Sri Ramakrishna Engineering College

About: Sri Ramakrishna Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Control theory. The organization has 1030 authors who have published 843 publications receiving 3822 citations.

Hazard Identification & Risk Assesment in New Chassis Assembly Line

Abstract: Chassis assemblies in any automobile industries are vulnerable to several hazards. In order to reduce the hazards we need to study and carry out Hazard Identification & Risk Assessment in New Chassis assembly to provide engineering solutions for preventing Accidents / dangerous occurrences and to evaluate the Risk. We have conducted many inspections and observation in the chassis assembly of an automobile industry. From our observations and findings we identified nearly 20 intolerable risks in the chassis line, for which the intolerable risks are converted into tolerable through small projects and those which cannot be converted are reduced through Safe Job Procedures (SJP). All the significant risks are controlled by Occupational Health & Safety Management Program, Standard operating procedures & Operation Control Procedure. From the project, the hazard is minimized or eliminated which ensures safety in the assembly line as well as the safety of workers.

Nanomaterials, Properties and Applications

Abstract: Nanomaterials size range from 1 to 100 nm with unique optical, electrical, magnetic, mechanic and structural properties. There are some naturally occurring nanomaterials (viruses, protein, lotus leaf, spider-mite silk, and butterfly wings etc.) and more engineered nanomaterials (Au NPs, Ag NPs, etc.) with top-down and bottom-up approaches. The chapter detailed about properties and applications of nanomaterials.

Reverse Search Strategy Based Optimization Technique to Economic Dispatch Problems with Multiple Fuels

Abstract: This research article constitutes an efficient way to extract the minimum fuel cost for the economic dispatch problem considering multiple fuel options along with valve point effects. In general one convex cost function for one generator is assumed. The piecewise quadratic cost function is represented by selecting the convex cost function more than one for a generator. A new approach referred as Power Search Algorithm (PSA) based on reverse search strategy is suggested along with various constraints in ED. The proposed algorithm has been evaluated on a ten unit multi-fuel system for various power demands with different fuel input options. The outcomes acquired from the simulation are of good quality and furthermore it reveals that the proposed algorithm performs superior than the various algorithms discussed.

Design and implementation of truncated multipliers for precision improvement

Abstract: Truncated multipliers offers significant improvements in area, delay, and power. The proposed method finally reduces the number of full adders and half adders during the tree reduction. While using this proposed method experimentally, area can be saved. The output is in the form of LSB and MSB. Finally the LSB part is compressed by using operations such as deletion, reduction, truncation, rounding and final addition. In previous related papers, to reduce the truncation error by adding error compensation circuits. In this project truncation error is not more than 1 ulp (unit of least position). So there is no need of error compensation circuits, and the final output will be precised.

Assessment of Extended MNIST (EMNIST) dataset using Capsule Networks

Abstract: Image recognition is always been a most seek able research topic for many years. There is a development to compare various models with more datasets because of the novelty that is exhibited in each architecture. In this paper, we compare three models AlexNet, VGGNet and GoogleNet with Capsule Networks for the Extended MNIST dataset. We also illustrate the goodness of previous model inspite of the lack in accuracy. We have showed the highest accuracy produced by the capsule network in object detection.