Evaluating buffer memory organization impact on the message source detection procedures speed

Trudy MAI ◽  
2020 ◽  
pp. 14-14
Author(s):  
Maxim Tanygin ◽  
Haider Alshaea ◽  
Vyacheslav Dobritsa
Keyword(s):  
Memory Organization ◽  
Source Detection ◽  
Buffer Memory ◽  
Message Source

Masked Translation Priming Effects With Highly Proficient Simultaneous Bilinguals

2010 ◽  
Vol 57 (2) ◽  
pp. 98-107 ◽  
Author(s):  
Jon Andoni Duñabeitia ◽  
Manuel Perea ◽  
Manuel Carreiras
Keyword(s):  
Lexical Decision ◽  
Hierarchical Model ◽  
Priming Effect ◽  
Masked Priming ◽  
The Other ◽  
Memory Organization ◽  
Priming Effects ◽  
Bilingual Memory ◽  
Translation Priming ◽  
Masked Translation Priming

One essential issue for models of bilingual memory organization is to what degree the representation from one of the languages is shared with the other language. In this study, we examine whether there is a symmetrical translation priming effect with highly proficient, simultaneous bilinguals. We conducted a masked priming lexical decision experiment with cognate and noncognate translation equivalents. Results showed a significant masked translation priming effect for both cognates and noncognates, with a greater priming effect for cognates. Furthermore, the magnitude of the translation priming was similar in the two directions. Thus, highly fluent bilinguals do develop symmetrical between-language links, as predicted by the Revised Hierarchical model and the BIA+ model. We examine the implications of these results for models of bilingual memory.

A Preliminary Framework and Feasibility Study for Spacecraft Disturbance Source Detection and Isolation with Distributed Inertial Sensors

2021 ◽  
Author(s):  
Adam Augustyniak ◽  
David J. Hanley ◽  
Timothy W. Bretl ◽  
Neil J. Hejmanowski ◽  
David L. Carroll
Keyword(s):  
Feasibility Study ◽  
Inertial Sensors ◽  
Source Detection ◽  
Disturbance Source

scholarly journals Bayesian Reconstruction through Adaptive Image Notion

Proceedings ◽  
2019 ◽  
Vol 33 (1) ◽  
pp. 21
Author(s):  
Fabrizia Guglielmetti ◽  
Eric Villard ◽  
Ed Fomalont
Keyword(s):  
Inverse Problem ◽  
Image Plane ◽  
Source Distribution ◽  
Bayesian Probability ◽  
Model Parameters ◽  
Uncertain Information ◽  
Source Detection ◽  
Component Mixture ◽  
Ill Posed ◽  
Image Planes

A stable and unique solution to the ill-posed inverse problem in radio synthesis image analysis is sought employing Bayesian probability theory combined with a probabilistic two-component mixture model. The solution of the ill-posed inverse problem is given by inferring the values of model parameters defined to describe completely the physical system arised by the data. The analysed data are calibrated visibilities, Fourier transformed from the ( u , v ) to image planes. Adaptive splines are explored to model the cumbersome background model corrupted by the largely varying dirty beam in the image plane. The de-convolution process of the dirty image from the dirty beam is tackled in probability space. Probability maps in source detection at several resolution values quantify the acquired knowledge on the celestial source distribution from a given state of information. The information available are data constrains, prior knowledge and uncertain information. The novel algorithm has the aim to provide an alternative imaging task for the use of the Atacama Large Millimeter/Submillimeter Array (ALMA) in support of the widely used Common Astronomy Software Applications (CASA) enhancing the capabilities in source detection.

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