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Pollock model was one of the popular template matching algorithms, which constructs a three-dimensional description of each individual tree-crown envelope. Unfortunately, it is always challenging to determine parameters since each tree has different grown condition. This paper proposed an iterative least square fitting algorithm to form a Pollock model best fitting each individual tree for tree detection...
Multi-level morphological active contour algorithm (MMAC), was proposed in [3-4], to incorporate mathematical morphology for tree detection and crown delineation with the average prediction error around 4% in mountainous areas. However, two major drawbacks come with the design of MMAC algorithm, which are huge computational complexity and certain level of false alarm or omission rate. The paper provides...
Forests in mountainous areas normally contain a diverse variety, including tropical rain forests, subtropical evergreen forests, temperate forests, and alpine cold forests. These forests distribute vertically along the central region and can be categorized into broadleaved, mixed, and conifer forests. Terrain features in mountainous areas make manual inspection of forests both labor-intensive and...
To find the real risk points of internal dielectric charging (IDC), 3-D IDC simulation is performed to a typical dielectric structure considering GEO severe radiation environment (FLUMIC3). Charge transportation simulation is carried out by Geant4 and electric field is numerically computed according to the current conservation law. The aluminum shielding thickness is varied to investigate the shielding...
Elastic compute clouds are best represented by the virtual clusters in Amazon EC2 or in IBM RC2. This paper proposes a simulation based approach to scheduling scientific workflows onto elastic clouds. Scheduling multitask workflows in virtual clusters is a NP-hard problem. Excessive simulations in months of time may be needed to produce the optimal schedule using Monte Carlo simulations. To reduce...
Conventional autotuning configuration of parameters in distributed computing systems using evolutionary strategies increases integrated performance notably, though at the expense of consuming too much measurement time. An ordinal optimization (OO) based strategy is proposed in this work, combined with neural networks to improve system performance and reduce measurement time, which is fast enough to...
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