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A novel hybrid optimization enabled robust CNN algorithm for an IoT network intrusion detection approach.

PloS one
Due to the huge number of connected Internet of Things (IoT) devices within a network, denial of service and flooding attacks on networks are on the rise. IoT devices are disrupted and denied service because of these attacks. In this study, we propos...

Rutting prediction and analysis of influence factors based on multivariate transfer entropy and graph neural networks.

Neural networks : the official journal of the International Neural Network Society
The Rutting prediction model is an essential element of efficient pavement management systems. Accuracy of commonly used predictive model necessitates knowledge of the input parameters that was incorporated and local calibration of the model coeffici...

Identifying autism spectrum disorder in resting-state fNIRS signals based on multiscale entropy and a two-branch deep learning network.

Journal of neuroscience methods
BACKGROUND: The demand for early and precise identification of autism spectrum disorder (ASD) presented a challenge to the prediction of ASD with a non-invasive neuroimaging method.

Segmentation with mixed supervision: Confidence maximization helps knowledge distillation.

Medical image analysis
Despite achieving promising results in a breadth of medical image segmentation tasks, deep neural networks (DNNs) require large training datasets with pixel-wise annotations. Obtaining these curated datasets is a cumbersome process which limits the a...

Neurodynamics-driven holistic approaches to semi-supervised feature selection.

Neural networks : the official journal of the International Neural Network Society
Feature selection is a crucial part of machine learning and pattern recognition, which aims at selecting a subset of informative features from the original dataset. Because of label information, supervised feature selection performs better than unsup...

Combination of explainable machine learning and conceptual density functional theory: applications for the study of key solvation mechanisms.

Physical chemistry chemical physics : PCCP
We present explainable machine learning approaches for the accurate prediction and understanding of solvation free energies, enthalpies, and entropies for different salts in various protic and aprotic solvents. As key input features, we use fundament...

KDE-GAN: A multimodal medical image-fusion model based on knowledge distillation and explainable AI modules.

Computers in biology and medicine
BACKGROUND: As medical images contain sensitive patient information, finding a publicly accessible dataset with patient permission is challenging. Furthermore, few large-scale datasets suitable for training image-fusion models are available. To addre...

Multimodal medical image fusion algorithm based on pulse coupled neural networks and nonsubsampled contourlet transform.

Medical & biological engineering & computing
Combining two medical images from different modalities is more helpful for using the resulting image in the healthcare field. Medical image fusion means combining two or more images coming from multiple sensors. This technology obtains an output imag...

Graph Spring Network and Informative Anchor Selection for session-based recommendation.

Neural networks : the official journal of the International Neural Network Society
Session-based recommendation (SBR) aims at predicting the next item for an ongoing anonymous session. The major challenge of SBR is how to capture richer relations in between items and learn ID-based item embeddings to capture such relations. Recent ...

Computer-aided diagnosis of autism spectrum disorder from EEG signals using deep learning with FAWT and multiscale permutation entropy features.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Autism spectrum disorder (ASD), a neurodevelopment disorder, is characterized by significant difficulties in social interaction and emerges as a major threat to children. Its computer-aided diagnosis used by neurologists improves the detection proces...