Heritage Institute of Technology

About: Heritage Institute of Technology is a based out in . It is known for research contribution in the topics: Support vector machine & Transconductance. The organization has 581 authors who have published 1045 publications receiving 8345 citations.

Analytical approaches for the approximate solution of a nonlinear fractional ordinary differential equation

Abstract: The aim of the present analysis is to apply the Adomian decomposition method and He's variational method for the approximate analytical solution of a nonlinear ordinary fractional differential equation. The solutions obtained by the above two methods have been numerically evaluated and presented in the form of tables and also compared with the exact solution. It was found that the results obtained by the above two methods are in excellent agreement with the exact solution. Finally, a surface plot of the approximate solutions of the fractional differential equation by the above two methods is drawn for 0≤t≤2 and 1<α≤2.

Probabilistic exact deletion and probabilistic no-signalling

Abstract: In this work we show that one cannot use non-local resources for probabilistic signalling even if one can delete a quantum state with the help of probabilistic quantum deletion machine. Here we find that probabilistic quantum deletion machine is not going to help us in identifying two statistical mixture at remote location. Also we derive the bound on deletion probability from no-signalling condition.

A modified approach of identification and tracking of heart boundary from MRI image sequences

Abstract: In the present work, a robust algorithm for automatic identification and segmentation of heart portion from cardiac Magnetic Resonance video Image (MRI) is presented. At first, an outline has been generated to get the region of interest (ROI) by employing the moving object criterion, which eventually reduces the processing time significantly. In the next step, Expectation Maximization (EM) algorithm is used to segment the grey scale images into 5 distinct regions. This is done to make them more suitable for further processing and easy to use in the developed software. Finally Level set algorithm added with automatic contour generation module is used for tracking the exact heart boundary to segment it out from the rest of the image. This algorithm gives equally persistent result for both long axis and shot axis cardiac MRI data consisting of a movie (in AVI format) containing 32 separate frames of grayscale images.

Gene Ranking: A Novel Approach Using Multi-Objective Genetic Algorithm

Abstract: In a Gene Co-expression Network, the same or closely related genes are clustered into co-expressed groups. It is necessary to investigate the role that these genes play as far as some complex diseases like cancer are concerned in those networks. Ranking those genes actually discover the significant candidate genes for various types of cancers. There are several gene ranking algorithms proposed so far that produces the top ranked genes according to their importance with respect to a particular cancer disease. In this work, we apply multi-objective genetic algorithm, Multi-ObjectiveNetworkGA, on a gene coexpression network to find the top ranked cancer mediating genes. The algorithm is applied to publicly available real-life cancer datasets taken from NCBI (National Centre for Biotechnology Information) biological online repository. The performance of the algorithm is justified by classification using SVM classifier with linear kernel and it is compared with state-of-the-art methods on the basis of percentage of accuracy, precision, recall, and F1-Score.

Post-disaster Situational Awareness and Resource Management Services

Abstract: The previous chapter provides the details of developing map-based navigation services in the affected areas over opportunistic networks. The solution to the two other important post-disaster services such as situational awareness and resource management are discussed in this chapter. As mentioned earlier both of these services are invariably dependent on the existence of navigation support. Precisely, without the map-based navigation services not only the volunteers are unable to reach the affected areas to gather situational information but also would fail to identify the exact routes toward resource inventories in such a scenario.