edge computing

Synthetic Nonlinearity in Diffractive Optical Networks via Input‐Adaptive Modulation for Intelligent Vision

This work proposes an adaptive modulation strategy driven by the initial input that synthesizes effective nonlinearity within a standard linear optical framework, and reveals that shallow nonlinear architectures can outperform significantly deeper linear counterparts, demonstrating that computational nonlinearity can e...

Development of a Wireless Measuring System for Grinding Vibrations

In-process measurement of changes in grinding wheel condition is expected to prevent machining defects. A method for monitoring grinding wheel condition through grinding vibration analysis was examined in this study. To achieve this, a measurement device was developed by housing two accelerometers, a compact microcontr...

Edge-IoT Driven Smart Air Quality Monitoring Using the Proposed EdgeAQ-Net Distributed Deep Learning Model

An Edge-IoT-based smart air quality monitoring system based on the proposed EdgeAQ-Net distributed deep learning architecture that combines edge computing and IoT-based environmental sensors to allow real-time analysis and prediction of air quality to be performed at the network edge.

Latency-Optimal Geo-Distributed Storage over Structured Networks

It is shown that for every fixed number of files, computing a latency-minimizing assignment is NP-hard via a reduction from the domatic number problem.

APEX-RBD: Mixed-Precision Exploration Framework for Hardware-Efficient Robot Dynamics Accelerator Design

APEX-RBD is introduced, an automated framework that makes mixed-precision exploration computationally tractable while effectively identifying hardware-efficient configurations and employs a data-efficient, prior-informed surrogate model to enable rapid trajectory error prediction.

Edge computing-based mathematical model for latency reduction in urban transportation systems

A mathematical model based on the edge computing paradigm to minimize network latency in cyber-physical transportation systems is proposed and experimentally evaluated, confirming that the edge-based architecture contributes substantially to more stable and efficient traffic management during morning peak hours.

Caption-once, Frames-on-Demand: Visual-Need Routing for Budget-Aware Agentic Long Video Understanding

This work proposes Caption-once, Frames-onDemand (CFD), a budget-aware edge-cloud agentic framework that turns visual access into a first-class, query-conditioned cost, capping per-query frame consumption regardless of video length.

Predicting Train Delays in Finland Using Machine Learning and Weather Data

Reliable railway operations depend increasingly on real-time environmental intelligence delivered through wireless sensor infrastructures, a capability that 6G networks will substantially enhance through integrated sensing and edge computing. Adverse weather, particularly in Arctic regions with extreme temperatures and...

Turing universality, computability, and incompleteness in hypergraph Tur\'an theory

For every consistent computably axiomatized extension of ZFC and every sufficiently large fixed $r$, there is a finite family $\mathcal F$ for which the true equality $\pi(\mathcal F)=\tau_r$ is neither provable nor refutable; analogous independence holds for the five structural properties above.

A Piecewise-Linear Approximation-based Energy-Efficient Error-Optimized Unsigned Square Rooter for Accuracy-Critical Applications

Experimental results demonstrate that EOSQR achieves high computational accuracy with a superior CEM-based accuracy-hardware efficiency trade-off while maintaining visual quality and classification performance, making it well-suited for real-time edge-embedded systems.

Quantum-edge synergy for dynamic acoustic compensation in ultrasound safety: a narrative review of tissue heterogeneity challenges

It is suggested that multi-parameter acoustic correction coupled with cloud computing holds promise for improving ultrasound safety profiling and imaging precision, however, the current low-to-moderate certainty of evidence necessitates future validation of edge-cloud synergies to realize robust, personalized monitorin...

GraphMatch: A graph-based trust-aware framework for secure multi-objective task scheduling in heterogeneous edge computing