Digital Commons Network^™

(R2120) Flexible Group Service Map/Ph/1 Queueing Model With Working Vacation And Optional Service, G. Ayyappan, S. Kalaiarasi

Applications and Applied Mathematics: An International Journal (AAM)

There are many uses of queues, where services are provided in groups; these types of queues are widely studied in the literature. In this paper we examine a particular queueing model wherein the services are provided in groups and the group size may be less than or equal to the size initially fixed. The arrival follows a Markovian arrival process. The service time of each individual customer follows phase type distribution. The maximum of each customer’s individual service time within a group is defined as the group’s service time. At the service completion moment if there are fewer customers than …

(R2084) Clarification Of Mathematical Criteria For Conservative Forces And Vector Fields With A Point Singularity In Engineering Studies, Nelli Aleksandrova

Applications and Applied Mathematics: An International Journal (AAM)

The paper deals with a comprehensive analysis of existing mathematical criteria for conservative vector fields including algebraic and geometrical interpretation of Extended Green’s Theorem. Special attention is devoted to the fields containing a point singularity, which represents the primary challenge both in teaching Calculus and in carrying out scientific research in general in computer engineering. Examples of real-world physical fields such as gravitational, electric and magnetic ones are used to appreciate the proposed clarification while teaching various interchangeable disciplines such as mathematics, physics and engineering. Other examples from scientific research literature are provided as well to support the necessity of …

(R2122) Analysis Of Halo Orbits In The Elliptical R3bp With Mass Variation, Majhar Ali, Abdullah .

Applications and Applied Mathematics: An International Journal (AAM)

The elliptic restricted three-body problem investigates the motion behaviour of the variable mass infinitesimal body under the gravitational forces of the radiated oblate primary and dipole secondary. The equations of motion of the infinitesimal body are determined using Jeans law and Meshcherskii space time transformations. Using the Lindstedt-Poincaré method, we perform the solutions of the equations of motion. With the use of these solutions and the equations of motion, we numerically illustrate the time series, phase spaces, projections and the Halo orbits.

(R2134) Continuous Shooting Approach With Improved Shooting Slope For Solving Higher Integer Order Boundary Value Problem, Razaq Adekola Oderinu, Adebowale Niyi Aderibigbe, Saheed Alao, Ahmed Adeyi Yahaya

Applications and Applied Mathematics: An International Journal (AAM)

This study presents a semi-analytical shooting method for solving nonlinear higher-order boundary value problems by integrating the Adomian Decomposition Method into the shooting technique, enabling series-form solutions. To enhance convergence, new higher-order shooting slopes and their corresponding supplementary equation formulas were introduced. Three numerical examples demonstrated the method’s accuracy: for the first two, absolute errors were computed using available exact solutions, while the third was compared with reference literature due to the absence of an exact solution. The method achieved very small absolute errors in the first two cases, and results from the third closely matched the literature. Tolerance values—defined …

(R2094) On Mds Bisymmetric Rhotrices Using Self-Dual Bases And Conjugate Elements Of Finite Fields, Shalini Gupta, Ruchi Narang, Manpreet Singh

Applications and Applied Mathematics: An International Journal (AAM)

Bisymmetric matrices have wide range of applications in statistics, engineering problems, information theory and computer science including coding theory and cryptography. In cryptography, a rhotrix being a couple matrix doubles the security of the cryptosystem. Here, we construct maximum distance separable (MDS) bisymmetric rhotrices using self-dual bases and conjugate elements of finite fields. MDS rhotrices are very crucial for the designing of block ciphers and hash functions in cryptography.

Nonlinear Proudman Resonance Under Moving Atmospheric System, Chunyan Li

Faculty Publications

A nonlinear theoretical model with an exact solution is developed to critically examine the Proudman resonance problem. In this framework, a moving atmospheric pressure system forces a wave governed by the square of the wave Froude number (n=F²). Proudman’s classical linear solution, although widely cited, diverges to infinity at resonance (n=1), limiting its physical realism. This work extends the linear regime into the nonlinear by solving the governing equations exactly. The resulting solution remains finite at resonance. The first-order approximation recovers Proudman’s solution, while the second-order approximation already yields a finite resonant response—providing a more accurate and physically …

Pymelt-Px: A Python Script For Modeling Melting Of A Pyroxenite-Peridotite Bilithological Mantle, Ana L. Jimenez Bustos

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

The study of oceanic crust formation is a fundamental building block in our understanding of the processes of planetary formation, necessitating an understanding of the melt generation processes that help form oceanic crust. To aid in this purpose, we present pyMeltPX: a bilithological pyroxenite-peridotite mantle modeling script. Although the mantle is primarily comprised of peridotite, pyroxenite is a minor but ubiquitous feature of the mantle and can contribute a disproportionate amount of melt to crustal generation in mid-ocean ridge and ocean island basalt settings. Our model, pyMeltPX, is a python coded, extensible tool based on the Excel calculator by Lambart …

December 2025, Robert Kelly

Robert Kelly Manuscripts

No abstract provided.

Machine Learning-Optimized Porous Thermally Responsive Ss-Pcm With Switchable Transparency For Adaptive Building Envelope Coatings, Zhiying Xiao, Rajae Bousselham, Mingjiang Tao, Sergio Granados-Focil, Oren Mangoubi, Steven Van Dessel

Chemistry

Buildings account for nearly 40% of total energy consumption, with a significant share of heating and cooling demand arising from building envelopes. Conventional passive envelopes—such as cool roofs, radiative cooling surfaces, glazing systems, and passive solar walls—cannot automatically adapt to environmental conditions by switching between heating and cooling modes. To address this limitation, we propose a passive, adaptive building envelope coating system that responds to ambient temperature changes without external energy input. The system integrates solid–solid phase change materials (SS-PCM), Polydimethylsiloxane (PDMS) and Silver (Ag), enabling switchable radiative cooling and solar heating effects. We investigated the influence of porous structures …

Motivational Interviewing And Servant-Leadership: An Interview With Dr. William R. Miller, William Richard Miller, Jemima Neddy Organ

International Journal of Servant-Leadership

Dr. Miller is a leader in addiction research and treatment and co-founder of Motivational Interviewing (MI), an evidence-based method for helping people change. In this interview, he discusses how he developed MI, highlighting his collaborative approach to servant-leadership. He advocates organizational values that create a collegial, collaborative environment and help meet human needs for autonomy, relatedness, and competence. He discusses power dynamics in leadership and the importance of a person-centered approach to leadership.

Prevalence Of Sleep Disturbances And Factors Associated Among School Going Children In Uganda, A Cross-Sectional Study, Martha Sajatovic

Faculty Scholarship

Background: Sleep disturbances greatly impact children's academic performance and social well-being. This study set out to determine the prevalence of sleep disturbances and factors associated among school going children in Kawempe division, Kampala, Uganda. Methods: In a community cross-sectional study, 548 study participants using random cluster sampling were enrolled. The children start lessons at 8am and end the days classes at 5pm. Random cluster sampling method was used to select participants from the 19 parishes in Kawempe district. Data was collected using a semi-structured questionnaire and Sleep Disturbance Scale for Children (SDSC). Descriptive statistics and multivariate binary logistic regression were …

Real Topological Hochschild Homology Via The Norm And Real Witt Vectors, Gabriel Angelini-Knoll

Faculty Scholarship

We prove that Real topological Hochschild homology can be characterized as the norm from the cyclic group of order 2 to the orthogonal group O(2). From this perspective, we then prove a multiplicative double coset formula for the restriction of this norm to dihedral groups of order 2m. This informs our new definition of Real Hochschild homology of rings with anti-involution, which we show is the algebraic analogue of Real topological Hochschild homology. Using extra structure on Real Hochschild homology, we define a new theory of p-typical Witt vectors of rings with anti-involution. We end with an explicit computation of …

Effects Of Commission Errors During Prompting On Skill Acquisition And Maintenance, Molly K. Mutchler

Dissertations

Procedural fidelity refers to the extent to which procedures are implemented as intended. Engaging in procedural fidelity errors can lead to detrimental outcomes during skill acquisition and maintenance. The purpose of this study was to parametrically evaluate and compare two commission errors during prompting procedures using an arbitrary tacting task taught to college-aged students. Participants learned to tact four sets of arbitrary pictures and names. Prompting errors consisted of either providing the correct letters for a name in an incorrect order (i.e., an error within a component of the name) or providing the correct name for another picture (i.e., an …

Evaluating Defi Vulnerabilities: The Role Of Bug Bounty Programs On Defi Software Supply Chain, Ping Fan Ke, Yi Meng Lau, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Decentralized finance (DeFi), powered by blockchain technology, enables peer-to-peer financial transactions without intermediaries. Despite rapid adoption, DeFi attracts malicious actors exploiting vulnerabilities. To mitigate risks, we propose a framework assessing entry points in the DeFi software supply chain: smart contracts, oracles/third-party feeds, user interfaces, off-chain storage, and crypto wallets. Applying this framework, we evaluate whether industry solutions—particularly bug bounty programs—adequately address these gaps. Our preliminary analysis indicates that most programs cover smart contract vulnerabilities (85.7%), followed by user interface issues (21.3%) and crypto wallet loopholes (11.9%). However, third-party risks, such as oracle feeds, are frequently deemed out of scope. This …

A Socio-Technical Analysis Of Market Reactions On Meme Coins: Trump’S Presidential Effect, Ping Fan Ke, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Meme coins are a unique type of cryptocurrency whose value is shaped by internet culture and viral trends. This study introduces a socio-technical research model to examine key factors influencing meme coin dynamics and applies it to analyze market reactions to Donald Trump’s 2024 U.S. presidential election victory and inauguration, focusing on the $TRUMP meme coin and other politics-related meme coins, known as PolitiFi. Using a mixed-methods approach, we analyze publicly available news, social media activity, and marketplace data to investigate the interaction between social engagement and technical infrastructure. Econometric analysis shows that Trump-related events triggered short-term price surges, increased …

Registration Is A Powerful Rotation-Invariance Learner For 3d Anomaly Detection, Yuyang Yu, Zhengwei Chen, Xuemiao Xu, Lei Zhang, Haoxin Yang, Yongwei Nie, Shengfeng He

Research Collection School Of Computing and Information Systems

3D anomaly detection in point-cloud data is critical for industrial quality control, aiming to identify structural defects with high reliability. However, current memory bank-based methods often suffer from inconsistent feature transformations and limited discriminative capacity, particularly in capturing local geometric details and achieving rotation invariance. These limitations become more pronounced when registration fails, leading to unreliable detection results. We argue that point-cloud registration plays an essential role not only in aligning geometric structures but also in guiding feature extraction toward rotation-invariant and locally discriminative representations. To this end, we propose a registration-induced, rotation-invariant feature extraction framework that integrates the objectives …

Safe-Sora: Safe Text-To-Video Generation Via Graphical Watermarking, Zihan Su, Xuerui Qiu, Hongbin Xu, Tangyu Jiang, Jun-Hao Zhuang, Chun Yuan, Ming Li, Shengfeng He, Fei Yu

Research Collection School Of Computing and Information Systems

The explosive growth of generative video models has amplified the demand for reliable copyright preservation of AI-generated content. Despite its popularity in image synthesis, invisible generative watermarking remains largely underexplored in video generation. To address this gap, we propose Safe-Sora, the first framework to embed graphical watermarks directly into the video generation process. Motivated by the observation that watermarking performance is closely tied to the visual similarity between the watermark and cover content, we introduce a hierarchical coarse-to-fine adaptive matching mechanism. Specifically, the watermark image is divided into patches, each assigned to the most visually similar video frame, and further …

Jury-And-Judge Chain-Of-Thought For Uncovering Toxic Data In 3d Visual Grounding, Kaixiang Huang, Qifeng Zhang, Jin Wang, Jingru Yang, Yang Zhou, Huan Yu, Guodong Lu, Shengfeng He

Research Collection School Of Computing and Information Systems

3D Visual Grounding (3DVG) faces persistent challenges due to coarse scene-level observations and logically inconsistent annotations, which introduce ambiguities that compromise data quality and hinder effective model supervision. To address these challenges, we introduce Refer-Judge, a novel framework that harnesses the reasoning capabilities of Multimodal Large Language Models (MLLMs) to identify and mitigate toxic data. At the core of Refer-Judge is a Jury-and-Judge Chain-of-Thought paradigm, inspired by the deliberative process of the judicial system. This framework targets the root causes of annotation noise: jurors collaboratively assess 3DVG samples from diverse perspectives, providing structured, multi-faceted evaluations. Judges then consolidate these insights …

Misodice: Multi-Agent Imitation From Mixed-Quality Demonstrations, The Viet Bui, Tien Mai, Hong Thanh Nguyen

Research Collection School Of Computing and Information Systems

We study offline imitation learning (IL) in cooperative multi-agent settings, where demonstrations have unlabeled mixed quality - containing both expert and suboptimal trajectories. Our proposed solution is structured in two stages: trajectory labeling and multi-agent imitation learning, designed jointly to enable effective learning from heterogeneous, unlabeled data. In the first stage, we combine advances in large language models and preference-based reinforcement learning to construct a progressive labeling pipeline that distinguishes expert-quality trajectories. In the second stage, we introduce MisoDICE, a novel multi-agent IL algorithm that leverages these labels to learn robust policies while addressing the computational complexity of large joint …

Cssa-Fusion: Channel Selective And Spatial Alignment Infrared-Visible Image Fusion, Zhen Li, Zhi Zeng, Zhongrui Xiao, Ming Wen, Zhiyuan Zhang, Yibin Tian

Research Collection School Of Computing and Information Systems

Infrared-visible image fusion aims to integrate complementary information from two modalities to generate images with enriched semantic content. However, existing methods often neglect two critical aspects: the design of a local–global feature enhancement architecture and spatial alignment. To address these challenges, we propose Channel Selective and Spatial Alignment Fusion (CSSA-Fusion), a novel framework composed of two synergistic modules. The first is a selective channel and redundancy suppression module, which introduces a dual-branch selective channel attention mechanism to jointly capture local saliency and global channel importance for enhanced feature representation, and an informativeness–redundancy separation strategy to suppress redundant information while preserving …

The Rise Of Parameter Specialization For Knowledge Storage In Large Language Models, Yihuai Hong, Yiran Zhao, Wei Tang, Yang Deng, Yu Rong, Wenxuan Zhang

Research Collection School Of Computing and Information Systems

Over time, a growing wave of large language models from various series has been introduced to the community. Researchers are striving to maximize the performance of language models with constrained parameter sizes. However, from a microscopic perspective, there has been limited research on how to better store knowledge in model parameters, particularly within MLPs, to enable more effective utilization of this knowledge by the model. In this work, we analyze twenty publicly available open-source large language models to investigate the relationship between their strong performance and the way knowledge is stored in their corresponding MLP parameters. Our findings reveal that …

A Partition Cover Approach To Tokenization, Jia Peng Lim, Shawn Tan, Davin Choo, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Tokenization is the process of encoding strings into tokens of a fixed vocabulary size, and is widely utilized in Natural Language Processing applications. The leading tokenization algorithm today is Byte Pair Encoding (BPE), which formulates the tokenization problem as a compression problem and tackles it by performing sequences of merges. In this work, we formulate tokenization as an optimization objective, show that it is NP-hard via a simple reduction from vertex cover, and propose a polynomial-time greedy algorithm GreedTok. Our formulation naturally relaxes to the well-studied weighted maximum coverage problem which has a simple -approximation algorithm GreedWMC. Through empirical evaluations …

Sheetpedia: A 300k-Spreadsheet Corpus For Spreadsheet Intelligence And Llm Fine-Tuning, Zailong Tian, Zhuoheng Han, Houfeng Wang, Lizi Liao

Research Collection School Of Computing and Information Systems

Spreadsheets are widely used for data analysis and reporting, yet their complex structure and formula logic pose significant challenges for AI systems. We introduce Sheetpedia, a large-scale corpus of over 290,000 diverse spreadsheets (from 324,000+ workbooks) compiled from enterprise email archives and online forums. We detail a rigorous collection and preprocessing pipeline (integrating the Enron email spreadsheet archive and the Fuse web corpus, plus a new crawl of Excel forums) to standardize formats, filter languages, and remove duplicates. Sheetpedia provides extensive coverage of real formulas and annotations – addressing a gap left by prior table datasets (e.g. web tables used …

Cropcapsnet: Enhanced Capsule Network For Crop Disease Classification, Juan Qin, Linfan Deng, Cong Li, Junjie He, Haibo Pen, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

The prevention and treatment of crop diseases are crucial for the development of smart agriculture. The classification of crop diseases based on deep learning for early disease monitoring and control has become the mainstream direction of research. This paper proposes a novel deep learning model called ”CropCapsNet”, which combines Squeeze-and-Excitation Inception (SE-Inception) module and has improved capsule structure for crop disease classification. The network first extracts shallow features of input samples through double-layer convolution, then uses SE-Inception to achieve deep multi-scale feature acquisition, and finally outputs classification results through an improved capsule structure. SE-Inception adds Squeeze-and-Excitation(SE) attention after each multi-scale …

An Analysis Of Face Synthesis Methods And Their Influence On Human Perception, Maha Habib Almaimani

All Dissertations

Synthetic faces (e.g., computer-generated characters) have been increasingly utilized across various fields, including entertainment, healthcare, and education. Perceptual studies are often conducted to understand how synthetic faces are perceived by humans, aiming to enhance both quality and user experience in these domains. Over the years, numerous methods have been developed to create synthetic faces, ranging from traditional techniques such as image composites, Active Appearance Models, and 3D Morphable Models to more recent machine-learning-based frameworks like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).

Despite the growing adoption of synthetic face generation and the variety of algorithms available for their creation, …

Declined Charge: An Attempt At The Horror Game Genre, Fernando Sepulveda Guizar

Computer Science and Software Engineering

Books and movies are a great medium for people to experience new worlds and experiences through a usually passive method. This can be great for stories with a set story and have all the pieces fall into place as the author intended. Video games on the other hand can give players a more active role in the worlds and stories that they experience. Players have direct control over the player character, and their actions have consequences that may or may not persist throughout the entire game, which is not usually the case with movies or books. This is why horror …

The Power Of Core Memories In Financial Education For Gen Alpha Children, Karen Richel

Journal of Human Sciences and Extension

Financial education plays a critical role in shaping lifelong financial behaviors and decision-making skills. To create a lasting impact, it is essential to establish core memories associated with money management from an early age. This article explores the significance of these foundational experiences and their role in financial education for Gen Alpha children.

A series of eight immersive financial education events was developed to meet state and national standards for students in pre-kindergarten through sixth grade. These events employ play-based and object-based learning approaches, immersing students in engaging, age-appropriate activities that incorporate real-world scenarios. By creating a fun and memorable …

Wofford Today Winter 2025, Wofford College. Office Of Marketing And Communications

Wofford Today

No abstract provided.

The Influence Of Tight Binaries On Protoplanetary Disk Masses, K. Flaherty, P. Knowlton, T. Smith-Gandy, A. M. Hughes, M. Kounkel, Eric L.N. Jensen, J. Muzerolle, K. Covey

Physics & Astronomy Faculty Works

Binary systems are a common site of planet formation, despite the destructive effects of the binary on the disk. While surveys of planet-forming material have found diminished disk masses around binaries with medium separation (∼10–100 au), less is known about tight (< 10 au) binaries, where a significant circumbinary disk may escape the disruptive dynamical effects of the binary. We survey over 100 spectroscopic binaries in the Orion A region with the Atacama Large Millimeter/submillimeter Array (ALMA), detecting significant continuum emission among 21 of them with disk masses ranging from 1 to 100 M_⊕. We find evidence of systematically lower disk masses among the binary sample when compared to single-star surveys, which may reflect a diminished planet-forming potential around tight binaries. The infrared excess fraction among the binary sample is comparable to that of single stars, although the tight binaries without significant ALMA emission display tentative evidence of weaker 3–5 …

From Static Prediction To Mindful Machines: A Paradigm Shift In Distributed Ai Systems, Rao Mikkilineni, W. Patrick Kelly

Barowsky School of Business | Faculty Scholarship

A special class of complex adaptive systems—biological and social—thrive not by passively accumulating patterns, but by engineering coherence, i.e., the deliberate alignment of prior knowledge, real-time updates, and teleonomic purposes. By contrast, today’s AI stacks—Large Language Models (LLMs) wrapped in agentic toolchains—remain rooted in a Turing-paradigm architecture: statistical world models (opaque weights) bolted onto brittle, imperative workflows. They excel at pattern completion, but they externalize governance, memory, and purpose, thereby accumulating coherence debt—a structural fragility manifested as hallucinations, shallow and siloed memory, ad hoc guardrails, and costly human oversight. The shortcoming of current AI relative to human-like intelligence is therefore …