The frequent-pattern-tree (FP-tree) is an efficient data structure for association-rule mining without generation of candidate itemsets. It was used to compress a database into a tree structure which stored only large items. It, however, needed to process all transactions in a batch way. In real-world applications, new transactions are usually inserted into databases. In this paper, we thus att...

Indoor wireless localization using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel-separate fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localizatio...

Elliptic curve cryptosystems (ECC) are new generations of public key cryptosystems that have a smaller key size for the same level of security. The exponentiation on elliptic curve is the most important operation in ECC, so when the ECC is put into practice, the major problem is how to enhance the speed of the exponentiation. It is thus of great interest to develop algorithms for exponentiation...

Integration of data mining and database management systems could significantly ease the process of knowledge discovery in large databases. We consider implementations of frequent itemset mining algorithms, in particular pattern-growth algorithms similar to the top-down FP-growth variations, tightly coupled to relational database management systems. Our implementations remain within the confines...

Association rule mining has been widely used in decision support systems and web site personalization. Many of these systems are characterized by frequent data additions, which inevitably determines the mining results’ re-evaluation. In such a scenario, the use of traditional algorithms which mine the whole database each execution may be wasteful or even impracticable. In this paper we present ...

The influence of fluticasone propionate (FP) on vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (bFGF) production from nasal polyp fibroblasts (NPFs) was examined in vitro. NPFs, at a density of 2.5 x 10(5) cells/ml, were stimulated with 25 ng/ml TNF-alpha in the presence or absence of FP for 24 h. FP at more than 10(-6) M could suppress VEGF production from NPFs. b...

An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. First, it compresses the database representing frequent items into a frequent-pattern tree, or FPtree, which retains the itemset association information. It then divides the compressed database into a...

Frequent pattern mining is the widely researched field in data mining because of it’s importance in many real life applications. Many algorithms are used to mine frequent patterns which gives different performance on different datasets. Apriori, Eclat and FP Growth are the initial basic algorithm used for frequent pattern mining. The premise of this paper is to find major issues/challenges rela...

Let p be a odd prime such that 2 is a primitive element of finite field Fp. In this short note we propose a new algorithm for the computation of discrete logarithm in Fp.