Determining the optimal amount of cash stock reserved in each bank branch is a strategic decision. A certain level of cash stock must be kept and ready for cash withdrawal needs at a branch. However, holding too much cash not only forfeits opportunit...
Environmental science and pollution research international
Jun 6, 2022
The improvement of groundwater burial depth prediction accuracy is an important guiding significance for the development and management of groundwater resources. Groundwater burial depth sequence has the characteristics of uncertainty and nonlinearit...
Extraction of intravoxel incoherent motion (IVIM) parameters from noisy diffusion-weighted (DW) images using a biexponential fitting model is computationally challenging, and the reliability of the estimated perfusion-related quantities represents a ...
Neural networks : the official journal of the International Neural Network Society
Jun 6, 2022
Redundant manipulators could be efficient tools in industrial production as a result of their dexterity. However, existing kinematic control methods for redundant manipulators have two main disadvantages. On one hand, model uncertainties or unknown k...
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Jun 6, 2022
This paper describes a fully experimental hybrid system in which a [Formula: see text] memristive crossbar spiking neural network (SNN) was assembled using custom high-resistance state memristors with analogue CMOS neurons fabricated in 180 nm CMOS t...
Recently, research on the development of artificial intelligence (AI)-based computational toxicology models that predict toxicity without the use of animal testing has emerged because of the rapid development of computer technology. Various computati...
Ultrafast spectroscopy often involves measuring weak signals and long data acquisition times. Spectra are typically collected as a "pump-probe" spectrum by measuring differences in intensity across laser shots. Shot-to-shot intensity fluctuations are...
In this study, we focus on automated optimization design methodologies to concurrently trade off between power gain, output power, efficiency, and linearity specifications in radio frequency (RF) high-power amplifiers (HPAs) through deep neural netwo...
Convolutional Neural Networks (CNNs) are popular models that are widely used in image classification, target recognition, and other fields. Model compression is a common step in transplanting neural networks into embedded devices, and it is often use...
BACKGROUND: The non-local module has been primarily used in literature to capturing long-range dependencies. However, it suffers from prohibitive computational complexity and lacks the interactions among positions across the channels.
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