A unique pedagogical approach is used to teach the fundamentals of communication systems. The ebook contains 348 figures, of which 104 are interactive graphics. In-line questions provide the students with rapid feedback regarding their understanding of the material. The goal was to bring the material to life through the use of student-driven interactive graphics, dynamic performance metric calculations and in-line questions. The study rewards candidates for multimedia narratives that recognize those moments when the response to the design did not go to plan.Īn open educational resources ebook written in Mathematica is described. Study design rewards risk taking through its rubric-assessed processes of intention development, making and comprehensive evaluation of response, processes and performance. It rewards candidates for risk taking in the development of integrated electromechanical responses that are modeled and situated in a system. The study design is a deep STEM offering for matriculation level.
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A range of key circuits and code fragments are expressed as building blocks for learners to design, conduct, analyze, critique and display meaningful research. Key engineering goals include using a project management approach to optimize system efficiency and performance through agile processes. The study considers the interactions of systems with people, society and ecosystems. Students test and verify that the system is integrated, evaluate how the completed system meets the documented intention and reflect on the systems engineering process to create a design outcome.
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Integral to the study design is the identification and quantification of systems goals, the generation of system designs, trial and error, justified design tradeoffs, modeling and the implementation of a response. The Victorian Curriculum and Assessment Authority Systems Engineering Study involves the design, production, operation, evaluation and iteration of integrated systems. Finally, we demonstrate on an example that the neural-PK/PD model improves on a state-of-the-art model with respect to metrics for temporal prediction and enable the prediction of patient response time course with different dosing regimens. In particular, the forward Euler time stepping in the numerical approximation of the underlying ODE system can be compactly represented and visualized using the available functionalities offered by the Wolfram Language. We demonstrate how the neural network functionalities of the Wolfram Language have enabled the assembly of such models from component layers into network submodules in an efficient manner. By combining this novel methodology with key pharmacological principles, we have developed the neural-PK/PD modeling framework with the aim of automating model construction from data. Recently, advancements in the neural ordinary differential equation (neural ODE) methodology have opened up a new modeling paradigm, such that the governing equations can be learned directly from data. This requires considerable human expertise and trial and error in devising and identifying the appropriate model equations.
The analyses of patient response time courses following doses of therapeutics are currently performed using pharmacokinetic/pharmacodynamic (PK/PD) methodologies, based on differential equations.
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