Physical Sciences and Mathematics Commons^™

Multi-Objective Routing For Distributed Controllers, Konstantin Y. Rubin

Theses and Dissertations

A long-term goal of future naval shipboard power systems is the ability to manage energy flow with sufficient flexibility to accommodate future platform requirements such as better survivability, continuity, and support of pulsed and other demanding loads. To facilitate scalable, low-latency global distributed system control, each control module can include an integrated network interface connected through multiple channels onto a direct, multi-hop network topology. In this work, we focus on a 2D Torus, in which control nodes are arranged in a regular 2D grid, with each node connected through point-to-point connections to its four immediate neighbors. An important advantage of …

Optimization And Application Of Electrochemical Probes For Neurotransmitter Detection, Colby E. Witt

Theses and Dissertations

The brain is a complex matrix that is difficult to study. Signaling molecules, neurotransmitters, are constantly being released and sequestered back into neurons within milliseconds to facilitate communication and normal function, a process called neurotransmission. There are few analytical techniques available to selectively probe such a dynamic system, and even fewer can detect these discrete changes in real-time. In order to make robust measurements in the brain you need speed, sensitivity, selectivity and small probe size, which are encompassed by fast-voltammetry with microelectrodes. Traditional fast-voltammetry at carbon fiber microelectrodes (fast-scan cyclic voltammetry (FSCV)) requires background subtraction to overcome the large …

Towards More Trustworthy Deep Learning: Accurate, Resilient, And Explainable Countermeasures Against Adversarial Examples, Fei Zuo

Theses and Dissertations

Despite the great achievements made by neural networks on tasks such as image classification, they are brittle and vulnerable to adversarial example (AE) attacks, which are crafted by adding human-imperceptible perturbations to inputs in order that a neural-network-based classifier incorrectly labels them. Along with the prevalence of deep learning techniques, the threat of AEs attracts increasingly attentions since it may lead to serious consequences in some vital applications such as disease diagnosis.

To defeat attacks based on AEs, both detection and defensive techniques attract the research community’s attention. Given an input image, the detection system outputs whether it is an …

Cluster Hire In Social Networks Using Modified Weighted Structural Clustering Algorithm For Networks (Mwscan), Harshil Patal

Electronic Theses and Dissertations

The concept of effective collaboration within a group is immensely used in organizations as a viable means for improving team performance. Any organization or prominent institute, who works with multiple projects needs to hire a group of experts who can complete a set of projects. When hiring a group of experts, numerous considerations must be taken into account. In the Cluster Hire problem, we are given a set of experts, each having a set of skills. Also, we are given a set of projects, each requiring a set of skills. Upon completion of each project, a profit is generated for …

Computational Enzymology On Sulfur-Containing Enzymes: From Method To Application, Paul Meister

Electronic Theses and Dissertations

Sulfur-containing biomolecules display incredible functional diversity. Indeed, in addition to thiols and thioethers, S-nitrosothiols, 3,4-coordinate, sulfoxides, persulfides and now even polysulfides are commonly observed intermediates. Unfortunately, however, their biological synthesis and roles remain poorly understood. In addition, sulfur-containing species can access a broad range of oxidation states and thus can act as either an electrophile or nucleophile giving rise to an even more diverse set of sulfur-derived functional groups. However, these unique properties can lead to difficulties in characterizing such compounds experimentally and reinforces the need for computational studies to reliably predict their structural and energetic properties. In this dissertation, …

Comparative Study Of Reinforcement Learning Methods In Path Planning, Daniel Obawole

Electronic Theses and Dissertations

In order to perform a large variety of tasks and achieve human-level performance in complex real-world environments, an intelligent agent must be able to learn from its dynamically changing environment. Generally speaking, agents have limitations in obtaining an accurate description of the environment from what they perceive because they may not have all the information about the environment. The present research is focused on reinforcement learning algorithms that represent a defined category in the field of machine learning because of their unique approach based on a trial-error basis. Reinforcement learning is used to solve control problems based on received rewards. …

Exploring The Relationship Between Mandatory Helmet Use Regulations And Adult Cyclists’ Behavior In California Using Hybrid Machine Learning Models, Fatemeh Davoudi Kakhki, Maria Chierichetti

Mineta Transportation Institute

In California, bike fatalities increased by 8.1% from 2015 to 2016. Even though the benefits of wearing helmets in protecting cyclists against trauma in cycling crash has been determined, the use of helmets is still limited, and there is opposition against mandatory helmet use, particularly for adults. Therefore, exploring perceptions of adult cyclists regarding mandatory helmet use is a key element in understanding cyclists’ behavior, and determining the impact of mandatory helmet use on their cycling rate. The goal of this research is to identify sociodemographic characteristics and cycling behaviors that are associated with the use and non-use of bicycle …

Cluster Hire In Social Networks Using Modified Weighted Structural Clustering Algorithm For Networks (Mwscan), Harshil Patel

Electronic Theses and Dissertations

The concept of effective collaboration within a group is immensely used in organizations as a viable means for improving team performance. Any organization or prominent institute, who works with multiple projects needs to hire a group of experts who can complete a set of projects. When hiring a group of experts, numerous considerations must be taken into account. In the Cluster Hire problem, we are given a set of experts, each having a set of skills. Also, we are given a set of projects, each requiring a set of skills. Upon completion of each project, a profit is generated for …

The Development And Application Of Targeted Edna Metabarcoding For Monitoring Freshwater And Marine Ais, Yueyang Wu

Electronic Theses and Dissertations

Species invasions are of critical concern due to their significant impacts on ecosystems and social economies, of which aquatic invasive species (AIS) often pose significant challenges in their control and management, notably because of difficulties in early detection. Environmental DNA (eDNA) provides a promising tool in advancing the detection of newly introduced aquatic organisms because of its high sensitivity and ease of use compared to traditional capture-based methods. Although eDNA-based methods are increasingly used worldwide, especially in aquatic ecosystems, most studies focus on a limited number of target species despite a pressing need for broad taxonomic monitoring for conservation and …

Meta-Heuristic Approach For Course Scheduling Problem, Amanta Sunny

Electronic Theses and Dissertations

Nowadays, much research is being carried out to find efficient algorithms for optimal automated university course timetable problems (UCTP). UCTP allocates the university's events like lectures, exams to the various resources, including instructors, students, lecture time and classrooms. Class scheduling is one of the biggest challenging problems of educational institutions. In this thesis, the aim is to improve the state-of-art for a class scheduling problem considering some hard and soft constraints. Hard constraints must be satisfied. Soft constraints need not be satisfied, but there is a penalty for each soft constraint violation. We also have a timing penalty for scheduling …

Neural Network Based Approach For Detecting Location Spoofing In Vehicular Communication, Smarth Kukreja

Electronic Theses and Dissertations

Vehicular Ad hoc Network (VANET) is an evolving subset of MANET. It's deployed on the roads, where vehicles act as mobile nodes. Active security and Intelligent Transportation System (ITS) are integral applications of VANET, which require stable and uninterrupted vehicle-to-vehicle communication technology. VANET, is a type of wireless network, due to which it is quite prone to security attacks. Extremely dynamic connections, sensitive data sharing and time-sensitivity of this network make it a vulnerable to security attacks. The messages shared between the vehicles are the basic safety message (BSM), these messages are broadcasted by each vehicle in the network to …

A Study Of Some Transportation Networks From A Complex Network Perspective Chakrabarthy, Pooja., Pooja Chakrabarthy

Electronic Theses and Dissertations

Complex networks are ubiquitous; consider, for example, road networks, protein-protein interaction networks, metabolic networks, power networks etc. They can be applied to a wide range of areas like mathematics, computer science, social, and biological sciences. Random graphs can aid in observing the topological features in various data sources and give insights on their respective real-world networks. In this thesis, we study the particular case of small-world networks and compare them with random and regular networks. We start by explaining the complexity of networks and how graph theory can be applied to complex networks to understand their topological properties. Using which, …

Multifaceted Environmental Enrichment In Industrial Fish Hatcheries: The Influence Of Enriched Rearing On The In-Situ Behaviour And Post-Stocking Success Of Juvenile Atlantic Salmon (Salmo Salar), Justine Elizabeth Mcandrews

Electronic Theses and Dissertations

Hatchery fish reared and stocked to sustain or restore wild populations often perform poorly in novel environments compared to their wild counterparts. To combat maladaptive hatchery-acquired traits environmental enrichment is an emerging tool used to provide ‘life skills training’ to hatchery fish prior to release. Through the application of simple yet multifaceted enrichment protocols in an industrial fish hatchery, this thesis aimed to demonstrate how enrichment could be applied to improve the ecological viability of stocked fish. At a provincially-run fish hatchery, a subgroup of juvenile Atlantic salmon (Salmo salar) were subject to 10 weeks of environmental enrichment …

A Framework To Study The Impact Of Interventions On Social Isolation During Pandemics Using Multi-Agent Simulation, Simranpreet Kaur

Electronic Theses and Dissertations

The spread of Coronavirus, widely known as COVID-19, has posed detrimental effects worldwide, affecting almost every primary sector. Due to its asymptomatic behavior and non-early diagnosis, government and health organizations implemented interventions such as physical distancing, lockdown, and quarantine, to mitigate the spread of the virus. Studies have shown that a connection exists between social isolation and health risks experienced by individuals. Thus, this research proposes an agent-based model to address the impact of varying interventions in our society. For simulation purposes, the SEIR model is followed, and agents are categorized into two classes based on their pace of movement, …

Variational Energies For The Rydberg P States Of Helium, Cody Mcleod

Electronic Theses and Dissertations

The aim of this work is to solve the quantum mechanical three-body problem for helium, and to obtain high precision eigenvalues for the higher-lying Rydberg states where previous methods have been of limited accuracy. A variational method in correlated Hylleraas coordinates is used involving three distinct distance scales, called a triple basis set. The eigenvalues and matrix elements of other operators are computed for P states of helium up to n = 15 using the varational method with a triple basis set in Hylleraas coordinates. The construction of the wave functions, as well as the behaviour of the asymptotic, intermediate …

Packing Non-Self-Crossing Edge-Disjoint Spanning Paths Into A Point Set, Rishav Chatterjee

Electronic Theses and Dissertations

The term packing refers to the arrangement of multiple geometrical structures or shapes such as circles, squares, triangles, or polygons into a fixed and finite set of points. The geometric structures to be packed can also be trees and paths. Packing is also possible in a 3-dimensional space with geometric structures such as spheres, cylinders, and cubes.

The concept of packing was introduced more than half a century ago. Since then, many researchers have studied the packing strategies of different geometric structures in different configurations of point-set. Packing strategies help to construct and arrange multiple geometric structures in a predetermined …

Traffic Sign And Light Detection Using Deep Learning For Automotive Applications, Humaira Naimi

Electronic Theses and Dissertations

Traffic sign and light detection are core components of Advanced Driver Assistance Systems (ADAS) and self-driving vehicles. The automotive industry is widely employing numerous approaches for automation through computer vision techniques. Object detection algorithms based on deep learning can be divided into two main categories, two stage and single stage detection algorithms. Two stage algorithms are designed to improve detection accuracy. While single stage algorithms are constructed to be faster, this increases their suitability for real time applications. This thesis presents a lightweight traffic sign and light detector by adapting a single stage, Single Shot Multibox Detection (SSD) algorithm by …

Content-Based Image Retrieval Using Hierarchical Decomposition Of Feature Descriptors, Eisa Adil

Electronic Theses and Dissertations

Due to modern technological advancements, the pervasiveness and complexity of images have remarkably increased. Searching databases for similar visual content, i.e., Content-Based Image Retrieval (CBIR), remains an open research problem. In this thesis, we propose a novel CBIR approach, in which each symbolic image has a quadtree representation consisting of SIFT-based orientational keypoints. Every quadrant node in the tree represents the dominant orientation of a region in the image. The quadtree image representation is used for bitwise signature indexing and image similarity measurement. Also, we convert each quadtree image representation to a trainable feature vector for use in the K-Nearest …

Neural Network-Based Multi-Task Learning For Product Opinion Mining, Manil Patel

Electronic Theses and Dissertations

Aspect Based Opinion Mining (ABOM) systems take user's reviews or posts as input from social media. The system aims to extract the aspect terms (e.g., pizza) and categories (e.g., food) and their polarities, to help the customers and identify product weaknesses. By solving these product weaknesses, companies can enhance customer satisfaction, increase sales, and boost revenues. Neural networks are widely used as classification algorithms for performing ABOM tasks for both the training (learning) phase from historical reviews to form class labels and the testing phase to predict the label for unknown data (new reviews). Neural network algorithms consist of artificial …

Novel Approaches To Cognitive Load Estimation In Automated Driving Systems, Prarthana Pillai

Electronic Theses and Dissertations

Automation has become indispensable in all walks of everyday life. In driving environments, Automated Driving Systems (ADS) aid the driver by reducing the required workload and by improving road safety. However, the present-day ADS requires the human driver to remain vigilant at all times and be ready to take over whenever the driving task requires. Thus, continuous monitoring of the drivers is important for adopting ADS. Such monitoring can be done in ADS by measuring the cognitive load experienced by the drivers. Studies show various methods to estimate cognitive load, however, the state of the art in cognitive load estimation, …

Empirical Modeling Of Tilt-Rotor Aerodynamic Performance, Michael C. Stratton

Mechanical & Aerospace Engineering Theses & Dissertations

There has been increasing interest into the performance of electric vertical takeoff and landing (eVTOL) aircraft. The propellers used for the eVTOL propulsion systems experience a broad range of aerodynamic conditions, not typically experienced by propellers in forward flight, that includes large incidence angles relative to the oncoming airflow. Formal experiment design and analysis techniques featuring response surface methods were applied to a subscale, tilt-rotor wind tunnel test for three, four, five, and six blade, 16-inch diameter, propeller configurations in support of development of the NASA LA-8 aircraft. Investigation of low-speed performance included a maximum speed of 12 m/s and …

Geodetic Constraints On A 25-Year Magmatic Inflation Episode Near Three Sisters, Central Oregon, Robert Mccaffrey, Michael Lisowsk, Charles W. Wicks, Daniel Dzurisin

Geology Faculty Publications and Presentations

Crustal inflation near the Three Sisters volcanic center documented since the mid-1990s has persisted for more than two decades. We update past analyses of the event through 2020 by simultaneously inverting InSAR interferograms, GPS time series, and leveling data for time-dependent volcanic deformation source parameters. We explore several source models to estimate how the deformation rate varied through time and to identify parameters that can reproduce measured deformation. Our preferred model is a Mogi source 4.1 km below sea level (5.9 km below the surface) about 5 km west of the summit of South Sister. Inflation started in late 1995 …

Towards Enriching Responses With Crowd-Sourced Knowledge For Task-Oriented Dialogue, Yingxu He, Lizi Liao, Zheng Zhang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Task-oriented dialogue agents are built to assist users in completing various tasks. Generating appropriate responses for satisfactory task completion is the ultimate goal. Hence, as a convenient and straightforward way, metrics such as success rate, inform rate etc., have been widely leveraged to evaluate the generated responses. However, beyond task completion, there are several other factors that largely affect user satisfaction, which remain under-explored. In this work, we focus on analyzing different agent behavior patterns that lead to higher user satisfaction scores. Based on the findings, we design a neural response generation model EnRG. It naturally combines the power of …

Mlcatchup: Automated Update Of Deprecated Machine-Learning Apis In Python, Stefanus Agus Haryono, Thung Ferdian, David Lo, Julia Lawall, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Machine learning (ML) libraries are gaining vast popularity, especially in the Python programming language. Using the latest version of such libraries is recommended to ensure the best performance and security. When migrating to the latest version of a machine learning library, usages of deprecated APIs need to be updated, which is a time-consuming process. In this paper, we propose MLCatchUp, an automated API usage update tool for deprecated APIs of popular ML libraries written in Python. MLCatchUp automatically infers the required transformation to migrate usages of deprecated API through the differences between the deprecated and updated API signatures. MLCatchUp offers …

Target-Guided Emotion-Aware Chat Machine, Wei Wei, Jiayi Liu, Xianling Mao, Guibing Guo, Feida Zhu, Pan Zhou, Yuchong Hu, Shanshan Feng

Research Collection School Of Computing and Information Systems

The consistency of a response to a given post at the semantic level and emotional level is essential for a dialogue system to deliver humanlike interactions. However, this challenge is not well addressed in the literature, since most of the approaches neglect the emotional information conveyed by a post while generating responses. This article addresses this problem and proposes a unified end-to-end neural architecture, which is capable of simultaneously encoding the semantics and the emotions in a post and leveraging target information to generate more intelligent responses with appropriately expressed emotions. Extensive experiments on real-world data demonstrate that the proposed …

The Efficacy Of Collaborative Authoring Of Video Scene Descriptions, Rosiana Natalie, Jolene Kar Inn Loh, Huei Suen Tan, Joshua Shi-Hao Tseng, Ian Luke Yi-Ren Chan, Ebrima H. Jarjue, Hernisa Kacorri, Kotaro Hara

Research Collection School Of Computing and Information Systems

The majority of online video contents remain inaccessible to people with visual impairments due to the lack of audio descriptions to depict the video scenes. Content creators have traditionally relied on professionals to author audio descriptions, but their service is costly and not readily-available. We investigate the feasibility of creating more cost-effective audio descriptions that are also of high quality by involving novices. Specifically, we designed, developed, and evaluated ViScene, a web-based collaborative audio description authoring tool that enables a sighted novice author and a reviewer either sighted or blind to interact and contribute to scene descriptions (SDs)—text that can …

Token Shift Transformer For Video Classification, Zhang Hao, Yanbin. Hao, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Transformer achieves remarkable successes in understanding 1 and 2-dimensional signals (e.g., NLP and Image Content Understanding). As a potential alternative to convolutional neural networks, it shares merits of strong interpretability, high discriminative power on hyper-scale data, and flexibility in processing varying length inputs. However, its encoders naturally contain computational intensive operations such as pair-wise self-attention, incurring heavy computational burden when being applied on the complex 3-dimensional video signals. This paper presents Token Shift Module (i.e., TokShift), a novel, zero-parameter, zero-FLOPs operator, for modeling temporal relations within each transformer encoder. Specifically, the TokShift barely temporally shifts partial [Class] token features back-and-forth …

Quantum Computing: Computational Excellence For Society 5.0, Paul R. Griffin, Michael Boguslavsky, Junye Huang, Robert J. Kauffman, Brian R. Tan

Research Collection School Of Computing and Information Systems

In this chapter, we consider which general business problems may be suitable for exploring the utilization of quantum computing and provide a framework for applying quantum computing. The characteristics of quantum computing systems are mapped into business problems to show the potential advantages of quantum computing. The framework shows how quantum computing can be applied in general, and a use case is offered for quantum machine learning (QML) related to the credit ratings of small and medium-size enterprises (SMEs).

Design And Supervision Model Of Group Projects For Active Learning, Yi Meng Lau, Kyong Jin Shim, Swapna Gottipati

Research Collection School Of Computing and Information Systems

This research paper presents a group project framework for a second-year programming course, which was conducted during the COVID-19 pandemic. The framework offers well defined stages of the group project which allow students to work on their choice of a real-world problem, integrate their learnings from previous courses, and present a working solution. In the group project, students actively participate, reflect, and contribute to achieving the goals set in the learning objectives of the course. Our framework incorporates key features from Kolb’s Experiential Learning Theory (1984) and principles of active learning from Barnes (1989) to achieve active and experiential learning …

Can Differential Testing Improve Automatic Speech Recognition Systems?, Muhammad Hilmi Asyrofi, Zhou Yang, Jieke Shi, Chu Wei Quan, David Lo

Research Collection School Of Computing and Information Systems

Due to the widespread adoption of Automatic Speech Recognition (ASR) systems in many critical domains, ensuring the quality of recognized transcriptions is of great importance. A recent work, CrossASR++, can automatically uncover many failures in ASR systems by taking advantage of the differential testing technique. It employs a Text-To-Speech (TTS) system to synthesize audios from texts and then reveals failed test cases by feeding them to multiple ASR systems for cross-referencing. However, no prior work tries to utilize the generated test cases to enhance the quality of ASR systems. In this paper, we explore the subsequent improvements brought by leveraging …