Digital Commons Network^™

Hybrid Recommender Systems Via Spectral Learning And A Random Forest, Alyssa Williams

Electronic Theses and Dissertations

We demonstrate spectral learning can be combined with a random forest classifier to produce a hybrid recommender system capable of incorporating meta information. Spectral learning is supervised learning in which data is in the form of one or more networks. Responses are predicted from features obtained from the eigenvector decomposition of matrix representations of the networks. Spectral learning is based on the highest weight eigenvectors of natural Markov chain representations. A random forest is an ensemble technique for supervised learning whose internal predictive model can be interpreted as a nearest neighbor network. A hybrid recommender can be constructed by first …

Manus Descriptions Of An Undescribed Mastodon From The Latest Miocene-Earliest Pliocene Gray Fossil Site, With Comparisons To Other North American Proboscidean Taxa, Brenna Hart-Farrar

Electronic Theses and Dissertations

A detailed morphological description of a proboscidean manus from the Gray Fossil Site (GFS), Gray, Tennessee is provided. Manus elements from an American mastodon (Mammut americanum), a Britt’s shovel-tusker (Amebelodon britti), an undescribed small gomphothere species, and a Columbian mammoth (Mammuthus columbi) are used for comparisons. Linear measurements indicate proportional differences between the GFS mastodon and other proboscidean taxa ranging from the Hemphillian to Rancholabrean land mammal ages. Possible pathologies are also described. The purpose of this study is to determine how the GFS mastodon differs in manus morphology and locomotion from different proboscidean …

When Keystroke Meets Password: Attacks And Defenses, Ximing Liu

Dissertations and Theses Collection (Open Access)

Password is a prevalent means used for user authentication in pervasive computing environments since it is simple to be deployed and convenient to use. However, the use of password has intrinsic problems due to the involvement of keystroke. Keystroke behaviors may emit various side-channel information, including timing, acoustic, and visual information, which can be easily collected by an adversary and leveraged for the keystroke inference. On the other hand, those keystroke-related information can also be used to protect a user's credentials via two-factor authentication and biometrics authentication schemes. This dissertation focuses on investigating the PIN inference due to the side-channel …

Gesture-Based Profiling Of Commonplace Lifestyle And Physical Activity Behaviors, Meeralakshmi Radhakrishnan

Dissertations and Theses Collection (Open Access)

The widespread availability of sensors on personal devices (e.g., smartphones, smartwatches) and other cheap, commoditized IoT devices in the environment has opened up the opportunity for developing applications that capture and enhance various lifestyle-driven daily activities of individuals. Moreover, there is a growing trend of leveraging ubiquitous computing technologies to improve physical health and wellbeing. Several of the lifestyle monitoring applications rely primarily on the capability of recognizing contextually relevant human movements, actions and gestures. As such, gesture recognition techniques, and gesture-based analytics have emerged as a fundamental component for realizing personalized lifestyle applications.

This thesis explores how such wealth …

Stem Professional Development For Youth Workers: Results Of A Triangulated Study, Melissa Pearman Fenton, Leslie Hawley, Saundra Wever Frerichs, Kathleen Lodl

Journal of Youth Development

To increase the quality of informal science, technology, engineering, and math (STEM) learning opportunities, many youth development professionals working in out-of-school time (OST) programs need professional development focused on facilitating these types of activities. Nebraska Extension developed an open-access repository of resources that support an ongoing, blended approach to STEM professional development for youth workers. The current study evaluated the impact on staff, programs, and youth achieved by implementing Click2Science resources in sites at a large youth serving organization. Data sources included site or program director/coordinator and frontline staff perceptions about their experiences during the professional development events, observations of …

Estimation Of The Fatigue Life Of Additively Manufactured Metallic Components Using Modified Strain Life Parameters Based On Surface Roughness, Peter Grohs

Masters Theses

In this study, a method is developed to estimate the effects of surface roughness on the fatigue life of additively manufactured titanium Ti6Al4V, aluminum 7075–T6, and steel 4340 alloys through modified strain life parameters using finite element analysis (FEA). This method is highly beneficial to the fatigue analysis of as-built additively manufactured metal components, which possess rough surfaces that reduce fatigue life significantly but are challenging to analyze directly using finite element simulation because of complex geometries, i.e., modeling an exact surface profile is arduous.

An effective stress concentration factor, incorporating roughness data, is defined to quantify their effects on …

Teens In The Somali Diaspora: An Evaluative Program Study, Jennifer Skuza

Journal of Youth Development

Program evaluation is a critical part of program sustainability because evaluation can inform improvements and document impact. Here, 2 Minnesota organizations came together in partnership with the Somali American community to work toward a shared vision, which was to develop a new sustainable program that prepared refugee and immigrant youth for their educational and workforce futures while supporting their cultural way of being. This article shares the evaluative study of this program, which reached teens in the Somali diaspora living in Minnesota. The program team had a long-term interest in developing an evidence-based model to suit this special population; this …

A Heavy Burden: Associations Between Sexual Minority Status, Mental Health, And Bmi In Women, Alison E. A. Goldblatt

Graduate Masters Theses

Sexual minority women (SMW) are at increased risk of elevated body mass index (BMI) compared to heterosexual women, which increases their vulnerability to a variety of chronic diseases. This increased risk of elevated BMI is likely due to unique minority stressors faced by sexual minority individuals, such as internalized heterosexism and discrimination. Minority stressors are associated with poorer mental and physical health among SMW, and SMW may engage in unhealthy coping strategies, like binge eating, to cope with these minority stressors. Research suggests that bisexual women, and other women with non-monosexual orientations, face elevated risks to their physical and psychological …

The Existing Intersectionality Of Gender And Race Differences In Science, Technology, Engineering And Math Fields, Rachael Carrillo

Undergraduate Honors Theses

This thesis will examine the gender differences women and men experience in Science, Technology, Engineering and Math fields (STEM) in undergraduate education focusing on the binary genders--men and women--and their experiences in STEM. Thus, the research question is: Do undergraduate women in STEM experience higher levels of gender differences compared to men in STEM? This is an important research question because if female undergraduates in STEM are experiencing sexism while their male colleagues are not, this phenomenon may create a large issue of inequalities for women in our society. STEM fields are typically higher paying fields and if women are …

Examining The Educational Experiences Of Community Day School Graduates: A Narrative Inquiry, Willie J. Jones Iii

Electronic Theses, Projects, and Dissertations

Community day school graduates enter society with decisions about college, career, and work. Community day schools operate as a non-traditional education system that provides a separate and often unique education to many disenfranchised students, with lessened accountability protocols to assess whether these systems prepare graduates for life after high school. The number of community day schools and enrollment is declining, due in part to excessive changes within the law and stricter guidelines required to be met.

Rank Reduction Of String C-Group Representations, Peter A. Brooksbank, Dimitri Leemans

Faculty Journal Articles

We show that a rank reduction technique for string C-group representations first used in [Adv. Math. 228 (2018), pp. 3207–3222] for the symmetric groups generalizes to arbitrary settings. The technique permits us, among other things, to prove that orthogonal groups defined on d-dimensional modules over fields of even order greater than 2 possess string C-group representations of all ranks. The broad applicability of the rank reduction technique provides fresh impetus to construct, for suitable families of groups, string C-groups of highest possible rank. It also suggests that the alternating group Alt(11)—the only known group having “rank gaps”—is perhaps more unusual …

Testing Isomorphism Of Graded Algebras, Peter A. Brooksbank, James B. Wilson, Eamonn A. O'Brien

Faculty Journal Articles

We present a new algorithm to decide isomorphism between finite graded algebras. For a broad class of nilpotent Lie algebras, we demonstrate that it runs in time polynomial in the order of the input algebras. We introduce heuristics that often dramatically improve the performance of the algorithm and report on an implementation in Magma.

6th Annual Sustainability Report, Saint Mary's College Of California

Sustainability Report

Highlights from the past year include reviving the Sustainability Living Learning Community in South Claeys (formerly called the “Green LLC”) with double the anticipated enrollment, representing Saint Mary's at Al Gore's Climate Reality Leadership Training in Minneapolis, and launching several new paid Sustainability Student Leadership positions.

Uncertainty And Error In Combat Modeling, Simulation, And Analysis, Jason A. Blake

Theses and Dissertations

Due to the infrequent and competitive nature of combat, several challenges present themselves when developing a predictive simulation. First, there is limited data with which to validate such analysis tools. Secondly, there are many aspects of combat modeling that are highly uncertain and not knowable. This research develops a comprehensive set of techniques for the treatment of uncertainty and error in combat modeling and simulation analysis. First, Evidence Theory is demonstrated as a framework for representing epistemic uncertainty in combat modeling output. Next, a novel method for sensitivity analysis of uncertainty in Evidence Theory is developed. This sensitivity analysis method …

An Interview With Aisha Sharif, Natalie Hayes

Gandy Dancer Archives

No abstract provided.

An Empirical Study Of Sms One-Time Password Authentication In Android Apps, Siqi Ma, Runhan Feng, Juanru Li, Yang Liu, Surya Nepal, Elisa Bertino, Robert H. Deng, Zhuo Ma, Sanjay Jha

Research Collection School Of Computing and Information Systems

A great quantity of user passwords nowadays has been leaked through security breaches of user accounts. To enhance the security of the Password Authentication Protocol (PAP) in such circumstance, Android app developers often implement a complementary One-Time Password (OTP) authentication by utilizing the short message service (SMS). Unfortunately, SMS is not specially designed as a secure service and thus an SMS One-Time Password is vulnerable to many attacks. To check whether a wide variety of currently used SMS OTP authentication protocols in Android apps are properly implemented, this paper presents an empirical study against them. We first derive a set …

Compositional Verification Of Heap-Manipulating Programs Through Property-Guided Learning, Long H. Pham, Jun Sun, Quang Loc Le

Research Collection School Of Computing and Information Systems

Analyzing and verifying heap-manipulating programs automatically is challenging. A key for fighting the complexity is to develop compositional methods. For instance, many existing verifiers for heap-manipulating programs require user-provided specification for each function in the program in order to decompose the verification problem. The requirement, however, often hinders the users from applying such tools. To overcome the issue, we propose to automatically learn heap-related program invariants in a property-guided way for each function call. The invariants are learned based on the memory graphs observed during test execution and improved through memory graph mutation. We implemented a prototype of our approach …

Do My Students Understand? Automated Identification Of Doubts From Informal Reflections, Siaw Ling Lo, Kar Way Tan, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

Traditionally teaching is usually one directional where the instructor imparts knowledge and there is minimal interaction between learners and instructor. With the focus on learner-centred pedagogy, it can be a challenge to provide timely and relevant guidance to individual learners according to their levels of understanding. One of the options available is to collect reflections from learners after each lesson to extract relevant and high-value feedback so that doubts or questions can be addressed in a timely manner. In this paper, we derived an approach to automate the identification of doubts from the informal reflections through features analysis and machine …

Smu Teaching Bank: Case Study Of A Multiyear Development Project Utilizing Student Resources, Alan Megargel, Terence P. C. Fan, Venky Shankararaman

Research Collection School Of Computing and Information Systems

A domain refers to a business sector such as banking, healthcare, insurance, manufacturing etc. For an IS student, it is imperative that the domain knowledge includes a comprehension and understanding of business processes, technology and data related to the chosen domain. For example, when learning the retail banking domain, an IS student must have an understanding of the transactions concerned with retail banking such as fund transfers and loan repayments. The student must also gain a strong foothold in transaction fulfilment processes, the various application services that are used, the data that is transferred, etc. Teaching domain knowledge is very …

Strongly Leakage Resilient Authenticated Key Exchange, Revisited, Guomin Yang, Rongmao Chen, Yi Mu, Willy Susilo, Guo Fuchun, Jie Li

Research Collection School Of Computing and Information Systems

Authenticated Key Exchange (AKE) protocols allow two (or multiple) parties to authenticate each other and agree on a common secret key, which is essential for establishing a secure communication channel over a public network. AKE protocols form a central component in many network security standards such as IPSec, TLS/SSL, and SSH. However, it has been demonstrated that many standardized AKE protocols are vulnerable to side-channel and key leakage attacks. In order to defend against such attacks, leakage resilient (LR-) AKE protocols have been proposed in the literature. Nevertheless, most of the existing LR-AKE protocols only focused on the resistance to …

Learning To Self-Train For Semi-Supervised Few-Shot Classification, Xinzhe Li, Qianru Sun, Yaoyao Liu, Shibao Zheng, Qin Zhou, Tat-Seng Chua, Bernt Schiele

Research Collection School Of Computing and Information Systems

Few-shot classification (FSC) is challenging due to the scarcity of labeled training data (e.g. only one labeled data point per class). Meta-learning has shown to achieve promising results by learning to initialize a classification model for FSC. In this paper we propose a novel semi-supervised meta-learning method called learning to self-train (LST) that leverages unlabeled data and specifically meta-learns how to cherry-pick and label such unsupervised data to further improve performance. To this end, we train the LST model through a large number of semi-supervised few-shot tasks. On each task, we train a few-shot model to predict pseudo labels for …

Finding Needles In A Haystack: Leveraging Co-Change Dependencies To Recommend Refactorings, Marcos César De Oliveira, Davi Freitas, Rodrigo Bonifacio, Gustavo Pinto, David Lo

Research Collection School Of Computing and Information Systems

A fine-grained co-change dependency arises when two fine-grained source-code entities, e.g., a method,change frequently together. This kind of dependency is relevant when considering remodularization efforts (e.g., to keep methods that change together in the same class). However, existing approaches forrecommending refactorings that change software decomposition (such as a move method) do not explorethe use of fine-grained co-change dependencies. In this paper we present a novel approach for recommending move method and move field refactorings, which removes co-change dependencies and evolutionary smells, a particular type of dependency that arise when fine-grained entities that belong to different classes frequently change together. First …

A Signature Enrichment Design With Bayesian Adaptive Randomization For Cancer Clinical Trials, Fang Xia

Dissertations and Theses (Open Access)

Clinical trials in the era of precision medicine demand more flexible and efficient trial designs. Adaptive clinical trial designs allow pre-specified modifications of an on-going clinical trial and could shorten the trial duration. We reviewed five common types of adaptive clinical trials based on adaptation methods. In particular, outcome-randomization becomes more popular as it can assign more patients to the promising treatments based on the accumulated trial data. This data-driven allocation allows more patients to benefit from the trial, which is especially important for cancer patients. We compared different Bayesian outcome-adaptive randomization methods and discussed them from both methodological and …

An Ai Approach To Measuring Financial Risk, Lining Yu, Wolfgang Karl Hardle, Lukas Borke, Thijs Benschop

Sim Kee Boon Institute for Financial Economics

AI artificial intelligence brings about new quantitative techniques to assess the state of an economy. Here, we describe a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter (λ" role="presentation" style="box-sizing: border-box; display: inline; font-style: normal; font-weight: normal; line-height: normal; font-size: 18px; text-indent: 0px; text-align: left; text-transform: none; letter-spacing: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;">λλ) of a linear quantile lasso regression. The FRM is calculated by taking the average …

Navigational Feasibility Of Flyby / Impact Missions To Interstellar Objects, Declan Moore Mages

Master's Theses

In October 2017, the first interstellar object, designated 1I/2017 U1 and more commonly referred to as Oumuamua, was detected passing through our solar system by the Pan-STARRS telescope, followed recently by the detection of 2I/Borisov in August 2019. These detections came much sooner than thought possible, and have redefined our understanding of the population of interstellar objects. With the construction of the next generation of powerful observatories, future detections are estimated to occur as frequently as two per year, and while there is significant scientific understanding to be gained from observing these objects remotely, a spacecraft sent to intercept one …

Hybrid Ground Vehicle Thermal Management System Using Heat Pipes—Model And Control, Junkui Huang

All Dissertations

The development of Hybrid Electric and Unmanned Ground Vehicles (HEV and UGV) offer various benefits including improved vehicle performance, compatibility with high level control systems, reduced fuel consumption, and less environmental pollution. According to the International Energy Agency (IEA), the number of HEVs and EVs is expected to reach 20 million by the year 2020 (Green Car Congress, 2017). Compared with traditional Internal Combustion (IC) engines, hybrid powertrains are more complicated due to additional electronics including the electric motor, battery pack, and control units. However, these additional components introduce new challenges for the powertrain thermal management system design since they …

Design And Evaluation Of Flow Mapping Systems For Heterogeneous Wireless Networks, Jianwei Liu

All Dissertations

Mobile wireless networks are always challenged by growing application demand. The increasing heterogeneity of both mobile device connection capability and wireless network coverage forms a general heterogeneous wireless network (HetNet). This type of HetNet contains sub-networks of different Radio Access Technologies. How to better coordinate the mappings of flows between Access Points (AP) and User Equipment (UE) inside this type of HetNet to improve system and user-level performance is an interesting research problem. The flow mapping systems used by off-the-shelf mobile devices make policy-based decisions from local information. Several global information based flow mapping systems that use Generalized Proportional Fairness …

A Case Of Arts Coordination In A Rural School District: A Distributed Perspective, Anna Shealy Wages

All Dissertations

Though researchers have demonstrated the benefit of prolonged engagement in the arts (Catterall, Dumais, & Hapden-Thompson, 2012) school districts struggle to maintain high quality programs. Rural programs, in particular, are faced with unique challenges to providing arts programs (Donovan & Brown, 2017). Despite these challenges, some rural school districts have succeeded in providing quality programs, which are more in line with more resourced urban districts. Arts researchers (Bodilly, Augustine, & Zakaras, 2008) have found that arts coordination is a strategy to increase access to and the quality of an arts program. Further, districts of quality, even small ones, have arts …

A Parallel Geometric Multigrid Method For Adaptive Finite Elements, Thomas Conrad Clevenger

All Dissertations

Applications in a variety of scientific disciplines use systems of Partial Differential Equations (PDEs) to model physical phenomena. Numerical solutions to these models are often found using the Finite Element Method (FEM), where the problem is discretized and the solution of a large linear system is required, containing millions or even billions of unknowns. Often times, the domain of these solves will contain localized features that require very high resolution of the underlying finite element mesh to accurately solve, while a mesh with uniform resolution would require far too much computational time and memory overhead to be feasible on a …

Optimizing Block-Stacking Operations With Relocation, Hueon Lee

Graduate Theses and Dissertations

The focus of the dissertation is developing the optimization problem of finding the minimum-cost operational plan of block stacking with relocation as well as devising a solution procedure to solve practical-sized instances of the problem. Assuming changeable row depth instead of permanent row depth, this research is distinguished from conventional block stacking studies.

The first contribution of the dissertation is the development of the optimization problem under the assumption of deterministic demand. The problem is modeled using integer programming as a variation of the unsplittable multi-commodity flow problem. To find a good feasible solution of practical-sized instances in reasonable time, …