Digital Commons Network^™

Hold Paramount The Health, Safety, And Welfare Of The Public And The Planet, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Machine Learning In Peak Demand Forecasting: Foundations, Trends, And Insights, Shuang Dai, Fanlin Meng, Hongsheng Dai, Qian Wang, Xizhong Chen, Wenlei Bai, Peizhi Shi, Richard Allmendinger, Yuchen Zhang, Jian Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Peak demand forecasting involves predicting the maximum electricity demand within a specific period, which plays a key role in maintaining the efficiency and stability of power systems. The rapid evolution of power systems, driven by advanced metering infrastructure, local energy applications such as electric vehicles, and the increasing adoption of intermittent renewable energy, has introduced greater randomness and reduced predictability in peak demand. Given the pressing need to address more diverse implementation requirements across different contexts, accurate and reliable peak demand forecasting has become increasingly important. To the best of our knowledge, this study is the first to provide a …

Prisrv+: Privacy And Usability-Enhanced Wireless Service Discovery With Fast And Expressive Matchmaking Encryption, Yang Yang, Guomin Yang, Yingjiu Li, Pengfei Wu, Rui Shi, Minming Huang, Jian Weng, Hwee Hwa Pang, Deng, Robert H.

Research Collection School Of Computing and Information Systems

The evolution of decentralized identity (DID) and self-sovereign identity (SSI) frameworks, as endorsed by W3C Verifiable Credentials (VC) and eIDAS 2.0, underscores the need for secure, efficient, and privacy-preserving credential management. However, existing credential systems often depend on centralized issuers, lack efficient aggregation mechanisms, or fail to ensure unlinkability across authentication sessions. To address these challenges, we propose DISC (Decentralized Identity System with Self-Sovereign Credential Aggregation), a novel credential system that enables multi-authority credential issuance, user-controlled credential aggregation, and unlinkable authentication. DISC allows users to aggregate credentials from multiple issuers while maintaining constant-size authentication tokens and supporting batch verification for …

One-Step Purification Of A Bioactive Pak1-Derived Peptide, Djamali Muhoza, Emily P. Esquivel, Stacy R. Hunter, Pateince S. Okoto, Thallapuranam K.S. Kumar, Paul D. Adams

Chemistry & Biochemistry Faculty Publications and Presentations

The serine/threonine kinase PAK1 serves as a mediator of cytoskeletal reorganization and cancer-related signaling downstream of the small GTPases. Due to the challenges in purifying PAK1 complexes, a 46-residue peptide from PAK1, is widely used to study PAK1-Cdc42 signaling. Traditionally, this purification involved multi-step chromatography of recombinant GST-PBD46 complexes, yielding approximately 1 mg per 1.5 L culture. In this study, a 30 min heat treatment step after thrombin cleavage was used to precipitate GST while leaving pure PBD46 in solution. This step eliminated the need for further affinity and size-exclusion chromatography steps. This improved protocol produces proteins with a 6.5-fold …

Removed: When Taxi Drivers Meet Dynamic Pricing: A Lesson From Singapore's Justgrab Program, Shih-Fen Cheng, Wen-Tai Hsu, Jing Li

Research Collection School Of Economics

This paper studies how dynamic pricing influences taxi drivers’ behaviors using a unique event, the inception of the JustGrab program in Singapore in 2017, which introduces dynamic pricing to some, but not all, taxi drivers. This is the first time in history that traditional taxi drivers have access to dynamic pricing. Using data covering the universe of taxi trips before and after the inception of JustGrab, we find that there is spatial reallocation that directs more taxi drivers to the previously less-served areas, that there is also a temporal reallocation that directs more taxi drivers to rush hours, as well …

Efficient Function Orchestration For Large Language Models, Xiaoxia Liu, Peng Di, Cong Li, Jun Sun, Jingyi Wang

Research Collection School Of Computing and Information Systems

Function calling is a fundamental capability of today's large language models, but sequential function calling posed efficiency problems. Recent studies have proposed to request function calls with parallelism support in order to alleviate this issue. However, they either delegate the concurrent function calls to users for execution which are conversely executed sequentially, or overlook the relations among various function calls, rending limited efficiency. This paper introduces LLMOrch, an advanced framework for automated, parallel function calling in large language models. The key principle behind LLMOrch is to identify an available processor to execute a function call while preventing any single processor …

Quantum Chebyshev Transform-Based Graph Neural Networks For Financial Fraud Detection, Minrui Xu, Bingyan Guan, Bethel Hui Ting Loke, Paul R. Griffin

Research Collection School Of Computing and Information Systems

Financial fraud detection is a critical challenge requiring accurate identification of anomalous patterns in complex transaction networks. Graph Neural Networks (GNNs) have emerged as powerful tools for fraud detection by capturing relational structures among entities. Meanwhile, quantum computing offers new possibilities to enhance machine learning through high-dimensional Hilbert spaces and parallelism. In this paper, we propose a hybrid classical-quantum model called QCTGNN (Quantum Chebyshev Transform-based Graph Neural Network) for financial fraud detection. The QCTGNN integrates a classical graph neural network component based on Simplified Graph Convolutions (SGConv) with a quantum component that performs a Chebyshev polynomial-based transform via variational quantum …

Lagrangian Motion Fields For Long-Term Motion Generation, Yifei Yang, Zikai Huang, Chenshu Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

Long-term motion generation is a challenging task that requires producing coherent and realistic sequences over extended durations. Current methods primarily rely on framewise motion representations, which capture only static spatial details and overlook temporal dynamics. This approach leads to significant redundancy across the temporal dimension, complicating the generation of effective long-term motion. To overcome these limitations, we introduce the novel concept of Lagrangian Motion Fields, specifically designed for long-term motion generation. By treating each joint as a Lagrangian particle with uniform velocity over short intervals, our approach condenses motion representations into a series of "supermotions" (analogous to superpixels). This method …

Prompt Tuning Without Labeled Samples For Zero-Shot Node Classification In Text-Attributed Graphs, Sethupathy Parameswaran, Suresh Sundaram, Yuan Fang

Research Collection School Of Computing and Information Systems

Node classification is a fundamental problem in information retrieval with many real-world applications, such as community detection in social networks, grouping articles published online and product categorization in e-commerce. Zero-shot node classification in text-attributed graphs (TAGs) presents a significant challenge, particularly due to the absence of labeled data. In this paper, we propose a novel Zero-shot Prompt Tuning (ZPT) framework to address this problem by leveraging a Universal Bimodal Conditional Generator (UBCG). Our approach begins with pre-training a graph-language model to capture both the graph structure and the associated textual descriptions of each node. Following this, a conditional generative model …

G-Trac: Graph-Textual Representations Alignment For Cold-Start Recommendations, Li Yang Chang, Yuan Fang, Ming Feng Tsai, Chuan Ju Wang

Research Collection School Of Computing and Information Systems

The cold-start problem remains a significant challenge in recommendation systems, particularly for new users or unseen items with little to no historical data. Existing methods, including graph neural networks, often struggle in such scenarios. Inspired by the success of transformer models in natural language processing, we propose G-TRAC (Graph-Textual Representations Alignment for Cold-start Recommendations), a novel approach that integrates transformer-based textual modeling with graph neural networks. By effectively leveraging both textual and structural information, G-TRAC addresses cold-start challenges more effectively. Extensive experiments demonstrate its ability to enhance recommendation quality and generalize well across diverse scenarios.

Mm-Attackg: A Multimodal Approach To Attack Graph Construction With Large Language Models, Yongheng Zhang, Xinyun Zhao, Yunshan Ma, Haokai Ma, Yingxiao Guan, Guozheng Yang, Yuliang Lu, Xiang Wang

Research Collection School Of Computing and Information Systems

Cyber Threat Intelligence (CTI) parsing aims to extract key threat information from massive data, transform it into actionable intelligence, enhance threat detection and defense efficiency, including attack graph construction, intelligence fusion, and indicator extraction. Among these research topics, Attack Graph Construction (AGC) is essential for visualizing and understanding the potential attack paths of threat events from CTI reports. Existing approaches primarily construct the attack graphs purely from the textual data to reveal the logical threat relationships between entities within the attack behavioral sequence. However, they typically overlook the specific threat information inherent in visual modalities, which preserves key threat details …

The Gains Do Not Make Up For The Losses: A Comprehensive Evaluation For Safety Alignment Of Large Language Models Via Machine Unlearning, Weixiang Zhao, Yulin Hu, Xingyu Sui, Zhuojun Li, Yang Deng, Yanyan Zhao, Bing Qin, Wanxiang Che

Research Collection School Of Computing and Information Systems

Machine Unlearning (MU) has emerged as a promising technique for aligning large language models (LLMs) with safety requirements to steer them forgetting specific harmful contents. Despite the significant progress in previous studies, we argue that the current evaluation criteria, which solely focus on safety evaluation, are actually impractical and biased, leading to concerns about the true effectiveness of MU techniques. To address this, we propose to comprehensively evaluate LLMs after MU from three aspects: safety, over-safety, and general utility. Specifically, a novel benchmark MuBench with 18 related datasets is first constructed, where the safety is measured with both vanilla harmful …

The Case For Ai Authorship In Copyright Law, Cheng Lim Saw, Duncan Lim

Research Collection Yong Pung How School Of Law

Today, with generative AI, literary and artistic works can be created almost effortlessly. There is at present intense debate as to whether works generated by AI – broadly categorised as “AI-assisted” and “AI-generated” works – ought to attract copyright protection. AI-assisted works are those that involve some degree of human intervention. Where AI-generated works are concerned, however, such works are created autonomously by the AI itself with minimal (de minimis) input from an identifiable human being. Presently, it is generally accepted that AI-generated works do not attract copyright protection for want of a human author. This article examines whether it …

New Fast Polynomial Root-Finders, Soo Go

Dissertations, Theses, and Capstone Projects

Univariate polynomial root-finding has been studied for four millennia and very intensively in the last decades. Our {\em black box root-finder} involves no coefficients and works for a black box polynomial, defined by an oracle (that is, black box subroutine) for its evaluation. Such root-finders have various benefits, e.g., are particularly efficient where a polynomial can be evaluated fast, say, is a sum of a small number of shifted monomials (x-c)^a.

Our root-finder approximates all d complex zeros of a dth degree polynomial p(x) (aka roots of equation p(x)=0) by using Las Vegas expected number of bit-operations within a factor …

Development Of Novel Anti-Cancer Colchicine Analogs: Synthesis And Configurational Studies, Orugbani S. Eli

Dissertations, Theses, and Capstone Projects

Colchicine, a naturally occurring alkaloid, has long been known as a potent therapeutic agent. Despite its efficacy treating gout and other inflammatory disorders, its severe toxicity, limited selectivity, and poor pharmacological profile have restricted its broader clinical application. Reported advantages of colchicine-site ligands as vascular-disrupting agents, including reduced susceptibility to multidrug resistance, have revived interest in the colchicine site on tubulin as a validated therapeutic target for cancer. This dissertation focuses on the development of new colchicine analogs, detailing the synthetic method to functionalized AC-ring derivatives, as well as the evaluation of their configurational stability and biological activity.

In Chapter …

Typeface: Machine-Viewing Gentrification On Storefront Imagery In Bedford-Stuyvesant, Brooklyn, Alexander Mcquilkin

Dissertations, Theses, and Capstone Projects

Gentrification—broadly, the replacement of a less powerful group by a more powerful one in an urban context—is oft-discussed in the popular press, but its definition is much-debated in the urban planning literature. Furthermore, academic treatments of displacement understandably focus on measurable yet fairly abstract indicators like changes in rent or income, whereas neighborhood change is often registered by residents on the ground using visual, but difficult-to-quantify markers like retail turnover. This project uses image recognition technology on a set of storefront photos to index the visual streetscape of a neighborhood, as well as to track changes to that portrait over …

Courts Of New York: A Visual Atlas Of The City’S Public Basketball Spaces, Nathaniel Rattner

Dissertations, Theses, and Capstone Projects

Basketball courts in New York City are recreation facilities, community anchors and part of the city’s cultural image. In the basketball capital of the world, New Yorkers are rarely more than a few blocks away from a court. The visual diversity of these courts, however, is not widely documented in systematic ways.

This project makes that diversity visible to the public, combining open data, aerial imagery and computational analysis to document this important public space across the five boroughs. It is a narrative story and digital atlas of New York City’s public basketball courts, using surface color as a way …

Design Of Lithium-Based Battery Electrolyte Compositions For Extreme Operating Conditions Using Alternative Solvents, Co-Solvents And Additives, Michael J. Keating

Dissertations, Theses, and Capstone Projects

Lithium-ion battery utilization is widespread due to relatively high capacity and long cycle life. Advanced technologies have specific demands of their energy storage devices that traditional Li-ion batteries are unable to meet. Lithium-ion batteries utilize a graphite anode which has a limited theoretical capacity. Traditional lithium-ion batteries also utilize flammable solvents in their electrolyte mixtures. Due to the flammable electrolyte, lithium-ion batteries are not considered practical for large scale applications. Additionally, the lithium-ion battery has a narrow optimal operating temperature window. The temperature limitation of lithium-ion batteries leads to issues for many applications such as operating in extreme temperature environments, …

Monosaccharide Binding To Synthetic Carbohydrate Receptor Microarrays, Milan A. Shlain

Dissertations, Theses, and Capstone Projects

Chapter 1: A glycan detection platform comprised of synthetic carbohydrate receptors (SCRs) immobilized onto polymer brushes was prepared. SCR043, an alkene-containing SCR, was incorporated into grafted-from polymer brushes using hypersurface photolithography, resulting in microarrays of SCR043-functionalized polymer brushes, where brush height (h) and SCR grafting density (Γ) is controlled precisely at each feature in the array. The influence of h and Γ on the binding to five fluorescently labelled monosaccharides – α-glucose (α-Gluc-FL), α-galactose (α-Gal-FL), α-mannose (α-Man-FL), β-glucose (β-Gluc-FL), and β-galactose (β-Gal-FL) – in aqueous buffer …

6d Rigid Object Pose Estimation Using Deep Learning, Zhujun Li

Dissertations, Theses, and Capstone Projects

6D object pose estimation is the task of determining an object’s 3D rotation and translation with respect to a camera, and plays a critical role in applications such as robotic manipulation, autonomous navigation, and augmented reality. While recent advances in deep learning have substantially improved performance, many existing methods still face limitations in learning robust and generalizable representations. Factors such as variations in object appearance, occlusion, sensor noise, and domain shifts can degrade model accuracy, highlighting the need for more effective representation learning strategies that capture rich geometric and semantic cues for reliable pose estimation across diverse conditions.

This dissertation …

Computational Characterization Of A Recently Identified Disinfection Byproduct In Drinking Water: The Chloronitramide Anion And Its Monohydrate Complex, Thufail M. Ismail, Max R. Tucker, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

The chloronitramide anion (ClNNO₂⁻) was recently identified as disinfection byproduct in drinking water, and various quantum chemistry methods (CCSD(T), MP2, B3LYP, ωB97XD, and M06-2X) are employed in this study to characterize this negatively charged species and its monohydrate complex. Both vertical and adiabatic quantities indicate the excess electron is bound by 3–4 eV. Four ClNNO₂⁻ monohydrate minima were identified, each exhibiting double ionic hydrogen bonding. The computed ClNNO₂⁻⋯H₂O interaction approaches 15 kcal/mol, and it induces pronounced vibrational frequency shifts in both fragments. Natural bond orbital analysis shows a redistribution of …

Leveraging Molecular Mechanisms Of Desorption To Enhance Pfas Bioavailability In Contaminated Soils, Husam Kafeenah, Margaret D. Taiwo, Patrica Ivy Agorsor, Michael O. Eze

Chemistry Faculty Research & Creative Works

Per- and polyfluoroalkyl substances (PFAS) are known for their strong binding properties to soil matrices owing to their amphiphilic properties. While most studies focus on the search for novel PFAS bio degraders, our knowledge of sustainable biomolecules that could drive PFAS desorption and make them more bioavailable is limited. This study investigated the effectiveness of rhamnolipids and organic acids in desorbing PFAS compounds from contaminated soil. Rhamnolipids (25 mg/L) significantly enhanced the release of PFAS compounds from soil, achieving up to 90 % desorption. Acetic acid provided 60–90 % desorption efficiency for most of the PFAS studied, except for PFDA …

Electric Dipole Forbidden, Quadrupole Allowed Transitions In The Pure Rotational Spectrum Of Cyclopropylchloromethyldifluorosilane, Alexander R. Davies, Abanob G. Hanna, Alma Lutas, Gamil A. Guirgis, S. A. Cooke, Garry S. Grubbs

Chemistry Faculty Research & Creative Works

In a recent publication, some electric dipole forbidden, quadrupole allowed ΔJ = +2 and x-type transitions were observed in the chirped-pulse Fourier transform microwave spectrum of two conformations of cyclopropylchloromethyldifluorosilane. Many of these transitions arise from a handful of mixed states and mechanisms are proposed through which these transitions become weakly allowed. Observations of electric dipole forbidden, quadrupole allowed transitions in rotational spectra are unusual for molecules which contain a chlorine nucleus owing to the small quadrupole moment of ³⁵Cl and ³⁷Cl; thus, we believe we are the first to observe x-type transitions arising from perturbations caused by …

Nightmare In The Library, Charles A. Coppin

Journal of Humanistic Mathematics

Students of real analysis and calculus find that the completeness property of the real numbers is difficult to understand, especially, its importance. The word numbers denote real numbers throughout this piece. After all, the real numbers are not any less imaginary than the so-called imaginary numbers. Although, sometimes, it does gain some mention in calculus courses, its presence as a topic is a mere will-o’-the-wisp of bygone days when teachers would often reach deep into the big ideas of calculus as a mainstay of their courses. For the sake of cultural literacy and the development of mathematical maturity, we believe …

The Tool/Weapon Duality Of Mathematics, Alexandre Borovik

Journal of Humanistic Mathematics

This paper outlines the principal moral and ethical issues of mathematics and existential choices a mathematician may face in his professional life. My text is a manifesto; it is a list of declarations rather than a systematic development of the theme. Indeed each section could be expanded into a paper on its own. I hope to write fairly soon a more detailed exposition.

Sumthin: A Context-Dependent African American Vernacular English Word For Variables, Mark Apedo

Journal of Humanistic Mathematics

If mathematics is a language, then African American Vernacular English (AAVE) could hold the key to a fascinating understanding of the evolution of algebra from human speech in North America. The use of the pronoun something (sumthin) to depict an unknown amount of money that varies implies that algebra developed as a logical necessity in human communication. Exploring this phenomenon and leveraging it to demonstrate the concept of algebra could enhance the comprehension of the subject among speakers of AAVE.

The Math Teaching Atlas: Trails, Anchors, And Compass In Action, Ivan Z. Feng

Journal of Humanistic Mathematics

This paper advocates a shift grounded in mathematical reasoning: teach and write math through explicit routeways rather than narratives, anchor new ideas to familiar concepts on a roadmap, and use motivation and concrete examples as a compass and simulation for discovery.

Reminiscences Of My Past Life As A High School Math Teacher, Wayne Nirode

Journal of Humanistic Mathematics

In this article, I reflect on my twenty years as a high school math teacher. I describe four distinct phases of my career in five-year increments. I aim to make public both what makes teaching high school students rewarding and what makes it difficult. Also, my writing illuminates how indelible the first five years were to my development as a teacher. I hope that this brief memoir helps early-career teachers see past the tumultuous beginnings while also inspiring veteran teachers to reflect on their own careers.

Why Read The Classics (Of Mathematical Proofs)?, Cosimo Perini Brogi

Journal of Humanistic Mathematics

Inspired by Italo Calvino’s (almost) homonymous writing, this short essay suggests a formal perspective to complement the typical categorisation of classical results in mathematics on aesthetic bases. The traditional proof that √2 is not a rational number provides a simple example of proof mining. When studied through the tools of logic, that proof has also led to designing new systems for formal proving based on cyclic proofs. This example thus supports the central thesis of this essay that reading the classics of mathematical proofs enables us to acquire a taste for mathematical beauty and can open new directions in mathematics …

A Mathematician Expresses Grief, Richard Delaware

Journal of Humanistic Mathematics

A famous Scottish mathematician of the eighteenth century shares a tragic sorrow.