Ranking of Fault Mitigation Techniques for Spatial Radiation in Commercial Off-the-Shelf Field Programmable Gate Array

Barbosa, Adilson Luiz; Loureiro, Geilson; Manea, Silvio; Duarte, José Marcelo Lima; Garbi, Giuliani Paulineli

doi:10.1109/tla.2020.9082217

Cited by 2 publications

(1 citation statement)

References 45 publications

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“…Additionally, the works [ 19 , 26 , 27 , 28 , 29 ] describe in detail the precautions to be taken in image acquisition and processing. In particular, according to [ 27 , 30 ], the monitoring of the interactions with the terrestrial surfaces is very important, where each intensity of the solar radiation must be observed. That is, the intensity of solar radiation received by the surface depends on the solar zenith angle that is calculated, considering [ 27 , 31 ] the incident solar radiation, the solar radiation intensity and the solar zenith angle.…”

Section: Developmentmentioning

confidence: 99%

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning

Silva

Mendes

Blas

et al. 2022

Sensors

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Due to the increasing urban development, it has become important for municipalities to permanently understand land use and ecological processes, and make cities smart and sustainable by implementing technological tools for land monitoring. An important problem is the absence of technologies that certify the quality of information for the creation of strategies. In this context, expressive volumes of data are used, requiring great effort to understand their structures, and then access information with the desired quality. This study are designed to provide an initial response to the need for mapping zones in the city of Itajaí (SC), Brazil. The solution proposes to aid object recognition employing object-based classifiers OneR, NaiveBayes, J48, IBk, and Hoeffding Tree algorithms used together with GeoDMA, and a first approach in the use of Region-based Convolutional Neural Network (R-CNN) and the YOLO algorithm. All this is to characterize vegetation zones, exposed soil zones, asphalt, and buildings within an urban and rural area. Through the implemented model for active identification of geospatial objects with similarity levels, it was possible to apply the data crossover after detecting the best classifier with accuracy (85%) and the kappa agreement coefficient (76%). The case study presents the dynamics of urban and rural expansion, where expressive volumes of data are obtained and submitted to different methods of cataloging and preparation to subsidize rapid control actions. Finally, the research describes a practical and systematic approach, evaluating the extraction of information to the recommendation of knowledge with greater scientific relevance. Allowing the methods presented to apply the calibration of values for each object, to achieve results with greater accuracy, which is proposed to help improve conservation and management decisions related to the zones within the city, leaving as a legacy the construction of a minimum technological infrastructure to support the decision.

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Section: Developmentmentioning

confidence: 99%

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning

Silva

Mendes

Blas

et al. 2022

Sensors

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AM&FT: An Aging Mitigation and Fault Tolerance Framework for SRAM-Based FPGA in Space Applications

Yang

Huang

et al. 2022

J CIRCUIT SYST COMP

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Field programmable gate arrays (FPGAs) have become very widely used devices in space applications, and their runtime reconfigurable architecture allows for the area and power acceleration for complex applications. However, FPGAs are increasingly susceptible to aging effects and failures due to harsh space environments and long operation cycles, which reduce the reliability and lifetime of such devices. Although offline aging-aware layout-based methods are effective in aging mitigation, existing studies ignore the fault tolerance needs of the task and the layout strategy will completely fail after a hard failure occurs. This paper presents a reliability framework AM&FT for SRAM-based FPGAs in space applications to support on-chip aging mitigation and fault tolerance. We use an Integer Linear Programming (ILP) model to solve mapping relationships between tasks and reconfigurable blocks (Rbs) in the offline phase to achieve the aging and reliability-aware layout strategy. Second, the ILP model is incorporated into the Design Space Exploration (DSE) to generate a set of layout strategies to tolerate hard faults. Moreover, the state model is used for runtime fault management to handle the impact of different types of faults on the device. Experimental results demonstrate that our framework achieves FPGA on-chip aging mitigation and fault tolerance. Compared with the existing methods, AM&FT can guarantee the fault tolerance requirements of tasks and give priority to guarantee the Quality of Service (QoS) of critical tasks under the condition of hard faults accumulation. In addition, our framework delivers up to [Formula: see text] mean time to failure (MTTF) than the baseline.

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Ranking of Fault Mitigation Techniques for Spatial Radiation in Commercial Off-the-Shelf Field Programmable Gate Array

Cited by 2 publications

References 45 publications

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning

AM&FT: An Aging Mitigation and Fault Tolerance Framework for SRAM-Based FPGA in Space Applications

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