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Frequency: 12 issues per year
ISSN: 2250–3005 (online version)
Published by: IJCER
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International Journal of Computational Engineering Research

(IJCER)

 

Articles

 

Research Article  open access
Pattern Discovery Using Apriori and Ch-Search Algorithm
Prof.Kumbhar S.L., Mahesh Aivale, Kailas Patil, Pravin Jadhav, Baliram Sonawane
India
Paper Indexed : :03.3005/0530106
International Journal of Computational Engineering Resaerch 2014, Volume 05 ~ Issue 03 (March 2015)

Abstract

The association rule describes and discovers the relations between variables in large databases. Generally association rules are based on the support and confidence framework. In apriori algorithm, association rules are used for finding minimum support & minimum confidence. But this method can lead to loss of rules i.e. negative rules are lost. Hence Ch-Search algorithm is introduced which uses its strongest rule i.e. commonly used the Coherent rule which promotes information correctness and leads to appropriate decision making among the same item sets. The coherent rule discovers positive as well as negative outcomes, and does not require finding minimum support & minimum confidence frameworks leading to no loss of any rules. The paper describes how the Ch algorithm is used by coherent rule for exact pattern discovery in large databases over apriori algorithm.

Keywords:Data Mining, Association Rule, Apriori algorithm, Support, Confidence, Coherent Rule, Ch-Search Algorithm etc…

 

Research Article  open access
Efficient Data Distribution in CDBMS based on Location and User Information for Real Time Applications
Tejas Bhatt, Mr. Manjunath H
India
Paper Indexed : : 03.3005/05307013
International Journal of Computational Engineering Resaerch 2014, Volume 05 ~ Issue 03 (March 2015)

Abstract

In today's world users need to store data in every application and applications has a lot number of users data stored at databases. The retrieval time of data depends on how many records a database contains and not the configuration of the server. The less the number of records the less the retrieval time. Many methods are available when it comes to data partitioning, each with its own functionality for a specific application and requirement. This paper focus on the methods of data partitioning and the effective algorithm to partition the data equally between N numbers of nodes running on the cloud having database with same entities which contain the distributed data of user used in real time user application. Proposed method concentrate on data distribution in real time "user" application where user activities are primary requirement.

Keywords:Data, Database, Data Distribution, Data Partitioning, Horizontal Partitioning, Vertical Partitioning, Cloud Database, User Information, Database Server, Nodes, CDBMS, OLAP, Fragmentation, Index.,

Research Article  open access
On an Optimal control Problem for Parabolic Equations
M. H. FARAG||T. A. NOFAL|| A. I. EL-NASHAR|| N. M. AL-BAQMI
Egypt
Paper Indexed : :03.3005/053014021
International Journal of Computational Engineering Resaerch 2014, Volume 05 ~ Issue 03 (March 2015)

Abstract

Consideration was given to the problem of optimal control of parabolic equations. The existence solution of the considering optimal control parabolic problem is proved. The expression of the gradient of the cost functional using the adjoint system is obtained. Lipschitz continuity of the gradient is derived.

Keywords:Optimal control problem, parabolic Equations, Existence solution, Fréchet gradient, Adjoint problem, Lipschitz continuity.

Research Article  open access
Reuse Options of Reclaimed Waste Water in Chennai City
K.Deepa || M. Krishnaven
India
Paper Indexed : :03.3005/053022028
International Journal of Computational Engineering Resaerch 2014, Volume 05 ~ Issue 03 (March 2015)

Abstract

In the present research work Sholinganallur taluk which comes under the zone of Chennai city expansion area was taken for management of wastewater effectively. Overlay operation in GIS tool was performed by selected decentralized wastewater treatment site map on reclassified landuse map. A 1000 m buffer map was created around each decentralized wastewater treatment sites to suggest various reuse options. The landuse map within the buffer zone comprises of detailed classification of ward number and its boundary. The settlement area which falls in the buffer zones includes number of households and population density, educational institutions like schools, colleges, industrial buildings like IT buildings, manufacturing buildings, government offices, shopping complex, hospitals, hotels, restaurants, etc., public areas like parks, pavement area etc. and crop land, forest area, salt pan, sand bar etc. Reuse of treated wastewater is broadly categorized into two purposes namely potable and non potable purposes. Treated waste water for potable purpose such as for drinking and recharge of ground water require higher standard of water quality. Whereas the non potable reuse such as domestic purpose like gardening, toilet flushing, car washing, industrial reuse, recreational, agriculture, landscape irrigation, wetland applications etc requires low standard of treated waste water quality. The reuse options considered in the present study are the urban, Industrial, recreational, groundwater respectively.

Keywords:GIS, Overlay analysis, Decentralisation, Wastewater

Research Article  open access
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thakare Guide
Ajinkya Kunjir || Poonam Pardeshi || Shrinik Doshi || Karan Naik
India
Paper Indexed : :03.3005/053029034
International Journal of Computational Engineering Resaerch 2014, Volume 05 ~ Issue 03 (March 2015)

Abstract

In this paper we will discuss about the problem that are faced by higher education institutions. One of the biggest challenges that higher education faces today is predicting the right path of students. Institutions would like to know, which students will enroll in which course, and which students will need more assistance in particular subject and what efforts should be taken for weak students. Also some time management needs more information about student like their overall result, interest in co-curricular and extra-curricular activities and about the success of new offered courses. One way to effectively address the challenges for improving the quality of students and education is to provide new knowledge related to the educational processes and entities to the system. This knowledge can be extracted from historical data that reside in the educational organization's databases using the techniques of data mining technology. If data mining techniques such as clustering, decision tree, association, classification and prediction can be applied to higher education processes, it can definitely help improve students' overall performance, their life cycle management, selection of course and predict their dropout rate.

Keywords:Data mining, Higher education, Clustering, Decision tree, neural network, classification, prediction, association rule analysis.