In this Letter, we propose a novel three-dimeusional （3D） color microscopy for microorganisms under photon- starved conditions using photon counting integral imaging and Bayesian estimation with adaptive priori info...In this Letter, we propose a novel three-dimeusional （3D） color microscopy for microorganisms under photon- starved conditions using photon counting integral imaging and Bayesian estimation with adaptive priori infor- mation. In photon counting integral imaging, 3D images can be visualized using maximum likelihood estimation （MLE）. However, since MLE does not consider a priori information of objects, the visual quality of 3D images may not be accurate. In addition, the only grayscale image can be reconstructed. Therefore, to enhance the visual quality of 3D images, we propose photon counting microscopy using maximum a posteriori with adaptive priori information. In addition, we consider a wavelength of each basic color channel to reconstruct 3D color images. To verify our proposed method, we carry out optical experiments.展开更多
Mobile devices are resource-limited, and task migration has become an important and attractive feature of mobile clouds. To validate task migration, we propose a novel approach to the simulation of task migration in a...Mobile devices are resource-limited, and task migration has become an important and attractive feature of mobile clouds. To validate task migration, we propose a novel approach to the simulation of task migration in a pervasive cloud environment. Our approach is based on Colored Petri Net（CPN）. In this research, we expanded the semantics of a CPN and created two task migration models with different task migration policies： one that took account of context information and one that did not. We evaluated the two models using CPN-based simulation and analyzed their task migration accessibility, integrity during the migration process, reliability, and the stability of the pervasive cloud system after task migration. The energy consumption and costs of the two models were also investigated. Our results suggest that CPN with context sensing task migration can minimize energy consumption while preserving good overall performance.展开更多
基金supported in part by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science,Information and Communications TechnologiesFuture Planning(No.2011-0030079)Basic Science Research Program through the NRF funded by the Ministry of Education(NRF-2013R1A1A2057549)
文摘In this Letter, we propose a novel three-dimeusional （3D） color microscopy for microorganisms under photon- starved conditions using photon counting integral imaging and Bayesian estimation with adaptive priori infor- mation. In photon counting integral imaging, 3D images can be visualized using maximum likelihood estimation （MLE）. However, since MLE does not consider a priori information of objects, the visual quality of 3D images may not be accurate. In addition, the only grayscale image can be reconstructed. Therefore, to enhance the visual quality of 3D images, we propose photon counting microscopy using maximum a posteriori with adaptive priori information. In addition, we consider a wavelength of each basic color channel to reconstruct 3D color images. To verify our proposed method, we carry out optical experiments.
文摘Mobile devices are resource-limited, and task migration has become an important and attractive feature of mobile clouds. To validate task migration, we propose a novel approach to the simulation of task migration in a pervasive cloud environment. Our approach is based on Colored Petri Net（CPN）. In this research, we expanded the semantics of a CPN and created two task migration models with different task migration policies： one that took account of context information and one that did not. We evaluated the two models using CPN-based simulation and analyzed their task migration accessibility, integrity during the migration process, reliability, and the stability of the pervasive cloud system after task migration. The energy consumption and costs of the two models were also investigated. Our results suggest that CPN with context sensing task migration can minimize energy consumption while preserving good overall performance.
