There is a growing demand for accountability of nonprofit organizations, and nonprofit business leaders are increasingly under pressure to demonstrate operational effectiveness. The problem is that some business leaders of nonprofit organizations lack strategies for identifying and selecting actionable performance measures of operational effectiveness. Using the plan-do-study-act conceptual framework, this single case study of a nonprofit organization located in the mid-Atlantic region of United States was conducted to explore strategies that 3 of its business leaders used to identify and select actionable performance measures of operational effectiveness. Using thematic analysis of data collected from semistructured interviews, documents, and public sources, emergent themes included: (a) usefulness of measures, (b) customer experience, and (c) workforce education. The findings of this study may have implications for social change by helping nonprofit business leaders achieve consensus on measures of effectiveness beyond financial measures. Additionally, the findings could support the usefulness of transparency in reporting performance outcomes, encourage a shift in focus from program spending and ratios to effectiveness, and prompt external stakeholders to expect performance measures that demonstrate effectiveness in nonprofit program operations.

This thesis is divided into two parts. The first part considers and develops some of the statistics used in genetic programming (GP) while the second uses those statistics to study and develop a form of incremental evolution and an early termination heuristic for GP. The first part looks in detail at success proportion, Koza's minimum computational effort, and a measure we rename "success effort". We describe and develop methods to produce confidence intervals for these measures as well as confidence intervals for the difference and ratio of these measures. The second part studies Jackson's fitness-based incremental evolution. If the number of fitness evaluations are considered (rather than the number of generations) then we find some potential benefit through reduction in the effort required to find a solution. We then automate the incremental evolution method and show a statistically significant improvement compared to GP with automatically defined functions (ADFs). The success effort measure is shown to have the critical advantage over Koza's measure as it has the ability to include a decreasing cost of failure. We capitalise on this advantage by demonstrating an early termination heuristic that again offers a statistically significant advantage.

<p>In line with the company-wide CS09 project being carried out at Volvo CE Components, Cell 14 will have changes in terms of distribution of machines and parts routing to meet the lean manufacturing goals established.  These changes are of course dependant on future production volumes, as well as lot sizing and material handling considerations.</p><p>In this context, an important emphasis is given to the awareness of the performance measures that support decision making in these production development projects.  By using simulation as a confirmation tool, it is possible to re-assess these measures by testing the impact of changes in complex situations, in line with the lean manufacturing principles.</p><p>The aim of the project is to develop a discrete event simulation model following the methodology proposed by Banks et al (1999).  A model of Cell 14 will be built using the software Technomatix Plant Simulation ® which is used by the Company and the results from the simulation study will be analyzed.</p>

In line with the company-wide CS09 project being carried out at Volvo CE Components, Cell 14 will have changes in terms of distribution of machines and parts routing to meet the lean manufacturing goals established.  These changes are of course dependant on future production volumes, as well as lot sizing and material handling considerations. In this context, an important emphasis is given to the awareness of the performance measures that support decision making in these production development projects.  By using simulation as a confirmation tool, it is possible to re-assess these measures by testing the impact of changes in complex situations, in line with the lean manufacturing principles. The aim of the project is to develop a discrete event simulation model following the methodology proposed by Banks et al (1999).  A model of Cell 14 will be built using the software Technomatix Plant Simulation ® which is used by the Company and the results from the simulation study will be analyzed.

The primary purpose of this study was to determine the effect of ingesting an 8% carbohydrate (CHO) beverage during a moderate intensity exercise trial on performance outcomes, fuel utilization and blood glucose levels of wheelchair athletes (spinal cord injury (SC I) or cerebral palsy (CP)). The secondary purpose was to analyze the dietary intake of the eight participants and to determine if they were meeting current sport nutrition guidelines for macronutrients and fluids recommended in the joint position statement developed by the American Dietetic Association (ADA), the American College of Sports Medicine (ACSM) and Dietitians of Canada (DC).<p> Under random, double blind conditions eight athletes (6 males, 2 females); mean age 36 ± 8.5 y with a SCI (n = 7) or CP (n = 1) completed two exercise trials on an adapted stationary hand cycle; each trial was 60 minutes in duration at 65 % VO2peak followed immediately by a 30-minute performance trial. During the first 60-minutes the participants were given four 200 ml dosages (15, 30, 45, 60-min) of an 8% CHO beverage or a taste-matched placebo beverage. Blood lactate and glucose levels were sampled during the 60-minute exercise trial (pre, 20, 40, 60-min) and immediately after the 30-minute performance trial (post, 2, 5, 10-min). Heart rate was monitored continuously during the exercise and performance trial. Expired gas samples were also taken for 5-min periods during the exercise trial and then continuously during the performance trial. These values were used to calculate respiratory exchange ratio (RER) and carbohydrate oxidation. Dietary intake was assessed with a three day food record.<p> No significant differences were apparent between beverage trials for total distance (km), average speed (kmhr-1) or maximum speed achieved (kmhr-1). Significant differences were evident for blood glucose values, RER and CHO oxidation between the two beverage trials (p< .05). At the end of the 30-minute performance trial blood glucose values were significantly higher in the CHO trial (4.8 ± 1.3 mmol.l-1 vs. 4.0 ± 0.5 mmol.l-1 for placebo trial; p< .05). The CHO beverage resulted in higher CHO oxidation during the last 5 minutes of the performance trial, 2.1 ± 1.0 gmin-1 vs. the placebo beverage 1.9 ± 1.0 gmin-1 (p< .05). The CHO beverage trial resulted in significantly higher RER values during the final 5 minutes of the exercise trial and during the final 10 minutes of the performance trial. At the 20-25 minute mark RER values were significantly higher with the CHO beverage trial (1.04 ± 0.10) vs. the placebo trial (1.01 ± 0.11) (p< .05). During the final 5 minutes of the performance trial RER values were also significantly higher with the CHO beverage trial (1.06 ± 0.11) vs. the placebo trial (1.01 ± 0.10) (p< .05). The results indicated the participants were not meeting the current dietary guidelines for able-bodied athletes and active adults. Only 25% of the participants met the daily caloric requirements for active adults. Carbohydrate recommendations of 6 to 10 gkg-1 body weightd -1 were not met by any of the wheelchair athletes Seven participants were within the acceptable macronutrient range (AMDR) for CHO. For protein intake, 63% of the participants were meeting the protein recommendations active adults and all of them were within the AMDR. Average caloric intake from fat exceeded current recommendations of 20 to 25%; two participants were above the AMDR. The results demonstrate that the 8% CHO beverage consumed during exercise resulted in higher CHO oxidation rates and elevated blood glucose values, but it did not result in a performance gain.

Performance measurement has grown in importance within transportation agencies due to decreased and stipulated funding and federal focus on system performance. A shift has occurred in how transportation planning and decision making historically took place including a rise in prominence of the Metropolitan Planning Organization (MPO). The public, state and local agencies, and other stakeholders are mutually served by the regional MPO to assure that transportation funding allocation and project selection meet the regional needs and coordinate the transportation planning process to provide a seamless transportation system. The recent Federal transportation funding program MAP-21 establishes performance measures for each MPO in coordination with the State department of transportation (DOT). Small MPOs, those which serve populations of less than 200,000 people, differ vastly from larger MPOs in the amount of funds available and authority to allocate funds as well as the resources that are available to perform a performance measurement program. Small MPOs often lack the resources to identify and use performance measures, even though performance measurement at the MPO level has promoted efficient decision-making in large MPOs. This research strives to find by interviews and surveys of the small Texas MPOs if the use of certain performance measures in small MPOs can be financially upheld with limited resources and budget. This thesis is timely in relation to the MAP-21 performance measurement requirements as it shows that performance measurement is, at this time, difficult to impossible based on small Texas MPOs’ very limited resources. Due to the estimated costs of basic performance measurement programs and the difficulty in quantifying the tangible benefits, the use of performance measurements in small Texas MPOs is unlikely. Small Texas MPOs listed potential performance measurement program benefits such as: project prioritization, funding allocation, and showing the public that professional planning is useful. It was found that any potential benefits of performance measurements are limited when dealing with small communities with fairly obvious transportation problems. The estimated cost of a basic performance measurement program in a small Texas MPO was determined to be around $150,000 per year. This cost exceeded both their abilities to fund a performance measurement program and the perceived benefits of such an effort. This research suggests the following performance measures are most likely to be beneficial when proven cost effective: V/C ratios, travel times, crash rates (safety) and VMT. These measures are often easily accessible and could be beneficial in the long-range planning of a local transportation system. However, fiscal and staffing limitations, along with realities of planning for a small community make the use of performance measures difficult. The results of this study can aid the Secretary of Transportation in understanding the limited technical capacities of small Texas MPOs in regards to performance measurement.

Transportation safety has been recognized as a public health issue worldwide, consequently, transportation researchers and practitioners have been attempting to provide adequate safety performance for the various transportation components and facilities to all road users given the usually scarce resources available. Safety engineers have been trying to make decisions affecting safety based on the knowledge extracted from different types of statistical models and/or observational before-after analysis. It is generally recognized that this type of factual knowledge is not easily obtained either statistically or empirically. Despite the intuitive link between road safety and observed crashes, a good understanding of the sequence of events prior to the crash can provide a more rational basis for the development of engineering countermeasures. The development of more comprehensive mechanistic models for safety assessment is heavily dependent on detailed vehicle tracking data that is not readily available. The potential of microscopic simulation in traffic safety and traffic conflict analysis has gained increasing interest mostly due to recent developments in human behaviour modelling and real-time vehicle data acquisition. In this thesis, we present a systematic investigation of the use of existing behavioural microscopic simulation models in short-term road safety studies. Initially, a microscopic framework is introduced to identify potentially unsafe vehicle interactions for different vehicle movements based on three types of traffic behaviour protocols: car-following, lane change and gap acceptance. This microscopic model for safety assessment applies a safety performance measure based on pairwise comparisons of spacing and speed differential between adjacent vehicles and individual braking power in real-time. A calibration/validation procedure using factorial analysis is presented to select best model input parameters for this safety performance measure by using high resolution vehicle tracking data. The ability of the proposed safety performance measure to reflect real-life observed high-risk vehicular interactions is explored in three intuitive tests using observed crash data. Finally, the usefulness of the model is illustrated through its application to investigate the safety implications of two different geometric and operational traffic strategies. The overall results indicate that, notwithstanding the fact that actual behavioural microscopic algorithms have not been developed strictly to model crashes, they are able to replicate several factors directly related to high risk situations that could lead to crashes with reasonable accuracy. With the existing upward trend in computing power, modelling techniques and increasing availability of detailed vehicle tracking data, it is likely that safety studies will be carried out using a more mechanistic and inclusive approach based on disruptive driving behaviour rather than ultimate unpredictable and heavily restrictive crash events.

No description available.

This short note discusses performance bounds for "Ahrens" algorithm, that can generate random variates from continuous distributions with monotonically decreasing density. This rejection algorithms uses constant hat-functions and constant squeezes over many small intervals. The choice of these intervals is important. Ahrens has demonstrated that the equal area rule that uses strips of constant area leads to a very simple algorithm. We present bounds on the rejection constant of this algorithm depending only on the number of intervals. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

Transportation safety has been recognized as a public health issue worldwide, consequently, transportation researchers and practitioners have been attempting to provide adequate safety performance for the various transportation components and facilities to all road users given the usually scarce resources available. Safety engineers have been trying to make decisions affecting safety based on the knowledge extracted from different types of statistical models and/or observational before-after analysis. It is generally recognized that this type of factual knowledge is not easily obtained either statistically or empirically. Despite the intuitive link between road safety and observed crashes, a good understanding of the sequence of events prior to the crash can provide a more rational basis for the development of engineering countermeasures. The development of more comprehensive mechanistic models for safety assessment is heavily dependent on detailed vehicle tracking data that is not readily available. The potential of microscopic simulation in traffic safety and traffic conflict analysis has gained increasing interest mostly due to recent developments in human behaviour modelling and real-time vehicle data acquisition. In this thesis, we present a systematic investigation of the use of existing behavioural microscopic simulation models in short-term road safety studies. Initially, a microscopic framework is introduced to identify potentially unsafe vehicle interactions for different vehicle movements based on three types of traffic behaviour protocols: car-following, lane change and gap acceptance. This microscopic model for safety assessment applies a safety performance measure based on pairwise comparisons of spacing and speed differential between adjacent vehicles and individual braking power in real-time. A calibration/validation procedure using factorial analysis is presented to select best model input parameters for this safety performance measure by using high resolution vehicle tracking data. The ability of the proposed safety performance measure to reflect real-life observed high-risk vehicular interactions is explored in three intuitive tests using observed crash data. Finally, the usefulness of the model is illustrated through its application to investigate the safety implications of two different geometric and operational traffic strategies. The overall results indicate that, notwithstanding the fact that actual behavioural microscopic algorithms have not been developed strictly to model crashes, they are able to replicate several factors directly related to high risk situations that could lead to crashes with reasonable accuracy. With the existing upward trend in computing power, modelling techniques and increasing availability of detailed vehicle tracking data, it is likely that safety studies will be carried out using a more mechanistic and inclusive approach based on disruptive driving behaviour rather than ultimate unpredictable and heavily restrictive crash events.