Titlebook: Mathematical and Engineering Methods in Computer Science; 10th International D Jan Kofroň,Tomáš Vojnar Conference proceedings 2016 Springer

peptic-ulcer

Flexible Interpolation for Efficient Model Checking,hms rely on over-approximating the reachable state space of the system. This task is critical since it not only greatly affects the efficiency of the verification but also whether the model-checking procedure terminates. This paper reports an implementation of an over-approximation tool based on fir

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Oratory

Practical Exhaustive Generation of Small Multiway Cuts in Sparse Graphs,support a complete analysis of critical combinations of road disruptions in real-world road networks. Our algorithm elaborates on a simple underlying idea from matroid theory – that a circuit-cocircuit intersection cannot have cardinality one (here cocircuits are the generated cuts). We evaluate the

Amenable

Self-Adaptive Architecture for Multi-Sensor Embedded Vision System,ngle color sensor and they do not address the heterogeneous sensors challenge. However, more and more applications require other types of sensor, in addition, such as infrared or low-light sensor, so that the vision system could face various luminosity conditions. These heterogeneous sensors could d

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,Exceptional Configurations of Quantum Walks with Grover’s Coin,ansformation — Grover’s diffusion transformation — has a wide class of exceptional configurations of marked locations, for which the probability of finding any of the marked locations does not grow over time. This extends the class of known exceptional configurations; until now the only known such c

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GPU-Accelerated Real-Time Mesh Simplification Using Parallel Half Edge Collapses,simplification, the parallel half edge collapse. Based on the half edge collapse that replaces an edge with one of its endpoints, we have devised a simplification method that allows the execution of half edge collapses on multiple vertex pairs of a mesh in parallel, using a set of per-vertex boundar

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Classifier Ensemble by Semi-supervised Learning: Local Aggregation Methodology,NAR instances as mine or mine-like object. The proposed semi-supervised algorithm minimizes some target functions, which fuse context identification, multi-algorithm fusion criteria and a semi-supervised learning term. Our optimization purpose is to learn contexts as compact clusters in subspaces of