Birla Institute of Technology, Mesra

About: Birla Institute of Technology, Mesra is a education organization based out in Ranchi, India. It is known for research contribution in the topics: Computer science & Dielectric. The organization has 2801 authors who have published 4789 publications receiving 52426 citations. The organization is also known as: BIT.

Analysing the impact of anthropogenic activities on waterlogging dynamics in Indo-Gangetic Plains, northern Bihar, India

Abstract: Historical to recent spatial variability in surface waterlogging was evaluated using a topographical map of 1925 and satellite images of 1975, 1988, 1999 and 2006. A visual satellite image interpretation technique was used to delineate waterlogged areas and associated infrastructure details. Areas of 31, 73.89, 163.86, 143.61 and 102.59 km2 were found to be affected by surface waterlogging during 1925, 1975, 1988, 1999 and 2006, respectively. A sharp increase in waterlogging from 1925 to 1975 is attributed to the functioning of irrigation projects in the region. The very high areas under waterlogging during 1988 and 1999 reflect intensification of agricultural activity. A substantial decrease in waterlogging during 2006 is attributed to the implementation of government wasteland reclamation measures. The area statistics of waterlogging computed for the buffer zone along select features showed that the maximum waterlogging occurs along canals and railways followed by rivers and the least along roads.

Defect detection of steel surface using entropy segmentation

Abstract: Today, because of high manufacturing speed in steel industry, there is a need of fast and accurate detection of steel defect for quality assurance of product. Unlike other papers on defect detection of steel surface based on entropy this paper presents a new pre-processing and processing algorithm. The method presented here overcomes the limitations of traditional segmentation method or adaptive segmentation method like Otsu's method. This paper presents a new defect detection algorithm based on entropy. As a pre-processing step illumination compensation of image has been introduced using inverse illumination to remove non-uniformity of light intensity in the image. In the second part Local entropy of image has been used to detect the region of defect. The paper also suggests the concept of dynamic updation which helps to find a good background i.e. ideal steel surface and provides an effective method to classify the defects in its initial stage into defective and non-defective image. Background subtraction method is then used to extract the defective portion of image from the entropy image by comparing the entropy of image with the entropy of background image. Histogram thresholding method has been introduced to separate the background and defective portion in the background subtracted image to get the segmented image. The method was successfully tested on three kinds of defect on steel surface i.e. water droplet, blister and scratch.

A comprehensive optimization model for integrated solid waste management system: A case study

Abstract: Solid waste management (SWM) is one of the poorly rendered services in developing countries – limited resources, increasing population, rapid urbanization and application of outdated systems leads to inefficiency. Lack of proper planning and inadequate data regarding solid waste generation and collection compound the SWM problem. Decision makers need to formulate solutions that consider multiple goals and strategies. Given the large number of available options for SWM and the inter-relationships among these options, identifying SWM strategies that satisfy economic or environmental objectives is a complex task. The paper develops a mathematical model for a municipal Integrated SWM system, taking into account waste generation rates, composition, transportation modes, processing techniques, revenues from waste processing, simulating waste management as closely as possible. The constraints include those linking waste flows and mass balance, processing plants capacity, landfill capacity, transport vehicle capacity and number of trips. The linear programming model integrating different functional elements was solved by LINGO optimization software and various possible waste management options were considered during analysis. The model thus serves as decision support tool to evaluate various waste management alternatives and obtain the least-cost combination of technologies for handling, treatment and disposal of solid waste.