
Mobile and Ubiquitous Systems: Computing, Networking and Services
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This book constitutes the proceedings of the 21st International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2024, held in Oslo, Norway, during November 12-14, 2024.
The 32 full papers presented in this book were carefully reviewed and selected from 73 submissions. They were organized into the following topical sections: Health, Biomedical Applications, and Human-Centric Computing; IoT, Cybersecurity, and Wireless Communication; Machine Learning, AI, and Smart Systems; Robotics and Autonomous Systems; and Simulation, Optimization, and Specialized Techniques.
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Content
.- Health, Biomedical Applications, and Human-Centric Computing.
.- A Preliminary Study on Core Temperature Estimation Using a Neonatal Thermal Model via Backpropagation Algorithm.
.- A Two-Step Deep Neural Network Approach for Real-Time Context-Aware Health Monitoring of Hajj Pilgrims.
.- Environment Independent Fall Detection with WiFi Streams.
.- Real-time mobile health analytics & interventions pipeline to detect acute events in COPD.
.- Wearable-based Fair and Accurate Pain Assessment Using Multi-Attribute Fairness Loss in Convolutional Neural Networks.
.- EEGAmp+: Investigating the Efficacy of Functional Connectivity for Detecting Events in Low Resolution EEG.
.- IoT, Cybersecurity, and Wireless Communication.
.- Resilience Against APTs: A Provenance-based IIoT Dataset for Cybersecurity Research.
.- Verifying Multi-Vendor IoT Deployments using Conditional Tables.
.- Supporting an Ephemeral Shared Dataspace with a BLE connectionless protocol.
.- Adaptive Deployment of Application-level Sensing and Data Processing Pipelines in a Wireless Network of Embedded Devices.
.- Exploiting NLOS Links for Energy-Efficient Opportunistic Routing in IoV.
.- Spatio-Temporal Analysis of Concurrent Networks.
.- VF-RL: A Reinforcement Learning-Based Coverage Improvement in Mobile IoT Networks using Virtual Force.
.- Machine Learning, AI, and Smart Systems.
.- A Service-based Real-time Anomaly Detection Method for Sensor Stream Data.
.- AI Robust Anomaly Localization for DC Microgrid Using Adversarial Autoencoder.
.- DERGB: An Android malware adversarial attack technique based on RGB images.
.- Deep Generative Domain Adaptation with Temporal Relation Knowledge for Cross-User Activity Recognition.
.- Genetic Algorithm Optimization for Mobile Crowd-sensing of On-street Parking.
.- GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homes.
.- Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs.
.- Scene Graph driven Context Query Generation: A Focus on Diversity and Situation-Specific Queries.
.- Robotics and Autonomous Systems.
.- A Framework for Devising, Evaluating and Fine-tuning Indoor Tracking Algorithms.
.- CSI Phase Fingerprinting for Indoor Positioning Services using Deep Reinforcement Learning.
.- Automatic Marker Placement Method for Marker-based Virtual Reality.
.- Establishing a Data-Efficient Witness Protocol for Connected Autonomous Vehicles.
.- Real-Time Obstacle Detection and Safe Operation for Industrial Autonomous Mobile Robots.
.- Simulating and Evaluating Search Strategies for Highly Accurate Localization based on Wireless Technologies using Autonomous Unmanned Aerial Vehicles.
.- Simulation, Optimization, and Specialized Techniques.
.- Event-driven Performance Evaluation of Statecharts and MicroPython on ESP32-C3 Platforms.
.- Simulating Urban Pedestrian Flows by Fusing Wide-Area Location Data and Spot Pedestrian Counts.
.- MDMV: A Malware Detection Method based on Memory and Visualization on KVM.
.- Collection Scheduling with Memory Constraints for Low Earth Orbit Satellite Constellations.
.- Smartphone Contact-Object Estimation by Acoustic Sensing Focusing on Abstraction Level.
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