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Articles 1 - 30 of 72
Full-Text Articles in Engineering
Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley
Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley
Dissertations and Theses
This thesis outlines the design of an IQ Test Bench that allows for experimentation of quadrature modulation techniques. Quadrature modulation utilizes two signals I and Q, 90° out of phase from each other, to greatly increase communication data rates. Using Desmos, a thorough mathematical analysis of waveform mixing is presented, and constellation diagrams are plotted from the results. From this an ancient fire signaling technique known as the Polybius Square is encoded into the system. The IQ Test Bench is built from fundamental components that would be contained within an RFFE: a local oscillator and two frequency mixers. The LO …
Multi-Agent Deep Reinforcement Learning For Radiation Localization, Benjamin Scott Totten
Multi-Agent Deep Reinforcement Learning For Radiation Localization, Benjamin Scott Totten
Dissertations and Theses
For the safety of both equipment and human life, it is important to identify the location of orphaned radioactive material as quickly and accurately as possible. There are many factors that make radiation localization a challenging task, such as low gamma radiation signal strength and the need to search in unknown environments without prior information. The inverse-square relationship between the intensity of radiation and the source location, the probabilistic nature of nuclear decay and gamma ray detection, and the pervasive presence of naturally occurring environmental radiation complicates localization tasks. The presence of obstructions in complex environments can further attenuate the …
A Privacy-Preserving Strategy For The Trust Layer Of The Energy Grid Of Things Distributed Energy Resource Management System, Mohammed Abdullah Alsaid
A Privacy-Preserving Strategy For The Trust Layer Of The Energy Grid Of Things Distributed Energy Resource Management System, Mohammed Abdullah Alsaid
Dissertations and Theses
Emergent from the shadows of the traditional grid flaws, the Smart Grid (SG) idea was born and led by government mandates toward cleaner energy production. The SG represents the next generation of electricity distribution systems that subsume recent technological innovations. It uses digital communication between its components and entities to attain more automation, self-sufficiency, and reliability. Unfortunately, this relatively new concept is not flawless; the intrinsic reliance on increased digital communication spreads open attack paths for adversaries. Therefore, finding solutions that address information exchange vulnerabilities has become imperative.
The Energy Grid of Things (EGoT) is Portland State University's implementation of …
A Distributed Trust Model Simulator For Energy Grid Of Things Distributed Energy Resource Management System, Abdullah Barghouti
A Distributed Trust Model Simulator For Energy Grid Of Things Distributed Energy Resource Management System, Abdullah Barghouti
Dissertations and Theses
The evolution of networks into more distributed, self-reliant nodes has mitigated single-point failures that plagued traditional centralized networks. Applied to power grids, distributed systems can increase the integrity and availability of grid services while also offering a power management solution. However, while distributed networks provide scalability, security, and sustainability compared to centralized networks, their distributed nature makes them harder for anomaly detection and prevention. Incorporating a Distributed Trust Model (DTM) System into an Energy Grid of Things Distributed Energy Resource Management System (EGOT DERMS) allows grid participants to be characterized and their communication to be analyzed for possible attacks. A …
Methodologies For Quantum Circuit And Algorithm Design At Low And High Levels, Edison Tsai
Methodologies For Quantum Circuit And Algorithm Design At Low And High Levels, Edison Tsai
Dissertations and Theses
Although the concept of quantum computing has existed for decades, the technology needed to successfully implement a quantum computing system has not yet reached the level of sophistication, reliability, and scalability necessary for commercial viability until very recently. Significant progress on this front was made in the past few years, with IBM planning to create a 1000-qubit chip by the end of 2023, and Google already claiming to have achieved quantum supremacy. Other major industry players such as Intel and Microsoft have also invested significant amounts of resources into quantum computing research.
Any viable computing system requires both hardware and …
Design And Control Of Quasi-Direct Drive Actuation For Lightweight And Versatile Wearable Robots, Shuangyue Yu
Design And Control Of Quasi-Direct Drive Actuation For Lightweight And Versatile Wearable Robots, Shuangyue Yu
Dissertations and Theses
Wearable robots have shown great potential for augmenting the physical capabilities of humans in lab settings. However, wearable robots for augmenting the physical capabilities of humans under community-based conditions are the new frontier of robotics. Furthermore, the design and control are still considered to be grand challenges for providing physical augmentation for humans. In terms of design, the state-of-the-art exoskeletons are typically rigid, bulky, and limited to lab settings. In terms of control, most of the rhythmic controllers are not versatile and are focused only on steady-state walking assistance.
The motivation behind my research is to improve both the design …
The Application Of Design Thinking On Evaluating A User Self-Service Data Analytics/Science Platform, Aheeka Pattnaik
The Application Of Design Thinking On Evaluating A User Self-Service Data Analytics/Science Platform, Aheeka Pattnaik
Dissertations and Theses
This thesis is aimed at utilising design thinking and the first half of the double diamond framework to i) set-up a research and select the appropriate participants, ii) gather requirements and define user personas from those eligible participants, and then iii) define the framework for evaluating a user self-service data analytics/science platform. Derived from the author’s own experiences, both as a Business Analyst (BA) and Citizen Data Scientist, with no-, low-, and code-based data analytics and science platforms are being implemented for enabling user self-service analytics – for users who are completely new to the space of data analysis and …
Respiratory Sound Analysis For The Evidence Of Lung Health, Priyanka Sreerama
Respiratory Sound Analysis For The Evidence Of Lung Health, Priyanka Sreerama
Dissertations and Theses
Significant changes have been made on audio-based technologies over years in several different fields along with healthcare industry. Analysis of Lung sounds is a potential source of noninvasive, quantitative information along with additional objective on the status of the pulmonary system. To do that medical professionals listen to sounds heard over the chest wall at different positions with a stethoscope which is known as auscultation and is important in diagnosing respiratory diseases. At times, possibility of inaccurate interpretation of respiratory sounds happens because of clinician’s lack of considerable expertise or sometimes trainees such as interns and residents misidentify respiratory sounds. …
Automated Statistical Structural Testing Techniques And Applications, Yang Shi
Automated Statistical Structural Testing Techniques And Applications, Yang Shi
Dissertations and Theses
Statistical structural testing(SST) is an effective testing technique that produces random test inputs from probability distributions. SST shows superiority in fault-revealing power over random testing and deterministic approaches since it heritages the merits from both of them. SST ensures testing thoroughness by setting up a probability lower-bound criterion for each structural cover element and test inputs that exercise a structural cover element sampled from the probability distribution, ensuring testing randomness. Despite the advantages, SST is not a widely used approach in practice. There are two major limitations. First, to construct probability distributions, a tester must understand the underlying software's structure, …
The Revenue Operations (Revops) Framework: A Qualitative Study Of Industry Practitioners., Oliviero Mottola
The Revenue Operations (Revops) Framework: A Qualitative Study Of Industry Practitioners., Oliviero Mottola
Dissertations and Theses
In recent years Revenue Operations or RevOps has emerged in professional circles as a new approach to manage Sales, Marketing and Customer Success teams in the context of b2b sales. In practitioner circles, RevOps definitions range from the increased collaboration of the three job functions to an all-out creation of job function within organizations. While the subject of interdepartmental alignment has been covered extensively in academia (albeit not exhaustively), RevOps as a term and set of practices has received no attention and industry practitioners struggle to find a unified set of best practices that isn’t coming from organizations trying to …
A Method For Comparative Analysis Of Trusted Execution Environments, Stephano Cetola
A Method For Comparative Analysis Of Trusted Execution Environments, Stephano Cetola
Dissertations and Theses
The problem of secure remote computation has become a serious concern of hardware manufacturers and software developers alike. Trusted Execution Environments (TEEs) are a solution to the problem of secure remote computation in applications ranging from "chip and pin" financial transactions to intellectual property protection in modern gaming systems. While extensive literature has been published about many of these technologies, there exists no current model for comparing TEEs. This thesis provides hardware architects and designers with a set of tools for comparing TEEs. I do so by examining several properties of a TEE and comparing their implementations in several technologies. …
Automated Test Generation For Validating Systemc Designs, Bin Lin
Automated Test Generation For Validating Systemc Designs, Bin Lin
Dissertations and Theses
Modern system design involves integration of all components of a system on a single chip, namely System-on-a-Chip (SoC). The ever-increasing complexity of SoCs and rapidly decreasing time-to-market have pushed the design abstraction to the electronic system level (ESL), in order to increase design productivity. SystemC is a widely used ESL modeling language that plays a central role in modern SoCs design process. ESL SystemC designs usually serve as executable specifications for the subsequent SoCs design flow. Therefore, undetected bugs in ESL SystemC designs may propagate to low-level implementations or even final silicon products. In addition, modern SoCs design often involves …
Blockchain-Based Architecture For Secured Cyberattack Signatures And Features Distribution, Oluwaseyi J. Ajayi
Blockchain-Based Architecture For Secured Cyberattack Signatures And Features Distribution, Oluwaseyi J. Ajayi
Dissertations and Theses
One effective way of detecting malicious traffic in computer networks is intrusion detection systems (IDS). Despite the increased accuracy of IDSs, distributed or coordinated attacks can still go undetected because of the single vantage point of the IDSs. Due to this reason, there is a need for attack characteristics' exchange among different IDS nodes. Another reason for IDS coordination is that a zero-day attack (an attack without a known signature) experienced in organizations located in different regions is not the same. Collaborative efforts of the participating IDS nodes can stop more attack threats if IDS nodes exchange these attack characteristics …
Challenges To Adopting Hybrid Methodology: Addressing Organizational Culture And Change Control Problems In Enterprise It Infrastructure Projects, Harishankar Krishnakumar
Challenges To Adopting Hybrid Methodology: Addressing Organizational Culture And Change Control Problems In Enterprise It Infrastructure Projects, Harishankar Krishnakumar
Dissertations and Theses
IT infrastructure projects have long been an overlooked field superseded by the more popular software development silos and cross-functional project teams when it comes to enterprise Agile transformations. This paper presents a systematic literature review by leveraging a qualitative research methodology based on empirical evidence provided in contemporary scholarly research articles to explore how certain variables such as organizational culture- including team structure, leadership hierarchy, geolocation, etc. along with an organization’s change management processes affect the adoption of a Hybrid/Agile project management methodology, focusing on reported challenges and critical success factors that define such large-scale enterprise transformations. The salient features …
Domestic Violence In Pakistan From 1990 – 2020: A Mixed Method Approach, Hamida Khatri
Domestic Violence In Pakistan From 1990 – 2020: A Mixed Method Approach, Hamida Khatri
Dissertations and Theses
This study assessed domestic violence from the perspective of the victims who experienced trauma due to sexual, emotional, and psychological abuse in Pakistan.
Synthesizing Expressive Behaviors For Humanoid Robots, Mathias Irwan Sunardi
Synthesizing Expressive Behaviors For Humanoid Robots, Mathias Irwan Sunardi
Dissertations and Theses
Humanoid robots are expected to be able to communicate with expressive gestures at the same level of proficiency as humans. However, creating expressive gestures for humanoid robots is difficult and time consuming due to the high number of degrees of freedom (DOF) and the iterations needed to get the desired expressiveness.
Current robot motion editing software has varying levels of sophistication of motion editing tools ranging from basic ones that are text-only, to ones that provide graphical user interfaces (GUIs) which incorporate advanced features, such as curve editors and inverse kinematics. These tools enable users to create simple motions; but …
Adaptive Effort Classifiers: A System Design For Partitioned Edge/Cloud Inference, Divya Sankar
Adaptive Effort Classifiers: A System Design For Partitioned Edge/Cloud Inference, Divya Sankar
Dissertations and Theses
The massive growth in availability of real-world data from connected devices and the overwhelming success of Deep Neural Networks (DNNs) in many ArtificialIntelligence (AI) tasks have enabled AI-based applications and services to become commonplace across the spectrum of computing devices from edge/Internet-of-Things (IoT) devices to data centers and the cloud. However, DNNs incur high computational cost (compute operations, memory footprint and bandwidth),which far outstrip the capabilities of modern computing platforms. Therefore improving the computational efficiency of DNNs wide-spread commercial deployment and success.In this thesis, we address the computational efficiency challenge in the context ofAI inference applications executing on edge/cloud systems, …
V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha
V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha
Dissertations and Theses
In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …
Audio Beat Detection With Application To Robot Drumming, Michael James Engstrom
Audio Beat Detection With Application To Robot Drumming, Michael James Engstrom
Dissertations and Theses
This Drumming Robot thesis demonstrates the design of a robot which can play drums in rhythm to an external audio source. The audio source can be either a pre-recorded .wav file or a live sample .wav file from a microphone. The dominant beats-per-minute (BPM) of the audio would be extracted and the robot would drum in time to the BPM. A Fourier Analysis-based BPM detection algorithm, developed by Eric Scheirer (Tempo and beat analysis of acoustical musical signals)i was adopted and implemented. In contrast to other popular algorithms, the main advantage of Scheirer's algorithm is it has …
Design Of A Canine Inspired Quadruped Robot As A Platform For Synthetic Neural Network Control, Cody Warren Scharzenberger
Design Of A Canine Inspired Quadruped Robot As A Platform For Synthetic Neural Network Control, Cody Warren Scharzenberger
Dissertations and Theses
Legged locomotion is a feat ubiquitous throughout the animal kingdom, but modern robots still fall far short of similar achievements. This paper presents the design of a canine-inspired quadruped robot named DoggyDeux as a platform for synthetic neural network (SNN) research that may be one avenue for robots to attain animal-like agility and adaptability. DoggyDeux features a fully 3D printed frame, 24 braided pneumatic actuators (BPAs) that drive four 3-DOF limbs in antagonistic extensor-flexor pairs, and an electrical system that allows it to respond to commands from a SNN comprised of central pattern generators (CPGs). Compared to the previous version …
Memcapacitive Reservoir Computing Architectures, Dat Tien Tran
Memcapacitive Reservoir Computing Architectures, Dat Tien Tran
Dissertations and Theses
In this thesis, I propose novel brain-inspired and energy-efficient computing systems. Designing such systems has been the forefront goal of neuromorphic scientists over the last few decades. The results from my research show that it is possible to design such systems with emerging nanoscale memcapacitive devices.
Technological development has advanced greatly over the years with the conventional von Neumann architecture. The current architectures and materials, however, will inevitably reach their physical limitations. While conventional computing systems have achieved great performances in general tasks, they are often not power-efficient in performing tasks with large input data, such as natural image recognition …
Unsupervised Feature Learning For Point Cloud By Contrasting And Clustering With Graph Convolutional Neural Network, Ling Zhang
Dissertations and Theses
Recently, deep graph neural networks (GNNs) have attracted significant attention for point cloud understanding tasks, including classification, segmentation, and detection. However, the training of such deep networks still requires a large amount of annotated data, which is both expensive and time-consuming. To alleviate the cost of collecting and annotating large-scale point cloud datasets, we propose an unsupervised learning approach to learn features from unlabeled point cloud ”3D object” dataset by using part contrasting and object clustering with GNNs. In the contrast learning step, all the samples in the 3D object dataset are cut into two parts and put into a …
Integrating Multi-Source Weather Data For Deep Learning, Haidar A. Alanbari Mr
Integrating Multi-Source Weather Data For Deep Learning, Haidar A. Alanbari Mr
Dissertations and Theses
Big Data has been playing a major role in the domain of Deep Learning applications as many companies and institutions continue to find solutions and extract certain trends in fields of climate change, weather forecasting and meteorology. This project extracts weather events data from multiple data sources that are supported by National Centers for Environmental information (NCEI) [1] and Amazon Web Services (AWS) [2]. Data sources include Next-Generation NEXRAD [3] Doppler radar reflectivity, GOES-16 [4] multi-channel satellite imagery and NCEI [1] storm events. Then, it integrates and refines data in proper formats to be fed to the open-source Detectron [5] …
Biomimetic Design And Construction Of A Bipedal Walking Robot, Alexander Gabriel Steele
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 …
Silicon Compilation And Test For Dataflow Implementations In Gasp And Click, Swetha Mettala Gilla
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 …
Making Software, Making Regions: Labor Market Dualization, Segmentation, And Feminization In Austin, Portland And Seattle, Dillon Mahmoudi
Making Software, Making Regions: Labor Market Dualization, Segmentation, And Feminization In Austin, Portland And Seattle, Dillon Mahmoudi
Dissertations and Theses
Through mixed-methods research, this dissertation details the regionally variegated and place-specific software production processes in three second-tier US software regions. I focus on the relationship between different industrial, firm, and worker production configurations and broad-based economic development, prosperity, and inequality. I develop four main empirical findings.
First, I argue for a periodization of software production that tracks with changes in software laboring activity, software technologies, and wage-employment relationships. Through a GIS-based method, I use the IPUMS-USA to extensively measure the amount and type of software labor in industries across the US between 1970 and 2015. I map the uneven geography …
Brief Study Of Classification Algorithms In Machine Learning, Ramesh Sankara Subbu
Brief Study Of Classification Algorithms In Machine Learning, Ramesh Sankara Subbu
Dissertations and Theses
The purpose of this study is to briefly learn the theory and implementation of three most commonly used Machine Learning algorithms: k-Nearest Neighbors (kNN), Decision Trees and Naïve Bayes. All these algorithms fall under the Classification algorithm category of Unsupervised Machine Learning. This paper is constructed structurally in explaining the working theory behind each algorithm and an implementation of a Machine Learning problem solved by each algorithm. KNN algorithm is designed using Euclidean distance measurement and Decision Trees make use of ID3 algorithm as a basis. We conclude the study by providing an overall picture of its strengths and weaknesses …
2d Vector Map And Database Design For Indoor Assisted Navigation, Luciano Caraciolo Albuquerque
2d Vector Map And Database Design For Indoor Assisted Navigation, Luciano Caraciolo Albuquerque
Dissertations and Theses
In this paper we implemented a 2D Vector Map, map editor and Database design intended to provide an efficient way to convert cad files from indoor environments to a set of vectors representing hallways, doors, exits, elevators, and other entities embedded in a floor plan, and save them in a database for use by other applications, such as assisted navigation for blind people.
A graphical application as developed in C++ to allow the user to input a CAD DXF file, process the file to automatically obtain nodes and edges, and save the nodes and edges to a database for posterior …
Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi
Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi
Dissertations and Theses
The overall objective of this thesis is to build an integrated, inexpensive, human-sized humanoid robot from scratch that looks and behaves like a human. More specifically, my goal is to build an android robot called Marie Curie robot that can act like a human actor in the Portland Cyber Theater in the play Quantum Debate with a known script of every robot behavior. In order to achieve this goal, the humanoid robot need to has degrees of freedom (DOF) similar to human DOFs. Each part of the Curie robot was built to achieve the goal of building a complete humanoid …
Information Representation And Computation Of Spike Trains In Reservoir Computing Systems With Spiking Neurons And Analog Neurons, Amin Almassian
Information Representation And Computation Of Spike Trains In Reservoir Computing Systems With Spiking Neurons And Analog Neurons, Amin Almassian
Dissertations and Theses
Real-time processing of space-and-time-variant signals is imperative for perception and real-world problem-solving. In the brain, spatio-temporal stimuli are converted into spike trains by sensory neurons and projected to the neurons in subcortical and cortical layers for further processing.
Reservoir Computing (RC) is a neural computation paradigm that is inspired by cortical Neural Networks (NN). It is promising for real-time, on-line computation of spatio-temporal signals. An RC system incorporates a Recurrent Neural Network (RNN) called reservoir, the state of which is changed by a trajectory of perturbations caused by a spatio-temporal input sequence. A trained, non- recurrent, linear readout-layer interprets the …