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Machine-learning abstractions for component-based self-optimizing systems
This paper features an approach that combines machine-learning abstractions with a component model. We target modern self-optimizing systems and...
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Component level diagnosability of discrete event systems based on observations
Diagnosability of a discrete event system is usually dealt at the system level entailing synchronous composition of component automata leading to...
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Maintaining temporal validity of real-time data in component-based systems
How to schedule the sensor transactions to maintain the temporal validity of real-time data is an important research issue for cyber-physical...
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Detector-based component model abstraction for microservice-based systems
One of the chief problems in software architecture is avoiding architecture model drift and erosion in all kinds of complex software systems....
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Enabling Dynamic Selection of Implementation Variants in Component-Based Parallel Programming for Heterogeneous Systems
Heterogeneous systems, consisting of CPUs and GPUs, offer the capability to address the demands of compute- and data-intensive applications. However,...
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A Mechanized Semantics for Component-Based Systems in the HAMR AADL Runtime
Many visions for model-driven component-based development emphasize models as the “single source of truth” by which different forms of analysis,...
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Adaptive Spatial Filtering-based Component Exploration model for SSVEP-based Brain-Computer Interface for target identification
Non-invasive Brain-Computer Interface (BCI) systems have gained a massive boost from the advancement and developments in signal processing...
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Research on Script-Based Software Component Development
As software demand proliferates and software size and complexity increase, traditional software development models face enormous challenges. As a...
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A formal component model for UML based on CSP aiming at compositional verification
Model-based engineering emerged as an approach to tackle the complexity of current system development. In particular, compositional strategies assume...
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UEBCS: Software Development Technology Based on Component Selection
Current software development has moved away from the traditional manual workshop model and emphasizes improving software product quality. To address...
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Integrating Distributed Component-Based Systems Through Deep Reinforcement Learning
Modern system design and development often consists of combining different components developed by separate vendors under some known constraints that...
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A machine learning-based clustering approach to diagnose multi-component degradation of aircraft fuel systems
Accurate fault diagnosis and prognosis can significantly reduce maintenance costs, increase the safety and availability of engineering systems that...
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From low-level programming to full-fledged industrial model-based development: the story of the Rubus Component Model
Develo** distributed real-time systems is a complex task that has historically entailed specialized handcraft. In this paper, we propose a...
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Automated Property-Based Testing from AADL Component Contracts
Effective and scalable quality assurance techniques are essential for realizing formal model-based development techniques for high-assurance systems....
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Robustness improvement of component-based cloud computing systems
With the increasing popularity of Cloud computing systems, the demand for highly dependable Cloud applications has increased significantly. For this,...
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A principal component fusion-based thresholded bin-stretching for CT image enhancement
Computed tomography (CT) images play an important role in the medical field to diagnose unhealthy organs, the structure of the inner body, and other...
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Monitoring Distributed Component-Based Systems
We monitor asynchronous distributed component-based systems with multi-party interactions. We consider independent components whose interactions are...
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PRINS: scalable model inference for component-based system logs
Behavioral software models play a key role in many software engineering tasks; unfortunately, these models either are not available during software...
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An effective framework based on hybrid learning and kernel principal component analysis for face manipulation detection
Face manipulation is the process of modifying facial features in videos or images to produce a variety of artistic or deceptive effects. Face...
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Network Intrusion Detection by Variational Component-Based Feature Saliency Gaussian Mixture Clustering
Anomaly detection is a core function of the network intrusion detection system, and due to the high volume and dimensionality of network data,...