Drmgr Educational And Research Institute University

Chennai, India

Drmgr Educational And Research Institute University

Chennai, India
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Mohanavel V.,St Peters University | Rajan K.,Drmgr Educational And Research Institute University | Senthil P.V.,St Peters University
Materials Today: Proceedings | Year: 2017

The lineage of applied materials science is always in demand for light weight and highly performing materials. Such materials would find their applications in structural, non-structural, marine, automobile and aerospace industries. In the present investigation, an aluminum alloy AA6351 was reinforced with different percentages (0, 4 and 8 wt%) of TiB2 particles which were effectively fabricated by exothermic reaction of inorganic salts, potassium hexafluoro-titanate and potassium tetrafluoro-borate, with molten aluminium melt to bringout unprecedented properties. Tensile strength, yield strength, compression strength, microhardness and macrohardness of the composite were examined. In situ reaction between the halide salts K2TiF6 and KBF4 and molten aluminum leads to the formation of TiB2 particles. The produced aluminum matrix composites were characterized using X-ray diffraction, optical microscope and scanning electron microscope. Scanning electron photomicrographs exhibited a homogeneous dispersal of TiB2 particles in the aluminum matrix. The test results revealed that the Al/8wt% TiB2 MMCs had exhibited higher hardness, tensile, compression strength than the plain matrix alloy. © 2017 Elsevier Ltd. All rights reserved.


Mohanavel V.,St Peters University | Rajan K.,Drmgr Educational And Research Institute University | Senthil P.V.,St Peters University
Materials Today: Proceedings | Year: 2017

In the current scenario, particulate reinforced aluminium matrix composites present a plenty of applications to aircraft, marine, structural, transportation and automobile industries. This article deals with the fabrication of hybrid AA6351 aluminium matrix composites which incorporates stir casting route. In the process of fabrication AA6351 is reinforced in which Al2O3 and Gr are the hybriding materials.The microstructure and the mechanical behavior of the parent alloy and the produced composites were studied. The reinforcing effect of Al2O3/Gr combined with the parent alloy is studied wherein the investigation went into the intensity of macrohardness, microhardness, tensile strength and flexural strength. Optical microscope was adapted for characterizing the composites. Optical microscope observed the particle distribution of the produced composites. Optical microphotographs depict the nearly homogeneous distribution of the reinforcement particles in the base metal matrix. The hardness, thetensile strength and the flexural strength are found to increase in the AA6351 base matrix alloy with the increase in reinforcement. The mechanical properties of the AA6351 alloy are significantly improved after the dispersion of Al2O3/Gr particles. © 2017 Elsevier Ltd. All rights reserved.


Vinu Kiran S.,Apollo Computer | Prasanna Devi S.,Apollo Computer | Manivannan S.,Drmgr Educational And Research Institute University
Procedia Computer Science | Year: 2016

Agricultural geography is one of the subportion of human and our economic geography which examines the primary, secondary, tertiary and quaternary yield types activities that are carried out in agriculture. In this paper, we are examining the spatial distribution and concentration of crops and their yields along with their crop periods using Big data Analytics to find out the cropping patterns and combinations that varies in space and time. Our primary objective is to findout the crop associations and patterns under climatic influence for each geographical segmentation, to give better yeilds. The Big data analytic based association won't to last as many of the farmers and scientists are rightly challenging over the agricultural sustainability. However, there is a strong possibility of the farmers to adopt a new combination in the coming decades as the Big data analytic based crop pattern decision facilitates the farmers, always try to optimize their agricultural re-turns and adopt new innovations which gives better yeilds since we are performing factual data centric analytics. © 2016 The Authors.


Srinivasan R.,Dr. M.G.R. Educational and Research Institute | Manivannan S.,Drmgr Educational And Research Institute University | Ethiraj N.,Drmgr Educational And Research Institute University | Prasanna Devi S.,Apollo Computer | Vinu Kiran S.,Apollo Computer
Procedia Computer Science | Year: 2016

As the industrial revolution started, the complexity of new products in manufacturing as well as fleet industry has improved to meet the ever increasing needs and expectations of successful business. Degradation of Products due to age and/or operational usage and failures when they are unable to carry out their normal functions. The product had a n-year warranty and these warranty data is available for all applicable units in an organization. Data on essentially all failures was available for the initial level of operation on all units. A large set of data on Warranty among operational units contains useful information about product quality and reliability. They are available as coarse data because most often they are aggregated values, delayed reports, filtered, missing or vague and more importantly erroneous due to human mistakes. They are only forms of warranty data an organization has. Analyzing such data is therefore needed and can also be of benefit to organization and in identifying early warnings of abnormalities in their products, providing useful information about failures, nature of failure modes to aid design modification, finding out product reliability for warranty policy and predicting future warranty claims needed for preparing warranty reserves plans. © 2016 The Authors.


Sujatha V.,Vellore Institute of Technology | Prasanna Devi S.,Apollo Computer | Vinu Kiran S.,Apollo Computer | Manivannan S.,Drmgr Educational And Research Institute University
Procedia Computer Science | Year: 2016

In this paper, we had analyzed a large scale Diabetic data sets for several patients to find the length of time taken for treatment for each class of Diabetes and the risk of re-admission of diabetic patients performing Bigdata analytics, the type of diabetes and its outcome which acted as a high risk sample of patient data sets. We have collected and integrated different sources of diabetic information for several patients, from primary and secondary treatment information to administrative information, to analyze novel view of patient care processes such as type of treatments and every patient behaviors on which results multifaceted nature of chronic care that we take into our account to predict the survival factors and length of stay. Nowadays by using electronic medical equipments with high quality and high degree calibrations, we are able to gather large amounts of real-time diabetic data sets. The requires the usage of distributed platforms for making BigData analysis that results on making decisions based on available data and its trends. This type of Bigdata analysis allows geographical and environmental information of patients' enables the capability of interpreting the ethnicity of data gathered and extract new analysis to identify survival options and treatment timelines (LOS) from them. © 2016 The Authors.


Vinu Kiran S.,Apollo Computer | Prasanna Devi S.,Drmgr Educational And Research Institute University | Manivannan S.,Drmgr Educational And Research Institute University
Procedia Computer Science | Year: 2016

In this paper, we propose to transform the global matching mechanism in an electronic exchange between the producers and consumers in the SCM system for perishable commodities over large scale data sets. Matching of of consumers and producers satisfactions are mathematically modeled based on preferential evaluations based on the bidding request and the requirements data which is supplied as a matrix to Gale Shapely matching algorithm. The matching works over a very transparent approach in a e-trading environment over large scale data. Since, Bigdata is involved; the global SCM could be much clearer and easier for allocation of perishable commodities. These matching outcomes are compared with the matching and profit ranges obtained using simple English auction method which results Pareto-optimal matches. We are observing the proposed method produces stable matching, which is preference-strategy proof with incentive compatibility for both consumers and producers. Our design involves the preference revelation or elicitation problem and the preference-aggregation problem. The preference revelation problem involves eliciting truthful information from the agents about their types that are used for computation of Incentive compatible results. We are using Bayesian incentive compatible mechanism design in our match-making settings where the agents' preference types are multidimensional. This preserves profitability up to an additive loss that can be made arbitrarily small in polynomial time in the number of agents and the size of the agents' type spaces. © 2016 The Authors.


Kasturi E.,M. S. University of Baroda | Prasanna Devi S.,Apollo Computer | Vinu Kiran S.,Apollo Computer | Manivannan S.,Drmgr Educational And Research Institute University
Procedia Computer Science | Year: 2016

Applying vital decisions for new airline routes and aircraft utilization are important factors for airline decision-making. For data driven analysis key points such as airliners route distance, availability on seats/freight/mails and fuel are considered. The airline route profitability optimization model is proposed based on performing Big data analytics over large scale aviation data under multiple heuristic methods, based on which practical problemsareanalysed. Analysis should be done based on key criteria, identified by operational needs and load revenues from operational systems e.g. passenger, cargo, freights, airport, country, aircraft, seat class etc., The result shows that the analysis is simple and convenient with concrete decision. © 2016 The Authors.


Srinivasan R.,Dr. M.G.R. Educational and Research Institute | Manivannan S.,Drmgr Educational And Research Institute University | Ethiraj N.,Drmgr Educational And Research Institute University | Prasanna Devi S.,Apollo Computer | Vinu Kiran S.,Apollo Computer
Procedia Computer Science | Year: 2016

In this paper we have analyzed the huge volume of warranty data for segregating the fraudulent warranty claims using pattern recognition and clustering methodology. Recent survey of automotive industry shows up to 10% of warranty costs are related to warranty claims fraud, costing manufacturers several billions of dollars. Most of the automotive companies are suspecting and aware of warranty fraud. But they are not sure of the extent and ways to eliminate it. The existing methods to detect warranty fraud are very complex and expensive as they are dealing with inaccurate and vague data, causing manufacturers to bear the excessive costs. We are proposing model to find anomalies on warranty data along with component failure data and patterns based on historic warranty claims data under particular region and for specific component as the data are of high volume. We are managing to isolate all the imapcting the factors that indicate a claim, that has a high probability of fraudulence such as failure date and claim date, mode of failure etc., In addition to this we discover suspecting claims that have the greatest adjustment potential for further review by claim process. We altogether integrating data with with claims processing, reports and business rules along with reported mode of failure as we are minimizing changes to existing systems, since the analysis is carried out by identifying patterns. Since we are working with factual data, it gives more room to identify the actual cost involved on warranty claim. © 2016 Published by Elsevier B.V.


Vasuki R.,Bharath University | Hari R.,Drmgr Educational And Research Institute University
International Journal of Pharmacy and Technology | Year: 2014

The present study dealt with the investigation of anti-obesity and anti-diabetic effects of ethanolic extract of leaves of Solanum torvum (STE) using obese, diabetic-induced albino rats. The animals received either normal diet, high-fat diet or high-fat diet with additional STE for 12 weeks. After the end of administration, body weight, plasma glucose, insulin, and liver triglyceride, Cholesterol Content and antioxidant activity were measured. The result revealed that , compared to the high-fat diet group, increases in body weight, plasma glucose and insulin were significantly suppressed for STE groups.STE also proved to possess good antioxidant activity.These results suggest that STE is expected to be an useful plant extract for alleviating the adversse effect of obesity associated with diabetes mellitus. © 2014, International Journal of Pharmacy and Technology. All rights reserved.


Jayaprakash J.,Drmgr Educational And Research Institute University
International Journal of Applied Engineering Research | Year: 2014

This paper presents a multi-agent system (MAS) for modeling and simulation of complex Inventory Routing Problem (IRP). The agents are used to represent various entities in the IRP and each agent has its own local objective functions and responsibilities, they also interact with each other. Thus, they cooperate at the same time, it compete with each other for resource optimization. In this way, the multi-agent framework allows to capture the cooperation and competition nature of the global optimization in the IRP. This paper proposes a multi agent based IRP and its JADE simulation results are obtained. © Research India Publications.

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