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Full-Text Articles in Physical Sciences and Mathematics

Growing Reservoir Networks Using The Genetic Algorithm Deep Hyperneat, Nancy L. Mackenzie May 2022

Growing Reservoir Networks Using The Genetic Algorithm Deep Hyperneat, Nancy L. Mackenzie

Student Research Symposium

Typical Artificial Neural Networks (ANNs) have static architectures. The number of nodes and their organization must be chosen and tuned for each task. Choosing these values, or hyperparameters, is a bit of a guessing game, and optimizing must be repeated for each task. If the model is larger than necessary, this leads to more training time and computational cost. The goal of this project is to evolve networks that grow according to the task at hand. By gradually increasing the size and complexity of the network to the extent that the task requires, we will build networks that are more …


Expanding Temperature Sensing For The Orion Bms 2, Samuel J. Parker Oct 2021

Expanding Temperature Sensing For The Orion Bms 2, Samuel J. Parker

University Honors Theses

Formula SAE (FSAE) is an annual collegiate design competition that takes place across the globe. Portland State University’s team, Viking Motorsports, was committed to designing an Electric Vehicle (EV) for the 2021 FSAE competition. The team designed a completely custom lithium-ion cell battery that is managed by an Orion BMS 2 battery management system. The FSAE rulebook requires a robust temperature monitoring system for any EV power supply. The Orion BMS 2 can only directly collect data from eight temperature sensors, which is not enough to meet FSAE regulation. However, the BMS can be configured to monitor many more sensors …


Quantum Grover's Oracles With Symmetry Boolean Functions, Peng Gao Aug 2021

Quantum Grover's Oracles With Symmetry Boolean Functions, Peng Gao

Dissertations and Theses

Quantum computing has become an important research field of computer science and engineering. Among many quantum algorithms, Grover's algorithm is one of the most famous ones. Designing an effective quantum oracle poses a challenging conundrum in circuit and system-level design for practical application realization of Grover's algorithm.

In this dissertation, we present a new method to build quantum oracles for Grover's algorithm to solve graph theory problems. We explore generalized Boolean symmetric functions with lattice diagrams to develop a low quantum cost and area efficient quantum oracle. We study two graph theory problems: cycle detection of undirected graphs and generalized …


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 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 …


An Application Of Deep Learning Models To Automate Food Waste Classification, Alejandro Zachary Espinoza Dec 2019

An Application Of Deep Learning Models To Automate Food Waste Classification, Alejandro Zachary Espinoza

Dissertations and Theses

Food wastage is a problem that affects all demographics and regions of the world. Each year, approximately one-third of food produced for human consumption is thrown away. In an effort to track and reduce food waste in the commercial sector, some companies utilize third party devices which collect data to analyze individual contributions to the global problem. These devices track the type of food wasted (such as vegetables, fruit, boneless chicken, pasta) along with the weight. Some devices also allow the user to leave the food in a kitchen container while it is weighed, so the container weight must also …


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 …


Spectral Clustering For Electrical Phase Identification Using Advanced Metering Infrastructure Voltage Time Series, Logan Blakely Jan 2019

Spectral Clustering For Electrical Phase Identification Using Advanced Metering Infrastructure Voltage Time Series, Logan Blakely

Dissertations and Theses

The increasing demand for and prevalence of distributed energy resources (DER) such as solar power, electric vehicles, and energy storage, present a unique set of challenges for integration into a legacy power grid, and accurate models of the low-voltage distribution systems are critical for accurate simulations of DER. Accurate labeling of the phase connections for each customer in a utility model is one area of grid topology that is known to have errors and has implications for the safety, efficiency, and hosting capacity of a distribution system. This research presents a methodology for the phase identification of customers solely using …


Dark Current Rts-Noise In Silicon Image Sensors, Benjamin William Hendrickson Jun 2018

Dark Current Rts-Noise In Silicon Image Sensors, Benjamin William Hendrickson

Dissertations and Theses

Random Telegraph Signal (RTS) noise is a random noise source defined by discrete and metastable changes in the magnitude of a signal. Though observed in a variety of physical processes, RTS is of particular interest to image sensor fabrication where progress in the suppression of other noise sources has elevated its noise contribution to the point of approaching the limiting noise source in scientific applications.

There have been two basic physical sources of RTS noise reported in image sensors. The first involves a charge trap in the oxide layer of the source follower in a CMOS image sensor. The capture …


Using Reservoir Computing To Build A Robust Interface With Dna Circuits In Determining Genetic Similarities Between Pathogens, Christopher Neighbor, Christof Teuscher May 2018

Using Reservoir Computing To Build A Robust Interface With Dna Circuits In Determining Genetic Similarities Between Pathogens, Christopher Neighbor, Christof Teuscher

Student Research Symposium

As computational power increases, the field of neural networks has advanced exponentially. In particular recurrent neural networks (RNNs) are being utilized to simulate dynamic systems and to learn to predict time series data. Reservoir computing is an architecture which has the potential to increase training speed while reducing computational costs. Reservoir computing consists of a RNN with a fixed connections “reservoir” while only the output layer is trained. The purpose of this research is to explore the effective use of reservoir computing networks with the eventual application towards use in a DNA based molecular computing reservoir for use in pathogen …


Generalized Differential Calculus And Applications To Optimization, R. Blake Rector Jun 2017

Generalized Differential Calculus And Applications To Optimization, R. Blake Rector

Dissertations and Theses

This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of set-valued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations …


Power-Aware Datacenter Networking And Optimization, Qing Yi Mar 2017

Power-Aware Datacenter Networking And Optimization, Qing Yi

Dissertations and Theses

Present-day datacenter networks (DCNs) are designed to achieve full bisection bandwidth in order to provide high network throughput and server agility. However, the average utilization of typical DCN infrastructure is below 10% for significant time intervals. As a result, energy is wasted during these periods. In this thesis we analyze traffic behavior of datacenter networks using traces as well as simulated models. Based on the insight developed, we present techniques to reduce energy waste by making energy use scale linearly with load. The solutions developed are analyzed via simulations, formal analysis, and prototyping. The impact of our work is significant …


Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly Dec 2016

Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly

Dissertations and Theses

Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat.

An implantable cardiac …


The Effects Of Phosphonic Acids In Dye-Sensitized Solar Cells, Keith Edward James May 2016

The Effects Of Phosphonic Acids In Dye-Sensitized Solar Cells, Keith Edward James

Dissertations and Theses

Novel methods for the construction of dye-sensitized solar cells (DSSCs) were developed. A thin dense underlayer of TiO2 was applied on fluorine-doped tin oxide (FTO) glass using as a precursor Tyzor AA-105. Subsequently a mesoporous film of P-25 TiO2 was applied by spreading a suspension uniformly over the surface of the underlayer and allowing the plate to slowly dry while resting on a level surface. After sintering at 500° C slides were treated with TCPP as a sensitizing dye and assembled into DSSCs. A novel method was used to seal the cells; strips of Parafilm® were used as …


Physics-Based Imaging Methods For Terahertz Nondestructive Evaluation Applications, Gabriel Paul Kniffin May 2016

Physics-Based Imaging Methods For Terahertz Nondestructive Evaluation Applications, Gabriel Paul Kniffin

Dissertations and Theses

Lying between the microwave and far infrared (IR) regions, the "terahertz gap" is a relatively unexplored frequency band in the electromagnetic spectrum that exhibits a unique combination of properties from its neighbors. Like in IR, many materials have characteristic absorption spectra in the terahertz (THz) band, facilitating the spectroscopic "fingerprinting" of compounds such as drugs and explosives. In addition, non-polar dielectric materials such as clothing, paper, and plastic are transparent to THz, just as they are to microwaves and millimeter waves. These factors, combined with sub-millimeter wavelengths and non-ionizing energy levels, makes sensing in the THz band uniquely suited for …


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 …


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 …


Evaluation Of Data-Path Topologies For Self-Timed Conditional Statements, Navaneeth Prasannakumar Jamadagni Aug 2015

Evaluation Of Data-Path Topologies For Self-Timed Conditional Statements, Navaneeth Prasannakumar Jamadagni

Dissertations and Theses

This research presents a methodology to evaluate data path topologies that implement a conditional statement for an average-case performance that is better than the worst-case performance. A conditional statement executes one of many alternatives depending on how Boolean conditions evaluate to true or false. Alternatives with simple computations take less time to execute. The self-timed designs can exploit the faster executing alternatives and provide an average-case behavior, where the average depends on the frequency of simple and complex computations, and the difference in the completion times of simple and complex computations. The frequency of simple and complex computations depends on …


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 …


Design, Construction, And Utilization Of Physical Vapor Deposition Systems For Medical Sensor Fabrication, Nicholas Sayre, Erik J. Sánchez, Joe Kowalski May 2015

Design, Construction, And Utilization Of Physical Vapor Deposition Systems For Medical Sensor Fabrication, Nicholas Sayre, Erik J. Sánchez, Joe Kowalski

Student Research Symposium

The development of a novel blood glucose sensor is realized through construction of a homemade plasma coating system and utilization of semiconductor manufacturing processes in a small scale cleanroom environment. Photolithography, plasma sputtering, chemical etching and thin film measurement technologies are used in the medical sensor fabrication process. General process flow will be discussed, and system design and the plasma sputtering process will be presented as it is achieved by the system currently under development.


Performance Metrics For Depth-Based Signal Separation Using Deep Vertical Line Arrays, John K. Boyle Mar 2015

Performance Metrics For Depth-Based Signal Separation Using Deep Vertical Line Arrays, John K. Boyle

Dissertations and Theses

Vertical line arrays (VLAs) deployed below the critical depth in the deep ocean can exploit reliable acoustic path (RAP) propagation, which provides low transmission loss (TL) for targets at moderate ranges, and increased TL for distant interferers. However, sound from nearby surface interferers also undergoes RAP propagation, and without horizontal aperture, a VLA cannot separate these interferers from submerged targets. A recent publication by McCargar and Zurk (2013) addressed this issue, presenting a transform-based method for passive, depth-based separation of signals received on deep VLAs based on the depth-dependent modulation caused by the interference between the direct and surface-reflected acoustic …


Prussian Green: A High Rate Capacity Cathode For Potassium Ion Batteries, Prasanna Pradigi, Joseph Thiebes, Mitchell Swan, Gary Goncher, David Evans, Raj Solanki Mar 2015

Prussian Green: A High Rate Capacity Cathode For Potassium Ion Batteries, Prasanna Pradigi, Joseph Thiebes, Mitchell Swan, Gary Goncher, David Evans, Raj Solanki

Physics Faculty Publications and Presentations

The influence of the precursors, namely potassium ferrocyanide and potassium ferricyanide on the particles sizes of Prussian Blue (PB) and Prussian Green (PG), under identical reaction conditions have been investigated. It was found that the particle sizes influence the gravimetric capacity utilization of these materials as cathodes for aqueous potassium (K+ ) ion batteries. The PG particle sizes were on the order of 50-75 nm, whereas PB particles size were on the order of 2-10 microns. The PG cathodes demonstrated a reversible capacity of 121.4 mAhr/g, with a coulombic efficiency of 98.7% compared to PB cathodes which demonstrated 53.8 …


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.


Synthesis Of Irreversible Incompletely Specified Multi-Output Functions To Reversible Eosops Circuits With Pse Gates, Robert Adrian Fiszer Dec 2014

Synthesis Of Irreversible Incompletely Specified Multi-Output Functions To Reversible Eosops Circuits With Pse Gates, Robert Adrian Fiszer

Dissertations and Theses

As quantum computers edge closer to viability, it becomes necessary to create logic synthesis and minimization algorithms that take into account the particular aspects of quantum computers that differentiate them from classical computers. Since quantum computers can be functionally described as reversible computers with superposition and entanglement, both advances in reversible synthesis and increased utilization of superposition and entanglement in quantum algorithms will increase the power of quantum computing.

One necessary component of any practical quantum computer is the computation of irreversible functions. However, very little work has been done on algorithms that synthesize and minimize irreversible functions into a …


Slm-Based Fourier Differential Interference Contrast Microscopy, Sahand Noorizadeh Oct 2014

Slm-Based Fourier Differential Interference Contrast Microscopy, Sahand Noorizadeh

Dissertations and Theses

Optical phase microscopy provides a view of objects that have minimal to no effect on the detected intensity of light that are unobservable by standard microscopy techniques. Since its inception just over 60 years ago that gave us a vision to an unseen world and earned Frits Zernike the Nobel prize in physics in 1953, phase microscopy has evolved to find various applications in biological cell imaging, crystallography, semiconductor failure analysis, and more. Two common and commercially available techniques are phase contrast and differential interference contrast (DIC). In phase contrast method, a large portion of the unscattered light that accounts …


An Eigenvector-Based Test For Local Stationarity Applied To Array Processing, Jorge Quijano, Lisa M. Zurk Jun 2014

An Eigenvector-Based Test For Local Stationarity Applied To Array Processing, Jorge Quijano, Lisa M. Zurk

Electrical and Computer Engineering Faculty Publications and Presentations

In sonar array processing, a challenging problem is the estimation of the data covariance matrix in the presence of moving targets in the water column, since the time interval of data local stationarity is limited. This work describes an eigenvector-based method for proper data segmentation into intervals that exhibit local stationarity, providing data-driven higher bounds for the number of snapshots available for computation of time-varying sample covariance matrices. Application of the test is illustrated with simulated data in a horizontal array for the detection of a quiet source in the presence of a loud interferer.


A Comparative Study Of Reservoir Computing For Temporal Signal Processing, Alireza Goudarzi, Peter Banda, Matthew R. Lakin, Christof Teuscher, Darko Stefanovic Jan 2014

A Comparative Study Of Reservoir Computing For Temporal Signal Processing, Alireza Goudarzi, Peter Banda, Matthew R. Lakin, Christof Teuscher, Darko Stefanovic

Computer Science Faculty Publications and Presentations

Reservoir computing (RC) is a novel approach to time series prediction using recurrent neural networks. In RC, an input signal perturbs the intrinsic dynamics of a medium called a reservoir. A readout layer is then trained to reconstruct a target output from the reservoir's state. The multitude of RC architectures and evaluation metrics poses a challenge to both practitioners and theorists who study the task-solving performance and computational power of RC. In addition, in contrast to traditional computation models, the reservoir is a dynamical system in which computation and memory are inseparable, and therefore hard to analyze. Here, we compare …


Optics And Spectroscopy In Massive Electrodynamic Theory, Adam Caccavano Oct 2013

Optics And Spectroscopy In Massive Electrodynamic Theory, Adam Caccavano

Dissertations and Theses

The kinematics and dynamics for plane wave optics are derived for a massive electrodynamic field by utilizing Proca's theory. Atomic spectroscopy is also examined, with the focus on the 21 cm radiation due to the hyperfine structure of hydrogen. The modifications to Snell's Law, the Fresnel formulas, and the 21 cm radiation are shown to reduce to the familiar expressions in the limit of zero photon mass.


A Parabolic Equation Analysis Of The Underwater Noise Radiated By Impact Pile Driving, Nathan Laws Jul 2013

A Parabolic Equation Analysis Of The Underwater Noise Radiated By Impact Pile Driving, Nathan Laws

Dissertations and Theses

Impact pile driving can produce extremely high underwater sound levels, which are of increasing environmental concern due to their deleterious effects on marine wildlife. Prediction of underwater sound levels is important to the assessment and mitigation of the environmental impacts caused by pile driving. Current prediction methods are limited and do not account for the dynamic pile driving source, inhomogeneities in bathymetry and sediment, or physics-based sound wave propagation.

In this thesis, a computational model is presented that analyzes and predicts the underwater noise radiated by pile driving and is suitable for shallow, inhomogeneous environments and long propagation ranges. The …