The consumer surplus and economic rent methods of resource valuation were applied to boating recreation in Utah. Total consumer surplus and economic rent values were estimated for twenty-four boating sites. These values incorporate the relationship existing between the variable use cost and the units of activity associated with the site. Data were collected by a mail survey directed to boaters during the 1973 boating season. Approximately 1,408 questionnaires were analyzed. Additional data were collected from the Utah Division of Parks and Recreation. Economic rent and consumer surplus were compared by using a common mathematical model and empirical observation. The concepts of economic rent and consumer surplus were assumed to be consistent methods of resource valuation and that the models would yield equivalent values. Three stages of the calculation procedure were considered in analyzing the comparison of the two methodologies . In the first stage, the economic rent and consumer surplus values were compared and the economic rent estimate consistently exceeded the consumer surplus. In the second and third stages, the projected values for an origin visiting a site were compared with the total values for a site. This process did not demonstrate any unique relationship between the two resource valuation methodologies. The most significant factors contributing to the inconsistent relationship between economic rent and consumer surplus are using the number of trips in the economic rent model and the numbers of trips per capita in the consumer surplus model, the constant economic rent per trip, and the decline in the consumer surplus for an additional trip per capita; and the respective projection factors of the two models.

<p>The expansion of wind energy production creates an increase in wind turbine (WT) noise. The purpose of this paper is to examine if a possible reduction of WT noise might be achieved by adding natural ambient sounds, so called auditory masking. A loudness experiment was conducted to explore this possibility, using four ambient sounds of trees, birds and water as maskers. Sixteen listeners assessed the loudness of WT noise heard alone or in the presence of 40 dB masking sounds, using the method of magnitude estimation. Partial masking of WT noise was found in the presence of all ambient sounds. The masking effect corresponded to a dB-reduction of the WT noise from a few dB for signal-to-noise ratios (S/N) close to 0 dB up to around 10 dB at -15 dB S/N. These results indicate that addition of ambient sounds may be a useful method for masking unwanted noise from wind turbines.</p>

No description available.

This thesis proposes a new proof of the acoustic transparency theorem for material with a bounded variation. The theorem states that if the material properties (density, bulk modulus) is of bounded variation, the net power transmitted through the point z = 0 over a time interval [−T,T] is greater than some constant times the energy at the time zero over a spatial interval [0,Z], provided that T equals the time of travel of a wave from 0 to Z. This means the reflected energy of an input into the earth will be received. Otherwise, the reflections may not arrive at the surface. A proof gives a lower bound for material properties (density, bulk modulus) with bounded variation using sideways energy estimate. A different lower bound that works only for piecewise constant coefficients is also given. It gives a lower bound by analyzing reflections and transmissions of the waves at the jumps of the material properties. This thesis also gives an example to illustrate that the bounded variation assumption may not be necessary for the medium to be transparent. This thesis also discusses relations between the transparency property and the data of an inverse problem.

Taiwan's surrounding waters rich in terrain, and a number of shares of the sea converge along the coastal waters of Taiwan created a rich fishing ground.However, due to excessive fishing efforts to longterm investment , But lack of proper management of fitness , so even though the number of vessels increased, but the overall fishery production continued to decrease. The management of fisheries resources requires the correct results as the scientific basis for resource assessment , before they can properly apply effective management to achieve goals , and resources conservation and use of a balance between fisheries. The correct resource assessment,you need detailed information on the basis of the catch,the most important time, space and other efforts to catch the amount of information is the most common practitioners of business operating statements made . Taiwan's coastal fisheries,as yet mandatory for the industry to report their operating statements provided management measures , so in the past this type of information is achieved through the visits, but the mission is not only the high cost of information , a small number and accuracy is not high also limited to the funding and cooperation from the fishermen often intermittent , resulting in a serious ack of resources and ssessmenta information. Taiwan Caost Guard Administrstion in order to monitor the waters around Taiwan ,the dynamic vessel offshore the coast of Taiwan are build Caost Radar Systems.These systems approach to proactive scanning , within 24 hours for the scan to monitor vessels and left navigation records including the vessel name , time location information of the vessel .These data separated by fishing information , speed of calculation,it is possible to estimate the fishing vessels fishing effort in the future with the sale of the ships coming into port unloading data information on fishing operations as an alternative complementary information on the shortcomings of the report did not work . The purpose of this study , that Caost Radar Systems in the use of bank information obtained , isolated fishing information , conduct analysis and calculation , and the actual data for verification visits to explore the application of Caost Radar Systems on shore along the coastal fisheries management feasibility . The results showed : Caost Radar Systems data from the isolated shore fishing vessels that the correct information to the operating position, and velocity analysis based on fishing operations , can estimate fishing effort,and calculate the frequency of operating out of position, draw fishing boats operating region .But the study also found the sea wave and blind area factor will be off the lock occur ,resulting in boat speed and position information a short time gaps , but this does not affect the overall assessment of fishery resoures, through projections to supplement the information in this section.

Escalation of right-of-way (ROW) costs have been shown to be a prime contributor to project cost escalation in the highway industry. Two problems contribute to ROW cost escalation: 1) the ROW cost estimation and cost estimate management process generally lacks structure and definition as compared to other areas of cost estimation; and 2) there is a lack of integration and communication between those responsible for ROW cost estimating and those responsible for general project cost estimating. The research for this thesis was preceded by a literature review to establish the basis for the study. Data collection was completed through interviews of seven state highway agencies (SHAs) and two local public agencies (LPAs). The findings of the research are presented in a set of ROW flowcharts which document the steps, inputs, and outputs of the ROW cost estimation and cost estimate management process. Three ROW cost estimates and a cost management process take place throughout project development. An effort was made from the onset of the research to relate the ROW cost estimating and cost estimate management process to the first four project development phases (planning, programming. preliminary design, and final design). There are five flowcharts produced as a result of this research: 1) an agency-level flowchart showing all cost estimates and the interaction of ROW with the project development process; 2) a conceptual ROW cost estimating flowchart which depicts the required steps during planning; 3) a baseline ROW cost estimating flowchart which depicts the required steps during programming; 4) an update ROW cost estimating flowchart which depicts the required steps during preliminary design to include a cost estimate management loop; and 5) a ROW cost management flowchart which depicts the required steps during final design. Although selected SHA contacts provided input following the development of the flowcharts, the flowcharts were only validated to a limited extent due to time and budget constraints. These flowcharts attempt to address the two contributing problems to ROW cost escalation by providing structure to the ROW cost estimation process and by developing the ROW process flowcharts linked to the project development process. Based on the input provided by SHA contacts, the flowcharts appear to have the potential to provide guidance to SHAs in improving the accuracy of ROW cost estimates through addressing these two problems.

The use of statistics has been common practice within the petroleum industry for over a decade. With such a mature subject that includes specialized software and numerous articles, the challenge of this project was to introduce a duplicable method to perform deterministic regression while confirming the mathematical and actual validation of the resulting model. A five-step procedure was introduced using Statistical Analysis Software (SAS) for necessary computations to obtain a model that describes an event by analyzing the environmental variables. Since SAS may not be readily available, the code to perform the five-step methodology in R has been provided. The deterministic five-step procedure methodology may be applied to new fields with a limited amount of data. As an example case, 17 wells drilled in north central Texas were used to illustrate how to apply the methodology to obtain a deterministic model. The objective was to predict the number of days required to drill a well using environmental conditions and technical variables. Ideally, the predicted number of days would be within +/- 10% of the observed time of the drilled wells. The database created contained 58 observations from 17 wells with the descriptive variables, technical limit (referred to as estimated days), depth, bottomhole temperature (BHT), inclination (inc), mud weight (MW), fracture pressure (FP), pore pressure (PP), and the average, maximum, and minimum difference between fracture pressure minus mud weight and mud weight minus pore pressure. Step 1 created a database. Step 2 performed initial statistical regression on the original dataset. Step 3 ensured that the models were valid by performing univariate analysis. Step 4 history matched the models-response to actual observed data. Step 5 repeated the procedure until the best model had been found. Four main regression techniques were used: stepwise regression, forward selection, backward elimination, and least squares regression. Using these four regression techniques and best engineering judgment, a model was found that improved time prediction accuracy, but did not constantly result in values that were +/- 10% of the observed times. The five-step methodology to determine a model using deterministic statistics has applications in many different areas within the petroleum field. Unlike examples found in literature, emphasis has been given to the validation of the model by analysis of the model error. By focusing on the five-step procedure, the methodology may be applied within different software programs, allowing for greater usage. These two key parameters allow companies to obtain their time prediction models without the need to outsource the work and test the certainty of any chosen model.

The purpose of this study was to advance understanding of perceived intellectual and social attainment gains of first-generation, first-year college students participating in First Generation Access Programs at the University of South Florida (USF), a large, public research university in Florida. Understanding the self-reported intellectual and personal/social gains of these students in higher education can lead to higher retention rates, creative strategies that promote academic success, affective cognitive and personal development activities and services that meet the needs of this rapidly growing at-risk student population with their persistence and transition to college. Researchers have sought to examine variables that may help to increase the persistence rates of students by understanding the impact of students enrolled in First Generation Access Programs on first-generation students' academic success, as measured by grade point average. Several studies have indicated that first-generation, first-year college students have pre-collegiate characteristics that impede their intellectual and personal/social growth. In addition, research studies show that First Generation Access Programs are successful in assisting at-risk student populations successful in their transition to and persistence in college. However, there is scarcity of literature that examines the estimates of intellectual and personal/social gains of first-generation, first-year students enrolled in First Generation Access Programs. As such, this study explored the extent to which self-reported intellectual and personal/social gains predict the academic success, as measured by grade point average, for first-generation, first-year college students enrolled in First Generation Access Programs. Theoretical frameworks from higher education were used to provide an understanding of perceived intellectual and personal/social attainment and academic success of first-generation, first-year, students enrolled in First Generation Access Programs for the context of this study. According to Kuh (1995), college impact models from Astin and Tinto and Pusser were studied, as they have been used to assist higher education professionals in understanding "outcomes produced by interactions between students and their institutions' environments..." (p. 126 - 127). In the context of both college impact models, Astin's Inputs-Environment-Outcomes Model (1991) and Tinto and Pusser's Model of Institutional Action for Student Success (2006), results of this study indicated that First Generation Access Programs increase the intellectual and personal/social attainment of first-generation, first-year students. Several statistical analyses were conducted to examine relationships between variables (self-reported intellectual and personal/social gains, gender, and academic success) including multivariate analysis of variance (MANOVA), simple regression tests, and Pearson Product Moment Correlation. Results of this study were based on the responses of 184 participants. Results indicated that the participants self-reported significant intellectual and personal/social gains. However, findings indicated that there is no statistically significant relationship between self-reported gains and academic success as measured by grade point average, but there is a statistically significant relationship based on gender. One implication for higher education administrators and student affairs professionals is the need to investigate alternative measures for academic success of first-generation, first-year students enrolled in First Generation Access Programs. Grade point average does not seem to accurately measure academic success on perceived intellectual and personal/social gains of this at-risk population. Second, institutions should seek to understand the factors and specific strategies of First Generation Access Programs that increase the cognitive and social growth and development of first-generation, first-year college students so that it may be successfully implemented for first-generation, first-year college students who do not participate in FGAP.

The expansion of wind energy production creates an increase in wind turbine (WT) noise. The purpose of this paper is to examine if a possible reduction of WT noise might be achieved by adding natural ambient sounds, so called auditory masking. A loudness experiment was conducted to explore this possibility, using four ambient sounds of trees, birds and water as maskers. Sixteen listeners assessed the loudness of WT noise heard alone or in the presence of 40 dB masking sounds, using the method of magnitude estimation. Partial masking of WT noise was found in the presence of all ambient sounds. The masking effect corresponded to a dB-reduction of the WT noise from a few dB for signal-to-noise ratios (S/N) close to 0 dB up to around 10 dB at -15 dB S/N. These results indicate that addition of ambient sounds may be a useful method for masking unwanted noise from wind turbines.

Treatment–covariate interaction is often used in clinical trials to assess the homogeneity of treatment effects over these subgroups defined by a baseline covariate, which is frequently conducted after primary analysis including all patients is completed. When the endpoint is the time to an event, as in the cancer clinical trials, the Cox proportional hazard model with an interaction term has been used exclusively to test the significance of treatment-covariate interaction in oncology literature. But the proportional hazards assumption may not be satisfied by the data from clinical trials. Although there are several procedures proposed in statistical literature to assess the interaction based on a nonparametric measure of interaction or nonparametric models, some of these procedures do not take into the account of the nature of the data well, while some are very complicated which may have limited their applications in practice. In this thesis, a non-parametric procedure based on the smoothed estimate of Patel–Hoel measure is first derived to test the interaction between the treatment and a binary covariate with censored data. The theoretical distribution of the test statistic of the proposed procedure is derived. The proposed procedure is also evaluated through Monte-Carlo simulations and applications to data from a cancer clinical trial. Jackknifed versions of two test statistics based on nonparametric models are then derived by simplifying these test statistics and applying the jackknife method to estimate their variances. These jackknifed tests are also compared with the smoothed test and other related tests. / Thesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2011-09-27 11:09:28.449