Many applications widely use broadcast communications (BC) due to their efficiency in simultaneously distributing data to many receivers. More specifically, BC is essential in resource-constrained devices (RCDs) for c...
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The proceedings contain 26 papers. The special focus in this conference is on Engineering of computer-Based systems. The topics include: Comparative Analysis of Uppaal SMC, ns-3 and MATLAB/Simulink;Using Aut...
ISBN:
(纸本)9783031492518
The proceedings contain 26 papers. The special focus in this conference is on Engineering of computer-Based systems. The topics include: Comparative Analysis of Uppaal SMC, ns-3 and MATLAB/Simulink;Using Automata Learning for Compliance Evaluation of Communication Protocols on an NFC Handshake Example;Towards LLM-Based System Migration in Language-Driven Engineering;synthesizing Understandable Strategies;ReProInspect: Framework for Reproducible Defect Datasets for Improved AOI of PCBAs;cyber-Physical Ecosystems: Modelling and Verification;integrating IoT Infrastructures in Industrie 4.0 Scenarios with the Asset Administration Shell;A Software Package (in progress) that Implements the Hammock-EFL Methodology;toward Responsible Artificial Intelligence systems: Safety and Trustworthiness;Dynamic Priority Scheduling for Periodic systems Using ROS 2;continuous Integration of Neural networks in Autonomous systems;building a Digital Twin Framework for Dynamic and Robust distributedsystems;a Simple End-to-End computer-Aided Detection Pipeline for Trained Deep Learning Models;astrocyte-Integrated Dynamic Function Exchange in Spiking Neural networks;Correct Orchestration of Federated Learning Generic Algorithms: Formalisation and Verification in CSP;careProfSys - Combining Machine Learning and Virtual Reality to Build an Attractive Job Recommender System for Youth: Technical Details and Experimental Data;ambient Temperature Prediction for Embedded systems Using Machine Learning;a Federated Learning Algorithms Development Paradigm;machine Learning Data Suitability and Performance Testing Using Fault Injection Testing Framework;IDPP: Imbalanced Datasets Pipelines in Pyrus;learning in Uppaal for Test Case Generation for Cyber-Physical systems;a Literature Survey of Assertions in Software Testing;FPGA-Based Encryption for Peer-to-Peer Industrial Network Links.
Recently, many deep learning applications have been used on the mobile platform. To deploy them in the mobile platform, the networks should be quantized. The quantization of computer vision networks has been studied w...
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This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is pos...
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The SDN-based network architecture currently lacks a framework for the efficient development and deployment of machine learning (ML) functions within the data plane. This paper addresses this gap by proposing a unifie...
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Recent improvements in nanotechnology and Internet of Things (IoT) have led to the emergence of the concept of Internet of Nano-Things (IoNT). This concept provided ease of access and communication facilities for the ...
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Recent improvements in nanotechnology and Internet of Things (IoT) have led to the emergence of the concept of Internet of Nano-Things (IoNT). This concept provided ease of access and communication facilities for the nano-devices in applications of different fields operating at the molecular level such as health, industry, agriculture, robotics and military. These distributed devices interconnect over the Wireless Nano-Sensor networks (WNSNs) in nano-scale which have limited energy and capacity. Therefore, these devices need to use their energy efficiently when communicating with each other to ensure network continuity and maintain all processes of IoNT applications. In this paper, a novel energy-efficient distributed routing algorithm, namely DEEPNT, is proposed in order to extend the lifetime of WNSNs in IoNT applications. The communication backbone of WNSNs constructed by DEEPNT by selecting cluster head nodes can be used in all types of IoNT applications in nano-scale in order to provide continuous data flow in critical areas such as healthcare running in vivo. This novel energy-efficient distributed protocol is compared with the traditional flooding based method and with an energy aware routing algorithm. According to the results, DEEPNT prolongs the WNSNs average lifetime respectively up to 10.78 and 5.95 times compared to mentioned algorithms despite the larger network sizes in nano-scale.(C) 2022 Elsevier B.V. All rights reserved.
The proceedings contain 30 papers. The topics discussed include: learning to identify graphs from node trajectories in multi-robot networks;task elimination: faster coalition formation for overtasked collectives;ant c...
ISBN:
(纸本)9798350370768
The proceedings contain 30 papers. The topics discussed include: learning to identify graphs from node trajectories in multi-robot networks;task elimination: faster coalition formation for overtasked collectives;ant colony optimization for heterogeneous coalition formation and scheduling with multi-skilled robots;virtual omnidirectional perception for downwash prediction within a team of nano multirotors flying in close proximity;from distributed coverage to multi-agent target tracking;selective negotiations for scaling stochastic dynamic games;diffusion models for multi-target adversarial tracking;adversarial search and tracking with multiagent reinforcement learning in sparsely observable environment;and optimizing fuel-constrained UAV-UGV routes for large scale coverage: bilevel planning in heterogeneous multi-agent systems.
Cybersecurity has become a significant concern for automotive manufacturers as modern cars increasingly incorporate electronic components. Electronic Control Units (ECUs) have evolved to become the central control uni...
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Over the past ten years, graph representation learning has garnered a lot of attention due to the variety of graph-structured data and its efficiency in both time and space. One essential method for obtaining effectiv...
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Effective diagnosis of diabetes is crucial for managing the disease and preventing complications. This study explores the use of machine learning for diabetes prediction, focusing on the impact of data preprocessing o...
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