Jibitesh Mishra

Bio: Jibitesh Mishra is an academic researcher from Biju Patnaik University of Technology. The author has contributed to research in topics: Fractal & Fractal dimension. The author has an hindex of 14, co-authored 74 publications receiving 564 citations. Previous affiliations of Jibitesh Mishra include Central Institute of Freshwater Aquaculture & Techno India.

An improved method to estimate the fractal dimension of colour images

Abstract: Summary Fractal dimension (FD) is an important feature of fractal geometry has many applications in various fields including image processing, image analysis, texture segmentation, shape classification and identifying the image features such as roughness and smoothness of an image. There are many techniques to estimate the dimension of fractal surface. The famous technique to calculate fractal dimension is the grid dimension method, which is popularly known as box counting method and some of the other improved methods like differential box counting and improved differential box counting method are used to estimate fractal dimension of grayscale images. The usual way of estimating the roughness or FD of color image involves two steps: (i) converting color image to grayscale and (ii) finding the roughness of generated grayscale image. But due to this conversion, significant color information is lost and leads to inaccurate roughness estimation. To avoid such inaccuracy this paper proposes the development and study of novel technique for estimating fractal dimension of color images. In this study, the improved differential box counting method is applied to the 24 bit representation of RGB color images to extract the roughness of color images. The validation of the proposal is performed by generating twelve different synthesized color images in terms of small variation of intensity value in RGB space and compared with previously three well defined existing methods that are weighted sum, average and desaturation method. The results showed that our proposed method is able to capture the accurate sharp variation of roughness as compared to the existing methods.

Economic Commission for Europe

Abstract: In 2018, the Finnish economy grew by 1.7 percent. According to the quarter-to-quarter figures, the economic growth decelerated, and in the last quarter of the year the growth was no more than 0.1 percent compared to the third quarter. Even though the private consumption still sustained economic growth, the main reason for the economic slowing down was the poor performance of exports, the growth rate of which fell by 6.5 percentage points from the previous year and remained only at 1.1 percent on annual bases. Also, the investment activity slowed down together with the increasing risks and uncertainties concerning global economic environment.

Global patterns of tropical forest fragmentation

Abstract: Remote sensing enables the quantification of tropical deforestation with high spatial resolution. This in-depth mapping has led to substantial advances in the analysis of continent-wide fragmentation of tropical forests. Here we identified approximately 130 million forest fragments in three continents that show surprisingly similar power-law size and perimeter distributions as well as fractal dimensions. Power-law distributions have been observed in many natural phenomena such as wildfires, landslides and earthquakes. The principles of percolation theory provide one explanation for the observed patterns, and suggest that forest fragmentation is close to the critical point of percolation; simulation modelling also supports this hypothesis. The observed patterns emerge not only from random deforestation, which can be described by percolation theory, but also from a wide range of deforestation and forest-recovery regimes. Our models predict that additional forest loss will result in a large increase in the total number of forest fragments-at maximum by a factor of 33 over 50 years-as well as a decrease in their size, and that these consequences could be partly mitigated by reforestation and forest protection.

The hypothalamic-pituitary-thyroid (HPT) axis in fish and its role in fish development and reproduction.

Abstract: Bony fishes represent the largest vertebrate class and are a very diverse animal group. This chapter provides a thorough review of the available scientific literature on the thyroid system in these important vertebrate animals. The molecular components of the hypothalamic-pituitarythyroid (HPT) axis in this group correspond closely to those of mammals. The thyroid tissue in the fishes is organized as diffuse follicles, with a few exceptions, rather than as an encapsulated gland as is found in most other vertebrate species. The features of this diffuse tissue in fishes are reviewed with an emphasis on feedback relationships within the HPT axis, the molecular biology of the thyroid system in fishes, and comparisons versus the thyroid systems of other vertebrate taxa. A review of the role of thyroid hormone in fish development and reproduction is included. Available information about the HPT axis in fishes is quite detailed for some species and rather limited or absent in others. This review focuses on species that have been intensively studied for their value as laboratory models in assays to investigate disruption in normal function of the thyroid system. In addition, in vitro and in vivo assay methods for screening chemicals for their potential to interfere with the thyroid system are reviewed. It is concluded that there are currently no in vitro or in vivo assays in fish species that are sufficiently developed to warrant recommendation for use to efficiently screen chemicals for thyroid disruption. Methods are available that can be used to measure thyroid hormones, although our ability to interpret the causes and implications of potential alterations in T4 or T3 levels in fishes is nonetheless limited without further research.