Results 91 to 100 of about 3,561,056 (252)

Uncertainty Modeling of a Modified SEIR Epidemic Model for COVID-19. [PDF]

Biology (Basel), 2022
Wang Y, Wang P, Zhang S, Pan H.
europepmc   +1 more source

Uncertainty-Informed Model Selection Method for Nonlinear System Identification and Interpretable Machine Learning [PDF]

Modeling uncertainty has been an active and important topic in the fields of data-driven modeling and machine learning. Uncertainty ubiquitously exists in any data modeling process, making it challenging to identify the optimal models among many ...
Gu, Yuanlin, Wei, Hua-Liang
core   +1 more source

Tolerance analysis approach based on the classification of uncertainty (aleatory / epistemic) [PDF]

, 2012
Uncertainty is ubiquitous in tolerance analysis problem. This paper deals with tolerance analysis formulation, more particularly, with the uncertainty which is necessary to take into account into the foundation of this formulation.
Qureshi, A.J., LEMAIRE, Maurice, Etienne, A., DANTAN, Jean-Yves, Gayton, Nicolas, QURESHI, Ahmed Jawad, GAYTON, N., Lemaire, M., ETIENNE, Alain, Dantan, J.Y.   +9 more
core   +1 more source

Determinants of undergraduate bioscience engagement: Validating attendance barriers and classroom spatial behaviour across institutions

FEBS Open Bio, EarlyView.
Student engagement extends beyond simple attendance. Across 891 bioscience students from three universities, attendance behaviour was associated mainly with structural influences, whereas classroom spatial behaviour reflected affective and sensory factors.
Nigel Page, Rachel J. Hunt, Lauren J. Albee, Daniel Berwick, Alison Snape   +4 more
wiley   +1 more source

A new 2D-3D registration gold-standard dataset for the hip joint based on uncertainty modeling. [PDF]

Med Phys, 2021
D'Isidoro F, Chênes C, Ferguson SJ, Schmid J.   +3 more
europepmc   +1 more source

Self‐Regulated Learning Meets AI: Reinterpreting Self‐Regulation, Co‐Regulation, and Socially Shared Regulation in Human–AI Interaction

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Advancing artificial intelligence (AI) has transformed learning and work, yet higher education and professional development programs have not systematically equipped learners for AI‐prevalent environments. This lack of preparation creates uncertainty regarding control, responsibility, trust, and accountability.
Moon‐Heum Cho, Jerusalem Merkebu
wiley   +1 more source

Analysis of the interaction network relationship between drugs using a graph neural network

Frontiers in Pharmacology
IntroductionThe ever-increasing complexity of biochemical systems, alongside the rapid growth of pharmaceutical and biomedical data, underscores the urgent need for intelligent, scalable, and interpretable computational models.
Zhongyi Chai, Jing Wang, Huili Du
doaj   +1 more source

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

Dimensionality Reduction and Uncertainty Quantification for Inverse Problems [PDF]

, 2015
Many inverse problems in science and engineering involve multi-experiment data and thus require a large number of forward simulations. Dimensionality reduction techniques aim at reducing the number of forward solves by (randomly) subsampling the data. In
van Leeuwen, Tristan, Mathematical Modeling, Sub Mathematical Modeling   +2 more
core  

Modeling and simulation of call centers.

, 2006
In this review, we introduce key notions and describe the decision problems commonly encountered in call center management. Main themes are the central role of uncertainty throughout the decision hierarchy and the many operational complexities and ...
L'Ecuyer, P., Avramidis, A.N.
core   +1 more source