Results 41 to 50 of about 8,821,946 (173)
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 +2 more
wiley +1 more source
Robot introspection through learned hidden Markov models [PDF]
, 2006 In this paper we describe a machine learning approach for acquiring a model of a robot behaviour from raw sensor data. We are interested in automating the acquisition of behavioural models to provide a robot with an introspective capability.
Maria Fox +11 more
core +2 more sources
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
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 +5 more
wiley +1 more source
Speech Synthesis Based on Hidden Markov Models [PDF]
, 2013 This paper gives a general overview of hidden Markov model (HMM)-based speech synthesis, which has recently been demonstrated to be very effective in synthesizing speech.
Toda, T. +5 more
core +1 more source
Flexible unimodal density estimation in hidden Markov models
Methods in Ecology and Evolution, EarlyView.Abstract Hidden Markov models (HMMs) are powerful tools for modelling time‐series data with underlying state structure. However, selecting appropriate parametric forms for the state‐dependent distributions is often challenging and can lead to model misspecification.
Jan‐Ole Fischer +5 more
wiley +1 more source
IEEE Access, 2020 In this paper, we design a mathematical model for performance and reliability evaluation of the IEEE 802.11p Enhanced Distributed Channel Access (EDCA) broadcast scheme in Dedicated Short-Range Communication (DSRC) with the presence of hidden terminals ...
Lin Hu, Zhijian Dai
doaj +1 more source
British Journal of Educational Psychology, EarlyView.Abstract Background Emotional and motivational aspects of teacher–student relationships are central to adolescents' psychological need satisfaction and academic development. However, few longitudinal studies examine how these relational experiences evolve during adolescence or co‐occur with emotional‐motivational functioning.
Fabian Schimmelpfennig, Diana Raufelder
wiley +1 more source
Perfect posterior simulation for mixture and hidden Markov models [PDF]
, 2010 In this paper we present an application of the read-once coupling from the past algorithm to problems in Bayesian inference for latent statistical models.
Berthelsen, Kasper Klitgaard +6 more
core +1 more source
Learning Evolutionary Stages with Hidden Semi-Markov Model for Predicting Social Unrest Events
Discrete Dynamics in Nature and Society, 2020 Social unrest events are common happenings in modern society which need to be proactively handled. An effective method is to continuously assess the risk of upcoming social unrest events and predict the likelihood of these events. Our previous work built
Fengcai Qiao, Xin Zhang, Jinsheng Deng
doaj +1 more source