AIMC Topic: Neural Networks, Computer

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Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor.

Sensors (Basel, Switzerland)
Metal oxide semiconductor (MOS) gas sensors have many advantages, but the main obstacle to their widespread use is the cross-sensitivity observed when using this type of detector to analyze gas mixtures. Thermal modulation of the heater integrated wi...

Classification Framework of the Bearing Faults of an Induction Motor Using Wavelet Scattering Transform-Based Features.

Sensors (Basel, Switzerland)
In the machine learning and data science pipelines, feature extraction is considered the most crucial component according to researchers, where generating a discriminative feature matrix is the utmost challenging task to achieve high classification a...

Classification and Prediction on Hypertension with Blood Pressure Determinants in a Deep Learning Algorithm.

International journal of environmental research and public health
Few studies classified and predicted hypertension using blood pressure (BP)-related determinants in a deep learning algorithm. The objective of this study is to develop a deep learning algorithm for the classification and prediction of hypertension w...

DNN-PNN: A parallel deep neural network model to improve anticancer drug sensitivity.

Methods (San Diego, Calif.)
With the rapid development of deep learning techniques and large-scale genomics database, it is of great potential to apply deep learning to the prediction task of anticancer drug sensitivity, which can effectively improve the identification efficien...

A review of recent developments in the application of machine learning in solar thermal collector modelling.

Environmental science and pollution research international
Over the past few decades, the popularity of solar thermal collectors has increased dramatically because of many significant advantages like being a free, natural, environmentally friendly and permanent energy source. Today, developing and optimising...

RGN: Residue-Based Graph Attention and Convolutional Network for Protein-Protein Interaction Site Prediction.

Journal of chemical information and modeling
The prediction of a protein-protein interaction site (PPI site) plays a very important role in the biochemical process, and lots of computational methods have been proposed in the past. However, the majority of the past methods are time consuming and...

Fine-Grained Unsupervised Temporal Action Segmentation and Distributed Representation for Skeleton-Based Human Motion Analysis.

IEEE transactions on cybernetics
Understanding the fine-grained temporal structure of human actions and its semantic interpretation is beneficial to many real-world tasks, such as sports movements, rehabilitation exercises, and daily-life activities analysis. Current action segmenta...

Robust Traffic Prediction From Spatial-Temporal Data Based on Conditional Distribution Learning.

IEEE transactions on cybernetics
Traffic prediction based on massive speed data collected from traffic sensors plays an important role in traffic management. However, it is still challenging to obtain satisfactory performance due to the complex and dynamic spatial-temporal correlati...