A technique has been designed for capturing outlines by exploiting the properties of cubic Bezier curves. The planar images are used to extract the outline. The outline is divided into curve segments at high curvature points and each segment is processed independently for piecewise curve approximation. The proposed algorithm avoids the traditional method of least square fitting which is time co...

The model not only underpredicts civil war onsets, but it also had inconsistent success in its point predictions. It points to 1960-61 as the years Chad was most vulnerable to a civil war (over six percent probability for each of these years). Yet the first civil was onset was not until 1965 when the odds were a bit over one percent, about two-thirds the world average. Although the model does n...

Learning rules from knowledge graphs (KG) is a crucial task for KG completion, cleaning and curation. The majority of existing approaches are capable of learning only Horn rules from KGs, which are, however, insufficiently expressive for capturing exceptions and thus might make incorrect predictions on missing facts. In this paper we discuss our recent progress in addressing this limitation. Mo...

1. Teichm uller space and the Teichm uller metric d(X; Y) = inf(1=2) log K(), where : X ! Y ranges over all quasiconformal mappings in the appropriate isotopy class. 2. Teichm uller's theorem: If X is compact, or more generally if X is obtained from a compact Riemann surface by removing a nite number of points, then there is an essentially map f minimizing the innmum above. (This map is unique ...

majority of models in location literature are based on assumptions such as point demand, absence of competitors, as well as monopoly in location, products, and services. however in real-world applications, these assumptions are not well-matched with reality. in this study, a new mixed integer nonlinear programming model based on weighted goal programming approach is proposed to maximize the cap...

Hierarchical graphs are a frequent solution for capturing symbolic data due the importance of hierarchies for defining knowledge. In these graphs, relations among elements may contain large portions of the element’s semantics. However, knowledge discovery based on analyzing the patterns of hierarchical relations is rarely used. We outline four inference based algorithms exploiting semantic prop...