Informatics Publishing Limited

N. Sowndarya ¹, V. Umarani ¹

Affiliations
1 Sri Ramakrishna College of Arts and Science for Women, Coimbatore-641044, IN

Abstract

Cloud computing is the delivery of computing service done through the internet. Cloud computing services are carried by a third party provider who owns the organization. Cloud computing is a new computational pattern that offers an innovative business model for organizations to agree IT services without blunt investment. Cloud computing moves the application software and database to the large data center where the data management and service may not fully trustworthy. Cloud computing does not need the original data for its check, and only two small messages need to be exchanged for each check. Both of these properties should be attractive to designer of remote storage schemes. As Peer-to- Peer technology has matured, a number of systems such as Oceanstore, Intermemory, Ivy, PAST, Starfish, FarSite have been built to utilize remote data storage. In this paper, we discuss about data storage and security issues of Cloud computing.

 

Keywords

Cloud Computing, Services, Data Storage, Access Control.

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M. Banu Priya ¹, V. Umarani ¹

Affiliations
1 Department of Computer Science, Sri Ramakrishna College of Arts & Science for Women, Coimbatore, IN

Abstract

Data Mining is often considered as a process of automatic discovery of new knowledge from large databases. The extensive amount of knowledge and data stored in databases requires the development for storing and accessing the data, data analysis and effective use of stored knowledge of data. Association Rule Mining (ARM) is one of the important aspects in data mining, which generates large amount of itemsets in database. Many algorithms have been proposed to efficiently mine association rules. One of the most important approaches is the frequent pattern growth (FP-growth) method, which is efficient and scalable. In order to improve the efficiency of FP-growth method, this paper is surveyed on association rule mining with the aid of FP-growth algorithm in various aspects.

Keywords

FP-Tree, Frequent Itemset Mining, Association Rule.

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L. Padmavathy ¹, V. Umarani ¹

Affiliations
1 Department of Computer Science, Sri Ramakrishna College of Arts & Science for Women, Coimbatore, IN

Abstract

Association rule mining (ARM) is one of the most important techniques in data mining. The task is to find relationship between presences of various items in a given database. Frequent itemset mining plays an important role in data mining and also used to form association rules. A rule is represented as A=>B, where A and B are individual items in the database. Many business applications focus on discovery of frequent itemsets and association rules in order to improve their strategy. Association rule mining is efficiently improved by using various techniques. One of the widely used techniques among them is Hashing technique. Hashing technique utilizes hash tables to store itemsets and reduce the complexity of deriving association rules from large databases. This paper focus on how to improve the efficiency of association rules based on hashing technique.

Keywords

Association Rules, Frequent Itemset, Hashing, and Collisions.

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V. Umarani ¹, S. Palanivel ¹, U. Elaya Perumal ¹

Affiliations
1 Department of Plant Biology and Plant Biotechnology, Guru Nanak College (GRI), Chennai – 600042, Tamil Nadu, IN

Abstract

Objectives: Arulmigu Sri Thiyagarajaswamy Temple, Thiruvottiyur, Tamil Nadu has a tank which is unexplored for its algal flora. Thus an attempt has been made to study the diversity of algae. Methods: Water samples were randomly collected in plastic bottles from different sites of the tank. Samples were also collected by scrapping the steps of the temple tank to get the epilithic algae. Habitat was checked for its pH and Temperature. Samples were brought to the laboratory and preserved in 4% formalin for further studies. Observation and documentation of the algae was done using HOVERLABS Research Photo Microscopic Unit. Findings: In the present study a total number of 28 genera 39 taxa belonging to the three different Classes namely Cyanophyceae, Chlorophyceae and Bacillariophyceae were recorded. Maximum number of 9 taxa was observed from the family Scenedesmaceae of Chlorophyceae. It was interesting to note that 16 families had only a single taxon. The result clearly shows that the temple tank has rich algal flora and greater diversity. Applications: This study divulges that the temple tanks are one of the best habitats for microalgae. Hence the algal diversity can be used for determining the pollution level of such tanks.

Keywords

Bacillariophyceae, Chlorophyceae, Cyanophyceae, Temple Tank.

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