The proceedings contain 57 papers. The topics discussed include: water quality pH prediction study based on improved Ceemdan and RLNNA;research on the military application and development suggestions of artificial int...
ISBN:
(纸本)9798400711237
The proceedings contain 57 papers. The topics discussed include: water quality pH prediction study based on improved Ceemdan and RLNNA;research on the military application and development suggestions of artificial intelligence;vision-based leader-follower formation control for mobile robots;research and application of e-commerce marketing fraud detection method based on graph neural network;machine learning-based income inequality prediction: a case study;an experimental study of the tones of Guangxi Fu Yang official dialect based on computer technology;significance target detection based on improved pool net;research on profit prediction of backup clamps for conductors and ground wires in transmission line engineeringbased on machine learning;and interactive exhibition design and application of museums under virtual simulation technology.
This mini review examines the security challenges faced by purchasers in the metaverse, focusing on issues such as data protection, privacy, identity theft, financial fraud, and software vulnerabilities. The metaverse...
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In serverless computing, the service provider takes full responsibility for function management. However, serverless computing has many challenges regarding data security and function scheduling. To address these chal...
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In this article, we will review our advances in intelligence modeling the mind and explore various efforts to mimic the processes that would allow humans to perform cognition files and line widgets of processing. It p...
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Recent advancements in autonomous vehicles and robotics have underscored the importance of robust 3D object detection(3DOD) systems. Among various sensor modalities, 3D LiDAR stands out for its ability to provide dens...
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This paper presents a Cross-domain Machine-Generated Text Detection model developed for the COLING 2025 workshop on Detecting AI-generated Content (DAIGenC). As large language models evolve, detecting machine-generate...
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The proceedings contain 22 papers. The special focus in this conference is on engineering of Complex computersystems. The topics include: Automated Parameter Determination for Enhancing the Product Configur...
ISBN:
(纸本)9783031664557
The proceedings contain 22 papers. The special focus in this conference is on engineering of Complex computersystems. The topics include: Automated Parameter Determination for Enhancing the Product Configuration System of Renault: An Experience Report;optimal Solution Guided Branching Strategy for Neural Network Branch and Bound Verification;AccMILP: An Approach for Accelerating Neural Network Verification based on Neuron Importance;Word2Vec-BERT-bmu:Classification of RISC-V Architecture Software Package Build Failures;Test Architecture Generation by Leveraging BERT and Control and Data Flows;less is More: An Empirical Study of Undersampling Techniques for Technical Debt Prediction;modeling and Verification of Solidity Smart Contracts with the B Method;template-based Smart Contract Verification: A Case Study on Maritime Transportation Domain;QuanSafe: A DTBN-based Framework of Quantitative Safety Analysis for AADL Models;a Event-B-based Approach for Schedulability Analysis For Real-Time Scheduling Algorithms through Deadlock Detection;Validation of RailML Using ProB;reachability Analysis of Concurrent Self-modifying Code;an Iterative Formal Model-Driven Approach to Railway systems Validation;an Efficient Distributed Dispatching Vehicles Protocol for Intersection Traffic Control;confidentiality Management in Complex systems Design;analyzing Excessive Permission Requests in Google Workspace Add-Ons;formal Verification Techniques for Post-quantum Cryptography: A Systematic Review;autoWeb: Automatically Inferring Web Framework Semantics via Configuration Mutation;safePtrX: Research on Mitigation of Heap-based Memory Safety Violations for Intel x86-64;towards Efficiently Parallelizing Patch-Space Exploration in Automated Program Repair.
Data breaches, identity theft, and the lack of user control within traditional digital identity management systems, it begs a more secure and decentralized alternative. In this study we propose a blockchain based digi...
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Pneumonia continues to pose a substantial global health challenge, necessitating prompt and precise diagnosis to enhance patient outcomes. In order to detect pneumonia and classify its severity into mild, moderate, an...
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Event-B is a refinement-based formal method that enables incremental modeling of complex systems and supports verifying system properties. Real-time systems adhere to strict timing constraints by the tasks within the ...
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ISBN:
(纸本)9783031664557;9783031664564
Event-B is a refinement-based formal method that enables incremental modeling of complex systems and supports verifying system properties. Real-time systems adhere to strict timing constraints by the tasks within the system. The real-time scheduling algorithm serves as the cornerstone to guarantee the timely completion of tasks. Therefore, modeling real-time scheduling algorithms and verifying schedulability represent prominent areas of focus within the realm of real-time systems. While existing approaches often employ model checking, the scalability of the model and the problem of state explosion during verification remain challenges. Relying on theorem proving, Event-B allows for rigorous verification of system properties and circumvents state explosion. Benefiting from model refinement, the abstract model can be extended and refined to implement various scheduling algorithms. This paper introduces an Event-B-based framework for modeling realtime scheduling algorithms and verifying properties, including schedulability. The framework provides a common refinement pattern for modeling the schedulability of the Event-B model. It facilitates the transformation of the schedulability analysis on the obtained model into the deadlock detection problem within the model. Deadlock detection can be effectively addressed through either theorem proving or model checker. We utilized Event-B to model and refine several real-time scheduling algorithms. Following the formal verification of functional and environmental requirements, we analyzed and verified the model's schedulability within the proposed framework.
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