AIMC Topic: Time

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Temporal information extraction with the scalable cross-sentence context for electronic health records.

Journal of biomedical informatics Mar 15, 2022
Temporal information is essential for accurate understanding of medical information hidden in electronic health record texts. In the absence of temporal information, it is even impossible to distinguish whether the mentioned symptom is a current cond...
Algorithms Electronic Health Records Natural Language Processing Information Storage and Retrieval Time
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Human Being Detection from UWB NLOS Signals: Accuracy and Generality of Advanced Machine Learning Models.

Sensors (Basel, Switzerland) Feb 20, 2022
This paper studies the problem of detecting human beings in non-line-of-sight (NLOS) conditions using an ultra-wideband radar. We perform an extensive measurement campaign in realistic environments, considering different body orientations, the obstac...
Humans Machine Learning Time Radar
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Attention-Based Deep Recurrent Neural Network to Forecast the Temperature Behavior of an Electric Arc Furnace Side-Wall.

Sensors (Basel, Switzerland) Feb 12, 2022
Structural health monitoring (SHM) in an electric arc furnace is performed in several ways. It depends on the kind of element or variable to monitor. For instance, the lining of these furnaces is made of refractory materials that can be worn out over...
Neural Networks, Computer Forecasting Temperature Electricity Time
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A novel combined model for prediction of daily precipitation data using instantaneous frequency feature and bidirectional long short time memory networks.

Environmental science and pollution research international Jan 29, 2022
Meteorological events constantly affect human life, especially the occurrence of excessive precipitation in a short time causes important events such as floods. However, in case of insufficient precipitation for a long time, drought occurs. In recent...
Neural Networks, Computer Forecasting Time Droughts Meteorology
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Trade off analysis between fixed-time stabilization and energy consumption of nonlinear neural networks.

Neural networks : the official journal of the International Neural Network Society Jan 13, 2022
This paper concentrates on trade off analysis between fixed-time stabilization and energy consumption for a type of nonlinear neural networks (NNs). By constructing a compound switching controller and utilizing inequality techniques, a sufficient con...
Neural Networks, Computer Time
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Finite-time stabilization of complex-valued neural networks with proportional delays and inertial terms: A non-separation approach.

Neural networks : the official journal of the International Neural Network Society Jan 13, 2022
This article mainly dedicates on the issue of finite-time stabilization of complex-valued neural networks with proportional delays and inertial terms via directly constructing Lyapunov functions without separating the original complex-valued neural n...
Neural Networks, Computer Feedback Time
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Reconstructing Unsteady Flow Data From Representative Streamlines via Diffusion and Deep-Learning-Based Denoising.

IEEE computer graphics and applications Dec 10, 2021
We propose VFR-UFD, a new deep learning framework that performs vector field reconstruction (VFR) for unsteady flow data (UFD). Given integral flow lines (i.e., streamlines), we first generate low-quality UFD via diffusion. VFR-UFD then leverages a c...
Neural Networks, Computer Algorithms Deep Learning Diffusion Time
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A Bidirectional Interpolation Method for Post-Processing in Sampling-Based Robot Path Planning.

Sensors (Basel, Switzerland) Nov 8, 2021
This paper proposes a post-processing method called bidirectional interpolation method for sampling-based path planning algorithms, such as rapidly-exploring random tree (RRT). The proposed algorithm applies interpolation to the path generated by the...
Algorithms Computer Simulation Robotics Time
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Fractional-order discontinuous systems with indefinite LKFs: An application to fractional-order neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society Nov 5, 2021
In this article, we discuss bipartite fixed-time synchronization for fractional-order signed neural networks with discontinuous activation patterns. The Filippov multi-map is used to convert the fixed-time stability of the fractional-order general so...
Neural Networks, Computer Algorithms Computer Simulation Time
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Energy Load Forecasting Using a Dual-Stage Attention-Based Recurrent Neural Network.

Sensors (Basel, Switzerland) Oct 27, 2021
Providing a stable, low-price, and safe supply of energy to end-users is a challenging task. The energy service providers are affected by several events such as weather, volatility, and special events. As such, the prediction of these events and havi...
Neural Networks, Computer Machine Learning Forecasting Weather Time
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