Physical Sciences and Mathematics Commons^™

Making Data Meaningful: Stakeholder Perceptions On Data Visualization And Data Management Practices Within A Multi-Tiered System Of Supports (Mtss), Domenick Saia

Dissertations

Data-driven decision-making and collaboration are core pillars of a multi-tiered system of supports (MTSS); however, timely and accessible data use, as well as data literacy and visualization literacy skills, are challenges school leaders and educators face related to implementing such frameworks. I hypothesized efficient data management systems and data visualization tools enable school teams to predict student learning outcomes, readily communicate, and better understand student data. The purpose of this study design was to highlight a need for more efficient data structures that allow school stakeholders to balance their roles within an MTSS framework more effectively. The context of this …

Models And Algorithms For Promoting Diverse And Fair Query Results, Md Mouinul Islam

Dissertations

Ensuring fairness and diversity in search results are two key concerns in compelling search and recommendation applications. This work explicitly studies these two aspects given multiple users' preferences as inputs, in an effort to create a single ranking or top-k result set that satisfies different fairness and diversity criteria. From group fairness standpoint, it adapts demographic parity like group fairness criteria and proposes new models that are suitable for ranking or producing top-k set of results. This dissertation also studies equitable exposure of individual search results in long tail data, a concept related to individual fairness. First, the dissertation focuses …

Diversification And Fairness In Top-K Ranking Algorithms, Mahsa Asadi

Dissertations

Given a user query, the typical user interfaces, such as search engines and recommender systems, only allow a small number of results to be returned to the user. Hence, figuring out what would be the top-k results is an important task in information retrieval, as it helps to ensure that the most relevant results are presented to the user. There exists an extensive body of research that studies how to score the records and return top-k to the user. Moreover, there exists an extensive set of criteria that researchers identify to present the user with top-k results, and result diversification …

Human-Ai Complex Task Planning, Sepideh Nikookar

Dissertations

The process of complex task planning is ubiquitous and arises in a variety of compelling applications. A few leading examples include designing a personalized course plan or trip plan, designing music playlists/work sessions in web applications, or even planning routes of naval assets to collaboratively discover an unknown destination. For all of these aforementioned applications, creating a plan requires satisfying a basic construct, i.e., composing a sequence of sub-tasks (or items) that optimizes several criteria and satisfies constraints. For instance, in course planning, sub-tasks or items are core and elective courses, and degree requirements capture their complex dependencies as constraints. …

Data-Driven 2d Materials Discovery For Next-Generation Electronics, Zeyu Zhang

Dissertations

The development of material discovery and design has lasted centuries in human history. After the concept of modern chemistry and material science was established, the strategy of material discovery relies on the experiments. Such a strategy becomes expensive and time-consuming with the increasing number of materials nowadays. Therefore, a novel strategy that is faster and more comprehensive is urgently needed. In this dissertation, an experiment-guided material discovery strategy is developed and explained using metal-organic frameworks (MOFs) as instances. The advent of 7r-stacked layered MOFs, which offer electrical conductivity on top of permanent porosity and high surface area, opened up new …

Using Materialized Views For Answering Graph Pattern Queries, Michael Lan

Dissertations

Discovering patterns in graphs by evaluating graph pattern queries involving direct (edge-to-edge mapping) and reachability (edge-to-path mapping) relationships under homomorphisms on data graphs has been extensively studied. Previous studies have aimed to reduce the evaluation time of graph pattern queries due to the potentially numerous matches on large data graphs.

In this work, the concept of the summary graph is developed to improve the evaluation of tree pattern queries and graph pattern queries. The summary graph first filters out candidate matches which violate certain reachability constraints, and then finds local matches of query edges. This reduces redundancy in the representation …

Android Security: Analysis And Applications, Raina Samuel

Dissertations

The Android mobile system is home to millions of apps that offer a wide range of functionalities. Users rely on Android apps in various facets of daily life, including critical, e.g., medical, settings. Generally, users trust that apps perform their stated purpose safely and accurately. However, despite the platform’s efforts to maintain a safe environment, apps routinely manage to evade scrutiny. This dissertation analyzes Android app behavior and has revealed several weakness: lapses in device authentication schemes, deceptive practices such as apps covering their traces, as well as behavioral and descriptive inaccuracies in medical apps. Examining a large corpus of …

Machine Learning-Based Data Analytics For Understanding Space Weather And Climate, Yasser Abduallah

Dissertations

This dissertation addresses multiple crucial problems in space weather and climate, presenting new machine learning-based data analytics algorithms and models for tackling the problems.

First, the dissertation presents two new approaches to predicting solar flares. One approach, called DeepSun, predicts solar flares by utilizing a machine-learning-as-a-service (MLaaS) platform. The DeepSun system provides a friendly interface for Web users and an application programming interface (API) for remote programming users. It adopts an ensemble learning method that employs several machine learning algorithms to perform multiclass flare prediction. The other approach, named SolarFlareNet, forecasts the occurrence of solar flares within the next 24 …

On Performance Optimization And Prediction Of Parallel Computing Frameworks In Big Data Systems, Haifa Alquwaiee

Dissertations

A wide spectrum of big data applications in science, engineering, and industry generate large datasets, which must be managed and processed in a timely and reliable manner for knowledge discovery. These tasks are now commonly executed in big data computing systems exemplified by Hadoop based on parallel processing and distributed storage and management. For example, many companies and research institutions have developed and deployed big data systems on top of NoSQL databases such as HBase and MongoDB, and parallel computing frameworks such as MapReduce and Spark, to ensure timely data analyses and efficient result delivery for decision making and business …

Exploring, Understanding, Then Designing: Twitter Users’ Sharing Behavior For Minor Safety Incidents, Mashael Yousef Almoqbel

Dissertations

Social media has become an integral part of human lives. Social media users resort to these platforms for various reasons. Users of these platforms spend a lot of time creating, reading, and sharing content, therefore, providing a wealth of available information for everyone to use. The research community has taken advantage of this and produced many publications that allow us to better understand human behavior. An important subject that is sometimes discussed and shared on social media is public safety. In the past, Twitter users have used the platform to share incidents, share information about incidents, victims and perpetrators, and …

Participatory Learning: Measuring Learning And Educational Technology Acceptance, Erick Sanchez Suasnabar

Dissertations

Participatory Learning (PL) integrates several learning approaches, engaging students throughout the entire assignment process for both online and face-to-face courses. Beyond simply providing a solution, students also craft a problem (problem-based learning), grade each other (peer assessment and feedback), evaluate themselves (self-assessment), and can view others’ work (learning by example). This dissertation research explores the resulting learning effects. Contributions to both educational and Information Systems research include extending an early PL model and experiments that applied the PL approach to examinations, by validating and testing new constructs based on user activity and critical thinking. In addition, the study explores a …

Impact Of User Traversal On Performance Of Stem Learners In Immersive Virtual Environments, Eric W. Nersesian

Dissertations

The emerging technologies of augmented and virtual reality (AR/VR) may have vast implications to societal communication and representation of information. AR/VR computer interfaces are unique in that they may be placed spatially around the user in three-dimensional (3D) space; this affords new methods of both presentation and user interaction with the target information.

This may be especially impactful in the education of science, technology, engineering, and mathematics (STEM) professionals. Prior research has shown that simulations and visualizations improve the performance of STEM learners compared to live instruction and textbook reading. Yet, research into AR/VR as a learning environment for widespread …

Drone-Assisted Emergency Communications, Di Wu

Dissertations

Drone-mounted base stations (DBSs) have been proposed to extend coverage and improve communications between mobile users (MUs) and their corresponding macro base stations (MBSs). Different from the base stations on the ground, DBSs can flexibly fly over and close to MUs to establish a better vantage for communications. Thus, the pathloss between a DBS and an MU can be much smaller than that between the MU and MBS. In addition, by hovering in the air, the DBS can likely establish a Line-of-Sight link to the MBS. DBSs can be leveraged to recover communications in a large natural disaster struck area …

Supporting User Interaction And Social Relationship Formation In A Collaborative Online Shopping Context, Yu Xu

Dissertations

The combination of online shopping and social media allow people with similar shopping interests and experiences to share, comment, and discuss about shopping from anywhere and at any time, which also leads to the emergence of online shopping communities. Today, more people turn to online platforms to share their opinions about products, solicit various opinions from their friends, family members, and other customers, and have fun through interactions with others with similar interests. This dissertation explores how collaborative online shopping presents itself as a context and platform for users' interpersonal interactions and social relationship formation through a series of studies. …

Global Optimization Algorithms For Image Registration And Clustering, Cuicui Zheng

Dissertations

Global optimization is a classical problem of finding the minimum or maximum value of an objective function. It has applications in many areas, such as biological image analysis, chemistry, mechanical engineering, financial analysis, deep learning and image processing. For practical applications, it is important to understand the efficiency of global optimization algorithms. This dissertation develops and analyzes some new global optimization algorithms and applies them to practical problems, mainly for image registration and data clustering.

First, the dissertation presents a new global optimization algorithm which approximates the optimum using only function values. The basic idea is to use the points …

Changing The Focus: Worker-Centric Optimization In Human-In-The-Loop Computations, Mohammadreza Esfandiari

Dissertations

A myriad of emerging applications from simple to complex ones involve human cognizance in the computation loop. Using the wisdom of human workers, researchers have solved a variety of problems, termed as “micro-tasks” such as, captcha recognition, sentiment analysis, image categorization, query processing, as well as “complex tasks” that are often collaborative, such as, classifying craters on planetary surfaces, discovering new galaxies (Galaxyzoo), performing text translation. The current view of “humans-in-the-loop” tends to see humans as machines, robots, or low-level agents used or exploited in the service of broader computation goals. This dissertation is developed to shift the focus back …

An Automated Feedback System To Support Student Learning Of Conceptual Knowledge In Writing-To-Learn Activities, Ye Xiong

Dissertations

As a pedagogical strategy, Writing-to-Learn (WTL) intends to use writing to improve students’ understanding of course content. However, most of the existing feedback systems for writing are mainly focused on improving students’ writing skills rather than their conceptual development. In this dissertation, an automatic approach is proposed to generate timely, actionable, and individualized feedback based on comparing knowledge representations extracted from lecture slides and individual students’ writing assignments. The novelty of the proposed approach lies in the feedback generation: to help students assimilate new knowledge into their existing knowledge better, their current knowledge is modeled as a set of matching …

Maia And Admonita: Mandatory Integrity Control Language And Dynamic Trust Framework For Arbitrary Structured Data, Wassnaa Al-Mawee

Dissertations

The expansion of attacks against information systems of companies that operate nuclear power stations and other energy facilities in the United States and other countries, are noticeable with potential catastrophic real-world implications. Data integrity is a fundamental component of information security. It refers to the accuracy and the trustworthiness of data or resources. Data integrity within information systems becomes an important factor of security protection as the data becomes more integrated and crucial to decision-making. The security threats brought by human errors whether, malicious or unintentional, such as viruses, hacking, and many other cybersecurity threats, are dangerous and require mandatory …

Early Detection Of Fake News On Social Media, Yang Liu

Dissertations

The ever-increasing popularity and convenience of social media enable the rapid widespread of fake news, which can cause a series of negative impacts both on individuals and society. Early detection of fake news is essential to minimize its social harm. Existing machine learning approaches are incapable of detecting a fake news story soon after it starts to spread, because they require certain amounts of data to reach decent effectiveness which take time to accumulate. To solve this problem, this research first analyzes and finds that, on social media, the user characteristics of fake news spreaders distribute significantly differently from those …

Applied Deep Learning In Intelligent Transportation Systems And Embedding Exploration, Xiaoyuan Liang

Dissertations

Deep learning techniques have achieved tremendous success in many real applications in recent years and show their great potential in many areas including transportation. Even though transportation becomes increasingly indispensable in people’s daily life, its related problems, such as traffic congestion and energy waste, have not been completely solved, yet some problems have become even more critical. This dissertation focuses on solving the following fundamental problems: (1) passenger demand prediction, (2) transportation mode detection, (3) traffic light control, in the transportation field using deep learning. The dissertation also extends the application of deep learning to an embedding system for visualization …

Storage Systems For Mobile-Cloud Applications, Nafize R. Paiker

Dissertations

Mobile devices have become the major computing platform in todays world. However, some apps on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud.

This dissertation aims to ensure that the tasks in a mobile app that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. …

Virtual Smarts - Optimizing The Coalescing Of People For Collective Action Within Urban Communities, Stephen Thomas Ricken

Dissertations

Despite the importance of individuals coming together for social group-activities (e.g., pick-up volleyball), the process by which such groups coalesce is poorly understood, and as a consequence is poorly supported by technology. This is despite the emergence of Event-Based Social Network (EBSN) technologies that are specifically designed to assist group coalescing for social activities. Existing theories focus on group development in terms of norms and types, rather than the processes involved in initial group coalescence. This dissertation addresses this gap in the literature through four studies focusing on understanding the coalescing process for interest-based group activities within urban environments and …

Supporting User Evaluation Of Messaging Interactions With Potential Romantic Partners Discovered Online, Douglas Zytko

Dissertations

Online dating systems have transformed the way people pursue romance. To arrive at a decision to meet for a face-to-face date, users gather information about each other online pertinent to romantic attraction. Yet sometimes they discover on the date that they made the wrong choice. One aspect of online dating system-use that may be a contributing factor, but is largely overlooked in the literature, is interaction through text-based messaging interfaces. This dissertation explores how messaging interactions inform face-to-face meeting decisions through two qualitative studies, and explores through a mixed methods field study how innovative messaging interfaces that embody theory from …

A Conversation Centric Approach To Understanding And Supporting The Coordination Of Social Group-Activities, Richard P. Schuler

Dissertations

Despite the widespread and large variety of communication tools available to us such as, text messaging, Skype, email, twitter, Facebook, instant messaging, GroupMe, WhatsApp, Snapchat, etc., many people still routinely find coordinating activities with our friends to be a very frustrating experience. Everyone, has at least once, encountered the difficulties involved with deciding what to do as a group. Some friends may be busy, others may have already seen the movie that the others want to see, and some do not like Mexican food. It is a challenge everyone has faced and continue to face. This is a result of …

Detecting User Demographics In Twitter To Inform Health Trends In Social Media, Christopher R. Markson

Dissertations

The widespread and popular use of social media and social networking applications offer a promising opportunity for gaining knowledge and insights regarding population health conditions thanks to the diversity and abundance of online user-generated information (UGHI) relating to healthcare and well-being. However, users on social media and social networking sites often do not supply their complete demographic information, which greatly undermines the value of the aforementioned information for health 2.0 research, e.g., for discerning disparities across population groups in certain health conditions. To recover the missing user demographic information, existing methods observe a limited scope of user behaviors, such as …

Viewability Prediction For Display Advertising, Chong Wang

Dissertations

As a massive industry, display advertising delivers advertisers’ marketing messages to attract customers through graphic banners on webpages. Display advertising is also the most essential revenue source of online publishers. Currently, advertisers are charged by user response or ad serving. However, recent studies show that users barely click or convert display ads. Moreover, about half of the ads are actually never seen by users. In this case, advertisers cannot enhance their brand awareness and increase return on investment. Publishers also lose much revenue. Therefore, the ad pricing standards are shifting to a new model: ad impressions are paid if they …

Collaborative Development Of A Small Business Emergency Planning Model, Arthur Henry Hendela

Dissertations

Small businesses, which are defined by the US Small Business Administration as entities with less than 500 employees, suffer interruptions from diverse risks such as financial events, legal situations, or severe storms exemplified by Hurricane Sandy. Proper preparations can help lessen the length of the interruption and put employees and owners back to work. Large corporations generally have large budgets available for planning, business continuity, and disaster recovery. Small businesses must decide which risks are the most important and how best to mitigate those risks using minimal resources.

This research uses a series of surveys followed by mathematical modeling to …

Mediating Chance Encounters Through Opportunistic Social Matching, Julia M. Mayer

Dissertations

Chance encounters, the unintended meeting between people unfamiliar with each other, serve as an important social lubricant helping people to create new social ties, such as making new friends or finding an activity, study or collaboration partner. Unfortunately, social barriers often prevent chance encounters in environments where people do not know each other and people have to rely on serendipity to meet or be introduced to interesting people around them. Little is known about the underlying dynamics of chance encounters and how systems could utilize contextual data to mediate chance encounters. This dissertation addresses this gap in research literature by …

Task-Based User Profiling For Query Refinement (Toque), Chao Xu

Dissertations

The information needs of search engine users vary in complexity. Some simple needs can be satisfied by using a single query, while complicated ones require a series of queries spanning a period of time. A search task, consisting of a sequence of search queries serving the same information need, can be treated as an atomic unit for modeling user’s search preferences and has been applied in improving the accuracy of search results. However, existing studies on user search tasks mainly focus on applying user’s interests in re-ranking search results. Only few studies have examined the effects of utilizing search tasks …

Continuous Monitoring Of Enterprise Risks: A Delphi Feasibility Study, Robert Baksa

Dissertations

A constantly evolving regulatory environment, increasing market pressure to improve operations, and rapidly changing business conditions are creating the need for ongoing assurance that organizational risks are continually and adequately mitigated. Enterprises are perpetually exposed to fraud, poor decision making and/or other inefficiencies that can lead to significant financial loss and/or increased levels of operating risk. Increasingly, Information Systems are being harnessed to reinvent the risk management process. One promising technology is Continuous Auditing, which seeks to transform the audit process from periodic reviews of a few transactions to a continuous review of all transactions. However, the highly integrated, rapidly …