Occupational Fraud Detection Through Visualization

Occupational fraud affects many companies worldwide causing them economic loss and liability issues towards their customers and other involved entities. Detecting internal fraud in a company requires significant effort and, unfortunately cannot be entirely prevented. The internal auditors have to process a huge amount of data produced by diverse systems, which are in most cases in textual form, with little automated support. In this paper, we exploit the advantages of information visualization and present a system that aims to detect occupational fraud in systems which involve a pair of entities (e.g., an employee and a client) and periodic activity. The main visualization is based on a spiral system on which the events are drawn appropriately according to their time-stamp. Suspicious events are considered those which appear along the same radius or on close radii of the spiral. Before producing the visualization, the system ranks both involved entities according to the specifications of the internal auditor and generates a video file of the activity such that events with strong evidence of fraud appear first in the video. The system is also equipped with several different visualizations and mechanisms in order to meet the requirements of an internal fraud detection system

Multi-level caching with delayed-multicast for video-on-demand

Delayed-Multicast is a novel transmission technique to support Video-on-Demand. It introduces buffers within the network to bridge the temporal delays between similar requests thus minimizing the aggregate bandwidth and server load. This paper introduces an improved online algorithm for resource allocation with Delayed-Multicast by utilizing prior knowledge of each clip's popularity. The algorithm is intended to be simple so as to allow for deployment at multiple levels in a distribution network. The result is greater backbone traffic savings and a corresponding reduction in the server load

Many-to-One Boundary Labeling with Backbones

In this paper we study \emph{many-to-one boundary labeling with backbone leaders}. In this new many-to-one model, a horizontal backbone reaches out of each label into the feature-enclosing rectangle. Feature points that need to be connected to this label are linked via vertical line segments to the backbone. We present dynamic programming algorithms for label number and total leader length minimization of crossing-free backbone labelings. When crossings are allowed, we aim to obtain solutions with the minimum number of crossings. This can be achieved efficiently in the case of fixed label order, however, in the case of flexible label order we show that minimizing the number of leader crossings is NP-hard.Comment: 23 pages, 10 figures, this is the full version of a paper that is about to appear in GD'1

Computing upward topological book embeddings of upward planar digraphs

This paper studies the problem of computing an upward topological book embedding of an upward planar digraph G, i.e. a topological book embedding of G where all edges are monotonically increasing in the upward direction. Besides having its own inherent interest in the theory of upward book embeddability, the question has applications to well studied research topics of computational geometry and of graph drawing. The main results of the paper are as follows. -Every upward planar digraph G with n vertices admits an upward topological book embedding such that every edge of G crosses the spine of the book at most once. -Every upward planar digraph G with n vertices admits a point-set embedding on any set of n distinct points in the plane such that the drawing is upward and every edge of G has at most two bends. -Every pair of upward planar digraphs sharing the same set of n vertices admits an upward simultaneous embedding with at most two bends per edge