Abstract

In the present study an attempt has been made to study the 1D (One Dimensional), 2D (Two Dimensional) and 3D (Three Dimensional) ground response of pond ash collected from Odisha under different earthquake motions. 1D ground response analysis of pond ash deposit has been carried out by using equivalent linear and nonlinear analysis method using SHAKE2000 and Cyclic1D software respectively. 2D and 3D ground response analysis of pond ash deposit has been carried out by using finite element software Plaxis2D and Plaxis3D respectively. The response analyses of the pond ash deposit have been performed under the excitation of North East India earthquake (Mw-7.5) and Nepal earthquake (Mw-7.8). The results of the response analyses have been presented in terms of acceleration, displacement, excess pore pressure and excess pore pressure ratio. A comparative study between 1D, 2D and 3D ground response analysis has been performed to predict seismic risk of the pond ash site in Odisha.

Abstract

Utilization of fy ash, bottom ash and municipal solid waste in the feld of geotechnical engineering necessitates determination of its physical, chemical, morphological and engineering properties. This paper presents detailed physical, chemical and geotechnical characterization of fy ash, bottom ash and municipal solid waste from Telangana State in India. Fly ash and bottom ash samples were collected from Kakatiya thermal power station in India. Municipal solid waste (MSW) sample was collected from Borabanda municipal dump site in the city of Hyderabad, India. From the experimental results, it is noticed that specifc gravity of fy ash, bottom ash and municipal solid waste were found to be 1.86, 1.77 and 2.2 respectively. Presence of quartz and mullite; quartz, mullite and calcium carbonate; and quartz and corundum are found to be predominant in fy ash, bottom ash and MSW respectively. The peak friction angle of fy ash, bottom ash and municipal solid waste were found to be 37.02°, 33.77° and 35.23° respectively. Permeability characteristics of fy ash, bottom ash and municipal solid waste were observed to be 1.01E−04 cm/s, 2.01E−04 cm/s and 1.16E−04 cm/s respectively. From the observation of experimental results, it can be concluded that fyash, bottom ash and municipal solid waste from Telangana state are efective material to be used as backfll material, flter material and embankment construction

Abstract

Abstract In the current study laboratory experiments were conducted to elucidate the allelopathic and autotoxic effects of Parthenium hysterophorus, Senna uniflora and Hyptis suaveolens. The seed germination experiments were conducted using the leachates obtained from different organs of the three species. Ten grams, each of the plant materials were homogenized in 100 mL of quartz-distilled water for 24 hours, filtered and used as a stock solution of 100% concentration. From the stock solution, 25, 50 and 75% concentrations were prepared by diluting with quartz-distilled water. Three replicates with 30 seeds each for each plant species were maintained. Observations were made at regular intervals of 24 hours. The emergence of radicle was taken as the indicator of germination. Germination, root and shoot elongation was monitored for eight days. The study revealed inhibition of germination …

Abstract

The Kondapalli reserve forest (KRF) of the Eastern Ghats, India is subjected to severe anthropogenic interference, despite its status as reserve forest. The present research focuses on assessing the land use and land cover changes in and around KRF using temporal satellite data. It is evident from the current study that there has been a considerable decrease in the forest cover from 1990 to 2015; as seen from 2017 data, huge urban expansions and development activities were observed around KRF. This increase is linked to the growth in population, thereby consuming land available for their basic needs. To assess the rate of urban expansion around the forest, Land consumption rate and Land absorption coefficient were computed. The result of this analysis showed a rapid growth in built-up land between 1990 and 2017 while the periods between 1990 and 2015 witnessed a reduction in the forest class. Further

Abstract

Forest inventory parameters, primarily tree diameter and height, are required for several management and planning activities. Currently, Terrestrial Laser Scanning (TLS) is a promising technology in automated measurements of tree parameters using dense 3D point clouds. In comparison with conventional manual field inventory methods, TLS systems would supplement field data with detailed and relatively higher degree of accurate measurements and increased measurement frequency. Although, multiple scans from TLS captures more area, they are resource and time consuming to ensure proper co-registration between the scans. On the other hand, Single scans provide a fast and recording of the data but are often affected by occlusions between the trees. The current study evaluates potential of single scan TLS data to (1) develop an automatic method for tree stem identification and diameter estimation …

Abstract

Forest inventories are critical for effective management of forest resources. Recently, the use of terrestrial laser scanning (TLS) to automatically extract forest inventory parameters at tree level (eg tree location, diameter at breast height (DBH) and height) has gained significant importance. TLS using both single-scan and multi-scan techniques, not only helps in detailed and accurate measurements of tree objects but also helps increase the measurement frequency. In the current study, we develop an automated solution to extract forest inventory parameters at individual tree level from TLS data by using random sample consensus (RANSAC)-based circle fitting algorithm. The method was evaluated on both single-and multiscan data by characterizing four circular plots of radius 20 m in dry deciduous forests of Betul, Madhya Pradesh (India). Over all the plots, tree detection rates of 75% and 97% were obtained using single-and multi-scan TLS data respectively. Tree detection rates were significantly affected by increase in distance from the scanner, in single-scan approach when compared to multi-scan approach. Field based DBH measurements correlated well using both single (R2= 0.96) and multiple scans (R2= 0.99). The DBH estimates from multi-scan TLS data resulted in low root-meansquare error (RMSE) of 2.2 cm compared to that of 4.1 cm using single-scan. Further, tree heights were extracted from TLS data and validated with selectively measured trees on field (R2= 0.98; N= 65). The RMSE of tree height was estimated to be 1.65 m. The current results show the potential use of TLS in automatically deriving forest inventory parameters with …

Abstract

pgRouting library provides functions to compute shortest path between any two points of a road network which is of great demand and also a topic of interest in the field of GIS, graph theory and transportation. To compute path in a road network, pgRouting functions process the entire road network which is a major bottleneck when it comes to routing in large road networks leading to the requirement of large server resources. A reduction/compression in the input network that is to be processed for path computation would improve the performance of pgRouting. In this study a map generalization based network model is proposed which extracts a significantly smaller subset of the road network aka skeleton which further used to divide the network into zones, that shall be selectively used in path computation. This results in processing a much smaller part of the network to compute path between any two points leading to an overall improvement in query performance of pgRouting when computing path, especially on large road networks. As part of assessment of this approach and its applicability to large road networks, the paper presents an in-depth analysis of the trade-offs between deviation in computed path and the performance gain in terms of space and time on road networks of varying sizes and topology to get a better understanding for both providing a sound proof of the utility of the proposed method and also to show its implementability within the current model of pgRouting or any other routing platforms.

Abstract

Recent years has seen an increase in the work done on indoor data mapping and modeling. The standard data models provide different ways to store and access the indoor data but the way it is done is specific to the domain in which they are used. Although models like IFC, CityGML and IndoorGML provides rich functionality, the widespread availability of indoor data is not in these formats. This paper presents a step by step methodology to convert indoor building data of existing buildings, represented in architectural drawings into a topologically consistent and semantically rich indoor spatial model. The workflow presented consists of extracting relevant geometric entities from CAD drawings, assessing their topological relationships, using it to derive semantic information of spaces and making the data available in the form of IndoorGML. Since the current IndoorGML features lack the capability to store relevant semantic information, a semantic extension to IndoorGML is also proposed. The extraction of primitive spatial elements in rectilinear buildings like walls and doors are considered for the work presented in this paper. Development of a toolkit which implements this methodology in a seamless manner is work in progress and would incorporate extraction of complex spatial elements like staircases, ramps, curvilinear walls and windows, which is out of scope of the current work presented in this paper.

Abstract

Discovery of copy number variations (CNVs), a major category of structural variations, have dramatically changed our understanding of differences between individuals and provide an alternate paradigm for the genetic basis of human diseases. CNVs include both copy gain and copy loss events and their detection genome-wide is now possible using high-throughput, low-cost next generation sequencing (NGS) methods. However, accurate detection of CNVs from NGS data is not straightforward due to non-uniform coverage of reads resulting from various systemic biases. We have developed an integrated platform, iCopyDAV, to handle some of these issues in CNV detection in whole genome NGS data. It has a modular framework comprising five major modules: data pre-treatment, segmentation, variant calling, annotation and visualization. An important feature of iCopyDAV is the functional annotation module that enables the user to identify and prioritize CNVs encompassing various functional elements, genomic features and disease-associations. Parallelization of the segmentation algorithms makes the iCopyDAV platform even accessible on a desktop. Here we show the effect of sequencing coverage, read length, bin size, data pre-treatment and segmentation approaches on accurate detection of the complete spectrum of CNVs. Performance of iCopyDAV is evaluated on both simulated data and real data for different sequencing depths. It is an open-source integrated pipeline available at https://github.com/vogetihrsh/icopydav and as Docker’s image at http://bioinf.iiit.ac.in/icopydav/.

Abstract

Discovery of copy number variations (CNVs), a major category of structural variations, have dramatically changed our understanding of differences between individuals and provide an alternate paradigm for the genetic basis of human diseases. CNVs include both copy gain and copy loss events and their detection genome-wide is now possible using high-throughput, low-cost next generation sequencing (NGS) methods. However, accurate detection of CNVs from NGS data is not straightforward due to non-uniform coverage of reads resulting from various systemic biases. We have developed an integrated platform, iCopyDAV, to handle some of these issues in CNV detection in whole genome NGS data. It has a modular framework comprising five major modules: data pre-treatment, segmentation, variant calling, annotation and visualization. An important feature of iCopyDAV is the functional annotation module that enables the user to identify and prioritize CNVs encompassing various functional elements, genomic features and disease-associations. Parallelization of the segmentation algorithms makes the iCopyDAV platform even accessible on a desktop. Here we show the effect of sequencing coverage, read length, bin size, data pre-treatment and segmentation approaches on accurate detection of the complete spectrum of CNVs. Performance of iCopyDAV is evaluated on both simulated data and real data for different sequencing depths. It is an open-source integrated pipeline available at https://github.com/vogetihrsh/icopydav and as Docker’s image at http://bioinf.iiit.ac.in/icopydav/.