Computer Sciences Commons^™

Design Implications For Montessori Education, Olivia Chilvers

Student Scholar Symposium Abstracts and Posters

This project aims to identify the design implications for children’s educational apps that seek to align with the principles of the Montessori Philosophy and contribute to the development of educational technology. By analyzing critical features of apps that engage children and promote their natural desire to learn, this project aligns with the Montessori philosophy of fostering independent, self-directed learning. To uncover the design implication, we conducted a qualitative analysis of reviews of popular educational apps, defined by having at least 3,000 reviews and a rating of 3 stars or higher, that appeared from search results using the keyword “Montessori” in …

Software Implementations And Analyses Of The Emotional Impact Of Various Binaural Beat Classifications Layered Into Music., Neil Azimi

Student Scholar Symposium Abstracts and Posters

This study explores the psychoacoustic effects of binaural beats, which are produced when sinusoidal waves of slightly differing frequencies are played into each ear, leading to brainwave entrainment. Binaural beats are categorized by frequency bands (e.g., Beta: 14–30 Hz for energy, Theta: 4–8 Hz for relaxation), each associated with different psychological effects. This research contributes to the field by empirically analyzing whether binaural beats alter the emotional impact of music. Past studies have investigated the potential benefits of binaural beats in relaxation and energy stimulation. However, their effects, when combined with music, especially regarding a song's perceived emotional quality or …

Developing A Nearly Automated Open-Source Pipeline For Conducting Computational Fluid Dynamics Simulations In Anterior Brain Vasculature: A Feasibility Study, Mostafa Rezaeitaleshmahalleh, Nan Mu, Zonghan Lyu, Joseph Gemmete, Aditya Pandey, Jingfeng Jiang

Michigan Tech Publications

Intracranial aneurysms (IA) pose significant health risks and are often challenging to manage. Computational fluid dynamics (CFD) simulation has emerged as a powerful tool for understanding lesion-specific hemodynamics in and around IAs, aiding in the clinical management of patients with an IA. However, the current workflow of CFD simulations is time-consuming, complex, and labor-intensive and, thus, does not fit the clinical environment. To address these challenges, we have developed a semi-automated pipeline integrating multiple open-source software packages to streamline the CFD simulation process. Specifically, the study utilized medical angiography data from 18 patients. An in-house open-source DL image segmentation model …

Lstm-Transformer Based Robust Hybrid Deep Learning Model For Financial Time Series Forecasting, Md R. Kabir

Theses and Dissertations

The inherent challenges of financial time series forecasting demand advanced modeling techniques for reliable predictions. Financial data, belonging to the category of multimedia data, contains an extensive quantity of information that is widely used for data analysis and decision-making tasks. Effective financial time series forecasting is crucial for financial risk management and the formulation of investment decisions. Accurate prediction of stock prices is a subject of study in the domains of investing and national policy. This problem appears to be challenging due to the presence of multi-noise, nonlinearity, volatility, and chaotic natures in stocks. This paper proposes a novel financial …

Applying Positive Unlabeled Learning Techniques And Using The Kullback-Leibler Divergence To Improve Geothermal Surveying Assessments, Martín Thomas Rodriguez

Dissertations and Theses

As we face the current climate crisis, the discovery of geothermal energy resources has the potential to greatly reduce our dependence on fossil fuels worldwide. However, the development of any new energy infrastructure is expensive and depends on the willingness of energy agencies and developers to make initial investments based on calculated risk measures. One such measure, called geothermal favorability, is the likelihood that a site has conditions favorable for geothermal systems containing recoverable energy potential. Its prediction from existing geophysical datasets proves to be a nontrivial task. The prediction of geothermal favorability can be framed as a binary classification …

The Computational Eye. Deconstructing Style In Digital Art History, Paul Guhennec, Ellen Charlesworth

Artl@s Bulletin

With the aim of grounding digital methods in the art historic tradition, this paper uses the discussions around style as a springboard to ask how digital art history can extend beyond providing quantitative confirmation of known trends to enrich our current understanding of visual cultures. Drawing from the examples throughout this issue, we explore how an analysis of computational ways of seeing—or the ‘computational eye’—can expose the underlying preoccupations and priorities of our own research.

Afin de mieux ancrer les méthodes numériques dans la tradition de l’histoire de l’art, cet article se sert des discussions récentes autour du concept de …

Visualization Of Paleocurrents On A Web Application Using Gplates, Anjan Sapkota

MS in Computer Science Theses

Paleocurrents are flow directions derived from features of sedimentary rocks that reveal the direction of the current of wind or water that deposited the sediment. In 2015, Brand et al. created a global database of paleocurrents, which contains over 1,000,000 measurements worldwide: North America, South America, Australia, Great Britain, parts of Western Europe, China, Africa are fairly well represented; Antarctica, Eastern Europe, and Asia are modestly represented and Russia is poorly represented. The contribution of this thesis is a web application that uses the GPlates’ Application Programming Interface (API) to visualize global paleocurrents through time in an interactive way based …

Artificial Creativity: How Artificial Intelligence Will Impact Creativity Via Post-Production, Nicole Dwyer

Honors Thesis

My thesis lives in the world of Post-Production, and it contains both a creative and written component. I was the editor for four Undergraduate thesis projects. Seeking to gain experience in editing various genres, I worked in drama, sports, period piece, coming of age, and adventure. My biggest takeaways from these projects are the importance of organization, communication, time management, and editing with a sense of imagination. I became a more confident, resilient, and prepared editor through these experiences.

Along with the hands-on filmmaking element of my thesis, I also conducted research on how artificial intelligence will impact conceptions of …

Graph Neural Networks Powered Scientific Paper Recommendation, Junhao Shen

Computer Science and Engineering Theses and Dissertations

Scientific paper recommendation systems aim to help researchers discover relevant papers amidst the vast and ever-growing body of literature. With the exponential yearly increase in scientific publications, the demand for effective paper recommendation solutions has become both critical and increasingly challenging. In recent years, deep learning techniques have revolutionized recommender systems, and scientific paper recommendations have naturally integrated these advancements. In this dissertation, we address these challenges through three progressive contributions.

First, we enhance traditional content-based methods using Graph Neural Networks (GNNs) by introducing a Graph Convolutional Network-strengthened Topic Modeling (GCN-TM) approach. This method improves upon conventional topic modeling techniques …

Machine Visual Perception From Sim-To-Real Transfer Learning For Autonomous Docking Maneuvers, Derek Worth, Jeffrey Choate, Ryan M. Raettig, Scott L. Nykl, Clark N. Taylor

Faculty Publications

This paper presents a comprehensive approach to enhancing autonomous docking maneuvers through machine visual perception and sim-to-real transfer learning. By leveraging relative vectoring techniques, we aim to replicate the human ability to execute precise docking operations. Our study focuses on autonomous aerial refueling as a use case, demonstrating significant advancements in relative navigation and object detection. We introduce a novel method for aligning digital twins using fiducial targets and motion capture data, which facilitates accurate pose estimation from real-world imagery. Additionally, we develop cost-efficient annotation automation techniques for generating high-quality You Only Look Once training data. Experimental results indicate that …

Website Portfolio, Thomas Roch

Honors Program Theses and Projects

No abstract provided.

Alphafold2-Based Characterization Of Apo And Holo Protein Structures And Conformational Ensembles Using Randomized Alanine Sequence Scanning Adaptation: Capturing Shared Signature Dynamics And Ligand-Induced Conformational Changes, Nishank Raisinghani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Proteins often exist in multiple conformational states, influenced by the binding of ligands or substrates. The study of these states, particularly the apo (unbound) and holo (ligand-bound) forms, is crucial for understanding protein function, dynamics, and interactions. In the current study, we use AlphaFold2, which combines randomized alanine sequence masking with shallow multiple sequence alignment subsampling to expand the conformational diversity of the predicted structural ensembles and capture conformational changes between apo and holo protein forms. Using several well-established datasets of structurally diverse apo-holo protein pairs, the proposed approach enables robust predictions of apo and holo structures and conformational ensembles, …

Screensafefuture: A Parent-Empathetic And Pragmatic Mhealth Application For Toddlers' Brain Development Addressing Screen-Addiction Challenges, Nafisa Anjum, Md. Mehedi Hasan, Syeda Umme Salma, Liang Zhao, Maria Valero, Nazmus Sakib

Faculty Articles

The surging incidents of infants and toddlers screen addiction in the United States are becoming a pressing concern, given its compound impact on cognitive, mental, and physical growth. To address this era's critical child health and development problem, in this paper an innovative mHealth application—ScreenSafeFuture—is proposed. ScreenSafeFuture provides practical solutions that seamlessly fit into parents' busy lifestyles, acknowledging the effectiveness and convenience of smartphones as a healthcare tool. The solution includes essential features designed to enhance the experience between parents and their children under 3 years old encompassing an alternative activity advocator for a personalized parent-offspring scenario, screen time tracking …

Applications Of Neural Networks In Parkinson’S Disease Diagnosis, Saladin Minhaaj

Theses

Parkinson's disease (PD) is a complex and debilitating neurodegenerative disorder that affects millions of people worldwide. Early and accurate diagnosis is crucial for effective treatment and management of PD. This thesis explores the application of neural networks in PD diagnosis, leveraging their ability to learn patterns from large datasets and make accurate predictions.

Thesis provides an overview of PD, including its symptoms, diagnosis, and current challenges in diagnosis. We then delve into the fundamentals of neural networks, including supervised learning, mathematical interpretations, and parametric models. This research focuses on the development of neural network models that can accurately diagnose PD …

The Impact Of Student Engagement Activities On Future Climate Change Adaptation: The Case Of Student Simulation Models, Bassel Mostafa Elkalaf

Future Journal of Social Science

This paper explores the critical role of student engagement in addressing the growing challenges of climate change, with a focus on the Model United Nations (MUN) as a case study. As climate-related security threats increase globally, educational platforms that prepare youth for effective leadership in climate politics are more essential than ever. MUN, a widely practiced student activity simulating global policy-making, provides a valuable opportunity for students to deepen their understanding of the interconnectedness between climate change, peace, and security. By participating in MUN simulations, students engage in debates, develop innovative solutions, and practice diplomatic skills, all while exploring the …

Why Linear Faults Have Fewer Earthquakes: A Geometric Explanation, Julio C. Urenda, Aaron Velasco, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Earthquakes usually occur in the vicinity of fault lines. Until recently, geophysical analysis implied that the fault shape should not strongly affect the frequency of its earthquakes. However, recent statistical analysis has shown that faults whose shape is close to linear experience much fewer earthquakes than faults of more complex shape. Based on this empirical fact, researchers have adjusted the corresponding geophysical models, so the updated models do explain this newly discovered phenomenon. The experience of geophysics shows that the updated model will probably need to be updated again when new data appears. It is therefore desirable to come up …

Fair Economic Division: How To Modify Shapley Value To Take Into Account That Different People Have Different Productivity, Christian Servin, Vladik Kreinovich

Departmental Technical Reports (CS)

Purpose: When several participants, working together, gained some amount of money, what is the fair way to distribute this amount between them? This is the problem that the future Nobelist Lloyd Shapley was working on when he proposed what is now called the Shapley value -- a division uniquely determined by natural fairness assumptions. However, this solutions is not universal: it assumes that all participants are equal -- in particular, that they have equal productivity. In practice, people have different productivity levels, and these productivity levels can differ a lot: e.g., some software engineers are several times more productive than …

How Shapley Value And Its Generalizations Can Help In The Analysis Of Complex Engineering Systems And What Next, Niklas Winnewisser, Michael Beer, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

For a complex engineering system -- such as a city's street network -- it is important to predict how its functionality is decreased when some of these components break down, and, if repairs are needed and repairs budget is limited, which subset of the set of components should be repaired first to maximize the resulting functionality. For systems with a large number of components, the number of possible subsets is astronomical, we cannot try to simulate all these subsets. So, the natural idea is to approximate the actual dependence of functionality on the subset by a simple expression -- linear …

What Is Optimal Granularity When Estimating Reliability Of A Complex Engineering Systems, Niklas Winnewisser, Michael Beer, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

For complex engineering systems, the usual way to estimate their reliability is to run simulations. If the resulting estimate does not satisfy the desired reliability level, we must replace some components with more reliable and again run simulations. This can take several iterations, so the required computation time often becomes unrealistically long. It is known that it is possible to speed up computations if components belong to a few types, and components of each type are identical. So, a natural idea to deal with the general case is to use the general granularity idea, i.e., to group components with similar …

Universal Shape Replication Via Self-Assembly With Signal-Passing Tiles, Andrew Alseth, Daniel Hader, Matthew J. Patitz

Computer Science and Computer Engineering Faculty Publications and Presentations

In this paper, we investigate shape-assembling power of a tile-based model of self-assembly called the Signal-Passing Tile Assembly Model (STAM). In this model, the glues that bind tiles together can be turned on and off by the binding actions of other glues via “signals”. Specifically, the problem we investigate is “shape replication” wherein, given a set of input assemblies of arbitrary shape, a system must construct an arbitrary number of assemblies with the same shapes and, with the exception of size-bounded junk assemblies that result from the process, no others. We provide the first fully universal shape replication result, namely …

Grosafe: In-Classroom Technology-Enabled Solution To Build Societal Resilience Against Child Grooming, Christina Thorpe, Fiona Jennings

Conference Papers

GroSafe is an innovative initiative developed by TU Dublin in partnership with the ISPCC to address the critical issue of child grooming. By leveraging cutting-edge digital technologies, GroSafe focuses on educating children, caregivers, and educators to recognise, report, and prevent grooming behaviours. It integrates a 3D educational gaming environment with adaptive learning tools, enabling safe and effective engagement for children, including those with diverse learning needs. Designed to align with Ireland’s SPHE curriculum, GroSafe empowers schools and communities to tackle grooming through early intervention and resilience building.

Using Llms To Establish Implicit User Sentiment Of Software Desirability, Sherri Weitl-Harms, John D. Hastings, Jonah Lum

Research & Publications

This study explores the use of LLMs for providing quantitative zero-shot sentiment analysis of implicit software desirability, addressing a critical challenge in product evaluation where traditional review scores, though convenient, fail to capture the richness of qualitative user feedback. Innovations include establishing a method that 1) works with qualitative user experience data without the need for explicit review scores, 2) focuses on implicit user satisfaction, and 3) provides scaled numerical sentiment analysis, offering a more nuanced understanding of user sentiment, instead of simply classifying sentiment as positive, neutral, or negative.

Data is collected using the Microsoft Product Desirability Toolkit (PDT), …

Classroom To Console, Ashton Headley

ART 108: Introduction to Games Studies

In an era where technology is continuously growing and intertwined into daily life, the field of education has seen drastic changes and innovation. Including changes we see today, with the ability to connect to class online, procter tests, submit assignments etc. And amongst these innovations, educational games have surfaced as a resource for helping learners across various age groups. By merging entertainment/gamification with educational content, these games offer an interactive and entertaining approach to acquiring knowledge and learning essential or non-essential skills. Whether it is implemented in classrooms, workplaces, or home settings, educational games are transforming the educational environment effectively …

Ethics And Environmental Impact Of Video Games, Anushka Chokshi

ART 108: Introduction to Games Studies

As video games grow in popularity, concerns regarding their ethical and environmental implications are brought up. While once, topics like their impact on child development or harm to Earth might have been considered minor or irrelevant, these concerns are now voiced in numerous articles across the internet, amplifying the urgency to develop games in an ethical context before matters are blown out of proportion. For the purposes of exploring both past and present views, this work draws from older and newer sources surrounding many topics on the idea of game development in the video game industry. Essentially, video game development …

Multi-Criteria Decision-Making Approach Based On Correlation Coefficient For Multi-Polar Interval-Valued Neutrosophic Soft Set, Hamza Naveed, Saalam Ali

Neutrosophic Systems with Applications

The correlation coefficient between two factors is crucial in statistical computation, indicating the extent and evolution of the appropriate link. The precision of applicability evaluations frequently relies on the thoroughness and caliber of data obtained from a certain dataset. Statistical research sometimes entails data marked by intrinsic trade-offs and uncertainty. This study seeks to present m-polar interval-valued neutrosophic soft sets (mPIVNSSs) through the integration of m-polar fuzzy sets with interval-valued neutrosophic soft sets. The suggested mPIVNSS structure is a significantly generalized version of m-polar neutrosophic soft sets and serves as a substantial extension of interval-valued neutrosophic soft sets. In this …

Neutrosophic Cox Proportional Hazards Model For Robust Variable Selection In Survival Analysis, Ibrahim Yasser, Aya A. Abd El-Khalek, A. A. Salama, Doaa A. Abdo

Neutrosophic Systems with Applications

This paper introduces a novel approach for variable selection in survival analysis by integrating neutrosophic logic into the Cox Proportional Hazards (Cox PH) model to address the limitations of recent studies related to high dimensionality. Neutrosophic logic, is a mathematical framework that allows for uncertainty, indeterminacy, and inconsistency, and particularly well suited for handling the complexity and often-ambiguous nature of biological data. By incorporating neutrosophic sets into the Cox PH model, we aim to enhance model robustness, improve variable selection, and address the curse of dimensionality. We compare the performance of the neutrosophic-enhanced Cox PH model with traditional variable selection …

On Neutrosophic Pδs-Irresolute Functions In Neutrosophic Topological Spaces, Bishnupada Debnath, Anjan Mukherjee

Neutrosophic Systems with Applications

In general topology the notion of pds-irresolute and aδs-irresolute functions were introduced by Beceren and Noiri. In the present paper, these concepts of pδs-irresolute (briefly, Npδs-irresolute) and aδs-irresolute (briefly, Naδs-irresolute) functions are explored for the first time in neutrosophic topological spaces (NTS) as generalized version. We proved that every Naδs-irresolute function is Npδs-irresolute function but not conversely. Some characterizations, counter examples, and fundamental features are also presented. By neutrosophic pre-open, neutrosophic δ-open, and neutrosophic δ-semi-open sets, some new fundamental properties of such functions are provided. Furthermore, under Npδs-irresolute functions, the behavior of neutrosophic semi-connected, neutrosophic pre-connected, neutrosophic pre-T2, neutrosophic δ-semi-T2, …

Analysis Of Bck/Bci-Algebras Based On Bipolar Complex Intuitionistic Fuzzy Soft Ideals, Zeeshan Ali

Neutrosophic Systems with Applications

In this article, we design an informative and reliable technique of bipolar complex intuitionistic fuzzy soft sets with numerous operational laws by merging the model of soft sets, complex fuzzy sets, and bipolar intuitionistic fuzzy sets to handle imprecise data. In addition, an ideal in a BCK-algebra is derived based on bipolar complex intuitionistic fuzzy soft set theory are proposed which can capture the information of hesitancy, vagueness, and non-membership information within the circumstance of BCK-algebra. Moreover, we design union, intersection, AND, and OR based on bipolar complex intuitionistic fuzzy soft ideal and simplify it with the help of numerous …

Comparative Analysis Of Multi-Criteria Techniques In Neutrosophic Environment And Their Applications To Economic Condition Assessment, Asmaa Elsayed, Mai Mohamed

Neutrosophic Systems with Applications

In economic decision-making, the challenge of evaluating multiple, often conflicting criteria necessitates advanced Multi-Criteria Decision-Making (MCDM) techniques. Traditional methods can struggle with the inherent uncertainty, ambiguity, and imprecision of real-world data. This paper addresses these challenges by investigating the effectiveness of various MCDM techniques within neutrosophic environments, with a particular focus on the Criteria-wise Alternatives Ranking and Correlation Analysis for Composite Scoring (CARCACS) method. Neutrosophic sets, which incorporate truth, falsity, and indeterminacy, provide a robust framework for addressing the vagueness and inconsistencies found in economic indicators such as GDP growth, employment levels, inflation rates, trade balances, investment activity, and government …

Toward An Insider Threat Education Platform: A Theoretical Literature Review, Haywood Gelman, John D. Hastings, David Kenley, Eleanor Loiacono

Research & Publications

Insider threats (InTs) within organizations are small in number but have a disproportionate ability to damage systems, information, and infrastructure. Existing InT research studies the problem from psychological, technical, and educational perspectives. Proposed theories include research on psychological indicators, machine learning, user behavioral log analysis, and educational methods to teach employees recognition and mitigation techniques. Because InTs are a human problem, training methods that address InT detection from a behavioral perspective are critical. While numerous technological and psychological theories exist on detection, prevention, and mitigation, few training methods prioritize psychological indicators. This literature review studied peer-reviewed, InT research organized by …