Physical Sciences and Mathematics Commons^™

An Overview Of Elements And Relations: Aspects Of A Scientific Metaphysics, Martin Zwick

Systems Science Faculty Publications and Presentations

A talk on my book, Elements and Relations: Aspects of a Scientific Metaphysics. Book description:

This book develops the core proposition that systems theory is an attempt to construct an “exact and scientific metaphysics,” a system of general ideas central to science that can be expressed mathematically. Collectively, these ideas would constitute a non-reductionist “theory of everything” unlike what is being sought in physics. Inherently transdisciplinary, systems theory offers ideas and methods that are relevant to all of the sciences and also to professional fields such as systems engineering, public policy, business, and social work. To demonstrate the generality …

Reducing Opioid Use Disorder And Overdose Deaths In The United States: A Dynamic Modeling Analysis, Erin J. Stringfellow, Tse Yang Lim, Keith Humphreys, Catherine Digennero, Celia Stafford, Elizabeth Beaulieu, Jack Homer, Wayne Wakeland, Multiple Additional Authors

Systems Science Faculty Publications and Presentations

Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; …

Modeling Post-Fire Successional Trajectories Under Climate Change In Interior Alaska Using Landis Ii, Shelby A. Weiss

Systems Science Friday Noon Seminar Series

Alaska boreal forest ecosystems are experiencing a greater frequency of wildfire relative to the region’s historic fire regime. These increases in fire frequency, as well as annual burned area, increase the probability of forests re-burning within shorter intervals than were experienced historically. Such changes to the fire regime have the potential to shift successional trajectories in this ecosystem. To better understand potential changes in vegetation composition following short-interval, repeat fires, we are using LANDIS-II, a forest landscape model, to simulate changes in forest composition in response to climate change and increasing fire frequency. This seminar will include a description of …

Systems Thinking As A Design Process, Elizabeth Lockwood

Systems Science Friday Noon Seminar Series

During my master’s degree I analyzed sustainable practices in the built environment. What came from that work was a deep level of understanding that the current practices and rating systems appeared to be technical approaches to a larger system at play. I realized I have a gift to see hidden connections and find links between systems. Currently I use systems mapping as part of the design process to unearth the hidden elements in a system. I believe it is important to understand where designers, clients and stakeholders can insert themselves into a system. Part of this understanding is having empathy …

The Complexities Of Open Data, Hector Dominguez

Systems Science Friday Noon Seminar Series

Hector Dominguez is the current Open Data Coordinator at the City of Portland, and there are several lessons learned and strategies developed in the several months of work in this position. Hector will share some challenges on creating trusted and reliable data and information services, as well as the opportunities to work with Urban Data to resolve city challenges and to support achieving the City's goals in the coming years.

In this talk, Hector will share how modeling and defining the right metrics are not the only factors to implementing a citywide program, but rather, how ethics, communications and strategy …

Latent Space Models For Temporal Networks, Jasper Alt

Systems Science Friday Noon Seminar Series

In many contexts we may expect the structure of networks to be derived from some kind of abstract distance between actors. We refer to this phenomenon as homophily: like nodes connect to like. For example, people with similar beliefs may be more likely to form social relations.

We formalize this notion by positioning the nodes in a latent space representing the possible values of the homophilous attributes. Realistically, we should expect latent attributes like beliefs to change over time in some nontrivial way, and the structures of temporal networks to evolve accordingly. We introduce a model of latent space dynamics …

The Changing Moral Mirror Of Society: From Human To Artifical Intelligent Systems, Gary Langford, Teresa Langford

Engineering and Technology Management Faculty Publications and Presentations

Management of technology and its development carry along the responsibility and consequences for interactions between Human and Artificial Intelligent Systems (AIS). In spite of all good intentions, the effects and repercussions of conflicts between Human and the systems built with intent to assist Human may be proceeding along the path that will recognize a dismal mistake in judgment. Dreadful and intolerable impositions on Human behavior may arise regardless of how AIS is designed. That is not to say progress should cease, but rather to make the case that intensely determined efforts need to delve into the uses and implications of …

Domain Process Model Overcome Limitations Of Engineering Models For Developing Artificial Intelligent Systems, Gary O. Langford, John Green, Daniel P. Burns, Alexander Keller, Dean C. Schmidt

Engineering and Technology Management Faculty Publications and Presentations

The integrated set of prognostic domains (ISPD) of technology presented here provides a normative means to construct a wholly new process model for guiding Technology Management of Artificial Intelligent Systems (AIS). Seventeen domains represent all-inclusive stakeholder perspectives that encapsulate lifecycle analyses, evaluations, feasibilities, and tradeoffs with the domain contexts. Following Systems Model-Based thinking (SMBT), a postulated focal point interaction is the entry condition from which each domain is considered and thereafter traversed. Domains are interactive with each other through concurrent, iterative, recursive, and non-recursive processes. This interactive work continues until the completion milestones of each domain are satisfied. Techniques such …

Computational Methods For Asynchronous Basins, Ian H. Dinwoodie

Mathematics and Statistics Faculty Publications and Presentations

For a Boolean network we consider asynchronous updates and define the exclusive asynchronous basin of attraction for any steady state or cyclic attractor. An algorithm based on commutative algebra is presented to compute the exclusive basin. Finally its use for targeting desirable attractors by selective intervention on network nodes is illustrated with two examples, one cell signalling network and one sensor network measuring human mobility.

Prediction: The Quintessential Model Validation Test, Wayne Wakeland

Systems Science Friday Noon Seminar Series

It is essential to objectively test how well policy models predict real world behavior. The method used to support this assertion involves the review of three SD policy models emphasizing the degree to which the model was able to fit the historical outcome data and how well model-predicted outcomes matched real world outcomes as they unfolded. Findings indicate that while historical model agreement is a favorable indication of model validity, the act of making predictions without knowing the actual data, and comparing these predictions to actual data, can reveal model weaknesses that might be overlooked when all of the available …

Systems Ideas For The Scientific And Societal Imperatives Of The Coastal Ocean: Case Of The Bp Oil Gusher In The Gulf Of Mexico, Spring & Summer 2010, Christopher Mooers

Systems Science Friday Noon Seminar Series

In recent decades, great progress has been made in advancing the scientific understanding of the coastal ocean (i.e., the 200 nautical mile Exclusive Economic Zone (EEZ)) across a broad set of disciplines. Simultaneously, the societal use of the coastal ocean has skyrocketed through, for example, increased shipping & boating, sports & commercial fishing, and exploitation of non-living resources, such as, oil & gas extraction and sand & gravel mining. International law and national policy assign coastal nations the responsibility for stewardship (i.e., wise management) of their respective EEZs. The scope of the stewardship and applications can be summarized as (1) …

Integer Optimization And Computational Algebraic Topology, Bala Krishnamoorthy

Systems Science Friday Noon Seminar Series

We present recently discovered connections between integer optimization, or integer programming (IP), and homology. Under reasonable assumptions, these results lead to efficient solutions of several otherwise hard-to-solve problems from computational topology and geometric analysis. The main result equates the total unimodularity of the boundary matrix of a simplicial complex to an algebraic topological condition on the complex (absence of relative torsion), which is often satisfied in real-life applications . When the boundary matrix is totally unimodular, the problem of finding the shortest chain homologous under Z (ring of integers) to a given chain, which is inherently an integer program, can …

On The Effect Of Criticality And Topology On Learning In Random Boolean Networks, Alireza Goudarzi

Systems Science Friday Noon Seminar Series

Random Boolean networks (RBN) are discrete dynamical systems composed of N automata with a binary state, each of which interacts with other automata in the network. RBNs were originally introduced as simplified models of gene regulation. In this presentation, I will present recent work done conjointly with Natali Gulbahce (UCSF), Thimo Rohlf (MPI, CNRS), and Christof Teuscher (PSU). We extend the study of learning in feedforward Boolean networks to random Boolean networks (RBNs) and systematically explore the relationship between the learning capability, the network topology, the system size N, the training sample T, and the complexity of the computational task. …

Random Automata Networks: Why Playing Dice Is Not A Vice, Christof Teuscher

Systems Science Friday Noon Seminar Series

Random automata networks consist of a set of simple compute nodes interacting with each other. In this generic model, one or multiple model parameters, such as the the node interactions and/or the compute functions, are chosen at random. Random Boolean Networks (RBNs) are a particular case of discrete dynamical automata networks where both time and states are discrete. While traditional RBNs are generally credited to Stuart Kauffman (1969), who introduced them as simplified models of gene regulation, Alan Turing proposed unorganized machines as early as 1948. In this talk I will start with Alan Turing's early work on unorganized machines, …

Biologically Inspired Computing: The Darpa Synapse Program & The Hierarchical Temporal Memory, Dan Hammerstrom

Systems Science Friday Noon Seminar Series

This presentation provides an update on biologically inspired computation. In particular, it focuses on two important developments in this area, the DARPA SyNAPSE program (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) and the HTM (Hierarchical Temporal Memory) being developed by Numenta.

The SyNAPSE Program’s ultimate goal is to build a low-power, compact electronic chip combining novel analog circuit design and a neuroscience-inspired architecture that can address a wide range of cognitive abilities: perception, planning, decision making and motor control. According to DARPA program manager Todd Hylton, “Our research progress in this area is unprecedented, No suitable electronic synaptic device that …

Understanding Classification Decisions For Object Detection, Will Landecker, Michael David Thomure, Melanie Mitchell

Systems Science Friday Noon Seminar Series

Computer vision systems are traditionally tested in the object detection paradigm. In these experiments, a vision system is asked whether or not a specific object--for example an animal--occurs in a given image. A system that often answers correctly is said to be very accurate. In this talk, we will discuss some ambiguity that exists in this measure of accuracy. We will also propose a new measure of object-detection accuracy that addresses some of this ambiguity, and apply this measure to the hierarchical "standard model" of visual cortex.

Holism And Human History, Martin Zwick

Systems Science Faculty Publications and Presentations

We want and need the ‘whole story,’ but the whole story is difficult to tell. We can reduce the magnitude of the task by taking a cue from the title of the meeting, namely “Cosmos, Nature, Culture: A Transdisciplinary Conference.” The ‘whole story’ can be divided into three stories: the story of the unfolding of the universe (‘cosmos’), the story of the evolution of life (‘nature’), and the story of human history (‘culture’). This paper focuses on the third of these. Of course, human history is rooted in nature which is a manifestation of cosmos on our planet, but its …

An Information Theoretic Methodology For Prestructuring Neural Networks, Bjorn Chambless, George G. Lendaris, Martin Zwick

Systems Science Faculty Publications and Presentations

Absence of a priori knowledge about a problem domain typically forces use of overly complex neural network structures. An information-theoretic method based on calculating information transmission is applied to training data to obtain a priori knowledge that is useful for prestructuring (reducing complexity) of neural networks. The method is applied to a continuous system, and it is shown that such prestructuring reduces training time, and enhances generalization capability.

Wholes And Parts In General Systems Methodology, Martin Zwick

Systems Science Faculty Publications and Presentations

Reconstructability analysis (RA) decomposes wholes, namely data in the form either of set-theoretic relations or multivariate probability distributions, into parts, namely relations or distributions involving subsets of variables. Data is modeled and compressed by variablebased decomposition, by more general state-based decomposition, or by the use of latent variables. Models, which specify the interdependencies among the variables, are selected to minimize error and complexity.

Prestructuring Neural Networks Via Extended Dependency Analysis With Application To Pattern Classification, George G. Lendaris, Thaddeus T. Shannon, Martin Zwick

Systems Science Faculty Publications and Presentations

We consider the problem of matching domain-specific statistical structure to neural-network (NN) architecture. In past work we have considered this problem in the function approximation context; here we consider the pattern classification context. General Systems Methodology tools for finding problem-domain structure suffer exponential scaling of computation with respect to the number of variables considered. Therefore we introduce the use of Extended Dependency Analysis (EDA), which scales only polynomially in the number of variables, for the desired analysis. Based on EDA, we demonstrate a number of NN pre-structuring techniques applicable for building neural classifiers. An example is provided in which EDA …

On Matching Ann Structure To Problem Domain Structure, George G. Lendaris, Martin Zwick, Karl Mathia

Systems Science Faculty Publications and Presentations

To achieve reduced training time and improved generalization with artificial neural networks (ANN, or NN), it is important to use a reduced complexity NN structure. A "problem" is defined by constraints among the variables describing it. If knowledge about these constraints could be obtained a priori, this could be used to reduce the complexity of the ANN before training it. Systems theory literature contains methods for determining and representing structural aspects of constrained data (these methods are herein called GSM, general systems method). The suggestion here is to use the GSM model of the given data as a pattern for …

"Large Systems", Richard Ernest Bellman

Special Collections: Oregon Public Speakers

No abstract provided.

"The Curious Behavior Of Complex Systems: Lessons From Biology", Heinz Von Foerster

Special Collections: Oregon Public Speakers

No abstract provided.

"Education For Managing Complexity", Harold A. Linstone

Special Collections: Oregon Public Speakers

No abstract provided.