The traffic-forecasting model, when considered as a system with inputs of historical and current data and outputs of future data, behaves in a nonlinear fashion and varies with time of day. Traffic data are found to change abruptly during the transition times of entering and leaving peak periods. Accurate and real-time models are needed to approximate the nonlinear time-variant functions between system inputs and outputs from a continuous stream of training data. A proposed local linear regression model was applied to short-term traffic prediction. The performance of the model was compared with previous results of nonparametric approaches that are based on local constant regression, such as the k-nearest neighbor and kernel methods, by using 32-day traffic-speed data collected on US-290, in Houston, Texas, at 5-min intervals. It was found that the local linear methods consistently showed better performance than the k-nearest neighbor and kernel smoothing methods.
Electromuscular incapacitating devices (EMDs), such as Tasers, deliver high current, short duration pulses that cause muscular contractions and temporarily incapacitate the human subject. Some reports suggest that EMDs can kill. To help answer the question, "Can the EMD directly cause ventricular fibrillation (VF)?", ten tests were conducted to measure the dart-to-heart distance that causes VF in anesthetized pigs [mass = 64 kg +/- 6.67 standard deviation (SD)] for the most common X26 Taser. The dart-to-heart distance that caused VF was 17 mm +/- 6.48 (SD) for the first VF event and 13.7 mm +/- 6.79 (SD) for the average of the successive VF events. The result shows that when the stimulation dart is close enough to the heart, X26 Taser current will directly trigger VF in pigs. Echocardiography of erect humans shows skin-to-heart distances from 10 to 57 mm (dart-to-heart distances of 1-48 mm). These results suggest that the probability of a dart on the body landing in 1 cm2 over the ventricle and causing VF is 0.000172.
The framework of a traffic prediction model that could eliminate noise caused by random travel conditions is investigated. This model also can quantitatively calculate the influence of special factors. The framework combined several artificial intelligence technologies, such as wavelet transform, neural network, and fuzzy logic. The wavelet denoising method is emphasized and analyzed.
The maximum distance between the heart and a model Taser stimulation dart, called the dart-to-heart distance, at which the Taser can directly cause ventricular fibrillation (VF), was measured in pigs. A 9-mm-long blunt probe was advanced snugly through the surrounding tissues toward the heart. Five animals [pig mass=61.2+/-6.23 standard deviation (SD) kg] for ten dart-to-heart distances where the Taser caused VF were tested. The dart-to-heart distances where the Taser caused VF of the first stimulation site ranged from 4 to 8 mm with average 6.2 mm+/-1.79 (SD) and of the second stimulation site ranged from 2 to 8 mm with average 5.4 mm+/-2.41 (SD). The results help inform the evolving discussion of risks associated with Tasers.
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