2 resultados para Cross-device interaction
em CaltechTHESIS
Resumo:
Precise measurements of the total reaction cross section for 3He(3He,2p)4He He have been made in the range of center-of-mass energies between 1100 keV and 80 keV. A differentially pumped gas target modified to operate with a limited quantity of the target gas was employed to minimize the uncertainties in the primary energy and energy straggle. Beam integration inside the target gas was carried out by a calorimetric device which measures the total energy spent in a heat sink rather than the total charge in a Faraday cup. Proton energy spectra have been obtained using a counter telescope consisting of a gas proportional counter and a surface barrier detector and angular distributions of these protons have been measured at seven bombarding energies. Cross section factors, S(E), have been calculated from the total cross sections and fitted to a linear function of energy over different ranges of energy. For Ecm < 500 keV
S(Ecm) = S0 + S1 Ecm
where S0 = (5.0 +0.6-0.4) MeV - barns and S1 = (-1.8 ± 0.5) barns.
Resumo:
In the first section of this thesis, two-dimensional properties of the human eye movement control system were studied. The vertical - horizontal interaction was investigated by using a two-dimensional target motion consisting of a sinusoid in one of the directions vertical or horizontal, and low-pass filtered Gaussian random motion of variable bandwidth (and hence information content) in the orthogonal direction. It was found that the random motion reduced the efficiency of the sinusoidal tracking. However, the sinusoidal tracking was only slightly dependent on the bandwidth of the random motion. Thus the system should be thought of as consisting of two independent channels with a small amount of mutual cross-talk.
These target motions were then rotated to discover whether or not the system is capable of recognizing the two-component nature of the target motion. That is, the sinusoid was presented along an oblique line (neither vertical nor horizontal) with the random motion orthogonal to it. The system did not simply track the vertical and horizontal components of motion, but rotated its frame of reference so that its two tracking channels coincided with the directions of the two target motion components. This recognition occurred even when the two orthogonal motions were both random, but with different bandwidths.
In the second section, time delays, prediction and power spectra were examined. Time delays were calculated in response to various periodic signals, various bandwidths of narrow-band Gaussian random motions and sinusoids. It was demonstrated that prediction occurred only when the target motion was periodic, and only if the harmonic content was such that the signal was sufficiently narrow-band. It appears as if general periodic motions are split into predictive and non-predictive components.
For unpredictable motions, the relationship between the time delay and the average speed of the retinal image was linear. Based on this I proposed a model explaining the time delays for both random and periodic motions. My experiments did not prove that the system is sampled data, or that it is continuous. However, the model can be interpreted as representative of a sample data system whose sample interval is a function of the target motion.
It was shown that increasing the bandwidth of the low-pass filtered Gaussian random motion resulted in an increase of the eye movement bandwidth. Some properties of the eyeball-muscle dynamics and the extraocular muscle "active state tension" were derived.