TL;DR: In this article, the authors present a methodology for estimating the Time of Emergence (ToE) for individual climate models, and use it to make maps of ToE for surface air temperature (SAT) based on the CMIP3 global climate models.
Abstract: [1] The time at which the signal of climate change emerges from the noise of natural climate variability (Time of Emergence, ToE) is a key variable for climate predictions and risk assessments. Here we present a methodology for estimating ToE for individual climate models, and use it to make maps of ToE for surface air temperature (SAT) based on the CMIP3 global climate models. Consistent with previous studies we show that the median ToE occurs several decades sooner in low latitudes, particularly in boreal summer, than in mid-latitudes. We also show that the median ToE in the Arctic occurs sooner in boreal winter than in boreal summer. A key new aspect of our study is that we quantify the uncertainty in ToE that arises not only from inter-model differences in the magnitude of the climate change signal, but also from large differences in the simulation of natural climate variability. The uncertainty in ToE is at least 30 years in the regions examined, and as much as 60 years in some regions. Alternative emissions scenarios lead to changes in both the median ToE (by a decade or more) and its uncertainty. The SRES B1 scenario is associated with a very large uncertainty in ToE in some regions. Our findings have important implications for climate modelling and climate policy which we discuss.
TL;DR: In this article, a steering system for vehicles in which the steered angle ratio of a rear wheel to a front wheel is controllable in accordance with the vehicle speed is presented.
Abstract: A steering system for vehicles in which the steered angle ratio of a rear wheel to a front wheel is controllable in accordance with the vehicle speed. The steering system is provided with a manual switch device for selecting to set an arbitrary one of a plurality of predetermined steered angle ratios. The steering system may be further provided with a switch lock device for locking the switch state of the manual switch device. The switch lock device may be actuated when the vehicle speed is higher than a predetermined reference vehicle speed. Further, the switch lock device may be actuated when a reduction gear is shifted to a shift position having a relatively low reduction ratio. The switch lock device may also be actuated when the steered angle of the front wheel is larger than a predetermined value.
TL;DR: In this article, a total of 128 fillet welded specimens were re-analysed by using an energy-based Notch Stress Intensity Factor (N-SIF) approach and the local weld toe geometry, characterised by its angle and radius, was measured with accuracy for the actual test series.
Abstract: In the Notch Stress Intensity Factor (N-SIF) approach the weld toe region is modelled as a sharp V-shaped corner and local stress distributions in planar problems can be expressed in closed form on the basis of the relevant mode I and mode II N-SIFs. Initially thought of as parameters suitable for quantifying only the crack initiation life, N-SIFs were shown able to predict also the total fatigue life, at least when a large part of the life is spent as in the propagation of small cracks in the highly stressed region close to the notch tip. While the assumption of a welded toe radius equal to zero seems to be reasonable in many cases of practical interest, it is well known that some welding procedures are able to assure the presence of a mean value of the weld toe radius substantially different from zero. Under such conditions any N-SIF-based prediction is expected to underestimate the fatigue life. In order to investigate the degree of conservatism, a total of 128 fillet welded specimens are re-analysed in the present work by using an energy-based N-SIF approach. The local weld toe geometry, characterised by its angle and radius, has been measured with accuracy for the actual test series. The aim of the work is to determine if the N-SIF-based model is capable of taking into account the large variability of the toe angle, and to quantify the inaccuracy in the predictions due to the simplification of setting the toe radius equal to zero.
TL;DR: In this article, the turning angle of the rear wheels is controlled in accordance with a turning angle ratio characteristic curve defined on a θF-θR plane, where θ and θR respectively represent the turning angles of the front and rear wheels.
Abstract: In the four-wheeled vehicle, both the front and rear wheels are turned in response to operation of the steering wheel. The turning angle of the rear wheels is controlled in accordance with a turning angle ratio characteristic curve defined on a θF-θR plane wherein θF and θR respectively represent the turning angles of the front and rear wheels. The turning angle ratio characteristic curve is substantially a broken line having a positive inclination in the region where the value of the front wheel turning angle θF is smaller than a predetermined value and having a smaller inclination in the region where the value of the front wheel turning angle θF is larger than the predetermined value. The turning angle ratio characteristic curve is changed according to the vehicle speed so that the turning angle ratio θR/θF is increased as the vehicle speed increases.
TL;DR: The proposed detection method is mainly based on Principal Component Analysis (PCA) for feature generation and Support Vector Machine (SVM) for multi-pattern classification and demonstrates that the proposed approach is robust and efficient in detecting abnormal gait patterns.
Abstract: In this paper we introduce a shoe-integrated system for human abnormal gait detection. This intelligent system focuses on detecting the following patterns: normal gait, toe in, toe out, oversupination, and heel walking gait abnormalities. An inertial measurement unit (IMU) consisting of three-dimensional gyroscopes and accelerometers is employed to measure angular velocities and accelerations of the foot. Four force sensing resistors (FSRs) and one bend sensor are installed on the insole of each foot for force and flexion information acquisition. The proposed detection method is mainly based on Principal Component Analysis (PCA) for feature generation and Support Vector Machine (SVM) for multi-pattern classification. In the present study, four subjects tested the shoe-integrated device in outdoor environments. Experimental results demonstrate that the proposed approach is robust and efficient in detecting abnormal gait patterns. Our goal is to provide a cost-effective system for detecting gait abnormalities in order to assist persons with abnormal gaits in the developing of a normal walking pattern in their daily life.