Results 201 to 210 of about 1,702,710 (310)

Does a decision support tool designed to depict West Nile virus risk explain variation in ruffed grouse Bonasa umbellus use of managed forests?

Wildlife Biology, EarlyView.
Infectious diseases are commonly cited as significant contributors to wildlife population declines. It is, therefore, important to investigate the extent to which tools designed to mitigate the effects of infectious diseases explain wildlife responses to habitat management.
Jacob Goldman, Darin J. McNeil, Lauren M. Chronister, Randall Koleck, Samuel Lapp, Jeffery T. Larkin, Reina Tyl, Justin Kitzes, Jeffery L. Larkin   +8 more
wiley   +1 more source

AI-driven routing pipeline in software-defined networks using DQL: a mini review. [PDF]

Front Artif Intell
Goteti D, Reddy VK.
europepmc   +1 more source

A Cluster-Tree Routing Algorithm with Reduced Routing Overhead in ZigBee Networks

Energy Procedia, 2011
Yan Liu, Hao Zhu, Zonghai Gu, Shenshen Zhu, Wei Li   +4 more
openaire   +1 more source

Dusky grouse seasonal resource selection in the Great Basin isolated mountain ranges of Nevada, USA

Wildlife Biology, EarlyView.
Dusky grouse Dendragapus obscurus are a montane forest grouse species with a paucity of information regarding their temporal and spatial resource use during critical times of high mortality and reproductive output. This lack of vital data may leave dusky grouse at risk of sub‐optimal management in many areas of their distribution, especially in the ...
Stephanie Landry, Brian Smith, Erica Stuber, Shawn Espinosa, David Dahlgren   +4 more
wiley   +1 more source

The performance of drones and artificial intelligence for monitoring sage‐grouse at leks

Wildlife Biology, EarlyView.
Accurately monitoring sage‐grouse populations is critical for conservation, yet traditional ground‐based visual surveys face challenges in scalability and consistency, prompting the exploration of innovative drone‐based methodologies enhanced by artificial intelligence.
Lance B. McNew, Jason Hanlon, Ilya Buzytsky   +2 more
wiley   +1 more source

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha, Mohammad Kamrul Hasan, Shayla Islam, Shailesh Khapre, Salwani Abdullah, Taher M. Ghazal, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nguyen Vo, Md Akhtaruzzaman   +9 more
wiley   +1 more source

ECG‐TransCovNet: A hybrid transformer model for accurate arrhythmia detection using Electrocardiogram signals

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Abnormalities in the heart's rhythm, known as arrhythmias, pose a significant threat to global health, often leading to severe cardiac conditions and sudden cardiac deaths. Therefore, early and accurate detection of arrhythmias is crucial for timely intervention and potentially life‐saving treatment.
Hasnain Ali Shah, Faisal Saeed, Muhammad Diyan, Nouf Abdullah Almujally, Jae‐Mo Kang   +4 more
wiley   +1 more source

TNCOA: Efficient Exploration via Observation‐Action Constraint on Trajectory‐Based Intrinsic Reward

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Efficient exploration is critical in handling sparse rewards and partial observability in deep reinforcement learning. However, most existing intrinsic reward methods based on novelty rely on single‐step observations or Euclidean distances.
Jingxiang Ma, Hongbin Ma, Youzhi Zhang
wiley   +1 more source

Transformation‐Equivariant Network Fused With Multi‐Stage Cascade Attention for Point Cloud Object Detection

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Object detection of unmanned firefighting vehicles faces challenges such as strong electromagnetic interference, drastic lighting changes and dynamic object variations. To address these issues, we propose a two‐stage 3D point cloud object detection algorithm called TED‐CasA‐Fusion.
Jiangdong Wu, Qun Chao, Yintai Wang, Hongyuan Sun, Tengfei Zhang, Chengliang Liu   +5 more
wiley   +1 more source