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Published in 2017 at "Real-Time Systems"
DOI: 10.1007/s11241-017-9283-6
Abstract: Contemporary distributed embedded systems in many domains have become highly complex due to ever-increasing demand on advanced computer controlled functionality. The resource reservation techniques can be effective in lowering the software complexity, ensuring predictability and…
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Keywords:
resource;
distributed embedded;
embedded systems;
end end ... See more keywords
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Published in 2018 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2018.07.173
Abstract: Abstract The paper proposes a statistical classification method devoted to multisensor embedded systems. It is based on estimation of multidimensional probability density function (pdf) which describes statistical properties of multisensor measurement data. Various methods of…
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Keywords:
classification method;
density function;
multidimensional probability;
probability density ... See more keywords
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Published in 2019 at "Measurement"
DOI: 10.1016/j.measurement.2018.10.014
Abstract: Abstract In recent years, embedded control systems are extensively replacing the mechanical control systems in the agriculture industry, following passenger car and commercial vehicle segments. The main role of these electronic based control system is…
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Keywords:
system;
automation;
test;
embedded systems ... See more keywords
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Published in 2020 at "AIP Advances"
DOI: 10.1063/1.5140466
Abstract: The technological revolution affects the growth of systems in terms of functionality and complexity. Industries of embedded systems become increasingly an area of interest for researchers to develop Computer-Aided Design (CAD) environments to support at…
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Keywords:
embedded systems;
system level;
level simulation;
simulation ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2923219
Abstract: With the advent of the Internet-of-Things (IoT) era, the demand for lightweight embedded systems is rapidly increasing. So far, ultra-low power (ULP) processors have been leading the development of lightweight embedded systems. However, as the…
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Keywords:
lightweight embedded;
embedded systems;
memory management;
network chip ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2952321
Abstract: Online remote laboratories are a particularly promising tool for effective STEM education. They offer online universal access to different hardware devices in which students can experiment and can test and improve their knowledge. However, most…
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Keywords:
remote laboratories;
hardware;
architecture;
embedded systems ... See more keywords
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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3013721
Abstract: Multicore platforms offer great potential for task-level redundancy to achieve a degree of fault-tolerance/reliability in embedded systems by exploiting the idle cores. However, due to the Thermal Design Power (TDP) constraint, it may not be…
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Keywords:
primary backup;
power aware;
power;
embedded systems ... See more keywords
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Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3074070
Abstract: The low-power design of software and hardware is crucial for the efficiency and sustainability of embedded systems. Accurate energy consumption measurement plays a vital role in evaluating the energy performance of software and hardware, which…
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Keywords:
embedded systems;
consumption measurement;
energy consumption;
energy ... See more keywords
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Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3088395
Abstract: This paper presents a novel security approach called Anomalous Resource Consumption Detection (ARCD), which acts as an additional layer of protection to detect cyberattacks in embedded systems (ESs). The ARCD approach is based on the…
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Keywords:
system;
resource utilization;
resource;
approach ... See more keywords
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Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3403033
Abstract: Negative Group Delay (NGD) is a concept not widely explored in embedded digital signal processing systems, and this study aims to fill this gap. It presents a novel methodology for implementing NGD using second-order Finite…
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Keywords:
methodology;
novel digital;
time;
fpga based ... See more keywords
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Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3416034
Abstract: Phase picking is a critical task in seismic data processing, where deep learning methods have been applied to enhance its accuracy. While lightweight deep learning networks have been optimized for edge computing devices, there is…
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Keywords:
branch;
network;
embedded systems;
seismic phase ... See more keywords