Digital Commons Network^™

Quaternion Algebra And Neutrosophic Integers For Generating An Efficient Mathematical Encryption System, Majida H. Majeed, Mohammed Hassan Hamza, Abdullah Mhmood Jasim, Hassan Yassein

Neutrosophic Sets and Systems

No abstract provided.

Correlation Coefficient Under Rough Neutrosophic Set For Effectiveness Assessment Of Students' Mental Health Education In Higher Education Institutions, Shuang Cui

Neutrosophic Sets and Systems

No abstract provided.

M-Polar Diophantine Neutrosophic N-Soft Set For Digital Competencies And Traditional Skills: Toward Holistic Training For New Craftsmen, Kaixia Zhuo

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophic Sets And Systems, Vol. 91,2025, Florentin Smarandache, Mohamed Abdel-Basset, Maikel. Leyva Vazquez

Neutrosophic Sets and Systems

No abstract provided.

The Future Is Now: Empowering Society Through Ai Literacy, Jason S. Wrench, Sanae Elmoudden

Milne Open Textbooks

Artificial Intelligence (AI) is no longer a futuristic concept—it is the reality of the present. From the algorithms shaping our social media feeds to the generative tools transforming our workplaces, AI has permeated every aspect of modern life. The Future is Now moves beyond the hype to provide a comprehensive roadmap for understanding, navigating, and shaping this technological revolution.

Demystifying the Machine

This textbook serves as a user-friendly guide to the “black box” of AI. It breaks down complex technical concepts—from machine learning and neural networks to large language models—making them accessible to students across all disciplines. By establishing a …

Sopo: Text-To-Motion Generation Using Semi-Online Preference Optimization, Xiaofeng Tan, Hongsong Wang, Xin Geng, Pan Zhou

Research Collection School Of Computing and Information Systems

Text-to-motion generation is essential for advancing the creative industry but often presents challenges in producing consistent, realistic motions. To address this, we focus on fine-tuning text-to-motion models to consistently favor highquality, human-preferred motions—a critical yet largely unexplored problem. In this work, we theoretically investigate the DPO under both online and offline settings, and reveal their respective limitation: overfitting in offline DPO, and biased sampling in online DPO. Building on our theoretical insights, we introduce Semi-online Preference Optimization (SoPo), a DPO-based method for training text-to-motion models using “semi-online” data pair, consisting of unpreferred motion from online distribution and preferred motion in …

Uniteformer: Unifying Node And Edge Modalities In Transformers For Vehicle Routing Problem, Dian Meng, Zhiguang Cao, Jie Gao, Yaoxin Wu, Yaqing Hou

Research Collection School Of Computing and Information Systems

Neural solvers for the Vehicle Routing Problem (VRP) have typically relied on either node or edge inputs, limiting their flexibility and generalization in real-world scenarios. We propose UniteFormer, a unified neural solver that supports node-only, edge-only, and hybrid input types through a single model trained via joint edge-node modalities. UniteFormer introduces: (1) a mixed encoder that integrates graph convolutional networks and attention mechanisms to collaboratively process node and edge features, capturing cross-modal interactions between them; and (2) a parallel decoder enhanced with query mapping and a feed-forward layer for improved representation. The model is trained with REINFORCE by randomly sampling …

Learning Memory-Enhanced Improvement Heuristics For Flexible Job Shop Scheduling, Jiaqi Wang, Zhiguang Cao, Peng Zhao, Rui Cao, Yubin Xiao, Yuan Jiang, You Zhou

Research Collection School Of Computing and Information Systems

The rise of smart manufacturing under Industry 4.0 introduces mass customization and dynamic production, demanding more advanced and flexible scheduling techniques. The flexible job-shop scheduling problem (FJSP) has attracted significant attention due to its complex constraints and strong alignment with real-world production scenarios. Current deep reinforcement learning (DRL)-based approaches to FJSP predominantly employ constructive methods. While effective, they often fall short of reaching (near-)optimal solutions. In contrast, improvement-based methods iteratively explore the neighborhood of initial solutions and are more effective in approaching optimality. However, the flexible machine allocation in FJSP poses significant challenges to the application of this framework, including …

Instance-Level Video Depth In Groups Beyond Occlusions, Yuan Liang, Yang Zhou, Ziming Sun, Tianyi Xiang, Guiqing Li, Shengfeng He

Research Collection School Of Computing and Information Systems

Depth estimation in dynamic, multi-object scenes remains a major challenge, especially under severe occlusions. Existing monocular models, including foundation models, struggle with instance-wise depth consistency due to their reliance on global regression. We tackle this problem from two key aspects: data and methodology. First, we introduce the Group Instance Depth (GID) dataset, the first large-scale video depth dataset with instance-level annotations, featuring 101,500 frames from real-world activity scenes. GID bridges the gap between synthetic and real-world depth data by providing high-fidelity depth supervision for multi-object interactions. Second, we propose InstanceDepth, the first occlusion-aware depth estimation framework for multi-object environments. Our …

Robust Hallucination Detection In Llms Via Adaptive Token Selection, Mengjia Niu, Hamed Haddadi, Guansong Pang

Research Collection School Of Computing and Information Systems

Hallucinations in large language models (LLMs) pose significant safety concerns that impede their broader deployment. Recent research in hallucination detection has demonstrated that LLMs’ internal representations contain truthfulness hints, which can be harnessed for detector training. However, the performance of these detectors is heavily dependent on the internal representations of predetermined tokens, fluctuating considerably when working on free-form generations with varying lengths and sparse distributions of hallucinated entities. To address this, we propose HaMI, a novel approach that enables robust detection of hallucinations through adaptive selection and learning of critical tokens that are most indicative of hallucinations. We achieve this …

Sempo: Lightweight Foundation Models For Time Series Forecasting, Hui He, Kun Yi, Yuanchi Ma, Qi Zhang, Zhengdong Niu, Guansong Pang

Research Collection School Of Computing and Information Systems

The recent boom of large pre-trained models witnesses remarkable success in developing foundation models (FMs) for time series forecasting. Despite impressive performance across diverse downstream forecasting tasks, existing time series FMs possess massive network architectures and require substantial pre-training on large-scale datasets, which significantly hinders their deployment in resource-constrained environments. In response to this growing tension between versatility and affordability, we propose SEMPO, a novel lightweight foundation model that requires pretraining on relatively small-scale data, yet exhibits strong general time series forecasting. Concretely, SEMPO comprises two key modules: 1) energy-aware SpEctral decomposition module, that substantially improves the utilization of pre-training …

Towards Inclusive Digital Futures Of Cultural Heritage: Insights From A Critical Discourse Analysis Of Unesco Dialogues, Shiqing Huang, Keng Siau, Xiaoting Chen

Research Collection School Of Computing and Information Systems

Digital technologies are shaping many aspects of cultural heritage, but very little research has examined the implications of digital transformation. Drawing on concepts from Fairclough’s three-dimensional critical discourse analysis, this research examines the discourse using seven online dialogues (available on the UNESCO website) between 18 professionals who have different backgrounds and cultures to identify social practices related to the digital transformation of cultural heritage. We identify four digital transformation discourse types in professional dialogues: documentation, management, interpretation, and interaction. We also identify seven main groups: memory institutions including libraries, archives, and museums (LAMs), governments, international organizations, art and creative supporters, …

Benthic Infaunal Responses To Shoreline Restoration, Jessica Lauren Cline

Theses and Dissertations

In the age of increasing urban coastal sprawl, natural shorelines are being replaced by hard armoring structures, which result in the loss of valuable ecosystem services. Hybrid living shorelines, areas that include limited and less intensive armoring strategies paired with the integration of plants and other natural materials, present an opportunity to marry the need for more aggressive stabilization with the continued preservation of ecosystem functions and biological communities. This project uses benthic infauna to evaluate the success of a living shoreline installation in Palm Bay, Florida. The deployment features experimental treatments of breakwaters and red mangroves to explore how …

Comparative Assessment Of Lower Limb Neuromusculoskeletal Activation And Joint Kinematics In Normal And Impaired Gait, Jack Ryan Schule

Theses and Dissertations

This thesis evaluates whether accessible and affordable technologies can provide clinically significant, quantifiable gait analysis comparable to traditional marker-based motion capture systems. Modern high-end systems offer excellent accuracy but remain financially and logistically inaccessible to many clinicians and researchers. To address this gap, a framework was developed using markerless pose estimation using the model, MediaPipe, inertial measurement units (IMUs) processed through an Extended Kalman Filter (EKF), and surface electromyography (sEMG) to measure joint kinematics and neuromuscular activity during gait. An experiment was performed where data was collected from participants with both normal gait and pathologies including: Osgood–Schlatter disease, Plica Band …

Effect Of Capillary And Viscous Forces On Carbon Dioxide Desorption In Porous Adsorbent Layers, Caroline Isabel Mcclung

Theses and Dissertations

Temperature swing adsorption-based (TSA) carbon dioxide (CO₂) separation processes, which involve an alternating flow of gases and liquids in adsorbent-coated microchannels, have been shown to yield superior and environmentally friendly performance than the existing processes. This technique begins by sending the impure gas mixture through hydrophobic silicalite adsorbent-coated microchannels, which results in the adsorption of CO₂. Subsequently, hot water heat transfer fluid (HTF) flows through the same channels, displaces the purified gas stream, heats the adsorbent, desorbs the CO₂, and removes that desorbed CO₂ from the channel. This stage is followed by cooling …

Thermodynamic Evaluation Of The Thermal Methane Pyrolysis Process, Chinaecherem S. Okwuonu

Theses and Dissertations

Natural gas flaring is a persistent challenge which undermines global sustainability and decarbonization efforts as it leads to the waste of valuable energy resources alongside the release of harmful greenhouse gases into the environment. Even when natural gas is utilized through commonly adopted pathways, significant emission of carbon dioxide tends to be realized. Methane pyrolysis offers a promising route in which methane can be decomposed into solid carbon and hydrogen gas with no direct CO2 emissions. However, despite extensive studies of the methane pyrolysis process, a fundamental thermodynamic rationale of the process behavior remains insufficiently explored. This study 1) develops …

Employers’ Perceptions Of Workplace Readiness Skills, Tabitha S. Young, Natalie K. Ferand

Journal of Research in Technical Careers

Employability skills are continually changing, and the workforce provides the transparency needed for the success of business employment. Workplace readiness skills and human capital theory form the backbone for organizational success and sustainability. This study examined employers’ perceptions of workplace readiness skills at the expected proficiency level of an entry-level employee, the average level of skill for an entry-level employee, and the level of importance of the skill to their industry. The Virginia Workplace Readiness Skills have impacted employers and prepared students for the workplace. The results indicated that the workplace readiness skills mentioned in the literature align with the …

Reported Value Of Culturally Responsive Teaching Practices Of Virginia Agricultural Education Teachers, Natalie K. Ferand, Kendrick Spencer, Bradley Bowen

Journal of Research in Technical Careers

To address the increasing diversity in schools and the monolithic culture of teachers, researchers have called for pedagogies that reflect the diverse and pluralistic identities of students. While core academic areas have long adopted culturally relevant pedagogy, school-based agricultural education (SBAE) has lagged behind. This study aimed to determine the views of agricultural education teachers in Virginia on culturally responsive pedagogy dispositions and identify areas of professional development need. Teachers valued the differences among students and the communities in which their schools are located. However, results revealed a need for professional development in using the local community as a resource …

Online Experiential Learning In Career And Technical Education, Matthew Bornak

Journal of Research in Technical Careers

This scoping review investigates the integration of OEL into Career and Technical Education (CTE) programs. Using Arksey and O’Malley’s five-step scoping review framework, articles were identified through ERIC and Google Scholar and managed in Zotero. MAXQDA was used for coding, revealing thematic clusters related to modalities (synchronous, asynchronous, hybrid), technologies (LMS, AR/VR, simulation tools), and learner characteristics (nontraditional students, CTE-specific learning styles). The review highlights the conceptual anchors of Kolb’s Experiential Learning Theory, Carver et al.’s Experiential E-Learning Model, and Baasanjav’s online experiential design. Findings reveal that while OEL in CTE remains underexplored, it offers potential to increase accessibility, inclusivity, …

Extraction Of Cellulose From Paper Towels For Sustainable Bio-Based Polyurethane Adhesives, Yashkumar J. Patel

Electronic Theses & Dissertations

The increasing consumption of paper towels generates significant waste, necessitating sustainable recycling solutions. This study investigates the extraction of cellulose from waste paper towels and its application in bio-based polyurethane (PU) adhesives. The extraction process includes alkali treatment, bleaching, and acid hydrolysis to obtain recycled cellulose (rCL). The extracted cellulose is then used in PU synthesis alongside castor oil polyol (COP) and methylene diphenyl diisocyanate (MDI), with performance compared to industrial cellulose-based PU. The obtained rCL and synthesized PU adhesives have been characterized with FT-IR spectra for structural confirmation. In addition, the synthesized PU adhesives demonstrated improved mechanical and thermal …

Data-Driven Evaluation Of Sustainable Waste-To-Energy Pathways For Intelligent Urban Systems, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

The handling of municipal solid waste (MSW) in swiftly urbanizing Philippine cities poses intricate energy and governance challenges. In Baguio City, reliance on landfills has reached critical levels due to diminishing capacity, rising transport costs, and opposition to trash transfers by nearby LGUs. Although shaped by unique topographical and governance constraints, Baguio’s situation reflects issues faced by other rapidly growing Philippine cities; therefore, analyzing it offers insights for national MSW decision-making. This study applies a triple bottom line (TBL) framework to assess three management scenarios: (1) Status Quo, where all MSW is landfilled with no energy recovery; (2) Landfill with …

Engineering Risk And Indigenous Resilience Toward Intelligent Decision Support For Mining In Ancestral Lands, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

Mining within ancestral territories reveals an ongoing conflict between technical viability and Indigenous consent. This collaborative study, conducted by an engineering scholar and a policy researcher of Indigenous heritage in Benguet among the Ibaloi and Kankanaey peoples, investigates how risk transparency and policy alignment can bridge existing divides, while formulating principles applicable to other Indigenous mining contexts. The study provides an initial evaluation of the feasibility of a proposed large-scale mining operation within a risk-informed, data-driven governance framework. Three elements of engineering risk were assessed utilizing literature-derived and proxy parameters: (1) Land degradation is indicated by a Soil Productivity Index …

Comprehensive Drought Analysis: Machine Learning-Based Meterological Drought Forecasting And Pca-Driven Agricultural Drought Monitoring., Bishal Poudel

Theses

Drought is a long-term natural disaster that affects many aspects of human life from health, water supply to ecosystems and agriculture. Drought’s occurrence and intensity has increased in recent years because of global warming, which urges for proper and accurate monitoring and forecasting of drought. For better understanding of droughts, this study uses two approaches. In first part, the study uses the historical temperature and precipitation data from period of 1960 to 2021 as input features for three different machine learning models – Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest (RF). The research focuses on calculating …

Prediction Of Geometric Deviation In Additively Manufactured Tpms Lattice Structures Using Non-Destructive Evaluation And Conditional Generative Adversarial Networks, Prateek Neupane

Theses

Metal 3D printing has emerged as a widely used additive manufacturing method, finding applications across numerous industries and research areas. However, its application is often hindered by geometric inaccuracies and surface quality issues resulting from the complex interplay of laser power, melt pool behavior, and cooling characteristics. These inconsistencies have a significant impact on the design and functionality of printed parts, affecting structural integrity and dimensional accuracy. Thus, an effective data-driven approach is crucial to predict these deviations before manufacturing. This study proposes a methodology that incorporates Non-destructive evaluation techniques, like in-situ monitoring and X-ray CT scan, with Conditional Generative …

Visionglow: Evaluating Minimal-Disruption Smart-Home Control In Apple Vision Pro, Hongxiao Zheng

Dartmouth College Master’s Theses

Smart-home control in mixed-reality environments like Apple Vision Pro often relies on disruptive, application-based paradigms, such as using a smartphone or a windowed virtual interface. These methods create a “mode switch” that imposes cognitive load and pulls users from their primary tasks. We present VisionGlow, a minimal-disruption spatial interaction technique for Vision Pro. VisionGlow represents devices as spatially-anchored “orbs.” To control a device, the user looks at its orb and performs a pinch gesture, which invokes a compact, contextual control panel. We conducted a within-subjects study (N=18) comparing VisionGlow against two baselines: the standard Apple Home app on a smartphone …

Investigating The Efficiency Of Ingan P-N-P-N Homojunction Solar Cells, Moath Alhejji, Mohammad Alavijeh, Jacob Kupernik, Mirsaeid Sarollahi, Abbas Jammali, Seyed Taghavi, Reem Alhelais, Md Hel Uddin Maruf, Morgan Ware

Electrical Engineering and Computer Science Faculty Publications and Presentations

This research investigates the development of a novel p-n-p-n homostructure solar cell, through semiconductor simulations using the Nextnano software. InGaN was used as a model system in order to achieve a bandgap with optimized efficiency for a p-n homojunction solar cell. By increasing the uniform doping concentration from 1.5*10(16) cm(-3) to 1.5*10(17) cm(-3), the open circuit voltage (V-oc) increased while the short-circuit current density (J(sc)) decreased, as expected in simple p-n junctions. The p-n-p-n structure achieved a peak efficiency of 32.91% at a doping level of 6.5*10(16) cm(-3), a similar to 7% improvement over a conventional p-n junction's 25.31% efficiency …

Long-Term Sedimentation Rates And Patterns Of Alluvial Ridge Basins (Esteros) Of The Rio Grande Delta (Tx, United States Of America), Kynan Joseph Rutan

Theses and Dissertations

Little is known about the century-scale sedimentation rates and patterns of Alluvial Ridge basins within river deltas, especially in the Rio Grande Delta (RGD). To better constrain this, 22 cores were collected in the Bahia Grande Complex (BGC) and analyzed for grain size, organic content, age dates, and elemental composition.

Results show that grain size and sedimentation rates decrease from an artificial inlet to the basin interior, with elevated sedimentation in the south. Also, human activities, such as the construction of the Brownsville shipping channel in the 1930s, altered sedimentation dynamics in the basin by blocking natural inlets and leading …

The "Woundosome" Concept And Its Impact On Procedural Outcomes In Patients With Chronic Limb-Threatening Ischemia, Lorenzo Patrone, Edoardo Pasqui, Michael S Conte, Alik Farber, Roberto Ferraresi, Matthew Menard, Joseph L Mills, John Rundback, Peter Schneider, August Ysa, Kumar Abhishek, George L Adams, Naseer Ahmad, Irfan Ahmed, Vlad A Alexandrescu, Max Amor, David Alper, Martin Andrassy, Christopher Attinger, Andy Baadh, Hashem Barakat, Lukla Biasi, Theodosios Bisdas, Zagum Bhatti, Erwin Blessing, Marc P Bonaca, Stefano Bonvini, Michel Bosiers, Andrew W Bradbury, Robert Beasley, Christian-Alexander Behrendt, Marianne Brodmann, Gonzalo Cabral, Roberto Cancellieri, Andrea Casini, Venita Chandra, Emiliano Chisci, Omar Chohan, Edward T C Choke, Patrick F S Chong, Giacomo Clerici, Raphael Coscas, Mary Costantino, Luca Dalla Paola, Sabeen Dand, Robert S M Davies, Mario D'Oria, Athanasios Diamantopoulos, Sebastian Debus, Koen Deloose, Costantino Del Giudice, Gianmarco De Donato, Brian De Rubertis, Jean Paul De Vries, Nuno V Dias, Larry Diaz-Sandoval, Florian Dick, Konstantinos Donas, Anahita Dua, Fabrizio Fanelli, Stefano Fazzini, Mazin Foteh, Roberto Gandini, Mauro Gargiulo, Luca Garriboli, Elizabeth A Genovese, Edward Gifford, Yann Goueffic, Peter Goverde, Prem Chand Gupta, Robert Hinchliffe, Andrew Holden, Kim C Houlind, Dominic Pj Howard, Bella Huasen, Giacomo Isernia, Konstantinos Katsanos, Barry Katzen, Philippe Kolh, Igor Koncar, Grigorios Korosoglou, Prakash Krishnan, Thomas Kroencke, Miltiadis Krokidis, Arun Kumarasamy, Paul Hayes, Osamu Iida, Enrique Alejandre Lafont, Ralf Langhoff, Alexandre Lecis, Mark Lessne, Hady Lichaa, Michael Lichtenberg, Marta Lobato, Alice Lopes, Giorgio Loreni, Pierleone Lucatelli, Sreekumar Madassery, Lieven Maene, Marco Manzi, Martin Maresch, Jay Santhosh Mathews, James Mccaslin, Antonio Micari, Stefano Michelagnoli, Bruno Migliara, Robert Morgan, Luis Morelli, Daniele Morosetti, Nicolas Mouawad, Paul Moxey, Stefan Müller-Hülsbeck, Jihad Mustapha, Tatsuya Nakama, Bahaa Nasr, Zola N'Dandu, Richard Neville, Elias Noory, Joakim Nordanstig, Katariina Noronen, Luis Mariano Palena, Gianbattista Parlani, Ashish S Patel, Parag Patel, Rafiuddin Patel, Sanjay Patel, Costantino Pena, Drazen Perkov, Mark Portou, Giovanni Pratesi, Christos Rammos, Jim Reekers, Vicente Riambau, Trisha Roy, Kenneth Rosenfield, Maria Antonella Ruffino, Fadi Saab, Athanasios Saratzis, Paolo Sbarzaglia, Andrej Schmidt, Eric Secemsky, Michael Siah, Henrik Sillesen, Gioele Simonte, Marc Sirvent, Jill Sommerset, Sabine Steiner, Ahmed Sakr, Dierk Scheinert, Mehdi Shishebor, Stavros Spiliopoulos, Alessio Spinelli, Konstantinos Stravoulakis, Gergana Taneva, Desarom Teso, Joerg Tessarek, Selva Theivacumar, Anish Thomas, Shannon Thomas, Narayan Thulasidasan, Giovanni Torsello, Ramesh Tripathi, Nicola Troisi, Srini Tummala, Venkat Tummala, Christopher Twine, Raman Uberoi, Alessandro Ucci, Domenico Valenti, Jos Van Den Berg, Daniel Van Den Heuvel, Isabelle Van Herzeele, Ramon Varcoe, Melina Vega De Ceniga, Frank J Veith, Maarit Venermo, Badri Vijaynagar, Sanjiv Virdee, Conrad Von Stempel, Michiel T Voûte, Kak Khee Yeung, Thomas Zeller, Hany Zayed, Miguel Montero Baker

Faculty, Staff and Student Publications

No abstract provided.

Governing Complexity: A Comparative Assessment Of Four Governance Models With Applications To Climate Change Mitigation And Adaptation, J. B. Ruhl, Niko Soininen, Barbara Cosens, Lance Gunderson

Vanderbilt Law School Faculty Publications

Responses to ongoing global climate change include economy-wide mitigation efforts and large-scale societal adaptation that demand novel approaches to governance. An array of innovative governance models has been proposed since the late 1900s and early 2000s as scholars observed inadequacies of government-centric and formal legal approaches to natural resource management, complexity and uncertainty, failures of neoliberal economic reforms, and cross-scale institutional arrangements. Four such models have come to dominate the solution-oriented discourse on climate change governance: adaptive governance, transition governance, transformation governance, and anticipatory governance. We compare these models in terms of their origin and applicability to deal with the …

On Sobolev Spaces And The Existence Of Weak Solutions To Boundary Value Problems, Skye X. Paul

Master's Theses

Many boundary value problems that arise in mathematical models have close connections to second order elliptic partial differential equations. This thesis introduces the idea of weak derivatives and Sobolev Spaces to generalize possible solutions. Using functional analysis centered around the Lax-Milgram theorem, we show the existence of these generalized solutions to boundary value problems including Laplace's Equation, 2nd order linear ODEs, and ultimately a general second order elliptic PDE. The work cumulates with recovering a number of central theorems of functional analysis in the context of Sobolev Spaces, creating a new perspective on the solvability of these boundary value problems.