scholarly journals Accident prevention via information transfer from vehicles to pedestrians based on visual functions of velocity perception

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Yasuhi Yokoya ◽  
Hitoshi Soma
Author(s):  
David A. Grano ◽  
Kenneth H. Downing

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.


Author(s):  
D. Van Dyck

An (electron) microscope can be considered as a communication channel that transfers structural information between an object and an observer. In electron microscopy this information is carried by electrons. According to the theory of Shannon the maximal information rate (or capacity) of a communication channel is given by C = B log2 (1 + S/N) bits/sec., where B is the band width, and S and N the average signal power, respectively noise power at the output. We will now apply to study the information transfer in an electron microscope. For simplicity we will assume the object and the image to be onedimensional (the results can straightforwardly be generalized). An imaging device can be characterized by its transfer function, which describes the magnitude with which a spatial frequency g is transferred through the device, n is the noise. Usually, the resolution of the instrument ᑭ is defined from the cut-off 1/ᑭ beyond which no spadal information is transferred.


2009 ◽  
Vol 14 (1) ◽  
pp. 78-89 ◽  
Author(s):  
Kenneth Hugdahl ◽  
René Westerhausen

The present paper is based on a talk on hemispheric asymmetry given by Kenneth Hugdahl at the Xth European Congress of Psychology, Praha July 2007. Here, we propose that hemispheric asymmetry evolved because of a left hemisphere speech processing specialization. The evolution of speech and the need for air-based communication necessitated division of labor between the hemispheres in order to avoid having duplicate copies in both hemispheres that would increase processing redundancy. It is argued that the neuronal basis of this labor division is the structural asymmetry observed in the peri-Sylvian region in the posterior part of the temporal lobe, with a left larger than right planum temporale area. This is the only example where a structural, or anatomical, asymmetry matches a corresponding functional asymmetry. The increase in gray matter volume in the left planum temporale area corresponds to a functional asymmetry of speech processing, as indexed from both behavioral, dichotic listening, and functional neuroimaging studies. The functional anatomy of the corpus callosum also supports such a view, with regional specificity of information transfer between the hemispheres.


2006 ◽  
Author(s):  
Ayse P. Gurses ◽  
Yan Xiao ◽  
Paul Gorman ◽  
Brian Hazlehurst ◽  
Grant Bochicchio ◽  
...  

2014 ◽  
Vol 75 (S 01) ◽  
Author(s):  
Liliya Khisanova ◽  
Bakhtiyar Pashaev ◽  
Gulnar Vagapova ◽  
Valery Danilov ◽  
Dmitry Bochkarev

2001 ◽  
Vol 7 (4) ◽  
pp. 38-44
Author(s):  
O.V. Zbruts'kyi ◽  
◽  
O.I. Nesterenko ◽  
O.V. Prokhorchuk ◽  
◽  
...  

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