Cloud storage is an emerging archetype used by businesses for data storage. Clients require easy access to data in the cloud, which helps clients with limited computing power move their high-value, high-risk principle...
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Time-of-flight neutron imaging offers complementary attenuation contrast to X-ray computed tomography (CT), coupled with the ability to extract additional information from the variation in attenuation as a function of...
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The Density-functional theory(DFT) should be the most popular approach that used in computational physics or computational chemistry community. Normally, the computational time is unknown until the calculation is done...
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The Density-functional theory(DFT) should be the most popular approach that used in computational physics or computational chemistry community. Normally, the computational time is unknown until the calculation is done. And as such, researchers can hardly arrange their schedules rationally. Additionally, for calculations that are carried out with computing clusters, unreasonable schedules would greatly increase the time and energy cost. Herein, we introduced a smart forecasting system based on three machine learning models, which are RF with FNNs(random forest with feedforward neural networks), Bi-LSTM with attention mechanism[1,2,3] and MPNN[4](message passing neural networks). The three models can accept the molecular information, calculating scheme(the combination of basis set and functional etc.) and machine configuration information as inputs, and then can predict the proposed computational cost. Comparing to the actual computational time, the average relative error is generally less than 20%, and it follows the normal distribution[5].
The accurate electronic structure calculation for strongly correlated chemical systems requires an adequate description for both static and dynamic electron correlation, and is a persistent challenge for quantum chemi...
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The recent development of the density matrix renormalization group (DMRG) method in multireference quantum chemistry makes it practical to evaluate static correlation in a large active space, while dynamic correlation...
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Multipath transmission in intermediate nodes is a promising approach to support high bandwidth applications. To prevent out-of-order packet deliveries, packet re-sequencing nodes must be deployed. In this paper, we pr...
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ISBN:
(纸本)9781479917761
Multipath transmission in intermediate nodes is a promising approach to support high bandwidth applications. To prevent out-of-order packet deliveries, packet re-sequencing nodes must be deployed. In this paper, we propose a multipath transmission model that incorporates packet re-sequencing buffers and the Random with Availability Check policy. After mathematically analyzing the model, we show numerical comparisons between the Random with Availability Check and Random policies.
This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to ac...
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This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to ac...
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This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to activation detection in task-related functional Magnetic Resonance Imaging (fMRI) of the human brain. The method is illustrated using fMRI data simulated under one paradigm as well as one real dataset, and its performance is compared to those of a leading model based (General Linear Model ? GLM) and a leading data-driven (Region Growing Method ? RGM) approach. It is concluded that the proposed method achieves much better performance than the computationally inefficient RGM and is slightly more sensitive than GLM. Experimental results support its efficiency and sensitivity, which indicates that it is to become a viable alternative to the fMRI analysis.
Recently, combining a video recording of a presentation along with the digital slides used in it has become popular in e-learning and presentation of archives. For users of the archives, it is useful to preview a dige...
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Recently, combining a video recording of a presentation along with the digital slides used in it has become popular in e-learning and presentation of archives. For users of the archives, it is useful to preview a digest of such content to grasp the atmosphere and/or an outline of the presentation. This paper proposes a method of automatic digest generation by extracting important scenes from the presentation content. The extracted scenes are chosen based on several factors such as frequency and specificity of words, scene duration and order. Finally, the effectiveness of the proposed methods are evaluated by comparing with testers' answer sets for actual lectures.
In this paper, a new texture feature set based on M-band wavelet analysis is proposed for online Palmprint identification. First, the central part of a palm was decomposed by M-band wavelets transformation, then, 1-no...
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