Karel Bauters

A modular and hierarchically structured techno-economic model for FTTH deployments Comparison of technology and equipment placement as function of population density and number of flexibility points

Telecommunications is a domain that is characterized by a constant and rapid evolution. The available bandwidth keeps on increasing as the amount and quality of the offered services grows almost continuously, and it is generally accepted that upgrades towards Fiber-to-the-Home (FTTH) are necessary. FTTH comes in a plentitude of variations, mainly differing between Point-to-Point and Point-to-Multipoint solutions. Several techno-economic calculations comparing these options are available in literature today, but they lack a generic structured calculation and never focus on the impact of the size of the area and population density on the cost of deployment and operations of an FTTH network. This paper will present a flexible, generic model for techno-economic evaluation of an FTTH network that compares different solutions considering equipment type and placement for a broad range of population densities. The outcome of the simulations proofs the versatility of the generic techno-economic calculation approach and show the impact of the tradeoff in equipment placement and distance to the central office.

An automated work cycle classification and disturbance detection tool for assembly line work stations

The trend towards mass customization has led to a significant increase of the complexity of manufacturing systems. Models to evaluate the complexity have been developed, but the complexity analysis of work stations is still done manually. This paper describes an automated analysis tool that makes us of multi-camera video images to support the complexity analysis of assembly line work stations.

Abnormal work cycle detection based on dissimilarity measurement of trajectories

This paper proposes a method for detecting the abnormalities of the executed work cycles for the factory workers using their tracks obtained in a multi-camera network. The method allows analyzing both spatial and temporal dissimilarity between the pairwise tracks. The main novelty of the methods is calculating spatial dissimilarity between pair-wise tracks by aligning them using Dynamic Time Warping (DTW) based on coordinate distance, and specially the velocity and dwell time dissimilarity using a different track alignment based on velocity difference. These dissimilarity measurements are used to cluster the executed work cycles and detect abnormalities. The experimental results show that our algorithm outperforms other methods on clustering the tracks because of the use of temporal dissimilarity.