Association rule data mining is an important technique for finding important relationships in large datasets. Several frequent itemsets mining techniques have been proposed using a prefix-tree structure, FP-tree, a compressed data structure for database representation. The DIFFset data structure has also been shown to significantly reduce the run time and memory utilization of some data mining ...

background family planning (fp) program in pakistan has been struggling to achieve the desired indicators. despite a well-timed initiation of the program in late 50s, fertility decline has been sparingly slow. as a result, rapid population growth is impeding economic development in the country. a high population growth rate, the current fertility rate, a stagnant contraceptive prevalence rate a...

A fusion protein, FP 6/3, composed of IGF binding protein (IGFBP)-6 and IGFBP-3 was synthesized where the complete sequences of each binding protein were fused together into a single chimeric protein. The orientation of this fusion protein's structure has the N terminus of IGFBP-3 fused to the C terminus of IGFBP-6, leaving the key binding areas of each open. FP 6/3 bound to cells via its IGFBP...

Since the amount of text data stored in computer repositories is growing every day, we need more than ever a reliable way to group or categorize text documents. Most of the existing document clustering techniques use a group of keywords from each document to cluster the documents. In this thesis, we have used a sense based approach to cluster documents instead of using only the frequency of the...

Since the amount of text data stored in computer repositories is growing every day, we need more than ever a reliable way to group or categorize text documents. Most of the existing document clustering techniques use a group of keywords from each document to cluster the documents. In this thesis, we have used a sense based approach to cluster documents instead of using only the frequency of the...

Approximate frequent itemsets (AFI) mining from noisy databases are computationally more expensive than traditional itemset mining. This is because the AFI algorithms generate large number of candidate itemsets. article proposes an algorithm to mine AFIs using pattern growth approach. The major contribution proposed approach it mines core patterns and examines approximate conditions directly wi...

Finding frequent patterns plays an essential role in mining associations, correlations, and many other interesting relationships among variables in transactional databases. The performance of a frequent pattern mining algorithm depends on many factors. One important factor is the characteristics of databases being analyzed. In this paper we propose FEM (FP-growth & Eclat Mining), a new algorith...

Discovering association rules by identifying relationships among sets of items in a transaction database is an important problem in Data Mining. Finding frequent itemsets is computationally the most expensive step in association rule discovery and therefore it has attracted significant research attention. In this paper, we describe a more efficient algorithm for mining complete frequent itemset...

Let Fq be a finite field of q elements of characteristic p. The classical algorithm of Berlekamp [1] reduces the problem of factoring polynomials of degree n over Fq to the problem of factoring squarefree polynomials of degree n over Fp that fully split in Fp, see also [8, Chapter 14]. Shoup [15, Theorem 3.1] has given a deterministic algorithm that fully factors any polynomial of degree n over...

The main objective of this paper is to model and optimize the parallel and relatively complex FuzzyP+FuzzyI+FuzzyD (FP+FI+FD) controller for simultaneous control of the voltage and frequency of a micro-grid in the islanded mode. The FP+FI+FD controller has three parallel branches, each of which has a specific task. Finally, as its name suggests, the final output of the controller is derived fro...