Development of a Hybrid Reference Model for Performance Evaluation of Resolvers

2021 ◽  
Vol 70 ◽  
pp. 1-8
Author(s):  
MohammadSadegh KhajueeZadeh ◽  
Hamid Saneie ◽  
Zahra Nasiri-Gheidari
2021 ◽  
Vol 32 (3) ◽  
pp. 13-29
Author(s):  
Adedibu Sunny Akingboye ◽  
◽  
Andy Anderson Bery ◽  
◽  

Geophysicists use electrical methods to investigate and characterise the earth’s subsurface geology. This study aims to evaluate the performance of copper and conventional stainless-steel electrodes in subsurface tomographic investigations using electrical resistivity tomography (ERT) and induced polarisation (IP) at two sites in Penang, Malaysia. Site 1 and Site 2 employed profile lengths of 200 m and 100 m, with electrodes spacing of 5.0 m and 2.5 m, respectively. In the results of the final data inversion, it was observed that the ERT and IP tomographic models of Site 1 have the best convergence limits with percentage relative differences (copper as reference model) ranging from –70% to 70%, while Site 2 recorded –8% to 8%. The electrodes performance evaluation showed that population root mean square (RMS) error and population mean absolute percentage error (MAPE) of data points between copper and stainless-steel electrodes yielded large values for Site 1 with values above 28% and that of Site 2 was less than 4%. Hence, copper (good electrical conductivity and non-polarisable) electrodes have improved the quality and quantity of infield data which give low values of population RMS error and population MAPE compared to conventional stainless-steel electrodes, especially for large unit electrode spacing surveys. Most notably, this work has contributed to the understanding of the capability of copper electrodes in providing precise and reliable inversion models for subsurface tomographic investigations in pre- and post-land uses (engineering work), hydrogeology/groundwater, environmental studies, etc.


2020 ◽  
Vol 8 (6) ◽  
pp. 4576-4581

This paper presents the performance evaluation of RISC – V architecture based processor using Gem5 simulator. The performance analysis metrics such as bandwidth, latency, throughput, branch prediction, pipeline stages and memory hierarchy of the processor architecture are studied using Gem5 simulator. Different simulation models are carried out to arrive the best reference model for RISC-V architecture design and development. In this reference model cache memory functionality feature is verified with the verification methodology called Universal Verification Methodology (UVM). From simulations it is found that both the program and data cache provides optimum performance in terms of execution time, hit rates, miss rate and miss latencies.


2002 ◽  
Vol 16 (2) ◽  
pp. 87-97 ◽  
Author(s):  
Jens Möller ◽  
Britta Pohlmann ◽  
Lilian Streblow ◽  
Julia Kaufmann

Zusammenfassung: Das I/E-Modell (“Internal/External Frame of Reference Model”) von Marsh (1986) postuliert, dass Schülerinnen und Schüler dimensionale Vergleiche der eigenen Leistungen in einem Fach mit den Leistungen in einem anderen Fach anstellen. Diese Vergleiche führen dazu, dass z. B. Schüler mit guten Leistungen in Mathematik ihre verbalen Fähigkeiten niedriger einschätzen. Gegenstand dieser Untersuchung mit N = 1114 Probanden ist die Frage, ob die Überzeugungen von Personen zum Zusammenhang von mathematischer und verbaler Begabung die Effekte dimensionaler Vergleiche moderieren. Analysen zeigten die Bedeutung der Begabungsüberzeugungen der Schülerinnen und Schüler: Negative Zusammenhänge zwischen den Fachleistungen in einem Fach und dem akademischen Selbstkonzept in einem anderen Fach ergaben sich insbesondere für Personen, die annehmen, dass Begabung domänenspezifisch ist, man also entweder mathematisch oder sprachlich begabt ist. Für Schüler mit eher wenig spezifischer Begabungsüberzeugung ergaben sich geringere Effekte dimensionaler Vergleiche.


Author(s):  
Carl Malings ◽  
Rebecca Tanzer ◽  
Aliaksei Hauryliuk ◽  
Provat K. Saha ◽  
Allen L. Robinson ◽  
...  

1981 ◽  
Author(s):  
Ross L. Pepper ◽  
Robert S. Kennedy ◽  
Alvah C. Bittner ◽  
Steven F. Wiker

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