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Full-Text Articles in Engineering

An Overview Of Elements And Relations: Aspects Of A Scientific Metaphysics, Martin Zwick Nov 2023

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 …


Systems Thinking Activities Used In K-12 For Up To Two Decades, Diana Fisher, Systems Thinking Association Feb 2023

Systems Thinking Activities Used In K-12 For Up To Two Decades, Diana Fisher, Systems Thinking Association

Systems Science Faculty Publications and Presentations

Infusing systems thinking activities in pre-college education (grades K-12) means updating precollege education so it includes a study of many systemic behavior patterns that are ubiquitous in the real world. Systems thinking tools include those using both paper and pencil and the computer and enhance learning in the classroom making it more student-centered, more active, and allowing students to analyze problems that have been heretofore beyond the scope of K-12 classrooms. Students in primary school have used behavior over time graphs to demonstrate dynamics described in story books, like the Lorax, and created stock-flow diagrams to describe what was needed …


Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick Jan 2023

Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick

Systems Science Faculty Publications and Presentations

This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Bayesian Networks, Support Vector Regression, and Neural Networks. The aims of the research are to identify predictive variables and obtain a new stand-alone model that improves prediction accuracy and reduces the INC (ability to increase generation) and DEC (ability to decrease generation) Resource Sufficiency Requirements for Western Energy Imbalance Market participants. This …


Data From: Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick Dec 2022

Data From: Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick

Systems Science Faculty Datasets

This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Bayesian Networks, Support Vector Regression, and Neural Networks. The aims of the research are to identify predictive variables and obtain a new stand-alone model that improves prediction accuracy and reduces the INC (ability to increase generation) and DEC (ability to decrease generation) Resource Sufficiency Requirements for Western Energy Imbalance Market participants. This …


System Dynamics Modeling For Traumatic Brain Injury: Mini-Review Of Applications, Erin S. Kenzie, Elle L. Parks, Nancy Carney, Wayne Wakeland Aug 2022

System Dynamics Modeling For Traumatic Brain Injury: Mini-Review Of Applications, Erin S. Kenzie, Elle L. Parks, Nancy Carney, Wayne Wakeland

Systems Science Faculty Publications and Presentations

Traumatic brain injury (TBI) is a highly complex phenomenon involving a cascade of disruptions across biomechanical, neurochemical, neurological, cognitive, emotional, and social systems. Researchers and clinicians urgently need a rigorous conceptualization of brain injury that encompasses nonlinear and mutually causal relations among the factors involved, as well as sources of individual variation in recovery trajectories. System dynamics, an approach from systems science, has been used for decades in fields such as management and ecology to model nonlinear feedback dynamics in complex systems. In this mini-review, we summarize some recent uses of this approach to better understand acute injury mechanisms, recovery …


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 Jun 2022

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; …


Reconstructability Analysis: Discrete Multivariate Modeling, Martin Zwick Jan 2022

Reconstructability Analysis: Discrete Multivariate Modeling, Martin Zwick

Systems Science Faculty Publications and Presentations

An introduction to Reconstructability Analysis for the Discrete Multivariate Modeling course and for other purposes.


Digitally Reporting Trail Obstructions In Forest Park, Colton S. Maybee Aug 2021

Digitally Reporting Trail Obstructions In Forest Park, Colton S. Maybee

REU Final Reports

The inclusion of technology on the trail can lead to better experiences for everyone involved in the hobby. Hikers can play a more prominent role in the maintenance of the trails by being able to provide better reports of obstructions while directly on the trail. This paper goes into the project of revamping the obstruction report system applied at Forest Park in Portland, Oregon. Most of my contributions to the project focus on mobile app development with some research into path planning algorithms related to the continuations of this project.


Forest Park Trail Monitoring, Adan Robles, Colton S. Maybee, Erin Dougherty Aug 2021

Forest Park Trail Monitoring, Adan Robles, Colton S. Maybee, Erin Dougherty

REU Final Reports

Forest Park, one of the largest public parks in the United States with over 40 trails to pick from when planning a hiking trip. One of the main problems this park has is that there are too many trails, and a lot of the trails extend over 3 miles. Due to these circumstances’ trails are not checked frequently and hikers are forced to hike trails in the area with no warnings of potential hazards they can encounter. In this paper I researched how Forest Park currently monitors its trails and then set up a goal to solve the problem. We …


Graphical Models In Reconstructability Analysis And Bayesian Networks, Marcus Harris, Martin Zwick Jul 2021

Graphical Models In Reconstructability Analysis And Bayesian Networks, Marcus Harris, Martin Zwick

Systems Science Faculty Publications and Presentations

Reconstructability Analysis (RA) and Bayesian Networks (BN) are both probabilistic graphical modeling methodologies used in machine learning and artificial intelligence. There are RA models that are statistically equivalent to BN models and there are also models unique to RA and models unique to BN. The primary goal of this paper is to unify these two methodologies via a lattice of structures that offers an expanded set of models to represent complex systems more accurately or more simply. The conceptualization of this lattice also offers a framework for additional innovations beyond what is presented here. Specifically, this paper integrates RA and …


Universal Biological Motions For Educational Robot Theatre And Games, Rajesh Venkatachalapathy, Martin Zwick, Adam Slowik, Kai Brooks, Mikhail Mayers, Roman Minko, Tyler Hull, Bliss Brass, Marek Perkowski Jun 2021

Universal Biological Motions For Educational Robot Theatre And Games, Rajesh Venkatachalapathy, Martin Zwick, Adam Slowik, Kai Brooks, Mikhail Mayers, Roman Minko, Tyler Hull, Bliss Brass, Marek Perkowski

Systems Science Faculty Publications and Presentations

Paper presents a concept that is new to robotics education and social robotics. It is based on theatrical games, in motions for social robots and animatronic robots. Presented here motion model is based on Drift Differential Model from biology and Fokker-Planck equations. This model is used in various areas of science to describe many types of motion. The model was successfully verified on various simulated mobile robots and a motion game of three robots called "Mouse and Cheese."


A Golden Age For Computing Frontiers, A Dark Age For Computing Education?, Christof Teuscher May 2021

A Golden Age For Computing Frontiers, A Dark Age For Computing Education?, Christof Teuscher

Electrical and Computer Engineering Faculty Publications and Presentations

There is no doubt that the body of knowledge spanned by the computing disciplines has gone through an unprecedented expansion, both in depth and breadth, over the last century. In this position paper, we argue that this expansion has led to a crisis in computing education: quite literally the vast majority of the topics of interest of this conference are not taught at the undergraduate level and most graduate courses will only scratch the surface of a few selected topics. But alas, industry is increasingly expecting students to be familiar with emerging topics, such as neuromorphic, probabilistic, and quantum computing, …


Using Information Theory To Extract Patterns From Categorical Raster Data, David Percy Apr 2021

Using Information Theory To Extract Patterns From Categorical Raster Data, David Percy

Systems Science Faculty Publications and Presentations

Information theory -- Reconstructability Analysis (RA) implemented in the Occam software -- was used to extract patterns from National Land Cover Data. The aim was to predict temporal change in evergreen forests from time-lagged and spatially adjacent states. The NLCD satellite data were preprocessed with Python and submitted to Occam for analysis, and Occam output was also explored with R-studio. The effectiveness of RA methodology for the analysis of this type of categorical space-time grid data was demonstrated.


Sensitivity Analysis Of An Agent-Based Simulation Model Using Reconstructability Analysis, Andey M. Nunes, Martin Zwick, Wayne Wakeland Dec 2020

Sensitivity Analysis Of An Agent-Based Simulation Model Using Reconstructability Analysis, Andey M. Nunes, Martin Zwick, Wayne Wakeland

Systems Science Faculty Publications and Presentations

Reconstructability analysis, a methodology based on information theory and graph theory, was used to perform a sensitivity analysis of an agent-based model. The NetLogo BehaviorSpace tool was employed to do a full 2k factorial parameter sweep on Uri Wilensky’s Wealth Distribution NetLogo model, to which a Gini-coefficient convergence condition was added. The analysis identified the most influential predictors (parameters and their interactions) of the Gini coefficient wealth inequality outcome. Implications of this type of analysis for building and testing agent-based simulation models are discussed.


Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt Nov 2020

Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt

Mechanical and Materials Engineering Faculty Publications and Presentations

Engineering neural networks to perform specific tasks often represents a monumental challenge in determining network architecture and parameter values. In this work, we extend our previously-developed method for tuning networks of non-spiking neurons, the “Functional subnetwork approach” (FSA), to the tuning of networks composed of spiking neurons. This extension enables the direct assembly and tuning of networks of spiking neurons and synapses based on the network’s intended function, without the use of global optimization ormachine learning. To extend the FSA, we show that the dynamics of a generalized linear integrate and fire (GLIF) neuronmodel have fundamental similarities to those of …


A Quantum Algorithm For Automata Encoding, Edison Tsai, Marek Perkowski Jan 2020

A Quantum Algorithm For Automata Encoding, Edison Tsai, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Encoding of finite automata or state machines is critical to modern digital logic design methods for sequential circuits. Encoding is the process of assigning to every state, input value, and output value of a state machine a binary string, which is used to represent that state, input value, or output value in digital logic. Usually, one wishes to choose an encoding that, when the state machine is implemented as a digital logic circuit, will optimize some aspect of that circuit. For instance, one might wish to encode in such a way as to minimize power dissipation or silicon area. For …


A Resource Constrained Shortest Paths Approach To Reducing Personal Pollution Exposure, Elling Payne Jun 2019

A Resource Constrained Shortest Paths Approach To Reducing Personal Pollution Exposure, Elling Payne

REU Final Reports

As wildfires surge in frequency and impact in the Pacific Northwest, in tandem with increasingly traffic-choked roads, personal exposure to harmful airborne pollutants is a rising concern. Particularly at risk are school-age children, especially those living in disadvantaged communities near major motorways and industrial centers. Many of these children must walk to school, and the choice of route can effect exposure. Route-planning applications and frameworks utilizing computational shortest paths methods have been proposed which consider personal exposure with reasonable success, but few have focused on pollution exposure, and all have been limited in scalability or geographic scope. This paper addresses …


Good Similar Patches For Image Denoising (Poster), Si Lu Jan 2019

Good Similar Patches For Image Denoising (Poster), Si Lu

Computer Science Faculty Publications and Presentations

Patch-based denoising algorithms like BM3D have achieved outstanding performance. An important idea for the success of these methods is to exploit the recurrence of similar patches in an input image to estimate the underlying image structures....


Incorporating Priors For Medical Image Segmentation Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell, James A. Tanyi, Arthur Y. Hung Feb 2016

Incorporating Priors For Medical Image Segmentation Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell, James A. Tanyi, Arthur Y. Hung

Computer Science Faculty Publications and Presentations

Medical image segmentation is typically performed manually by a physician to delineate gross tumor volumes for treatment planning and diagnosis. Manual segmentation is performed by medical experts using prior knowledge of organ shapes and locations but is prone to reader subjectivity and inconsistency. Automating the process is challenging due to poor tissue contrast and ill-defined organ/tissue boundaries in medical images. This paper presents a genetic algorithm for combining representations of learned information such as known shapes, regional properties and relative position of objects into a single framework to perform automated three-dimensional segmentation. The algorithm has been tested for prostate segmentation …


3d Fpga Cell Matrix By Self-Assembly, Jeffrey Udall Jan 2016

3d Fpga Cell Matrix By Self-Assembly, Jeffrey Udall

Undergraduate Research & Mentoring Program

Physical size limitations in miniaturizing two-dimensional (2D) transistors are becoming more difficult to overcome. In order to continue increasing the processing power of electronic circuits, new design paradigms are needed. Three-dimensional (3D) architectures provide a solution to this issue and are currently being implemented via wafer stacking. However, more significant gains in terms of packing and speed can be achieved by CMOS components with truly integrated 3D cellular architectures. One of these is the Cell Matrix, a self-configurable defect- and fault-tolerant architecture, which is ideally suited for ultra large-scale integration. For this project, we worked to expand the Cell Matrix …


Emerging Adaptive Architectures For Biomolecular Computation, Matthew Fleetwood Jan 2016

Emerging Adaptive Architectures For Biomolecular Computation, Matthew Fleetwood

Undergraduate Research & Mentoring Program

The goal of this work is to explore applications of reservoir computing in biomolecular computation. Reservoir computing is a unique model for representing a mapping from one instance in time to a specific output. A neural network of randomly connected neurons is linked with a single output neuron or multiple output neurons. The output neurons are capable of mapping inputs to desired outputs using adaptable algorithms. This framework is investigated by using the Python programming language and object oriented design and programming. Neurons are created in programs by bundling information like input data and attributes of the network, which utilize …


From Boolean Equalities To Constraints, Sergio Antoy, Michael Hanus Dec 2015

From Boolean Equalities To Constraints, Sergio Antoy, Michael Hanus

Computer Science Faculty Publications and Presentations

Although functional as well as logic languages use equality to discriminate between logically different cases, the operational meaning of equality is different in such languages. Functional languages reduce equational expressions to their Boolean values, True or False, logic languages use unification to check the validity only and fail otherwise. Consequently, the language Curry, which amalgamates functional and logic programming features, offers two kinds of equational expressions so that the programmer has to distinguish between these uses. We show that this distinction can be avoided by providing an analysis and transformation method that automatically selects the appropriate operation. Without this distinction …


A Constraint Language For Static Semantic Analysis Based On Scope Graphs, Hendrik Van Antwerpen, Pierre Néron, Andrew Tolmach, Eelco Visser, Guido Wachsmuth Sep 2015

A Constraint Language For Static Semantic Analysis Based On Scope Graphs, Hendrik Van Antwerpen, Pierre Néron, Andrew Tolmach, Eelco Visser, Guido Wachsmuth

Computer Science Faculty Publications and Presentations

In previous work, we introduced scope graphs as a formalism for describing program binding structure and performing name resolution in an AST-independent way. In this paper, we show how to use scope graphs to build static semantic analyzers. We use constraints extracted from the AST to specify facts about binding, typing, and initialization. We treat name and type resolution as separate building blocks, but our approach can handle language constructs—such as record field access—for which binding and typing are mutually dependent.We also refine and extend our previous scope graph theory to address practical concerns including ambiguity checking and support for …


A Scaffolded, Metamorphic Ctf For Reverse Engineering, Wu-Chang Feng Aug 2015

A Scaffolded, Metamorphic Ctf For Reverse Engineering, Wu-Chang Feng

Computer Science Faculty Publications and Presentations

Hands-on Capture-the-Flag (CTF) challenges tap into and cultivate the intrinsic motivation within people to solve puzzles, much in the same way Sudoku and crossword puzzles do. While the format has been successful in security competitions, there have been a limited number of attempts to integrate them into a classroom environment. This paper describes MetaCTF, a metamorphic set of CTF challenges for teaching reverse code engineering. MetaCTF is 1) scaffolded in a way that allows students to make incremental progress, 2) integrated with the course material so that students can immediately apply knowledge gained in class, 3) polymorphic and metamorphic so …


Compiling Collapsing Rules In Certain Constructor Systems, Sergio Antoy, Andy Jost Jul 2015

Compiling Collapsing Rules In Certain Constructor Systems, Sergio Antoy, Andy Jost

Computer Science Faculty Publications and Presentations

The implementation of functional logic languages by means of graph rewriting requires a special handling of collapsing rules. Recent advances about the notion of a needed step in some constructor systems offer a new approach to this problem. We present two results: a transformation of a certain class of constructor-based rewrite systems that eliminates collapsing rules, and a rewrite-like relation that takes advantage of the absence of collapsing rules. We formally state and prove the correctness of these results. When used together, these results simplify without any loss of efficiency an implementation of graph rewriting and consequently of functional logic …


Automatic Fault Injection For Driver Robustness Testing, Kai Cong, Li Lei, Zhenkun Yang, Fei Xie Jul 2015

Automatic Fault Injection For Driver Robustness Testing, Kai Cong, Li Lei, Zhenkun Yang, Fei Xie

Computer Science Faculty Publications and Presentations

Robustness testing is a crucial stage in the device driver development cycle. To accelerate driver robustness testing, effective fault scenarios need to be generated and injected without requiring much time and human effort. In this pa- per, we present a practical approach to automatic runtime generation and injection of fault scenarios for driver robust- ness testing. We identify target functions that can fail from runtime execution traces, generate effective fault scenarios on these target functions using a bounded trace-based it- erative strategy, and inject the generated fault scenarios at runtime to test driver robustness using a permutation-based injection mechanism. We …


Naturalized Communication And Testing, Marly Roncken, Swetha Mettala Gilla, Hoon Park, Navaneeth Prasannakumar Jamadagni, Christopher Cowan, Ivan Sutherland May 2015

Naturalized Communication And Testing, Marly Roncken, Swetha Mettala Gilla, Hoon Park, Navaneeth Prasannakumar Jamadagni, Christopher Cowan, Ivan Sutherland

Computer Science Faculty Publications and Presentations

We ”naturalize” the handshake communication links of a self-timed system by assigning the capabilities of filling and draining a link and of storing its full or empty status to the link itself. This contrasts with assigning these capabilities to the joints, the modules connected by the links, as was previously done. Under naturalized communication, the differences between Micropipeline, GasP, Mousetrap, and Click circuits are seen only in the links — the joints become identical; past, present, and future link and joint designs become interchangeable. We also “naturalize” the actions of a self-timed system, giving actions status equal to states — …


Micro-Policies: Formally Verified, Tag-Based Security Monitors, Arthur Azevedo De Amorim, Maxime Denes, Nick Giannarakis, Cătălin Hriţcu, Benjamin C. Pierce, Antal Spector-Zabusky, Andrew Tolmach May 2015

Micro-Policies: Formally Verified, Tag-Based Security Monitors, Arthur Azevedo De Amorim, Maxime Denes, Nick Giannarakis, Cătălin Hriţcu, Benjamin C. Pierce, Antal Spector-Zabusky, Andrew Tolmach

Computer Science Faculty Publications and Presentations

Recent advances in hardware design have demonstrated mechanisms allowing a wide range of low-level security policies (or micro-policies) to be expressed using rules on metadata tags. We propose a methodology for defining and reasoning about such tag-based reference monitors in terms of a high-level “symbolic machine,” and we use this methodology to define and formally verify micro-policies for dynamic sealing, compartmentalization, control-flow integrity, and memory safety; in addition, we show how to use the tagging mechanism to protect its own integrity. For each micro-policy, we prove by refinement that the symbolic machine instantiated with the policy’s rules embodies a high-level …


Semi-Modular Delay Model Revisited In Context Of Relative Timing, Hoon Park, Anping He, Marly Roncken, Xiaoyu Song Feb 2015

Semi-Modular Delay Model Revisited In Context Of Relative Timing, Hoon Park, Anping He, Marly Roncken, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

A new definition of semi-modularity to accommodate relative timing constraints in self-timed circuits is presented. While previous definitions ignore such constraints, the new definition takes them into account. The difference on a design solution for a well-known speed-independent circuit implementation of the Muller C element and a set of relative timing constraints that renders the implementation hazard free is illustrated. The old definition produces a false semi-modularity conflict that cannot exist due to the set of imposed constraints. The new definition correctly accepts the solution.


Static Conflict Detection For A Policy Language, Alix Trou, Robert Dockins, Andrew Tolmach Jan 2015

Static Conflict Detection For A Policy Language, Alix Trou, Robert Dockins, Andrew Tolmach

Computer Science Faculty Publications and Presentations

We present a static control flow analysis used in the Simple Unified Policy Programming Language (SUPPL) compiler to detect internally inconsistent policies. For example, an access control policy can decide to both “allow” and “deny” access for a user; such an inconsistency is called a conflict. Policies in Suppl. follow the Event-Condition-Action paradigm; predicates are used to model conditions and event handlers are written in an imperative way. The analysis is twofold; it first computes a superset of all conflicts by looking for a combination of actions in the event handlers that might violate a user-supplied definition of conflicts. SMT …