Call for Comming Issue
 

Volume 2, Issue 4 April 2014

S.No. Title Page No.
01
Evaluating the Gaps in Color Constancy Algorithms
1Irvanpreet kaur, 2Rajdavinder Singh Boparai
Abstract : Color constancy is a part of the visual perception system which permits people to recognize color in a variety of conditions, and to see some consistency in the color. Different color constancy algorithms are used like gray world, white patch, gray world 1st order derivative, gray world 2nd order derivative. This work focuses on using the gray world 2nd order derivative because this algorithm is based on 8 neighbors. The main objectives of this paper are to review the existing work on color constancy algorithms. The overall objective of this work is to find the limitations of the edge based color constancy using 2nd order derivation and suggest suitable solution for the same.
001-006
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02
IMAGE SEGMENTATION USING EXPECTATION MAXIMIZATION ALGORITHM
1Vishwajit K. Barbudhe, 2Shailesh N. Sisat, 3Abhishek Kumar
Abstract: Image pre-processing and registration are discussed, as well as methods of validation. In this paper, we present a new multiresolution algorithm that extends the well-known Expectation Maximization (EM) algorithm for image segmentation. The conventional EM algorithm has prevailed many other segmentation algorithms because of its simplicity and performance. However, it is found to be highly sensitive to noise. To overcome the drawbacks of the EM algorithm we propose a multiresolution algorithm which proved more accurate segmentation than the EM algorithm.
007-013
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03
A Penalty/MPQI Method for Constrained Parabolic Optimal Control Problems
M. H. FARAG1,2 , FATHY H. RIAD2 and W. A. HASHEM2
Abstract : This paper is concerned with the numerical implementation and testing of penalty/MPQI algorithm for solving problems in PDE-constrained optimization. It uses this method to transform a constrained optimal control problem into a sequence of unconstrained optimal control problems. It is shown that the solutions to the original constrained problem. Convergence results are proved numerically.
014-022
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04
AN EVALUATION ON DIFFERENT IMAGE FUSION TECHNIQUES
Jasmeetkaur, Er.Rajdavinder Singh Boparai
Abstract: This paper presents an evaluation of several image fusion methods. The image fusion is being used one of the popular techniques in image processing. A number of image fusion techniques have been used in various applications. Image fusion combines the information from different images of single scene to get an informative image which is more appropriate for human visualisation or further vision processing.Image superiority is a strongly related to image focus. The major objective of image fusion is to combine information from various images of the single scene in order to deliver only the valuable information. The discrete cosine transforms (DCT) based techniques of image fusion are more appropriate and time-saving in real-time systems using DCT based principles of still image.
023-028
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05
A Novel Approach for Evaluating Effectiveness of Recommendation Algorithms
Mubbashir Nazir1, Umar Mir2 and Anuj Yadav3
Abstract : Different algorithms are being developed in order to provide better recommendations. The Recommendation algorithms developed are tested extensively by subjecting the algorithms to best possible inputs so as to validate whether the algorithm is performing effectively or not. In order to analyze the usefulness of recommendation algorithms we need a novel approach by which we can measure the quality of recommendation. One way of doing is that by using AB Testing to validate recommendation, but in order to have one good measure for measuring recommendation effectives it becomes difficult to analyze each Ab testing variant in all possible ways, thus it is better to provide multiple views of the same data which can be achieved through signals named: 1. Click Through Ratio (CTR) 2. Conversions 3. Bounce Rate In this paper we will combine CTR, Conversions and Bounce Rate signals to present a novel approach for evaluating the effectiveness of Recommendation Algorithms
029-033
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06
To Enhance the Security in Terms of Malicious node attacks by using Alarm Protocol in WSN
Neelam Shekhawat1, Moumita Ghosh2
Abstract: The wireless sensor network is the self configuring type of network. In these kinds of networks mobile nodes can leave or join the network when they want. In such type of networks many active and passive attacks are possible. To prevent from these active and passive attacks trust relationship between the mobile nodes must be maintained. The trust relationship between the mobile nodes is provided by mutual authentication. ALARM is the protocol for providing trust relationship between the mobile nodes. In this protocol the clocks of the mobile nodes are weakly synchronized by using GPS. In such case reply attack is possible. To prevent reply attack clocks of the mobile nodes must be strongly synchronized. In our new proposed technique, we are enhancing t the ALARM protocol to provide strong clock synchronization between the mobile nodes. Our new technique will be based on the network time protocol..
034-039
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07
Text Summarization using Sports Ontology with Graphical Representation
Prof.Mr.R.V.Argiddi 1, Dr.Prof.S.S Apte 2 , L .R. Salgare3
Abstract : Now a day, we see news contains small sentence on screen related to particular topic like example sports. But when if news contains multiple sentences, at that time difficult to display whole document each time on screen .For that purpose we are using sports ontology to find the most important sentence from that document .Ontology is the presented method including the domain ex. sports domain concepts organized into categories and interconnected by relationships, as well as instances and connections among them, effectively becomes the classifier. Using this ontology concept we summarize most important sentence from the text document.
040-042
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08
An approach for Search Engine Optimization Using Classification - A data Mining Technique
Rajesh Singh1, S.K. Gupta2
Abstract : Search engines play an important role in information retrieval on the web. Given a query, search engines, such as Google, Yahoo! and Bing, return a ranked list of results.. For different queries, the result set includes documents on a variety of topics, rather than a single topic. This variation is probably due to the matter that a typical query contains about only two to three terms, which is not sufficient to locate the desired information unambiguously. For example, the query “God" will often return documents referring to both the God and the good. While the user is only interested in one topic, it is not possible for a search engine to know which topic is relevant based on the query alone. Moreover, the standard ranking of the documents in the result set is independent of the topic. So, the rank-ordered result should have an arbitrary topic ordering. Referring to the “GOD" example, this means that a user should scroll through a ranked list in which many documents may be wrong.
043-046
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