IEEE

A Federated Learning-Based Data Augmentation Method for Privacy Preservation Under Heterogeneous Data

Abstract: Federated learning is an important distributed machine learning paradigm. This study proposes a privacy-preserving data augmentation model for federated learning of heterogeneous data, which ...
IEEE

Joint Channel Estimation and Data Detection for OTFS Systems: A Lightweight Deep Learning Framework With a Novel Data Augmentation Method

Abstract: Orthogonal time frequency space (OTFS) modulation is expected to address the performance degradation of orthogonal frequency division multiplexing (OFDM) modulated signals, particularly due ...
Data Center Frontier

Distributed Data Collection: The Foundation for Secure, Scalable DCIM

Many centralized DCIM architectures create dangerous single points of failure. Learn how next-generation DCIM leverages secure, distributed data collection to isolate legacy ...
BMJ Open

Severe Mental Illness Longitudinal Evaluation (SMILE): protocol for establishing a cohort and bioresource for UK-based patients with psychosis

Introduction Psychotic disorders account for significant morbidity and healthcare costs and yet their pathophysiology remains poorly understood. The National Institute for Health and Care Research ...
BMJ Open

‘Gambling is an escape’: a qualitative study of problematic gambling among sexually diverse adults in Canada

Background Problem gambling among sexual and gender diversity (SGD) populations has received increasing attention in research. While the literature shows that these populations are more likely than ...