Digital Commons Network^™

Information Bottleneck‑Guided Mlps For Robust Spatial‑Temporal Forecasting, Min Chen, Guansong Pang, Wenjun Wang, Cheng Yan

Research Collection School Of Computing and Information Systems

Spatial-temporal forecasting (STF) plays a pivotal role in urban planning and computing. Spatial-Temporal Graph Neural Networks (STGNNs) excel at modeling spatial-temporal dynamics, thus being robust against noise perturbations. However, they often suffer from relatively poor computational efficiency. Simplifying the architectures can improve efficiency but also weakens robustness with respect to noise interference. In this study, we investigate the problem: can simple neural networks such as Multi-Layer Perceptrons (MLPs) achieve robust spatial-temporal forecasting while remaining efficient? To this end, we first reveal the dual noise effect in spatial-temporal data and propose a theoretically grounded principle termed Robust Spatial-Temporal Information Bottleneck (RSTIB), …

Generalization Analysis For Supervised Contrastive Representation Learning Under Non‑Iid Settings, Minh Hieu Nong, Antoine Ledent

Research Collection School Of Computing and Information Systems

Contrastive Representation Learning (CRL) has achieved impressive success in various domains in recent years. Nevertheless, the theoretical understanding of the generalization behavior of CRL has remained limited. Moreover, to the best of our knowledge, the current literature only analyzes generalization bounds under the assumption that the data tuples used for contrastive learning are independently and identically distributed. However, in practice, we are often limited to a fixed pool of reusable labeled data points, making it inevitable to recycle data across tuples to create sufficiently large datasets. Therefore, the tuple-wise independence condition imposed by previous works is invalidated. In this paper, …

Fashiondpo: Fine‑Tune Fashion Outfit Generation Model Using Direct Preference Optimization, Mingzhe Yu, Yunshan Ma, Lei Wu, Changshuo Wang, Xue Li, Lei Meng

Research Collection School Of Computing and Information Systems

Personalized outfit generation aims to construct a set of compatible and personalized fashion items as an outfit. Recently, generative AI models have received widespread attention, as they can generate fashion items for users to complete an incomplete outfit or create a complete outfit. However, they have limitations in terms of lacking diversity and relying on the supervised learning paradigm. Recognizing this gap, we propose a novel framework FashionDPO, which fine-tunes the fashion outfit generation model using direct preference optimization. This framework aims to provide a general fine-tuning approach to fashion generative models, refining a pre-trained fashion outfit generation model using …

Grokformer: Graph Fourier Kolmogorov‑Arnold Transformers, Guoguo Ai, Guansong Pang, Hezhe Qiao, Yuan Gao, Hui Yan

Research Collection School Of Computing and Information Systems

Graph Transformers (GTs) have demonstrated remarkable performance in graph representation learning over popular graph neural networks (GNNs). However, self-attention, the core module of GTs, preserves only low-frequency signals in graph features, leading to ineffectiveness in capturing other important signals like high-frequency ones. Some recent GT models help alleviate this issue, but their flexibility and expressiveness are still limited since the filters they learn are fixed on predefined graph spectrum or spectral order. To tackle this challenge, we propose a Graph Fourier Kolmogorov-Arnold Transformer (GrokFormer), a novel GT model that learns highly expressive spectral filters with adaptive graph spectrum and spectral …

Explaining Explanations: An Empirical Study Of Explanations In Code Reviews, Ratnadira Widyasari, Ting Zhang, Abir Bouraffa, Walid Maalej, David Lo

Research Collection School Of Computing and Information Systems

Code reviews are central for software quality assurance. Ideally, reviewers should explain their feedback to enable authors of code changes to understand the feedback and act accordingly. Different developers might need different explanations in different contexts. Therefore, assisting this process first requires understanding the types of explanations reviewers usually provide. The goal of this article is to study the types of explanations used in code reviews and explore the potential of Large Language Models (LLMs), specifically ChatGPT, in generating these specific types. We extracted 793 code review comments from Gerrit and manually labeled them based on whether they contained a …

How Are We Detecting Inconsistent Method Names? An Empirical Study From Code Review Perspective, Kisub Kim, Xin Zhou, Dongsun Kim, Julia Lawall, Kui Liu, Tegawendé F. Bissyandé, Jacques Klein, Jaekwon Lee, David Lo

Research Collection School Of Computing and Information Systems

Proper naming of methods can make program code easier to understand, and thus enhance software maintainability. Yet, developers may use inconsistent names due to poor communication or a lack of familiarity with conventions within the software development lifecycle. To address this issue, much research effort has been invested into building automatic tools that can check for method name inconsistency and recommend consistent names. However, existing datasets generally do not provide precise details about why a method name was deemed improper and required to be changed. Such information can give useful hints on how to improve the recommendation of adequate method …

Enhancing Project-Specific Code Completion By Inferring Internal Api Information, Le Deng, Xiaoxia Ren, Chao Ni, Ming Liang, David Lo, Zhongxin Liu

Research Collection School Of Computing and Information Systems

Project-specific code completion, which aims to complete code based on the context of the project, is an important and practical software engineering task. The state-of-the-art approaches employ the retrieval-augmented generation (RAG) paradigm and prompt large language models (LLMs) with information retrieved from the target project for project-specific code completion. In practice, developers always define and use custom functionalities, namely internal APIs, to facilitate the implementation of specific project requirements. Thus, it is essential to consider internal API information for accurate project-specific code completion. However, existing approaches either retrieve similar code snippets, which do not necessarily contain related internal API information, …

Search For Extremely-High-Energy Neutrinos And First Constraints On The Ultrahigh-Energy Cosmic-Ray Proton Fraction With Icecube, Karen Andeen

Physics Faculty Research and Publications

We present a search for the diffuse extremely-high-energy neutrino flux using 12.6 years of IceCube data. The nonobservation of neutrinos with energies well above 10 PeV constrains the all-flavor neutrino flux at 1018  eV to a level of 𝐸2⁢Φ𝜈𝑒+𝜈𝜇+𝜈𝜏≃10−8  GeV cm−2 s−1 sr−1, the most stringent limit to date. Using these data, we constrain the proton fraction of ultrahigh-energy cosmic rays (UHECRs) above ≃30  EeV to be  ≲70% (at 90% CL) if the cosmological evolution of the sources is comparable to or stronger than the star formation rate. This is the first result to disfavor the “proton-only” hypothesis for UHECR …

Rattler Python, Samer Jabor

Systems Manuals - 2026

The Rattler Python project is an interactive game-based learning system that intends to teach the basic concepts of Python programming through guided instruction, gameplay challenges, and review-based assessments. The document contains a proposal for this system consisting of problem definition, background research, existing solutions, and the proposed product, together with the system scope, assumptions, and the organization of the remainder of this document.

Garage Sale Web-Based Information System, Sonachi Mogbogu

Systems Manuals - 2026

The Garage Sale web application is in response to a business need of an online interactive system. This system will support the interaction between owners and shoppers of garage sale event. The online information system is a great idea to implement because it will help create sales awareness which will lead to increase in the customer base, and increased sales for event organizers. People are used to the traditional approaches, advertising events through word-of-mouth and posting signs alongside roads, however, having an online information system will be more effective in reaching a wider market of buyers. The traditional approaches do …

Ready Or Not? Predicting Readiness For And Success In Eighth-Grade Algebra I, Samantha N. Staples

Doctor of Education (Ed.D)

In recent years, enrollment in Algebra I in eighth grade has increased as middle schools have administratively placed more students in the class as an opportunity to earn high school credit before entering high school. However, many students are not ready to take Algebra I in eighth grade and are unsuccessful. Framed by Piaget’s (1936) theory of cognitive development and Vygotsky’s (1978) theory of the zone of proximal development, the purpose of this study was to determine which academic factors best predict Algebra I readiness and Algebra I success for eighth-grade students taking Algebra I in one Southwest Florida school …

Realism, Instrumentalism, And The Language Of Science Teaching: A Quantitative Study, James M. Almand

Doctor of Education (Ed.D)

The purpose of this quantitative, non-experimental, correlational study was to investigate how science educators' epistemological orientations, specifically, their leanings toward realism or instrumentalism, influence the degree of certainty in their instructional language. The study addressed a significant gap in science education literature by empirically analyzing whether educators' philosophical beliefs about the nature of scientific knowledge predict the language they use when teaching science. Data were collected through a researcher-developed survey, the Science Educators' Epistemological Beliefs and Classroom Language Practices Survey, which measured participants' epistemological positions and linguistic tendencies across a sample of current and former science educators in the United …

Data-Driven Police Profiling, Christopher Slobogin

Vanderbilt Law School Faculty Publications

Police departments increasingly rely on algorithms and other data- driven methods of identifying high-crime areas andpeople who are at high risk for involvement in crime. This Article examines several constitutional obstacles to this type ofpolicing. First, to the extent that these algorithms rely on data entitled to privacy protection, they may violate the Fourth Amendment. Second, the steps police take in response to a "hot" place or person designation must also be subject to constitutional regulation. Further, the principle of legality should prohibit the police from acting on any risk designation, even one that is very likely accurate, in the …

Artificial Intelligence And Humanoid Robotics: Bioethical Implications Of Replacing Human Agency In Healthcare And Beyond, Sara Feizyab, Gabriele Bonetti, Maria Chiara Medori, Cecilia Micheletti, Immacolata De Luca, Kevin Donato, Jan Miertuš, Mehmet Sait Dundar, Miroslava Vráblová, Gary Henehan, Richard Brown, Robert Marks, Stanislav Miertus, Lorenzo Lorusso, Gianluca Martino Tartaglia, Munis Dundar, Sandro Michelini, Stephen Thaddeus Connelly, Ariola Bacu, Tommaso Beccari, Ornela Gordani, Xhilda Dhamo, Eglantina Kalluci, Dominika Vešelényiová, Iveta Dirgová Luptáková, Jiri Pospíchal, Matteo Bertelli

Research Outputs: 2025-Present

The integration of advanced artificial intelligence (AI) and humanoid robotics into healthcare represents a critical evolution in biotechnology with profound societal implications. This review explores the bioethical implications of these technologies, and their potential to displace human agency in life-critical decisions. It adopts an interdisciplinary approach encompassing ethics, law, and technology. The review examines how innovations in AI and robotics might shift autonomy from humans to machines, and addresses the accountability challenges inherent in such transitions. We synthesize discussions on the ethical management of AI and robotics, underscoring the importance of maintaining human oversight and integrating ethical standards in technology …

Budget Deficit Spending Causes Inflation, Roberto B. Raymundo, Paulynne J. Castillo

DLSU Business & Economics Review

Using the Cochrane-Orcutt iterative procedure, the paper provides strong statistical evidence that inflation is a monetary phenomenon caused by budget deficit spending when the central bank buys government debt. Regression results validate that increasing budget deficits lead to the issuance of more debt securities the central bank uses to back the creation of new money. The central bank purchases government securities from commercial banks to implement expansionary monetary policy. The increase in money supply is not possible without the issuance of government debt securities, which, in turn, is only undertaken by the Bureau of Treasury when it finances budget deficits. …

Reaction Control Mechanism In Deoxyuridine 5'-Triphosphate Nucleotidohydrolase, Aaron Delay

School of Biological Sciences: Dissertations, Theses, and Student Research

Deoxyuridine 5'-triphosphate nucleotidohydrolase (dUTPase) is an enzyme involved in the pyrimidine biosynthesis pathway, a key component of cellular DNA metabolism. It regulates intracellular uracil carrying triphosphate levels by hydrolyzing dUTP, thereby providing a substrate for thymidylate synthase (TS). The effective inhibition of dUTPase is expected to enhance TS-targeted chemotherapy by promoting thymine-less apoptosis.

Although the reaction mechanism of dUTPase has been studied, the human nuclear homotrimeric form remains complex, as all three subunits cooperatively form a single active site. As a result, the detailed molecular dynamics of its catalysis are still not fully understood. In this study, I investigated the …

The Impact Computer-Assisted Learning Has On Elementary Students Mastering Math Standards, Amanda Geelan

Master's Theses & Capstone Projects

Math fact fluency is a fundamental skill students need to become proficient in to engage in higher-level math skills. For many students, learning their math facts and becoming fluent in them can be a challenge. This inquiry-based research study aims to determine if the use of computer-assisted learning programs such as Math Fact Lab can help educators meet the varying needs of their students while also making learning math facts an engaging and personalized educational experience for students. The study utilized a quantitative approach, using both Math Fact Lab placement test scores as well as data from the learning levels …

Personalized Learning Strategies In The Classroom, Kendra Carlson

Master's Theses & Capstone Projects

Personalized learning is essential for students to be more engaged and have higher achievement in the classroom. There are too many students who are struggling in the classroom with staying engaged and this is then leading to students struggling with their learning. Research has shown that personalized learning strategies can provide promising outcomes for students who are struggling in the classroom. This inquiry-based research study aims to determine if personalized learning strategies can help struggling learners to be engaged and learn in the classroom. The study utilized a qualitative approach, using both teacher surveys and observations of a summer school …

Supporting Productive Struggle Within The Special Education Classroom, Nicole Snitkey

Master's Theses & Capstone Projects

Students with significant disabilities are frequently taught using highly structured, direct instruction, often with an errorless component. While this approach can build confidence in specific tasks, it may limit opportunities for developing independent problem-solving skills. When these students are presented with unfamiliar challenges, they may experience frustration and dysregulation. This study aims to investigate what productive struggle strategies are effective in supporting students when engaging in challenging tasks while also maintaining regulation. Qualitative data was gathered utilizing field notes to determine what, if any, productive struggle strategies support students in special education through a challenging task. The results of this …

Data Annotations, Bradley M. Ratliff

Model Desert Terrain Monochromatic DoT Dataset

Pixel-wise object masks for each polarimetric scene in ASL file format for the Model Desert Terrain Monochromatic DoT data.

Numerical Approach To The Optimization Of The Bandwidth Tunability Of A Non-Cascaded Multifunctional Optical Filter, Ramon Benedict L. Lapina, Benjamin B. Dingel, Clint Dominic Bennett

Ateneo Innovation Center

Previously, we reported a multifunctional optical filter which is a Photonic Integrated Circuit (PIC)–based, noncascaded bandpass filter wherein the Ring Resonators-based Direct-Coupled-All-Pass Filter (D-APF) and Cross-coupled All-pass Filter (C-APF) are attached to each of the arms of a single Mach Zehnder Interferometer (MZI). This device is an alternative platform to the conventional platform of programmable photonic filters that does not rely on combining different photonic elements to implement various filter functionalities. For one, it can generate (i) Narrowband Filter, (ii) Asymmetric Interleaver (AI) and (iii) Symmetric Interleaver (SI) responses by varying limited number of specific parameters of the device. It …

Virtual Reality For Improving One-Class Classification Accuracy On Pharmaceutical And Medical Data, Hyrum Redd, John H. Kalivas

Idaho Conference on Undergraduate Research

Virtual reality (VR) is quickly expanding its jurisdiction in terms of usability in classrooms and professional settings. In this poster, VR is used as an interface where the user can perform one-class classification (OCC) to make sample classification decisions producing higher accuracy results than an autonomous ML algorithm. This VR practice, a branch of the larger scientific domain termed immersive analytics, takes advantage of a human’s innate ability to recognize patterns and solve problems when faced with novel situations, something that machine learning (ML) and large language models struggle with. One-class classification is an important scenario that arises in many …

Cappadocian Theory Of Matter, Dispositionalism + Bundle Theory, And Modern Cosmogony, Flavius D. Raslau

Faith and Philosophy: Journal of the Society of Christian Philosophers

No abstract provided.

Eeg Based Real Time Classification Of Consecutive Two Eye Blinks For Brain Computer Interface Applications, Masud Rabbani, Nafi Us Sabbir Sabith, Anubhav Parida, Iysa Iqbal, Sayed Mashroor Mamun, Rumi Ahmed Khan, Farhad Ahmed, Sheikh Iqbal Ahamed

Computer Science Faculty Research and Publications

Human eye blinks are considered a significant contaminant or artifact in electroencephalogram (EEG), which impacts EEG-based medical or scientific applications. However, eye blink detection can instead be transformed into a potential application of brain–computer interfaces (BCI). This study introduces a novel real-time EEG-based framework for classifying three blink states: no blink, single blink, and two consecutive blinks in one model. EEG data were collected from ten healthy participants using an 8-channel wearable headset under controlled blinking conditions. The data were preprocessed and analyzed using four feature extraction techniques: basic statistical, time-domain, amplitude-driven, and frequency-domain methods. The most significant features were …

The Ethics Of Consent: Reflecting On The Case Of R/Changemyview, Casey Fiesler, Jessica Vitak, Michael Zimmer

Computer Science Faculty Research and Publications

The SIGCHI Research Ethics Committee was established in 2016 in recognition of how the shifting technological landscape has complicated research ethics in HCI. Our research community has also taken up the call to help understand and guide this complex space, examining topics such as research taking place on online platforms without explicit consent, the use of bots as confederates in field experiments, debriefing for large-scale experiments, HCI research that involves or implicates marginalized populations, and ethical considerations for studying social media platforms such as Reddit.

High Frequency Factor Analysis With Partially Observable Factors, Dachuan Chen, Wenqi Lu, Siyu Xie

Research Collection School Of Economics

This paper considers a novel factor structure – Partially Observable Factor Model – where both observable factors and latent factors exist in the model simultaneously. Such factor structure can make sure both interpretability and goodness-of-fit at the same time. Necessary estimation methodologies for this partially observable factor model are developed in this paper for the high frequency data. The proposed estimation methodology is robust to jumps, microstructure noise and asynchronous observation times simultaneously.When the observable factors are exogenous, we provide the estimation theory for the integrated eigenvalues of the residual covariance matrix, which including the bias-corrected estimator, central limit theorem …

Seconds From Impact: Anticipatory Vehicular Crash Prediction Using Video Vision Transormers, Ryan P. Geisen

Master's Theses

Vehicular collisions represent a significant public health concern, necessitating re search into advanced emergency notification systems. While deep learning has shown promise in accident detection, a research gap persists in applying state-of-the-art transformer architectures to the task of anticipatory, real-time crash prediction from video. This thesis addresses this gap by developing and evaluating a Video Vision Transformer (ViViT) for the binary classification of imminent vehicular collisions. Utilizing a curated dataset of 1,493 unique collision sequences, this study systemati cally investigates the impact of temporal context by comparing the ViViT against a single-frame Vision Transformer (ViT) baseline and conducting comprehensive exper …

Retaining Teacehrs In A Small, Rural District In A Post-Pandemic World, Sonya Murrah Bryant

Theses and Dissertations

This dissertation in practice uses improvement science to examine the system in an attempt to improve teacher retention. The improvement project centers around improving teacher retention in a small, rural school district in a post-pandemic world. The district in question saw a stark increase in teachers leaving the district after the pandemic. The improvement team consisting of six district certified staff members including the superintendent, the assistant superintendent for personnel and instruction, the director of special services, the public information officer, a primary school principal, and a teacher. After collaboratively designing a fishbone diagram and driver diagram to analyze the …

The Impact Of Teachers’ Cultural Competence On Curriculum Development In Advanced English Courses, Rhine D. Kirkland

Theses and Dissertations

As student demographics become increasingly more diverse, it is imperative that classroom teachers are responsive to the needs of learners from varied backgrounds. The purpose of this study was to examine the impact of teachers’ cultural competence on their curriculum development in advanced English courses. This case study provided insight on the use of administrative instructional coaching as a professional learning approach to aid in teachers’ creation and implementation of culturally responsive curriculums based on the tenets of Culturally Relevant Pedagogy. The analysis and triangulation of survey, interview, document, and observation data yielded key themes regarding the considerations and conditions …

Exploring Professional Development Of Expatriate Teachers In Kuwait Through Mentoring, Taji Abdul-Raheem

Theses and Dissertations

Professional growth as a teacher is fundamental for teacher retention and an overall determinant of favorable student outcomes. Academic research underscores professional development as an indicator of success for a school’s success as well. Expatriate teachers in Kuwait, who comprise a significant portion of the workforce, come from various backgrounds and levels of readiness for teaching in a contextually and culturally unfamiliar setting. Due to how teachers are hired and approved for teaching without induction, an implementation for continuous professional development has yet to be materialized for teachers in the private sector. This qualitative study leverages Improvement Science to diagnose …