indicates the location of metal implants. b) Auto-calibrated SENSE (RMSE = 1037). c) SENSE with single calibration (RMSE = 3364). The arrow indicates image artifacts. d) Autocalibrated ARC (RMSE=372). e) ARC recon using single calibration (RMSE = 383). f) ARC recon using two concatenated calibration data sets (RMSE = 364). Figure 3: a) Fast spin-echo image. b) Fully sampled MAVRIC image c)Under...

This study was conducted to assess the ability of the VCS2001 (E+V, Oranienburg, Germany) video image analysis system to predict pork carcass composition. Pork carcasses (n = 278) were selected from a commercial packing plant to differ in weight, Fat-O-Meater (FOM) predicted percentage lean, and gender. Carcasses were imaged three times with the VCS2001, chilled overnight, and then sequentially...

Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be a misleading indicator of average error, and thus the MAE would be a better metric for that purpose. While some concerns over using RMSE raised by W...

This paper describes the participation of the CAPS-PRC system developed at the LMU Munich in the personality recognition shared task (PR-SOCO) organized by PAN at the FIRE16 Conference. The machine learning system uses the output of a Java code analyzer to investigate the structure of a given program, its length, its average variable length and also it takes into account the comments a given pr...

OBJECTIVE To evaluate the accuracy of body mass index (BMI) as a predictor of body fat in elderly women. RESEARCH METHODS AND PROCEDURES A total of 1423 women aged 67 +/- 5 (mean +/- SD, range: 60 to 88) years were consecutively enrolled into the study. Fat mass (FM) was measured using DXA. RESULTS BMI explained 72.9% of FM variance (p < 0.0001), with a root mean square error of estimate (R...

We evaluated the accuracy of skinfold thicknesses, BMI and waist circumference for the prediction of percentage body fat (PBF) in a representative sample of 372 Swiss children aged 6-13 years. PBF was measured using dual-energy X-ray absorptiometry. On the basis of a preliminary bootstrap selection of predictors, seven regression models were evaluated. All models included sex, age and pubertal ...