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.

A Modified Continuous Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem

Abstract: A continuous version of particle swarm optimization (CPSO) is employed to solve uncapacitated facility location (UFL) problem which is one of the most widely studied in combinatorial optimization. The basic algorithm had already been published in the Research Article “A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem” [1]. But in addition to that, the algorithm is slightly modified here to get better result in a lesser time. To make a reasonable comparison, the same benchmark suites that are collected from OR-library [6] are applied here. In conclusion, the results showed that this modified CPSO algorithm is slightly better than the published CPSO algorithm.

Unconventional localization phenomena in a spatially non-uniform disordered material

Abstract: A completely opposite behavior of electronic localization is revealed in a spatially non-uniform disordered material compared to the traditional spatially uniform disordered one. This fact is substantiated by considering an order-disorder separated (ODS) nanotube and studying the response of non-interacting electrons in presence of magnetic flux . We critically examine the behavior of flux induced energy spectra and circular current for different band fillings, and it is observed that maximum current amplitude (MCA) gradually decreases with disorder strength for weak disorder regime, while surprisingly it (MCA) increases in the limit of strong disorder suppressing the effect of disorder, resulting higher conductivity . This is further confirmed by investigating Drude weight and exactly same anomalous feature is noticed. It clearly gives a hint that localization-to-delocalization transition (LTD) is expected upon the variation of disorder strength which is justified by analyzing the nature of different eigenstates. Our analysis may give some significant inputs in analyzing conducting properties of different doped materials.

Two-warehouse production inventory model for a deteriorating item with time-varying demand and shortages: a genetic algorithm with varying population size approach

Abstract: A production-inventory model for a deteriorating item with time-varying demand and fully backlogged shortages is developed for a two warehouse system. For display and storage of inventory, management hires one warehouse of finite capacity at the market place, called own warehouse abbreviated as OW and another warehouse with large capacity as it may be required at a distance place from the market, called rented warehouse abbreviated as RW. Though the time of transporting items from RW to OW is ignored the transportation cost for transporting items is taken to be dependent on the transported amount. Here the objective is to minimize the total cost for a finite planning horizon. A genetic algorithm (GA) is designed to determine the optimum number of production cycles and the cycle times within a finite planning horizon. In this GA a subset of better children is included with the parent population for next generation and size of this subset is a percentage of the size of its parent set. Performance of this GA with respect to some other GAs is compared. Two particular cases (i) with non-deteriorating items and (ii) without shortages are also investigated. Finally, to illustrate the model and to show the effectiveness of the proposed approach, a numerical example is provided. With respect to the demand parameters, a sensitivity analysis is performed and presented. In this paper, we have pointed out that the expression of Lee and Hsu (2009) can be obtained as a particular case.

Development of graphene oxide/chitosan composite membrane on ceramic support for atrazine remediation by MBR process

Abstract: Graphene oxide (GO)-based composite ultrafiltration (UF) membranes were prepared on macroporous ceramic support tubes following a new way. Chitosan was used as an intermediate matrix between the substrate and GO coating. It has hydroxyl and amine groups, which enhances its film forming capacity with hydrophilic GO. This led us to use them as precursors for membrane development. Process efficiency of the prepared UF membrane was assessed in terms of the removal of toxic pesticide atrazine in side-stream membrane bioreactor (MBR) processes. Response surface methodology (RSM) was used to optimize the atrazine biodegradation efficiency. Enhanced atrazine removal of > 95% was obtained in the MBR treatment at the optimized conditions. Hermia’s model equations were applied to analyze the mechanism of membrane fouling in the UF-MBR system. The influencing parameters were studied in details and pneumatic backpulsing was applied to minimize fouling in the UF-MBR system by statistical analysis. Mixed liquor suspended solids (MLSS) was found to affect both atrazine biodegradation and membrane fouling; hence, its effect was thoroughly analyzed. The developed process hence proved to be highly proficient in terms of such organic pesticides removal for long-term operations.

Voronoi based location aware collaborative filtering

Abstract: Recommender systems help users in making decisions by recommending items of interest like movies, music, books, news, images, web pages, etc. to them. Collaborative filtering is one of the most widely studied and widely used techniques behind recommendation algorithms. It tries to recommend items to users based on user-user or item-item similarities computed from existing data. In this work, we propose a recommendation algorithm that takes the user's location into account. The algorithm uses Voronoi Diagrams which are widely used in Computational Geometry to decompose a metric space into regions based on distances from a specified finite set of points. We have tested the algorithm on the MovieLens dataset.