Past researches that evaluated hip fracture risk had focused on sideways falls, while backward falls were also reported to cause as many hip fractures as the sideways falls do. To understand the mechanism of hip fracture during a backward fall, we conducted fall simulations using a "Multi-body and Finite-element Coupled Human Model". This model was effective and efficient in simulating both the kinematic behavior of the whole body and the stress distribution around the femoral neck simultaneously and in evaluating hip fracture risk resulting from the fall. In the simulations, the lateral area of the greater trochanter contacted the floor in the sideways fall, and the proximal top of the greater trochanter contacted the floor in the backward fall with the upper body tilted laterally. In the backward fall, the impact velocity and the contact force with the floor were low. However, as the geometrical relationship among the femur, hip joint, and pelvis made the contact force work more efficiently, the shearing force and the torsional moment in the femoral neck were large and the maximum values of each stress were the same or higher as compared to that of the sideways fall. Besides, the pubic rami are likely to break and thereby prevent a femoral neck fracture in the sideways fall, but not while in the backward fall. This result shows that the risk of a hip fracture in the backward fall is the same or even higher than that in the sideways fall.
Abstract Techniques for predicting the trajectory of vulnerable road users are important to the development of perception systems for autonomous vehicles to avoid accidents. The most effective trajectory prediction methods, such as Social-LSTM, are often used to predict pedestrian trajectories in normal passage scenarios. However, they can produce unsatisfactory prediction results and data redundancy, as well as difficulties in predicting trajectories using pixel-based coordinate systems in collision avoidance systems. There is also a lack of validations using real vehicle-to-pedestrian collisions. To address these issues, some insightful approaches to improve the trajectory prediction scheme of Social-LSTM were proposed, such methods included transforming pedestrian trajectory coordinates and converting image coordinates to world coordinates. The YOLOv5 detection model was introduced to reduce target loss and improve prediction accuracy. The DeepSORT algorithm was employed to reduce the number of target transformations in the tracking model. Image Perspective Transformation (IPT) and Direct Linear Transformation (DLT) theories were combined to transform the coordinates to world coordinates, identifying the collision location where the accident could occur. The performance of the proposed method was validated by training tests using MS COCO (Microsoft Common Objects in Context) and ETH/UCY datasets. The results showed that the target detection accuracy was more than 90% and the prediction loss tends to decrease with increasing training steps, with the final loss value less than 1%. The reliability and effectiveness of the improved method were demonstrated by benchmarking system performance to two video recordings of real pedestrian accidents with different lighting conditions.
Multielement oscillators with a quasi-optical resonator are reported. The resonator consists of a Fabry-Perot cavity with a grooved mirror (grating) and a concave mirror. It is possible to mount solid-state devices (Gunn diode, GaAs MESFET, etc.) in the grooved mirror. The oscillator has the capability for power-combining of solid-state sources in the millimeter- and submillimeter-wave regions.< >
The 19 papers in this special issue on terahertz technology span a range of new interests in terahertz devices, components, instruments, and applications.
The aim of this study was to clarify the pattern of child pedestrian injury, injury severity, and its relation to collision velocity in bonnet-type-vehicle collision.In-depth data were retrospectively collected from the Institute for Traffic Accident Research and Data Analysis on pedestrians younger than 13 years old with any bodily injuries from collisions with bonnet-type vehicles between 1993 and 2004.Forty-seven patients from 43 collisions with a mean age of 6.9 ± 2.5 years were included in the study. Injury severity was not significantly different between patients who were hit by the front of the vehicle and those who were hit by the side of the vehicle. In front collisions, impact with the vehicle was associated with significantly higher Abbreviated Injury Scale (AIS) scores than those for impact with the road, especially for the lower extremities (mean: 1.2 vs 0.2, P < 0.001). Injury severity of the lower extremities and collision velocity were examined. The estimated collision velocity of the vehicle was not significantly different between patients with lower extremity AIS scores of 0 or 1 and those of 2 or 3.Some pediatric pedestrians suffer from collisions with bonnet-type vehicles without lower extremity fractures owing to the characteristics of child pedestrians. Providing injury prevention programs for children in communities and schools, developing active safety devices in the vehicle, and modifying the vehicle body to a pediatric pedestrian-friendly structure may increase pedestrian protection.
In this paper, we present the development of an advanced MMIC receiver for a 94-GHz band passive millimeter-wave (PMMW) imager. Our configuration is based on a Dicke receiver in order to reduce fluctuations in the detected voltage. By introducing an electronic switch in the MMIC, we achieved a high resolution millimeter-wave image in a shorter image collection time compared to that with a conventional mechanical chopper. We also developed an imaging array using MMIC receivers.
