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Model reuse in diverse problem solversPrice, Christopher John January 1994 (has links)
No description available.
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The prevalence of model-based reasoning in CSCOPE curriculum for sixth grade scienceGonzalez, Jose Ricardo 24 February 2012 (has links)
This research was conducted on model-based reasoning and its prevalence in CSCOPE curriculum. Communications with seven CSCOPE representatives out of twenty regions revealed that CSCOPE is simply a name, not an acronym. The primary focus of CSCOPE is to impact instructional practices in the classroom to improve student performance. This report discusses the history of CSCOPE, its framework, and its exemplar lessons. It also looks at model-based reasoning, taxonomy of models, and model-eliciting activities. The research also aims to determine if the exemplar lessons in CSCOPE can be classified as model-based. / text
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The use of scheduling and hierarchical modelling techniques for time-limited diagnosisAldea-Corrales, Aranzazu A. January 1994 (has links)
No description available.
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Hyperbolic Distributions and Transformations for Clustering Incomplete Data with Extensions to Matrix Variate NormalityPocuca, Nikola January 2023 (has links)
Under realistic scenarios, data are often incomplete, asymmetric, or of high-dimensionality.
More intricate data structures often render standard approaches infeasible due to
methodological or computational limitations. This monograph consists of four contributions each solving a specific problem within model-based clustering. An R package
is developed consisting of a three-phase imputation method for both elliptical and hyperbolic parsimonious models. A novel stochastic technique is employed to speed up
computations for hyperbolic distributions demonstrating superior performance overall. A hyperbolic transformation model is conceived for clustering asymmetrical data
within a heterogeneous context. Finally, for high-dimensionality, a framework is developed for assessing matrix variate normality within three-way datasets. All things
considered, this work constitutes a powerful set of tools to deal with the ever-growing
complexity of big data / Dissertation / Doctor of Science (PhD)
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Methodology for rapid static and dynamic model-based engine calibration and optimizationLee, Byungho 04 August 2005 (has links)
No description available.
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Time Based Requirements and Partitioning of Systems with Automatic Test Case GenerationEwing, Tony January 2008 (has links)
Automatic test case generation is a process that starts with text based functional requirements which are converted to a formal system requirements model. Once the formal system requirements model is created the automatic test case generation software creates a set of test scenarios that will verify that the requirements are all met. The automatic test case generation software accomplishes the conversion in a four step process: create base scenarios, identify unverified requirements, enhance scenarios to cover all requirements and allow black box testing, and then combine the scenarios into a single scenario tree. The automatic test case generation system outputs a set of scenarios by walking the final scenario tree. This dissertation expands on automatic test case generation for embedded systems in two major ways. The first is to extend functional automatic test case generation to allow for time based requirements as first class objects. The second is to use the automatic test case generation system to enable system partitioning decisions. The addition of time based requirements to the automatic test case generation system allows more complex systems to be developed. By providing a partitioning recommendation based on the test cases generated from the system requirements, the scope and capabilities of a single designer can be expanded to more complex systems. The resulting upgrades to the theory of automatic test case generation could be applied to the existing tools or incorporated in modern UML/SysML based design tools.
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Abstract data types and the integrated project support environment databaseJackson, A. R. January 1988 (has links)
No description available.
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Model-Based Methodology for Building Confidence in a Dynamic Measuring SystemReese, Isaac Mark 03 October 2013 (has links)
This thesis examines the special case in which a newly developed dynamic measurement system must be characterized when an accepted standard qualification procedure does not yet exist. In order to characterize this type of system, both physical experimentation and computational simulation methods will be used to build trust in this measurement system. This process of establishing credibility will be presented in the form of a proposed methodology.
This proposed methodology will utilize verification and validation methods that apply within the simulation community as the foundation for this multi-faceted approach. The methodology will establish the relationships between four key elements: physical experimentation, conceptual modeling, computational simulations, and data processing. The combination of these activities will provide a comprehensive characterization study of the system.
In order to illustrate the methodology, a case study was performed on a dynamic force measurement system owned by Sandia National Laboratories. This system was designed to measure the force required to pull a specimen to failure in tension at a user-input velocity. The results of the case study found that there was a significant measurement error occurring as the pull event involved large break loads and high velocities. 100 pull events were recorded using an experimental test assembly. The highest load conditions discovered a force measurement error of over 100%. Using computational simulations, this measurement error was reduced to less than 10%. These simulations were designed to account for the inertial effects that skew the piezoelectric load cells. This thesis displays the raw data and the corrected data for five different pull settings. The simulations designed using the methodology significantly reduced the error in all five pull settings.
In addition to the force analysis, the simulations provide insight into the complete system performance. This includes the analysis of the maximum system velocity as well as the analysis of several proposed design changes. The findings suggest that the dynamic measurement system has a maximum velocity of 28 fps, and that this maximum velocity is unaffected by the track length or the mass of the moving carriage.
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Empowering students' scientific reasoning about energy through experimentation and data analysesAbdelkareem, Hasan. January 2008 (has links)
Thesis (Ph. D.)--Michigan State University. Dept. of Curriculum, Teaching, and Educational Policy, 2008. / Title from PDF t.p. (viewed on July 7, 2009) Includes bibliographical references (p. 105-109). Also issued in print.
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Automatic Conversion of the Mathworks' Stateflow Models to C++Hannis, Melissa Katherine 14 December 2018 (has links)
Finite state machines are often used for modeling the decision logic for simulated systems. MathWorks’ Stateflow has a graphical user interface that allow users to model finite state machines. A Stateflow model can be added as a block to a Matlab/Simulink model and be executed seamlessly together. Stateflow blocks are developed as “charts” but they are natively stored as XML documents. This research explores the possibility of extracting the behavior of the finite state machines as defined in a Stateflow chart. This is done by parsing the corresponding XML document and reproducing this behavior in a C++ implementation that can be instantiated within a large, C++ based simulation system. Furthermore, the goal of this research is to develop a tool that will automatically generate an equivalent C++ representation, given an arbitrary Stateflow XML model. This research is performed in the context of developing highidelity powertrain simulations to be executed in High-Performance Computing environments.
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