Results 101 to 110 of about 18,734 (258)

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

Multi-state analysis of hypertension and mortality: application of semi-Markov model in a longitudinal cohort study. [PDF]

BMC Cardiovasc Disord, 2020
Ramezankhani A, Blaha MJ, Mirbolouk MH, Azizi F, Hadaegh F, Hadaegh F.   +5 more
europepmc   +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

Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi‐scenario applications, and translational prospects

Smart Molecules, EarlyView.
AI is transforming TPD by improving the design, prediction, and optimization of degraders such as PROTACs, molecular glues, and LYTACs. This review summarizes key AI‐driven advances, highlights applications across drug discovery stages, and discusses remaining challenges and future directions for accelerating the development of therapies against ...
Shuanglin Qin, Rui Peng, Guangshuai Zhang, Si Yan, Jin Xiao, Zishu Liu, Ziyu Tan, Qingqing Xie, Shangjie Li, Wei Luo, Xiaohe Xiao   +10 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

The planktonic food web in the Gulf of Naples based on the analysis of carbon and nitrogen stable isotope ratios

Marine Ecology, EarlyView., 2023
Abstract Plankton play a key role in marine food webs by producing and transferring organic matter and energy to higher trophic levels. To define the trophic structure and interactions within the planktonic communities in the Gulf of Naples, we determined carbon and nitrogen stable isotope ratios in particulate organic matter (POM, <20 μm ...
Louise Merquiol, Maria Grazia Mazzocchi, Isabella D'Ambra   +2 more
wiley   +1 more source

Comparative Analysis of the Unavailability Factors for Two Types of Optical Cable Section Repair under Conditions of Gradual and Sudden Failures

Proceedings of the International Conference on Applied Innovations in IT
The article presents a comparison of unavailability factors for two optical cable section types of repair under conditions of degradation and sudden failures.
Viatcheslav Shuvalov, Irina Kvitkova
doaj   +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

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