While it is well known that rain may influence the performance of automotive LIDAR sensors commonly used in ADAS applications, there is a lack of quantitative analysis of this effect. In particular, there is very little published work on physically-based simulation of the influence of rain on terrestrial LIDAR performance. Additionally, there have been few quantitative studies on how rain-rate influences ADAS performance. In this work, we develop a mathematical model for the performance degradation of LIDAR as a function of rain-rate and incorporate this model into a simulation of an obstacle-detection system to show how it can be used to quantitatively predict the influence of rain on ADAS that use LIDAR.

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Background: Virtual reality (VR) is becoming a widespread tool in rehabilitation, especially for postural stability. However, the impact of using VR in a “moving wall paradigm” (visual perturbation), specifically without and with anticipation of the perturbation, is unknown. Methods: Nineteen healthy subjects performed three trials of static balance testing on a force plate under three different conditions: baseline (no perturbation), unexpected VR perturbation, and expected VR perturbation. The statistical analysis consisted of a 1 × 3 repeated-measures ANOVA to test for differences in the center of pressure (COP) displacement, 95% ellipsoid area, and COP sway velocity. Results: The expected perturbation rendered significantly lower (p < 0.05) COP displacements and 95% ellipsoid area compared to the unexpected condition. A significantly higher (p < 0.05) sway velocity was also observed in the expected condition compared to the unexpected condition. Conclusions: Postural stability was lowered during unexpected visual perturbations compared to both during baseline and during expected visual perturbations, suggesting that conflicting visual feedback induced postural instability due to compensatory postural responses. However, during expected visual perturbations, significantly lowered postural sway displacement and area were achieved by increasing the sway velocity, suggesting the occurrence of postural behavior due to anticipatory postural responses. Finally, the study also concluded that VR could be used to induce different postural responses by providing visual perturbations to the postural control system, which can subsequently be used as an effective and low-cost tool for postural stability training and rehabilitation.

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To make comparative assessments of competing technologies, consistent ground rules must be applied when developing cost estimates. This document provides a uniform set of assumptions, ground rules, and requirements that can be used in developing cost estimates for advanced nuclear power technologies. 1. INTRODUCTION Several advanced power plant concepts are currently under development. These include the Modular High Temperature Oas Cooled Reactors (MHTGR), the Advanced ta Liquid Metal Reactor (ALMR) and the Advanced Light Water Reactors (ALWR). One • measure of the attractiveness of a new concept is its cost. Invariably, the cost of a new type of power plant will be compared with other alternative forms of electrical generation. This report provides a common starting point, whereby the cost estimates for the various power plants to be considered are developed with common assumptions and ground rules. Comparisons can then be made on a consistent basis. This is the second update of these cost estimate guidelines, t_ Changes have been made to make the guidelines more current (January 1, 1992) and in response to suggestions made as a result of the use of the previous report.2 The principal changes are that the reference site has been changed from a generic Northeast (Middletown) site to a more central site (EPRI's East/West Central site) and that reference bulk commodity prices and labor productivity rates have been added.This report is designed to provide a framework for the preparation and reporting of costs. The cost estimates will consist of the overnight construction cost, the total plant capital ms_ cost, the operation and maintenance (O&M) costs, the fuel costs, decommissioning costs and _. the power production or busbar generation cost. While providing a generic set of assumptions and ground rules, this document does not provide scenarios or assumptions specific to the 2 individual concepts, nor does it provide reporting requirements. Thus, these guidelines may be used in a variety of studies when supplemented with concept specific data.Power plant capital costs in this report will be developed using the U.S. Department of Energy (DOE) Energy Economic Data Base3 (EEDB) Program Code of Accounts that has evolved from the NUS Corporation Code of Accounts 4 through modification and expansion over two decades.The utilization of the EEDB Code of Accounts will allow for comparisons between the advanced concept cost estimate and costs of other plants reported it,, the EEDB format.The levelized busbar generation costs will be developed using the methodology presented in the U.S. DOE Nuclear Energy Cost Data Base (NECDB). 5 Ali costs will be developed using the methods and tax provisions in the Tax Reform Act of 1986.These ground rules will be updated as necessary to provide and maintain a common and consistent cost basis. The DOE Office of Nuclear Energy (NE) is responsible for approving changes to this document. Requested changes should be made in writing to