Results 21 to 30 of about 969,371 (282)
IEEE Open Journal of Antennas and Propagation, 2021 Computational Intelligence (CI) is the theory, design, application and development of biologically and linguistically motivated computational paradigms.
Sotirios K. Goudos +5 more
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IEEE Transactions on Machine Learning in Communications and NetworkingThis paper proposes two energy-efficient reinforcement learning (RL)-based algorithms for millimeter wave (mmWave)-enabled unmanned aerial vehicle (UAV) communications toward beyond-5G (B5G).
Ahmad Gendia +3 more
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Bias-variance decomposition in Genetic Programming
Open Mathematics, 2016 We study properties of Linear Genetic Programming (LGP) through several regression and classification benchmarks. In each problem, we decompose the results into bias and variance components, and explore the effect of varying certain key parameters on the
Kowaliw Taras, Doursat René
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Probability Theory and Mathematical Statistics E-course in Nomotex DLS [PDF]
ITM Web of Conferences, 2020 The paper considers the concept of constructing Probability Theory and Mathematical Statistics electronic course for interactive learning. The approach to the design of the e-course is described, and the advantages of using the new teaching technology in
Dimitrienko Yury I. +3 more
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Students' Proficiency in Computational Thinking Through Constructivist Learning Theory
International Journal of Mathematics and Mathematics EducationThis study aims to assess students' mathematical computational thinking skills in the Mathematics Education program, focusing on the constructivist learning paradigm.
Lilis Marina Angraini +2 more
semanticscholar +1 more source
Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models
Current Directions in Psychological Science, 2020 How do children learn to read? How do deficits in various components of the reading network affect learning outcomes? How does remediating one or several components change reading performance? In this article, we summarize what is known about learning to
J. Ziegler, C. Perry, M. Zorzi
semanticscholar +1 more source
The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior. [PDF]
PLoS ONE, 2013 The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (
Mark G Orr +2 more
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Jurnal Math Educator Nusantara: Wahana Publikasi Karya Tulis Ilmiah di Bidang Pendidikan Matematika, 2021 The implementation of online learning in computational mathematics courses has encountered various obstacles in addition to the decline in student learning outcomes. Therefore, research is aimed to explore student perceptions of online learning that has
Filda Febrinita, Wahyu Dwi Puspitasari
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Molecular Oncology, EarlyView.Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra +10 more
wiley +1 more source
Efficient learning of a one-dimensional density functional theory
Physical Review Research, 2020 Density functional theory underlies the most successful and widely used numerical methods for electronic structure prediction of solids. However, it has the fundamental shortcoming that the universal density functional is unknown.
M. Michael Denner +2 more
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