Results 71 to 80 of about 6,719 (190)

An Improved Fault Detection Method based on HSMM: Application to a Chemical Process

International Journal of Prognostics and Health Management
This paper proposes a fault detection method for multivariate statistical process control. The proposed method combines the Forward-Backward Hidden Semi-Markov Model (HSMM) and Principal Component Analysis (PCA). A stochastic automaton was used for multi-
Lestari Handayani, Pascal Vrignat, Frédéric Kratz   +2 more
doaj   +1 more source

Learning Controllers for Reactive and Proactive Behaviors in Human-Robot Collaboration

Frontiers in Robotics and AI, 2016
Designed to safely share the same workspace as humans and assist them in a variety of tasks, the new collaborative robots are targeting manufacturing and service applications that once were considered unattainable.
Sylvain eCalinon, Leonel eRozo, João eSilvério, Darwin Gordon Caldwell   +3 more
doaj   +1 more source

Conversational AI Agents: The Effect of Process and Outcome Variation on Anthropomorphism and Trust

Information Systems Journal, EarlyView.
ABSTRACT Organisations increasingly deploy conversational AI agents (CAs) in agentic roles where behavioural variations are inevitable. Prior work often conflates two distinct forms of variation: outcome variation (where success fluctuates) and process variation (where the path to completion varies).
Kambiz Saffarizadeh, Mark Keil
wiley   +1 more source

Explicit Modeling of Brain State Duration Using Hidden Semi Markov Models in EEG Data

IEEE Access
We consider the detection and characterization of brain state transitions based on ongoing electroencephalography (EEG). Here, a brain state represents a specific brain dynamical regime or mode of operation that produces a characteristic quasi-stable ...
Nelson J. Trujillo-Barreto, David Araya Galvez, Aland Astudillo, Wael El-Deredy   +3 more
doaj   +1 more source

Structured Inference for Recurrent Hidden Semi-markov Model [PDF]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Segmentation and labeling for high dimensional time series is an important yet challenging task in a number of applications, such as behavior understanding and medical diagnosis. Recent advances to model the nonlinear dynamics in such time series data, has suggested to involve recurrent neural networks into  Hidden Markov Models.
Hao Liu, Lirong He, Haoli Bai, Bo Dai, Kun Bai, Zenglin Xu   +5 more
openaire   +1 more source

Breeding 5.0: Artificial intelligence (AI)‐decoded germplasm for accelerated crop innovation

Journal of Integrative Plant Biology, EarlyView.
ABSTRACT Crop breeding technologies are vital for global food security. While traditional methods have improved yield, stress tolerance, and nutrition, rising challenges such as climate instability, land loss, and pest pressure now demand new solutions.
Jiayi Fu, Shouzhi Zheng, Longjiang Fan, Xiaoming Zheng, Qian Qian   +4 more
wiley   +1 more source

A New State Recognition and Prognosis Method Based on a Sparse Representation Feature and the Hidden Semi-Markov Model

IEEE Access, 2020
Equipment degradation state recognition and prognosis are considered two significant parts of a prognostics and health management (PHM) system that help to reduce downtime and decrease economic losses.
Yun-Fei Ma, Xisheng Jia, Qiwei Hu, Huajun Bai, Chiming Guo, Shuangchuan Wang   +5 more
doaj   +1 more source

Financial Time Series Uncertainty: A Review of Probabilistic AI Applications

Journal of Economic Surveys, EarlyView.
ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen, Tord Johan Espe, Kristoffer Grude, Morten Risstad, Rickard Sandberg   +4 more
wiley   +1 more source

A perspective on automated rapid eye movement sleep assessment

Journal of Sleep Research, Volume 34, Issue 2, April 2025.
Summary Rapid eye movement sleep is associated with distinct changes in various biomedical signals that can be easily captured during sleep, lending themselves to automated sleep staging using machine learning systems. Here, we provide a perspective on the critical characteristics of biomedical signals associated with rapid eye movement sleep and how ...
Mathias Baumert, Huy Phan
wiley   +1 more source

Research on Residual Life Prediction for Electrical Connectors Based on Intermittent Failure and Hidden Semi-Markov Model

Applied Sciences, 2018
Based on the dynamic properties of electrical connector intermittent failure, the model and methods for residual life prediction for electrical connectors are studied in this paper.
Qian Li, Kehong Lv, Jing Qiu, Guanjun Liu   +3 more
doaj   +1 more source