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ABSTRACT: This paper presents the results of a study funded by Transport Canada to investigate the safety implications of mandated truck speed limiters. The study adopted a microscopic simulation approach that was applied to a number of maximum speed control strategies, including 105 km/h. The sensitivity of safety performance with respect to changes in geometric and traffic scenarios was investigated. The study found that truck speed limiters produced positive safety gains for different assumed volumes and percentages of trucks and different compliance levels. Under certain conditions, such as high volumes and high percentage of trucks, speed limiters produced a reduction in safety.
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ABSTRACT: Objectives: Evidence suggests that age at smoking initiation has implications for tobacco use, nicotine dependence, and resulting long-term health and chronic disease outcomes. The objective of the current study was to examine two different measures of smoking onset and to compare their validity in predicting future adolescent smoking survey. Methods: Data from grades 9-12 students who participated in the 2012/2013 Youth Smoking Survey, a nationally-generalizable Canadian survey, and who had ever tried a cigarette, even a few puffs (n = 8126) were used in a multivariable logistic regression analysis to examine the association between age at smoking onset and current smoking behavior. Results: Both "age at first puff" and "age at first whole cigarette" were significantly associated with current smoking status. Specifically, a delay of one year in the age at first puff was associated with lower odds of being a current smoker by 24% (AOR = 0.76, 95% CI = 0.73-0.79). Similarly, high school students who smoked their first whole cigarette at old age were less likely to report being a current smoker (AOR = 0.66, 95% CI = 0.62-0.71). Conclusion: Efforts to prevent smoking uptake among youth, especially younger youth, are especially important in tobacco control efforts.
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ABSTRACT: The power cost of running a data center is a significant portion of its total annual operating budget. With the aim of reducing power bills of data centers, “Green Computing” has emerged with the primary goal of making software more energy efficient without compromising the performance. Developers play an important role in controlling the energy cost of data center software while writing code. In this paper, we show how software developers can contribute to energy efficiency of servers by choosing energy efficient APIs (Application Programming Interface) with the optimal choice of parameters while implementing file reading, file copy, file compression and file decompression operations in Java; that are performed extensively on large scale servers in data centers. We performed extensive measurements of energy cost of those operations on a Dell Power Edge 2950 machine running Linux and Windows servers. Measurement results show that energy costs of various APIs for those operations are sensitive to the buffer size selection. The choice of a particular Java API for file reading with different buffer sizes has significant impact on the energy cost, giving an opportunity to save up to 76%. To save energy while copying files, it is important to use APIs with tunable buffer sizes, rather than APIs using fixed size buffers. In addition, there is a trade off between compression ratio and energy cost: because of more compression ratio, xz compression API consumes more energy than zip and gzip compression APIs. Finally, we model the energy costs of APIs by polynomial regression to avoid repeated measurements.
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