Aviation activities are constantly increasing as a result of the growth of the global economic system. How to increase airspace capacity within the limited airspace resources while ensuring smooth and safe aircraft operations is a challenge for civil...
Neuromorphic computing is considered a promising method for resolving the traditional von Neumann bottleneck. Natural biomaterial-based artificial synapses are popular units for constructing neuromorphic computing systems while suffering from poor li...
Ultrasound, as a common clinical examination tool, inevitably has human errors due to the limitations of manual operation. Artificial intelligence is an advanced computer program that can solve this problem. Therefore, the relevant literature on the ...
Pulse signal is one of the most important physiological features of human body, which is caused by the cyclical contraction and diastole. It has great research value and broad application prospect in the detection of physiological parameters, the dev...
Computational intelligence and neuroscience
Sep 15, 2022
Green smart building is the development direction of future architecture. It is of great significance to carry out risk assessment. Fire risk is the key content of building risk, so this paper takes fire risk as the research object, with the help of ...
Diffusion weighted imaging (DWI) with multiple, high b-values is critical for extracting tissue microstructure measurements; however, high b-value DWI images contain high noise levels that can overwhelm the signal of interest and bias microstructural...
Environmental science and pollution research international
Sep 14, 2022
Increasing water demand is exacerbating water shortages in water-scarce regions (such as India, China, and Iran). Effective water demand forecasting is essential for the sustainable management of water supply systems in watersheds. To alleviate the c...
Neural networks : the official journal of the International Neural Network Society
Sep 14, 2022
In this paper we characterize the set of functions that can be represented by infinite width neural networks with RePU activation function max(0,x), when the network coefficients are regularized by an ℓ (quasi)norm. Compared to the more well-known Re...
In the last decade, convolutional neural networks (ConvNets) have been a major focus of research in medical image analysis. However, the performances of ConvNets may be limited by a lack of explicit consideration of the long-range spatial relationshi...
The computational limitations of complex numerical models have led to adoption of statistical emulators across a variety of problems in science and engineering disciplines to circumvent the high computational costs associated with numerical simulatio...
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