Results 71 to 80 of about 71,442 (256)

Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel, Xavier Boulanger, Vegard Arneson   +2 more
wiley   +1 more source

Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning

SmartBot, EarlyView.
Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo, Rodrigo S. Jamisola Jr., Molaletsa Namoshe   +2 more
wiley   +1 more source

DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley   +1 more source

Estimating crippling loss from hunting with multistate models: a case study on northern bobwhites

Wildlife Biology, EarlyView.
Hunting as a recreational pursuit provides an important ecosystem service worldwide. Harvest management plays a vital role in regulating wildlife take to ensure long‐term population sustainability and meet value‐based objectives (e.g. hunter satisfaction). However, managers rarely have complete control or observability of harvest mortality.
Amanda S. Cramer, Justin A. Rectenwald, William B. Lewis, Michael A. Hazelbaker, Alexander L. Jackson, Holly K. Lott, Geoff Beane, D. Clay Sisson, Melanie R. Kunkel, Nicole M. Nemeth, James A. Martin   +10 more
wiley   +1 more source

Nested Selves: Self‐Organization and Shared Markov Blankets in Prenatal Development in Humans

Topics in Cognitive Science, EarlyView., 2023
Abstract The immune system is a central component of organismic function in humans. This paper addresses self‐organization of biological systems in relation to—and nested within—other biological systems in pregnancy. Pregnancy constitutes a fundamental state for human embodiment and a key step in the evolution and conservation of our species. While not
Anna Ciaunica, Michael Levin, Fernando E. Rosas, Karl Friston   +3 more
wiley   +1 more source

Life‐history stages and behavior influence demographic classification of moose captured on remote cameras

Wildlife Biology, EarlyView.
Obtaining accurate information on demographic states, such as the age and sex classes of animals, is an important step for monitoring wildlife populations. Traditionally, demographic data are collected from harvest, aerial surveys and telemetry studies.
Alexej P. K. Sirén, Zalmai Moheb, Emily Carlson, Adam Beiner, Michael Pfeister, Ian Doherty, Bruno López Del Hierro, Claudio López Del Hierro, Isabella Hanley, Helena Firlings, Ela Shevket, Arielle Lifton‐Jochnowitz, Lee Kantar, Scott R. McLellan, Carter Barthelman, Tammy L. Wilson   +15 more
wiley   +1 more source

Exploration and Exploitation: A Study on Sample Efficiency in Reinforcement Learning With Multifaceted Curiosity Rewards and Adaptive Experience Replay Utilisation in Sparse Reward Environments

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT In recent years, the widespread application of deep reinforcement learning (DRL) in autonomous systems has highlighted the importance of achieving high sample efficiency under sparse reward conditions. To improve sample efficiency in sparse reward environments, this paper proposes a reinforcement learning framework built upon the Soft Actor ...
Jingyi Huang, Guipeng Xi, Meixiu Lin, Haohui Zhang, Bo Li, Evgeny Neretin   +5 more
wiley   +1 more source

Alternative seed trait strategies are linked to a trade‐off between spatial and temporal dispersal

Functional Ecology, EarlyView.
Read the free Plain Language Summary for this article on the Journal blog. Abstract Seed dispersal allows plants to seek favourable conditions or spread the risk of unfavourable conditions through space and time. While theory predicts a trade‐off between spatial and temporal dispersal, empirical tests have been stymied by the difficulty of measuring ...
Marina L. LaForgia, Susan P. Harrison, Michal J. Borton, Pierre‐Olivier Cheptou, Lauren M. Hallett, Jennifer R. Gremer   +5 more
wiley   +1 more source

The effect of nearby listings on house sale prices in Sydney: A spatio‐temporal regularization approach

Real Estate Economics, EarlyView.
Abstract We estimate the price impact of very nearby concurrently listed properties in the Sydney housing market and assess their competition effects. We apply a hedonic model with spatiotemporal effects regularized via a graph Laplacian prior at the month‐by‐SA2 regional level to seven SA4 subregions of metropolitan Sydney. The model structure enables
Willem P. Sijp, Mengheng Li
wiley   +1 more source

Behavioural state identification from ultra‐high‐frequency movement data

Methods in Ecology and Evolution, EarlyView.
Abstract The hidden Markov model (HMM) is a central framework for identifying behavioural state changes from animal movement data. In this context, movement is typically represented as a sequence of observed metrics, such as step length and turning angle distributions, generated by an unobserved behavioural state process.
Abdulmajeed F. Alharbi, Paul G. Blackwell, James Redcliffe, Luca Börger, Jonathan R. Potts   +4 more
wiley   +1 more source