This paper proposes a prediction engine designed for non-dedicated clusters, which is able to estimate the turnaround time for parallel applications, even in the presence of serial workload of the workstation owner. T...
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This paper proposes a prediction engine designed for non-dedicated clusters, which is able to estimate the turnaround time for parallel applications, even in the presence of serial workload of the workstation owner. The prediction engine can be configured to work with three different estimation kernels: a Historical kernel, a Simulation kernel based on analytical models and an integration of both, named Hybrid kernel. These estimation proposals were integrated into a scheduling system, named CISNE, which can be executed in an on-line or off-line mode. The accuracy of the proposed estimation methods was evaluated in relation to different job scheduling policies in a real and a simulated cluster environment. In both environments, we observed that the Hybrid system gives the best results because it combines the ability of a simulation engine to capture the dynamism of a non-dedicated environment together with the accuracy of the historical methods to estimate the application runtime considering the state of the resources.
This paper presents a fully automated and unsupervised method for the segmentation of tumours in PET images. The segmentation technique incorporates a pre-processing stage and a hierarchical approach based on an impro...
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This paper presents a fully automated and unsupervised method for the segmentation of tumours in PET images. The segmentation technique incorporates a pre-processing stage and a hierarchical approach based on an improved region-scalable energy fitting model. The advantages of the approach lie in its multi-level processing. It first considers the whole range of grey levels in the image volume, which is able to avoid local maxima. Subsequently, the local grey levels range is utilized to refine the segmentation which effectively avoids false negative segmentations. We validate our method using real PET images of head-and-neck cancer patients as well as custom-designed phantom PET images. Compared with other popular approaches, the experimental results on both data sets show that our method can accurately segment tumours in PET images.
Nowadays cardiovascular diseases are one of the most major causes of mortality. Computed Tomography Angiography (CTA) is a very useful imaging tool for cardiovascular disease diagnosis. So it is important to analyze C...
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ISBN:
(纸本)9781467331289
Nowadays cardiovascular diseases are one of the most major causes of mortality. Computed Tomography Angiography (CTA) is a very useful imaging tool for cardiovascular disease diagnosis. So it is important to analyze CTA images well. This paper proposed a new method for fully automatic cardiovascular segmentation based on combination of Hough transform and region growing algorithm. It is a robust method which segments ascending aorta, descending aorta, and left ventricle concurrently. Comparing to the manual method which is done by cardiologist and previous automatic and semi-automatic works, our method is faster, more accurate, and fully automatic. This procedure also can be applied to coronary segmentation. The validation of the acquired cardiovascular images is evaluated by a cardiologist. By evaluating 10 datasets, which contain about 5000 images, the accuracy of the method is 97.3% comparing to the gold standard. Our gold standard is the images segmented by cardiologist. In addition, average elapsed time is 0.18s per image.
In order to capture a selective packaging mechanism among eight RNA segments in influenza A viruses, we assume that almost nucleotides in the positions of packaging signals must be simultaneously changed. In this pape...
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ISBN:
(纸本)9781467327428
In order to capture a selective packaging mechanism among eight RNA segments in influenza A viruses, we assume that almost nucleotides in the positions of packaging signals must be simultaneously changed. In this paper, we formulate such positions as correlated mutations based on a joint entropy ratio, develop a method of finding all of them by using set enumeration with pruning and apply to nucleotide sequences among RNA segments in H3N2 influenza viruses.
This paper presents a combination of existing advanced methods to solve the partial volume segmentation problem. It uses region-based active surface modelling in a hierarchical scheme to eliminate segmentation errors,...
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This paper presents a combination of existing advanced methods to solve the partial volume segmentation problem. It uses region-based active surface modelling in a hierarchical scheme to eliminate segmentation errors, followed by an alpha matting step to further refine the segmentation. This method can have an interest in several applications in medical imaging. We have validated our method on real PET images of head-and-neck cancer patients as well as custom designed phantom PET images. Experiments show that our method can generate more accurate segmentation than existing approaches.
In this paper,a robust distributed order PI controller design method is derived,which tolerates certain system *** theory and implementation of the distributed order operators are discussed in both time and frequency
In this paper,a robust distributed order PI controller design method is derived,which tolerates certain system *** theory and implementation of the distributed order operators are discussed in both time and frequency
An improved inductor layout with non-uniform metal width and non-uniform spacing is proposed to increase the quality factor(Q factor).For this inductor layout,from outer coil to inner coil,the metal width is reduced...
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An improved inductor layout with non-uniform metal width and non-uniform spacing is proposed to increase the quality factor(Q factor).For this inductor layout,from outer coil to inner coil,the metal width is reduced by an arithmetic-progression step,while the metal spacing is increased by a geometric-progression step. An improved layout with variable width and changed spacing is of benefit to the Q factor of RF spiral inductor improvement(approximately 42.86%),mainly due to the suppression of eddy-current loss by weakening the current crowding effect in the center of the spiral *** order to increase the Q factor further,for the novel inductor, a patterned ground shield is used with optimized layout *** results indicate that,in the range of 0.5 to 16 GHz,the Q factor of the novel inductor is at an optimum,which improves by 67%more than conventional inductors with uniform geometry dimensions(equal width and equal spacing),is enhanced by nearly 23%more than a PGS inductor with uniform geometry dimensions,and improves by almost 20%more than an inductor with an improved layout.
The IEEE RAS Ontologies for Robotics and Automation Working Group is dedicated to developing a methodology for knowledge representation and reasoning in robotics and automation. As part of this working group, the Auto...
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We consider the security of continuous-variable quantum key distribution using thermal (or noisy) Gaussian resource states. Specifically, we analyze this against collective Gaussian attacks using direct and reverse re...
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We consider the security of continuous-variable quantum key distribution using thermal (or noisy) Gaussian resource states. Specifically, we analyze this against collective Gaussian attacks using direct and reverse reconciliation where both protocols use either homodyne or heterodyne detection. We show that in the case of direct reconciliation with heterodyne detection, an improved robustness to channel noise is achieved when large amounts of preparation noise is added, as compared to the case when no preparation noise is added. We also consider the theoretical limit of infinite preparation noise and show a secure key can still be achieved in this limit provided the channel noise is less than the preparation noise. Finally, we consider the security of quantum key distribution at various electromagnetic wavelengths and derive an upper bound related to an entanglement-breaking eavesdropping attack and discuss the feasibility of microwave quantum key distribution.
The problem of the distributed identification of a macroscopic first-order traffic model, viz. the Cell Transmission Model (CTM), is considered in the paper. The parameters to be identified characterize the dynamics o...
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ISBN:
(纸本)9781457710957
The problem of the distributed identification of a macroscopic first-order traffic model, viz. the Cell Transmission Model (CTM), is considered in the paper. The parameters to be identified characterize the dynamics of the density in different sections of the freeway (cells). We explore different distributed identification schemes. The purposes of the approach are mainly to obtain good prediction models through the minimization of the one-step ahead prediction error of the densities of the cells, and to reduce the computational time and the effort required to perform the identification. The methodology is validated relying on real-life data measured on a portion of the A12 freeway in The Netherlands. An evaluation of the performance of the identified model used as a set of virtual sensors in different scenarios is presented.
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