Image Segmentation for Animal Images using Finite Mixture of Pearson Type VI Distribution

Image Segmentation is one of the significant tool for analyzing images, the feature vector of the images are different for different types of images. In remote sensing, Environmental ecological systems, forest studies, conservation of rare animals, the animal images are more important. In this paper we developed and analyze an image segmentation algorithm using mixture of Pearson Type VI Distribution. The Pearsonian Type VI Distribution will characterize the image regions of animal images. The appropriateness Pearsonian Type VI distribution for the pixel intensities of image region in animal images is carried by fitting Pearsonian Type VI Distribution to set of animal images taken from Berkeley image data set. The image segmentation algorithm is developed using EM algorithm for estimating the parameters of the model and maximum likelihood for image component under Bayesian framework. For fast convergence of EM algorithm the initial estimates of the model parameters are obtained by dividing the whole image into K image regions using K-means and Hierarchical clustering algorithm and utilizing the moment method of estimates. The performance of proposed algorithm is studied by conducting an experiment with set of animal images and computing image quality metrics such as PRI, GCE and VOI. A comparative study of developed image segmentation by Gaussian Mixture model and found the proposed algorithm performed better for animal images due to asymmetrically distributed nature of pixel intensities in the image regions

Modeling of Turbulent Flows and Boundary Layer

Non

Effect of Hall Currents, Thermal Radiation Convective Heat Transfer Flow of a Rotating Nano-Fluid Past a Vertical Plate with Oscillatory Wall Velocity

We investigate the effect of thermal radiation and oscillatory wall velocity on unsteady convective heat transfer flow of a nanofluid past a vertical plate in the presence of heat generating sources. Analytical closed form solutions are obtained for both the momentum and the energy equations using the regular perturbation method. Graphs are used to illustrate the significance of key parameters on the nanofluid velocity and temperature distributions. Keywords: Thermal Radiation, Heat transfer, Nanofluid, Vertical Plat

Light Curve Solutions of Eclipsing Binaries in SMC

We propose a procedure for light-curve solution of eclipsing binary stars in the Small Magellanic Cloud for which photometric data have been obtained in the framework of the OGLE project as well as way of determination of the global stellar parameters on the basis of the obtained solutions, some empirical relations as well as the distance to the SMC. Several examples illustrate this procedure.Comment: 10 pages, 2 figures, accepte

Image Segmentation Based on Doubly Truncated Generalized Laplace Mixture Model and K Means Clustering

The present paper aims at performance evaluation of Doubly Truncated Generalized Laplace Mixture Model and K-Means clustering (DTGLMM-K) for image analysis concerned to various practical applications like security, surveillance, medical diagnostics and other areas. Among the many algorithms designed and developed for image segmentation the dominance of Gaussian Mixture Model (GMM) has been predominant which has the major drawback of suiting to a particular kind of data. Therefore the present work aims at development of DTGLMM-K algorithm which can be suitable for wide variety of applications and data. Performance evaluation of the developed algorithm has been donethrough various measures like Probabilistic Rand index (PRI), Global Consistency Error (GCE) and Variation of Information (VOI). During the current work case studies forvarious different images having pixel intensities has been carried out and the obtained results indicate the superiority of the developed algorithm for improved image segmentation

Free A*-algebras

In this paper we studied the free A*-algebras, the sub A*-algebra generated by a subset and its characterization, an A*-algebra freely generated by a subset and introduced the concept of A*-field of sets. Also we established some theorems on making A*-field of sets into A*-algebras

Estimation of the growth curve parameters in Macrobrachium rosenbergii

Growth is one of the most important characteristics of cultured species. The objective of this study was to determine the fitness of linear, log linear, polynomial, exponential and Logistic functions to the growth curves of Macrobrachium rosenbergii obtained by using weekly records of live weight, total length, head length, claw length, and last segment length from 20 to 192 days of age. The models were evaluated according to the coefficient of determination (R2), and error sum off square (ESS) and helps in formulating breeders in selective breeding programs. Twenty full-sib families consisting 400 PLs each were stocked in 20 different hapas and reared till 8 weeks after which a total of 1200 animals were transferred to earthen ponds and reared up to 192 days. The R2 values of the models ranged from 56 – 96 in case of overall body weight with logistic model being the highest. The R2 value for total length ranged from 62 to 90 with logistic model being the highest. In case of head length, the R2 value ranged between 55 and 95 with logistic model being the highest. The R2 value for claw length ranged from 44 to 94 with logistic model being the highest. For last segment length, R2 value ranged from 55 – 80 with polynomial model being the highest. However, the log linear model registered low ESS value followed by linear model for overall body weight while exponential model showed low ESS value followed by log linear model in case of head length. For total length the low ESS value was given by log linear model followed by logistic model and for claw length exponential model showed low ESS value followed by log linear model. In case of last segment length, linear model showed lowest ESS value followed by log linear model. Since, the model that shows highest R2 value with low ESS value is generally considered as the best fit model. Among the five models tested, logistic model, log linear model and linear models were found to be the best models for overall body weight, total length and head length respectively. For claw length and last segment length, log linear model was found to be the best model. These models can be used to predict growth rates in M. rosenbergii. However, further studies need to be conducted with more growth traits taken into consideratio

Profitability of Cotton on a Pest Management Continuum in Guntur District of Andhra Pradesh

The plant protection response of farmers in the Guntur district of Andhra Pradesh has been examined with particular reference to the adoption of Bt cotton varieties and IPM components. The farmers have been found to follow a wide range of practices to manage the insect pests in cotton. The use of chemical insecticides has accounted for, about 37 per cent of the total variable costs. No significant reduction in plant protection expenditure has been recorded on adoption of Bt varieties without IPM practices. The adoption of IPM practices, however, has led to reduced use of insecticides and increased profitability. The saving on plant protection chemicals has more than compensated the cost of adopting IPM components. Consequently, the net returns have been found increased considerably from cotton cultivation.Crop Production/Industries,

A new analytical method for determination of ledipasvir and sofosbuvir in pharmaceutical formulations by HPLC method

A simple, Accurate, precise method was developed for the simultaneous estimation of the Sofosbuvir and Ledipasvir in Tablet dosage form. Chromatogram was run through Std Discovery C8 150 x 4.6 mm, 5m. Mobile phase containing Buffer 0.1% OPA: Acetonitrile taken in the ratio 60:40 was pumped through column at a flow rate of 1 ml/min. Buffer used in this method was 0.1% OPA buffer. Temperature was maintained at 30°C. Optimized wavelength selected was 260 nm. Retention time of Sofosbuvir and Ledipasvir were found to be 2.367 min and 3.436 min. %RSD of the Sofosbuvir and Ledipasvir were and found to be 0.6 and 0.5 respectively. %Recovery was obtained as 99.61% and 99.80% for Sofosbuvir and Ledipasvir respectively. LOD, LOQ values obtained from regression equations of Sofosbuvir and Ledipasvir were 0.67, 2.02 and 0.70, 2.12 respectively. Regression equation of Sofosbuvir is y = 4266.x + 7700, and y = 4861.x + 2656.of Ledipasvir. Retention times were decreased and run time was decreased, so the method developed was simple and economical that can be adopted in regular Quality control test in Industries