edge computing

Recent Advances in Flexible Sensing and Edge Intelligence for Embedded Medical Devices: Challenges in Clinical Translation

Enabled by chronic disease management, aging trends, and digital health, medical monitoring is evolving from intermittent testing to continuous personalized monitoring. In this context, embedded medical devices integrate physiological data acquisition with edge computing technologies. This review examines the developme...

Comparative Analysis of Lightweight Kubernetes Distributions for Edge Computing: CPU Microarchitecture and Energy Efficiency

Lyapunov Optimization with Virtual Queues for adaptive task offloading in multi access edge computing

Multi-access edge computing (MEC) enhances the performance of resource-constrained devices by offloading computation to nearby edge servers, but simultaneously achieving energy efficiency and low latency under dynamic conditions remains challenging. This paper proposes Lyapunov Optimization with Virtual Queues (LOVQ),...

Multiwavelength InSAR time-series analysis and change detection for improved signal detection quality in open-source radar Earth observing systems

Satellite interferometric synthetic aperture radar (InSAR) is a powerful geodetic technique that uses the differences in phase between repeat SAR acquisitions to remotely detect subtle (cm-scale) surface deformation over large (10s to 100s of km) footprints. Over Antarctica, 6-day repeat InSAR from Sentinel-1 provides...

Persistent Homology of a Complete Rhinovirus Capsid at Twelve Million Points

We compute the persistent homology in degrees zero and one of a complete virus capsid, taken directly from its cryo-electron microscopy density map with no subsampling. The input is the deposited map EMD-50844 of the empty capsid of rhinovirus A89, a 1000^3 grid at 0.413 Å per voxel, from which every voxel above a fixe...

Impacts of Edge AI/agentic AI on supply chain management and operations research

Edge AI refers to the deployment and execution of artificial intelligence (AI) algorithms on decentralized, local computing devices (e.g., Internet of Things) rather than relying on centralized cloud‐based computing infrastructures. The literature has addressed the increasing importance of AI in supply chain and oper...

Real-time infrared image edge enhancement and AI-enabled recognition using FPGA-based edge computing architecture

Infrared images frequently exhibit low contrast, weak target boundaries, nonuniform detector responses, and scene-dependent thermal interference, making reliable edge extraction difficult when a fixed detector and thresholding rule are used. This study presents an AI-guided infrared edge-enhancement framework with a re...

Bi-wavelength-Gated Plasticity in Defect-Engineered β - Ga2O3 Optoelectronic Synapses for Bioinspired Visual Systems

Abstract Optoelectronic synapses that integrate light sensing, memory, and preprocessing are highly desirable for neuromorphic vision. However, most reported optoelectronic synapses rely on a single optical stimulus and mainly exhibit passive modulation of the photoresponse, making it difficult to actively distinguish...

Design and Implementation of a Deep Learning-Based “Smart Classroom Manager” System

Verifying whether learners are actually engaged with online course resources is challenging. Ineffective learning behaviors are common. These include dropping out midway and letting videos play without watching. The "Smart Classroom Manager" is a deep learning system with three layers: perception, analysis and applicat...

ServerlessEdgeTaskOffloadingDataset

## Dataset: Serverless Edge Task Offloading Workload A synthetic workload dataset of **5,000 tasks** for evaluating task-offloadingdecisions in serverless edge computing. Each row represents one task generatedby an IoT device, together with the network and device conditions at thatmoment. The dataset was generated with...

Digital Twin Technologies for Plasma Reactor Modeling and Optimization

Technology based on the creation of a digital twin has been developed as an innovative solution to cope with increasing complexities of modern plasma engineering systems. Traditional approaches to modeling plasma reactors are focused on performing static simulations, empirical optimization, and inadequate experiments t...

Robust Multi-Sensor Fusion via Memristive Deep Reservoir Computing With Differential-Pair Fault Tolerance