper, a novel feature based image steganalysis technique is proposed. Various statistical moments have been used along with some similarity metric. The proposed steganalysis technique has been designed based on transformation in four wavelet domains, which include Haar, Daubechies, Symlets and Biorthogonal. Each domain is being subjected to various classifiers, namely K-nearest-neighbor, K* Classifier, Locally weighted learning, Naive Bayes classifier, Neural networks, Decision trees and Support vector machines. The experiments are performed on a large set of pictures which are available freely in image database. The system also predicts the different message length definitions.
Abstract: Fibrin degradation is an important part in prevention
or treatment of intravascular thrombosis and cardiovascular diseases.
Plasmin like fibrinolytic enzymes has given new hope to patient with
cardiovascular diseases by treating fibrin aggregation related diseases
with traditional plasminogen activator which have many side effects.
Various researches involving wide range of sources for production of
fibrinolytic proteases, from bacteria, fungi, insects and fermented
foods. But few have looked into endophytic fungi as a potential
source. Sixteen (16) endophytic fungi were isolated from Hibiscus sp.
leaves from six different locations in Shah Alam, Selangor. Only two
endophytic fungi, FH3 and S13 showed positive fibrinolytic protease
activities. FH3 produced 5.78cm and S13 produced 4.48cm on Skim
Milk Agar after 4 days of incubation at 27°C. Fibrinolytic activity
was observed; 3.87cm and 1.82cm diameter clear zone on fibrin plate
of FH3 and S13 respectively. 18srRNA was done for identification of
the isolated fungi with positive fibrinolytic protease. S13 had the
highest similarity (100%) to that of Penicillium citrinum strain TG2
and FH3 had the highest similarity (99%) to that of Fusarium sp.
FW2PhC1, Fusarium sp. 13002, Fusarium sp. 08006, Fusarium
equiseti strain Salicorn 8 and Fungal sp. FCASAn-2. Media
composition variation showed the effects of carbon nitrogen on
protein concentration, where the decrement of 50% of media
composition caused drastic decrease in protease of FH3 from 1.081 to
0.056 and also S13 from 2.946 to 0.198.
Abstract: The need to extract R&D keywords from issues and use
them to retrieve R&D information is increasing rapidly. However, it is
difficult to identify related issues or distinguish them. Although the
similarity between issues cannot be identified, with an R&D lexicon,
issues that always share the same R&D keywords can be determined.
In detail, the R&D keywords that are associated with a particular issue
imply the key technology elements that are needed to solve a particular
issue.
Furthermore, the relationship among issues that share the same
R&D keywords can be shown in a more systematic way by clustering
them according to keywords. Thus, sharing R&D results and reusing
R&D technology can be facilitated. Indirectly, redundant investment
in R&D can be reduced as the relevant R&D information can be shared
among corresponding issues and the reusability of related R&D can be
improved. Therefore, a methodology to cluster issues from the
perspective of common R&D keywords is proposed to satisfy these
demands.
Abstract: An extensive amount of work has been done in data
clustering research under the unsupervised learning technique in Data
Mining during the past two decades. Moreover, several approaches
and methods have been emerged focusing on clustering diverse data
types, features of cluster models and similarity rates of clusters.
However, none of the single clustering algorithm exemplifies its best
nature in extracting efficient clusters. Consequently, in order to
rectify this issue, a new challenging technique called Cluster
Ensemble method was bloomed. This new approach tends to be the
alternative method for the cluster analysis problem. The main
objective of the Cluster Ensemble is to aggregate the diverse
clustering solutions in such a way to attain accuracy and also to
improve the eminence the individual clustering algorithms. Due to
the massive and rapid development of new methods in the globe of
data mining, it is highly mandatory to scrutinize a vital analysis of
existing techniques and the future novelty. This paper shows the
comparative analysis of different cluster ensemble methods along
with their methodologies and salient features. Henceforth this
unambiguous analysis will be very useful for the society of clustering
experts and also helps in deciding the most appropriate one to resolve
the problem in hand.
Abstract: A theoretical study has been presented to describe the boundary layer flow and heat transfer on an exponentially shrinking sheet with a variable wall temperature and suction, in the presence of magnetic field. The governing nonlinear partial differential equations are converted into ordinary differential equations by similarity transformation, which are then solved numerically using the shooting method. Results for the skin friction coefficient, local Nusselt number, velocity profiles as well as temperature profiles are presented through graphs and tables for several sets of values of the parameters. The effects of the governing parameters on the flow and heat transfer characteristics are thoroughly examined.
Abstract: The process in which the complementary information from multiple images is integrated to provide composite image that contains more information than the original input images is called image fusion. Medical image fusion provides useful information from multimodality medical images that provides additional information to the doctor for diagnosis of diseases in a better way. This paper represents the wavelet based medical image fusion algorithm on different multimodality medical images. In order to fuse the medical images, images are decomposed using Redundant Wavelet Transform (RWT). The high frequency coefficients are convolved with morphological operator followed by the maximum-selection (MS) rule. The low frequency coefficients are processed by MS rule. The reconstructed image is obtained by inverse RWT. The quantitative measures which includes Mean, Standard Deviation, Average Gradient, Spatial frequency, Edge based Similarity Measures are considered for evaluating the fused images. The performance of this proposed method is compared with Pixel averaging, PCA, and DWT fusion methods. When compared with conventional methods, the proposed framework provides better performance for analysis of multimodality medical images.
Abstract: Object detection using Wavelet Neural Network (WNN) plays a major contribution in the analysis of image processing. Existing cluster-based algorithm for co-saliency object detection performs the work on the multiple images. The co-saliency detection results are not desirable to handle the multi scale image objects in WNN. Existing Super Resolution (SR) scheme for landmark images identifies the corresponding regions in the images and reduces the mismatching rate. But the Structure-aware matching criterion is not paying attention to detect multiple regions in SR images and fail to enhance the result percentage of object detection. To detect the objects in the high-resolution remote sensing images, Tagged Grid Matching (TGM) technique is proposed in this paper. TGM technique consists of the three main components such as object determination, object searching and object verification in WNN. Initially, object determination in TGM technique specifies the position and size of objects in the current image. The specification of the position and size using the hierarchical grid easily determines the multiple objects. Second component, object searching in TGM technique is carried out using the cross-point searching. The cross out searching point of the objects is selected to faster the searching process and reduces the detection time. Final component performs the object verification process in TGM technique for identifying (i.e.,) detecting the dissimilarity of objects in the current frame. The verification process matches the search result grid points with the stored grid points to easily detect the objects using the Gabor wavelet Transform. The implementation of TGM technique offers a significant improvement on the multi-object detection rate, processing time, precision factor and detection accuracy level.
Abstract: This research aims to study species, abundance, status
of birds, the similarities and activity characteristics of birds which
reap benefits from the research area in boat touring routes in Tha Ka
sub-district, Amphawa District, Samut Songkram Province, Thailand.
from October 2012 – September 2013. The data was analyzed to find
the abundance, and similarity index of the birds. The results from the
survey of birds on all three routes found that there are 33 families and
63 species. Route 3 (traditional coconut sugar making kiln – resort)
had the most species; 56 species. There were 18 species of commonly
found birds with an abundance level of 5, which calculates to 28.57%
of all bird species. In August, 46 species are found, being the greatest
number of bird species benefiting from this route. As for the status of
the birds, there are 51 resident birds, 7 resident and migratory birds,
and 5 migratory birds. On Route 2 and Route 3, the similarity index
value is equal to 0.881. The birds are classified by their activity
characteristics i.e. insectivore, piscivore, granivore, nectrivore and
aquatic invertebrate feeder birds. Some birds also use the area for
nesting.
Abstract: The inhibition of SH2 domain regulated protein-protein interactions is an attractive target for developing an effective chemotherapeutic approach in the treatment of disease. Molecular simulation is a useful tool for developing new drugs and for studying molecular recognition. In this study, we searched potential drug compounds for the inhibition of SH2 domain by performing structural similarity search in PubChem Compound Database. A total of 37 compounds were screened from the database, and then we used the LibDock docking program to evaluate the inhibition effect. The best three compounds (AP22408, CID 71463546 and CID 9917321) were chosen for MD simulations after the LibDock docking. Our results show that the compound CID 9917321 can produce a more stable protein-ligand complex compared to other two currently known inhibitors of Src SH2 domain. The compound CID 9917321 may be useful for the inhibition of SH2 domain based on these computational results. Subsequently experiments are needed to verify the effect of compound CID 9917321 on the SH2 domain in the future studies.
Abstract: In general, algorithms to find continuous k-nearest neighbors have been researched on the location based services, monitoring periodically the moving objects such as vehicles and mobile phone. Those researches assume the environment that the number of query points is much less than that of moving objects and the query points are not moved but fixed. In gaming environments, this problem is when computing the next movement considering the neighbors such as flocking, crowd and robot simulations. In this case, every moving object becomes a query point so that the number of query point is same to that of moving objects and the query points are also moving. In this paper, we analyze the performance of the existing algorithms focused on location based services how they operate under gaming environments.
Abstract: This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.
Abstract: The effect of mass transfer on MHD mixed convective flow along inclined porous plate with thermodiffusion have been analyzed on the basis of boundary layer approximations. The fluid is assumed to be incompressible and dense, and a uniform magnetic field is applied normal to the direction of the flow. A Similarity transformation is used to transform the problem under consideration into coupled nonlinear boundary layer equations which are then solved numerically using the Runge-Kutta sixth-order integration scheme together with Nachtsheim-Swigert shooting iteration technique. The behavior of velocity, temperature, concentration, local skin-friction, local Nusselt number and local Sherwood number for different values of parameters have been computed and the results are presented graphically, and analyzed thereafter. The validity of the numerical methodology and the results are questioned by comparing the findings obtained for some specific cases with those available in the literature, and a comparatively good agreement is reached.
Abstract: The problem of magnetohydrodynamics boundary layer flow and heat transfer on a permeable stretching surface in a second grade nanofluid under the effect of heat generation and partial slip is studied theoretically. The Brownian motion and thermophoresis effects are also considered. The boundary layer equations governed by the PDE’s are transformed into a set of ODE’s with the help of local similarity transformations. The differential equations are solved by variational finite element method. The effects of different controlling parameters on the flow field and heat transfer characteristics are examined. The numerical results for the dimensionless velocity, temperature and nanoparticle volume fraction as well as the reduced Nusselt and Sherwood number have been presented graphically. The comparison confirmed excellent agreement. The present study is of great interest in coating and suspensions, cooling of metallic plate, oils and grease, paper production, coal water or coal-oil slurries, heat exchangers technology, materials processing exploiting.
Abstract: We propose obstacle classification method based on 2D
LIDAR Database. The existing obstacle classification method based
on 2D LIDAR, has an advantage in terms of accuracy and shorter
calculation time. However, it was difficult to classifier the type of
obstacle and therefore accurate path planning was not possible. In
order to overcome this problem, a method of classifying obstacle type
based on width data of obstacle was proposed. However, width data
was not sufficient to improve accuracy. In this paper, database was
established by width and intensity data; the first classification was
processed by the width data; the second classification was processed
by the intensity data; classification was processed by comparing to
database; result of obstacle classification was determined by finding
the one with highest similarity values. An experiment using an actual
autonomous vehicle under real environment shows that calculation
time declined in comparison to 3D LIDAR and it was possible to
classify obstacle using single 2D LIDAR.
Abstract: The present analysis considers the steady stagnation point flow and heat transfer towards a permeable shrinking sheet in an upper-convected Maxwell (UCM) electrically conducting fluid, with a constant magnetic field applied in the transverse direction to flow and a local heat generation within the boundary layer, with a heat generation rate proportional to (T-T)p Using a similarity transformation, the governing system of partial differential equations is first transformed into a system of ordinary differential equations, which is then solved numerically using a finite-difference scheme known as the Keller-box method. Numerical results are obtained for the flow and thermal fields for various values of the stretching/shrinking parameter λ, the magnetic parameter M, the elastic parameter K, the Prandtl number Pr, the suction parameter s, the heat generation parameter Q, and the exponent p. The results indicate the existence of dual solutions for the shrinking sheet up to a critical value λc whose value depends on the value of M, K, and s. In the presence of internal heat absorption (Q
Abstract: In this paper, the steady laminar three-dimensional boundary layer flow and heat transfer of a copper (Cu)-water nanofluid in the vicinity of a permeable shrinking flat surface in an otherwise quiescent fluid is studied. The nanofluid mathematical model in which the effect of the nanoparticle volume fraction is taken into account is considered. The governing nonlinear partial differential equations are transformed into a system of nonlinear ordinary differential equations using a similarity transformation which is then solved numerically using the function bvp4c from Matlab. Dual solutions (upper and lower branch solutions) are found for the similarity boundary layer equations for a certain range of the suction parameter. A stability analysis has been performed to show which branch solutions are stable and physically realizable. The numerical results for the skin friction coefficient and the local Nusselt number as well as the velocity and temperature profiles are obtained, presented and discussed in detail for a range of various governing parameters.
Abstract: Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.
Abstract: This analysis is performed to study the momentum, heat and mass transfer characteristics of MHD mixed convective flow past inclined porous plate in porous medium, including the effect of fluid suction. The fluid is assumed to be steady, incompressible and dense. Similarity solution is used to transform the problem under consideration into coupled nonlinear boundary layer equations which are then solved numerically by using the Runge-Kutta sixth-order integration scheme together with Nachtsheim-Swigert shooting iteration technique. Numerical results for the various types of parameters entering into the problem for velocity, temperature and concentration distributions are presented graphically and analyzed thereafter. Moreover, expressions for the skin-friction, heat transfer co-efficient and mass transfer co-efficient are discussed with graphs against streamwise distance for various governing parameters.
Abstract: Mosaic refers to a technique that makes image by gathering lots of small materials in various colors. This paper presents an automatic algorithm that makes the photo-mosaic image using photos. The algorithm is composed of 4 steps: partition and feature extraction, block matching, redundancy removal and color adjustment. The input image is partitioned in the small block to extract feature. Each block is matched to find similar photo in database by comparing similarity with Euclidean difference between blocks. The intensity of the block is adjusted to enhance the similarity of image by replacing the value of light and darkness with that of relevant block. Further, the quality of image is improved by minimizing the redundancy of tiles in the adjacent blocks. Experimental results support that the proposed algorithm is excellent in quantitative analysis and qualitative analysis.