A large class of hyperbolic and advection-dominated PDEs can have solutions with discontinuities. This paper investigates, both theoretically and empirically, the operator learning of PDEs with discontinuous solutions...
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In this paper, a novel multiband phased array antenna with endfire radiation pattern is designed at millimeter-wave (mmWave) frequency bands for 5G mobile applications. The proposed antenna element is a compact quasi-...
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Existing permanental processes often impose constraints on kernel types or stationarity, limiting the model’s expressiveness. To overcome these limitations, we propose a novel approach utilizing the sparse spectral r...
Electronic structure calculations in the time domain provide a deeper understanding of nonequilibrium dynamics in materials. The real-time Boltzmann equation (rt-BTE), used in conjunction with accurate interactions co...
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This paper is designed to provide a comprehensive overview of the latest developments in fault tolerance methods for cloud computing. Maintaining high availability and reliability of cloud environments requires fault ...
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ISBN:
(数字)9798331540173
ISBN:
(纸本)9798331540180
This paper is designed to provide a comprehensive overview of the latest developments in fault tolerance methods for cloud computing. Maintaining high availability and reliability of cloud environments requires fault tolerance. This paper explores fault tolerance in the context of cloud computing and discusses recent challenges and innovations in the field. Moreover, it examines the ongoing research efforts to improve fault-tolerance architectures. At the end of the paper, the paper presents system-level metrics that are relevant to fault tolerance.
With the emergence of current developments and their devices that allow correspondence between organizations with each other, just as it is between organizations and service providers, just as with their customers, fo...
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Compared with rasterization rendering, ray tracing rendering can improve the image’s visual effect and make the image look more realistic. Real-time ray tracing requires very high computing power of graphics processi...
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Superconducting-nanostrip photon detectors with optical sampling method now function as true photon-number resolving detectors in real-time without multiplexing. We applied this technique for quantum state generation ...
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Image enhancement, particularly in low-light conditions, has long been a research focus to improve visual quality. Low-light settings often cause visibility issues and detail loss, which recent deep-learning technique...
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ISBN:
(数字)9798331505264
ISBN:
(纸本)9798331505271
Image enhancement, particularly in low-light conditions, has long been a research focus to improve visual quality. Low-light settings often cause visibility issues and detail loss, which recent deep-learning techniques have effectively addressed. This study explores the combination of a low-light convolutional neural network (LLCNN), a convolutional neural network designed explicitly for low-light image enhancement, with a Squeeze and Excitation Network (SEN), which recalibrate features to emphasise critical details and suppress noise. Integrating SEN into LLCNN enhances image details while reducing noise and artefacts typically present in low-light conditions. Experimental results show that this combined approach outperforms existing methods in objective metrics, such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), as well as visual quality.
Motivated by the quantum speedup for dynamic programming on the Boolean hypercube by Ambainis et al. (2019), we investigate which graphs admit a similar quantum advantage. In this paper, we examine a generalization of...
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