The impact of non-Gaussianity on the error covariance for observations of the Epoch of Reionization 21-cm power spectrum

For abstract see published article

ICT Based Agricultural Knowledge Transfer of Women Farmers: A Case of Gender Responsiveness from a Developing Country Perspective

Women are increasingly becoming an integral part of the rural economy. Feminization and empowerment in agriculture is taking place while outmigration of males in the rural Bangladesh is visible due to higher off farm income. The objective of this study is to determine the current state of the ICT-based agricultural knowledge transfer of female farmers in Bangladesh involved in agricultural operations. Data were collected through survey method using structured questionnaire from 140 female farmers involved in public ICT service centers of Bangladesh. The questionnaire was administrated face-to-face and collected data were analysed with SPSS version 23.0. The result from the data showed that the variables such as assets, inputs, land, education, extension and financial services, and technology affect farmers’ production and farm income. The gaps like gender parity and small farm holding were found in the study. The research suggests that effective agricultural information dissemination services through ICT tools in farming are essential. Special emphasis should be given to address gender disparity and resolve farm holding problems for ensuring women’s participation in agriculture

An Approach for Design Search Engine Architecture for Document Summarization

Query focused multi document summarization is an emerging area of research. A lot of work has already been done on the subject and a lot more is going on. The following document outlines the effort done by us in this particular field. This work proposes an approach to address automatic Multi Document text summarization in response to a query given by a user. For the explosion of information in the World Wide Web, this work proposed a new method of query-focused multi-documents summarization using genetic algorithm, search engine are used to extract relevant documents and genetic algorithm is used to extract the sentences to form a summary, and it is based on a fitness function formed by three factors: query-focused feature, importance feature, and non-redundancy feature. Experimental result shows that the proposed summarization method can improve the performance of summary, genetic algorithm is efficient. We have developed a very powerful search engine one. On the same note, it also has a great potential for growth. It can be easily applied for systems with not only a few documents but for very large systems with a large number of documents

Detecting galaxies in a large H{\sc i}~spectral cube

The upcoming Square Kilometer Array (SKA) is expected to produce humongous amount of data for undertaking H{\sc i}~science. We have developed an MPI-based {\sc Python} pipeline to deal with the large data efficiently with the present computational resources. Our pipeline divides such large H{\sc i}~21-cm spectral cubes into several small cubelets, and then processes them in parallel using publicly available H{\sc i}~source finder {\sc SoFiA-$2$}. The pipeline also takes care of sources at the boundaries of the cubelets and also filters out false and redundant detections. By comapring with the true source catalog, we find that the detection efficiency depends on the {\sc SoFiA-$2$} parameters such as the smoothing kernel size, linking length and threshold values. We find the optimal kernel size for all flux bins to be between $3$ to $5$ pixels and $7$ to $15$ pixels, respectively in the spatial and frequency directions. Comparing the recovered source parameters with the original values, we find that the output of {\sc SoFiA-$2$} is highly dependent on kernel sizes and a single choice of kernel is not sufficient for all types of H{\sc i}~galaxies. We also propose use of alternative methods to {\sc SoFiA-$2$} which can be used in our pipeline to find sources more robustly.Comment: 15 pages, 7 figures, Accepted for publication in the Special Issue of Journal of Astrophysics and Astronomy on "Indian Participation in the SKA'', comments are welcom

Interpreting the HI 21-cm cosmology maps through Largest Cluster Statistics -- I: Impact of the synthetic SKA1-Low observations

We analyse the evolution of the largest ionized region using the topological and morphological evolution of the redshifted 21-cm signal coming from the neutral hydrogen distribution during the different stages of reionization. For this analysis, we use the "Largest Cluster Statistics" - LCS. We mainly study the impact of the array synthesized beam on the LCS analysis of the 21-cm signal considering the upcoming low-frequency Square Kilometer Array (SKA1-Low) observations using a realistic simulation for such observation based on the 21cmE2E-pipeline using OSKAR. We find that bias in LCS estimation is introduced in synthetic observations due to the array beam. This in turn shifts the apparent percolation transition point towards the later stages of reionization. The biased estimates of LCS, occurring due to the effect of the lower resolution (lack of longer baselines) and the telescope synthesized beam will lead to a biased interpretation of the reionization history. This is important to note while interpreting any future 21-cm signal images from upcoming or future telescopes like the SKA, HERA, etc. We conclude that one may need denser $uv$-coverage at longer baselines for a better deconvolution of the array synthesized beam from the 21-cm images and a relatively unbiased estimate of LCS from such images.Comment: 37 pages, 14 figures, text revised, Comments are welcom