Improving workforce scheduling of aircraft line maintenance at Sabena Technics.

This paper presents our application of a visualization tool and optimization model based on mixed-integer linear programming to solve a workforce staffing and scheduling problem at Sabena Technics, a major aircraft maintenance company in Belgium. We used the software to generate many alternative, cost-efficient schedules and to analyze multiple scenarios. In several management meetings, takeholders evaluated the schedules and raised concerns. We subsequently changed the model to successfully address their concerns. The model has resulted in considerable savings and a more efficient use of human resources.Workforce staffing; Scheduling; Optimization; Visualization; Aircraft maintenance;

Design of Electrophoresis Device for Optimation of Dna Visualization and Dna Concentration Using Software

Molecules of deoxyribo nucleic acid (DNA) show a strong polarization allowing for both motions of the dielectrophoresis induced by polarization and electrophoresis based on its negative charge. Considering high subjective and less quantifiable result of the visualization based qualitative test of DNA on gel electrophoresis, designing the tool using a combination of the principles of electrophoresis and dielectrophoresis completed with a software for optimization of DNA visualization and to measure the concentration of small and large–sized DNA fragment is very needed. Accuracy of measurement of DNA concentration using a spectrophotometer UV /VIS is depend on its availability in the laboratory. The aim of this study was to design device for optimization of DNA visualization and measuring the concentration in the gel electrophoresis using MatLab- based software. Experiment using this software measured the concentration of DNA based on its visualization and compared it with calculation obtained from spectrophotometer UV/VIS. The research results showed that the amount of DNA analysed using a spectrophotometer tend to similar with the measurement results using the MatLab-based software although there was differences in quantitative values

Modularity-Based Clustering for Network-Constrained Trajectories

We present a novel clustering approach for moving object trajectories that are constrained by an underlying road network. The approach builds a similarity graph based on these trajectories then uses modularity-optimization hiearchical graph clustering to regroup trajectories with similar profiles. Our experimental study shows the superiority of the proposed approach over classic hierarchical clustering and gives a brief insight to visualization of the clustering results.Comment: 20-th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012), Bruges : Belgium (2012

The application of computational modeling to data visualization

Researchers have argued that perceptual issues are important in determining what makes an effective visualization, but generally only provide descriptive guidelines for transforming perceptual theory into practical designs. In order to bridge the gap between theory and practice in a more rigorous way, a computational model of the primary visual cortex is used to explore the perception of data visualizations. A method is presented for automatically evaluating and optimizing data visualizations for an analytical task using a computational model of human vision. The method relies on a neural network simulation of early perceptual processing in the retina and visual cortex. The neural activity resulting from viewing an information visualization is simulated and evaluated to produce metrics of visualization effectiveness for analytical tasks. Visualization optimization is achieved by applying these effectiveness metrics as the utility function in a hill-climbing algorithm. This method is applied to the evaluation and optimization of two visualization types: 2D flow visualizations and node-link graph visualizations. The computational perceptual model is applied to various visual representations of flow fields evaluated using the advection task of Laidlaw et al. The predictive power of the model is examined by comparing its performance to that of human subjects on the advection task using four flow visualization types. The results show the same overall pattern for humans and the model. In both cases, the best performance was obtained from visualizations containing aligned visual edges. Flow visualization optimization is done using both streaklet-based and pixel-based visualization parameterizations. An emergent property of the streaklet-based optimization is head-to-tail streaklet alignment, the pixel-based parameterization results in a LIC-like result. The model is also applied to node-link graph diagram visualizations for a node connectivity task using two-layer node-link diagrams. The model evaluation of node-link graph visualizations correlates with human performance, in terms of both accuracy and response time. Node-link graph visualizations are optimized using the perceptual model. The optimized node-link diagrams exhibit the aesthetic properties associated with good node-link diagram design, such as straight edges, minimal edge crossings, and maximal crossing angles, and yields empirically better performance on the node connectivity task