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

Ecological monitoring of trawling grounds

The development of mechanized fishing in India is traced to point out the harmful effects of trawling by way of disturbing the ecological balance of the ecosystem, of which the fish stocks are a part. It may cause the disappearance of some demersal species from the catches as brought out poignantly in the case of a marine catfish namely, Arius tenuispinis. History of trawling has been the same all over the world showing that depletion of demersal fish stocks is not only due to excessive harvesting but also due to the damage done to the ecological balance of the trawling grounds. The need for ecological monitoring of the trawling grounds is pointed out

Facile preparation of agarose-chitosan hybrid materials and nanocomposite ionogels using an ionic liquid via dissolution, regeneration and sol-gel transition

We report simultaneous dissolution of agarose (AG) and chitosan (CH) in varying proportions in an ionic liquid (IL), 1-butyl-3-methylimidazolium chloride [C4mim][Cl]. Composite materials were constructed from AG-CH-IL solutions using the antisolvent methanol, and IL was recovered from the solutions. Composite materials could be uniformly decorated with silver oxide (Ag2O) nanoparticles (Ag NPs) to form nanocomposites in a single step by in situ synthesis of Ag NPs in AG-CH-IL sols, wherein the biopolymer moiety acted as both reducing and stabilizing agent. Cooling of Ag NPs-AG-CH-IL sols to room temperature resulted in high conductivity and high mechanical strength nanocomposite ionogels. The structure, stability and physiochemical properties of composite materials and nanocomposites were characterized by several analytical techniques, such as Fourier transform infrared (FTIR), CD spectroscopy, differential scanning colorimetric (DSC), thermogravimetric analysis (TGA), gel permeation chromatography (GPC), and scanning electron micrography (SEM). The result shows that composite materials have good thermal and conformational stability, compatibility and strong hydrogen bonding interactions between AG-CH complexes. Decoration of Ag NPs in composites and ionogels was confirmed by UV-Vis spectroscopy, SEM, TEM, EDAX and XRD. The mechanical and conducting properties of composite ionogels have been characterized by rheology and current-voltage measurements. Since Ag NPs show good antimicrobial activity, Ag NPs -AG-CH composite materials have the potential to be used in biotechnology and biomedical applications whereas nanocomposite ionogels will be suitable as precursors for applications such as quasi-solid dye sensitized solar cells, actuators, sensors or electrochromic displays

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

A case study of the disappearance of Arius tenuispinis (marine catfish) in the vicinity of Visakhapatnam due to mechanised fishing

Visakhapatnam is on the eastern sea board of India (17 degree 40' N and 83 degree 15' E) having a continental shelf of 45 km width which is provided with a polychaete rich, silty clay sea floor to a distance of 15 km and beyond, from the shore. Repeated trawling by a large number of trawlers over an area of 900 sq.km (30 x 30) resulted in the hardening of the substratum to the extent of making it uninhabitable to the polychaetes and polychaete feeding fish. The shoaling and strictly demersal marine catfish, Arius tenuispinis, which is a prolific polychaete feeder on the fishing grounds off Visakhapatnam, has been on the decline since 1979. The catch rate of fish dropped from 9.7 kg/boat per day in 1979 to 2.6 kg by 1985-86. In the bottomset gillnets, the catch per net dwindled from 4.4 kg in 1973 to 0.04 kg by 1985-86. The species has virtually disappeared from the fishing grounds off Visakhapatnam and further north, as a results of the cumulative effect of overfishing with trawlnets and bottomset gillnets. It is further aggravated by the hardening of the sea floor on these grounds due to repeated trawling over a narrow zone

HIV/Aids epidemic in India and predicting the impact of the national response: mathematical modeling and analysis

After two phases of AIDS control activities in India, the third phase of the National AIDS Control Programme (NACP III) was launched in July 2007. Our focus here is to predict the number of people living with HIV/AIDS (PLHA) in India so that the results can assist the NACP III planning team to determine appropriate targets to be activated during the project period (2007-2012). We have constructed a dynamical model that captures the mixing patterns between susceptibles and infectives in both low-risk and high-risk groups in the population. Our aim is to project the HIV estimates by taking into account general interventions for susceptibles and additional interventions, such as targeted interventions among high risk groups, provision of anti-retroviral therapy, and behavior change among HIV-positive individuals. Continuing the current level of interventions in NACP II, the model estimates there will be 5.06 million PLHA by the end of 2011. If 50 percent of the targets in NACP III are achieved by the end of the above period then about 0.8 million new infections will be averted in that year. The current status of the epidemic appears to be less severe compared to the trend observed in the late 1990s. The projections based on the second phase and the third phase of the NACP indicate prevention programmes which are directed towards the general and high-risk populations, and HIV-positive individuals will determine the decline or stabilization of the epidemic. Model based results are derived separately for the revised HIV estimates released in 2007. We perform a Monte Carlo procedure for sensitivity analysis of parameters and model validation. We also predict a positive role of implementation of anti-retroviral therapy treatment of 90 percent of the eligible people in the country. We present methods for obtaining disease progression parameters using convolution approaches. We also extend our models to age-structured populations

A frictional Cosserat model for the flow of granular materials through a vertical channel

A rigid-plastic Cosserat model has been used to study dense, fully developed flow of granular materials through a vertical channel. Frictional models based on the classical continuum do not predict the occurrence of shear layers, at variance with experimental observations. This feature has been attributed to the absence of a material length scale in their constitutive equations. The present model incorporates such a material length scale by treating the granular material as a Cosserat continuum. Thus localised couple stresses exist and the stress tensor is asymmetric. The velocity profiles predicted by the model are in close agreement with available experimental data. The predicted dependence of the shear layer thickness on the width of the channel is in reasonable agreement with data. In the limit of the ratio of the particle diameter to the half-width of the channel being small, the model predicts that the shear layer thickness scaled by the particle diameter grows.Comment: 17 pages, 12 PostScript figures, uses AmsLaTeX, psfrag and natbib. Accepted for publication in Acta Mechanic