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Clinical Psychology Review, 2010 Optimism is an individual difference variable that reflects the extent to which people hold generalized favorable expectancies for their future. Higher levels of optimism have been related prospectively to better subjective well-being in times of adversity or difficulty (i.e., controlling for previous well-being).
Charles S, Carver +2 more
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High-efficacy global optimization of antenna structures by means of simplex-based predictors
Scientific Reports, 2023 Design of modern antenna systems has become highly dependent on computational tools, especially full-wave electromagnetic (EM) simulation models. EM analysis is capable of yielding accurate representation of antenna characteristics at the expense of ...
Slawomir Koziel +1 more
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Energy Efficient Power Allocation for Downlink NOMA Heterogeneous Networks With Imperfect CSI
IEEE Access, 2019 Non-orthogonal multiple access (NOMA) is a promising emerging technology that can significantly improve the utilization of spectrum and system capacity in heterogeneous wireless networks.
Xin Song +4 more
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Two-stage hybrid algorithm for recognition of industrial slab numbers with data quality improvement
Complex & Intelligent Systems, 2022 As the unique recognition of each slab, the accurate recognition of slab number is especially critical for the hot rolling production process. However, the collected data are often of low quality due to poor production environment conditions, making ...
Qingqing Liu +2 more
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On the Optimality of Optimal Income Taxation [PDF]
SSRN Electronic Journal, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Joint Uplink and Downlink Resource Allocation for D2D Communications System
Future Internet, 2019 In cellular networks, device-to-device communications can increase the spectrum efficiency, but some conventional schemes only consider uplink or downlink resource allocation.
Xin Song +4 more
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Optimization and Optimizers for Adversarial Robustness
CoRR, 2023 Empirical robustness evaluation (RE) of deep learning models against adversarial perturbations entails solving nontrivial constrained optimization problems. Existing numerical algorithms that are commonly used to solve them in practice predominantly rely on projected gradient, and mostly handle perturbations modeled by the $\ell_1$, $\ell_2$ and $\ell_\
Hengyue Liang +5 more
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Secure Communication for Uplink Cellular Networks Assisted with Full-Duplex Device-to-Device User
Future Internet, 2020 In this paper, the secure communication based on the full-duplex (FD) device-to-device (D2D) in cellular networks is proposed. For the proposed scheme, the novel model is established, in which a D2D user is played as a relay operating in FD mode to ...
Xin Song, Lin Xia, Siyang Xu, Yue Wang
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Journal of Engineering, 2018 Pilot test of complex thermal fluid recovery technology was conducted in NB35-2 heavy oil field. Wellhead uplift was detected among some oil wells, and development of offshore thermal recovery technology could be restricted by the serious safety problems
Shexia Dong +4 more
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Constrained ear decompositions in graphs and digraphs [PDF]
Discrete Mathematics & Theoretical Computer Science, 2019 Ear decompositions of graphs are a standard concept related to several major problems in graph theory like the Traveling Salesman Problem. For example, the Hamiltonian Cycle Problem, which is notoriously N P-complete, is equivalent to deciding whether a ...
Frédéric Havet, Nicolas Nisse
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