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Based on Optimization Research on the Evaluation System of English Teaching Quality Based on GA-BPNN Algorithm.

Computational intelligence and neuroscience
English teaching is an important part of basic teaching in our country, which has been deeply concerned by all aspects. Its teaching quality not only is related to the purpose of English teaching, but also has a far-reaching impact on students' Engli...

Research on User Experience of Sports Smart Bracelet Based on Fuzzy Comprehensive Appraisal and SSA-BP Neural Network.

Computational intelligence and neuroscience
Due to the marked increase in the prevalence of overweight and obesity worldwide and an environment leading to a series of chronic diseases, physical exercise is an important way to prevent chronic diseases. Additionally, a good exercise smart bracel...

Improving Speech Emotion Recognition With Adversarial Data Augmentation Network.

IEEE transactions on neural networks and learning systems
When training data are scarce, it is challenging to train a deep neural network without causing the overfitting problem. For overcoming this challenge, this article proposes a new data augmentation network-namely adversarial data augmentation network...

Entropy-Based Variational Scheme with Component Splitting for the Efficient Learning of Gamma Mixtures.

Sensors (Basel, Switzerland)
Finite Gamma mixture models have proved to be flexible and can take prior information into account to improve generalization capability, which make them interesting for several machine learning and data mining applications. In this study, an efficien...

Multi-Stage Feature Extraction and Classification for Ship-Radiated Noise.

Sensors (Basel, Switzerland)
Due to the complexity and unique features of the hydroacoustic channel, ship-radiated noise (SRN) detected using a passive sonar tends mostly to distort. SRN feature extraction has been proposed to improve the detected passive sonar signal. Unfortuna...

MLCV: Bridging Machine-Learning-Based Dimensionality Reduction and Free-Energy Calculation.

Journal of chemical information and modeling
Importance-sampling algorithms leaning on the definition of a model reaction coordinate (RC) are widely employed to probe processes relevant to chemistry and biology alike, spanning time scales not amenable to common, brute-force molecular dynamics (...

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automatic segmentation methods are an important advancement in medical image analysis. Machine learning techniques, and deep neural networks in particular, are the state-of-the-art for most medical image segmentation tasks. Issues with class imbalanc...

Tinnitus-like "hallucinations" elicited by sensory deprivation in an entropy maximization recurrent neural network.

PLoS computational biology
Sensory deprivation has long been known to cause hallucinations or "phantom" sensations, the most common of which is tinnitus induced by hearing loss, affecting 10-20% of the population. An observable hearing loss, causing auditory sensory deprivatio...

Charge-Transfer Landscape Manifesting the Structure-Rate Relationship in the Condensed Phase Machine Learning.

The journal of physical chemistry. B
In this work, we develop a machine learning (ML) strategy to map the molecular structure to condensed phase charge-transfer (CT) properties including CT rate constants, energy levels, electronic couplings, energy gaps, reorganization energies, and re...

Recognition study of denatured biological tissues based on multi-scale rescaled range permutation entropy.

Mathematical biosciences and engineering : MBE
The recognition of denatured biological tissue is an indispensable part in the process of high intensity focused ultrasound treatment. As a nonlinear method, multi-scale permutation entropy (MPE) is widely used in the recognition of denatured biologi...