作者：
Grout, IanMullin, LenoreUniversity of Limerick
Faculty of Science and Engineering Department of Electronic and Computer Engineering Limerick Ireland University at Albany
SUNY College of Engineering and Applied Sciences Department of Computer Science AlbanyNY United States
In this paper, the Mathematic of Arrays (MoA) approach to solving complex multi-dimensional array computations using array indexing is considered with reference in its implementation in code targeting embedded systems...
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In Biomedicine, computersoftware is applied to the medical image for content analysis by MRI scanning for the program. Preprocessing, removal of noise, processing images in order to detect objects and analysis of the...
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Medical errors contribute significantly to morbidity and mortality, emphasizing the critical role of Clinical Guidelines (GLs) in patient care. Automating GL application can enhance GL adherence, improve patient outco...
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The intrinsic complexity of deep neural networks (DNNs) makes it challenging to verify not only the networks themselves but also the hosting DNN-controlled systems. Reachability analysis of these systems faces the sam...
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ISBN:
(纸本)9783031505201;9783031505218
The intrinsic complexity of deep neural networks (DNNs) makes it challenging to verify not only the networks themselves but also the hosting DNN-controlled systems. Reachability analysis of these systems faces the same challenge. Existing approaches rely on overapproximating DNNs using simpler polynomial models. However, they suffer from low efficiency and large overestimation, and are restricted to specific types of DNNs. This paper presents a novel abstraction-based approach to bypass the crux of over-approximating DNNs in reachability analysis. Specifically, we extend conventional DNNs by inserting an additional abstraction layer, which abstracts a real number to an interval for training. The inserted abstraction layer ensures that the values represented by an interval are indistinguishable to the network for both training and decision-making. Leveraging this, we devise the first blackbox reachability analysis approach for DNN-controlled systems, where trained DNNs are only queried as black-box oracles for the actions on abstract states. Our approach is sound, tight, efficient, and agnostic to any DNN type and size. The experimental results on a wide range of benchmarks show that the DNNs trained by using our approach exhibit comparable performance, while the reachability analysis of the corresponding systems becomes more amenable with significant tightness and efficiency improvement over the state-of-the-art white-box approaches.
An integrated monitoring system for power dispatching control for power market is proposed. The logical structure, software structure and configuration structure are analyzed. The software and hardware monitoring of p...
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This study addresses the issue of double frequency fluctuations caused by cascade converters in high-voltage DC transmission systems by designing a system that uses a 4.3kV, 50Hz three-phase AC input and ultimately ou...
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Network systems function based on rules that are intrinsically dynamic, subject to temporal circumstances set by outside events like host utilisation, bandwidth measurements, intrusion detection, or time-specific even...
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Examining the complex interplay between softwareengineering and silicon technology, "Systematic Structures and Silicon Stories Shaping the Saga of software Solutions" is an interdisciplinary investigation t...
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It is vital to guarantee that engineering graduates have learned essential skills required to excel in a dynamic technological landscape. Today the proliferation of low-cost, high-speed computing devices offer opportu...
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Intel software development ecosystem is complex, consisting of components produced in-house, third-party vendors and open-source community. Different tools and processes are being used to manage individual deliverable...
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