Mining frequent itemsets from the large transactional database is a very critical and important task. Many algorithms have been proposed from past many years, But FP-tree like algorithms are considered as very effective algorithms for efficiently mine frequent item sets. These algorithms considered as efficient because of their compact structure and also for less generation of candidates itemse...

One practical inconvenience in frequent pattern mining is that it often yields a flood of common or uninformative patterns, and thus we should carefully adjust the minimum support. To alleviate this inconvenience, based on FP-growth, this paper proposes RP-growth, an efficient algorithm for top-k mining of discriminative patterns which are highly relevant to the class of interest. RP-growth con...

The present study was carried out to determine the effects of fenugreek powder (FP) and extract (FE) on performance, egg quality, blood parameters and immune responses of laying hens. One-hundred and fifty Leghorn laying hens were used in a completely randomized design with five treatments and five replicates for eight weeks. Treatments were various levels of FP and FE including zero (control; ...

Splicing of the last intron (intron D) of the bovine growth hormone pre-mRNA requires the presence of a downstream exonic splicing enhancer (ESE). This enhancer is contained within a 115-nucleotide FspI-PvuII (FP) fragment located in the middle of the last exon (exon 5). Previous work showed that the splicing factor SF2/ASF binds to this FP region and stimulates splicing of intron D in vitro. H...

Dalam mengembangkan bisnis perusahaan distribusi produk chemicals, penerapan teknologi informasi menjadi sangat penting untuk menjamin kelancaran penjualan kebersihan yang ditawarkan. Perusahaan dihadapkan pada tantangan memberikan pelayanan terbaik kepada pembeli Menerapkan rencana efektif menghindari kerugian. Oleh karena itu, Untuk meningkatkan ditawarkan, harus mencari strategi bagus. Algor...

We assessed the ability of several penalized regression methods for linear and logistic models to identify outcome-associated predictors and the impact of predictor selection on parameter inference for practical sample sizes. We studied effect estimates obtained directly from penalized methods (Algorithm 1), or by refitting selected predictors with standard regression (Algorithm 2). For linear ...