This work-in-progress paper presents our current effort toward the development of compositional modeling formalisms and scalable algorithms for high-assurance design of industrial cyber-physical systems, with emphasis...
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ISBN:
(纸本)9781665409674
This work-in-progress paper presents our current effort toward the development of compositional modeling formalisms and scalable algorithms for high-assurance design of industrial cyber-physical systems, with emphasis on smart manufacturing systems. A requirement engineering methodology is implemented within CHASE, a software framework supporting contract-based representations of systems and components to facilitate analysis and design space exploration. We provide an overview of CHASE and discuss its application to the design of a robotic arm. This paper is accompanied by a poster describing the architecture of CHASE and a demonstration of its application to the case study.
The proceedings contain 68 papers. The special focus in this conference is on computer Aided Verification. The topics include: Rely-Guarantee Reasoning for Causally Consistent Shared Memory;unblocking Dynamic Par...
ISBN:
(纸本)9783031377082
The proceedings contain 68 papers. The special focus in this conference is on computer Aided Verification. The topics include: Rely-Guarantee Reasoning for Causally Consistent Shared Memory;unblocking Dynamic Partial Order Reduction;3D Environment modeling for Falsification and Beyond with Scenic 3.0;a Unified Model for Real-Time systems: Symbolic Techniques and Implementation;closed-Loop Analysis of Vision-Based Autonomous systems: A Case Study;hybrid Controller Synthesis for Nonlinear systems Subject to Reach-Avoid Constraints;safe Environmental Envelopes of Discrete systems;verse: A Python Library for Reasoning About Multi-agent Hybrid System Scenarios;counterexample Guided Knowledge Compilation for Boolean Functional Synthesis;Automated Analyses of IOT Event Monitoring systems;Guessing Winning Policies in LTL Synthesis by Semantic Learning;Policy Synthesis and Reinforcement Learning for Discounted LTL;synthesizing Permissive Winning Strategy Templates for Parity Games;synthesizing Trajectory Queries from Examples;learning Assumptions for Compositional Verification of Timed Automata;online Causation Monitoring of Signal Temporal Logic;process Equivalence Problems as Energy Games;commutativity for Concurrent Program Termination Proofs;fast Termination and Workflow Nets;Lincheck: A Practical Framework for Testing Concurrent Data Structures on JVM;nekton: A Linearizability Proof Checker.
In this study, resource allocation techniques based on reinforcement learning (RL) for 5G millimeter wave (mmWave) networks are compared and analyzed. The high bandwidth and large available spectrum in mmWave networks...
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The electric balance optimization measures and verification methods of electric vehicles were introduced, the electrical system modeling and simulation analysis, intelligent power management module design, energy dist...
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ISBN:
(数字)9798350377255
ISBN:
(纸本)9798350377262
The electric balance optimization measures and verification methods of electric vehicles were introduced, the electrical system modeling and simulation analysis, intelligent power management module design, energy distribution design, load control strategy design were carried out, and the test methods were optimized. The load control strategy is designed, and the test method is optimized, and the effectiveness of the vehicle electric balance optimization measures is proved by comparing the data before and after optimization. This study provides valuable solutions and references for the design and verification of electric balance for electric vehicles, and is of great significance for promoting the further development of electric vehicle technology.
For a short-medium-range aircraft at cruise, the Environmental Control System (ECS) consumes about 75% of the total extracted engine bleed air on average. The Air Management System (AMS) of the ECS significantly reduc...
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ISBN:
(纸本)9780791887929
For a short-medium-range aircraft at cruise, the Environmental Control System (ECS) consumes about 75% of the total extracted engine bleed air on average. The Air Management System (AMS) of the ECS significantly reduces the bleed air pressure and temperature to meet the inlet requirements of the Pressurized Air Conditioning Kit (PACK). This paper aims to understand the impact of the conventional AMS on the engine performance and proposes an alternative AMS architecture for effective utilization of the bleed off-take pressure and temperature. Subsequently, a steady-state 0D thermodynamic analysis of the conventional and alternative AMS architectures is carried out using PROOSIS (TM) software, to study their impact on engine performance for different mission phases. Based on this preliminary thermodynamic analysis the alternative AMS shows a potential improvement of the engine performance mainly in terms of the TSFC, up to 0.7% across different mission phases.
Cloud is very effective technology, which works over the Internet provides services such as servers, storage, networking, workstations, virtual environment etc. This technology supports the distributed environment wit...
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Software modeling, as used in Model-Driven Engineering (MDE), is the process of abstracting software systems using formal or informal notations to help with communication, analysis, and design. This study looks into t...
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In recent years, the electromagnetic scattering characteristics of large ground equipment have attracted more and more attention, and how to accurately and efficiently obtain the electromagnetic scattering characteris...
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This paper discusses recent developments in the data-based modeling and control of nonlinear chemical process systems using sparse identification of nonlinear dynamics (SINDy). SINDy is a recent nonlinear system ident...
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Neural network models have become the leading solution for a large variety of tasks, such as classification, natural language processing, and others. However, their reliability is heavily plagued by adversarial inputs...
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ISBN:
(数字)9789819916399
ISBN:
(纸本)9789819916382;9789819916399
Neural network models have become the leading solution for a large variety of tasks, such as classification, natural language processing, and others. However, their reliability is heavily plagued by adversarial inputs: inputs generated by adding tiny perturbations to correctly-classified inputs, and for which the neural network produces erroneous results. In this paper, we present a new method called Robustness measurement and Assessment (RoMA), which measures the robustness of a neural network model against such adversarial inputs. Specifically, RoMA determines the probability that a random input perturbation might cause misclassification. The method allows us to provide formal guarantees regarding the expected frequency of errors that a trained model will encounter after deployment. The type of robustness assessment afforded by RoMA is inspired by state-of-the-art certification practices, and could constitute an important step toward integrating neural networks in safety-critical systems.
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