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Today, Association Rules are considered to be one of the more studied fields under Data Mining. It recently has come under a lot of notice by the data base warehouses. Its main use is to extract interesting associations, co-relations and frequent patterns among the groups of items recorded of the transactional databases or some different form of data storages. In this paper, a categorization and comparison of the different association rule algorithms that are present today is provided.

Data Mining, Association Rules, AssociationRule Algorithms, Database, Data Analysis

[Agrwl93] RakeshAgrawal, Tomasz_Imielinski and Arun N. Swami, Mining_Association_RulesBetweenSets of Items in Large_Databases.
[Agrwl98] Charu C. Aggarwal and Philip_S. Yu, A New Framework for Itemset_Generation.

[Chn96] Ming-Syan Chen, Jiawei Han and Philip_S. Yu, Data Mining: An Overview from a Database_Perspective.
[Fayyd96] Usama M. Fayyad, Gregory_Piatetsky-Shapiro, and Padhraic Smyth, From Data Mining to knowledge Discovery: An Overview, Advances in Knowledge Discovery and Data Mining, pp 1-34.
[Chng96c] David Wai-Lok Cheung, Ada Wai-Chee Fu, Vincent T. Ng, and Yongjian Fu, Efficient Mining of Association_Rules in Distributed_Databases, Vol. 8, No. 6, pp. 911-922.

NOTATIONS
[1] I: Set of data items
[2] n: No. of data items
[3] D: Transactional database
[4] s: Support
[5] α: Confidence
[6] T: Tuples in database
[7] X,Y: Itemsets
[8] X ⇒ Y: Association rule
[9] Lk: Set of large itemsets of size `k`
[10] Li: Set of large itemsets for partition Di
[11] L: Set of large itemsets
[12] l :Large itemset

P. Saxena, R. Jain, "Association Rule Mining," International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.153-158, 2014.

In today�s day and age, a rapid proliferation of technology has enabled efficient global communication. As a result, the last decade has seen social networking emerge as the backbone of global interactions. At the kernel of this advent, lies the concept of networks. Networks are arrangements of interconnections among a variety of entities. From this we can deduce that social networks are social structures comprising individuals and the interactions they have with each other. The computational analysis of these networks is known as social network analysis.

Social Network Analysis, Directed Acyclic Graph, Statistical Relational Learning

[1] Hierarchical structure and the prediction of missing links in networks by Aaron Clauset, Christopher Moore, M. E. J. Newman3.
[2] Predicting Hierarchical Structure in Small World Social Networks by Hussain, Dil Muhammed Akbar.
[3] Link Prediction In Social Networks by Prof. William H. Hsu.
[4] Networks, Crowds, and Markets: Reasoning about a Highly Connected World by David Easley and Jon Kleinberg. Cambridge University Press, 2010.
[5] The Link-Prediction Problem for Social Networks by David Liben-Nowell and Jon Kleinberg.
[6] Adamic, L.A., & Adar, E. (2003). Friends and neighbours on the Web. Social Networks, 25(3), 211�230.
[7] Statistical Relational Learning: A Tutorial by Lise Getoor University of Maryland, College Park ECML/PKDD 2007 Tutorial.
[8] Link prediction problem for soc net by David Liben-Nowell n Jon Kleinberg.
[9] Clauset, A., Moore, C., and Newman, M. E. J. Hierarchical structure and the prediction of missing links in networks.
[10] Citation: Social Network Analytics by Elena Pupazan.
[11] Emergence of global status hierarchy in social networks by Yue Chen, Jia Ji, Yizheng Liao.
[12] Ahmed, Elmagarmid, and Ipeirotis, Panagiotis G., and Verykios, Vassilios. (2007) Duplicate Record Detection: A Survey.
[13] Link prediction in social network by Muhammad Al Hassan n Muhammad J Zaki.

S. Chahar, "Social Networking Analysis," International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.159-163, 2014.

Tourism is travel for recreational, leisure, or business purposes, usually of a limited duration. Tourism is commonly associated with trans-national travel, but may also refer to travel to another location within the same country.. E-tourism is the digitization of all the processes and value chains in the tourism, travel, hospitality and catering industries that enable organizations to maximize their efficiency and effectiveness. Journey of tourism to e-tourism start at year 1962 with Central reservation system followed by Airline Computer Reservations Systems, e-ticketing ,Graphical information system and cloud technology service in tourism.

Central Reservation System, Global Distribution Systems, E-Ticketing, Global Distribution Systems, Cloud Technology

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[3] Njegus, Angelina. Angelinalesson-3-from-computer-reservation-systems-to-global-distribution-systems. http://www.slideshare.net. [Online] Jul 16, 2013. [Cited: april 21, 2014.] http://www.slideshare.net/AngelinaNjegus/lesson-3-from-computer-reservation-systems-to-global-distribution-systems.
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V.V. Pawar, S.D. Mundhe , "E-tourism-Paradigm Shift," International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.164-167, 2014.

In this paper, we are reviewing several research papers regarding study and analysis towards improvement of image contrast in case of poor light. In this paper we most focus on many algorithms that has been designed for enhancement of image, At the end, a study has been made by comparing all the proposed parameters that with certain advantages and having limitations too, that have been conducted a relevant experimental analysis to evaluate both their robustness and their performance. Our review work involves a comparative study of Improvement of Image Contrast for image enrichment with respect to the following parameter Performance, Scalability, Image enhancement, Image Acquisition, Applying Morphological operators, Detecting and extracting the background, Applying contrast enhancement operators:- block analysis and opening by reconstruction, Applying image enhancement techniques like image sharpening etc.

: Digital Image Processing, Denoiser, Morphological Operators, Filters, Image contrast, Image segmentation

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[27] Saibabu Arigela and Vijayan K. Asari, �Adaptive and Nonlinear Techniques for Visibility Improvement of Hazy Images, in Lecture Notes in Computer Science Volume 6939, pp. 75�84, 2011.
[28] Vishnukumar Galigekere, Gutemberg Guerra-Filho, �A Synthesis-and-Analysis Approach to Image Based Lighting�, in Lecture Notes in Computer Science Volume 7431, pp. 292�304, 2012.
[29] M. Hofmann, P. Tiefenbacher, G. Rigoll, �Background Segmentation With Feedback: The Pixel-Based Adaptive Segmenter�, in: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 38�43, 2012.
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[34] Vasileios Zografos, Reiner Lenz, Michael Felsberg, �The Weibull Manifold in Low-Level Image Processing: An Application to Automatic Image Focusing,�, Image and Vision Computing, Volume 31, pp. 401�417, 2013.
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P. Mishra, A. Sinhal, D.S. Tomar, "A Comprehensive Review of Improvement of Image Contrast in Case of Poor Light," International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.168-175, 2014.

Whenever any new algorithm for data encryption is designed the main concern is upon the security of data. As encryption is done for encrypt data or change data in a secure form, so such encryption techniques should be used which provide the best security to the network. The main goal of any algorithm should be to secure data from any outside attack. In the recent days there are so many security issues regarding exchanging of data through a network. So data has to be encrypted in such a way that there is no threaten to secutiry. A new approach for data encryption is provided in this paper which will be helpful for security of data.

DES, Encryption, Decryption, Asymmetric Cryptography, Symmetric Cryptography

[1] R. Hauser, A. Przygienda and G. Tsudik, �Reducing the cost of security in link state routing�, In Symposium on Network and Distributed Systems Security (NDSS ‟97), San Diego, California, Internet Society, pp 93�99, February 1997.
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[6] A. Kush, C. Hwang and P. Gupta, �Secured Routing Scheme for Adhoc Networks� International Journal of Computer Theory and Engineering (IJCTE), Volume 3, pp 1793-1799, May 2009.
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R. Arya, "Data Encryption Approach For Security," International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.176-179, 2014.

Image retrieval is widely used area for number of applications like journalism, medicine, art collections, scientific database .Most of existing image search engines are text query based where retrieval result is ambiguous due to multiple meanings of provided textual query. So proposed system targets at the retrieving relevant images based on user�s search intention. A novel image retrieval approach uses Text query and Visual information of image for retrieval .Main objective of this system is to capture the user�s search intention in just �One Click� query image and to display most similar images to this clicked image based on its content . Firstly user�s intention is captured by asking user to click one image from result of text based image retrieval .After that clusters of images are formed based on their visual content and visual query hence text query is expanded . Finally Expanded keyword and Visual query expansion are used to retrieve more relevant images. In this paper best combination techniques for important features like Color ,Texture, and shape are used to measure visual similarity between images . Mainly Daubechies� wavelet transform for better frequency resolution and Frei-Chen edge detector which is less sensitive to noise and able to detect edges with small gradients is used .Experimental results shows that our system gives good result by using above combination which is tested on multiple queries and it helps in improving the precision of top-ranked images .

Image reranking, Image search, Intention, Image pool expansion, Keyword expansion, Precison.,Visual features,Visual query expansion

[1] Xiaoou Tang,Ke Liu, Jingyu Cui, �Intent Search: Capturing User Intention for One-Click Internet Image Search�, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 34, NO. 7, JULY 2012
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K. Upadhyay, G. Chhajed, "Daubchies Wavelet transform and Frei-Chen Edge detector for Intention based Image Search Engine," International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.180-186, 2014.

The delivery of computing services like servers, storage, databases, networking, software, analytics, and intelligence on the Internet is termed as cloud computing. The aim is to provide quick innovation, flexible resources, and economies of scale. The information that the user wants to access is stored in clouds. It is not necessary that the user should be at a specific place for accessing these clouds. Various organizations may find cloud technology affordable as it allows them to reduce the cost associated with management of information. The organizations do not need to keep their own servers and can use capacity rented from third parties. Cloud allows organizations for fast software updation as compared to other technologies.

Cloud computing; DaaS; IaaS; PaaS; Storage

[1] L. Qian, Z. Luo, Y. Du, L. Guo, “Cloud Computing: An Overview”, In: IEEE international conference on Cloud Computing, CloudCom 2009, Beijing, China, December 1- 4, 2009.
[2] W. Kim, “Cloud Computing: Today and Tomorrow”, Journal of object technology, Volume 8, Issue 1, Pages 65-72, 2009.
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Ramesh Thakur, "Recent Advancements in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.187-190, 2014.