In this chapter, we propose two novel and curvature-free features: run-lengths of Local Binary Pattern (LBPruns) and Cloud Of Line Distribution (COLD) features for writer identification. The LBPruns is the joint distribution of the traditional run-length and local binary pattern (LBP) methods, which computes the run-lengths of local binary patterns on both binarized images and gray scale images...

Sentiment analysis is an emerging research field that can be integrated with other domains, including data mining, natural language processing and machine learning. In political articles, it difficult to understand summarise the state or overall views due diversity size of social media information. A number studies were conducted in area sentiment analysis, especially using English texts, while...

The two-dimensional discrete bin-packing problem (2BP ) consists in minimizing the number of identical rectangles used to pack a set of smaller rectangles. This problem is NP-complete. It occurs in industry if pieces of steel, wood, or paper have to be cut from larger rectangles. It belongs to the family of cutting and packing (C & P) problems, more precisely Two-Dimensional Single Bin Size Bin...

Conventional binary classiication trees such as CART either split the data using axis-aligned hyperplanes or they perform a compu-tationally expensive search in the continuous space of hyperplanes with unrestricted orientations. We show that the limitations of the former can be overcome without resorting to the latter. For every pair of training data-points, there is one hyperplane that is orth...

Mathematics requires three markers to define a local coordinate system to calculate rotations in three dimensions (3D), as three coordinates are necessary to specify the orientation of a rigid body with respect to a fixed set of space axes. However, it is not uncommon in wheelchair literature to find papers (Veeger, et al., 1991) that used only two markers to define segment rotation in three di...

Strong restricted-orientation convexity is a generalization of standard convexity. We explore the properties of strongly convex sets in multidimensional Euclidean space and identify major properties of standard convex sets that also hold for strong convexity. We characterize strongly convex flats and halfspaces, and establish the strong convexity of the affine hull of a strongly convex set. We ...