Mining Closed Weighed Frequent Patterns from a Sliding Window over Data Stream

Weighted frequent pattern mining address to discover more important frequent pattern by considering different weights of every item, closed frequent pattern mining can significantly reduce the number of frequent itemset mining and keep sufficient result information. In this paper,we proposed an algorithm DS_CRWF to mine closed weighted frequent pattern over data stream,which is based on sliding window and take basic window as unit of updating,all the closed weighted frequent patterns can be mined through once scan.The experimental results show the feasibility of the algorithm.

New Policy of Maximal Frequent Itemsets in Data Stream Mining

According to the features of data streams and combined sliding window, a new algorithm A-MFI which is based on self-adjusting and orderly-compound policy for mining maximal frequent itemsets in data stream is proposed. This algorithm which is based on basic window updates information from data stream flow fragments and scans the stream only once to gain and store it in frequent itemsets list when the data stream flows. The core idea of this algorithm: construct self-adjusting and orderly-compound FP-tree, use mixed subset pruning techniques to reduce the search space, merge nodes which has equal minsup in the same branch and compress to generate the orderly-compound FP-tree to avoid superset checking when mining maximal frequent itemsets. The experimental results show that the algorithm has higher efficiency in time and space, and also has good scalability.

Maximal Frequent Itemsets in Data Stream Mining Based on Orderly-Compound Policy

Mining maximal frequent itemsets get the advantage of a relatively small number of itemsets. Compared to mining frequent itemsets and mining frequent closed itemsets, such algorithm has higher time and space efficiency. According to the features of data streams and combined sliding window, a new algorithm E-FPMFI which is based on orderly-compound policy for mining maximal frequent itemsets in data stream is proposed. The algorithm based on basic window updates information from data stream flow fragment and scans the stream only once to gain and store it in frequent itemsets list. The algorithm construct FP-tree, then compress orderly FP-tree by merging nodes which has equal minsup in same branch, also uses subset mix pruning technique, avoid superset checking. The experimental results show the algorithm has higher time, space efficiency and good scalability.

Dynamical Stellar Dust Shells: Different Perspectives

In the last decades considerable progress has been achieved in the physical understanding and modelling of dusty stellar atmospheres and surroundings, as represented by stationary dust driven winds, pulsating shells of Miras and LPVs, episodic phenomena, like occultations of RCrB stars, the atmospheres of brown dwarfs, or even by “hot” objects like dust forming Wolf-Rayet stars.For all these systems the notions “understanding” and “modelling” depend on the level of the physical approach defined by specific perspectives chosen by a basic “window of perception” for each class of particular objects and its appropriate description within this frame. This is defined by the fundamental assumptions with regard to the global and local appearance and the properties of the considered object, its focused characteristic length and time scales of the various determining processes taken into account, and, of course, by an appropriate body of physical equations necessary for an adequate description within the context of the adopted perspective. In this view, any real approach concentrates on special aspects (or a combination of it), like radiative transfer, wind generation, spectral appearance, dynamical behaviour, global and local stability, cluster nucleation, grain growth and processing, chemistry, interplay of physical and chemical processes, etc. Consequently, any approach projects only particular properties of the considered object, each constituting important ingredients necessary for a final consistent quantitative modelling and a comprehensive physical understanding.

Development and Use of the Documentation Design Aid

In aviation maintenance and inspection, work documents are critical to safety, as they act as both production control devices and job aids for mechanics and inspectors. Based on an analysis of the current state of documentation in aviation maintenance, there was a clear need to help document designers/writers utilize good human factors practice. Design guidelines were developed and tested (Patel et al, 1994) and then made accessible through a Visual Basic window, called the Documentation Design Aid or DDA, available on-screen while writing a procedure. This DDA was tested for usability by writers and for comprehension of the documents produced. A number of different evaluations showed that the DDA reduced comprehension errors significantly. The DDA is now available via a WWW site for users to download and use.