Digital Commons Network^™

Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness, Renqiang Luo, Huafei Huang, Shuo Yu, Fengqi Yu, Feng Xia, Sajal K. Das, Chengqi Zhang

Computer Science Faculty Research & Creative Works

Fairness-aware federated graph neural networks (FedGNNs) necessitate consideration of both the server and the clients. However, fairness-aware methods struggle to enhance dual-perspective (i.e., server and clients) fairness without sacrificing utility due to the distributed learning framework. As a consequence, the utility sacrifices of fairness-aware graph learning methods are even exacerbated in federated frameworks. In this work we propose F3GL, a dual-perspective fairness federated graph learning method that enhances both global (for the server) and local fairness (for clients) while preserving utility. Through theoretical analysis, we delineate the similarity between original sensitive features and those after convolution under different spectra. Our …

Escher: Efficient And Scalable Hypergraph Evolution Representation With Application To Triad Counting, S. M. Shovan, Arindam Khanda, Sanjukta Bhowmick, Sajal K. Das

Computer Science Faculty Research & Creative Works

Higher-order interactions beyond pairwise relationships in large complex networks are often modeled as hypergraphs. Analyzing hypergraph properties such as triad counts is essential, as hypergraphs can reveal intricate group interaction patterns that conventional graphs fail to capture. In realworld scenarios, these networks are often large and dynamic, introducing significant computational challenges. Due to the absence of specialized software packages and data structures, the analysis of large dynamic hypergraphs remains largely unexplored. Motivated by this gap, we propose ESCHER, a GPU-centric parallel data structure for Efficient and Scalable Hypergraph Evolution Representation, designed to manage largescale hypergraph dynamics efficiently. We also design …

Dermatology Skin Lesion Image Analysis, Victoria Wegley, Joshua Hoog, Tristan Crawford, Keith Miller, William Fons, K. Pugh, J. Taylor, S. Swinfard, A. Fernandes, G. Patel, J. Hagerty, W. V. Stoecker, Ronald Joe Stanley

Research Data

Dermatology skin lesion image analysis research has been ongoing at Missouri S&T (previously UMR) since the 1980s. Our group has been successful in finding over 20 key dermoscopic structures in melanoma, melanoma mimics, and nonmelanoma skin cancers using iterative structure-based analysis. Structures are chosen to reduce system errors which are concentrated in a few classes: amelanotic/featureless, regressed, and small in situ melanomas, and the most difficult benign lesions to identify: Clark nevi, lentigines, and seborrheic keratoses [1]. Preliminary research detecting and using annotated lesion structures [2-7] and lesion artifacts [8,9] guided by clinical experience [10] with image processing and deep …

Pahina: Precision-Aware Hierarchical In-Network Aggregation For Edge Distributed Training, Yingpu Nian, Bo Yi, Qiang He, Xingwei Wang, Geyong Min, Keqin Li, Sajal K. Das

Computer Science Faculty Research & Creative Works

The rise of edge intelligence is driving distributed machine learning toward a new paradigm of edge-collaborative computing. To overcome the severe communication bottleneck in this paradigm, In-Network Aggregation is a critical enabling technology. However, its effectiveness is fundamentally undermined by the profound resource heterogeneity of edge networks. Specifically, edge devices, adapting to hardware constraints, operate at varying numerical precisions, leading to significant data inflation as gradients are aggregated. Compounding this, unevenly distributed network resources and traditional, precision-oblivious routing strategies often misallocate critical, high-precision gradients to low-quality paths. This mismatch creates severe network congestion, crippling the efficiency of distributed training. To …

Smartflow: A Communication-Efficient Sdn Framework For Cross-Silo Federated Learning, Osama Abu Hamdan, Hao Che, Engin Arslan, Md Arifuzzaman

Computer Science Faculty Research & Creative Works

Cross-silo Federated Learning (FL) enables multiple institutions to collaboratively train machine learning models while preserving data privacy. In such settings, clients repeatedly exchange model weights with a central server, making the overall training time highly sensitive to network performance. However, conventional routing methods often fail to prevent congestion, leading to increased communication latency and prolonged training. Software-Defined Networking (SDN), which provides centralized and programmable control over network resources, offers a promising way to address this limitation. To this end, we propose SmartFLow, an SDN-based framework designed to enhance communication efficiency in cross-silo FL. SmartFLow dynamically adjusts routing paths in response …

Aim5b: Ai Integrated Semantic Framework For 5g And Beyond Network Management, Thanveer Sulthana, Ava Sharif Jourabchi, Venkat Rao Manavarthi, Jayadithya Nalajala, Ankitha Srirama Reddy, Baek Young Choi, Sejun Song

Computer Science Faculty Research & Creative Works

Scalable, interpretable, and intelligent network monitoring and management are critical for 5 G and future networks. This paper introduces Aim5B, an AI-integrated semantic framework for 5 G and beyond network management to address these challenges. Aim5B processes unstructured logs from key 5G core network functions, and transforms them into a knowledge graph aligned with the semantic structure of control-plane events. Leveraging a large language model (LLM), Aim5B enables natural language queries to be translated into Cypher graph queries, facilitating precise log retrieval, event analysis, temporal correlation, and statistical summarization-without relying on static parsing rules or predefined dashboards. Integrated on a …

Investigations In Hydrogen Ironmaking, Joseph William Govro

Doctoral Dissertations

The purpose of this research is to contribute to the Grid Interactive Steelmaking with Hydrogen (GISH) project. This research investigates the viability of both producing and melting Direct-Reduced Iron (DRI) utilizing hydrogen. Conventional CO reduced DRI will be referred to as “C-DRI” and DRI produced using hydrogen gas will be referred to as “H-DRI”.

An H-DRI pilot plant was constructed in Golden Colorado. The pilot plant was commissioned and successfully operated four campaigns. Process improvements were made throughout the campaigns and the process was optimized. In addition to running the pilot plant in a pure hydrogen condition, the pilot plant …

Architecting A Complex Adaptive System Model For Selecting Policies To Reduce Kidney Discard, Lirim Ashiku

Doctoral Dissertations

"The kidney allocation system is a complex, evolving system involving multiple heterogeneous agents. Each agent exhibits emergent behavior that may not fully align with the complex system goals. Therefore, there is a need for a transdisciplinary systems approach to visualize the interdependency among agents and understand the dominant patterns that shape the kidney allocation system.

First, this research presented an incremental hierarchical system engineering approach in identifying the agents’ needs and behaviors toward the complex systems’ goal of maximizing deceased donor kidney utilization and reducing kidney discard. The hierarchical systems approach linked with model-based system engineering aided in eliciting agents’ …

Fabrication And Characterization Of A High Strength Novel Aluminum Alloy For Implementation With Directed Energy Deposition, Rachel Boillat-Newport

Doctoral Dissertations

"Additive manufacturing (AM) is of significant interest due to the ability to fabricate 3D components layer-by-layer. Compared with traditional manufacturing methods, AM allows for the direct fabrication of complex, intricate parts without the need for extensive machining, reducing manufacturing time and tooling costs and minimizing material waste. Aluminum alloys are highly desired for implementation via AM due to their high strength-to-weight ratios; however, there are several challenges that complicate the situation and hinder the use of aluminum alloys. One of the most challenging issues is that the desired high-strength alloys are not compatible with AM processing methods. A method to …

Bond Graph And Extended Generalized Average Method With Applications In Cyber-Physical Systems And Power Electronics, Arnold Anthony Fernandes

Doctoral Dissertations

"This research examines two applications of control theory. The first application considers the bond graph (BG) modeling technique, which is used to develop the MATLAB structural analysis toolbox (MATSAT), an open-source toolbox for sensor placement and qualitative system analysis that considers the observability and fault-detection capabilities of multi-domain cyberphysical systems. The toolbox provides information on redundant sensors, guiding the system designer in cost and security trade-offs. The toolbox uses traditional BG causality assignment procedures. Additionally, MATSAT provides optimal causality assignment methods that perform significantly better at assigning causality to BGs with increased junctions, sources, and simple meshes, without encountering causality …

Harnessing Coherent-Wave Control For Sensing Applications In Scattering Media, Pablo Xavier Jara Palacios

Doctoral Dissertations

"Diffuse electromagnetic waves are widely used for non-invasive sensing and imaging in complex scattering media such as biological tissues. A fundamental limitation of such techniques is the scarcity of detected photons: as the source-detector separation increases to access deeper regions of the medium, the signal strength decays rapidly, leading to poor signal-to-noise ratio and limited sensitivity. This dissertation addresses this challenge through a combination of theory and computation.

We show that coherent control of the incident optical wavefront can compensate for the scarcity of detected photons that limits conventional diffuse optical imaging, typically performed in the near-infrared spectral region. By …

Soil Freezing Characteristic Surface For Partially Frozen Soils, Antai Dong, Xiong Zhang, Ming Xiao

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The soil freezing characteristic curve (SFCC), which relates unfrozen water content to temperature, is a fundamental constitutive relationship in frost heave simulations. However, the influence of soil suction, another critical state variable, is often neglected. This study highlights how the SFCC is significantly affected by suction conditions, with unfrozen water content varying markedly between saturated (suction = 0) and completely dried (suction = ∞) conditions at the same subfreezing temperature. Recognizing this limitation, the concept of the soil freezing characteristic surface (SFCS) is proposed to incorporate the impacts of both temperature and suction on unfrozen water content. After that a …

First Remi Experiments At A Cryogenic Ion Storage Ring, M. Schulz, F. Herrmann, W. Zhang, A. Dorn, M. Grieser, F. Grussie, H. Kreckel, O. Novotny, A. Wolf, T. Pfeifer, C. D. Schröter, R. Moshammer

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

We have recorded double, triple, and quadruple coincidences between neutralized projectiles, recoiling target ions, and two electrons created in collisions of slow anions with neutral atoms. The experiments were performed at the cryogenic storage ring in Heidelberg. The recoil ions and ejected electrons were momentum-analyzed using a Reaction Microscope (ReMi) spectrometer. Various processes involving electron detachment from the projectile accompanied by various transitions in the target were investigated. Detachment without any transition in the target is qualitatively well described by a quasi-free electron model in the case of an Ar target. In detachment with single target ionization, no signatures of …

A Four-Step Thermocatalytic Route For Converting Co2 Into High-Purity Oxalic Acid, Hao Feng, Muhammad Kashif Khan, Lei Li, Hongyan Ma, Xinhua Liang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This research outlines a four-step methodology for transforming CO₂ into high-purity oxalic acid. CO2 was first sequestered as KHCO₃ through its reaction with aqueous KOH, followed by hydrogenation using a supported AgPd/CNT catalyst in a batch reactor at an initial H₂ pressure of 60 bar and a temperature of 150°C. The formate yield reached 91.8% at optimum conditions. Potassium formate in the solid state was thermally coupled in the presence of KOH at 400°C under N2 flow, yielding potassium oxalate of up to 76% yield. The final step was the selective precipitation of potassium oxalate with ferrous …

Scalable Transfer Of Dna Origami–Directed Nanoparticle Arrays Onto Functional Surfaces Using Thermal Release Tape, Yuwei Zhang, Chikadibia Genevieve Edward, Ethan Keuhn, Shelley D. Minteer, Risheng Wang

Chemistry Faculty Research & Creative Works

Precise integration of DNA origami nanostructures onto functional substrates is essential for advancing electronics, photonics, and biosensing. However, most surface-assembly methods are highly sensitive to substrate type, limiting their broader applications. Here, we introduce a thermal release tape (TRT)-assisted transfer method that enables efficient, large-area printing of DNA origami-guided gold nanoparticle (AuNP-DNA origami) arrays from mica onto diverse surfaces. The method relies on differential adhesion: AuNP-DNA origami arrays form strong electrostatic and hydrogen-bonding interactions with 3-aminopropyltriethoxysilane (APTES)-functionalized receiver substrates, while the TRT adhesive weakens upon heating to 120°C, allowing release from the tape. Using this approach, well-ordered AuNP-DNA origami arrays …

Closing The Nitrogen Loop In Groundwater With Biohybrid Technologies, Linjie Zhou, Biao Li, Jianhua Guo, Shelley D. Minteer, Yifeng Zhang

Chemistry Faculty Research & Creative Works

Nitrate in groundwater should be treated as a nitrogen source rather than a contaminant. Biohybrid technologies coupling microbial selectivity with renewable electro(photo)chemical energy offer opportunities to convert nitrate to value-added ammonium, although challenges remain in scalability, microbial stability, material–microbe integration, process engineering, regulatory compliance, and economic feasibility.

Evaluation Of Chromium-Crosslinked Amps-Hpam Copolymer Gels: Effects Of Key Parameters On Gelation Time And Strength, Maryam Sharifi Paroushi, Baojun Bai, Thomas P. Schuman, Yin Zhang, Mingzhen Wei

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Controlling CO₂ channeling in heterogeneous reservoirs remains a major challenge for both enhanced oil recovery (EOR) and secure geological storage. AMPS-HPAM copolymers exhibit high-temperature resistance and brine tolerance compared with conventional HPAM gels, making them well suited for the harsh environments associated with CO₂ injection. Chromium-based crosslinkers (CrAc and CrCl₃) were investigated because sulfonic acid groups in AMPS can coordinate with trivalent chromium ions, enabling dual ionic crosslinking and the formation of a robust gel network. While organic crosslinked AMPS-HPAM gels have been widely studied, the behavior of chromium-crosslinked AMPS-containing systems, particularly their gelation kinetics under …

Effect Of Ionic Strength On Gelation Time And Strength Of Amps-Based Polymer Gels, Maryam Sharifi Paroushi, Xuyang Tian, Baojun Bai, Thomas P. Schuman, Yin Zhang, Mingzhen Wei

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polymer gel treatment has been widely applied for improving sweep efficiency and controlling excessive water and gas production. Their performance depends on gelation time and final gel strength. In most studies, brine salinity is used to describe the effect of formation water on gel behavior. However, changing salinity also changes ionic strength and ion composition at the same time. Because of this coupling, it is difficult to identify the mechanisms controlling gelation, which has led to inconsistent trends in the literature. Increasing salinity has been reported to either slow or accelerate gelation and to weaken or strengthen gels depending on …

Injectable Borate/Borosilicate Bioactive Glass Systems For The Regeneration Of Hard Tissue – A Critical Review Of The Literature, S. Sina Mohammadi, Sunjeev S. Phull, Ryan J. Gilbert, Mark R. Towler

Chemical and Biochemical Engineering Faculty Research & Creative Works

Bone defects caused by trauma, infection, or tumor resection remain difficult to treat because successful repair requires both structural restoration and control of the local pathological microenvironment. Osteolysis, defined as pathological bone resorption, is central to many of these conditions and is commonly driven by excessive osteoclast activity. Clinically translated injectable products such as NovaBone® Putty demonstrate the value of moldable bioactiveglass grafts for defect filling; however, conventional silicate bioactive glasses are permanent and provide limited therapeutic ion release. This limitation has motivated the development of injectable borate bioactive glass (B-BGs) and injectable borosilicate bioactive glass (BS-BG) systems as more …

Evaluation Of A Novel Re-Crosslinkable Preformed Particle Gel For Conformance Control In Ultra-High Temperature Reservoirs, Yanbo Liu, Tao Song, Caleb Kwasi Darko, Thomas P. Schuman, Mingzhen Wei, Baojun Bai

Chemistry Faculty Research & Creative Works

Preferential fluid flow remains a major challenge in subsurface energy production and gas storage operations, resulting in excessive water production in mature oil fields, reduced heat extraction in geothermal reservoirs, and low sweep and storage efficiency in CO₂-EOR projects. Polymer gels are widely used to mitigate high-permeability channels; however, conventional systems exhibit limited plugging efficiency and short lifetimes in ultra-high-temperature reservoirs due to poor thermal stability. This study presents a novel ultra-high-temperature-resistant preformed particle gel (UHT-PPG) developed for conformance control in reservoirs with temperatures of 150–275 °C and severe super-K or channeling problems. The material was evaluated in …

Progression Toward Terminal Oxidation Of Starch Via Hybrid Organic–Enzymatic Bioanode For Renewable Carbohydrate Conversion, Adam Milam, Jose Intano, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

The performance of starch-based biofuel cells is fundamentally limited by inefficient utilization of the fuel's inherent energy density. Sequential oxidation of carbohydrate fuels, such as glucose, the monomeric unit of starch, using minimal catalyst systems has therefore emerged as a promising strategy to improve biofuel cell efficiency. Here, we extend a previously reported three-catalyst, organic–enzymatic glucose oxidation cascade to polymeric carbohydrate fuels by integrating enzymatic starch depolymerization with downstream electrochemical oxidation. To our knowledge, this represents the first demonstration of a defined hybrid organic–enzymatic cascade designed to drive progression of starch-derived glucose equivalents toward terminal oxidation using a minimal catalyst …

January 2026 Cafe Newsletter - Special Events Edition, Missouri University Of Science And Technology

CAFE Faculty Newsletters

No abstract provided.

Environmental Engineers Develop Solutions To Problems Of Planetary Health: The Legacy Of Professor P. Aarne Vesilind, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The principal ethical obligation of the engineering profession, to "hold paramount the health, safety, and welfare of the public," has been challenged for decades. Professor P. Aarne Vesilind identified two primary deficiencies: an anthropocentric bias that values nature only instrumentally and the use of non-mandatory, aspirational language for environmental protection, which resulted in the exclusion of enforceable environmental canons. This paper argues that two recent developments provide a comprehensive response to Vesilind's recommendations for engineering ethics. First, the United States Bureau of Labor Statistics has redefined environmental engineering as "developing solutions to problems of planetary health." Second, Oerther proposed a …

Fairrfl: Fair And Robust Federated Learning In The Presence Of Selfish Clients, Andrea Augello, Ashish Gupta, Giuseppe Lo Re, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) is a paradigm that enables collaborative machine learning without disclosing the local data of the participants. However, in real-world FL deployment scenarios, some unscrupolous clients may alter the training process to skew the global model towards their local optimum, unfairly prioritizing their data distribution. Their influence can degrade overall model performance for normal clients and reduce fairness in the system. We call this novel category of misbehaving clients 'selfish'. This work proposes a Fair and Robust strategy for aggregation in the Federated Learning (FL) server to mitigate the effect of Selfish clients (FairRFL). FairRFL incorporates a novel …

Qura: Reinforcement Learning Based Routing For Quantum Networks, Tasdiqul Islam, Engin Arslan, Md Arifuzzaman

Computer Science Faculty Research & Creative Works

Quantum routing deals with identifying a set of quantum repeaters to use to create entanglement between distant endpoints. Previous approaches proposed shortest-path and linear programming methods to find a solution to this problem. While the shortest path approach results in suboptimal performance, linear programming takes too long to find a solution as the network size and constraints increase. In this paper, we apply Deep Q-Reinforcement Learning (DQRL) to optimize routing in quantum networks both in terms of execution time and performance. The proposed Quantum Routing Algorithm (QuRA) first chooses which request to schedule among all requests. It then determines which …

Evaluation And Design Of A Footing Hybrid Connection For Innovative Hollow-Core Fiber-Reinforced Polymer–Concrete–Steel Composite Columns, Mohanad M. Abdulazeez, Mohamed A. Elgawady

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

To support the advancement of accelerated bridge construction in high-seismic regions, this study investigates a novel prefabricated column-to-footing connection designed for improved resiliency, constructability, and cost efficiency. The socket connection utilizes hollow-core fiber-reinforced polymer–concrete–steel (HC-FCS) columns with embedded corrugated steel pipes (CSPs). The composite HC-FCS column consists of a concrete shell sandwiched between an outer fiber-reinforced polymer tube and an inner steel tube. The inner steel tube is embedded into the footing connection of the HC-FCS column. The same authors tested the innovative socket connection on a large HC-FCS column under seismic loads, showing high ductility, strong moment and drift …

Exploring Aggregate Morphological Characteristics Under Laboratory Polishing For Enhanced Pavement Skid Resistance, Ahmed S. El-Ashwah, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

As the use of recycled asphalt pavement (RAP) in pavement construction grows for sustainable development, it becomes essential to investigate potential frictional deterioration over time. This study evaluated the friction properties of recovered RAP material aggregates compared with raw aggregates across various polishing cycles. The micro-Deval test was employed to simulate aggregate loss of texture, while morphological and friction properties were measured using an aggregate imaging measurement system (AIMS-II), along with a British pendulum tester (BPT) and dynamic friction tester (DFT). Additionally, Fourier transform infrared spectroscopy (FTIR) was employed to assess its potential in determining the origin and composition of …

Deep Learning Approach For Microwave Imaging Based On Deep Convolutional Asymmetric Encoder-Decoder Structure And Physics-Induced Loss, He Ming Yao, Shiji Song, Michael Kwok Po Ng, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we introduce an innovative deep learning (DL) methodology designed for real-time quantitative microwave imaging (MWI). Our approach is centered around the utilization of a deep convolutional asymmetric encoder-decoder structure (DCAEDS), which requires only a single-frequency far-field measurement of the electromagnetic (EM) scattered field as input and subsequently predicts the contrasts (permittivities) of the target materials. During the offline training process, we incorporate an EM forward solver specifically crafted to compute the EM scattered field generated by the predicted target contrasts (permittivities) produced by the DCAEDS. The DCAEDS is seamlessly integrated with this EM forward solver to optimize …

Optimal Slotting In Hybrid Warehousing For Industry 4.0, Teng Yang

Masters Theses

In the era of Industry 4.0, the warehouse management system (WMS) employed by many firms prescribes hybrid storage, i.e., products with high turnover, called fast movers, are kept in random storage for a short time duration before being shifted to a dedicated storage area, while products with low turnover, called slow movers, remain in random storage. From dedicated storage, the products are dispatched to the customer. The challenge for managers is selecting the slot in dedicated storage to assign to each product while demand data change because of fluctuating market conditions; this problem is referred to as slotting in the …

Investigating The Dynamic Rating Method: Effects Of Flood Wave Geometry On Discharge Estimation, Daniel James Read

Masters Theses

Rating curves are a vital tool to convert from observed stage to discharge in streamflow monitoring. Most gaging sites utilize a simple rating curve, which assumes a monotonic relationship between stage and discharge. In most cases, this assumption is valid; however, dynamic effects of flood waves often cause significant error in discharge estimation for mildly sloped streams. The dynamic rating method utilizes a numerical solution of the St. Venant Equations applied to time series stage data to compute discharge. Within this method, there is a flood wave parameter called the flood wave factor. The researchers designed a formal computational model …