Results 131 to 140 of about 60,493 (305)
Harnessing microbial power to degrade hydrocarbon‐based plastics
mLife, EarlyView.Abstract The growing global plastic waste crisis demands the development of urgent, effective, and sustainable solutions. While conventional recycling methods present intrinsic limitations, microbial biodegradation of plastic waste has emerged as a promising alternative.
Hui Li +4 more
wiley +1 more source
Mathematical Methods in the Applied Sciences, EarlyView.We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés +2 more
wiley +1 more source
Accommodating availability bias on line transect surveys using hidden Markov models.
, 2009 Previously in the University eprints HAIRST pilot service at http://eprints.st-andrews.ac.uk/archive/00000458/Maximum likelihood methods are developed which accommodate intermittent animal availability of animals on line transect surveys.
Samara, Filipa I. P., Borchers, David L.
core
Multi‐Agent Reinforcement Learning for Joint Police Patrol and Dispatch
Naval Research Logistics (NRL), EarlyView.ABSTRACT Police patrol units need to split their time between performing preventive patrol and being dispatched to serve emergency incidents. In the existing literature, patrol and dispatch decisions are often studied separately. We consider joint optimization of these two decisions to improve police operations efficiency and reduce response time to ...
Matthew Repasky, He Wang, Yao Xie
wiley +1 more source
Information Design for Early‐Stage Dose‐Finding Trials
Naval Research Logistics (NRL), EarlyView.ABSTRACT To enhance enrollment rates in early‐stage dose‐finding clinical trials, we propose an information design approach, where the clinical investigator (CI) commits to an information releasing mechanism (IRM) based on the treatment's uncertain efficacy and toxicity to encourage patients to participate in the trial.
Amin Khademi, Ningyuan Chen
wiley +1 more source
Hidden Abstract Stack Markov Models with Learning Process
MathematicsWe present hidden abstract stack Markov models (HASMMs) with their learning process. The HASMMs we offer carry the more expressive nature of probabilistic context-free grammars (PCFGs) while allowing faster parameter fitting of hidden Markov models (HMMs)
Mete Özbaltan
doaj +1 more source
Quasi-exact Approximation of Hidden Markov Chain Filters [PDF]
This paper studies the application of exact simulation methods for multi-dimensional multiplicative noise stochastic differential equations to filtering.
Eckhard Platen, Renata Rendek
core
Impact of Packaging and Recycling Systems on Material Recirculation: A Stage‐Decomposition Model
Packaging Technology and Science, EarlyView.A system‐level view emerges from decomposing recycling into four stages (participation, collection, sorting and process yield), diagnosing constraints and targeting interventions. Cumulative equivalent uses (CEUs) quantify long‐term retention, revealing marginal improvements at high baselines generate disproportionately larger gains than low‐baseline ...
Diogo Figueirinhas +3 more
wiley +1 more source
South African Sign Language Recognition Using Feature Vectors and Hidden Markov Models
, 2010 >Magister Scientiae - MScThis thesis presents a system for performing whole gesture recognition for South African Sign Language. The system uses feature vectors combined with Hidden Markov models.
Naidoo, Nathan Lyle
core
Bivariate postprocessing of wind vectors
Quarterly Journal of the Royal Meteorological Society, EarlyView.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