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Deep Learning in Diverse Intelligent Sensor Based Systems.

Sensors (Basel, Switzerland)
Deep learning has become a predominant method for solving data analysis problems in virtually all fields of science and engineering. The increasing complexity and the large volume of data collected by diverse sensor systems have spurred the developme...

Application of grey feed forward back propagation-neural network model based on wavelet denoising to predict the residual settlement of goafs.

PloS one
To study the residual settlement of goaf's law and prediction model, we investigated the Mentougou mining area in Beijing as an example. Using MATLAB software, the wavelet threshold denoising method was used to optimize measured data, and the grey mo...

The Prediction of Steel Bar Corrosion Based on BP Neural Networks or Multivariable Gray Models.

Computational intelligence and neuroscience
The corrosion of steel bars in concrete has a significant impact on the durability of constructed structures. Based on the gray relational analysis (GRA) of the accelerated corrosion data and practical engineering data using MATLAB, a back propagatio...

Making use of noise in biological systems.

Progress in biophysics and molecular biology
Disorder and noise are inherent in biological systems. They are required to provide systems with the advantages required for proper functioning. Noise is a part of the flexibility and plasticity of biological systems. It provides systems with increas...

An Extended AI-Experience: Industry 5.0 in Creative Product Innovation.

Sensors (Basel, Switzerland)
Creativity plays a significant role in competitive product ideation. With the increasing emergence of Virtual Reality (VR) and Artificial Intelligence (AI) technologies, the link between such technologies and product ideation is explored in this rese...

A direct discretization recurrent neurodynamics method for time-variant nonlinear optimization with redundant robot manipulators.

Neural networks : the official journal of the International Neural Network Society
Discrete time-variant nonlinear optimization (DTVNO) problems are commonly encountered in various scientific researches and engineering application fields. Nowadays, many discrete-time recurrent neurodynamics (DTRN) methods have been proposed for sol...

Biological Robots: Perspectives on an Emerging Interdisciplinary Field.

Soft robotics
Advances in science and engineering often reveal the limitations of classical approaches initially used to understand, predict, and control phenomena. With progress, conceptual categories must often be re-evaluated to better track recently discovered...

Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time-Frequency-Based Features and Deep Learning Models.

Sensors (Basel, Switzerland)
The milling machine serves an important role in manufacturing because of its versatility in machining. The cutting tool is a critical component of machining because it is responsible for machining accuracy and surface finishing, impacting industrial ...

Detection of Missing Bolts for Engineering Structures in Natural Environment Using Machine Vision and Deep Learning.

Sensors (Basel, Switzerland)
The development of an accurate and efficient method for detecting missing bolts in engineering structures is crucial. To this end, a missing bolt detection method that leveraged machine vision and deep learning was developed. First, a comprehensive d...

Increasing Trust in AI Using Explainable Artificial Intelligence for Histopathology - An Overview.

Studies in health technology and informatics
Digital Pathology is an area that could benefit a lot from the automatic classification of scanned microscopic slides. One of the main problems with this is that the experts need to understand and trust the decisions of the system. This paper is an o...