AIMC Topic: Machine Learning

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Influence of Different Passing Methods of Physical Fitness in Football Using Deep Learning.

Computational intelligence and neuroscience
Deep learning is a new direction in the field of machine learning, which learns the inherent laws and levels of data sample representation. The information gained during learning plays an important role in interpreting data such as text, images, and ...

Optical sensors and machine learning algorithms in sensor-based material flow characterization for mechanical recycling processes: A systematic literature review.

Waste management (New York, N.Y.)
Digital technologies hold enormous potential for improving the performance of future-generation sorting and processing plants; however, this potential remains largely untapped. Improved sensor-based material flow characterization (SBMC) methods could...

Aglow: A Fluorescence Assay and Machine Learning Model to Identify Inhibitors of Intracellular Infection.

ACS infectious diseases
is a genus of Gram-negative bacteria that has for centuries caused large-scale morbidity and mortality. In recent years, the resurgence of rickettsial diseases as a major cause of pyrexias of unknown origin, bioterrorism concerns, vector movement, a...

A Machine Learning Approach for Predicting Non-Suicidal Self-Injury in Young Adults.

Sensors (Basel, Switzerland)
Artificial intelligence techniques were explored to assess the ability to anticipate self-harming behaviour in the mental health context using a database collected by an app previously designed to record the emotional states and activities of a group...

A Machine Learning Model for Predicting Sit-to-Stand Trajectories of People with and without Stroke: Towards Adaptive Robotic Assistance.

Sensors (Basel, Switzerland)
Sit-to-stand and stand-to-sit transfers are fundamental daily motions that enable all other types of ambulation and gait. However, the ability to perform these motions can be severely impaired by different factors, such as the occurrence of a stroke,...

Drowsiness Detection Using Ocular Indices from EEG Signal.

Sensors (Basel, Switzerland)
Drowsiness is one of the main causes of road accidents and endangers the lives of road users. Recently, there has been considerable interest in utilizing features extracted from electroencephalography (EEG) signals to detect driver drowsiness. Howeve...

What can we learn about the psychiatric diagnostic categories by analysing patients' lived experiences with Machine-Learning?

BMC psychiatry
BACKGROUND: To deliver appropriate mental healthcare interventions and support, it is imperative to be able to distinguish one person from the other. The current classification of mental illness (e.g., DSM) is unable to do that well, indicating the p...

Privacy-preserving for assembly deviation prediction in a machine learning model of hydraulic equipment under value chain collaboration.

Scientific reports
Hydraulic equipment, as a typical mechanical product, has been wildly used in various fields. Accurate acquisition and secure transmission of assembly deviation data are the most critical issues for hydraulic equipment manufacturer in the PLM-oriente...

Analysis and Prediction of Corporate Finance and Exchange Rate Correlation Based on Machine Learning Algorithms.

Computational intelligence and neuroscience
Based on the risk management of exposure to foreign exchange assets and liabilities and the application of financial derivatives, this paper provides an in-depth analysis of the financial and exchange rate risks of foreign-funded enterprises. Therefo...

Quantitative Diagnosis of TCM Syndrome Types Based on Adaptive Resonant Neural Network.

Computational intelligence and neuroscience
Artificial intelligence has become one of the most rapidly developing disciplines in the application field of pattern recognition. In target recognition, sometimes, there are multiple identical or similar copies of the target to be recognized in the ...