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Search Results: 1 - 10 of 467916 matches for " Dr. A. KUMARAVEL "
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Diabetes diagnosis using Artificial Neural Network .
Santosh Kumar,Dr. A. Kumaravel
International Journal of Engineering Sciences & Research Technology , 2013,
Abstract: In this paper, we present a study on the diagnosis of diabetes using different supervised learning algorithms of Artificial Neural Network. The network is trained using the data of about 250 diabetes patients between the age group,25 to 78 years. The performance of each algorithm is further compared through regression analysis. The prediction accuracy of the best algorithm is computed to validate accurate prediction.
Methodologies for Trend Detection Based on Temporal Text Mining
M. BANU PRIYA,Dr. A. KUMARAVEL
International Journal of Computer Science and Mobile Computing , 2013,
Abstract: We present two methodologies for the detection of emerging trends in the area of textual datamining. These manual methods are intended to help us improve the performance of our existing fullyautomatic trend detection system [3]. The first methodology uses citations traces with pruning metrics togenerate a document set for an emerging trend. Following this, threshold values are tested to determine theyear that the trend emerges. The second methodology uses web resources to identify incipient emergingtrends. We demonstrate with a confidence level of 99% that our second approach results in a significantimprovement in the precision of trend detection. Lastly we propose the integration of these methods for boththe improvement of our existing fully automatic approach as well as in the deployment of our semiautomatedCIMEL [20] prototype that employs emerging trends detection to enhance multimedia-basedComputer Science education.
Clustering Technique for Segmentation of Exudates in Fundus Image .
Md. Muhid Ahmed,Sujay Basu,Dr. A. Kumaravel
International Journal of Engineering Sciences & Research Technology , 2013,
Abstract: Exudates are a category of lipid retinal lesions visible through optical fundus imaging, and indicative of diabetic retinopathy. we tend to propose a clustering-based methodology to phase exudates, using multi-space clustering, and colorspace options. The tactic was evaluated on a group of eighty nine pictures from a publically obtainable dataset, and achieves an accuracy of 89.7% and positive prophetical price of 87%.
An Efficient I-MINE Algorithm for Materialized Views in a data Warehouse Environment
T.Nalini,Dr. A. Kumaravel,Dr.K.Rangarajan
International Journal of Computer Science Issues , 2011,
Abstract: The ability to afford decision makers with both accurate and timely consolidated information as well as rapid query response times is the fundamental requirement for the success of a Data Warehouse. Selecting views to materialize for the purpose of supporting the decision making efficiently is one of the most significant decisions in designing Data Warehouse. Selecting a set of derived views to materialize which minimizes the sum of total query response time maintenance of the selected views is defined as view selection problem. Therefore, to select an appropriate set of a view is the major target that diminishes the entire query response time and also maintains the selected views. Selecting a suitable set of views that minimizes the total cost associated with the materialized views is the key objective of data warehousing. However, these views have maintenance cost, so materialization of all views is not possible. In this paper we are taking into consideration of query frequency, query processing cost and space requirement. In order to find the frequent queries, we make use of I-mine mining techniques from which the frequently user accessible queries will be generated. Then, an appropriate set of views can be selected to materialize by minimizing the total query response time and/or the storage space along with maximizing the query frequency. These can be utilized by the users to obtain the quicker results once a set of views is materialized for the data warehouse.
Flank Wear Monitoring in Coated Carbide Tool Using Ae Signal Analysis, Cutting Force, Motor Current and Acceleration Due to Tool Vibration
S. Sundaram,P. Senthilkumar,A. Kumaravel,N. Manoharan
International Journal of Systems Signal Control and Engineering Application , 2012,
Abstract: Wear of a cutting tool in a machining operation is highly undesirable because it severely degrades the quality of machined surfaces and causes undesirable and unpredictable changes in the work geometry. From a process automation point of view, it is therefore necessary that an intelligent sensing system be devised to detect the progress of tool wear during cutting operations so that worn tools can be identified and replaced in time. As a non-destructive sensing methodology, Acoustic Emission (AE) based techniques offer some advantages over force or power based tool monitoring techniques because of the close relationship between the generation of the emission signal and the fracture or wear phenomenon in machining. The generation of the AE signals directly in the cutting zone makes them very sensitive to changes in the cutting process. Acoustic Emission Techniques (AET) is a relatively recent entry into the field of non-destructive evaluation (NDE) which has particularly shown very high potential for material characterization and damage assessment in conventional as well as nonconventional processes. This method has also been widely used in the field of metal cutting to detect process changes like tool wear etc. In this research work the results obtained from the analysis of Acoustic Emission sensor employs to predict flank wear in turning of C45 steel of 250 BHN hardness using Polycrystalline diamond (PCD) insert. Machining trails were conducted in 5 H.P all geared lathe to obtain the data. The observations noted during the experimental work are analyzed for correlations between the tool wear and the AE parameters.
Study of flank wear in single point cutting tool using acoustic emission sensor techniques
S. Sundaram,P. Senthilkumar,A. Kumaravel,N. Manoharan
Journal of Engineering and Applied Sciences , 2008,
Abstract: Wear of a cutting tool in a machining operation is highly undesirable because it severely degrades the quality of machined surfaces and causes undesirable and unpredictable changes in the work geometry. From a process automation point of view, it is therefore necessary that an intelligent sensing system be devised to detect the progress of tool wear during cutting operations so that worn tools can be identified and replaced in time. As a ‘non – destructive’ sensing methodology, Acoustic Emission (AE) based techniques offer some advantages over force or power based tool monitoring techniques because of the close relationship between the generation of the emission signal and the fracture or wear phenomenon in machining. The generation of the AE signals directly in the cutting zone makes them very sensitive to changes in the cutting process. Acoustic Emission Techniques (AET) is a relatively recent entry into the field of Non – Destructive Evaluation (NDE) which has particularly shown very high potential for material characterization and damage assessment in conventional as well as non-conventional processes. This method has also been widely used in the field of metal cutting to detect process changes like tool wear etc. In this research work the results obtained from the analysis of Acoustic Emission sensor employs to predict flank wear in turning of C45 steel of 250 BHN hardness using Polycrystalline diamond (PCD) insert. The correlation between the tool wear and AE parameters is analyzed using the experimental study conducted in 5 H.P all geared lathe.
Performance Analysis Of OSPF In Multicast Routing Using RPF Technique
K.Kumaravel,M.Sengaliappan,A.Marimuthu
International Journal of Distributed and Parallel Systems , 2012,
Abstract: Open Shortest Path first is most widely used interior gateway routing protocol, biggest it can update the routing in Autonomous system. Link-state routing protocols generate routing updates only when a change occurs in the network topology. When a link changes state, the device that detected the change creates a link-state advertisement (LSA) concerning that link and sends to all neighboring devices using a special multicast address. Each routing device takes a copy of the LSA, updates its link-state database (LSDB), and forwards the LSA to all neighboring devices. OSPF provides a technique RPF, the traffic may not occur and the packets can be freely to reach the destination router (DR).
The Inhibition of Mild Steel Corrosion in Sulphuric Acid Media by Acorus Calamus Extract
S. Ananth Kumar,A. Sankar,M. Kumaravel,S. Rameshkumar
International Journal of Engineering Innovations and Research , 2013,
Abstract: The inhibitive action of rhizome extracts of Acoruscalamus on mild steel corrosion in 0.5 N H2SO4 solution was studied using weight loss method, potentiodynamic polarization and EIS measurements. The results obtained indicate that the extracts functioned as good inhibitors in H2SO4 solution. Inhibition efficiency was found to increase with extract concentration. The adsorption of constituents in the plant extract on the surface of the metal is proposed for the inhibition behavior.
Islet Cell Biology, Regeneration, and Transplantation
A. N. Balamurugan,Velayutham Kumaravel,Subbiah Pugazhenthi,Bashoo Naziruddin
International Journal of Endocrinology , 2012, DOI: 10.1155/2012/139787
Abstract:
A comparative study analysis of materialized view for selection cost
T.Nalini,A.Kumaravel,K.Rangarajan
International Journal of Computer Science and Engineering Survey , 2012,
Abstract: Materialized view selection is one of the most crucial techniques to design data warehouse in an optimal manner. Selecting views to materialize for the purpose of supporting the decision making efficiently is one of the most significant decisions in designing Data Warehouse. Selecting a set of derived views tomaterialize which minimizes the sum of total query response time & maintenance of the selected views is defined as view selection problem. Selecting a suitable set of views that minimizes the total cost associated with the materialized views is the key objective of data warehousing. In this paper we compare the various research works on several parameters for controlling the selection process and also we compare time , query frequency and spatial cost.
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