Between Dec 19, 2024 and Jan 2, 2025, datasets can be submitted to DRUM but will not be processed until after the break. Staff will not be available to answer email during this period, and will not be able to provide DOIs until after Jan 2. If you are in need of a DOI during this period, consider Dryad or OpenICPSR. Submission responses to the UDC may also be delayed during this time.

Browsing by Subject "Graph theory"

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Design of Control Configurations for Complex Process Networks
    (2015-05) Heo, Seongmin
    Tight integration is the rule rather than the exception in chemical and energy plants. Despite the significant economic benefits which result from efficient utilization of energy/material resources, effective control of plants with such integration becomes challenging; the network-level dynamics emerging from process interconnections and the model complexity of such plants limit the effectiveness of decentralized control approaches traditionally followed in plant-wide control. The development of effective control methods for complex integrated plants is a challenging, open problem. This thesis proposes methods to develop effective control strategies for two classes of process networks. In the first part of the thesis, a class of process networks, in which slow network-level dynamics is induced by large rates of energy and/or material recycle, is considered. A graph theoretic algorithm is developed for such complex material integrated process networks to i) identify the material balance variables evolving in each time scale, and ii) design hierarchical control structures by classifying potential manipulated inputs and controlled outputs in each time scale. The application of a similar algorithm developed for energy integrated networks to representative chemical processes is also presented. The second part of the thesis focuses on generic process networks where tight integration is not necessarily reflected on a segregation of energy and/or material flows. A method is developed to systematically synthesize control configurations with favorable structural coupling, using relative degree as a measure of such coupling. Hierarchical clustering methods are employed to generate a hierarchy of control configurations ranging from fully decentralized ones to a fully centralized one. An agglomerative hierarchical clustering method is first developed, in which groups of inputs/outputs are merged successively to form fewer and larger groups that are strongly connected topologically. Then, a divisive hierarchical clustering method is developed, in which groups of inputs/outputs are decomposed recursively into smaller groups. The developed methods are applied to typical chemical process networks.
  • Thumbnail Image
    Item
    Developmental trade-offs following early life stress: Assessing the cost of accelerated maturation in emotion regulation circuitry
    (2020-07) Herzberg, Max
    Experiences of early life stress begin a developmental cascade that alters a number of stress biology systems. These physiological stress systems interact with atypical early environments to shape the development of crucial brain systems in the context of early life stress. Among the differences in brain development following early life stress are decreased cortical volume, blunted activity in the ventral striatum, and increased amygdala activity to negative images following early institutional care and childhood maltreatment (Goff et al., 2013; Hodel et al., 2018; Tottenham et al., 2011). Further, previous research has reported accelerated maturation of the functional connectivity of the amygdala – medial prefrontal cortex emotion regulation circuit following early life stress (Gee et al., 2013). Differences in behavior have also been reported, including lower executive function scores, increased impulsivity, and difficulty with risky-decision making following childhood maltreatment and institutional care (Cowell et al., 2015; Herzberg et al., 2018). The studies in this dissertation investigated the possibility of a developmental trade-off between emotion circuitry and higher-order cognition circuits underlying the behaviors known to be affected by early life stress. Two studies, one studying youth adopted from international institutions and another examining adults with prospectively assessed histories of childhood maltreatment, investigated the possibility of a developmental trade-off. Results indicated more mature patterns of amygdala – medial prefrontal cortex functional connectivity in adopted compared to non-adopted youth, consistent with previous research. Further, group differences in the within-system connectivity of the dorsal attention network were found. In contrast, no group differences were evident between adults with childhood maltreatment histories compared to those without. There was however, a significant relationship between adaptive behavior functioning in adulthood and variance in community size, a whole-brain measure of resting-state network maturity. Measures of functional connectivity were significant predictors of behavioral function in both samples. Taken together, the results of these studies do not support the notion of a developmental trade-off in resting-state functional connectivity following early life stress. Future research using longitudinal imaging designs is needed to extend this work and to fully address the question of a developmental trade-off following early adversity.
  • Thumbnail Image
    Item
    Dynamics and control theory of quantum walks on graphs
    (University of Minnesota. Institute for Mathematics and Its Applications, 2010-06) Albertini, Francesca; D’Alessandro, Domenico
  • Thumbnail Image
    Item
    Graph Representation And Distributed Control Of Lumped And Distributed Parameter System Networks
    (2019-05) Moharir, Manjiri
    Chemical plants are complex, integrated networks of individual process systems. The process system dynamics along with the interconnections among them make the task of controlling chemical plants challenging. Distributed control is a promising approach towards achieving plant-wide control of tightly integrated networks. The identification of sparsely interacting sub-networks in a given chemical network is key towards achieving superior performance from the distributed control structure. To this end, community detection algorithms have been adopted to determine the optimal decompositions for chemical networks by maximization of modularity. These algorithms are based on equation graph representations of the network. For lumped parameter system (LPS) networks, such representations are standard. Since chemical networks usually comprise lumped as well as distributed parameter systems (DPSs), this thesis aims at incorporating within the framework described above, the variables and topology of DPSs, to develop a unified framework to obtain optimal network decompositions (control structures) for distributed control. To this end, an equation graph representation for a generic DPS and a parameter which captures the strength of structural interactions among its variables analogous to relative degree in LPSs are proposed. A relationship is established between the length of the input-output path in the equation graph and the structural interaction parameter, which enables the incorporation of DPSs variables in the graph based community detection algorithms. Also, since in chemical networks, often the measurement of the entire state is not available and estimation of the unmeasured variables is a computationally expensive task, this thesis also addresses the problem of combined distributed state estimation and distributed control, using community detection for determining network decompositions for estimation as well as control.