The 13th issue of the Transactions on Computational Science journal consists of two parts. The six papers in Part I span the areas of computing collision probability, digital image contour extraction, multiplicatively weighted Voronoi diagrams, multi-phase segmentation, the rough-set approach to incomplete information systems, and fault-tolerant systolic arrays for matrix multiplications. The five papers in Part II focus on neural-network-based trajectory prediction, privacy in vehicular ad-hoc networks, augmented reality for museum display and the consumer garment try-on experience, and geospatial knowledge discovery for crime analysis.

The first part focuses on computational models The focus of the second part is on networks and augmented reality Both theoretical and applicational papers are included

Klappentext

The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. The 13th issue of the Transactions on Computational Science journal consists of two parts. The six papers in Part I span the areas of computing collision probability, digital image contour extraction, multiplicatively weighted Voronoi diagrams, multi-phase segmentation, the rough-set approach to incomplete information systems, and fault-tolerant systolic arrays for matrix multiplications. The five papers in Part II focus on neural-network-based trajectory prediction, privacy in vehicular ad-hoc networks, augmented reality for museum display and the consumer garment try-on experience, and geospatial knowledge discovery for crime analysis.

Inhalt
Collision Probability in an In-Line Machines Model.-A Computational-Geometry Approach to Digital Image ContourExtraction.-On Multiplicatively Weighted Voronoi Diagrams for Lines in the Plane.-Fast Streaming 3D Level Set Segmentation on the GPU for Smooth Multi-phase Segmentation.-Valued Dominance-Based Rough Set Approach to Incomplete Information System.-An FPGA-Based Fault-Tolerant 2D Systolic Array for Matrix Multiplications.-Neural Network Based Lane Change Trajectory Prediction in Autonomous Vehicles.-Conditional Privacy through Ring Signature in Vehicular Ad-Hoc Networks.-Establishing a Museum Display Platform by Using Combination of Reflection Holograms and Tangible Augmented Reality.-Applying Augmented Reality to Consumer Garment Try-On Experience.-Geospatial Knowledge Discovery Framework for Crime Domain.