AIMC Topic: Algorithms

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Unsupervised Learning for Product Use Activity Recognition: An Exploratory Study of a "Chatty Device".

Sensors (Basel, Switzerland)
To create products that are better fit for purpose, manufacturers require new methods for gaining insights into product experience in the wild at scale. "Chatty Factories" is a concept that explores the transformative potential of placing IoT-enabled...

Supervised Learning of Neural Networks for Active Queue Management in the Internet.

Sensors (Basel, Switzerland)
The paper examines the AQM mechanism based on neural networks. The active queue management allows packets to be dropped from the router's queue before the buffer is full. The aim of the work is to use machine learning to create a model that copies th...

Signal Recognition Based on APSO-RBF Neural Network to Assist Athlete's Competitive Ability Evaluation.

Computational intelligence and neuroscience
The advanced analysis and research methods of big data will provide theoretical support for the integration of athletes' talent training. The advanced technological methods of big data will also give full play to the advantages of tapping the potenti...

Magnetic-resonance-based measurement of electromagnetic fields and conductivity in vivo using single current administration-A machine learning approach.

PloS one
Diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) is a newly developed technique that combines MR-based measurements of magnetic flux density with diffusion tensor MRI (DT-MRI) data to reconstruct electrical conductivity ...

xECGNet: Fine-tuning attention map within convolutional neural network to improve detection and explainability of concurrent cardiac arrhythmias.

Computer methods and programs in biomedicine
Background and objectiveDetecting abnormal patterns within an electrocardiogram (ECG) is crucial for diagnosing cardiovascular diseases. We start from two unresolved problems in applying deep-learning-based ECG classification models to clinical pract...

Heart disease prediction using supervised machine learning algorithms: Performance analysis and comparison.

Computers in biology and medicine
Machine learning and data mining-based approaches to prediction and detection of heart disease would be of great clinical utility, but are highly challenging to develop. In most countries there is a lack of cardiovascular expertise and a significant ...

DBP-GAPred: An intelligent method for prediction of DNA-binding proteins types by enhanced evolutionary profile features with ensemble learning.

Journal of bioinformatics and computational biology
DNA-binding proteins (DBPs) perform an influential role in diverse biological activities like DNA replication, slicing, repair, and transcription. Some DBPs are indispensable for understanding many types of human cancers (i.e. lung, breast, and liver...

Pre-Processing Method to Improve Cross-Domain Fault Diagnosis for Bearing.

Sensors (Basel, Switzerland)
Models trained with one system fail to identify other systems accurately because of domain shifts. To perform domain adaptation, numerous studies have been conducted in many fields and have successfully aligned different domains into one domain. The ...

Pupil Size Prediction Techniques Based on Convolution Neural Network.

Sensors (Basel, Switzerland)
The size of one's pupil can indicate one's physical condition and mental state. When we search related papers about AI and the pupil, most studies focused on eye-tracking. This paper proposes an algorithm that can calculate pupil size based on a conv...