Heritage Institute of Technology
About: Heritage Institute of Technology is a(n) based out in . It is known for research contribution in the topic(s): Steganography & Support vector machine. The organization has 581 authors who have published 1045 publication(s) receiving 8345 citation(s).
Papers published on a yearly basis
TL;DR: The solution obtained by the decomposition method has been numerically evaluated and presented in the form of tables and then compared with those obtained by truncated series method.
Abstract: The aim of the present analysis is to apply Adomian decomposition method for the solution of a nonlinear fractional differential equation. Finally, the solution obtained by the decomposition method has been numerically evaluated and presented in the form of tables and then compared with those obtained by truncated series method. A good agreement of the results is observed.
TL;DR: An Empirical Mode Decomposition (EMD) based ECG signal enhancement and QRS detection algorithm is proposed and a single fold processing of each signal is required unlike other conventional techniques.
Abstract: In this paper an Empirical Mode Decomposition (EMD) based ECG signal enhancement and QRS detection algorithm is proposed. Being a non-invasive measurement, ECG is prone to various high and low frequency noises causing baseline wander and power line interference, which act as a source of error in QRS and other feature extraction. EMD is a fully adaptive signal decomposition technique that generates Intrinsic Mode Functions (IMF) as decomposition output. Here, first baseline wander is corrected by selective reconstruction based slope minimization technique from IMFs and then high frequency noise is removed by eliminating a noisy set of lower order IMFs with a statistical peak correction as high frequency noise elimination is accompanied by peak deformation of sharp characteristic waves. Then a set of IMFs are selected that represents QRS region and a nonlinear transformation is done for QRS enhancement. This improves detection accuracy, which is represented in the result section. Thus in this method a single fold processing of each signal is required unlike other conventional techniques.
01 Feb 2012-Chemical Engineering Journal
TL;DR: In this article, the adsorptive removal of Methylene Blue (MB) dye using a low cost adsorbent, prepared from Parthenium hysterophorus, has been investigated.
Abstract: The adsorptive removal of Methylene Blue (MB) dye using a low cost adsorbent, prepared from Parthenium hysterophorus, has been investigated. Response Surface Methodology has been employed to model statistically and optimize the process variables for preparation of adsorbent, removal of MB and recovery of adsorbed dye using Design Expert software. During optimization of carbonizing condition, weight ratio of activating agent to parthenium (1.0–1.5), temperature (450–550 °C) and time of carbonization (1–2 h) have been considered as input parameters and decolorizing power (DP) of prepared sample is regarded as response. The carbonization at 550 °C for 1 h, with a weight ratio of activating agent to parthenium at 1.05:1 has been found to be optimum condition. The sample thus obtained is termed as Charred Parthenium (CP) and is used for further studies on dye removal. To get the optimum condition for removal of dye using CP, four input parameters viz., initial concentration of dye (25–50 mg/L), weight of CP (0.2–0.5 g), pH (5–9) and temperature (30–40 °C) have been varied according to the experimental design as prescribed by software considering percentage removal of dye as response. The removal with initial concentration of MB 25 mg/L, weight of CP 0.22 g at pH 7 and temperature 35 °C has been found to be optimum and 93.4% removal is achieved. Finally, the spent adsorbent, termed as Spent Charred Parthenium (SCP), obtained at the optimum condition of dye removal has been taken to assess the recovery of dye. Three parameters viz., amount of SCP (0.2–0.5 g), pH (5–9) and contact time (1–3 h) have been chosen as input parameters whereas percentage recovery has been considered as response. The results indicate that pH has a great influence on the recovery of dye.
TL;DR: Test results reveal that three-level Haar feature set is more promising to address the problem of automatic defect detection on hot-rolled steel surface than the other wavelet feature sets as well as texture-based segmentation or thresholding technique of defect detection.
Abstract: Automatic defect detection on hot-rolled steel surface is challenging owing to its localization on a large surface, variation in appearance, and their rare occurrences. It is difficult to detect these defects either by physics-based models or by small-sample statistics using a single threshold. As a result, this problem is focused to derive a set of good-quality defect descriptors from the surface images. These descriptors should discriminate the various surface defects when fed to suitable machine learning algorithms. This research work has evaluated the performance of a number of different wavelet feature sets, namely, Haar, Daubechies 2 (DB2), Daubechies 4 (DB4), biorthogonal spline, and multiwavelet in different decomposition levels derived from 32 × 32 contiguous (nonoverlapping) pixel blocks of steel surface images. We have developed an automated visual inspection system for an integrated steel plant to capture surface images in real time. It localizes defects employing kernel classifiers, such as support vector machine and recently proposed vector-valued regularized kernel function approximation. Test results on 1000 defect-free and 432 defective images comprising of 24 types of defect classes reveal that three-level Haar feature set is more promising to address this problem than the other wavelet feature sets as well as texture-based segmentation or thresholding technique of defect detection.
TL;DR: An attempt has been made to obtain the solution of Bagley–Torvik equation by the relatively new Adomian decomposition method and a good agreement of the results is observed.
Abstract: The fractional derivative has been occurring in many physical problems such as frequency dependent damping behavior of materials, motion of a large thin plate in a Newtonian fluid, creep and relaxation functions for viscoelastic materials, the PI λ D μ controller for the control of dynamical systems, etc. Phenomena in electromagnetics, acoustics, viscoelasticity, electrochemistry and material science are also described by differential equations of fractional order. The solution of the differential equation containing fractional derivative is much involved. Instead of application of the existing methods, an attempt has been made in the present analysis to obtain the solution of Bagley–Torvik equation [R.L. Bagley, P.J. Torvik, On the appearance of the fractional derivative in the behavior of real materials, ASME J. Appl. Mech., 51 (1984) 294–298; I. Podlubny, Fractional Differential Equations, Academic Press, San Diego, CA, USA, 1999] by the relatively new Adomian decomposition method. The results obtained by this method are then graphically represented and then compared with those available in the work of Podlubny [I. Podlubny, Fractional Differential Equations, Academic Press, San Diego, CA, USA, 1999]. A good agreement of the results is observed.
Showing all 581 results
|S. Saha Ray||34||217||3888|
|Mrinal K. Ghosh||26||64||2243|
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