Results 91 to 100 of about 76,024 (266)
MathematicsThe demand for thermal power generation from natural gas has increased globally due to its cleaner burning properties compared to other fossil fuels.
Cristian Alejandro Blanco-Martínez +4 more
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Advanced Engineering Materials, EarlyView.A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
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工程科学学报In this paper, we explore the decentralized control problem through the lens of adaptive dynamic programming for continuous-time nonlinear systems, particularly those with unknown mismatched interconnections and asymmetric input constraints.
Ding WANG, Wenqian FAN, Ao LIU
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Approximating Scheduling Machines with Capacity Constraints
, 2009 In the Scheduling Machines with Capacity Constraints problem, we are given k identical machines, each of which can process at most m_i jobs. M jobs are also given, where job j has a non-negative processing time length t_j >= 0. The task is to find a schedule such that the makespan is minimized and the capacity constraints are met.
Chi Zhang +3 more
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Advanced Engineering Materials, EarlyView.A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source
Acta Polytechnica, 2004 The paper examines an effect of boundary constraints applied to the enhanced degrees of freedom of partition of unity based discontinuous elements. To highlight the present issue the problem is studied in a one-dimensional setting.
M. Audy, M. Šejnoha
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Upper-bound envelope learning via -norm regularized LSSVR
Machine Learning: Science and TechnologyMost data-driven regression approaches primarily estimate mean responses or function approximation rather than delivering empirical upper-bound descriptions of system outputs. This constraint limits their suitability for safety-critical applications that
Xiaoyong Liu, Peng Tian, Yun Liu
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Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
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Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
Convergent approximate solving of first-order constraints by approximate quantifiers
ACM Transactions on Computational Logic, 2004 Exactly solving first-order constraints (i.e., first-order formulas over a certain predefined structure) can be a very hard, or even undecidable problem. In continuous structures like the real numbers it is promising to compute approximate solutions instead of exact ones. However, the quantifiers of the first-order predicate language are an obstacle to
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