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Description
Nonregular screening designs can be an economical alternative to traditional resolution IV 2^(k-p) fractional factorials. Recently 16-run nonregular designs, referred to as no-confounding designs, were introduced in the literature. These designs have the property that no pair of main effect (ME) and two-factor interaction (2FI) estimates are completely confounded. In

Nonregular screening designs can be an economical alternative to traditional resolution IV 2^(k-p) fractional factorials. Recently 16-run nonregular designs, referred to as no-confounding designs, were introduced in the literature. These designs have the property that no pair of main effect (ME) and two-factor interaction (2FI) estimates are completely confounded. In this dissertation, orthogonal arrays were evaluated with many popular design-ranking criteria in order to identify optimal 20-run and 24-run no-confounding designs. Monte Carlo simulation was used to empirically assess the model fitting effectiveness of the recommended no-confounding designs. The results of the simulation demonstrated that these new designs, particularly the 24-run designs, are successful at detecting active effects over 95% of the time given sufficient model effect sparsity. The final chapter presents a screening design selection methodology, based on decision trees, to aid in the selection of a screening design from a list of published options. The methodology determines which of a candidate set of screening designs has the lowest expected experimental cost.
ContributorsStone, Brian (Author) / Montgomery, Douglas C. (Thesis advisor) / Silvestrini, Rachel T. (Committee member) / Fowler, John W (Committee member) / Borror, Connie M. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This dissertation explores different methodologies for combining two popular design paradigms in the field of computer experiments. Space-filling designs are commonly used in order to ensure that there is good coverage of the design space, but they may not result in good properties when it comes to model fitting. Optimal

This dissertation explores different methodologies for combining two popular design paradigms in the field of computer experiments. Space-filling designs are commonly used in order to ensure that there is good coverage of the design space, but they may not result in good properties when it comes to model fitting. Optimal designs traditionally perform very well in terms of model fitting, particularly when a polynomial is intended, but can result in problematic replication in the case of insignificant factors. By bringing these two design types together, positive properties of each can be retained while mitigating potential weaknesses. Hybrid space-filling designs, generated as Latin hypercubes augmented with I-optimal points, are compared to designs of each contributing component. A second design type called a bridge design is also evaluated, which further integrates the disparate design types. Bridge designs are the result of a Latin hypercube undergoing coordinate exchange to reach constrained D-optimality, ensuring that there is zero replication of factors in any one-dimensional projection. Lastly, bridge designs were augmented with I-optimal points with two goals in mind. Augmentation with candidate points generated assuming the same underlying analysis model serves to reduce the prediction variance without greatly compromising the space-filling property of the design, while augmentation with candidate points generated assuming a different underlying analysis model can greatly reduce the impact of model misspecification during the design phase. Each of these composite designs are compared to pure space-filling and optimal designs. They typically out-perform pure space-filling designs in terms of prediction variance and alphabetic efficiency, while maintaining comparability with pure optimal designs at small sample size. This justifies them as excellent candidates for initial experimentation.
ContributorsKennedy, Kathryn (Author) / Montgomery, Douglas C. (Thesis advisor) / Johnson, Rachel T. (Thesis advisor) / Fowler, John W (Committee member) / Borror, Connie M. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Surgery is one of the most important functions in a hospital with respect to operational cost, patient flow, and resource utilization. Planning and scheduling the Operating Room (OR) is important for hospitals to improve efficiency and achieve high quality of service. At the same time, it is a complex task

Surgery is one of the most important functions in a hospital with respect to operational cost, patient flow, and resource utilization. Planning and scheduling the Operating Room (OR) is important for hospitals to improve efficiency and achieve high quality of service. At the same time, it is a complex task due to the conflicting objectives and the uncertain nature of surgeries. In this dissertation, three different methodologies are developed to address OR planning and scheduling problem. First, a simulation-based framework is constructed to analyze the factors that affect the utilization of a catheterization lab and provide decision support for improving the efficiency of operations in a hospital with different priorities of patients. Both operational costs and patient satisfaction metrics are considered. Detailed parametric analysis is performed to provide generic recommendations. Overall it is found the 75th percentile of process duration is always on the efficient frontier and is a good compromise of both objectives. Next, the general OR planning and scheduling problem is formulated with a mixed integer program. The objectives include reducing staff overtime, OR idle time and patient waiting time, as well as satisfying surgeon preferences and regulating patient flow from OR to the Post Anesthesia Care Unit (PACU). Exact solutions are obtained using real data. Heuristics and a random keys genetic algorithm (RKGA) are used in the scheduling phase and compared with the optimal solutions. Interacting effects between planning and scheduling are also investigated. Lastly, a multi-objective simulation optimization approach is developed, which relaxes the deterministic assumption in the second study by integrating an optimization module of a RKGA implementation of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to search for Pareto optimal solutions, and a simulation module to evaluate the performance of a given schedule. It is experimentally shown to be an effective technique for finding Pareto optimal solutions.
ContributorsLi, Qing (Author) / Fowler, John W (Thesis advisor) / Mohan, Srimathy (Thesis advisor) / Gopalakrishnan, Mohan (Committee member) / Askin, Ronald G. (Committee member) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2010
Description

NASA has partnered with multiple colleges, including ASU, on a mission to study an asteroid called Psyche. Psyche is the first asteroid discovered made of metal, mostly iron, that is close enough for us to study and could give insight into what Earth’s core is like. The mission plans and

NASA has partnered with multiple colleges, including ASU, on a mission to study an asteroid called Psyche. Psyche is the first asteroid discovered made of metal, mostly iron, that is close enough for us to study and could give insight into what Earth’s core is like. The mission plans and research documents on how the various measurement tools work are not engaging to those without a background in STEM. This serves as inspiration to make a web-based game in order to make the information more engaging to the player. This web-based game will take the user through the Psyche mission going from the assembly of the measurement tools all the way to when the satellite is orbiting the asteroid. The creative project consisted of creating a simulation for a young audience, between ages 10 and 18, to experience what the mission could look like once the satellite is at the Psyche asteroid and what the data collected could mean. The asteroid could have been formed through a process called the dynamo process or it could be a piece of a larger parent body. It could be made mostly of metal or silicates, which will be determined during the mission. These are some of the results that will be generalized and relayed to the player. This creative project includes the four main sections of the orbit phase of the mission in which the users will perform tasks to collect some data in order to see some of the generalized possible results of the study of Psyche. Some of the data collected would be the amount of metal making up the asteroid and figuring out what the gravitational pull is. The first main section will use the magnetometer, the second section will use the multispectral imager, the third section will use X-Band Radio Waves, and the fourth section will use the gamma ray and neutron spectrometer.

ContributorsOgar, Scott (Author) / Carter, Lynn (Thesis director) / Chavez-Echeagaray, Maria Elena (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
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Description
The instruction of students in computer science concepts can be enhanced by creating programmable simulations and games. ASU VIPLE, which is a framework used to control simulations, robots, and for IoT applications, can be used as an educational tool. Further, the Unity engine allows the creation of 2D and 3D

The instruction of students in computer science concepts can be enhanced by creating programmable simulations and games. ASU VIPLE, which is a framework used to control simulations, robots, and for IoT applications, can be used as an educational tool. Further, the Unity engine allows the creation of 2D and 3D games. The development of basic minigames in Unity can provide simulations for students to program. One can run the Unity minigame and their corresponding VIPLE script to control them over a network connection as well as locally. The minigames conform to the robot output and robot input interfaces supported by VIPLE. With this goal in mind, a snake game, a space shooter game, and a runner game have been created as Unity simulations, which can be controlled by scripts made using VIPLE. These games represent simulated environments that, with movement output and sensor input, students can program simply and externally from VIPLE to help learn robotics and computer science principles.
ContributorsChristensen, Collin Riley (Author) / Chen, Yinong (Thesis director) / Kobayashi, Yoshihiro (Committee member) / Computer Science and Engineering Program (Contributor) / Computing and Informatics Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
The Migration Framework and Simulator is a combination of C# framework / library and Unity simulation tool used for studying basic migration patterns across the US. Users interact with the
Unity simulation tool by implementing political policies or adjusting values via sliders, buttons, etc., which will alter the values in the

The Migration Framework and Simulator is a combination of C# framework / library and Unity simulation tool used for studying basic migration patterns across the US. Users interact with the
Unity simulation tool by implementing political policies or adjusting values via sliders, buttons, etc., which will alter the values in the framework. The user can then use the simulation interface to view different estimated population values for categories of people, such as regional differences, education levels, and more.
ContributorsLarsen, Joseph (Co-author) / Spangler, Braydon (Co-author) / Kobayashi, Yoshihiro (Thesis director) / Nelson, Brian (Committee member) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description

The process of learning a new skill can be time consuming and difficult for both the teacher and the student, especially when it comes to computer modeling. With so many terms and functionalities to familiarize oneself with, this task can be overwhelming to even the most knowledgeable student. The purpose

The process of learning a new skill can be time consuming and difficult for both the teacher and the student, especially when it comes to computer modeling. With so many terms and functionalities to familiarize oneself with, this task can be overwhelming to even the most knowledgeable student. The purpose of this paper is to describe the methodology used in the creation of a new set of curricula for those attempting to learn how to use the Dynamic Traffic Simulation Package with Multi-Resolution Modeling. The current DLSim curriculum currently relates information via high-concept terms and complicated graphics. The information in this paper aims to provide a streamlined set of curricula for new users of DLSim, including lesson plans and improved infographics.

ContributorsMills, Alexander (Author) / Zhou, Xuesong (Thesis director) / Chen, Yinong (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
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ContributorsMills, Alexander (Author) / Zhou, Xuesong (Thesis director) / Chen, Yinong (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor)
Created2022-05
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ContributorsMills, Alexander (Author) / Zhou, Xuesong (Thesis director) / Chen, Yinong (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor)
Created2022-05
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ContributorsMills, Alexander (Author) / Zhou, Xuesong (Thesis director) / Chen, Yinong (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor)
Created2022-05