Infection control / Modes of transmission

Intelligent computing framework to analyze the transmission risk of COVID-19: Meyer wavelet artificial neural networks.

The optimum control methods for the epidemiology of the COVID-19 model are acknowledged using a novel advanced intelligent computing infrastructure that joins artificial neural networks with unsupervised learning-based optimizers i.e., Genetic Algorithms (GA) and sequential quadratic programming (SQP). Unsupervised learning strategy is provided which depends on the wavelet basis's sequential decon...

The fuzzy system ensembles entomological, epidemiological, demographic and environmental data to unravel the dengue transmission risk in an endemic city.

BACKGROUND: The effectiveness of dengue control interventions depends on an effective integrated surveillance system that involves analysis of multiple variables associated with the natural history and transmission dynamics of this arbovirus. Entomological indicators associated with other biotic and abiotic parameters can assertively characterize the spatiotemporal trends related to dengue transmi...

Spatiotemporal modelling of airborne birch and grass pollen concentration across Switzerland: A comparison of statistical, machine learning and ensemble methods.

BACKGROUND: Statistical and machine learning models are commonly used to estimate spatial and temporal variability in exposure to environmental stress...

Real-Time Calibration-Free Musculotendon Kinematics for Neuromusculoskeletal Models.

Neuromusculoskeletal (NMS) models enable non-invasive estimation of clinically important internal biomechanics. A critical part of NMS modelling is th...

Nanorobot-Based Direct Implantation of Flexible Neural Electrode for BCI.

Brain-Computer Interface (BCI) has gained remarkable prominence in biomedical community. While BCI holds vast potential across diverse domains, the im...

Predictive modeling of hepatitis B viral dynamics: a caputo derivative-based approach using artificial neural networks.

A fractional model for the kinetics of hepatitis B transmission was developed. The hepatitis B virus significantly affects the world's economic and he...

Image Processing for Smart Agriculture Applications Using Cloud-Fog Computing.

The widespread use of IoT devices has led to the generation of a huge amount of data and driven the need for analytical solutions in many areas of hum...

A Pneumatic Flexible Linear Actuator Inspired by Snake Swallowing.

Soft robots spark a revolution in human-machine interaction. However, developing high-performance soft actuators remains challenging due to trade-offs...

Machine Learning and Imputation to Characterize Human Norovirus Genotype Susceptibility to Sodium Hypochlorite.

Human norovirus (HuNoV) is the leading cause of foodborne illness in the developed world and a major contributor to gastroenteritis globally. Its low ...

On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering.

Protein design and directed evolution have separately contributed enormously to protein engineering. Without being mutually exclusive, the former reli...

Long-term trend prediction of pandemic combining the compartmental and deep learning models.

Predicting the spread trends of a pandemic is crucial, but long-term prediction remains challenging due to complex relationships among disease spread ...

Implementing Autonomous Control in the Digital-Twins-Based Internet of Robotic Things for Remote Patient Monitoring.

Conventional patient monitoring methods require skin-to-skin contact, continuous observation, and long working shifts, causing physical and mental str...

Sampled-data synchronization for fuzzy inertial cellular neural networks and its application in secure communication.

This paper designs the sampled-data control (SDC) scheme to delve into the synchronization problem of fuzzy inertial cellular neural networks (FICNNs)...

A Physics-Informed Neural Network approach for compartmental epidemiological models.

Compartmental models provide simple and efficient tools to analyze the relevant transmission processes during an outbreak, to produce short-term forec...

Unveiling the potential of a novel portable air quality platform for assessment of fine and coarse particulate matter: in-field testing, calibration, and machine learning insights.

Although low-cost air quality sensors facilitate the implementation of denser air quality monitoring networks, enabling a more realistic assessment of...

Prediction on the spatial distribution of the seropositive rate of schistosomiasis in Hunan Province, China: a machine learning model integrated with the Kriging method.

Schistosomiasis remains a formidable challenge to global public health. This study aims to predict the spatial distribution of schistosomiasis seropos...

PCP-GC-LM: single-sequence-based protein contact prediction using dual graph convolutional neural network and convolutional neural network.

BACKGROUND: Recently, the process of evolution information and the deep learning network has promoted the improvement of protein contact prediction me...

Enhancing Sports Injury Risk Assessment in Soccer Through Machine Learning and Training Load Analysis.

Sports injuries pose significant challenges in athlete welfare and team dynamics, particularly in high-intensity sports like soccer. This study used m...

Towards higher load capacity: innovative design of a robotic hand with soft jointed structure.

In this paper, the innovative design of a robotic hand with soft jointed structure is carried out and a tendon-driven mechanism, a master-slave motor ...

Novel glassbox based explainable boosting machine for fault detection in electrical power transmission system.

The reliable operation of electrical power transmission systems is crucial for ensuring consumer's stable and uninterrupted electricity supply. Faults...