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E-book: Designing Modern Embedded Systems: Software, Hardware, and Applications: 7th IFIP TC 10 International Embedded Systems Symposium, IESS 2022, Lippstadt, Germany, November 3-4, 2022, Proceedings

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Designing Modern Embedded Systems: Software, Hardware, and Applications: 7th IFIP TC 10 International Embedded Systems Symposium, IESS 2022, Lippstadt, Germany, November 3-4, 2022, ProceedingsLarger Image
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This book constitutes the refereed proceedings of the 7th IFIP TC 10 International Embedded Systems Symposium, IESS 2022, held in Lippstadt, Germany, during November 3-4, 2022.
The 10 full revised papers and 2 short papers presented were carefully reviewed and selected from 13 submissions. The presented research and technical works cover system-level design methods, algorithms, verification and validation techniques, estimation of system properties and characteristics, performance analysis, and real-time systems design. Also, the book presents industrial and real-world application case studies that discuss the challenges and realizations of modern embedded systems, especially when it comes to including artificial intelligence algorithms and techniques in embedded systems.


Evaluating the Perceptual Properties of Crosscutting Concerns Occurrence Points Specifications in Embedded Software.- Simulation of Timing Attacks and Challenges for Early Side-Channel Security Analysis.- Adaptation for Energy Saving in Time-triggered Systems Using Meta-scheduling with Sample Points.- Communication Layer Architecture for a Production Line Digital Twin Using Hierarchical Colored Petri Nets.- Exploiting Heterogeneity in PIM Architectures for Data-intensive Applications.- Demonstrating Scalability of the Checkerboard GPC with SystemC TLM-2.- MAFAT: Memory-Aware Fusing and Tiling of Neural Networks for Accelerated Edge Inference.- Memristor-only LSTM Acceleration with Non-linear Activation Functions.- Minimizing Memory Contention in an APNG Encoder Using a Grid of Processing Cells.- Analyzing the Characteristics of Neural Networks for the Recognition of Sugar Beets.- Synthetic Data for Machine Learning on Embedded Systems in Precision Agriculture.- Using Network Architecture Search for Optimizing Tensor Compression.

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