Results 191 to 200 of about 22,384 (303)
Abstract The pharmaceutical industry has increasingly adopted model‐informed drug discovery and development (MID3) to enhance productivity in drug discovery and development. Quantitative systems pharmacology (QSP), which integrates drug action mechanisms and disease complexities to predict clinical endpoints and biomarkers is central to MID3.
Hiroaki Iwata, Ryuta Saito
wiley +1 more source
Trigonometric words ranking model for spam message classification
Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi +7 more
wiley +1 more source
Bivariate postprocessing of wind vectors
We introduce three novel bivariate postprocessing approaches and analyze their performance for joint postprocessing of bivariate wind‐vector components in Germany. Bivariate vine‐copula‐based models, a bivariate gradient‐boosted version of ensemble model output statistics (EMOS), and a bivariate distributional regression network (DRN) are compared with
Ferdinand Buchner +3 more
wiley +1 more source
Features requirement elicitation process for designing a chatbot application
This article seeks to assist the chatbot community by outlining the characteristics that a chatbot needs to possess and explaining how to create a chatbot for a bank. In order to determine which capabilities are most crucial to ending users, a study of a small sample of chatbot users was conducted.
Nurul Muizzah Johari +4 more
wiley +1 more source
Multi-fidelity modelling via recursive co-kriging and Gaussian-Markov random fields. [PDF]
Perdikaris P +3 more
europepmc +1 more source
Epistemic and aleatoric uncertainty quantification in weather and climate models
Aleatoric and epistemic uncertainties over time on weather and climate time‐scales, estimated through ensembles that sample aleatoric and epistemic uncertainty using Bayesian neural networks for parameterisations in the Lorenz 1996 model. The spread shows the 16th and 84th percentiles.
Laura A. Mansfield +1 more
wiley +1 more source
Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi +3 more
wiley +1 more source
ABSTRACT This paper presents the first end‐to‐end framework that combines guidance, navigation, and centralized task allocation for multiple UAVs performing autonomous search‐and‐rescue (SAR) in GNSS‐denied indoor environments. A twin delayed deep deterministic policy gradient controller is trained with an artificial potential field (APF) reward that ...
Thomas Hickling +3 more
wiley +1 more source
A BAYESIAN HIERARCHICAL SPATIAL MODEL FOR DENTAL CARIES ASSESSMENT USING NON-GAUSSIAN MARKOV RANDOM FIELDS. [PDF]
Jin IH, Yuan Y, Bandyopadhyay D.
europepmc +1 more source
Network analysis of functional genes among prokaryotes, and eukaryotes in natural and artificial rivers. Abstract Periphyton in aquatic ecosystems plays vital roles in the elemental cycle process and is vulnerable to anthropogenic interference. However, few studies have explored the elemental cycles of carbon (C), nitrogen (N), phosphorus (P), and ...
Yulu Tian +4 more
wiley +1 more source

