AIMC Topic: Time Factors

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OPERAS decision support system versus manual job coding: a quantitative analysis on coding time and inter-coder reliability.

Occupational and environmental medicine
OBJECTIVES: The manual coding of job descriptions is time-consuming, expensive and requires expert knowledge. Decision support systems (DSS) provide a valuable alternative by offering automated suggestions that support decision-making, improving effi...

A hybrid predictor-corrector network and spatiotemporal classifier method for noisy plant PET image classification.

Physics in medicine and biology
. Plant Positron Emission Tomography (PET) is a new and efficient imaging technique which aims at providing a quantitative analysis of plant stress, enabling personalized crop management and maximizing productivity. However, a highly performant class...

Novel fusion-based time-frequency analysis for early prediction of sudden cardiac death from electrocardiogram signals.

Medical engineering & physics
Sudden cardiac death (SCD) is one of the leading causes of global mortality, often occurring without warning and driven by complex cardiac dynamics. Despite significant advances in cardiovascular diagnostics, accurately predicting SCD at an early sta...

A lightweight All-MLP time-frequency anomaly detection for IIoT time series.

Neural networks : the official journal of the International Neural Network Society
Anomaly detection in the Industrial Internet of Things (IIoT) aims at identifying abnormal sensor signals to ensure industrial production safety. However, most existing models only focus on high accuracy by building a bulky neural network with deep s...

Noise-resistant predefined-time convergent ZNN models for dynamic least squares and multi-agent systems.

Neural networks : the official journal of the International Neural Network Society
Zeroing neural networks (ZNNs) are commonly used for dynamic matrix equations, but their performance under numerically unstable conditions has not been thoroughly explored, especially in situations involving unequal row-column matrices. The challenge...

Decomposition-based multi-scale transformer framework for time series anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Time series anomaly detection is crucial for maintaining stable systems. Existing methods face two main challenges. First, it is difficult to directly model the dependencies of diverse and complex patterns within the sequences. Second, many methods t...

Event-based distributed cooperative neural learning control for nonlinear multiagent systems with time-varying output constraints.

Neural networks : the official journal of the International Neural Network Society
In practical engineering, many systems are required to operate under different constraint conditions due to considerations of system security. Violating these constraints conditions during operation may lead to performance degradation. Additionally, ...

Real-time integrated modeling of soft tissue deformation and stress based on deep learning.

Physics in medicine and biology
. Accurately and in real-time simulating soft tissue deformation and visualizing stress distribution are crucial for advancing surgical simulators closer to real surgical environments. The concept of using neural networks to accelerate the finite ele...

Multioutput Convolutional Neural Network for Improved Parameter Extraction in Time-Resolved Electrostatic Force Microscopy Data.

Journal of chemical information and modeling
Time-resolved scanning probe microscopy methods, like time-resolved electrostatic force microscopy (trEFM), enable imaging of dynamic processes ranging from ion motion in batteries to electronic dynamics in microstructured thin film semiconductors fo...

A CT-free deep-learning-based attenuation and scatter correction for copper-64 PET in different time-point scans.

Radiological physics and technology
This study aimed to develop and evaluate a deep-learning model for attenuation and scatter correction in whole-body 64Cu-based PET imaging. A swinUNETR model was implemented using the MONAI framework. Whole-body PET-nonAC and PET-CTAC image pairs wer...