National Institute of Technology, Raipur

About: National Institute of Technology, Raipur is a education organization based out in Raipur, Chhattisgarh, India. It is known for research contribution in the topics: Computer science & Fault (power engineering). The organization has 1549 authors who have published 3229 publications receiving 25258 citations. The organization is also known as: NIT Raipur & Govt. College of Mining & Metallurgy.

Reliable and Accurate Calcium Volume Measurement in Coronary Artery Using Intravascular Ultrasound Videos

Abstract: Quantitative assessment of calcified atherosclerotic volume within the coronary artery wall is vital for cardiac interventional procedures. The goal of this study is to automatically measure the calcium volume, given the borders of coronary vessel wall for all the frames of the intravascular ultrasound (IVUS) video. Three soft computing fuzzy classification techniques were adapted namely Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) for automated segmentation of calcium regions and volume computation. These methods were benchmarked against previously developed threshold-based method. IVUS image data sets (around 30,600 IVUS frames) from 15 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/s). Calcium mean volume for FCM, K-means, HMRF and threshold-based method were 37.84?±?17.38 mm3, 27.79?±?10.94 mm3, 46.44?±?19.13 mm3 and 35.92?±?16.44 mm3 respectively. Cross-correlation, Jaccard Index and Dice Similarity were highest between FCM and threshold-based method: 0.99, 0.92?±?0.02 and 0.95?+?0.02 respectively. Student's t-test, z-test and Wilcoxon-test are also performed to demonstrate consistency, reliability and accuracy of the results. Given the vessel wall region, the system reliably and automatically measures the calcium volume in IVUS videos. Further, we validated our system against a trained expert using scoring: K-means showed the best performance with an accuracy of 92.80?%. Out procedure and protocol is along the line with method previously published clinically.

Fault classification of phase to phase fault in six phase transmission line using Haar wavelet and ANN

Abstract: This paper presents a fault classification technique based on Haar Wavelet Transform (WT) and Artificial Neural Network (ANN) for six phase transmission line against phase to phase faults. The approximation & detailed coefficients of voltage & current signals are extracted using Haar WT. The standard deviation (SD) of approximated coefficient of voltage & current samples is used as input to the neural network for classification purpose. Six phase transmission line is modeled and the proposed protection technique has been developed using the Simulink® and Simpowersystem® toolboxes of MATLAB®7.01. The effect of variation of fault parameters such as fault distance location, resistance and inception angle are also considered. The simulation result of Haar WT and ANN based fault classifier is presented in this paper. This has been discovered that the proposed method classifies all types of phase-to-phase fault accurately. Thus simulation results demonstrate the suitability and effectiveness of the proposed algorithm.

Investigating the role of metallic fillers in particulate reinforced flexible mould material composites using evolutionary algorithms

Abstract: To reduce the cooling time in soft tooling (ST) process, high thermal conductive fillers (such as metallic filler) are included in flexible mould material. But addition of metallic fillers affects various properties of ST process and the influences may vary according to the types of materials used. Therefore, in order to investigate the role of various metallic fillers in particulate reinforced flexible mould material composites, multi-objective optimizations of maximizing equivalent thermal conductivity and minimizing effective modulus of elasticity of composite mould materials are conducted using evolutionary algorithms (EAs). Here we have adopted two EA-based algorithms namely NSGAII and SPEA2 in order to solve the present problem independently. Comparative study of the results reveals that NSGAII performs better over SPEA2 for investigating the role of metallic fillers in particulate reinforced flexible mould material composites. A recently proposed innovization procedure is also used to unveil salient properties associated with the obtained trade-off solutions. These solutions are analyzed to study the role of various parameters influencing the equivalent thermal conductivity and modulus of elasticity of the composite mould material. Based on the findings through investigations, the optimal selection of materials is suggested including the cost implication factor.

Synthesis and characterization of Eu 3+ -doped Y 2 O 3 phosphor

Abstract: The present paper reports on the synthesis and photoluminescence (PL) and thermoluminescence (TL) studies of Eu3+-doped Y2O3 phosphor using inorganic materials like yttrium oxide (Y2O3) and europium oxide (Eu2O3). The sample was prepared by the conventional solid state reaction method, which is the most suitable for large-scale production. The received phosphor sample was characterized using XRD, PL, TL, and CIE techniques. For the Y2O3 phosphor doped with Eu3+, the PL emission was observed in the 200–650 nm range. The excitation spectrum was found at 256 nm. Sharp peaks were found around 365, 469, 534, and 612 nm with high intensity. From the XRD data, using Scherer’s formula, the calculated average crystallite size of Eu3+-doped Y2O3 phosphor is around 205 nm. The thermoluminescence study was carried out for the phosphor with UV and beta irradiation. The present phosphor can act as a single host for red light emission in display devices.