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/.

Abstract

In building construction, RC frame structure are frequently used due to ease of construction and rapid progress of work. Generally these frames are filled by masonry in fill panel. However, during past earthquakes it was found that the performance of of such type of structures significantly depends on out-of-plane behavior of infill panel wall. In this study two type of infills are used i.e, unreinforced masonry infill and semi-interlocked masonry infill. For analysis purpose of infill, double strut nonlinear cyclic model is used. The main objective of the study is to investigate the importance interlocked brick infill in RC frame structure. For R factor components such as ductility reduction factor and over strength factors were computed from nonlinear static pushover analysis and finally response reduction factor is calculated for all models. In this work, primary focus is given to numerical modeling and nonlinear behavior of brick masonry building subjected to lateral loads and calculation of response reduction factor of RC infilled frame

Abstract

In this paper, Local Absorbing Boundary Conditions are presented for wave propagation through the viscoelastic media. This method is an extension of Local Absorbing Boundary Condition (ABC) proposed by Lysmer and Kuhlemeyer (1969). The proposed method does not converge for Kelvin type of viscoelastic materials but converges for Maxwell type of viscoelastic material model. This method is verified with 1D and 2D finite element models using explicit solver and the accuracy is compared with standard solutions. This study concluded that better responses can be obtained for the viscoelastic wave propagation using present approach when compared with traditional Local Absorbing Boundary Conditions. This study also concluded that the proposed method is suitable for low to medium viscous damping materials. For high viscous materials, the proposed method can be applied to transient wave propagation problems.

Abstract

Structural pounding may occur between two structures or at different parts of the same building during ground motions. Among all the structural damages, structural pounding has been commonly observed during several earthquakes in the past, which have lead to minor damage till complete collapse of the structure. The main focus of this paper is to study pounding responses and impact effects on structures subjected to ground motions. It is observed from the study that the response of stiff structure is more than flexible structure at dominant period of ground motion, irrespective of equal and unequal heights. If the structures vibrate at a non-dominant period of ground motion, then the response of flexible structure is observed more than the stiff structure.

Abstract

This paper is concerned with the study of effect of opening in infills on RC framed structures. Reinforced concrete buildings with masonry infill walls have been widely constructed for commercial, industrial, buildings. In this paper presents the results of analytical program showing behaviour of frames with different masonry infill i.e semi-interlocked masonry & Unreinforced masonry. The effect infill opening on seismic response of frame buildings were evaluated. A nonlinear static analysis has been carried out on different model frames by using finite element analysis software, seismostruct. The results obtained show that calculation of response reduction factor of RC infilled frames with & without opening on infill.

Abstract

Radiating boundary condition is an important consideration in the finite element modelling of unbounded media. Absorbing layer techniques such as Perfectly Matched Layers (PML) and Absorbing Layers by Increasing Damping (ALID) becoming popular as they are efficient in absorbing outward propagating waves energy. In this study, a comparative analysis has been carried out between PML and ALID+VABC (Absorbing Boundary conditions for Viscoelastic materials) methods. The methods are analyzed using LSDYNA explicit solver and the efficiency is compared with standard solutions. The study concluded that PML requires less number of elements to model the boundary conditions when compared with ALID+VABC. But PML requires a smaller element length which increases overall computational time. Both the methods are efficient in absorbing the wave energy. However, PML requires additional implementation cost to solve the complex equations.

Abstract

We developed a set of conformationally locked molecules each of which makes a single CH⋯O H-bond/short contact and has different electron density at the acceptor oxygen atom. The downfield shift of the 1H NMR signals due to the hydrogen involved in the CH⋯O H-bond varied from 0.93–1.6 ppm, and the magnitude of Δδ is in correlation with the hybridization state of the acceptor oxygen and with the CH⋯O H-bond strengths quantified using a computational method.