Digital Commons Network^™

Sage: Spatially Aware Gene Selection And Dual-View Embedding Fusion For Domain Identification In Spatial Transcriptomics, Yi He, Yunpei Xu, Liqing Ding, Hong-Dong Li, Yaohang Li, Shaokai Wang

Computer Science Faculty Publications

Despite enabling high-resolution mapping of gene expression within tissues, spatial transcriptomics (ST) still faces challenges in accurately segmenting spatial domains due to complex tissue architecture and limitations of current methods. Most approaches rely on local spatial priors, lack gene-level interpretability, and fall short in capturing structure-discriminative genes or long-range functional relationships, limiting their ability to resolve biologically meaningful architectures. We present Spatially Aware Gene selection and dual-view Embedding fusion (SAGE), a unified and reproducible framework for domain identification in spatial transcriptomics that combines topic-driven gene selection with dual-view embedding fusion to address these gaps. SAGE integrates non-negative matrix factorization (NMF)-based …

Application Paths Of Semantic Modeling In Financial Fraud Detection And Risk Identification, Victor P. Gauthier, Daniel S. Wu

Computer Science Faculty Publications

Financial fraud and risk pose significant threats to economic stability and individual well-being. Traditional detection methods often struggle to keep pace with increasingly sophisticated fraudulent schemes. Semantic modeling, which focuses on understanding the meaning and relationships within data, offers a promising avenue for enhancing fraud detection and risk identification. This review paper explores the application paths of semantic modeling in this domain. We begin with a historical overview of fraud detection techniques, highlighting the limitations of traditional approaches. Subsequently, we delve into core themes, including knowledge graph-based fraud detection and semantic rule-based inference for risk assessment. We then compare and …

Integration Of Hybrid Quantum-Neuromorphic Ai With Cloud, Edge, And High-Performance Computing Environments, Arun B. Prasad, Ajay Prasad, Dineshkumar Rajendran, Anurag Tiwari, T. Akilan, Islombek Khushvaktov

Computer Science Faculty Publications

The convergence of quantum computing, neuromorphic learning, and distributed cloud infrastructures has occurred very rapidly, and intelligent systems are now providing new opportunities, but the challenge of instability, complexity of orchestration, and noise sensitivity remains in the way of practical integration. The proposed work is based on a hybrid quantum and neuromorphic architecture, which is the integration of event-based neuromorphic adaptation and quantum-assisted global optimization, orchestrated by cloud-HPC. The architecture presents the thermodynamically regularized learning and resourceful task scheduling to the probabilistic search and the continuous local adaptation. Experimental evaluation across financial modeling, medical imaging, and physical system prediction shows …

Design And Analysis Of Modern Quantum Neural Network Architectures For Intelligent Systems, Lakshmi Chandrakanth Kasireddy, Prabhakara Rao Kapula, Dineshkumar Rajendran, Neha Bharani, Srikanth Pulipeti, Islombek Khushvaktov

Computer Science Faculty Publications

Quantum neural networks (QNNs) offer a principled pathway for integrating quantum computation with machine learning through superposition- and entanglement-based representations. This chapter proposes an architecture-aware design and evaluation framework for modern QNNs, emphasizing robustness and system feasibility alongside predictive performance. Multiple architectures variational QNNs, quantum convolutional neural networks, tensor-network hybrids, and fully quantum models—are assessed under a unified protocol. Experimental analysis shows that the proposed architecture-search–guided QNN achieves 91.8% classification accuracy and an F1-score of 0.914, outperforming fixed-template variational QNNs by approximately 5.6 percentage points. Under depolarizing noise with probability p = 0.10, the proposed model retains 85.3% accuracy, whereas …

Cognitive Prosthetic: An Ai-Enabled Multimodal System For Episodic Recall In Knowledge Work, Lawrence Obiuwevwi, Krzystof J. Rechowicz, Vikas Ashok, Sachin Shetty, Sampath Jayarathna

Computer Science Faculty Publications

Modern knowledge workplaces increasingly strain human episodic memory as individuals navigate fragmented attention, overlapping meetings, and multimodal information streams. Existing workplace tools provide partial support through note-taking or analytics but rarely integrate cognitive, physiological, and attentional context into retrievable memory representations. This paper presents the Cognitive Prosthetic Multimodal System (CPMS)—an AI-enabled proof-of-concept designed to support episodic recall in knowledge work through structured episodic capture and natural language retrieval. CPMS synchronizes speech transcripts, physiological signals, and gaze behavior into temporally aligned, JSON-based episodic records processed locally for privacy. Beyond data logging, the system includes a web-based retrieval interface that allows users …

Contextual Scaffolding And Self-Efficacy: Supporting Computer Skill Development Among Blind Learners In India, Akshay Kolgar Nayak, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Inclusive computer literacy education efforts, broadening the participation of blind or visually impaired (BVI) individuals, have gained traction in recent years. Existing literature investigating these efforts primarily draws evidence from affluent Global North contexts, where accessibility resources and legal frameworks are relatively more mature. Little is known about the in-situ teaching and learning challenges faced by trainers and BVI students, respectively, in resource-constrained, multicultural Global South countries like India. To address this knowledge gap, we conducted a four-month contextual inquiry at two computer training centers catering to 94 BVI students in India. We notably observed a rigid, experience-driven training environment …

Modeling Joint Visual Attention In Naturalistic Dyadic Interactions, Kuushini Thennakoon, Yasasi Abeysinghe, Bhanuka Mahanama, Vikas Ashok, Sampath Jayarathna

Computer Science Faculty Publications

Joint visual attention (JVA) provides important insight into how individuals coordinate attention during social interaction. Egocentric eye tracking enables the study of JVA in natural, multi-user settings. This work presents a multi-stage framework to identify and analyze JVA using egocentric video and gaze data. The approach consists of three steps: spatiotemporal tube-based visual similarity, gaze-guided object detection, and attention pattern analysis using the ambient–focal coefficient K. Results show that object-focused collaborative activities exhibit high JVA, with object detection capturing higher joint attention than visual similarity, whereas conversation-based or independent activities show lower and more fragmented joint attention. Analysis of K …

Roles Of Cytokines In Modulating Trypanosoma Brucei Rhodesiense Infection Outcomes In Vervet Monkeys, Clarah Jebet, John Kibuthu Thuita, Daniel Masiga, Benedict Owino Orindi, John Oidho, Mark C. Field, Enock Matovu, Vincent Owino Adung’A

All Peer-Reviewed Publications

Introduction:

Human African trypanosomiasis (HAT), caused by Trypanosoma brucei rhodesiense, is categorized as acute due to rapid disease progression but presents varying clinical outcomes. Although the mechanisms underpinning differential clinical progression are poorly understood, both host and parasite factors are implicated. Therefore, we sought to elucidate roles of primate host factors in mediating varying T. b. rhodesiense infection outcomes.

Methods:

Here, we assessed the roles of selected host cytokines in disease progression using a tsetse-mediated infection in a non-human primate (NHP) vervet monkey model that closely mimics HAT and natural infection. We quantified eight cytokines, including TNF-α, IFN-γ, IL-10, IL-6, …

Assessment Of Mechanical Performance And Quality Assurance In Fabricated Aa6061-T6, Anesti Nasi, Kledi Ushe, Klodian Dhoska, Anis Sulejmani, Odhisea Koça, Panagiotis Kyratsis, Aleksandra Petrovic

Babylonian Journal of Mechanical Engineering

This paper focuses on integrated methodology for the experimental mechanical properties of produced AA6061 aluminum alloy, coupled for a rigorous quality assurance framework to validate material reliability for structural applications. The approach combines microstructural analysis, tensile testing analysis, and systematic measurement uncertainty quantification, all performed through the relevant international standards. To ensure statistical reliability, the overall standard uncertainty was computed utilizing the propagation law of uncertainty for k = 2 with a confidence level of roughly 95%. The experimental results yielded a tensile strength of309.4±4.0N/mm2, showing excellent repeatability with a lower relative uncertainty that correspond to 1.3%. These values not …

Reinforce Trustworthiness In Multimodal Emotional Support System, Huy M. Le, Dat Tien Nguyen, Ngan T. T. Vo, Tuan D. Q. Nguyen, Nguyen Le Binh, Duy Minh Ho Nguyen, Daniel Sonntag, Lizi Liao, Binh T. Nguyen

Research Collection School Of Computing and Information Systems

In today's world, emotional support is increasingly essential, yet it remains challenging for both those seeking help and those offering it. Multimodal approaches to emotional support show great promise by integrating diverse data sources to provide empathetic, contextually relevant responses, fostering more effective interactions. However, current methods have notable limitations, often relying solely on text or converting other data types into text, or providing emotion recognition only, thus overlooking the full potential of multimodal inputs. Moreover, many studies prioritize response generation without accurately identifying critical emotional support elements or ensuring the reliability of outputs. To overcome these issues, we introduce …

Generalized Visual Relation Detection With Diffusion Models, Kaifeng Gao, Siqi Chen, Hanwang Zhang, Jun Xiao, Yueting Zhuang, Qianru Sun

Research Collection School Of Computing and Information Systems

Visual relation detection (VRD) aims to identify relationships (or interactions) between object pairs in an image. Although recent VRD models have achieved impressive performance, they are all restricted to pre-defined relation categories, while failing to consider the semantic ambiguity characteristic of visual relations. Unlike objects, the appearance of visual relations is always subtle and can be described by multiple predicate words from different perspectives, e.g., “ride” can be depicted as “race” and “sit on”, from the sports and spatial position views, respectively. To this end, we propose to model visual relations as continuous embeddings, and design diffusion models to achieve …

Paid Search Marketing Vs. Search Engine Optimization: Analytical Models Of Search Marketing Based On Search Engine Quality, Kai Li, Chunyang Shen, Mei Lin, Zhangxi Lin

Research Collection School Of Computing and Information Systems

As search engines are leading revenue growth in online marketing, search marketing has become a popular area of academic research. Although search engine advertising has interested researchers for decades and much has been learned, one thing that puzzles scholars is why search engine optimization companies are tolerated rather than excluded from the market, even though they capture a significant share of the advertising market. In this paper, we shed light on this phenomenon and establish an analytical model based on organic search quality. Through analysis of the model, we were able to draw several intriguing conclusions. First, there is no …

Design Principles For Customer-Engaging Digital Service Systems: An Action Research Study, Keng Leng Siau, Xiaofeng Chen, Xin Tan

Research Collection School Of Computing and Information Systems

Digital services represent a business approach employed by organizations to operate in the digital environment. However, systematic development guidelines for developing quality digital service systems are lacking in the literature. The authors identified four general challenges for developing and implementing customer-engaging digital service systems (CEDSS). By employing the method of canonical action research in a digital service system project, they derived 10 design principles for developing high-quality CEDSS. They empirically evaluated the design principles in the development project and through follow-up focus group sessions. The design principles provide applicable and actionable guidelines for the development of CEDSS.

Food Recognition With Visual Language Models: Search Re-Ranking Or Retrieval-Augmented Generation?, Kian Yu Gan, Phuong Anh Nguyen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Despite the rapid advances in Visual Language Models (VLMs), these models struggle to recognize culture-specific food items. While VLMs are effective in recognizing popular cultural dishes, their performance is suboptimal for dishes that are unique but not widely known internationally. Specifically, VLMs often generate either generic labels or hallucinated names for dishes that are localized to a particular culture. As a result, retrieval-augmented generation (RAG), which retrieves relevant recipes as references for VLMs, emerges as a promising approach. Nevertheless, recipe retrieval, which is itself imperfect, could mislead VLMs into generating inaccurate or culturally inappropriate dish names. This paper presents a …

Airaclex: Automated Detection Of Price Oracle Manipulations Via Llm-Driven Knowledge Mining And Prompt Generation, Bo Gao, Yuan Wang, Qingsong Wei, Yong Liu, Rick Siow Mong Goh, David Lo

Research Collection School Of Computing and Information Systems

Decentralized finance (DeFi) applications depend on accurate price oracles to ensure secure and fair transactions. However, poorly integrated oracles remain susceptible to manipulation, enabling attackers to exploit smart contract logic for unfair asset valuation and financial gain. While many such vulnerabilities are only detected after deployment, smart contracts are typically immutable once deployed, making post-hoc fixes costly or infeasible. This highlights the critical need for detecting oracle manipulation risks before deployment. In this paper, we propose AiRacleX, a novel LLM-driven framework that enables pre-deployment detection of price oracle manipulation vulnerabilities by leveraging the complementary strengths of multiple large language models …

Between ‘Technology Futures’: How Standards Are Transforming Digital Trade, Craig Atkinson

Centre for Digital Law

Digital trade relies on technical standards. As information technologies advance, international digital standards make the technologies used in trade – or ‘tradetech’ – more interoperable, scalable, and secure.

A wide range of tradetech use cases depend on digital standards, including those for document formats, electronic signatures, digital identity, and cybersecurity. They also encompass system specifications for cross-border payments, electronic transferable records (ETRs), transportation/logistics, trade facilitation, and financial compliance.

Most digital standards are voluntary and are produced by international Standards Development Organisations (SDOs) alongside a growing number of industry-led consortia.

Screening Anticancer Activity By Brine Shrimp Lethality Test Of Extracts Of Annona Stenophylla (Engl. & Diels), Strophanthus Petersianus (Klotzsch) And Synadenium Glaucescens (Pax), Roberto Luis Nhamussua, Faith Philemone Mabiki Mabiki, Alinanuswe Joel Mwakalesi, Lyndy Joy Mcgaw

All Rsif Scholars' Publications

Cancer continues to be one of the main public health challenges, driving the search for new compounds with therapeutic potential. Medicinal plants represent a valuable promising source of bioactive metabolites, and the Brine Shrimp Lethality Test has been widely used as a preliminary tool to assess the toxicity of natural extracts, providing clues to their possible anticancer activity. In this study, the cytotoxicity of the extracts of Annona stenophylla (Engl. & Diels), Strophanthus petersianus (Klotzsch), and Synadenium glaucescens (Pax) was investigated using the BSLT as a first step in screening for potential anticancer compounds. The plant materials were harvested in …

Metabolic Syndrome Beyond Diagnostic Criteria: Population-Scale Integrative Metabolomics Characterization, Marwa Talal

Theses and Dissertations

Background: Metabolic syndrome (MetS) is a complex cluster of interrelated metabolic abnormalities associated with elevated cardiometabolic risk. While diagnosis is based on well-established five clinical criteria, these may overlook early or atypical metabolic alterations. Large-scale metabolomic profiling offers an opportunity to identify biochemical signatures of MetS beyond diagnostic bias and to evaluate their relative importance across different presentations of the syndrome.

Methods: Data from 117,147 UK Biobank participants were analyzed in a cross-sectional design. High-throughput NMR quantified 75 circulating metabolites, for. Univariate analyses, MetS subtype stratification, and elastic net models with SHAP interpretation were applied to assess feature …

Study Of Bearing Capacity Testing And Soil Preparation Techniques In Lunar Highlands Simulant At Field Scale, Christi A. Lecaptain

Dissertations, Master's Theses and Master's Reports

Humanity seeks to return to the surface of the Moon with the advent of the Artemis missions. These endeavors plan to be the beginning of a new era as NASA and other space organizations seek to establish a lunar base. Ahead of any astronauts or mining infrastructure, the physical groundwork will need to be laid to support the arrival of rockets, boots, and rover wheels. As surfaces are prepared, they will need to be tested and verified to ensure the stability of any structures placed on top. Understanding the bearing capacity is vital to soil quality testing. A standard terrestrial …

Beyond Receptive Measures: Development And Validation Of The Spatial Grid Drawing Assessment (Sgda) As A Productive Measure Of Spatial Skill, Katrina L. Carlson

Dissertations, Master's Theses and Master's Reports

Spatial skills are vital in many STEM disciplines, starting at or prior to university training, and often extending throughout one’s career. The most widely used spatial ability measures (e.g., PSVT: R, MRT) rely on what I refer to as receptive skills: examining an object or design, mentally transforming it, and comparing it to given alternatives. But because work in many STEM disciplines also involves productive spatial skill such as drawing, I hypothesize that a productive measure of spatial skill may predict distinct aspects of spatial ability. This research investigates the relationship between traditional receptive Spatial Visualization (SV) assessments, such as …

Design And Validation Of A Low-Cost Wearable Electromyography (Emg) System For Monitoring Exercise-Induced Changes In Muscle Activity, Ingrid E. Halverson

Dissertations, Master's Theses and Master's Reports

Wearable technologies have expanded opportunities for monitoring athletic performance, but many existing systems remain costly and confined to laboratory or medical settings. This thesis presents the design, development, and evaluation of a low-cost, wearable EMG platform for monitoring neuromuscular activity during exercise. A wireless device incorporating a surface EMG sensor, an ESP32 microcontroller, and Wi-Fi transmission was developed to acquire muscle activation data. Signal processing techniques, including filtering, root-mean-square (RMS), mean frequency (MNF), and median frequency (MDF) analyses, were used to evaluate changes in muscle activation. Experimental testing demonstrated reliable wireless data acquisition and successful capture of physiological changes before …

Identifying Controls On The Biodegradation Of Dissolved Organic Matter To Inform Microbial Fuel Cell Applications, Lily N. O'Hagan

Dissertations, Master's Theses and Master's Reports

Microbial fuel cells (MFCs) harness dissolved organic matter (DOM) biodegradation to generate power. To evaluate effects of DOM source, nutrients (nitrate and phosphate), and oxygen on DOM biodegradation, we conducted 4-day DOM biodegradation experiments with water and sediments from the Chesapeake Bay. Compared to soil-derived DOM, algal-derived DOM composition changed more and nearly doubled carbon dioxide (CO₂) production, peak CO₂ rates, and carbon removal, indicating MFC site selection should target regions with algal-rich DOM. Aerobic conditions increased CO₂ production by ca. 16%, doubled peak CO₂ rates, and reached peak rates 1 hour faster than anaerobic …

Open Source Tools For Ecological Research, Alex P. Riebe

Dissertations, Master's Theses and Master's Reports

This thesis presents the development of an open source wireless sensor network for hibernacula manipulation with an emphasis on accessibility and reproducibility. It addresses the design of the electrical hardware, guidance on antennas and RF implementation, and design of an application-specific communication protocol, all with the explicit goal of enabling ecologists and other conservationists to be able to manufacture, deploy, operate, and maintain the system for their research. The resulting sensor network designed in this thesis is to control the temperature inside bat hibernacula during the winter to study the relationship between temperature and bat mortality rate due to White …

Slip Kinematics And Structural Analysis Of The Keweenaw Fault System From Lake Linden To Hancock, Michigan, Katherine M. Langfield

Dissertations, Master's Theses and Master's Reports

The Keweenaw fault is a crustal-scale fault spatially associated with Mesoproterozoic rocks of the Midcontinent Rift System. Along the fault, older Portage Lake Volcanics have been thrust southeastward over younger Jacobsville sandstone. Ideas on the fault’s origin, from oldest to most recent, include that it is: (1) a reverse fault, (2) a normal fault formed during midcontinent rifting that was reactivated and inverted to a reverse fault during the Grenville orogeny, and (3) a detached thrust fault system initiated during the Grenville orogeny.

This thesis is based on a U.S. Geological Survey EdMap grant to remap a portion of the …

Using Automotive Lidar To Reduce The Energy Consumption Of An Ego Autonomous Vehicle, Logan P. Schexnaydre

Dissertations, Master's Theses and Master's Reports

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model …

High-Performance Circuit Manufacturing And Testing Exercises, Benjamin S. Keppers

Dissertations, Master's Theses and Master's Reports

An advanced demonstrator Printed Circuit Board (PCB) has been designed and implemented providing a framework for advancing students’ knowledge in hands-on PCB design and manufacturing process through industry recognized test coupons, stack ups, and transmission lines. Students are guided through several key aspects of design and simulation relating to manufacturing and qualifications. Manufacturing allows students to refine process development and analyze performance data with respect to qualification tests specified by Global Electronics Association standards. Results are then used to build a stackup model, and complete a design activity for calculating expected test results for a series of controlled impedance electrical …

Valuing Life And Loss: Genre Analysis Of Insurance Claims Processing In Ghana, Cornelius Fuumaale Suom-Kogle

Dissertations, Master's Theses and Master's Reports

This thesis draws on theories from rhetorical genre studies (Spinuzzi’s genre ecology and Freadman’s uptake), biopolitics, and the social justice turn in Technical and Professional Communication to examine how decisions are made in the processing of insurance claims. I adopt a qualitative, interpretive approach to analyze one hundred and twelve (112) claims processing examples from Ghana’s insurance industry. The findings indicate that insurance claims processing is a complex communicative system in which institutional power is enacted, negotiated, and, at times, contested. The findings also reveal that insurer-authored genres frequently enact forms of oppression (exploitation, marginalization, and powerlessness) through technical language …

Antenna-Based Sensors For Dielectric Characterization Of Materials, Hilary Scott Nkimbeng Cho

Dissertations, Master's Theses and Master's Reports

This research introduces antenna-based sensors for dielectric characterization aimed at overcoming the limitations of conventional microwave sensors. Although traditional microwave sensors are widely used for their noncontact operation, high sensitivity, and ability to penetrate various materials, they often face challenges such as large size and high-power consumption. To address these issues, antenna-based sensors are explored for their compactness, ease of fabrication, and flexible design adaptability across diverse sensing applications. An in-depth analysis of multiple antenna sensor configurations is conducted, followed by the design and development of high-performance sensing structures. A saw-tooth slot antenna sensor is developed for highly sensitive liquid …

Targeted And Screening Based Approaches To Analyze Drm Transcriptional Repressor Complex Activity In Caenorhabditis Elegans, Emily Washeleski

Dissertations, Master's Theses and Master's Reports

The molecular machinery that control the eukaryotic cell cycle, specifically the processes that mediate the switch between cellular division or quiescence, are essential for cellular and organismal viability. However, how the same machinery integrates with developmental or differentiation programs is less well understood. In Caenorhabditis elegans, the 8-subunit DRM complex (for Dp, Rb and MuvB), whose subunits belong to the Synthetic Mulitivulva (SynMuv) B class genes, is a central regulator of the cell cycle but also prevents inappropriate cell fate specification. The conserved mammalian DREAM complex (for Dp, Rb, E2F, And MuvB) is best known as a transcriptional repressor …

Beyond Satisfaction: Developing A Data Storytelling Evaluation Protocol For Stem Equity Program Assessment, Karen Colbert

Dissertations, Master's Theses and Master's Reports

Higher education institutions routinely evaluate equity initiatives using measures of participation, engagement, and satisfaction. While these approaches provide useful information about program delivery, they offer limited insight into whether interventions change how participants understand institutional inequities. As a result, important dimensions of organizational learning and awareness often remain difficult to detect, particularly within STEM higher education environments where evaluation systems frequently emphasize measurable outputs over deeper indicators of change.

This dissertation examines how awareness-related outcomes can be identified, measured, and communicated within equity intervention contexts. Using a three-study design, the research first presents a systematic review of equity intervention evaluation …