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- All Subjects: Systems
- Creators: Colbourn, Charles J.
- Creators: Jianguo, Wu
- Resource Type: Text
Description
Sustainability is intrinsically interdisciplinary, but the implementation of nontraditional pedagogy in this area is in its infancy. I aim to show that music can be a model to demonstrate the protean systems that consistently involve each of us. The connection between systems thinking and musical improvisation is evident in musical improvisation ensembles; it is a system unto itself with individual players connected through their musical composition. Musical improvisation allows the players to learn about systems and system behaviors. Such ability to identify and understand the underlying dynamics involved in complex social-ecological systems is fundamental to taking advantage of leverage points and working towards a sustainable future. I use music and musical improvisation to demonstrate the three concept groups of the systems thinking competency: 1) Variables, structures and functions 2) Resilience, self-organization and hierarchy and 3) Scales and domains. These parts constitute complex systems and are made easier with the analogy of music that provides a more representative language for discussing them in an intuitive way. Furthermore, improvisation activities provide a method and space for these future practitioners to rehearse working with systems. From accepting the nature of systems, one is accepting of their role in the system, which enables them to make changes. Musical improvisation is a valuable method to systems thinking because it requires future practitioners to engage in mindfulness, because it demands remaining in an intuitive stance so to be able to respond (not react) thoughtfully. My thesis will explore how the practice of musical improvisation can enhance the understanding of the three systems thinking content groups and to argue that such practice is unique and necessary as it provides opportunities to rehearse being effective change agents.
ContributorsEller, Maria Sara (Author) / Jianguo, Wu (Thesis director) / Kaplan, Robert (Committee member) / School of Sustainability (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Complex systems are pervasive in science and engineering. Some examples include complex engineered networks such as the internet, the power grid, and transportation networks. The complexity of such systems arises not just from their size, but also from their structure, operation (including control and management), evolution over time, and that people are involved in their design and operation. Our understanding of such systems is limited because their behaviour cannot be characterized using traditional techniques of modelling and analysis.
As a step in model development, statistically designed screening experiments may be used to identify the main effects and interactions most significant on a response of a system. However, traditional approaches for screening are ineffective for complex systems because of the size of the experimental design. Consequently, the factors considered are often restricted, but this automatically restricts the interactions that may be identified as well. Alternatively, the designs are restricted to only identify main effects, but this then fails to consider any possible interactions of the factors.
To address this problem, a specific combinatorial design termed a locating array is proposed as a screening design for complex systems. Locating arrays exhibit logarithmic growth in the number of factors because their focus is on identification rather than on measurement. This makes practical the consideration of an order of magnitude more factors in experimentation than traditional screening designs.
As a proof-of-concept, a locating array is applied to screen for main effects and low-order interactions on the response of average transport control protocol (TCP) throughput in a simulation model of a mobile ad hoc network (MANET). A MANET is a collection of mobile wireless nodes that self-organize without the aid of any centralized control or fixed infrastructure. The full-factorial design for the MANET considered is infeasible (with over 10^{43} design points) yet a locating array has only 421 design points.
In conjunction with the locating array, a ``heavy hitters'' algorithm is developed to identify the influential main effects and two-way interactions, correcting for the non-normal distribution of the average throughput, and uneven coverage of terms in the locating array. The significance of the identified main effects and interactions is validated independently using the statistical software JMP.
The statistical characteristics used to evaluate traditional screening designs are also applied to locating arrays.
These include the matrix of covariance, fraction of design space, and aliasing, among others. The results lend additional support to the use of locating arrays as screening designs.
The use of locating arrays as screening designs for complex engineered systems is promising as they yield useful models. This facilitates quantitative evaluation of architectures and protocols and contributes to our understanding of complex engineered networks.
As a step in model development, statistically designed screening experiments may be used to identify the main effects and interactions most significant on a response of a system. However, traditional approaches for screening are ineffective for complex systems because of the size of the experimental design. Consequently, the factors considered are often restricted, but this automatically restricts the interactions that may be identified as well. Alternatively, the designs are restricted to only identify main effects, but this then fails to consider any possible interactions of the factors.
To address this problem, a specific combinatorial design termed a locating array is proposed as a screening design for complex systems. Locating arrays exhibit logarithmic growth in the number of factors because their focus is on identification rather than on measurement. This makes practical the consideration of an order of magnitude more factors in experimentation than traditional screening designs.
As a proof-of-concept, a locating array is applied to screen for main effects and low-order interactions on the response of average transport control protocol (TCP) throughput in a simulation model of a mobile ad hoc network (MANET). A MANET is a collection of mobile wireless nodes that self-organize without the aid of any centralized control or fixed infrastructure. The full-factorial design for the MANET considered is infeasible (with over 10^{43} design points) yet a locating array has only 421 design points.
In conjunction with the locating array, a ``heavy hitters'' algorithm is developed to identify the influential main effects and two-way interactions, correcting for the non-normal distribution of the average throughput, and uneven coverage of terms in the locating array. The significance of the identified main effects and interactions is validated independently using the statistical software JMP.
The statistical characteristics used to evaluate traditional screening designs are also applied to locating arrays.
These include the matrix of covariance, fraction of design space, and aliasing, among others. The results lend additional support to the use of locating arrays as screening designs.
The use of locating arrays as screening designs for complex engineered systems is promising as they yield useful models. This facilitates quantitative evaluation of architectures and protocols and contributes to our understanding of complex engineered networks.
ContributorsAldaco-Gastelum, Abraham Netzahualcoyotl (Author) / Syrotiuk, Violet R. (Thesis advisor) / Colbourn, Charles J. (Committee member) / Sen, Arunabha (Committee member) / Montgomery, Douglas C. (Committee member) / Arizona State University (Publisher)
Created2015