Time and Space Optimal Data Parallel Volume Rendering Using Permutation Warping

In this paper we present a data parallel volume rendering algorithm that possesses numerous advantages over prior published solutions. Volume rendering is a three-dimensional graphics rendering algorithm that computes views of sampled medical and simulation data, but has been much slower than other graphics algorithms because of the data set sizes and the computational complexity. Our algorithm usespermutation warpingto achieve linear speedup (run time is O(S/P) forPprocessors whenP\= O(S/logS) forS\=n³samples), linear storage (O(S)) for large data sets, arbitrary view directions, and high-quality filters. We derived a new processor permutation assignment of five passes (our prior known solution was eight passes), and a new parallel compositing technique that is essential for scaling linearly on machines that have more processors than view rays to process (P>n²). We show a speedup of 15.7 for a 16k processor over a 1k processor MasPar MP-1 (16 is linear) and two frames/second with a 128³volume and trilinear view reconstruction. In addition, we demonstrate volume sizes of 256³, constant run time over angles 5 to 75°, filter quality comparisons, and communication congestion of just 19 to 29\%.     

Discovering Robust Knowledge from Databases that Change

Many applications of knowledge discovery and data mining such as rule discovery for semantic query optimization, database integration and decision support, require the knowledge to be consistent with the data. However, databases usually change over time and make machine-discovered knowledge inconsistent. Useful knowledge should be robust against database changes so that it is unlikely to become inconsistent after database updates. This paper defines this notion of robustness in the context of relational databases and describes how robustness of first-order Horn-clause rules can be estimated. Experimental results show that our estimation approach can accurately identify robust rules. We also present a rule antecedent pruning algorithm that improves the robustness and applicability of machine discovered rules to demonstrate the usefulness of robustness estimation.     

Confounding Effect of Flow on Estuarine Response to Nitrogen Loading

The total maximum daily load (TMDL) concept provides the basis for regulating pollution load from riverine sources to impaired water bodies. However, load is comprised of two components: flow and concentration. These two components may have confounding, or even conflicting, effects on waterbody attributes of concern. This is particularly the case for dynamic, advective systems, such as estuaries. Resolving these components is critical for properly predicting the response of impaired systems to watershed management actions. The Neuse River Estuary in North Carolina is an example of such an impaired system. Nitrogen has been identified as the pollutant of concern, and the process of developing a TMDL for nitrogen is underway. We, therefore, analyze the extensive data that have been collected for the Neuse River and estuary to investigate spatiotemporal relationships between river flow, riverine total nitrogen (TN) inputs, water temperature, dissolved inorganic nitrogen concentration, algal density, and primary productivity. Results support the belief that phytoplankton in the estuary are under substantial riverine control. However, the riverine TN concentration alone has only a minor role in determining estuarine chlorophyll concentration. River flow has a stronger influence, likely through its effects on down-estuary nitrogen delivery, residence time, salinity, and turbidity. These results imply that using riverine nitrogen load as the metric to evaluate watershed nutrient management may not be appropriate. While nitrogen controls should reduce loads in the long term, in the short term, river flow is the dominant component of load and has the opposite effect of nitrogen on algae at the up-estuary locations.     

Reliability-Based Design for Internal Stability of Mechanically Stabilized Earth Walls

A parametric study was conducted using Monte Carlo simulation to assess how uncertainty in design parameters affects the probability of internal failure of mechanically stabilized earth (MSE) walls. Bishop’s simplified method was used to conduct the internal stability analyses. The results of the analyses indicate that the mean and coefficient of variation of the backfill friction angle, mean and coefficient of variation of the tensile strength of reinforcement, mean unit weight of the backfill, mean surcharge, mean reinforcement vertical spacing, and mean reinforcement length have a significant effect on the probability of internal failure of MSE walls. Based on the results of the parametric study, a series of additional simulations were conducted where the significant parameters were varied over a broad range. The results of these simulations were used to develop a set of reliability-based design (RBD) charts for internal stability of MSE walls. A method to adapt these charts to address model bias and model uncertainty is also presented. A MSE wall was designed using the RBD method and two other deterministic design methods. The required tensile strength of the reinforcement obtained from the RBD method fell between the strengths determined from the deterministic methods.     

Confirmatory Factor Analysis of the Psychopathy Checklist: Screening Version in Offenders With Axis I Disorders.

One hundred forty-nine inpatients within a maximum security psychiatric facility were assessed with the Psychopathy Checklist: Screening Version (PCL:SV; S. D. Hart, D. N. Cox, & R. D. Hare, 1995). Within the total sample, 68% had a psychotic disorder and 30% met criteria for psychopathy. Using confirmatory factor analysis, the authors tested the 2-factor PCL:SV model of psychopathy and recent 3- and 4-factor models. Results indicated good fit for each model, with the 4-factor model showing best overall fit. Structural equation modeling was used to determine which psychopathy factors predicted 6-month follow-up of inpatient aggression. The 2-, 3-, and 4-factor models, respectively, accounted for 16%.27%. and 3l% of the variance in aggression. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Wear of filled and unfilled dental restorative resins

The influence of double-pass sliding on the surface failure of filled and unfilled dental restorative resins was evaluated. Damage was more severe for double-pass than for single-pass sliding. Wear of restorative resins and composites was influenced by the resistance to penetration and by the mode of deformation during sliding.     

Adolescent exposure to drink driving as a predictor of young adults’ drink driving

The purpose of this study was to investigate the influence of exposure to others’ drink driving during adolescence on self-reported driving under the influence (DUI) of alcohol in young adulthood. Data were drawn from 1956 participants with a driving license enrolled in the International Youth Development Study from Victoria, Australia. During 2003 and 2004, adolescents in Grades 7, 9 and 10 (aged 12–17) completed questionnaires examining whether they had ridden in a vehicle with a driver who had been drinking, as well as other demographic, individual, peer and family risk factors for DUI. In 2010, the same participants (aged 18–24) then reported on their own DUI behaviour. 18% of young adults with a driving license reported DUI in the past 12 months. Exposure to others’ drink driving during adolescence was associated with an increased likelihood of DUI as a young adult (OR = 2.13, 95% CI 1.68–2.69). This association remained after accounting for the effects of other potential confounding factors from the individual, peer and family domains (OR = 1.62, 95% CI 1.23–2.13). Observing the drink driving behaviours of others during adolescence may increase the likelihood of DUI as a young adult. Strategies to reduce youth exposure to drink driving are warranted.     

Evaluating ten years of energy performance of HERS-rated homes in Alachua County,Florida

This paper evaluates the performance of 1,346 homes in Alachua County, Florida that were Home Energy Rating System (HERS)-rated between February 1998 and December 2009 for participation in various energy-efficiency programs for new residential construction. The primary analysis objective is to measure the energy-efficiency performance of these HERS-rated homes against conventionally built homes using metered energy consumption data for calendar years 2000–2010. A secondary objective is to assess performance of the four major builders of HERS-rated homes. In calendar year 2000, average energy savings for all HERS-rated homes was 18 %. However, over the following decade average savings degraded steadily, stabilizing around 7 % in the last 5 years of the analysis. We conclude that, while HERS-rated homes in the study area are performing better than similar conventionally built homes, the average HERS-rated home is not achieving the level of savings anticipated based on its HERS score and related energy-efficiency program participation. Differences in savings among builders of HERS-rated homes suggest that variations in program implementation and construction practices can yield significantly different energy performance results. Of the four builders tested, the least efficient averaged 3 % less energy consumed than conventionally built homes, while the most efficient averaged 21 % less. Overall, findings of this study indicate the need for re-examination of the HERS-rating process as a primary benchmark and for increased emphasis on direct measurement and verification of performance using historical energy consumption data.