Selection Of Appropriate Threshold Research Articles

Strong Linkage Between Observed Daily Precipitation Extremes and Anthropogenic Emissions Across the Contiguous United States

AbstractThe results of probabilistic event attribution studies depend on the choice of the extreme value statistics used in the analysis, particularly with the arbitrariness in the selection of appropriate thresholds to define extremes. We bypass this issue by using the Extended Generalized Pareto Distribution (ExtGPD), which jointly models low precipitation with a generalized Pareto distribution and extremes with a different Pareto tail, to conduct daily precipitation attribution across the contiguous United States (CONUS). We apply the ExtGPD to 12 general circulation models from the Coupled Model Intercomparison Project Phase 6 and compare counterfactual scenarios with and without anthropogenic emissions. Observed precipitation by the Climate Prediction Center is used for evaluating the GCMs. We find that greenhouse gases rather than natural variability can explain the observed magnitude of extreme daily precipitation, especially in the temperate regions. Our results highlight an unambiguous linkage of anthropogenic emissions to daily precipitation extremes across CONUS.

Topical pharmacokinetics of brinzolamide suspensions in rabbits and variability analysis for sample size and design considerations

Identifying critical attributes for complex locally acting ophthalmic formulations and establishing in vitro-in vivo correlations can facilitate selection of appropriate thresholds for formulation changes that reflect lack of impact on in vivo performance. In this study the marketed antiglaucoma product Azopt® (1% brinzolamide suspension) and five other brinzolamide formulations varying in particle size distributions and apparent viscosities were topically administered in rabbits, and their ocular pharmacokinetics was determined in multiple ocular tissues. Statistical evaluation with ANOVA showed no significant differences between the formulations in the peak drug concentration (Cmax) in the aqueous humor and iris-ciliary body. As a post-hoc analysis, the within animal and total variability was determined for Cmax in the aqueous humor and iris-ciliary body. Based on the observed variability, we investigated the sample size needed for two types of study designs to observe statistically significant differences in Cmax. For the sample size calculations, assuming both 25% and 50% true differences in Cmax between two formulations, two study designs were compared: paired-eye dosing design (one formulation in one eye and another formulation in the other eye of the same animal at the same time) versus parallel-group design. The number of rabbits needed in the paired-eye dosing design are much lower than in the parallel-group design. For example, when the true difference in aqueous humor Cmax is 25%, nine rabbits are required in the paired-eye design versus seventy rabbits (35 per treatment) in the parallel-group design to observe a statistically significant difference with a power of 80%. Therefore, the proposed paired-eye dosing design is a viable option for the design of pharmacokinetic studies comparing ophthalmic products to determine the impact of formulation differences.

Differences between accelerometer cut point methods among midlife women with cardiovascular risk markers.

Midlife women experience elevated risk for cardiovascular disease and often receive advice to increase physical activity to mitigate this risk. Use of accelerometers to measure ambulatory physical activity requires selection of appropriate thresholds for estimating moderate-to-vigorous physical activity (MVPA), and choice of cut points may lead to meaningfully different conclusions about midlife women's physical activity (PA) engagement. This is particularly important given the recent elimination of 10-minute bout requirements for MVPA. This two-phase study examined differences between four cut point methods among midlife women with cardiovascular disease (CVD) risk. We used findings from Study 1 (exploratory) to generate hypotheses for Study 2 (confirmatory). Across studies, participants (N = 65) were midlife women with an additional CVD risk factor (eg, hypertension). Participants wore waistband accelerometers for seven days. Daily totals were calculated for minutes in light and MVPA using four common quantification methods (Freedson, Matthews, Swartz, and Troiano). Multilevel models showed meaningful differences between methods (P < 0.0001). For total (non-bouted) minutes of MVPA, Freedson and Troiano methods showed that participants barely met MVPA recommendations (30 min per day), whereas Matthews and Swartz methods showed that participants greatly exceeded this goal. As differences between methods were smaller using MVPA bouts of 10 minutes or more (though remained significant), the observed variation was due in part to small bursts of MVPA dispersed throughout the day. Findings demonstrate the need for careful consideration of PA quantification among midlife women with CVD risk, and for further investigation to determine the most appropriate quantification method. : Video Summary:http://links.lww.com/MENO/A545.

Impact of Metric Selection on Wireless DeAuthentication DoS Attack Performance

DeAuthentication Denial of Service attacks in Public Access WiFi operate by exploiting the lack of authentication of management frames in the 802.11 protocol. Detection of these attacks rely almost exclusively on the selection of appropriate thresholds. In this work the authors demonstrate that there are additional, previously unconsidered, metrics which also influence DoS detection performance. A method of systematically tuning these metrics to optimal values is proposed which ensures that parameter choices are repeatable and verifiable.

An expert system based on fuzzy entropy for automatic threshold selection in image processing

In pattern recognition and image processing, the selection of appropriate threshold is a very significant issue. Especially, the selecting gray-level thresholds is a critical issue for many pattern recognition applications. Here, the maximum fuzzy entropy and fuzzy c-partition methods are used for the aim of the gray-level automatic threshold selection method. The fuzzy theory has been successfully applied to many areas, such as image processing, pattern recognition, computer vision, medicine, control, etc. The images have some fuzziness in nature. In this study, expert maximum fuzzy-Sure entropy (EMFSE) method for the maximum fuzzy entropy and fuzzy c-partition processes in automatic threshold selection is proposed. The experimental studies were conducted on many images by testing maximum fuzzy-Sure entropy against maximum fuzzy-Shannon entropy (MFSHE), maximum fuzzy-Havrada and Charvat entropy (MFHCE) methods for selecting optimum 2-level threshold value, respectively. The obtained experimental results show that the used MFSE method is superior to other MFSHE and MFHCE methods on selecting the 2-level threshold value automatically and effectively.