Physical inactivity is a major contributor to increased disease prevalence and reduced quality of life. Measuring behavioral economic demand for exercise may enable more effective physical activity intervention development. In study one, we developed the leisure-time-as-price exercise purchase task (LT-EPT), wherein participants (n = 175) indicate hypothetical likelihood to trade leisure time for access to exercise time. We observed weak to moderate correlations between demand indices (Q1%, α, BP1, and Pmax) generated from the LT-EPT and self-reported leisure and exercise time, demonstrating initial validation of the LT-EPT. In study two, we examine the effect of episodic future thinking (EFT; vivid, personalized prospection of future events) in adults not meeting physical activity guidelines (n = 127) on demand for exercise and delay discounting (sensitivity to delayed rewards). We observed reduced delay discounting in participants randomized to engage in EFT, but no difference between EFT and health information thinking (HIT) controls. In study three, we further examined the effect of EFT on demand for exercise in adults with type 2 diabetes and obesity participating in a 24-week randomized controlled trial (n = 71). All participants engaged in a multicomponent behavioral intervention focused on weight loss and glycemic control; additionally, participants were randomized to engage in EFT or HIT thrice daily beginning in week 3. We measured demand for exercise and delay discounting (among other outcomes) at weeks 0, 8, and 24, observing no differences between EFT or HIT groups in demand indices (Q1%, α) or delay discounting at any time point. In conclusion, early evidence suggests that the LT-EPT may be a valid method to measure behavioral economic demand for exercise; however, EFT may not be an effective intervention to increase demand for exercise. / Doctor of Philosophy / Physical inactivity poses a significant threat to our well-being, contributing to increased disease rates and a diminished quality of life. This dissertation details a novel method to measure how people value exercise and the effect of a behavioral intervention to increase exercise valuation. In the first study, we introduce the leisure-time-as-price exercise purchase task (LT-EPT), a tool designed to gauge individuals' willingness to trade leisure time for exercise time (i.e., exercise demand). Initial results show promising correlations between LT-EPT metrics and self-reported leisure and exercise time, providing a foundation for its potential as a valuable measurement tool. The second study examines the impact of episodic future thinking (EFT), a technique involving vivid and personalized visualization of future events, on exercise demand. While participants engaging in EFT showed increased preference for larger, delayed rewards over smaller, sooner rewards (i.e., reduced delay discounting), no significant difference was found between EFT and the health information thinking (HIT) control in terms of exercise demand. The third study expands our investigation to adults with type 2 diabetes and obesity undergoing a 24-week intervention. All participants engaged in a comprehensive behavioral program, while half were randomized to engage in EFT or HIT three times per day. No discernible differences were observed in exercise demand or delay discounting at any measurement point. In summary, our findings suggest that the LT-EPT may be a valid measure of exercise demand. However, the effectiveness of EFT in increasing demand for exercise remains inconclusive. These insights contribute to the ongoing efforts to develop more targeted and impactful interventions for promoting physical activity and improving overall health.

Evacuation planning is an important disaster management tool. A large-scale evacuation of a region by automobile is a difficult task, especially as demand is often greater than supply. This is made more difficult as the imbalance of supply and demand actually reduces supply due to congestion. Currently, most of the emphasis in evacuation planning is on supply management. The purpose of this dissertation is to introduce and study sophisticated demand management tools, specifically, staging and routing of evacuees. These tools can be used to produce evacuation strategies that reduce or eliminate congestion. A strategic planning model is introduced that accounts for evacuation dynamics and the non-linearities in travel times associated with congestion, yet is tractable and can be applied to large-scale networks. Objective functions of potential interest in evacuation planning are introduced and studied in the context of this model. Insights into the use of staging and routing in evacuation management are delineated and solution techniques are developed. Two different strategic approaches are studied in the context of this model. The first strategic approach is to control the evacuation at a disaggregate level, where customized staging and routing plans are produced for each individual or family unit. The second strategic approach is to control the evacuation at a more aggregate level, where evacuation plans are developed for a larger group of evacuees, based on pre-defined geographic areas. In both approaches, shelter requirements and preferences can also be considered. Computational experience using these two strategic approaches, and their respective solution techniques, is provided using a real network pertaining to Virginia Beach, Virginia, in order to demonstrate the efficacy of the proposed methodologies. / Ph. D.

We provide a comprehensive characterization of the relationship between optimal capacity and the degree of product substitution/complementarity under price/production postponement, considering different business practices (holdback versus clearance, negative price policies) and different demand models. Specifically, we consider a firm that produces two products, which can be substitutable or complementary. The demand of each product is a linear function of the prices of both products (with the relationship depending on the substitution/complementarity structure), and is subject to an additive stochastic shock. We consider two types of linear demand functions that are commonly used in the economics and operations management literature. The firm operates in a monopolistic setting and acts as a price-setter for both products. Overall the firm needs to make three sets of decisions: capacity, production quantities, and prices. While the capacity investment decision has to be made ex-ante observation of demand curves, price and/or quantity decisions can be postponed until after demand curves are observed. We consider two postponement strategies: price and quantity postponement, and price postponement only. We characterize the optimal pricing/production/investment decisions for each postponement strategy. Using these characterizations, we show that product substitution/complementarity is a key demand characteristic, which has a large impact on the optimal capacity. Our results show that how the optimal capacity behaves in substitution/complementarity parameter is quite similar under both postponement strategies, and under holdback and clearance. However, this behavior depends highly on other underlying assumptions (i.e., whether or not negative prices are allowed) and on the demand model used. / Ph. D.

Work-related musculoskeletal disorders (WMSDs) are prevalent among health care workers worldwide and underreporting among nurses may mask the true impact of these injuries. Nursing staff are consistently among the top 10 occupations at risk for experiencing WMSDs and patient-handling tasks are the precipitating event in the majority of back injuries experienced among nursing staff. Existing research has focused on patient-handling issues within long-term care facilities, and identifying physically demanding patient-handling tasks. The first study in this dissertation (Chapter 3) was conducted to determine whether nurses in acute care facilities are exposed to the same hazards as their cohorts in long-term care. The aim was to identify the top 10 patient-handling tasks being conducted and to rank these tasks by perceived physical demand. This two-phase study consisted of a procedural task analysis of patient-handling activities, and a questionnaire to identify the characteristics of the study population and obtain a ranking of physically demanding patient-handling tasks. All nurses providing direct inpatient care were recruited to participate in both phases of this study. Compared to long-term care facilities, in which the majority of tasks have been shown to be associated with performance of ADL tasks, the most frequently observed tasks in the acute care facility were repositioning tasks. Therefore, it is important to determine the patient-handling demands and needs that are unique to each type of healthcare facility. Generalizing across facilities or units may lead to incorrect assumptions and conclusions about physical demands being placed on nurses. A laboratory simulation was used for the second study (Chapter 4). The top four physically demanding patient-handling tasks (taken from Chapter 3) were simulated to determine the effect of an assistive device and assistance from another person. Sixteen nurse volunteers were recruited and provided perceptual responses regarding exertion and injury risk. Nurses perceived that assistance decreased their physical exertion and injury risk; however they consistently perceived exertion to be relatively higher than their injury risk. The aim of the third study (Chapter 5) was to determine the level of agreement between and within different expert groups. Three groups of participants were involved, with different levels of ergonomics expertise (i.e. researchers, consultants, and graduate students). These groups viewed digitized video clips from the laboratory simulation (Chapter 4) and provided ratings of perceived exertion, perceived injury risk and common WMSD risk factors (effort, posture, and speed). The major finding from this study was that poor agreement existed between nurses and the other expert groups (researchers, consultants and students). The current research laid the groundwork for measuring the magnitude of physical exposure to injury risk in the patient-handling environment. The research supports earlier evidence that suggests nurses underreport their discomfort and injury, which, in turn, contributes to increased exposure and risk. This knowledge will enable practitioners to focus interventions and designs on those factors in the work environment that contribute significantly to increased exposure and thereby more effectively reduce WMSD risk. / Ph. D.

The current airline practice is to assign aircraft capacity to scheduled flights well in advance of departure. At such an early stage in this process, the high uncertainty of demand poses a major impediment for airlines to best match the airplane capacities with the final demand. However, the accuracy of the demand forecast improves markedly over time, and revisions to the initial fleet assignment become naturally pertinent when the observed demand considerably differs from the assigned aircraft capacity. The Demand Driven Re-fleeting (DDR) approach proposed in this thesis offers a dynamic re-assignment of aircraft capacity to the flight network, as and when improved demand forecasts become available, so as to maximize the total revenue. Because of the need to preserve the initial crew schedule, this re-assignment approach is limited within a single family of aircraft and to the flights assigned to this particular family. This restriction significantly reduces the problem size. As a result, it becomes computationally tractable to include path level demand information into the DDR model, although the problem size can then get very large because of the numerous combinations of composing paths from legs. As an extension, models considering path-class level differences, day-of-week demand variations, and re-capture effects are also presented. The DDR model for a single family with path level demand considerations is formulated as a mixed-integer programming problem. The model's polyhedral structure is studied to explore ways for tightening its representation and for deriving certain classes of valid inequalities. Various approaches for implementing such reformulation techniques are investigated and tested. The best of these procedures for solving large-scale challenging instances of the problem turns out to be an integrated approach that uses certain selected model augmentations and valid inequalities generated via a suitable separation routine and a partial convex hull construction process. Using this strategy in concert with properly selected CPLEX options reduces the CPU time by an average factor of 7.48 over an initial model for a test-bed of problems each having 200 flights in total. Prompted by this integrated heuristic approach, a procedure for finding solutions within a prescribed limit of optimality is suggested. To demonstrate the effectiveness of these developed methodologies, we also solved two large-scale practical-sized networks that respectively involve 800 and 1060 flights, and 18196 and 33105 paths in total, with 300 and 396 flights belonging to the designated family. These problems were typically solved within 6 hours on a SUN Ultra 1 Workstation having 260 MB RAM and a clock-speed of 167 MHz, with one exception that required 14 hours of CPU time. This level of computational effort is acceptable considering that such models are solved at a planning stage in the decision process. / Master of Science

This thesis consists of two topics. The first topic is a performance assessment study of the flight operations in the North Atlantic Organized Track System. This study begins with the demand shortfall analysis of demand sets provided by the Federal Aviation Association (FAA). These sets were used to simulate OTS traffic for a number of scenarios that consider different separation minima. For this reason, algorithms were developed to modify the NAT OTS configuration applying reduced lateral separation between tracks and estimate the probability that any given flight that traverses the Atlantic will use the OTS. The preliminary results showed that the scenario with reduced lateral separation minimum (RLatSM) (25 nm) and the reduced longitudinal separation minimum (RLongSM) (8 nm) was the most optimal among all five that were simulated. The application of RLatSM also decrease the mean fuel consumption of flights that shift from traversing the OTS to flying random routes. The second topic is a noise study performed for the Chicago O'Hare International Airport. The contributions to this topic were three fold: 1) we analyzed data to understand the current operations at ORD airport 2) we verified the noise contours produced in 2002 by the FAA, Chicago Department of Aviation (CDA) and the engineering contractors 3) we produced noise contours for today's airport activity. / Master of Science

Air transportation demand forecasting is a core element in aviation planning and policy decision making. NASA Langley Research Center addressed the need of a global forecast model to be integrated into the Transportation Systems Analysis Model (TSAM) to fulfil the vision of the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters to develop a picture of future demand worldwide. Future forecasts can be performed using a range of techniques depending on the data available and the scope of the forecast. Causal models are widely used as a forecasting tool by looking for relationships between historical demand and variables such as economic and population growth. The Global Demand Model is an econometric regression model that predicts the number of air passenger seats worldwide using the Gross Domestic Product (GDP), population, and airlines market share as the explanatory variables. GDP and Population are converted to 2.5 arc minute individual cell resolution and calculated at the airport level in the geographic area 60 nautical miles around the airport. The global demand model consists of a family of models, each airport is assigned the model that best fits the historical data. The assignment of the model is conducted through an algorithm that uses the R2 as the measure of Goodness-of-Fit in addition to a sanity check for the generated forecasts. The output of the model is the projection of the number of seats offered at each airport for every year up to the year 2040. / Master of Science

Yes / Multi-Stage Flash (MSF) desalination process has been used for decades for making fresh water from seawater and is the largest sector in desalination industries. In this work, dynamic optimisation of MSF desalination is carried out using powerful and robust dynamic simulation and optimisation software called gPROMS model builder. For a fixed freshwater demand, a number of optimal combinations of the factors such as heat transfer area, brine flow rate, cooling water flow rate, steam flow in brine heater, Top Brine Temperature, the number of stages, etc. are determined with the objective of maximising the performance ratio of the process (defined as the amount of fresh water produced per unit of energy input) considering the seasonal variations. An attempt has been made to develop an operational schedule for a particular day using dynamic optimisation.

This study was conducted to investigate whether hamstring muscle activation rate could potentially serve as an indicator for slip-induced falls, particularly for older adults. Kinematics (heel contact velocity, walking velocity, slip distance, and step length), kinetics (friction demand), and electromyography (EMG) while walking over a slippery surface were collected and examined in the study. Normalized EMG data were examined in term of activation rate and compared to heel contact velocity. Twenty-eight subjects from two age groups (14 young and 14 elderly) walked across a track with embedded force platforms while wearing a fall arresting harness attached to an arresting rig for safety. In order to obtain realistic unexpected slip-induced fall data, the slippery surface was hidden from the subjects and unexpectedly introduced. The primary objective of the study was to evaluate if hamstring activation rate could be a valid indicator for the initiation of slip-induced falls. The results suggested that hamstring activation rate in younger adults was higher than older adults, whereas, younger adults’ heel contact velocity was not different from older adults. These results suggested that heel contact velocity in younger adults was sufficiently reduced before the heel contact phase of the gait cycle. This could be due to the outcome of higher hamstring activation rate in younger adults in comparison to older adults. However, an equal number of falls in two age groups, in spite of older adults’ slower walking velocity, lower RCOF, shorter slip distance, and slower peak sliding heel velocity, suggested that the recovery phase of the slip-induced fall accidents should be studied further. / Master of Science

In many situations, different consumers have different degrees of willingness to wait to get delivery of a product. So, consumers can be segregated based upon the demand lead time they are providing. In this paper, two types of consumers have been considered. The first category needs immediate delivery of the product, so there is no demand lead time; whereas for the other category, demand lead time is positive. A manufacturer, which produces the items using a base stock policy, can benefit from the advance demand information that the second category of consumers are providing. Early fulfillment for a particular order means fulfilling the order before the demand lead time. In this research, it is shown that a restrictive early fulfillment policy can help the firm to reduce the chances of order loss. A production control approach for restrictive early fulfillment is discussed and the factors that may affect the early fulfillment policy are examined. / Master of Science