Showing posts with label peer reviewed journals. Show all posts
Showing posts with label peer reviewed journals. Show all posts

Thursday, 26 October 2017

Call For Paper | IJSRD Journal

Call For Paper | IJSRD Journal

Volume - 5 - Issue - 9 November 2017


ISSN (Online)  : 2321-0613
Subject Category : Engineering Science and Technology
Frequency            : Monthly, 12 issues per year
Impact Factor       : 4.396
IC Value               : 64.81



Submit Your Article : http://ijsrd.com/SubmitManuscript

Saturday, 1 November 2014

IJSRD & TechFest 2014-15 (IIT-Bombay) presents TISC(Conference)

conferenceTechfest International Student Conference is an initiative to bring together the student community and professors with a common research background. TISC marks a step further in our endeavor to promote science and technology among the students by facilitating the exchange of knowledge between academia and industry.
Featured imageTechfest International Student Conference presents a unique opportunity for students to present their work in front of fellow students, senior professors from top universities, industrialists and policy-makers. It aims at giving recognition to students for their research at a relatively young age. An enriching experience to research oriented minds, TISC will give young scientists an insight into the topic, learn new ideas and build networks beneficial for the future.
The theme for the conference is Renewable Energy Systems, potentially the most important aspect of human life in forthcoming decades. TISC is being hosted by IIT Bombay, one of the premier institutes of science and technology in India known for its path-breaking research and quality education.

Tuesday, 7 October 2014

A Glimpse into the 3-D brain | #IJSRD

People who wish to know how memory works are forced to take a glimpse into the brain. They can now do so without bloodshed: Ruhr Univ. Bochum (RUB) researchers have developed a new method for creating 3-D models of memory-relevant brain structures. They published their results in the trade journal Frontiers in Neuroanatomy.
3-D image of the hippocampus of a rat. Image
Lets Research !!! DO IT >>>> IJSRD
Seahorse gave the hippocampus the name
The way neurons are interconnected in the brain is very complicated. This holds especially true for the cells of the hippocampus. It is one of the oldest brain regions and its form resembles a seahorse (hippocampus in Latin). The hippocampus enables us to navigate space securely and to form personal memories. So far, the anatomic knowledge of the networks inside the hippocampus and its connection to the rest of the brain has left scientists guessing which information arrived where and when.
Signals spread through the brain
Accordingly, Dr. Martin Pyka and his colleagues from the Mercator Research Group at RUB have developed a method which facilitates the reconstruction of the brain's anatomic data as a 3-D model on the computer. This approach is quite unique, because it enables automatic calculation of the neural interconnection on the basis of their position inside the space and their projection directions. Biologically feasible network structures can thus be generated more easily than it used to be the case with the method available to date. Deploying 3-D models, the researchers use this technique to monitor the way neural signals spread throughout the network time-wise. They have, for example, found evidence that the hippocampus’ form and size could explain why neurons in those networks fire in certain frequencies.
Information become memories
In future, this method may help us understand how animals, for example, combine various information to form memories within the hippocampus, in order to memorise food sources or dangers and to remember them in certain situations.
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Friday, 15 August 2014

#IJSRD Optimization of Machining Parameters in CNC Turning Using Firefly Algorithm

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Optimization of Machining Parameters in CNC Turning Using Firefly Algorithm

Abstract— now a day’s machining is done through various automated machines. One of the widely used machines is CNC. Even though the automated machines are used, the quality of the work is determined by parameters used. The cutting parameters of the CNC machine determine the productivity, surface finish, machining time and other qualities of the product. This study involves the optimization of those cutting parameters. In order to get optimized CNC parameters for a specific tool-work combination, Firefly Algorithm (FA) is used to compute the best parameters based on the experiments conducted on a CNC Turning center. The three cutting parameters are cutting speed (V), feed (f), and depth of cut (d). The practical constraints have been considered during both practical and experimental approaches.  The result reveals that FA is very well suited in solving parameters selection problems. 
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