edge computing

Proactive service migration in vehicular edge computing via map-aware mobility prediction and dynamic action-space deep reinforcement learning

Beyond accuracy in crop classification: calibration, selective prediction, and robustness

Introduction: Near-perfect crop-label accuracy can conceal uncertainty, perturbation sensitivity, and weak explanations. This study evaluates these reliability dimensions without treating benchmark classification as an agronomic recommendation. Materials and methods: Ten classifiers were evaluated using five matched st...

Scalable Real-Time Data Pipelines for AI and Machine Learning–Driven Enterprise Systems

The growth of enterprise data volumes across the 2000s and 2010s pushed traditional batch-oriented data processing infrastructures past their practical limits, motivating a sustained shift toward distributed, stream-based architectures capable of supporting real-time analytics and machine learning (ML). This article sy...

UAV-LiDAR, field inventory and coastline data for two Avicennia germinans chronosequences, Coronie, Suriname (2024)

Field, wood, soil, UAV laser scanning (ULS) and coastline data, with the analysis code, from two coast-perpendicular Avicennia germinans chronosequences on the mudbank coast of Coronie, Suriname. The data underlie: Feyen J. et al. Structural development of Avicennia mangrove forests along a successional chronosequence...

Safety-Structured Generation for a Ukrainian Clinical Assistant in Edge-Computing: Responsible QA Dataset, Gemma 3 270M Fine-Tuning, and NanoPi NEO Air On-Device Inference

Edge Computing vs. Cloud Computing: Which is the Future?

As businesses strive to improve efficiency, reduce latency, and leverage the power of data, understanding the strengths and limitations of these two computing paradigms is crucial. Full article: https://davidohnstad.net/edge-computing-vs-cloud-computing-which-is-the-future/

A reduced bump-on-tail plant for the steady operating region of a fast-ion-driven mode: amplitude equation, full-f Vlasov solver with Fokker-Planck collisions, regime map and a detection benchmark

Version 2 of this paper adds a related-work section placing the work against the analytic quasi-steady theory of Lestz and Duarte (2021), the regime maps of Zhang et al. (2026) and the steady-or-chirping criterion of Duarte et al. (2017, 2018); places the near-marginal comparison against Lestz and Duarte's two validity...

Inter-method agreement between digital occlusograms and mounted-cast articulator analysis in temporomandibular disorders with degenerative joint changes

Intraoral scanner occlusograms are increasingly used for non-invasive digital occlusal analysis, yet their agreement with an articulator-mounted reference in temporomandibular disorder (TMD) patients with degenerative joint changes is unknown. This is a methodological question about the fidelity of digital occlusal rec...

LARA: A Practical Evaluation of CPU-Efficient Object Detection Using YOLOv8, OpenVINO, and INT8 Quantization

The deployment of computer vision systems on resource-constrained computing platforms presents a practical challenge: modern deep learning models can provide strong detection capabilities, but their computational requirements may limit their responsiveness when dedicated graphics processing units (GPUs) are unavailable...

Physical Analogue Kolmogorov-Arnold Networks based on Reconfigurable Nonlinear-Processing Units

Kolmogorov-Arnold Networks (KANs) shift neural computation from linear layers to learnable nonlinear edge functions, but implementing these nonlinearities efficiently in hardware remains an open challenge. Here we introduce a physical analogue KAN architecture in which edge functions are realized in materia using recon...

Artifact and Datasets for Resource-Efficient Semantic Communication on Edge Networks (SEMCOM/EDGE)

Source code, simulation engine, AI encoder/decoder prompts, and anonymized interaction CSV logs for SEMCOM/EDGE, a prototype demonstrating resource-efficient semantic communication over edge networks. Semantic payloads are AI-encoded abstractions of text, voice, and image content; only the encoded payload is transmitte...

Non-Kinetic Propagation Dynamics: Macroscopic Electromagnetism as a Quantum Excitation Cascade and the Collapse of the Drude Model

This paper challenges the classical Drude kinetic model of electron propagation by proposing the Non-Kinetic Propagation framework. In this approach, macroscopic electromagnetism within industrial crystalline lattices, such as electric motor stators, is redefined as a quantum excitation cascade rather than a classical...