Titlebook: Applications in Electronics Pervading Industry, Environment and Society; APPLEPIES 2019 Sergio Saponara,Alessandro De Gloria Conference pro

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Alcove

Analyzing Machine Learning on Mainstream Microcontrollersor ARM microcontroller developers. This paper explores the use of one of such tools, namely the STM X-Cube-AI, on mainstream ARM Cortex-M microcontrollers, analyzing their performance, and comparing support and performance of other two common supervised ML algorithms, namely Support Vector Machines

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Quality Aware Selective ECC for?Approximate DRAMey are considered part of the building blocks in the larger area of approximate computing. Relaxing refresh rate has been proposed as an interesting solution to achieve better efficiency at the expense of rising error rate. However, some works have demonstrated that much better results are achieved

現(xiàn)暈光

Digital Random Number Generator Hardware Accelerator IP-Core for Security Applicationsity chain. They are employed for creation of encryption keys, and if generation process is weak, the whole chain can be compromised: weaknesses could be exploited to retrieve the key, thus breaking even the strongest cipher. This paper presents the architecture of a digital Random Number Generator (

ALLEY

An Energy Optimized JPEG Encoder for Parallel Ultra-Low-Power Processing-Platformsen a high amount of data needs to be sent wirelessly such as in Wireless Camera Sensors (WCS). Onboard real-time image compression is the appropriate solution to decrease the system’s energy. This paper proposes an optimized algorithm implementation tailored for PULP (Parallel Ultra Low Power) proce

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1876-1100 of application domains, from automotive to space and from heThis book provides a thorough overview of cutting-edge research on electronics applications relevant to industry, the environment, and society at large. It covers a broad spectrum of application domains, from automotive to space and from he

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https://doi.org/10.1007/0-387-33608-7 Dhrystone and CoreMark that may represent generic workloads. The results show certain block are more prone to fault than others, as also confirmed by a vulnerability analysis that correlates the number of observed faults and the rate of access to the blocks.

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