Computer Engineering Commons^™

Happiness And Policy Implications: A Sociological View, Sarah M. Kahl

Dissertations, Theses, and Capstone Projects

The World Happiness Report is released every year, ranking each country by who is “happier” and explaining the variables and data they have used. This project attempts to build from that base and create a machine learning algorithm that can predict if a country will be in a “happy” or “could be happier” category. Findings show that taking a broader scope of variables can better help predict happiness. Policy implications are discussed in using both big data and considering social indicators to make better and lasting policies.

Smartphone Control Of Rc Cars, Weston R. Fitzgerald

Electrical Engineering

The smartphone-controlled RC (remote-controlled) car is an inexpensive remote-controlled car designed to be fast and portable. Instead of manufacturing, packaging, and shipping a separate controller, the remote control is implemented in a phone application, which saves time and money in both the design process and the manufacturing process. Utilizing the user’s smartphone is more cost-effective since mobile devices are a common recurrence, and packaging fewer devices results in overall better portability of the product.

This smartphone-controlled car is speedy and intuitive to learn for typical smartphone users. The user can change the car’s speed and direction wirelessly using their phone; …

A Machine Learning Approach To Predicting The Onset Of Type Ii Diabetes In A Sample Of Pima Indian Women, Meriem Benarbia

Dissertations, Theses, and Capstone Projects

Type II diabetes is a disease that affects how the body regulates and uses sugar (glucose) as a fuel. This chronic disease results in too much sugar circulating in the bloodstream. High blood sugar levels can lead to circulatory, nervous, and immune systems disorders. Machine learning (ML) techniques have proven their strength in diabetes diagnosis. In this paper, we aimed to contribute to the literature on the use of ML methods by examining the value of a number of supervised machine learning algorithms such as logistic regression, decision tree classifiers, random forest classifiers, and support vector classifiers to identify factors …

Runtime Energy Savings Based On Machine Learning Models For Multicore Applications, Vaibhav Sundriyal, Masha Sosonkina

Electrical & Computer Engineering Faculty Publications

To improve the power consumption of parallel applications at the runtime, modern processors provide frequency scaling and power limiting capabilities. In this work, a runtime strategy is proposed to maximize energy savings under a given performance degradation. Machine learning techniques were utilized to develop performance models which would provide accurate performance prediction with change in operating core-uncore frequency. Experiments, performed on a node (28 cores) of a modern computing platform showed significant energy savings of as much as 26% with performance degradation of as low as 5% under the proposed strategy compared with the execution in the unlimited power case.

Strainer: State Transcript Rating For Informed News Entity Retrieval, Thomas M. Gerrity

Master's Theses

Over the past two decades there has been a rapid decline in public oversight of state and local governments. From 2003 to 2014, the number of journalists assigned to cover the proceedings in state houses has declined by more than 30\%. During the same time period, non-profit projects such as Digital Democracy sought to collect and store legislative bill and hearing information on behalf of the public. More recently, AI4Reporters, an offshoot of Digital Democracy, seeks to actively summarize interesting legislative data.

This thesis presents STRAINER, a parallel project with AI4Reporters, as an active data retrieval and filtering system for …

Accelerating Graphics Rendering On Risc-V Gpus, Joshua Simpson

Master's Theses

Graphics Processing Units (GPUs) are commonly used to accelerate massively parallel workloads across a wide range of applications from machine learning to cryptocurrency mining. The original application for GPUs, however, was to accelerate graphics rendering which remains popular today through video gaming and video rendering. While GPUs began as fixed function hardware with minimal programmability, modern GPUs have adopted a design with many programmable cores and supporting fixed function hardware for rasterization, texture sampling, and render output tasks. This balance enables GPUs to be used for general purpose computing and still remain adept at graphics rendering. Previous work at the …

A Study Of Grammar-Based Fuzzing Approaches, Ziwei Wu

Master's Theses

Fuzzing is the process of finding security vulnerabilities in code by creating inputs that will activate the exploits. Grammar-based fuzzing uses a grammar, which represents the syntax of all inputs a target program will accept, allowing the fuzzer to create well-formed complex inputs. This thesis conducts an in-depth study on two blackbox grammar-based fuzzing methods, GLADE and Learn&Fuzz, on their performance and usability to the average user. The blackbox fuzzer Radamsa was also used to compare fuzzing effectiveness. From our results in fuzzing PDF objects, GLADE beats both Radamsa and Learn&Fuzz in terms of coverage and pass rate. XML inputs …

Specialized Named Entity Recognition For Breast Cancer Subtyping, Griffith Scheyer Hawblitzel

Master's Theses

The amount of data and analysis being published and archived in the biomedical research community is more than can feasibly be sifted through manually, which limits the information an individual or small group can synthesize and integrate into their own research. This presents an opportunity for using automated methods, including Natural Language Processing (NLP), to extract important information from text on various topics. Named Entity Recognition (NER), is one way to automate knowledge extraction of raw text. NER is defined as the task of identifying named entities from text using labels such as people, dates, locations, diseases, and proteins. There …

Improving Relation Extraction From Unstructured Genealogical Texts Using Fine-Tuned Transformers, Carloangello Parrolivelli

Master's Theses

Though exploring one’s family lineage through genealogical family trees can be insightful to developing one’s identity, this knowledge is typically held behind closed doors by private companies or require expensive technologies, such as DNA testing, to uncover. With the ever-booming explosion of data on the world wide web, many unstructured text documents, both old and new, are being discovered, written, and processed which contain rich genealogical information. With access to this immense amount of data, however, entails a costly process whereby people, typically volunteers, have to read large amounts of text to find relationships between people. This delays having genealogical …

Low-Cost Uav Swarm For Real-Time Object Detection Applications, Joel Valdovinos Miranda

Master's Theses

With unmanned aerial vehicles (UAVs), also known as drones, becoming readily available and affordable, applications for these devices have grown immensely. One type of application is the use of drones to fly over large areas and detect desired entities. For example, a swarm of drones could detect marine creatures near the surface of the ocean and provide users the location and type of animal found. However, even with the reduction in cost of drone technology, such applications result costly due to the use of custom hardware with built-in advanced capabilities. Therefore, the focus of this thesis is to compile an …

Viability And Implementation Of A Vector Cryptography Extension For Risc-V, Jonathan W. Skelly

Master's Theses

RISC-V is an open-source instruction-set architecture (ISA) forming the basis of thousands of commercial and experimental microprocessors. The Scalar Cryptography extension ratified in December 2021 added scalar instructions that target common hashing and encryption algorithms, including SHA2 and AES. The next step forward for the RISC-V ISA in the field of cryptography and digital security is the development of vector cryptography instructions.

This thesis examines if it is viable to add vector implementations of existing RISC-V scalar cryptography instructions to the existing vector instruction format, and what improvements they can make to the execution of SHA2 and AES algorithms. Vector …

Who Is Missing? Characterizing The Participation Of Different Demographic Groups In A Korean Nationwide Daily Conversation Corpus, Haewoon Kwak, Jisun An, Kunwoo Park

Research Collection School Of Computing and Information Systems

A conversation corpus is essential to build interactive AI applications. However, the demographic information of the participants in such corpora is largely underexplored mainly due to the lack of individual data in many corpora. In this work, we analyze a Korean nationwide daily conversation corpus constructed by the National Institute of Korean Language (NIKL) to characterize the participation of different demographic (age and sex) groups in the corpus.

Freed: An Efficient Privacy-Preserving Solution For Person Re-Identification, Bowen Zhao, Yingjiu Li, Ximeng Liu, Hwee Hwa Pang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Person Re-IDentification (Re-ID) is a critical technology to identify a target person from captured person images by surveillance cameras. However, person Re-ID has triggered great concerns of personal image privacy. Although the law (e.g., GDPR) has stipulated person images are personal private data, there is no an efficient solution to tackle the image privacy concern for person Re-ID. To this end, we propose FREED, the first system solution for privacy-preserving person Re-ID, which supports the state-of-the-art person Re-ID operations on encrypted feature vectors of person images. To handle the encryption of feature vectors effectively and enable person Re-ID operations on …

Taxi Travel Time Based Geographically Weighted Regression Model (Gwr) For Modeling Public Housing Prices In Singapore, Yi’An Wang, Fangyi Cai, Shih-Fen Cheng, Bo Wu, Kai Cao

Research Collection School Of Computing and Information Systems

In this research, a taxi travel time based Geographically Weighted Regression model (GWR) is proposed and utilized to model the public housing price in the case study of Singapore. In addition, a comparison between the proposed taxi data driven GWR and other models, such as ordinary least squares model (OLS), GWR model based on Euclidean distance and GWR model based on public transport travel time, have also been carried out. Results indicates that taxi travel time based GWR model has better fitting performance than the OLS model, and slightly better than the Euclidean distance-based GWR model, however, it is not …

Local Learning Algorithms For Stochastic Spiking Neural Networks, Bleema Rosenfeld

Dissertations

This dissertation focuses on the development of machine learning algorithms for spiking neural networks, with an emphasis on local three-factor learning rules that are in keeping with the constraints imposed by current neuromorphic hardware. Spiking neural networks (SNNs) are an alternative to artificial neural networks (ANNs) that follow a similar graphical structure but use a processing paradigm more closely modeled after the biological brain in an effort to harness its low power processing capability. SNNs use an event based processing scheme which leads to significant power savings when implemented in dedicated neuromorphic hardware such as Intel’s Loihi chip.

This work …

Outdoor Operations Of Multiple Quadrotors In Windy Environment, Deepan Lobo

Dissertations

Coordinated multiple small unmanned aerial vehicles (sUAVs) offer several advantages over a single sUAV platform. These advantages include improved task efficiency, reduced task completion time, improved fault tolerance, and higher task flexibility. However, their deployment in an outdoor environment is challenging due to the presence of wind gusts. The coordinated motion of a multi-sUAV system in the presence of wind disturbances is a challenging problem when considering collision avoidance (safety), scalability, and communication connectivity. Performing wind-agnostic motion planning for sUAVs may produce a sizeable cross-track error if the wind on the planned route leads to actuator saturation. In a multi-sUAV …

Design And Control Of Next-Generation Uavs For Effectively Interacting With Environments, Caiwu Ding

Dissertations

In this dissertation, the design and control of a novel multirotor for aerial manipulation is studied, with the aim of endowing the aerial vehicle with more degrees of freedom of motion and stability when interacting with the environments. Firstly, it presents an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. The effectiveness of this method is demonstrated through simulation. Secondly, a humanoid robot arm is adopted to serve as …

Towards A Cross-Layer Coupled Design Framework For Big Data Workflows, Qianwen Ye

Dissertations

The processing and analysis of big data increasingly rely on workflow technologies for knowledge discovery and scientific innovation. The execution of such workflows goes far beyond the capability and capacity of single computers and is now commonly supported on reliable and scalable data storage and analysis platforms in distributed environments, such as the Hadoop ecosystem. Workflow performance largely depends on how big data systems are configured and used. For example, the makespan of a big data workflow is affected by multiple layers of big data systems, including the parallel computing engine it runs on, the resource manager that orchestrates various …

Rechargeable Multi-Cell Battery, Wei Qiao, Taesic Kim, Liyan Qu

Department of Electrical and Computer Engineering: Faculty Publications

A method for power management of a multi - cell battery includes identifying a desired power value and voltage value , determining a battery voltage value and a battery current value for a battery , determining a number of battery banks from a plurality of battery banks to use for the battery , where each battery bank includes one or more battery cells ( or battery modules ) , checking availability of each of the one or more battery cells ( or battery modules ) , selecting one or more battery banks from the plurality of battery banks , where …

Un-Fair Trojan: Targeted Backdoor Attacks Against Model Fairness, Nicholas Furth

Theses

Machine learning models have been shown to be vulnerable against various backdoor and data poisoning attacks that adversely affect model behavior. Additionally, these attacks have been shown to make unfair predictions with respect to certain protected features. In federated learning, multiple local models contribute to a single global model communicating only using local gradients, the issue of attacks become more prevalent and complex. Previously published works revolve around solving these issues both individually and jointly. However, there has been little study on the effects of attacks against model fairness. Demonstrated in this work, a flexible attack, which we call Un-Fair …

Meta-Algorithms In Machine Learning, Vishnu Pendyala

Open Educational Resources

This presentation explores how to make the best of models impacted by bias and variance. Meta-learning minimizes loss. Ensemble methods, including Bagging, Adaboost, Random Forest, Gradient Boosting, and Stacking, are discussed. These methods perturb data (X or Y) using techniques like bootstrap sampling, k-fold sampling, weighted sampling, and random subspaces. Models are generated in parallel or sequentially, with aggregation strategies such as mean, mode, weighted response, and metamodel. The presentation also touches upon deep learning and one-shot learning, and explains how distances become less meaningful in high dimensions.

More details: https://events.vtools.ieee.org/m/315184

Video Recording: https://ieeetv.ieee.org/video/meta-algorithms-in-machine-learning

Middle School Students Communicating Computational Thinking: A Systemic Functional Linguistics-Case Study Of Bilingual, Collaborative Teaching/Learning Of Computer Programming In Python, Jose Antonio Lecea Yanguas

Language, Literacy, and Sociocultural Studies ETDs

This dissertation presents the first Systemic Functional Linguistics-based analysis of the teaching/learning of computational thinking through computer programming and comprehensive analysis of discourse of a whole computer programming course at any educational level. The current educational research raises questions about the nature of authentic computational

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thinking teaching/learning environments and how they happen moment-to-moment. In one such environment, I examined the discourse of a facilitator, three students, and their Language Arts teacher in an introductory middle school after-school course (approximately 30 hours) in spring 2017 as students created a video in Python.

Methodologically, I show how a Systemic Functional Linguistics-based …

A High-Density Theta Burst Paradigm Enhances The Aftereffects Of Transcranial Magnetic Stimulation: Evidence From Focal Stimulation Of Rat Motor Cortex, Qinglei Meng, Hieu Nguyen, Antonia Vrana, Simone Baldwin, Charlotte Qiong Li, Antonia Giles, Jun Wang, Yihong Yang, Hanbing Lu

Department of Electrical and Computer Engineering: Faculty Publications

Background: Theta burst stimulation (TBS) is an efficient noninvasive neuromodulation paradigm that has been widely adopted, clinically. However, the efficacy of TBS treatment remains similarly modest as conventional 10 Hz repetitive transcranial magnetic stimulation (rTMS).

Objective/hypothesis: To develop a new TBS paradigm that enhances the effects of TMS administration while maintaining high time-efficiency.

Methods: We describe here a new TMS paradigm, named High-Density Theta Burst Stimulation (hdTBS). This paradigm delivers up to 6 pulses per burst, as opposed to only 3 in conventional TBS, while maintaining the inter-burst interval of 200 ms (or 5 Hz) - a …

Metasoftware: Building Blocks For Legal Technology, Houman Shadab

Seattle Journal of Technology, Environmental, & Innovation Law

This Article develops a novel concept in information technology called “metasoftware.” It then applies the concept of metasoftware to developing legal technology.

Metasoftware enables users to create the software of their choosing and stands in sharp contrast to traditional, functional. Functional software is the default type of software that is currently produced and includes word processing, email, social networking, enterprise resource management, online marketplaces, and video game software. Metasoftware, by contrast, is not functional. Metasoftware presents the user with a blank slate upon which to build functional software.

I argue that software is metasoftware to that extent that (1) it …

Collaborative Design And Simulation Integrated Method Of Civil Aircraft Take-Off Scenarios Based On X Language, Pengfei Gu, Lin Zhang, Zhen Chen, Junjie Ye

Journal of System Simulation

Abstract: For the large and complex products, the current traditional model-based systems engineering (MBSE) method of the integrated implementation of multiple modeling and simulation languages and platforms for system design and simulation verification can not ensure the efficient and accurate feedback of system design to realize the quick design optimization. X language, a new generation of integrated modeling and simulation language based on complex systems and supporting MBSE, is used to realize the integrated modeling and simulation on cross-domain subsystems of civil aircraft for the take-off scenarios. From the demand analysis of the take-off process of civil aircraft, the system-level …

Cross Level Switching Technology For Multi-Resolution Model Of Complex Products, Wei Li, Wenjia Zhang, Heming Zhang

Journal of System Simulation

Abstract: In the R&D of complex products, different design stages have different design goals and different simulation tasks, which need different resolution complex products simulation models. The models and interfaces for the multi-resolution characteristics are defined and thus the resolution control mechanism is studied. The description mechanisms for the system structure status and model resolution state are established separately, the control mechanism for the system resolution is proposed, and a cross level switching technology is sorted out. The experimental results show that the method can effectively solve the problem of model resolution switching, which ensures the simulation accuracy, improves …

A Cyber-Physical Integrated Modeling Method Oriented For Motion Simulation Of Complex Systems, Wenzheng Liu, Heming Zhang

Journal of System Simulation

Abstract: The traditional virtual modeling of motion simulation lacks the dynamic modeling of cyber subsystems and physical subsystems in complex systems. The advantages of the traditional kinematic virtual modeling and cyber calculation are combined, and aiming at the problem that the accuracy and real-time property of motion simulation cannot meet the actual industrial manufacturing requirements, a cyber physical integrated modeling method for the motion simulation of complex systems is proposed. The inconsistency between real robotic driving and virtual robot motion is solved, which is verified by a case study of mechanical arm motion control. A virtuality-reality mapping platform for complex …

Uav Formation Recovery And Consistency Simulation Based On Improved Potential Field, Ning Wang, Jiyang Dai, Jin Ying

Journal of System Simulation

Abstract: Aiming at the problems of multi-UAV formation collision avoidance, formation recovery and the consistency of position and velocity convergence, a distributed cooperative formation control algorithm based on the improved potential field principle and consistency theory is proposed. The static obstacle model, UAV particle model and the second-order system dynamic model are established; the coordination potential field function with coordination factors and communication weights is defined, which can achieve the control objectives of collision avoidance and formation recovery; on the basic consistency protocol, the formation center reference vector, expected speed and speed stabilization items are introduced to achieve the convergence …

Multi-Objective Optimization Configuration Of Agv System Based On Response Surface And Nsga-Ii, Jianlin Fu, Guofu Ding, Jian Zhang, Haifan Jiang, Peipei Guo

Journal of System Simulation

Abstract: Automated guided vehicle(AGV) system plays an important role in the production flexibility and efficiency in manufacturing systems. Due to the dynamic and stochastic characteristics of AGV system with many variables, its optimal configuration is relatively complex. A method combining system simulation, mathematical analysis and multi-objective optimization is proposed to optimize the configuration of AGV system. The discrete event simulation is used to simulate the operation of AGV system, the sensitivity analysis is used to separate design variables, the factorial experiments and response surface methods are used to build the fitting multi-objective optimization mathematical model, and the non-dominated sorting genetic …

Study On The Scale Characteristics Of Permeability Of Tpms Porous Materials, Tong Wu, Qinghui Wang, Zhijia Xu

Journal of System Simulation

Abstract: Triply Periodic Minimal Surface (TPMS) has been widely used in the design of porous materials, however, there is insufficient research on the scale characteristics of permeability. Four commonly used TPMS units are chosen as the research object, based on the introduction of their mathematical models and porosity control methods, a numerical simulation model based on CFD (computational fluid dynamics) is established; TPMS units and cubic porous structures with different porosities are analyzed, the quantitative correlation between their scales and permeability is clarified, i.e., within the selected scale range, the permeability of various TPMS units and cubic porous structures is …