Two -s-udies-were conducted in which five simulated aircraft attitude indicators,,representing three different indicating principles, were compared.Tw6v*,dicators were of the "earth reference" type, in mhich the moving element repres'ented the horizon as on the conventionalAatititude indioator. Two indicators were of an "airplane reference" type, which presented aircraft rather than horizon movement.Thqe fjfth indicator provided a "stabilized sphere" type of ýpresentatidn,. Tests Vere miad4 in a C-9 Link Trainer and records were performanceflight maneuvers reversals~following sifolotednrorgh iir gusti, anda pilot preferences.Major interest centered around comparison of the "earth reference" and "airplane reference" principles of attitude indication, since these provide opposite directions of movement on the indicator.Each of the five indicators was flown kry Air Force pilots, eight different pilots per instrument.In-additon, itwo indicators representing the two opposed types, were flown by college students with no prior flight experience.The Air Force pilots used in this study were highly experienced on the earth reference type of indicator, and had not previously flown indicators using the airplane reference principle. For this reason, apparently, they made more aileron reversals on the airplane reference type indicators. In the pitch dimension, however, t,)ey made slightly, but not significantly, fewer control reversals o4 thes'e/ idicators. Moreover, their preferences somewhat favored the unfamiliar airplane reference indicators.For the college students, both the control reversal and preference data favored the airplane reference principle. PUBLICATION REVIEW(This report has been reviewed and is approved.

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Building energy signature analysis is a well-established tool for understanding the temperature sensitivity of building energy consumption and measuring energy savings. This tool has been used to measure energy savings of residential, commercial, and even industrial buildings. The public availability of electricity loads (i.e., hourly electricity demand (MW)) from entire Balancing Authorities (BAs) provide an interesting opportunity to apply this approach to a large aggregate load. In this paper, we explore that opportunity for BAs and show that the correlations for large geographical areas are surprisingly coherent when the change-point linear regression analysis is used with the daily interval data of electricity demand and outside air temperature. The change-point linear regression models of all the BAs, except WAUW and OVEC, show R2 of 0.70 or more and CV-RMSE of 10.0% or less. We also suggest an analysis method that allows for meaningful comparisons between BAs and to assess changes in time for a given BA which could be used to interpret changes in load patterns year-to-year, accounting for changes in weather. This approach can be used to verify the impact of energy efficiency programs on a building component/system-wide basis. This study shows the annual electricity demand reductions for SCL and IPCO are 136,655 MWh (1.5%) and 182,053 MWh (1.1%), respectively.