Engineering Commons^™

Radar: Learning To Route With Asymmetry-Aware Distance Representations, Hang Yi, Ziwei Huang, Yining Ma, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Recent neural solvers have achieved strong performance on vehicle routing problems (VRPs), yet they mainly assume symmetric Euclidean distances, restricting applicability to real-world scenarios. A core challenge is encoding the relational features in asymmetric distance matrices of VRPs. Early attempts directly encoded these matrices but often failed to produce compact embeddings and generalized poorly at scale. In this paper, we propose RADAR, a scalable neural framework that augments existing neural VRP solvers with the ability to handle asymmetric inputs. RADAR addresses asymmetry from both static and dynamic perspectives. It leverages Singular Value Decomposition (SVD) on the asymmetric distance matrix to …

Chain-Of-Context Learning: Dynamic Constraint Understanding For Multi-Task Vrps, Shuangchun Gui, Suyu Liu, Xuehe Wang, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Multi-task Vehicle Routing Problems (VRPs) aim to minimize routing costs while satisfying diverse constraints. Existing solvers typically adopt a unified reinforcement learning (RL) framework to learn generalizable patterns across tasks. However, they often overlook the constraint and node dynamics during the decision process, making the model fail to accurately react to the current context. To address this limitation, we propose Chain-of-Context Learning (CCL), a novel framework that progressively captures the evolving context to guide fine-grained node adaptation. Specifically, CCL constructs step-wise contextual information via a Relevance-Guided Context Reformulation (RGCR) module, which adaptively prioritizes salient constraints. This context then guides node …

Resched: Rethinking Flexible Job Shop Scheduling From A Transformer-Based Architecture With Simplified States, Xiangjie Xiao, Cong Zhang, Wen Song, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Neural approaches to the Flexible Job Shop Scheduling Problem (FJSP), particularly those based on deep reinforcement learning (DRL), have gained growing attention in recent years. However, existing methods rely on complex feature-engineered state representations (i.e., often requiring more than 20 handcrafted features) and graph-biased neural architectures. To reduce modeling complexity and advance a more generalizable framework for FJSP, we introduce \textsc{ReSched}, a minimalist DRL framework that rethinks both the scheduling formulation and model design. First, by revisiting the Markov Decision Process (MDP) formulation of FJSP, we condense the state space to just four essential features, eliminating historical dependencies through a …

Towards Efficient Constraint Handling In Neural Solvers For Routing Problems, Jieyi Bi, Zhiguang Cao, Jianan Zhou, Wen Song, Yaoxin Wu, Jie Zhang, Yining Ma, Cathy Wu

Research Collection School Of Computing and Information Systems

Neural solvers have achieved impressive progress in addressing simple routing problems, particularly excelling in computational efficiency. However, their advantages under complex constraints remain nascent, for which current constraint-handling schemes via feasibility masking or implicit feasibility awareness can be inefficient or inapplicable for hard constraints. In this paper, we present Construct-and-Refine (CaR), the first general and efficient constraint-handling framework for neural routing solvers based on explicit learning-based feasibility refinement. Unlike prior construction-search hybrids that target reducing optimality gaps through heavy improvements yet still struggle with hard constraints, CaR achieves efficient constraint handling by designing a joint training framework that guides the …

Rrnco: Towards Real-World Routing With Neural Combinatorial Optimization, Jiwoo Son, Zhikai Zhao, Federico Berto, Chuanbo Hua, Zhiguang Cao, Changhyun Kwon, Jinkyoo Park

Research Collection School Of Computing and Information Systems

The practical deployment of Neural Combinatorial Optimization (NCO) for Vehicle Routing Problems (VRPs) is hindered by a critical sim-to-real gap. This gap stems not only from training on oversimplified Euclidean data but also from node-based architectures incapable of handling the node-and-edge-based features with correlated asymmetric cost matrices, such as those for real-world distance and duration. We introduce RRNCO, a novel architecture specifically designed to address these complexities. RRNCO's novelty lies in two key innovations. First, its Adaptive Node Embedding (ANE) efficiently fuses spatial coordinates with real-world distance features using a learned contextual gating mechanism. Second, its Neural Adaptive Bias (NAB) …

Generalizable Heuristic Generation Through Llms With Meta-Optimization, Yiding Shi, Jianan Zhou, Wen Song, Jieyi Bi, Yaoxin Wu, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

Heuristic design with large language models (LLMs) has emerged as a promising approach for tackling combinatorial optimization problems (COPs). However, existing approaches often rely on manually predefined evolutionary computation (EC) heuristic-optimizers and single-task training schemes, which may constrain the exploration of diverse heuristic algorithms and hinder the generalization of the resulting heuristics. To address these issues, we propose Meta-Optimization of Heuristics (MoH), a novel framework that operates at the optimizer level, discovering effective heuristic-optimizers through the principle of meta-learning. Specifically, MoH leverages LLMs to iteratively refine a meta-optimizer that autonomously constructs diverse heuristic-optimizers through (self-)invocation, thereby eliminating the reliance on …

Evaluating Human Rod Photoreceptor Function Using Pixelwise Intensity-Based Optoretinography, Gao Yang, Mina Gaffney, Robert F. Cooper

Biomedical Engineering Faculty Research and Publications

Purpose: More than 50 inherited retinal diseases are known, with rod photoreceptor functional loss serving as an early indicator in nearly half of them. The “optoretinogram” is a relatively new assay that detects optical changes in cells in response to stimuli. This tool has excellent potential for providing insights into the earliest functional changes of rod photoreceptors, with the potential to assist in the early detection, monitoring, and treatment of retinal diseases.

Methods: In this work, we obtained intensity-based optoretinograms (iORGs) from rod photoreceptors using an adaptive optics scanning laser ophthalmoscope. We explore the necessity of both individual rod identification …

Severity And Duration-Dependent Aortic Stiffening In A Rabbit Coarctation Model Identifies Constitutive Material Parameters As Promising Regional Biomarkers For Hypertension Progression, Arash Ghorbannia, Jamasp Azarnoosh, John F. Ladisa Jr.

Biomedical Engineering Faculty Research and Publications

Coarctation of the aorta (CoA) alters hemodynamics and drives regional remodeling, yet the influence of severity and duration on constitutive properties is undefined. We quantified mechanical responses from CoA to identify constitutive parameters capturing stiffening across clinical severities and durations. Mild (≤ 12 mmHg), intermediate (13–20 mmHg), and severe (> 20 mmHg) CoA was created in rabbits for short, long, and prolonged durations (~ 1, 3, or 22 weeks, respectively). Stress–stretch curves from proximal and distal regions were fit with multiple constitutive models (Linear Elastic, Neo-Hookean, Yeoh, Ogden, Mooney–Rivlin, Holzapfel). Model performance was evaluated by normalized RMSE and R², with …

Development And Acceptability Of A Patient Decision Aid For People With Degenerative Cervical Myelopathy: An International Mixed-Methods Study, Andrew R. Gamble, David B. Anderson, Marnee J. Mckay, Benjamin M. Davies, Sophie Macpherson, James Van Gelder, Tammy Hoffmann, Kirsten Mccaffery, Samuel X. Stevens, Carlo Ammendolia, Rohil V. Chauhan, Carl M. Zipser, Timothy F. Boerger, Lindsay A. Tetreault, Michael G. Fehlings, Elanor Dustan, Carolyn Nugent, Helen Holmgren, Andreas K. Demetriades, Justin M. Lantz, Rana Dhillon, Chris G. Maher, Joshua R. Zadro

Biomedical Engineering Faculty Research and Publications

Objectives To develop and user-test a patient decision aid for people diagnosed with degenerative cervical myelopathy and who are considering surgery.

Design Mixed-methods study describing the development of a patient decision aid.

Setting A draft decision aid was developed by a multidisciplinary steering group (including study authors with degenerative cervical myelopathy, health professionals and researchers) informed by the best available evidence, authorship consensus and existing patient decision aids.

Participants Patient-participants and health professional-participants who manage people with degenerative cervical myelopathy were recruited through social media and the steering group’s research and practice network. Quantitative questionnaires were used to gather baseline …

Plant-Mediated Green Synthesis Of Zinc Ferrite Nanoparticles: Mechanisms, Properties, And Advanced Applications In Environmental And Biomedical Fields, Rihab Jabbar

Al-Bahir

Recently, plant-mediated green synthesis has emerged as a sustainable, eco-friendly, and cost-effective strategy for synthesizing zinc ferrite (ZnFe₂O₄) nanoparticles (NPs). This review critically examines the advancements in biosynthesizing ZnFe₂O₄ NPs using various plant extracts, including Aloe vera, Hibiscus rosa-sinensis, Aegle marmelos, Eucalyptus leaves, Tragacanth gum, Piper nigrum, and Moringa oleifera, among others. It emphasizes their dual role as reducing, capping, chelating, and stabilizing agents. The article extensively compares physicochemical properties of the green-synthesized NPs in terms of crystallite size, morphology, magnetic behavior, and band gap energy. Achieved through different synthesis routes such as sol-gel, hydrothermal, co-precipitation, and microwave-assisted methods. …

Condition Monitoring Of Induction Motor Using Motor Current Signature Analysis, Francis Ikechukwu Obianke, Joseph Okhaifoh, Benjamin Akinloye

Al-Bahir

Induction machines serve as the cornerstone and driving force of modern manufacturing and production systems. This research aims to monitor and analyse the operating performance of induction motors using motor current signature analysis (MCSA). MCSA is employed to process the current signal of a motor into a frequency spectrum, known as the current signature by applying the Fast Fourier Transform (FFT) algorithm. The underlying principle is that vibration generated in a motor is closely related to the changes of the magnetic field density, and the induced voltage varies with the stator current.

A simulation model replicating the behaviour of an …

Recombinant Gelonin: Purification And Functional Validation For Electroporation-Assisted Delivery, Eleni Zivla, Giedrė Šilkūnienė, Andrei G. Pakhomov, Mantas Šilkūnas, Olga N. Pakhomova

Knowledge and Creativity Expo

Type I ribosome-inactivating proteins, such as gelonin, are enzymatically potent toxins but are effectively non-toxic under physiological conditions because they are unable to cross the plasma membrane[1]. Pulsed electric fields (PEF) overcome this delivery barrier by transiently permeabilizing the plasma membrane, allowing direct cytosolic entry. This enhances gelonin cytotoxicity by several thousand-fold, highlighting gelonin’s potential as an electrochemotherapy candidate[2]. Here, we present a recombinant gelonin (rGel) expression platform in E. coli with HPLC-based purification that enables reproducible protein production and structure-guided engineering.

The mature gelonin sequence (residues 47–297) was cloned into pET-32a(+) with an N-terminally fused Trx-6×His tag and TEV …

On The Extreme Complexity Of Certain Nearly Regular Graphs, Gregory P. Constantine, Gregory C. Magda

Theory & Applications of Graphs

The complexity of a graph is the number of its labeled spanning trees. It is demonstrated that the seven known triangle-free strongly regular graphs are graphs of maximal complexity among all graphs of the same order and degree; their complements are shown to be of minimal complexity. A generalization to nearly regular graphs with two distinct eigenvalues of the Laplacian is presented. Conjectures and applications of these results to biological problems on neuronal activity are described.

Requirements Of The Elderly In Interior Design Based On A Survey As A First Stage Of Smart Interior Design, Girges Sidhom, Christine Ezzat Danial

HBRC Journal

As the number of the aged in the world is expected to rise dramatically, the built environment should be adjusted to accommodate aging in place, and most of the facilities currently available are inadequate in terms of interior design requirements to support the functional and psychological needs of the aged. The purpose of this study is to establish the design needs of the aged by incorporating smart technology in interior architecture to make them safer and self-reliant. The methodology will apply a descriptive methodology by use of literature review and an analytical approach by use of a questionnaire of 153 …

Design And Construction Of Prestressed Concrete Balanced Cantilever Bridges, Ahmed S. Elareshy, Ashraf M. Osman, Ismail. M. Kamal, Amr A. Abdelrahman

HBRC Journal

Balanced cantilever concrete bridges have recently been widely used in mid and long-span bridges. This paper presents a comprehensive review of the development and design of prestressed concrete balanced cantilever (PCBC) bridges, focusing on research related to real case studies of both precast and cast-in-place box-girder bridges investigated through finite element modeling (FEM) or field measurements. The research strategy targeted peer-reviewed journal articles, conference papers, and technical reports published over the last two decades in major engineering databases. Construction methods, design methodology, and structural behavior of this type of bridge are discussed, alongside key findings on long-term response, dynamic performance, …

The Role Of Transformable Facade Technologies In Enhancing The Architectural Environment Quality In Educational Buildings, Waad Marawan Elashry, Ahmed Eltantawy Elmaidawy, Esraa Elazab

Mansoura Engineering Journal

In recent times, Educational Buildings development has become an increasingly important issue at all locations, even in the areas with the least means. Progress in the field of technology has impacted the development of architecture and modern technologies have provided for the architect enormous possibilities in the formation and design of buildings. The facade of a building plays a crucial role in providing environmental comfort, depending on the type of envelope and design. Architects and engineers need to consider many issues when working with facade designs, including environmental issues, aesthetic appearance, comfort of building occupants, and the view; these aspects …

Efficiency Comparison Of Reduced Graphene Oxide (Rgo) Composite-Incorporated Polyacrylonitrile Nanofibrous Filters For Respirable Crystalline Silica Dust And Coal Dust, Mahsa Moradi, Ashish Kakoria, Lina Zheng, Guang Xu

Mining Engineering Faculty Research & Creative Works

The health of miners working in underground mines is greatly threatened by their exposure to respirable crystalline silica (RCS) found in coal dust. While coal dust includes RCS, it is important to know the specific filtration efficiency for RCS particles compared to coal dust to improve protective measures. This study compares the filtration efficiency of reduced graphene oxide (rGO) composite-incorporated Polyacrylonitrile (PAN) nanofibrous filters at four different concentrations of rGO (0, 2, 6, and 10 wt.%) for RCS particles and coal dust. The filters were made using the electrospinning method. They were tested separately with RCS particles and coal dust …

Community Engagement Through Robotics Mentoring – Unlv, First Nv, And High School Robotics Teams, Brendan O'Toole

Community Engagement Expo Research Posters

The UNLV Robotics Mentorship program includes a two-semester course that trains students to support local high school FIRST Robotics Competition (FRC) teams. ‘ME 464 Robotics Mentoring I’ provides training in design, mentoring,  fabrication, and programming. ‘ME 465 Robotics Mentoring II’, pairs students with local high school teams to serve as technical mentors for the competition season.

Neutrosophic Probability With Dynamic Temporal Uncertainty (Nptu), Bhimraj Basumatary, Ashoke Kumar Brahma

Neutrosophic Systems with Applications

This paper introduces Neutrosophic Probability with Dynamic Temporal Uncertainty (NPTU), an extension of classical neutrosophic probability that incorporates the dimension of time. In classical neutrosophic probability, the degrees of truth, indeterminacy, and falsity are considered static. However, real-world uncertainties evolve, and their degrees change as new information becomes available. NPTU models these uncertainties dynamically, allowing for more accurate decision-making in time-varying environments. The paper explores key mathematical properties of NPTU, including entropy, distance measures, similarity measures, and Kullback-Leibler (KL) divergence, to quantify and compare temporal uncertainty states. The proposed framework is demonstrated through a case study on stock price prediction, …

Double-Valued Complex Neutrosophic Graphs, Suriyakumar G, V. J. Sudhakar, Takaaki Fujita

Neutrosophic Systems with Applications

This paper introduces a novel graph-theoretic framework, called the double-valued complex neutrosophic graph, as an extension of double-valued neutrosophic set theory. Within this framework, we investigate several important classes of such graphs, including self-complementary, strong, and full double-valued complex neutrosophic graphs, and establish a number of their fundamental properties. To clarify the proposed concepts and demonstrate their structural behavior, several relevant illustrative examples are also provided.

Neutrosophic Sets In Neural Networks: Theory, Applications, And Challenges, Vladimir Simic, Dragan Pamucar, Hafiz Muhammad Athar Farid

Neutrosophic Systems with Applications

The integration of neutrosophic sets into neural networks presents a novel approach to handling uncertainty, indeterminacy, and falsity in data. Traditional neural networks typically operate under the assumption of precise and complete data, but real-world applications often involve noisy, incomplete, or ambiguous information. Neutrosophic sets extend fuzzy logic by incorporating three components: truth, indeterminacy, and falsity, allowing for a more nuanced representation of uncertain data. This paper explores the theoretical foundations of neutrosophic sets and their integration with neural networks, highlighting the challenges in computational complexity, training, and optimization. The paper also discusses the potential applications of neutrosophic neural networks …

Emergent Operator Logic: A Foundational Framework For Dynamic Reasoning And Generative Intelligence, Mona Gharib, Abduallah Gamal, Muhammad Nawaz, Basma Nasir

Neutrosophic Systems with Applications

This paper introduces Emergent Operator Logic (EOL), a framework that treats propositions as continuous operators $F_p:X \rightarrow X$ on a complete metric state space $( X,d )$ and evaluates truth after action via a continuous valuation $V:X \rightarrow [ 0,1 ]$. Logical composition is realized by three operator-level connectives: sequential $p \circ q$(causal order), parallel $p\parallel q$(1-Lipschitz cooperative blend), and the emergent synthesis $E( p,q ) = \frac12( F_p \circ F_q + F_q \circ F_p )$, which symmetrizes non-commuting actions. We provide a Hilbert-style proof system (sound), an algebraic semantics via E-algebras, and show that the category of E-algebras is …

A Hybrid Multi-Criteria Decision-Making Approach For Sustainable Forest Fire Monitoring Using Unmanned Aerial Vehicles, Mohamed Eassa, Ahmed Abdelhafeez, Ahmad M. Nagm

Neutrosophic Systems with Applications

Unmanned aerial vehicles (UAVs) have become an effective tool for forest fire monitoring. This study evaluates UAVs for forest fire management, addressing the challenges posed by ambiguous and uncertain factors. Single-valued neutrosophic sets (SVNSs) are employed to model complex uncertainties, as they incorporate three distinct membership values: false, true, and indeterminate. The evaluation of UAVs is a multifaceted task due to the variety of factors involved. To address this complexity, multi-criteria decision-making (MCDM) methods are used. Specifically, the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are integrated with SVNS to …

Deep Learning-Based Structural Displacement Identification And Quantification Under Target Feature Loss, Lishuai Zhu, Guangcai Zhang, Qun Xie, Zhen Peng, Li Ai, Ruijun Liang, Taochun Taochun Yang

Civil Engineering Faculty Publications

Structural displacement monitoring faces significant challenges under complex environmental conditions due to the loss or degradation of target features, making it difficult for traditional methods to ensure high accuracy and robustness. Therefore, this study proposes a structural displacement identification and quantification method that integrates YOLOv8n with an improved edge-orientation gradient-based template matching algorithm. By combining deep learning techniques with traditional template matching methods, the accuracy and robustness of monitoring are enhanced under adverse conditions such as noise and extremely low illumination. Specifically, in the edge-orientation gradient matching stage, the Canny-Devernay sub-pixel edge detection technique and an improved ellipse-fitting method are …

Voltage Breakdown Strength And Energy Density Of Ceramic Srtio₃ At Cryogenic Temperatures From 295 K To 77 K, Hung Trinh, Alan Devoe, Fatih Dogan

Materials Science and Engineering Faculty Research & Creative Works

The low-temperature dependence of the DC dielectric breakdown strength (EBD) and the energy storage density (W) of capacitors, fabricated from high purity polycrystalline strontium titanate, were investigated in the temperature range from 295 K to 77 K. Test samples were constructed with a process similar to that used for multilayer ceramic capacitors (MLCCs). The permittivity, loss tangent, leakage current, and breakdown strength were measured as a function of temperature and voltage. Weibull statistical analysis was used to quantify breakdown distributions. Despite electric-field suppression of permittivity, breakdown strength increased significantly with decreasing temperatures, leading to enhanced energy density. The breakdown field …

The George-Anne Daily, Georgia Southern University

George-Anne Media Group: Newsletters & Magazines

No abstract provided.

Markov-Modulated Queueing Network For Mobile Traffic Aggregation With Threshold-Controlled Buffers, Anton A. Esin, Elmira Yu. Kalimulina

Mathematical Modelling and Numerical Simulation with Applications

We study the problem of data transmission from mobile platforms operating in high-speed transit between cellular base stations, under conditions of unstable and intermittent connectivity. Conventional queueing and connectivity models often fail to capture the combined effects of rapidly changing signal conditions, finite buffer capacity, and dynamic topology. We aim to develop a tractable yet expressive model that integrates stochastic link availability, queue dynamics, and buffer control. We propose a mathematical framework based on queues whose service intensities are modulated by a continuous-time Markov chain (CTMC) representing signal conditions along a high-speed trajectory. The core subsystem is a two-stage (aggregation …

Propagation And Interaction Of Gravity Currents Induced By Successive Release Of Two Lock Fluids, Khem Prasad Bhattarai, Subhas Karan Venayagamoorthy

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study investigates the dynamics of sequentially released gravity currents in a lock-exchange configuration consisting of two lock fluids using high-resolution numerical simulations and compares them with the classical single-lock exchange. The results demonstrate that, in a two-lock-fluid configuration, the overtaking of the lighter lock current by the heavier lock current alters the current's front dynamics, leading to complex velocity transitions. Before overtaking occurs, the front propagation is slower than in the classical single-lock-fluid case because of lower density contrast, but after overtaking, the heavier lock fluid accumulates at the head region of the current and enhances its speed. The …

Reinforcement Learning - Driven Satellite Attitude Recovery: Unknown Faults, Simulation-To-Processor In Loop, Chinmay Mirji, Saeed A Ahmadi

Student Research Symposium (SRS)

Conventional attitude control algorithms often degrade when faced with actuator faults, sensor noise, or system uncertainties. This work presents a reinforcement-learning (RL) framework for satellite attitude recovery under unknown failures, focusing on real-time deployment through a processor-in-the-loop (PIL) setup. A continuous-control DDPG agent is trained in a high-fidelity Python/Basilisk simulation environment, where domain randomization captures variations in inertia, external torque, and actuator limitations to promote robust policy learning.

Demonstrating Sysml V2’S Utility With Syside And Syson For Systems Modeling, Quinn Galen

Student Research Symposium (SRS)

This study highlights the practical utility of SysML v2’s kernel language, a formal, text based foundation for consistent, cross tool model definitions, in Model Based Systems Engineering (MBSE), using Air Traffic Management (ATM) as an illustrative example. SysIDE, an open source textual editor, enables rapid model creation with the kernel’s concise syntax, allowing users to define system components and behaviors (e.g., ATM radar or flight path interactions) with real time validation. SysON, a web based graphical tool, complements this by facilitating collaborative visualization of system architectures. Using ATM as an example case, we can showcase how the kernel language enhances …