edge computing

Cadaveric study of the ultrasound-guided erector spinae plane block over the dorsolateral edge of the transverse process of the ninth thoracic vertebra in dogs: transverse vs. longitudinal approach

Introduction Studies of the ultrasound-guided thoracic erector spinae plane (ESP) blocks in dogs are limited. This study aimed to describe a transverse (TV) ultrasound-guided ESP approach at the dorsolateral edge of the transverse process (DLETP) of T9, compare its distribution with a longitudinal (LNG) approach, and a...

Lightweight deep learning-based multicarrier modulation classification for UAV-assisted 5G communication systems

Purpose Unmanned aerial vehicle (UAV)–assisted communication leverages Automatic Modulation classification (AMC) to enhance wireless transmission efficiency. The classification of multicarrier modulation (MCM) signals is a critical component AMC, enabling robust signal demodulation and adaptive resource allocation. How...

AI-Driven Energy-Efficient 6G Smart City Networks: Traffic Prediction, Deep Reinforcement Learning, and Zero-Touch Control

Abstract: Sixth-generation (6G) communication is expected to support dense Internet of Things deployments, connected vehicles, immersive services, intelligent transport, remote health-care, and other data-intensive smart-city functions. The same ultra-dense radio access infrastructure, massive multiple-input multiple-o...

Maximum two-distance sets in Euclidean spaces of dimension up to twenty-one

A two-distance set is a finite set of points in ℝᵈ whose pairwise distances take exactly two values; g(d) denotes the largest cardinality of such a set. The values g(d) were known for d ≤ 8 (Einhorn–Schoenberg, Lisoněk) and, since a recent computer-assisted classification, for 9 ≤ d ≤ 12, where g(d) = C(d+1, 2) is atta...

What the Corpus Does Not Say: Reply structure, time and coverage in YouTube comment data

What linguists and other researchers should check before treating comments as conversation. Anyone planning a research project with YouTube comments meets the same technical hurdles: which tool to collect with, which fields can be trusted, and how to tell whether a corpus is complete. The hurdles are easy to miss when...

Adaptive actor-critic framework for efficient and reliability-aware SFC deployment in mobile edge computing

Machine Learning Enabled IoT Embedded Platform for RealTime Anomaly Detection in Drug Delivery Devices

The reliability of modern drug delivery devices such as infusion pumps and insulin pumps is critically dependent on accurate delivery of medication.However, despite advances in recent years, such devices are prone to failure with reported events including flow abnormalities, blockages, inaccurate dosage delivery and me...

A Low-Cost IoT-Based Framework for District-Level Soil Moisture Stress Monitoring Using Sentinel-1 SAR and Edge Visualization

Vibration and Noise Monitoring

Vibration and noise are among the most information-rich by-products of mining. Every blast, haul truck pass, crusher start-up, pump cycle, rockfall impact, and conveyor idler defect leaves a distinctive mechanical and acoustic fingerprint. This chapter develops a practical and scientific framework for monitoring vibrat...

CERN AI Core Implementation Plan

The CERN AI Strategy 2026-2030, endorsed by CERN Management in March 2026, establishes AI as a core organisational capability alongside computing, detectors, and engineering. This Implementation Plan translates that commitment into a phased programme with a defined resource envelope, governance model, and measurable ou...

Application of Digital Twin

A digital twin in mining is a dynamic, real-time virtual representation of physical assets and operational processes that supports predictive modeling, optimization, and decision-making. This chapter examines the architecture, data integration strategies, modeling approaches, and practical applications of digital twins...

EL-RAKHAWI ARCHITECTURE FOR REVERSIBLE, TOPOLOGICALLY PROTECTED NEUROMORPHIC COMPUTING VIA SPIN-ORBIT TORQUE IN 2D MATERIALS (RTN-SOT)

EL-RAKHAWI ARCHITECTURE RTN-SOT: POST-SILICON NEUROMORPHIC COMPUTING Author: Dr. Mohamed Kamal Arafa El-RakhawiDOI: 10.5281/zenodo.23334146 A revolutionary neuromorphic computing architecture breaking the Landauer energy barrier through integration of three proven phenomena: quasi-adiabatic magnetization switching, spi...