Using kinematic driving data to detect sleep apnea treatment adherence

People spend a significant amount of time behind the wheel of a car. Recent advances in data collection facilitate continuously monitoring this behavior. Previous work demonstrates the importance of this data in driving safety but does not extended beyond the driving domain. One potential extension of this data is to identify driver states related to health conditions such as obstructive sleep apnea (OSA). We collected driving data and medication adherence from a sample of 75 OSA patients over 3.5 months. We converted speed and acceleration behaviors to symbols using symbolic aggregate approximation and converted these symbols to pattern frequencies using a sliding window. The resulting frequency data was matched with treatment adherence information. A random forest model was trained on the data and evaluated using a held-aside test dataset. The random forest model detects lapses in treatment adherence. An assessment of variable importance suggests that the important patterns of driving in classification correspond to route decisions and patterns that may be associated with drowsy driving. The success of this approach suggests driving data may be valuable for evaluating new treatments, analyzing side effects of medications, and that the approach may benefit other drowsiness detection algorithms.     

Low-fi simulation of bridge team communication

The paper compares the pedagogical advantages of two simulation types used for training verbal maritime communication. It tests the hypothesis that “low-fi” simulation using online web conference software, specifically ‘chat’ or messaging, is a valid complementary tool for the instruction of Maritime English and full-mission simulation. Based on a series of exercises involving multi-national and multi-lingual students, various linguistic patterns are determined and compared to audio recordings of full-mission simulation. Probability of superiority effect sizes is computed to quantify the observed effects. The findings corroborate the proximity of language patterns found in low-fi and full-mission simulation. Pedagogical implications are discussed, and future research possibilities are outlined.     

Efficiency measurement of bus routes and exogenous operating environment effects on efficiency

This study develops an independent efficiency measurement model framework of bus routes, so as to treat preferably the heterogeneous outputs in a data envelopment analysis (DEA)-based efficiency measurement. It then introduces four new exogenous operating environment factors at the microscopic level of bus routes, and applies the three-stage DEA approach to incorporate operating environment effects and statistical noise into the efficiency measurement framework. The main purpose is to measure impartially the managerial efficiency of bus routes, purged of operating environment effects and statistical noise, and additionally to investigate the operating environment effects on efficiency. An empirical analysis, based on 39 routes operated in Jiangyin City, China, is presented. The principal finding is that the adoption of the independent efficiency measurement model framework is reasonable and has many virtues. Moreover, the proposed approach could substantially provide decision support both for regulators and for producers of bus services. In addition, the operating environment does indeed significantly affect operating efficiency and quality efficiency, especially the latter.     

The evolution of U.S. rail freight pricing in the post-deregulation era: revenues versus marginal costs for five commodity types

There have now been over three decades of experience with rate-making freedom for all modes of intercity freight transport in the United States. Most evidence suggests that regulatory change has been beneficial for the rail industry and its users. Despite evidence of positive impacts of regulatory reform of U.S. freight transport, there is limited evidence related to long-term pricing trends by commodity in the deregulated era. Moreover, U.S. shipper groups have called for increased regulation of U.S. railroads, citing increased rates and profits, and monopoly pricing to “captive shippers.” This study estimates U.S. railroad revenue-marginal cost ratios for seven different commodities between 1986 and 2008. Interestingly, we find no significant increase in revenue-cost margins for commodities thought to be “most captive” (coal and chemicals), while finding large increases for some commodities thought to be “non-captive.” These results may provide insight into the impacts of regulatory reform in other countries, where there are similar concerns of equitable pricing and financial viability. They suggest that a move toward a more market-based pricing system can enhance railroad viability without harming those with fewer transport options.     

Accuracy of nonlinear finite element collapse predictions for submarine pressure hulls with and without artificial corrosion damage

Nonlinear finite element (FE) collapse pressure predictions are compared to experimental results for submarine pressure hull test specimens with and without artificial corrosion and tested to collapse under external hydrostatic pressure. The accuracy of FE models, and their sensitivity to modeling and solution procedures, are investigated by comparing FE simulations of the experiments using two different model generators and three solvers. The standard FE methodology includes the use of quadrilateral shell elements, nonlinear mapping of measured geometric imperfections, and quasi-static incremental analyses including nonlinear material and geometry. The FE models are found to be accurate to approximately 11%, with 95% confidence, regardless of the model generator and solver that is used. Collapse pressure predictions for identical FE models obtained using each of the three solvers agree within 2.8%, indicating that the choice of FE solver does not significantly affect the predicted collapse pressure. The FE predictions are found to be more accurate for corroded than for undamaged models, and neglecting the shell eccentricity that arises due to one-sided shell thinning is found to significantly decrease the resulting accuracy of the FE model.