Digital Commons Network^™

Meshless Discrete Velocity Boltzmann Model For Porous Media Flow, Amandine Maidenberg

Doctoral Dissertations and Master's Theses

This dissertation explores the combination of two sophisticated techniques for addressing computational fluid dynamics: the discrete velocity Boltzmann equation (DVBE) and the localized collocation meshless model with upwinding (U-LCMM). The DVBE is a high-level model that describes the foundations of transport phenomena by addressing the microscale motions of particles themselves and the effect of their aggregate behaviors on continuum principles. This equation integrates multiple scales of phenomena; while it can be used for fluid flow at Navier-Stokes scales, it can also resolve fine features that can only be described at the molecular level. This type of model is necessary for …

Juxtaposing Approaches To Risk-Based Ai Governance In Different ‘Rights’ Contexts: A Comparative Analysis Between Singapore And The Eu, Jane Loo, Mark Findlay

Research Collection Yong Pung How School Of Law

Comparative analysis of European and certain Asian approaches to governance often degenerates into simplistic dichotomies based on universal human rights assumptions. This chapter rejects such dualities, ill-informed by theory and historical reflection. The emerging argument is founded on a historical realist approach to theorising difference. Assisted by Polanyi’s double movement, the detailed substantive comparison is preceded by considerations of how recent trends in governing AI have uniformly adopted a countermovement against the dis-embedding of data and technology from the social leading to a risk/responsibility paradigm. From here, a more nuanced reflection of AI governance approaches in the EU and Singapore …

Studying Topic Evolution Based On Bertopic Model And Semantic Function, Jiabin Qu, Mengyang Wang

Journal of Scientific Information Research

[Purpose/significance] Topic evolution analysis can help researchers quickly grasp the research hotspots and development trends of a discipline. However, existing topic models often overlook the semantic functions and structures of texts during topic extraction, making it difficult to reveal the deeper patterns of disciplinary development. This paper proposes an integrated framework for topic evolution analysis that combines the BERTopic model with semantic functions, aiming to enrich and improve the methodological system of topic evolution research.

[Method/process] Firstly, the BERTopic model is used to extract topics, obtaining the“Topic-Word”distribution. Next, a discourse parsing tool analyzes abstracts into five semantic function segments, resulting …

Reproducibility Debt In Scientific Software, Zara Hassan, Christoph Treude, Graham Williams, Michael Norrish, Alex Potanin

Research Collection School Of Computing and Information Systems

Reproducibility Debt (RpD) refers to accumulated technical and organisational issues in scientific software that hinder the ability to reproduce research results. While reproducibility is essential to scientific integrity, RpD remains poorly defined and under-addressed. This study introduces a formal definition of RpD and investigates its causes, effects, and mitigation strategies using a mixed-methods approach involving a systematic literature review (214 papers), interviews (23 practitioners), and a global survey (59 participants). We identify seven categories of contributing issues, 75 causes, 110 effects, and 61 mitigation strategies. Findings are synthesised into a cause-effect model and supported by taxonomies of team roles and …

Visual-Enhanced Multimodal Framework For Flexible Job Shop Scheduling Problem, Peng Zhao, Zhiguang Cao, Di Wang, Wen Song, Wei Pang, You Zhou, Yuan Jiang

Research Collection School Of Computing and Information Systems

Multimodal models leverage complementary information across modalities to enrich feature representations. While visual information shows potential in representing structure for some combinatorial optimization problems (COPs), its application to complex scheduling like the Flexible Job Shop Scheduling Problem (FJSP) remains underexplored. Current learning-based FJSP solvers predominantly rely on handcrafted state features. This dependence can lead to inconsistencies and may not fully capture the problem's intricate dynamics. Crucially, these methods overlook visual modalities. Visual representations offer a distinct advantage by inherently capturing the global topological structure and complex resource interactions within the FJSP state. Unlike localized handcrafted features, this holistic, structural view …

Advances In Iot, Ai, And Sensor‑Based Technologies For Disease Treatment, Health Promotion, Successful Ageing, And Ageing Well, Yuzhou Qian, Keng Siau

Research Collection School Of Computing and Information Systems

Recent advancements in the Internet of Things (IoT) and artificial intelligence (AI) are unlocking transformative opportunities across society. One of the most critical challenges addressed by these technologies is the ageing population, which presents mounting concerns for healthcare systems and quality of life worldwide. By supporting continuous monitoring, personal care, and data-driven decision-making, IoT and AI are shifting healthcare delivery from a reactive approach to a proactive one. This paper presents a comprehensive overview of IoT-based systems with a particular focus on the Internet of Healthcare Things (IoHT) and their integration with AI, referred to as the Artificial Intelligence of …

Genwardrobe: A Fully Generative System For Travel Fashion Wardrobe Construction, Peng Jin, Yilin Wen, Mingzhe Yu, Yunshan Ma, Rong Zheng, Jin‑Tu Fan, Chong Wah Ngo

Research Collection School Of Computing and Information Systems

With the increasing demand for outfit planning in real-world travel scenarios, the need for constructing a travel fashion wardrobe, a series of outfits tailored to a user's personalization and destination-specific context over a short travel period, has grown significantly. However, existing systems or works often focus on isolated factors and rely on retrieval-based methods, with insufficient utilization of generative models, limiting their adaptability to real-world travel scenarios. To address this issue, this study introduces GenWardrobe, a fully generative system for travel fashion wardrobe construction. GenWardrobe consists of three key modules: user query analysis, fashion knowledge retrieval via retrieval-augmented generation and …

Recovery Of Magnesium Sulfate And Calcium Sulfate From Zinc Flotation Tailing, Raquel Húngaro Costa, Jonathan Tenório Vinhal, Tatiana Scarazzato, Denise Crocce Romano Espinosa

Journal of Sustainable Mining

Resource recovery is a process that has been used to obtain products from industrial waste. Mining tailings can be used as an alternative through ore beneficiation to create by-products for this type of waste. The work herein investigated the recovery of two products from a real tailing generated in the Zn beneficiation route in the flotation step. A non-magnetic fraction was submitted to a hydrometallurgical route to produce MgSO₄ and CaSO_4. Thermodynamic simulations using FactSage software were performed to evaluate the optimal leaching conditions varying the S:L ratio, the sulfuric acid concentration, and temperature. The best modeled conditions …

The Saltpond Oilfield’S Second Life: Ghana’S Bioenergy With Carbon Capture And Storage (Beccs) Opportunity, Justice Appiah Nuamah

COP30

As the achievement of net-zero emissions requires the unavoidable deployment of Carbon Dioxide Removal (CDR) technologies, this paper presents a technical and policy case for Ghana to implement Bioenergy with Carbon Capture and Storage (BECCS) through the repurposing of the decommissioned Saltpond offshore oilfield for permanent CO2 sequestration. The proposal addresses two of Ghana’s developmental challenges in a single intervention: the conversion of millions of tonnes of agricultural and forestry residues into a sustainable feedstock solves a national waste management issue, while the resultant bioenergy generation supports rural electrification. This approach offers a more cost-effective CDR pathway than direct air …

High-Order Adaptive Solutions For Coupled Fractional Riccati Equations Via Daubechies Redundant Frames, Mutaz Mohammad, Alexander Trounev

Mathematical Modelling and Numerical Simulation with Applications

Coupled fractional Riccati equations play a fundamental role in modeling complex systems with memory effects and anomalous diffusion, frequently arising in engineering, control theory, finance, and quantum mechanics. Their analytical and numerical treatment remains highly challenging due to the nonlocal nature of fractional-order derivatives and the presence of nonlinear coupling terms. This study introduces an adaptive numerical framework that combines the Caputo fractional derivative with redundant Daubechies wavelet frames. The method leverages multi-resolution analysis, compact support, and controlled redundancy to achieve accurate approximation of both localized and global solution features, particularly in scenarios characterized by singular behavior and long-range memory …

The Consideration Of Two Scalarization Methods For The Multi-Objective Nurse-To-Patient Assignment Problem, Ilgın Acar, Steven E. Butt, Aydın Sipahioğlu, İslam Altın

Mathematical Modelling and Numerical Simulation with Applications

In this research, the application of two scalarization methods, namely the conic scalarization method and the $\varepsilon$-constraint method, is investigated within the context of a multi-objective optimization problem. These methods are used to address the challenge of assigning nurses to patients on a hospital unit during a shift. The two objective functions of this assignment problem are based on patient workload metrics and unit-related travel distance measures. The proposed solution approach demonstrates the ability to generate solutions that eluded the previous mathematical programming techniques that relied on simplistic weightings of conflicting objective functions. In addition, it is found that the …

Synergistic Modeling Of Hydrogel Gelation Via Time-Delay Dynamics And Machine Learning Algorithms, Mine Babaoglu, Dipesh ., Pankaj Kumar, Jagjit Singh Dhatterwal, Mansoor Alsulami

Mathematical Modelling and Numerical Simulation with Applications

This paper presents an integrated framework in which delay differential equation (DDE) modeling and machine learning (ML) approaches are coupled to study hydrogel formation kinetics, with emphasis on delayed crosslinker addition. Conventional mechanistic models disclose many physical and kinetic complexities of reacting mixtures; they seldom depict the nonlinear and time-evolving complexities inherent in developing polymer networks. To address this, a mathematical model is developed that examines how the insertion of crosslinkers affects system stability and equilibrium. Analytical and numerical results show that delays nearing critical levels cause bifurcation behavior with substantial implications on gelation kinetics. Sophisticated machine learning systems, including …

Dynamics And Optimal Intervention Strategies In A Shigellosis Transmission Model, Mehmet Gümüs, Shewafera Wondimagegnhu Teklu, Kemal Türk

Mathematical Modelling and Numerical Simulation with Applications

This research explores how water treatment contributes to limiting the transmission of Shigellosis, an infection caused by bacteria from the Shigella genus. A mathematical framework is formulated to evaluate the influence of protective strategies and water purification on the spread of the disease. To confirm the model's biological relevance, its well-posedness is investigated. The basic reproduction number $(\mathfrak{R}_0)$, a critical indicator of disease behavior, is derived using the matrix operator method. Findings indicate that if $\mathfrak{R}_01$, the infection persists, with the endemic equilibrium exhibiting local asymptotic stability. A comprehensive cost-effectiveness analysis reveals that combining environmental protection with water treatment represents …

Drawing On Uncertainty Methodologies Of Neutrosophic Hypersoft Sets In Cognitive Computing-Driven Healthcare Systems, Mona Mohamed, Nurhan Alaa

Neutrosophic Systems with Applications

A new paradigm called cognitive computing simulates human reasoning and decision-making through integrating advanced techniques such as artificial intelligence (AI) and natural language processing (NLP). Cognitive computing systems, in contrast to traditional systems, can handle both structured and unstructured data, adjust to new information, and offer context-sensitive insights. This study examines how cognitive computing improves decision-making, personalization, and human-machine collaboration in various fields. Cognitive computing in the healthcare sector processes clinical notes, imaging data, and electronic health records to help physicians with diagnosis, treatment planning, and patient engagement. This study examines key applications, including their role in diagnostic support, where …

Evaluating And Ranking Genai Chatbots Under Uncertainty: A Type-2 Neutrosophic Rancom–Marcos Mcdm Framework, Hend Ahmed, Abduallah Gamal

Neutrosophic Systems with Applications

Owing to integrate GenAI chatbots to enhance productivity across various tasks, this research presents T2NN-RANCOM-MARCOS multi-attribute decision-making model, which employs Type-2 Neutrosophic Number (T2NN) to handle uncertain data, the RANCOM method, distinguished by its easy, highly repeatable, less time consuming, more appropriate to deal with problems exceeds 5 criteria with expert errors to assign subjective weights to criteria and MARCOS method to evaluate and rank eight GenAI chatbots against six main criteria are included 23 sub-criteria: Quality of Information, Understanding and Reasoning, Expression Style and Persona, Safety and Harm, Trust and Confidence and Economic are primarily derived from QUEST evaluation …

Revised Final Uniform Federal Policyquality Assurance Project Plan, Hydrogeologic, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Revised Final Uniform Federal Policy- Quality Assurance Project Plan, Hydrogeologic, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Response To Epa Comments Dated September 29, 2025 For The Blacktail Creek Riparian Actions Draft Preliminary (30%) Remedial Design Report, Silver Bow Creek/Butte Area Superfund Site Silver Bow County, Montana, Montana Department Of Environmental Quality

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Comment Letter For Butte Priority Soils Operable Unit (Bpsou), Draft Preliminary (30%) Remedial Design Report, Blacktail Creek Riparian Actions (Dated July 28, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Significantly Enhanced Oxygen Reduction Reaction Activity In Co-N-C Catalysts Through Synergistic Boron Doping, Chang Lan, Jing-Sen Bai, Xin Guan, Shuo Wang, Nan-Shu Zhang, Yu-Qing Cheng, Jin-Jing Tao, Yu-Yi Chu, Mei-Ling Xiao, Chang-Peng Liu, Wei Xing

Journal of Electrochemistry

The weak adsorption energy of oxygen-containing intermediates on Co center leads to a considerable performance disparity between Co-N-C and costly Pt benchmark in catalyzing oxygen reduction reaction (ORR). In this work, we strategically engineer the active site structure of Co-N-C via B substitution, which is accomplished by the pyrolysis of ammonium borate. During this process, the in-situ generated NH₃ gas plays a critical role in creating surface defects and boron atoms substituting nitrogen atoms in the carbon structure. The well-designed CoB₁N₃ active site endows Co with higher charge density and stronger adsorption energy toward oxygen species, …

Local Electric Fields Coupled With Cl− Fixation Strategy For Improving Seawater Oxygen Reduction Reaction Performance, Yu-Rong Liu, Miao Zhang, Yan-Hui Yu, Ya-Lin Liu, Jing Li, Xiao-Dong Shi, Zhen-Ye Kang, Dao-Xiong Wu, Peng Rao, Ying Liang, Xin-Long Tian

Journal of Electrochemistry

Development of robust electrocatalyst for oxygen reduction reaction (ORR) in a seawater electrolyte is the key to realize seawater electrolyte-based zinc-air batteries (SZABs). Herein, constructing a local electric field coupled with chloride ions (Cl⁻) fixation strategy in dual single-atom catalysts (DSACs) was proposed, and the resultant catalyst delivered considerable ORR performance in a seawater electrolyte, with a high half-wave potential (E_1/2) of 0.868 V and a good maximum power density (Pmax) of 182 mW·cm⁻² in the assembled SZABs, much higher than those of the Pt/C catalyst (E_1/2: 0.846 V; Pmax: 150 mW·cm^{−2 …}

Wmu Maritime Affairs Conference 2025 : Transforming A Maritime Future : Digitalization And Decarbonization, World Maritime University

Books

No abstract provided.

Fourier Analyses Of Optical Profilometry As An Inferential Measurement For Impact Coverage., Langdon Feltner, Paul Mort

15th International Conference on Shot Peening

A critical consideration in peening process design is achieving sufficient impact coverage. Conventional methods for assessing coverage rely on manual inspection, which is time-consuming and poorly suited for automated control. In this work, we investigate the use of frequency-domain analysis to quantify surface modification in peened samples using optical profilometry (OP) data. Three-dimensional surface maps of Almen strips were acquired using a high-resolution OP system and analyzed via fast Fourier transform (FFT) to compute spatial power spectral densities (PSDs). PSD maps and radially averaged profiles reveal consistent amplification of harmonic components similar to the nominal particle size, with increasing intensity …

Reduced Order Approach For Peening Stress Field Variability, Langdon Feltner, Paul Mort

15th International Conference on Shot Peening

A common goal in shot peening research is to connect operational parameters to resultant residual stress fields, providing a means to control and optimize the effectiveness of surface treatment. In practice, experimental measurements of residual stresses are often averaged values over regions that are large in comparison to an impact dimple. In fact, the stochastic nature of impact locations leads to residual stress fields that are distributed. Finite element peening simulations confirm this observation. The goal of this report is to connect operational parameters to localized fluctuations in residual stress through probabilistic reasoning (Figure 1). In particular, the development of …

Synthesis And Characterization Of Fe-Zn Bimetallic Nanoparticles Via Two-Step Laser Ablation And Their Antibacterial Activity, Hudhaifa M. Mohammed, Sahar Naji Rashid

Karbala International Journal of Modern Science

In this study, Nd: YAG laser at a wavelength of (1064 nm), energies of (300 and 400 mJ), and a pulse repetition rate of (3 Hz) was used to synthesize metallic nanoparticles from iron and zinc individually using a one-step pulsed laser ablation approach, followed by the two-step synthesis of bimetallic nanoparticles. The physical properties of the synthesized nanoparticles were then investigated using UV-visible (UV-Vis), X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), and energy-dispersive X-ray (EDX) techniques. The results of characterization of the obtained NPs confirmed the formation of core-shell nanocomposites, as evidenced by the increased absorbance intensity of …

Carbon Metabolism And Multidrug Resistance In Bacillus Mobilis And Cupriavidus Campinensis Isolated From Cadmium-Spiked Soils, Philips O. Akinwole, Emma E.C. Jacobs '25, Nina G. Shaffer '25

Biology Faculty publications

Heavy metal contamination and antibiotic resistance are critical environmental and public health challenges, often exacerbated by co-selection pressures in polluted environments. This study identifies and characterizes Bacillus mobilis and Cupriavidus campinensis, two cadmium-tolerant bacterial species isolated from cadmium-amended soils with cadmium (Cd²⁺) concentrations exceeding those typically found in highly contaminated soils. Both species exhibited multidrug resistance and the ability to metabolize specific carbon substrates, including pyruvic acid methyl ester, itaconic acid, D-galactonic acid-γ-lactone, Tween-40, and Tween-80. These substrates enhance microbial activity and heavy metal bioavailability, supporting their potential roles in bioremediation, especially through the targeted introduction of …

Attenuation Characteristics And Wave Impedance Inversion Of Depth-Domain Nonstationary Seismic Data, Ma Ming, Ma Feng

Coal Geology & Exploration

Background The efficient application of depth migration methods has enabled the extensive implementation of depth-domain seismic data interpretation. Previous studies on the impacts of time-to-depth conversion and velocity models merely determine that an increase in depth corresponds to reduced dominant wavenumber of seismic waves and waveform stretching, without considering the changes in amplitude and phase. Objective This study aims to accurately characterize the waveforms of nonstationary seismic signals in the depth domain and enhance the impedance inversion accuracy. Methods First, based on energy dissipation and frequency dispersion effects during the propagation of seismic waves, this study investigated the complex mapping …

Solutions For Linear Fractional Differential Equations With Multiple Constraints Using Fractional B-Poly Bases, Md. Habibur Rahman, Muhammad I. Bhatti, Nicholas Dimakis

Physics & Astronomy Faculty Publications

This study presents an innovative numerical method for solving linear fractional differential equations (LFDEs) using modified Bernstein polynomial bases. The proposed approach effectively addresses the challenges posed by the nonlocal nature of fractional derivatives, providing a robust framework for handling multiple initial and boundary value constraints. By integrating the LFDEs and approximating the solutions with modified fractional-order Bernstein polynomials, we derive operational matrices to solve the resulting system numerically. The method’s accuracy is validated through several examples, showing excellent agreement between numerical and exact solutions. Comparative analysis with existing data further confirms the reliability of the approach, with absolute errors …

Re: Butte Priority Soils Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites Field Sampling Plan (Fsp): Bres No. 26 – Cripple Dump, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Collocation Point Sampling Method For Solving The Helmholtz Equation Using Physics-Informed Neural Networks, Shan Lianpu, Yu Caixia, Wang Yanfei

Coal Geology & Exploration

Background In the field of seismic wavefield simulation, physics-informed neural networks (PINNs) have emerged as a new method for efficiently solving the Helmholtz equation due to their characteristic of grid-free computation. However, for the forward modeling of complex medium models using the Helmholtz equation, traditional uniform grid-based methods for collocation point sampling are insufficient to efficiently provide gradient information, leading to prolonged training time and high resource consumption. Objective and Method To improve the forward modeling efficiency and accuracy based on PINNs and overcome the anomalous concentration of collocation points in the seismic source during dynamic sampling, this study proposed …