Infection control / Modes of transmission

Artificial intelligence (AI) use for personal protective equipment training, remediation, and education in health care.

BACKGROUND: Personal protective equipment (PPE) is a first-line transmission-based precaution for reducing the spread of nosocomial infections between health care workers (HCWs), patients, and staff. The COVID-19 pandemic highlighted a problematic skill gap in effective PPE donning/doffing.

A hybrid PKI and spiking neural network approach for enhancing security and energy efficiency in IoMT-based healthcare 5.0.

In the rapidly evolving field of healthcare 5.0, the Internet of Medical Things (IoMT) is expected to be an enabler that allows smart medical devices to collaborate and communicate with healthcare networks to speed up procedures, enhance care, and improve disease management. However, one of the critical issues for these networks still remains the secure and energy-efficient transmission of sensiti...

Advancing low-cost air quality monitor calibration with machine learning methods.

Low-cost monitors for measuring airborne contaminants have gained popularity due to their affordability, portability, and ease of use. However, they o...

An informed deep learning model of the Omicron wave and the impact of vaccination.

The Omicron (B.1.1.529) variant of SARS-CoV-2 emerged in November 2021 and has since evolved into multiple lineages. Understanding its transmission, v...

Meteorological and traffic effects on air pollutants using Bayesian networks and deep learning.

Traffic emissions have become the major air pollution source in urban areas. Therefore, understanding the highly non-stational and complex impact of t...

MagicGripper: A Multimodal Sensor-Integrated Gripper for Contact-Rich Robotic Manipulation

Contact-rich manipulation in unstructured environments demands precise, multimodal perception to enable robust and adaptive control. Vision-based ta...

InteractAnything: Zero-shot Human Object Interaction Synthesis via LLM Feedback and Object Affordance Parsing

Recent advances in 3D human-aware generation have made significant progress. However, existing methods still struggle with generating novel Human Ob...

Deep learning-driven automated mitochondrial segmentation for analysis of complex transmission electron microscopy images.

Mitochondria are central to cellular energy production and regulation, with their morphology tightly linked to functional performance. Precise analysi...

DeepTopoNet: A Framework for Subglacial Topography Estimation on the Greenland Ice Sheets

Understanding Greenland's subglacial topography is critical for projecting the future mass loss of the ice sheet and its contribution to global sea-...

Distributionally Robust Wireless Semantic Communication with Large AI Models

6G wireless systems are expected to support massive volumes of data with ultra-low latency. However, conventional bit-level transmission strategies ...

Adapting Segment Anything Model for Power Transmission Corridor Hazard Segmentation

Power transmission corridor hazard segmentation (PTCHS) aims to separate transmission equipment and surrounding hazards from complex background, con...

Deep Learning-Assisted 3D Pressure Sensors for Control of Unmanned Aerial Vehicles.

Accurately and reliably detecting and recognizing human body movements in real time, relaying appropriate commands to the machine, have substantial im...

Scalable and robust machine learning framework for HIV classification using clinical and laboratory data.

Human Immunodeficiency Virus (HIV) is a retrovirus that weakens the immune system, increasing vulnerability to infections and cancers. HIV spreads pri...

Towards Operational Automated Greenhouse Gas Plume Detection

Operational deployment of a fully automated greenhouse gas (GHG) plume detection system remains an elusive goal for imaging spectroscopy missions, d...

Stereo Radargrammetry Using Deep Learning from Airborne SAR Images

In this paper, we propose a stereo radargrammetry method using deep learning from airborne Synthetic Aperture Radar (SAR) images. Deep learning-base...

Stereo Radargrammetry Using Deep Learning from Airborne SAR Images

In this paper, we propose a stereo radargrammetry method using deep learning from airborne Synthetic Aperture Radar (SAR) images.Deep learning-based...

From human hand joints to continuum robot: how articular surface morphology shapes flexibility and stability in template-based designs.

The design of continuum robots often involves a dilemma between flexibility and stiffness, where increased flexibility may reduce stiffness and contro...

Multivariate forecasting of dengue infection in Bangladesh: evaluating the influence of data downscaling on machine learning predictive accuracy.

The increasing incidence of dengue virus (DENV) infections poses significant public health challenges in Bangladesh, demanding advanced forecasting me...

ControlTac: Force- and Position-Controlled Tactile Data Augmentation with a Single Reference Image

Vision-based tactile sensing has been widely used in perception, reconstruction, and robotic manipulation. However, collecting large-scale tactile d...

Task-Oriented Low-Label Semantic Communication With Self-Supervised Learning

Task-oriented semantic communication enhances transmission efficiency by conveying semantic information rather than exact messages. Deep learning (D...