Character Skeleton as a Pen Trace Model for Recognition from Reconstructed Trace

2021 ◽  
Vol 82 (11) ◽  
pp. 1835-1845
Author(s):  
S. P. Arseev ◽  
L. M. Mestetskiy
Keyword(s):  
2016 ◽  
Vol 42 (11) ◽  
pp. 1903-1922 ◽  
Author(s):  
Marcus Cappiello ◽  
Weiwei Zhang
Keyword(s):  

2019 ◽  
Vol 19 (03) ◽  
pp. 1950029 ◽  
Author(s):  
Jun Chen ◽  
Guo Ding ◽  
Stana Živanović

Developing a model for the dynamic force generated by a pedestrian’s foot on a supporting structure (single footfall trace model) is crucial to advanced numerical analysis and vibration serviceability assessment of the structure. A reliable model needs to reflect the inter-subject and intra-subject randomness of human walking. This paper introduces a stochastic single footfall trace model in the form of a Fourier series in which body weight, walking frequency, and the first eight harmonics are treated as random variables. An experiment used 73 test subjects, walking at a range of pacing frequencies, to record force time histories and the corresponding gait parameters. Two variability descriptors were used to indicate inter-subject and intra-subject randomness. Further statistical analysis identified the relationships between key parameters as well as the probability distribution functions of random variables. In the final step, an application of the proposed single footfall trace model was developed and tested. The proposed model represented the experimental data well in both time and frequency domains.


2019 ◽  
Author(s):  
Manisha Chawla ◽  
Richard Shillcock

Implemented computational models are a central paradigm of Cognitive Science. How do cognitive scientists really use such models? We take the example of one of the most successful and influential cognitive models, TRACE (McClelland & Elman, 1986), and we map its impact on the field in terms of published, electronically available documents that cite the original TRACE paper over a period of 25 years since its publication. We draw conclusions about the general status of computational cognitive modelling and make critical suggestions regarding the nature of abstraction in computational modelling.


Author(s):  
Marc Thieme ◽  
Wolfgang Tietsch ◽  
Rafael Macian ◽  
Victor Hugo Sanchez Espinoza

The validation of heat transfer models of safety analysis codes such as TRACE is very important due to the strong interaction of the thermal hydraulics parameters with the core neutronics. TRACE is the reference system code of the US NRC for LWR. It is being developed and extensively validated within the international CAMP-program. In this paper, the validation of heat transfer models of TRACE related to the prediction of the critical power is presented. The validation is based on a large number of critical power tests performed in the NUPEC BFBT (BWR Full-Size Fine-Mesh Bundle Tests) facility in Japan. These tests were analysed with the TRACE Version 5 RC 2. The comparison of predictions with the experimental data shows good agreement. The developed TRACE model and the comparison of experimental data with code results will be presented and discussed.


2008 ◽  
Vol 106 (3) ◽  
pp. 120-126 ◽  
Author(s):  
Thierry Massart ◽  
Cédric Meuter ◽  
Laurent Van Begin

Author(s):  
Sahil Luthra ◽  
Monica Y. C. Li ◽  
Heejo You ◽  
Christian Brodbeck ◽  
James S. Magnuson

AbstractPervasive behavioral and neural evidence for predictive processing has led to claims that language processing depends upon predictive coding. Formally, predictive coding is a computational mechanism where only deviations from top-down expectations are passed between levels of representation. In many cognitive neuroscience studies, a reduction of signal for expected inputs is taken as being diagnostic of predictive coding. In the present work, we show that despite not explicitly implementing prediction, the TRACE model of speech perception exhibits this putative hallmark of predictive coding, with reductions in total lexical activation, total lexical feedback, and total phoneme activation when the input conforms to expectations. These findings may indicate that interactive activation is functionally equivalent or approximant to predictive coding or that caution is warranted in interpreting neural signal reduction as diagnostic of predictive coding.


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