Computer Engineering Commons^™

Teen Driver System Modeling: A Tool For Policy Analysis, Celestin Missikpode, Corrine Peek-Asa, Daniel V. Mcgehee, James Torner, Wayne Wakeland, Robert Wallace

Systems Science Faculty Publications and Presentations

Background: Motor vehicle crashes remain the leading cause of teen deaths in spite of preventive efforts. Prevention strategies could be advanced through new analytic approaches that allow us to better conceptualize the complex processes underlying teen crash risk. This may help policymakers design appropriate interventions and evaluate their impacts.

Methods: System Dynamics methodology was used as a new way of representing factors involved in the underlying process of teen crash risk. Systems dynamics modeling is relatively new to public health analytics and is a promising tool to examine relative influence of multiple interacting factors in predicting a health …

Keyword-Based Patent Citation Prediction Via Information Theory, Farshad Madani, Martin Zwick, Tugrul U. Daim

Engineering and Technology Management Faculty Publications and Presentations

Patent citation shows how a technology impacts other inventions, so the number of patent citations (backward citations) is used in many technology prediction studies. Current prediction methods use patent citations, but since it may take a long time till a patent is cited by other inventors, identifying impactful patents based on their citations is not an effective way. The prediction method offered in this article predicts patent citations based on the content of patents. In this research, Reconstructability Analysis (RA), which is based on information theory and graph theory, is applied to predict patent citations based on keywords extracted from …

Exploring Adoption Of Augmented Reality Smart Glasses: Applications In The Medical Industry, Nuri A. Basoglu, Muge Goken, Marina Dabic, Dilek Ozdemir Gungor, Tugrul U. Daim

Engineering and Technology Management Faculty Publications and Presentations

This study explores the use of augmented reality smart glasses (ARSGs) by physicians and their adoption of these products in the Turkish medical industry. Google Glass was used as a demonstrative example for the introduction of ARSGs. We proposed an exploratory model based on the technology acceptance model by Davis. Exogenous factors in the model were defined by performing semi-structured in-depth interviews, along with the use of an expert panel in addition to the technology adoption literature. The framework was tested by means of a field study, data was collected via an Internet survey, and path analysis was used. The …

Biomimetic Design And Construction Of A Bipedal Walking Robot, Alexander Gabriel Steele

Dissertations and Theses

Human balance and locomotion control is highly complex and not well understood. To understand how the nervous system controls balance and locomotion works, we test how the body responds to controlled perturbations, the results are analyzed, and control models are developed. However, to recreate this system of control there is a need for a robot with human-like kinematics. Unfortunately, such a robotic testbed does not exist despite the numerous applications such a design would have in mobile robotics, healthcare, and prosthetics.

This thesis presents a robotic testbed model of human lower legs. By using MRI and CT scans, I designed …

Combining Algorithms For More General Ai, Mark Robert Musil

Undergraduate Research & Mentoring Program

Two decades since the first convolutional neural network was introduced the AI sub-domains of classification, regression and prediction still rely heavily on a few ML architectures despite their flaws of being hungry for data, time, and high-end hardware while still lacking generality. In order to achieve more general intelligence that can perform one-shot learning, create internal representations, and recognize subtle patterns it is necessary to look for new ML system frameworks. Research on the interface between neuroscience and computational statistics/machine learning has suggested that combined algorithms may increase AI robustness in the same way that separate brain regions specialize. In …

An Exploration Of Software Defined Radio And Gnu Radio Companion For Use In Drone-To-Drone Communication, Amanda K. H. Voegtlin

Undergraduate Research & Mentoring Program

In a world that increasingly relies on automation and intelligent robotics, there is a need for drones to expand their independence and adaptability in navigating their environments. One approach to this problem is the use of wireless communication between units in order to coordinate their sensor data and build real-time maps of the environments they are navigating. However, especially indoors, relying on a fixed transmission tower to provide data to the units faces connectivity challenges.

The purpose of this research was to determine the fitness of an on-drone assembly that uses the the NI B200mini software-defined radio board and Gnu …

Automating Knife-Edge Method Of Thz Beam Characterization, Christopher Charles Faber

Undergraduate Research & Mentoring Program

The goal of this project is to create a time and cost-effective solution for THz beam profiling.

The knife edge method of beam characterization is a technique to verify the intensity profile of a beam involving traveling a blade orthogonal to the beam path and measuring transmission in successive steps. We use a vector network analyzer (VNA) to measure S21 transmission from a THz source. Manual implementation of this method was time-consuming and inefficient.

Project hardware includes an Arduino, a motor shield, and a ball screw linear rail with stepper motor actuator. Software was created in LabView and data is …

Binder Free Graphene Hybridized Fe3o4 Nanoparticles For Supercapacitor Applications, Nathan D. Jansen

Undergraduate Research & Mentoring Program

In a world with increasing energy demands, the need for safe and mobile energy storage grows. There are a number of renewable energy sources that can be harvested, however peak demand and peak production times tend to not overlap. As the capabilities of collecting the energy grows so does the need to store the energy for later consumption. The two promising methods of storing energy are batteries or supercapacitors. Both technologies employ an electrode consisting of an active material bound to a current collector. This material participates in a redox reaction, storing charge electrochemically to later be used as energy, …

Laser-Scribed Graphene Micro-Supercapacitors, Kimi D. Owens

Undergraduate Research & Mentoring Program

M. F. El-Kady and R. B. Kaner, “Scalable fabrication of high-power graphene micro-supercapacitors for flexible and on-chip energy storage,” Nature Communications, vol. 4, p. 1475, Feb. 2013.

Supercapacitors are electrical components that have higher energy density than regular capacitors. Currently, they are large and bulky which makes it hard to be implemented into smaller electronic devices or on-chip. In Scalable Fabrication of High-power Graphene Micro-supercapacitors for Flexible and On-chip Energy Storage, El-Kady and Kaner developed an inexpensive and reliable method for scaling down supercapacitors to be approximately 7.53 x 5.35 mm. To make the laser-scribed graphene (LSG) micro-supercapacitors, an aqueous …

Learning In Bio-Molecular Computing Systems, Lauren Braun

Undergraduate Research & Mentoring Program

Many potential applications of biochemical computers involve the detection of highly adaptable and dynamic chemical systems, such as emerging pathogens. Current technology is expensive to develop and unique to each application, thus causing limitations in accessibility. In order to make this type of computing a realistic solution to problems in the medical field, a biochemical computer would need to be adaptable to work in a variety of applications. Banda et al. (2014) previously proposed a first dynamic biochemical system that was capable of autonomous learning. For this project we studied a framework similar to Banda’s but in two separate pieces, …

Improvement Of 802.11 Protocol On Fully Programmable Wireless Radio, Eunji Lee

Undergraduate Research & Mentoring Program

The growth in the number of connected device usage has led to a rapidly increased data traffic on wireless network and the demand for access to high speed and stable Internet connection is becoming more prominent. However, current off the shelf wireless cards are not programmable or observable across layers of the standard protocol stack, which leads to poor practical performance. Thus, Wireless Open Access Research Platform (WARP), a scalable wireless platform providing programmable functionality at every layer of the network stack, has been used for the real-time implementation and improvement of 802.11 protocol.

An Analysis Of Lora Low Power Technology And Its Applications, Gomathy Venkata Krishnan

Undergraduate Research & Mentoring Program

The number of Internet of Things (IoT) devices has exponentially increased in the last decade. With the increase in these devices, there is a necessity to effectively connect and control these devices remotely. Cellular technologies cannot handle this demand since they are not cost effective and easy to deploy. This is where LoRa technology comes handy. LoRa is long-range, low-power, low cost technology that supports internet of things applications. LoRa has many advantages in terms of capacity, mobility, battery lifetime and cost. It uses the unlicensed 915MHz ISM band and can be easily deployed.

This research is focused on setting …

Biochemical Reservoir Computing, Hoang Nguyen, Christof Teuscher

Student Research Symposium

Reservoir computing is an emerging machine learning paradigm. Compared to traditional feedforward neural networks, the reservoir can be unstructured and recurrent and only the output layer is trained. Reservoirs can be built with various types of physical components, yet, biochemical building blocks have not been widely used. This project focuses on designing and testing a reservoir computer (RC) based on chemical reaction network (CRN). We simulated high-level CRNs in MATLAB and their complex chemical dynamics were observed over time. A CRN constructed by a network of coupled deoxyribozyme oscillators was chosen for the final RC model. The inputs of the …

Radiation Source Localization By Using Backpropagation Neural Network, Jian Meng, Christof Teuscher, Walt Woods

Student Research Symposium

The most difficult part of the radiation localization is that we cannot use the traditional acoustic localization method to determine where the radiation source is. It’s mainly because the electromagnetic waves are totally different with the sound wave. From the expression of the radioactive intensity, we can tell that the intensity of radiation not only depend on the distance from the radiation but also related to the type of the nuclide. In general, the relationship between the intensity and the distance satisfy the inverse-square law, which is a non-linear relationship. In other words, if we can use the measurement and …

Real-Time Object Detection And Tracking On Drones, Tu Le

Undergraduate Research & Mentoring Program

Unmanned aerial vehicles, also known as drones, have been more and more widely used in recent decades because of their mobility. They appear in many applications such as farming, search and rescue, entertainment, military, and so on. Such high demands for drones lead to the need of developments in drone technologies. Next generations of commercial and military drones are expected to be aware of surrounding objects while flying autonomously in different terrains and conditions. One of the biggest challenges to drone automation is the ability to detect and track objects of interest in real-time. While there are many robust machine …

Silicon Compilation And Test For Dataflow Implementations In Gasp And Click, Swetha Mettala Gilla

Dissertations and Theses

Many modern computer systems are distributed over space. Well-known examples are the Internet of Things and IBM's TrueNorth for deep learning applications. At the Asynchronous Research Center (ARC) at Portland State University we build distributed hardware systems using self-timed computation and delay-insensitive communication. Where appropriate, self-timed hardware operations can reduce average and peak power, energy, latency, and electromagnetic interference. Alternatively, self-timed operations can increase throughput, tolerance to delay variations, scalability, and manufacturability.

The design of complex hardware systems requires design automation and support for test, debug, and product characterization.

This thesis focuses on design compilation and test support for dataflow …

Generating Adversarial Attacks For Sparse Neural Networks, Jack H. Chen, Walt Woods

Undergraduate Research & Mentoring Program

Neural networks provide state-of-the-art accuracy for image classification tasks. However traditional networks are highly susceptible to imperceivable perturbations to their inputs known as adversarial attacks that drastically change the resulting output. The magnitude of these perturbations can be measured as Mean Squared Error (MSE). We use genetic algorithms to produce black-box adversarial attacks and examine MSE on state-of-the-art networks. This method generates an attack that converts 90% confidence on a correct class to 50% confidence of a targeted, incorrect class after 2000 epochs. We will generate and examine attacks and their MSE against several sparse neural networks. We theorize that …

A Time-Efficient Cmos-Memristive Programmable Circuit Realizing Logic Functions In Generalized And-Xor Structures, Muayad Aljafar, Marek Perkowski, John M. Acken, Robin Tan

Electrical and Computer Engineering Faculty Publications and Presentations

This paper describes a CMOS-memristive Programmable Logic Device connected to CMOS XOR gates (mPLD-XOR) for realizing multi-output functions well-suited for two-level {NAND, AND, NOR, OR}-XOR based design. This structure is a generalized form of AND-XOR logic where any combination of NAND, AND, NOR, OR, and literals can replace the AND level. For mPLD-XOR, the computational delay, which is measured as the number of clock cycles, equals the maximum number of inputs to any output XOR gate of a function assuming that the number of XOR gates is large enough to calculate the outputs of the function simultaneously. The input levels …