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AGI’s Hierarchical Component Approach to Unsolvable by Direct Statistical Methods Complex Problems
Engineering Proceedings, 2023 The amazing deep neural network (DNN) advances over the past 10 years have made it possible, if there is enough data and computing power, to achieve solutions to unexpectedly complex problems.
Vladimir Smolin, Sergey Sokolov
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Uncertainty Analysis of Neutron Diffusion Eigenvalue Problem Based on Reduced-order Model
Yuanzineng kexue jishu, 2023 In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model ...
In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model based on POD-Galerkin method in core physical uncertainty analysis. The two-dimensional two group TWIGL benchmark question was taken as the research object, the key variation characteristics of the core flux distribution were extracted under the finite perturbation of the group constants of each material region, and the full-order neutron diffusion problem was projected on the variation characteristics to establish a reduced-order neutron diffusion model. The reduced-order model was used to replace the full-order model to carry out the uncertainty analysis of the group constants of the material region. The results show that the bias of the mathematical expectation of keff calculated by reduced-order and full-order models is close to 1 pcm. In addition, compared with the calculation time required for uncertainty analysis of full-order model, the analysis time of reduced-order model (including the calculation time of the full-order model required for the construction of reduced-order model) is only 11.48%, which greatly improves the efficiency of uncertainty analysis. The biases of mathematical expectation of keff calculated by reduced-order and full-order models based on Latin hypercube sampling and simple random sampling are less than 8 pcm, and under the same sample size, the bias from the Latin hypercube sampling result is smaller. From the TWIGL benchmark test results, under the same sample size, Latin hypercube sampling method is more recommended for POD-Galerkin reduced-order model.
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Alcohol consumption patterns of the Hungarian general and Roma populations
Frontiers in Public Health, 2023 IntroductionHarmful alcohol use is a significant public health problem worldwide, though the alcohol-related burden affects disproportionately certain populations and ethnic minorities, with the WHO European Region being the most heavily affected and ...
Ali Abbas Mohammad Kurshed +9 more
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Decomposition into Cycles I: Hamilton Decompositions [PDF]
, 1990 In this part we survey the results concerning the partitions of the edge-set of a graph into Hamilton cycles or into Hamilton cycles and a single perfect matching.
Alspach, Brian +2 more
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Ecology and Evolution, 2022 Decomposition is essential to carbon, nutrient, and energy cycling among and within ecosystems. Several methods have been proposed for studying litter decomposition by using a standardized and commercially available substrate. One of these methods is the
Lovisa Lind +4 more
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Computing cylindrical algebraic decomposition via triangular decomposition [PDF]
Proceedings of the 2009 international symposium on Symbolic and algebraic computation, 2009 Cylindrical algebraic decomposition is one of the most important tools for computing with semi-algebraic sets, while triangular decomposition is among the most important approaches for manipulating constructible sets. In this paper, for an arbitrary finite set $F \subset {\R}[y_1, ..., y_n]$ we apply comprehensive triangular decomposition in order to ...
Chen, Changbo +3 more
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Ecology and Evolution, 2022 Dung beetles are important actors in the self‐regulation of ecosystems by driving nutrient cycling, bioturbation, and pest suppression. Urbanization and the sprawl of agricultural areas, however, destroy natural habitats and may threaten dung beetle ...
Jana Englmeier +21 more
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Drought Impacts on Tree Root Traits Are Linked to Their Decomposability and Net Carbon Release
Frontiers in Forests and Global Change, 2022 Root trait plasticity can facilitate plant adjustment to water shortages, but the impact of altered traits on belowground carbon (C) cycling is mostly unknown.
Yolima Carrillo +4 more
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Smoothing the Boundaries between the Domains of the Surface Computational Mesh
Современные информационные технологии и IT-образование, 2021 For the efficient use of supercomputer computing resources in solving problems of simulation, a high-quality decomposition of the computational meshes is of great importance.
Andrey Bagrov, Alexey Rybakov
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Proceedings of the 2018 ACM Conference on International Computing Education Research, 2018 As new initiatives in computational thinking and computer science (CS/CT) are being developed and deployed, it is important to identify and understand the key concepts that are essential for student learning. In this study, we present the phases of construction of a learning trajectory (LT) for Decomposition in the context of CS/CT in K-8 education ...
Kathryn M. Rich +3 more
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