Power Saving Class (PSC) is an essential issue on IEEE 802.16-2009. In previous research, many algorithms had been proposed to reduce the consumption of power, but most of them only considered multiple connections in ...
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A parallel distributed approach to refine a mesh while preserving the curvature of a target geometry is presented. Our approach starts by generating a coarse linear mesh of the computational domain. Second, the former...
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A parallel distributed approach to refine a mesh while preserving the curvature of a target geometry is presented. Our approach starts by generating a coarse linear mesh of the computational domain. Second, the former coarse mesh is curved to match the curvature of the target geometry. Then, the curved mesh is partitioned and the subdomain meshes are sent to the slaves. Finally, the curved elements are uniformly subdivided in parallel targeting the geometry approximated by the curved mesh. The result is a distributed finer linear mesh featuring improved geometric accuracy. The key ingredient of our implementation is to approximate the target geometry as a linear mesh equipped with an elemental field corresponding to an element-wise polynomial geometry representation. Thus, the distribution of the curved geometry is equivalent to partitioning the linear mesh and sending the subdomain meshes and the elemental fields to the slaves. The main application of the obtained finer linear mesh is to compute in parallel steady state flow solutions on real topographies. The qualitative results show that for 2D and 3D steady state flow solutions, on real and synthetic topographies, our parallel subdivision approach mitigates the artificial artifacts that might appear with standard straight-sided subdivision methods. We also check the parallel performance of the implementation by performing a weak scalability test in 2D.
This paper presents a new multi-band stopband filter loaded by a shorted metamaterial circuit. Firstly, two filters loaded by stubs and open ring resonators (ORRs) are studied and compared. The ORRs allow more effects...
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The rise of ubiquitous deepfakes, misinformation, disinformation and post-truth, often referred to as fake news, raises concerns over the role of Internet and social media in modern democratic societies. Due to its ra...
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X-Ray fluorescence (XRF) scanning of works of art is becoming an increasingly popular non-destructive analytical method. The high quality XRF spectra is necessary to obtain significant information on both major and mi...
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ISBN:
(纸本)9781509019304
X-Ray fluorescence (XRF) scanning of works of art is becoming an increasingly popular non-destructive analytical method. The high quality XRF spectra is necessary to obtain significant information on both major and minor elements used for characterization and provenance analysis. However, there is a trade-off between the spatial resolution of an XRF scan and the Signal-to-Noise Ratio (SNR) of each pixel's spectrum, due to the limited scanning time. In this paper, we propose an XRF image super-resolution method to address this trade-off, thus obtaining a high spatial resolution XRF scan with high SNR. We use a sparse representation of each pixel using a dictionary trained from the spectrum samples of the image, while imposing a spatial smoothness constraint on the sparse coefficients. We then increase the spatial resolution of the sparse coefficient map using a conventional super-resolution method. Finally the high spatial resolution XRF image is reconstructed by the high spatial resolution sparse coefficient map and the trained spectrum dictionary.
There has recently been increasing interests in using system virtualization to improve the dependability of HPC cluster systems. However, it is not cost-free and may come with some performance degradation, uncertain Q...
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There has recently been increasing interests in using system virtualization to improve the dependability of HPC cluster systems. However, it is not cost-free and may come with some performance degradation, uncertain QoS and loss of functionalities. Meanwhile, many virtualization-enabled features such as online maintenance and fault tolerance do not require virtualization being always on. This paper proposes a technique, called self-virtualization, that supports dynamically attaching and detaching a full-fledged virtual machine monitor (VMM) beneath an operating system, without disturbing applications thereon, and rid the system of potential overhead when the virtualization is not needed. This technique enables HPC clusters to reap most benefits from virtualization without sacrificing performance. This paper presents the design and implementation of Mercury, a working prototype based on Linux and Xen VMM. Our performance measurement shows that Mercury incurs very little overhead: about 0.2 ms to complete a mode switch, and negligible performance degradation compared to Linux.
In this paper a different approach to build an uninterruptible power supply (UPS) system is presented. The proposed scheme includes features such as high power factor, low total harmonic distortion and good dynamic re...
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In this paper a different approach to build an uninterruptible power supply (UPS) system is presented. The proposed scheme includes features such as high power factor, low total harmonic distortion and good dynamic response at the output voltage. This scheme has the desirable features of high efficiency, simple circuit and low cost compared to a traditional standalone multiple stages UPS with power factor correction. The circuit operation, analysis and experimental results of the proposed UPS scheme are presented. The UPS approach is a good solution for low power applications (&le 500 W).
In this work, we present a method for automatic colorization of grayscale videos. The core of the method is a Generative Adversarial Network that is trained and tested on sequences of frames in a sliding window manner...
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In this paper, we propose an iterative algorithm towards the automatic labeling of Twitter accounts in respect to thematic categories derived from DBpedia properties. We describe the rationale behind the selection of ...
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ISBN:
(纸本)9781509052479
In this paper, we propose an iterative algorithm towards the automatic labeling of Twitter accounts in respect to thematic categories derived from DBpedia properties. We describe the rationale behind the selection of these thematic categories, and discuss their evaluation assessment. Finally, we propose and analyze two generic and adaptable methodologies for discovering the necessary linked data resources for further enhancing the thematic description of Twitter accounts.
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