In this paper, a bridgeless buck PFC structure is presented. To Fulfill soft switching for the main switches an auxiliary circuitry is utilized. The main switches of the proposed structure operate under ZVS condition ...
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In the field of software development, ensuring the accuracy and quality of code remains a paramount concern. The task of precisely classifying code as correct or incorrect poses inherent challenges. This research intr...
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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.
This paper addresses the problem of deploying complex systems in Kubernetes clusters. It discusses using the OperatorSDK framework supported by RedHat as a basis for implementing the Kubernetes operator for Lightweigh...
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The importance of computer network experiments in teaching is elaborated, while traditional computer network systems have low efficiency and chaotic management, these shortcomings affect the effectiveness of related t...
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The integration of artificial intelligence in agriculture has revolutionized farming practices, enhancing crop yields and resource efficiency. However, existing machine learning systems primarily focus on livestock, o...
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Reactive synthesis is an automated process for deriving correct-by-construction reactive systems from temporal specifications. GR(1), in particular, is a popular LTL fragment that balances efficient synthesis complexi...
[Context and Motivation]: Cyber-Physical systems (CPS) have become relevant in a wide variety of different domains, integrating hardware and software, often operating in an emerging and uncertain environment where hum...
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Deep Neural Networks (DNNs) have found successful applications in various non-safety-critical domains. However, given the inherent lack of interpretability in DNNs, ensuring their prediction accuracy through robustnes...
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ISBN:
(纸本)9783031664557;9783031664564
Deep Neural Networks (DNNs) have found successful applications in various non-safety-critical domains. However, given the inherent lack of interpretability in DNNs, ensuring their prediction accuracy through robustness verification becomes imperative before deploying them in safety-critical applications. Neural Network Verification (NNV) approaches can broadly be categorized into exact and approximate solutions. Exact solutions are complete but time-consuming, making them unsuitable for large network architectures. In contrast, approximate solutions, aided by abstraction techniques, can handle larger networks, although they may be incomplete. This paper introduces AccMILP, an approach that leverages abstraction to transform NNV problems into Mixed Integer Linear Programming (MILP) problems. AccMILP considers the impact of individual neurons on target labels in DNNs and combines various relaxation methods to reduce the size of NNV models while ensuring verification accuracy. The experimental results indicate that AccMILP can reduce the size of the verification model by approximately 30% and decrease the solution time by at least 80% while maintaining performance equal to or greater than 60% of MIPVerify. In other words, AccMILP is well-suited for the verification of large-scale DNNs.
The ubiquitous time-delay estimation (TDE) problem becomes nontrivial when sensors are non-co-located and communication between them is limited. Building on the recently proposed "extremum encoding" compress...
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