Evaluation Of Retesting in Kentucky\u27s Driver License Process

The objectives of this research were to first evaluate the existing practices regarding driver license renewal, driver retesting, and medical review board procedures and then identify and recommend methods that would improve these processes. The analysis of the Medical Review Board process indicated that, while it operates at an acceptable level in major urban areas, it is almost non-existent in most areas of the state. A brochure describing the process was developed for distribution to physicians. There is a universal agreement among researchers that vision has a significant role in driving performance and that visual abilities deteriorate with age. It is apparent that some type of vision screening should be implemented during the renewal process since it could identify individuals with potential deficiencies. Such screening could be achieved either with a test during the license renewal or with an eye exam prior to license renewal. In addition to the testing, a policy that identifies potential at-risk drivers should be considered. The combination of convictions (points) and crashes was considered as an appropriate means to distinguish such drivers. Special consideration should be given for older drivers at driver license renewal. In addition to the vision screening, a written test could be administered at license renewal along with a set of medical questions to determine their physical and mental status

REVIEWING THE ROOTS OF RESPONSE TO INTERVENTION:IS THERE ENOUGH RESEARCH TO SUPPORT THE PROMISE?

In the United States, Response to Intervention (RtI) is used to promote the use of evidence-based instruction in educational institutions, with the goal of supporting general and specialized educators and enabling these professionals to work together in a comprehensive, integrated manner. In doing so, RtI provides a protocol for identifying students with specific academic deficits and who demonstrate the need for individualized forms of instruction. Specifically, professional educators utilize quantitative data accumulated from common student assessment scores, which is thought to reflect a student’s response to instruction in the general classroom, in addition to his or her response to more targeted forms of intervention. This article presents a conceptual overview of RtI and discusses key dimensions most salient to its development and implementation within the United States, while carefully reviewing the research supporting the effectiveness of this multi-tiered framework. As RtI gains prominence in other countries, this article serves to educate others on what may well become a more universal response to intervention

Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

Automated data-driven decision making systems are increasingly being used to assist, or even replace humans in many settings. These systems function by learning from historical decisions, often taken by humans. In order to maximize the utility of these systems (or, classifiers), their training involves minimizing the errors (or, misclassifications) over the given historical data. However, it is quite possible that the optimally trained classifier makes decisions for people belonging to different social groups with different misclassification rates (e.g., misclassification rates for females are higher than for males), thereby placing these groups at an unfair disadvantage. To account for and avoid such unfairness, in this paper, we introduce a new notion of unfairness, disparate mistreatment, which is defined in terms of misclassification rates. We then propose intuitive measures of disparate mistreatment for decision boundary-based classifiers, which can be easily incorporated into their formulation as convex-concave constraints. Experiments on synthetic as well as real world datasets show that our methodology is effective at avoiding disparate mistreatment, often at a small cost in terms of accuracy.Comment: To appear in Proceedings of the 26th International World Wide Web Conference (WWW), 2017. Code available at: https://github.com/mbilalzafar/fair-classificatio

ENHANCED GROWTH RATE AND SILANE UTILIZATION IN AMORPHOUS SILICON AND NANOCRYSTALLINE-SILICON SOLAR CELL DEPOSITION VIA GAS PHASE ADDITIVES

Air Products set out to investigate the impact of additives on the deposition rate of both ÃÂõCSi and ÃÂñSi-H films. One criterion for additives was that they could be used in conventional PECVD processing, which would require sufficient vapor pressure to deliver material to the process chamber at the required flow rates. The flow rate required would depend on the size of the substrate onto which silicon films were being deposited, potentially ranging from 200 mm diameter wafers to the 5.7 m2 glass substrates used in GEN 8.5 flat-panel display tools. In choosing higher-order silanes, both disilane and trisilane had sufficient vapor pressure to withdraw gas at the required flow rates of up to 120 sccm. This report presents results obtained from testing at Air ProductsâÃÂàelectronic technology laboratories, located in Allentown, PA, which focused on developing processes on a commercial IC reactor using silane and mixtures of silane plus additives. These processes were deployed to compare deposition rates and film properties with and without additives, with a goal of maximizing the deposition rate while maintaining or improving film properties

HST Observations of the Host Galaxies of BL Lacertae Objects

Six BL Lac objects from the complete 1 Jy radio-selected sample of 34 objects were observed in Cycle 5 with the HST WFPC2 camera to an equivalent limiting flux of mu_I~26 mag/arcsec^2. Here we report results for the second half of this sample, as well as new results for the first three objects, discussed previously by Falomo et al. (1997). In addition, we have analyzed in the same way HST images of three X-ray-selected BL Lacs observed by Jannuzi et al. (1997). The ensemble of 9 BL Lac objects spans the redshift range from z=0.19 to ~1. Host galaxies are clearly detected in seven cases, while the other two, at z~0.258 (redshift highly uncertain) and z=0.997, are not resolved. The HST images constitute a homogeneous data set with unprecedented morphological information between a few tenths of an arcsecond and several arcseconds from the nucleus, allowing us in 6 of the 7 detected host galaxies to rule out definitively a pure disk light profile. The host galaxies are luminous ellipticals with an average absolute magnitude of M_I~-24.6 mag (with dispersion 0.7 mag), more than a magnitude brighter than L* and comparable to brightest cluster galaxies. The morphologies are generally smooth and have small ellipticities (epsilon<0.2). Given such roundness, there is no obvious alignment with the more linear radio structures. In the six cases for which we have HST WFPC2 images in two filters, the derived color profiles show no strong spatial gradients and are as expected for K-corrected passively evolving elliptical galaxies. The host galaxies of the radio-selected and X-ray-selected BL Lacs for this very limited sample are comparable in both morphology and luminosity.Comment: 23 pages, including 6 postscript figures and 3 tables (embedded). Latex requires aaspp4.sty and psfig.sty (not included). Accepted for publication in the Astrophysical Journa

Snow information is required in subcontinental scale predictions of mountain plant distributions

Aim To examine how snow cover and permafrost affect plant species distributions at a subcontinental extent. Location Mountain realm of Fennoscandia, northern Europe. Time period Species data from 1 January 1990-25 February 2019. Major taxa studied Arctic-alpine and boreal vascular plants. Methods We examined the effect of snow persistence and permafrost occurrence on the distributions of arctic-alpine and boreal plant species while controlling for climate, topography and geological factors. Data comprised 475,811 observations from 671 species in the Fennoscandian mountains. We investigated the relationships between species distributions and environmental variables using four modelling methods and ensemble modelling building on both non-spatial and spatial models. Results Snow persistence was the most important driver of plant species distributions, with the greatest variable importance for both arctic-alpine (38.2%) and boreal (49.9%) species. Permafrost had a consistent minor effect on the predicted distributions. Arctic-alpine plants occur in areas with long snow persistence and permafrost, whereas boreal species showed the opposite habitat preferences. Main conclusions Our results highlight the importance of snow persistence in driving the distribution of vascular plant species in cold environments at a subcontinental scale. The notable contribution of the cryosphere to plant species distribution models indicates that the inclusion of snow information in particular may improve our understanding and model predictions of biogeographical patterns in cold regions.Peer reviewe

Comparing ultra-high spatial resolution remote-sensing methods in mapping peatland vegetation

Peer reviewe