830 resultados para AUTOMATED DOCKING


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Con il seguente documento si vuole esaminare l'utilita trasportistica dei sistemi di trasporto del tipo Automated People Mover passando da un inquadramento storico generale all'uso dei sistemi nell'ambito aeroportuale dall'inizio degli anni '60 fino ai tempi piu moderni. Dopo avere analizzato le configurazioni e le caratteristiche tipiche dei sistemi APM in ambito aeroportuale si definira quale tipologia di infrastruttura e stata privilegiata negli aeroporti europei e mondiali. Successivamente si prendera in esame lo stato dell'arte dei sistemi APM installati nell'aeroporto principale di Parigi e uno dei piu trafficati del mondo, l'Aeroporto Internazionale Charles de Gaulle; e del sistema installato nell'Aeroporto Internazionale Galileo Galilei di Pisa.

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-tabletutorial- illustrates how Stata can be used to export statistical results and generate customized reports. Part 1 explains how results from Stata routines can be accessed and how they can be exported using the -file- comand or a wrapper such as, e.g., -mat2txt-. Part 2 shows how model estimation results can be archived using -estwrite- and how models can be tabulated and exported to LaTeX, MS Excel, or MS Word using -estout-. Part 3 illustrates how to set up automatic reports in LaTeX or MS Word. The tutorial is based on a talk given at CEPS/INSTEAD in Luxembourg in October 2008. After install, type -help tabletutorial- to start the tutorial (in Stata 8, type -whelp tabletutorial-). The -mat2txt-, -estwrite-, and -estout- packages, also available from SSC, are required to run the examples.

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This study was carried out to detect differences in locomotion and feeding behavior in lame (group L; n = 41; gait score ≥ 2.5) and non-lame (group C; n = 12; gait score ≤ 2) multiparous Holstein cows in a cross-sectional study design. A model for automatic lameness detection was created, using data from accelerometers attached to the hind limbs and noseband sensors attached to the head. Each cow's gait was videotaped and scored on a 5-point scale before and after a period of 3 consecutive days of behavioral data recording. The mean value of 3 independent experienced observers was taken as a definite gait score and considered to be the gold standard. For statistical analysis, data from the noseband sensor and one of two accelerometers per cow (randomly selected) of 2 out of 3 randomly selected days was used. For comparison between group L and group C, the T-test, the Aspin-Welch Test and the Wilcoxon Test were used. The sensitivity and specificity for lameness detection was determined with logistic regression and ROC-analysis. Group L compared to group C had significantly lower eating and ruminating time, fewer eating chews, ruminating chews and ruminating boluses, longer lying time and lying bout duration, lower standing time, fewer standing and walking bouts, fewer, slower and shorter strides and a lower walking speed. The model considering the number of standing bouts and walking speed was the best predictor of cows being lame with a sensitivity of 90.2% and specificity of 91.7%. Sensitivity and specificity of the lameness detection model were considered to be very high, even without the use of halter data. It was concluded that under the conditions of the study farm, accelerometer data were suitable for accurately distinguishing between lame and non-lame dairy cows, even in cases of slight lameness with a gait score of 2.5.

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Federal Highway Administration, Office of Safety and Traffic Operations, Washington, D.C.

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Mode of access: Internet.

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Mode of access: Internet.

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Turner-Fairbank Highway Research Center, Office of Safety Research and Development, McLean, Va.

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Includes bibliographical references.

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Federal Highway Administration, Washington, D.C.

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Federal Highway Administration, Washington, D.C.