Forty adult (15 months old) fat-tailed Egyptian rams and ewes of the Rahmani and Ossimi breeds were available at the Animal Breeding Research Farm, Giza, Egypt (30° N.). Body temperature and respiration rates were measured twice weekly throughout the year 1953–4. On days of observations, four readings were taken at 10 a.m., 12 noon, 2 p.m. and 4 p.m. Skin temperature was measured once weekly at noon for nine body regions, using a precision bridge thermometer. The effects of docking and pregnancy were also studied.

The structure, distribution and dimensions of skin strata and sweat glands have been investigated in Egyptian buffaloes and cattle. Samples from sixteen body regions were taken from three adult bulls of both species. Identical studies were also made on one buffalo calf and two buffalo embryos. Serial vertical and horizontal sections were cut from each body region using the ‘terpineol paraffin wax’ method. The following results were obtained.

Gaussian mixture models (GMMs) are recently employed to provide a robust technique for speaker identification. The determination of the appropriate number of Gaussian components in amodel for adequate speaker representation is a crucial but difficult problem. This number is in fact speaker dependent. Therefore, assuming a fixed number of Gaussian components for all speakers is not justified. In this paper, we develop a procedure for roughly estimating the maximum possible model order above which the estimation of model parameters becomes unreliable. In addition, a theoretical measure, namely, a goodness of fit (GOF) measure is derived and utilized in estimating the number of Gaussian components needed to characterize different speakers. The estimation is carried out by exploiting the distribution of the training data for each speaker. Experimental results indicate that the proposed technique provides results comparable to other well-known model selection criteria like the minimum description length (MDL) and the Akaike information criterion (AIC).