Dynamic model creation and support for the Lua scripting language was added to the Horizon Simulation Framework used for the verification and validation of system-level requirements. The addition of scripting support allows for subsystem models and their algorithms to be defined using a simpler scripting language, rather than C++. The Luabind library by Rasterbind software is used to expose the C++ algorithms and classes to Lua that are already defined in the framework. Interoperability between Lua and C++ code allows for the ease of use of a scripting language while utilizing the utility classes and functions already created. The dynamic model creation algorithm developed allows for the structure and logic of the simulated system to be defined completely using XML and text files as input to the framework. Dynamic model creation prevents the need to re-compile the framework every time small changes are made and greatly simplifies the changes required to simulate a different model. A runtime analysis shows that using a scripting language does not decrease the performance significantly, while increasing usability and decreasing the time required to set up simulations. Tests where the scripted code uses only classes and function exposed by luabind show that there is virtually no performance decrease when compared to the same algorithms in C++. Performance decreases as more of the algorithm implemented is executed in Lua. An example test scenario that represents the typical use of the framework showed only a minor decrease in performance. The multi-threaded scheduler developed works with the scripting support and allows for modern multi-core or multi-processor computers to be used most efficiently for simulations. This thesis describes the algorithms of dynamic model creation and scripting support, as well as the methodology used to expose C++ code to Lua. This thesis also presents the architecture changes required to support dynamic model creation, scripting support, and multi-threaded scheduling. Finally, runtime results of the added scripting support are presented.

Indiana University-Purdue University Indianapolis (IUPUI) / Hospital costs are the largest contributor to US health expenditures, making them a common target for cost containment policies. Policies that reduce fragmentation in health care and related systems could increase the value of these expenditures while improving outcomes. Efforts to address fragmentation of health care services, such as Accountable Care Organizations, have typically been enacted at the scale of health systems. However, coordination within health care facilities should also be explored. In three essays, I analyze the role of coordination in several forms. First, I examine the introduction of interdisciplinary care teams within a hospital. This analysis features care coordination within a health care facility with the potential to reduce resource utilization through improved communication between team members and between patients and their care providers. I find that care coordination reduced length of stay for some patients while maintaining care quality. This combination results in higher value care for patients and hospitals. Second, I explore whether these interdisciplinary care teams impact resource utilization and patient flow throughout the hospital. The primary outcome is reduction in patient transfers to the ICU. Here, care coordination includes interdisciplinary teams as well as coordination between interdisciplinary teams and intensivists in ICUs. Findings from this analysis suggest that ICU transfers were unaffected by care coordination. Finally, I examine coordination on a larger scale. I leverage data from a national database of trauma patients to compare mortality among adolescent patients with isolated traumatic brain injury between adult trauma centers and pediatric trauma centers. Previous work has shown that younger pediatric patients with this injury benefit from treatment at pediatric trauma centers. However, it is unclear whether this benefit extends to older pediatric patients on the cusp of adulthood. I find that, after adjusting for differences in injury severity, adolescent patients have no difference in mortality risk when treated at adult or pediatric trauma centers. This finding supports the current regionalized model of trauma care where severely injured patients are taken to the nearest trauma center, regardless of designation as pediatric or adult. / 2023-07-01

Despite the evidence that supports the benefits of a holistic, collaborative approach to autism intervention, but there is little training to teach those skills to professionals. Behavior analysts working in applied settings will often partner with different individuals from very different backgrounds and disciplines. Skilled Dialogue has been recommended as an approach to conversations that values everyone's contributions in fostering compassionate, collaborative, and culturally responsive care to benefit the children served. The purpose of this study was to evaluate the effects of a training workshop to teach the concept and strategies of skilled dialogue to behavior analysts in training. The participants were taught and practiced using the six strategies of Skilled Dialogue: welcoming, allowing, sense-making, appreciating, joining, and harmonizing through use of instructions, rationales, activities, simulations, and feedback. The success of the training was evaluated using a multiple baseline design across training components. Audio and video responses to role-play scenarios were recorded, transcribed, and scored to measure the results of the training workshop on communication skills. The results suggested that the training workshop was an effective method to teaching future behavior analysts how to engage in the strategies and components of skilled dialogue, increasingly the likelihood of collaborative, and children centered communication and care.

Multidisciplinary design optimisation incorporates several disciplines in one integrated optimisation problem. The benefi t of considering all requirements at once rather than in individual optimisations is that synergies between disciplines can be exploited to fi nd superior designs to what would otherwise be possible. The main obstacle for the use of multidisciplinary design optimisation in an industrial setting is the related computational cost which may become prohibitively large. This work is focused on the development of a multidisciplinary design optimisation framework that extends the existing trust-region based optimisation method known as the mid-range approximation method. The main novel contribution is an approach to solving multidisciplinary design optimisation problems using metamodels built in sub-spaces of the design variable space. Each metamodel is built in the sub-space relevant to the corresponding discipline while the optimisation problem is solved in the full design variable space. Since the metamodels are built in a space of reduced dimensionality, the computational budget for building them can be reduced without compromising their quality. Furthermore, a method for efficiently building kriging metamodels is proposed. This is done by means of a two-step hyper parameter tuning strategy. The fi rst step is a line search where the set of tuning parameters is treated as a single variable. The solution of the fi rst step is used in the second step, a gradient based hyper parameter optimisation where partial derivatives are obtained using the adjoint method. The framework is demonstrated on two examples, a multidisciplinary design optimisation of a thin-walled beam section subject to static and impact requirements, and a multidisciplinary design optimisation of an aircraft wing subject to static and bird strike requirements. In both cases the developed technique demonstrates a reduced computational effort compared to what would typically be achieved by existing methods.

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This study is derived from the claim that multidisciplinary groups are more innovative than homogeneous groups; a claim that has flooded the business industry and has become criteria for accreditation in higher education. However, the impact of disciplinary diversity in work groups is a growing area of research; therefore, it is yet to be thoroughly understood. The purpose of this study is to answer the question: are multidisciplinary teams more innovative than homogenous teams. To accomplish this university students from differing majors were sorted into multidisciplinary and homogeneous groups while participating in a two-day innovation course. The course taught the students about divergent thinking, and invited them to work as teams to develop an innovative product, system or service. Each group's final product was independently judged by three experts using the Creative Solutions Diagnosis Scale (CSDS) measuring the innovativeness (functional creativity) of student work. The homogeneous groups outscored the multidisciplinary groups in every category. Group dynamics have been assessed as also playing a vital role in the successfulness of a diverse group. The Teamwork Quality Questionnaire (TWQ) was used to measure the quality of team interactions, student sentiments, and student attitude. These self-evaluations were used to assess if the group dynamics played a significant role in the functional creativity of the end product by checking for correlation with the results of the CSDS. The findings were inconclusive, meaning they did not correlate. Despite the findings not aligning with past research, they should be considered important. At a minimum, they describe a context and environment where multidisciplinary groups do not function at the same level as homogenous groups. Accordingly, there is a need to further investigate group formations and function in regards to innovation and creativity production. We recommend for future research performing a similar study on a larger scale to discover if the findings from this study would vary when tested under similar or varying contexts. It would also be important to analyze how the make up of the group is affecting the students understanding and learning.

A flight test program that evaluated the results of a CP140 Aurora cockpit modernization project was conducted between May 2004 and October 2005. This paper uses the results of that test program to show how basic human factors principles were violated which led to the identification of multiple design deficiencies. This paper proposes that the failure to apply good human factors principles when designing aircraft displays can lead to unacceptable deficiencies. The result can be poor modal awareness, confusion in the cockpit, and often negative training for the pilots. In particular, four major deficiencies were analyzed to determine the specific human factors principles that were breached. The violations included a lack of concise and relevant feedback to the pilot, unclear and ambiguous annunciations, poor use of colour coding principles and logic, a lack of suitable attention capture cueing, inappropriate alert cueing, an absence of aural cueing during specific degraded modes of operation, excessive cognitive workload, and a failure to incorporate the pilot as the focal point of the display design, also known as a human centred design philosophy. Recommendations for system design enhancements are provided to ensure safe and effective operations of this prototype system prior to operational implementation. The evaluation of the prototype system design was conducted by a flight test team from the Aerospace Engineering Test Establishment in Cold Lake, Alberta and supported by the Maritime Proving and Evaluation Unit in Greenwood, Nova Scotia. The test program encompassed a thorough review of system design documentation, abinitio training and preliminary testing in a Systems Integration Lab and 40 flight test missions. The recorded deficiencies were based upon the observations of two Qualified Test Pilots.

The Chronic Pain Center (CPC) in Saskatoon offers a multidisciplinary treatment program whose goals are to facilitate improved coping skills, function and well-being, and to promote self-reliant lifestyles. They have documented a statistically significant improvement on several measures of physical and social functioning at the completion of the six week program, but to date have no formal evaluation of the long term effects.<p/> The purpose of this study was to re-evaluate the CPC clients (treatment group) at least one year following their completion of the treatment program to determine if they had maintained those improvements and also to compare them to the group of clients (control group) who underwent initial multidisciplinary assessment at the Centre, but did not attend the six week treatment program. Evaluation by mail out questionnaires assessed several important aspects of chronic pain. A 34% response rate resulted in 142 participants for this study.<p/> Data analyses involved a multi-stage process of univariate, bivariate and multivariate analyses. For the first goal, evaluating changes in the treatment group over time, the outcome variables considered had been administered at three points in time: admission to the CPC program, discharge from the six week program, and at study follow-up. For the second goal, the treatment and control groups were compared at one point in time; the study follow-up.<p/> The study demonstrated that the scores on all outcome variables used in the follow-up study improved significantly from the time of assessment to the time of discharge for the clients who attended the CPC treatment program. These improvements declined over time, but remained significantly improved from the admission scores. (Wilks Ë=.501, F(1,48)=4.788, p=.000) However, the study was unable to demonstrate any significant differences between the treatment and control groups on any of the outcome measures at the time of the study follow-up.(Wilks Ë=.930, F (1,107) = 1.014, p=.430) There were several limitations to this study, including the use of a non-randomized control group and the method of recruitment, which may have introduced bias into the study and affected the ability to effectively explain this finding.<p/>

A survey of the existing literature indicates that optimization on the power management logic of hybrid electric vehicle is mostly performed after the design of the powertrain architecture or the power source components are finalized. The goal of this research is to utilize Multidisciplinary Design Optimization (MDO) to automate and optimize the vehicle’s powertrain component sizes, while simultaneously determining the optimal power management logic in developing the most cost-effective system solution. A generic, modular, and flexible vehicle model utilizing a backward-looking architecture is created using scalable powertrain components. The objective of the research work is to study the energy efficiency of the vehicle system, where the dynamics of the vehicle is not of concern; a backward-looking architecture could be used to compute the power consumption and the overall efficiency accurately while minimizing the required computing resource. An optimization software platform utilizing multidisciplinary design optimization approach is implemented containing the generic vehicle model and an optimizer of the user’s choice. The software model is created in the MATLAB/Simulink environment, where the optimization code and the powertrain component properties are implemented using m-files, and the power consumption calculations of the vehicle system are performed in Simulink. Furthermore, a feature-based optimization technique is developed with the motivation of significantly reducing the simulation run-time. To demonstrate the capabilities of the developed approach and contributions of the research, two optimization case studies are undertaken: (i) series hybrid electric vehicles, and (ii) police vehicle anti-idling system. As the first case study, a plug-in battery-only series hybrid electric vehicle with similar power components as the Chevrolet Volt is created, where the battery size and the power management logic are simultaneously optimized. The objective function of the optimizer is defined from the financial cost perspective, where the objective is to minimize the initial cost of batteries, gasoline and electricity consumption over a period of five years, and the carbon tax as a penalty function for fuel emissions. The battery-only series hybrid electric vehicle is subsequently extended to include ultracapacitors, and the optimization process is expanded to the rest of the powertrain components and power management logic. A comparison between the optimization algorithms found that only genetic algorithm (GA) was capable of finding the optimal solution during a full simulation, while simulated annealing and pattern search were not able to converge to any solution after a 24-hour period. A comparison between the full genetic algorithm optimization and the feature-based (FB) method with secondary optimization found that although the final cost function of the FB methodology is higher than that of the full GA optimization, the total simulation run-time is approximately ten times less using the FB method. The behaviour of the solutions found via both methods exhibited almost identical characteristics, further confirming the validity of the feature-based methodology. Finally, a benchmarking comparison found that with more accurate manufacturers’ component data and additional appropriate performance requirements, the proposed software platform will be capable of predicting a solution that is comparable to the Chevrolet Volt. The second case study involves optimizing an anti-idling system for police vehicles using the same optimization algorithm and generic vehicle model. The goal of the optimization study is to select an additional battery and determine the power management logic to reduce the engine idling time of a police vehicle. It is found that depending on the SOC threshold, the duration of time over which the engine is activated varies in a non-linear fashion, where local minima and maxima exist. A design study confirmed that by utilizing the anti-idling system, significant cost reduction can be realized when compared to one without the anti-idling system. A comparison between the various optimization algorithms showed that the feature-based optimization can obtain a relatively accurate solution while reducing simulation time by approximately 90%. This significant reduction in simulation time warrants the feature-based optimization technique a powerful tool for vehicle design. Due to the high cost of the electrical energy storage components, it is currently still more cost-effective to use the fossil fuel as the primary energy source for transportation. However, given the rise of fuel cost and the advancement in the electrical energy storage technology, it is inevitable that the cost of the electrical and chemical energy storage method will reach a balance point. The proposed optimization platform allows the user the capability and flexibility to obtain the optimal vehicle solution with ease at any given time in the future.

The Chronic Pain Center (CPC) in Saskatoon offers a multidisciplinary treatment program whose goals are to facilitate improved coping skills, function and well-being, and to promote self-reliant lifestyles. They have documented a statistically significant improvement on several measures of physical and social functioning at the completion of the six week program, but to date have no formal evaluation of the long term effects.<p/> The purpose of this study was to re-evaluate the CPC clients (treatment group) at least one year following their completion of the treatment program to determine if they had maintained those improvements and also to compare them to the group of clients (control group) who underwent initial multidisciplinary assessment at the Centre, but did not attend the six week treatment program. Evaluation by mail out questionnaires assessed several important aspects of chronic pain. A 34% response rate resulted in 142 participants for this study.<p/> Data analyses involved a multi-stage process of univariate, bivariate and multivariate analyses. For the first goal, evaluating changes in the treatment group over time, the outcome variables considered had been administered at three points in time: admission to the CPC program, discharge from the six week program, and at study follow-up. For the second goal, the treatment and control groups were compared at one point in time; the study follow-up.<p/> The study demonstrated that the scores on all outcome variables used in the follow-up study improved significantly from the time of assessment to the time of discharge for the clients who attended the CPC treatment program. These improvements declined over time, but remained significantly improved from the admission scores. (Wilks Ë=.501, F(1,48)=4.788, p=.000) However, the study was unable to demonstrate any significant differences between the treatment and control groups on any of the outcome measures at the time of the study follow-up.(Wilks Ë=.930, F (1,107) = 1.014, p=.430) There were several limitations to this study, including the use of a non-randomized control group and the method of recruitment, which may have introduced bias into the study and affected the ability to effectively explain this finding.<p/>