Mobile Ad-hoc Networks (MANETs) by contrast of other networks have more vulnerability because of having nature properties such as dynamic topology and no infrastructure. Therefore, a considerable challenge for these networks, is a method expansion that to be able to specify anomalies with high accuracy at network dynamic topology alternation. In this paper, two methods proposed for dynamic anom...

The aim of this study is to explore the characteristics of innovative personality among teachers in Malaysia. Samples of the research were randomly selected among secondary school teachers in three districts in Malaysia. Research instrument was self-developed by the researchers based on interviews carried out with some resource persons who are both experts and authoritative in their fields, as ...

Functional data are data that can be represented by suitable functions, such as curves (potentially multi-dimensional) or surfaces. This paper gives an introduction to some basic but important techniques for the analysis of such data, and we apply the techniques to two datasets from biomedicine. One dataset is about white matter structures in the brain in multiple sclerosis patients; the other ...

We solve the tasks of strip line detection and thinning in image processing and pattern recognition with the help of a statistical learning technique called rival penalized competitive learning based local principal component analysis. Due to its model selection and noise resistance ability, the technique is experimentally shown to outperform conventional Hough transform and thinning algorithms...

Principal Component Analysis (PCA) is a popular technique with many applications. Recent randomized PCA algorithms scale to large datasets but face a bottleneck when the number of features is also large. We propose to mitigate this issue using a composition of structured and unstructured randomness within a randomized PCA algorithm. Initial experiments using a large graph dataset from Twitter s...