Digital Commons Network^™

Dodaf-Opm-Sd Cross-Layer Automated Mapping Method Based On A Unified Semantic Bridge, Lei Cheng, Gang Xiao, Binbin Wang, Siming Peng, Haozhe Liang, Xiangwu Gong

Journal of System Simulation

Abstract: To address the problems of the inability of DoDAF views to directly drive simulations and the insufficient cross-layer semantic alignment and consistency verification, a DoDAF-OPM-SD cross-layer semantic automated/semi-automated mapping and verification method was proposed in this paper. Targeting tactical/operational-level problems dominated by "conservation+feedback+time delay", the proposed method reduced manual mapping under expert adjudication based on a "minimal executable view set". The object-process methodology served as a semantic bridge to map architectural elements into the stock-flow-feedback structures of system dynamics; semantic embedding disambiguation, integer programming harmonization, and K-nearest neighbor parameter completion were integrated; end-to-end traceability was connected through traceability identifiers, …

Design And Implementation Of Hdrt Real-Time Simulation System, Huiji Zheng, Guangsen Wang, Qing Liu, Kang Wang, Zhiwei Wang, Zhenyu Zhang, Shuo Wang, Zhu Liu

Journal of System Simulation

Abstract: In view of the real-time simulation requirements of large-scale complex systems such as power electronics, a hidden dragon real-time(HDRT) simulation system was developed. The strict time constraints of simulation tasks were guaranteed based on a resource-dedicated real-time scheme, supporting fixed-step and multi-rate simulations from the second level to the hundred-nanosecond level. A hybrid CPU-field programmable gate array(FPGA) architecture was adopted to accelerate computation. The system could utilize multiple simulators for parallel simulation and realized microsecond-level real-time data interaction between simulators through a dedicated PCIe switch. A single simulator could be expanded through I/O interface equipment, supporting a maximum input …

Numerical Simulation Of Water Tank Solidification In A Firefighting Aircraft Under High-Altitude Cold-Soak Conditions, Guanmian Liu, Zhihang Cheng, Hejun Qin, Kangzhi Yang, Qing Wen, Kun Gao

Journal of System Simulation

Abstract: A systematic numerical simulation study was conducted to address the issue of internal water tank solidification in firefighting aircraft under high-altitude low-temperature conditions. Based on computational fluid dynamics methods, a solidification-melting model considering fluid-structure interaction heat transfer and phase change processes was adopted. Through reasonable simplification of the complex geometric model, a quasi-three-dimensional computational model suitable for engineering analysis was developed. The influence laws of key parameters, including high-altitude cold-soak temperature, ground initial water temperature, and cold-soak time, on the freezing characteristics of the water tank were investigated. Combining with the parameter influence laws, a safety criterion using the …

Combat Effectiveness Evaluation Of Anti-Ship Missiles For Intelligent Autonomous Recognition, Long Zhang, Xuanming Feng, Zhen Lei, Bo Yang, Ying Wang

Journal of System Simulation

Abstract: To address the core issues of poor adaptability of static fusion strategies in existing recognition models, as well as the simplistic evaluation system and its disconnection from dynamic confrontation requirements, a practical four-dimensional evaluation system encompassing "recognition accuracy, antijamming stability, decision timeliness, and modal complementarity" was constructed, and an operational effectiveness composite index (OECI) capable of dynamically adapting to tactical scenarios was proposed. A multimodal dynamic attention fusion network (MDA-Net) for anti-ship missiles in complex confrontation environments was designed. Through heterogeneous feature decoupling, dynamic weighting of cross-modal attention, and a hierarchical gating decision mechanism, the autonomous evaluation and adaptive …

Infrared Image Generation Method Based On Improved Cyclegan, Qiqi Jin, Xiang Zhang, Li Gao, Lin Zhang, Junliang Yan, Peiyao Li

Journal of System Simulation

Abstract: To address the problems in current infrared image generation such as insufficient contrast between target and scene, excessively large discrepancies from real scenes, indistinct thermal source features, and great difficulty in constructing measured infrared image datasets, an improved CycleGAN-based infrared image generation method was proposed. By optimizing the network structure of the generator and adding a non-local module and a CBAM convolutional attention mechanism into the generator, the extraction capability of CycleGAN for infrared features was enhanced, enabling the network to capture the subtle features of targets more accurately; a perceptual loss function was introduced to improve the detail …

Cost-Effectiveness Evaluation Of Artificial Intelligence-Assisted Chest Radiograph Interpretation For Tuberculosis Screening In Rural Health Units In The Philippines, Harold Henrison C. Chiu, Bryan Christopher C. Lao, Gloanne C. Adolor

Graduate School of Business Publications

Background: Tuberculosis remains a major public health burden in the Philippines, where diagnostic delays are amplified by limited radiology capacity in rural health units (RHUs) and geographically isolated and disadvantaged areas (GIDAs). Computer-aided diagnosis (CAD) using artificial intelligence (AI)-assisted chest radiograph interpretation may shorten the screening pathway and reduce reliance on scarce specialist readers. However, its economic value for RHUbased tuberculosis screening has not been fully evaluated.
Methods: We developed a decision-tree cost-effectiveness model in Microsoft Excel 365 to compare AI-assisted chest radiograph interpretation with conventional manual radiologist or teleradiology interpretation among a theoretical annual cohort of 1,000 presumptive tuberculosis …

Advancing Sdg 9 Through Ai-Powered Waste Diversion, Ally Murphy

Goal 9: Industry, Innovation and Infrastructure

No abstract provided.

Paleolimnology And Diatom Taxonomy From Lake Tanganyika, Sristika Adhikari

All-Inclusive List of Electronic Theses and Dissertations

Lake Tanganyika is one of the world's largest freshwater ecosystems, supporting rich aquatic biodiversity and providing several ecosystem services to surrounding communities. Environmental changes such as rising lake surface temperatures, pollution, and land-use alterations threaten the lake’s sustainability. This research examines spatial and temporal variations in nutrient dynamics and primary productivity of Lake Tanganyika using diatom assemblages from multiple locations. Our findings indicate reduced nutrient levels and longer stratification periods in the lake’s central basin during most of the Common Era, as indicated by a remarkable increase in the relative abundance of long, needle-shaped planktonic Nitzschia species. In the southern …

Visualizing The Phase Space Of Two Interacting Spherical Magnets Via Lagrangian Descriptors, Matthew Pontius

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis studies the motion of one spherical magnet sliding on another fixed spherical magnet. Although the setup is simple, the resulting motion can range from regular and predictable to chaotic as the energy increases. To understand this behavior, mathematical tools are used to visualize how all possible motions are organized in phase space. These methods reveal patterns such as stable regions, repeating motions, and chaotic trajectories. The results show how order and chaos coexist in this system and provide insight into how small changes in the initial conditions can lead to very different outcomes.

Human-Centered Electric Vehicle Adoption Framework For Smart Mobility: Modeling Perceived Range And Charging Anxiety As A Psychological Barrier, Fatemeh Nazari, Abolfazl (Kouros) Mohammadian, Thomas Stephens

Civil Engineering Faculty Publications

Electric vehicles (EVs) offer a transformative pathway toward reducing the environmental, economic, and health-related externalities of internal combustion engine vehicles in urban settings. Despite substantial advances in battery technology, charging infrastructure expansion, and supportive policy incentives, EV penetration remains limited which poses challenges for smart and sustainable mobility planning. A critical yet insufficiently modeled barrier to adoption lies in the psychological perceptions surrounding electric driving range and charging reliability, which is commonly framed as “range anxiety,” but more broadly reflecting perceived range and charging anxiety. To address this gap, this study introduces a latent psychological construct capturing individuals’ perceived range …

Llm-Based Early Rumor Detection With Imitation Agent, Fengzhu Zeng, Qian Shao, Ling Cheng, Wei Gao, Shih-Fen Cheng, Jing Ma, Cheng Niu

Research Collection School Of Computing and Information Systems

Early Rumor Detection (EARD) aims to identify the earliest point at which a claim can be accurately classified based on a sequence of social media posts. This is especially challenging in data-scarce settings. While Large Language Models (LLMs) perform well in few-shot NLP tasks, they are not well-suited for time-series data and are computationally expensive for both training and inference. In this work, we propose a novel EARD framework that combines an autonomous agent and an LLM-based detection model, where the agent acts as a reliable decision-maker for \textit{early time point determination}, while the LLM serves as a powerful \textit{rumor …

A Deep Reinforcement Learning Framework For Dynamic Order And Rack Scheduling In Robotic Mobile Fulfillment Systems, Lingjun Wang, Bayi Cheng, Zhiguang Cao, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Robotic mobile fulfillment systems play a vital role in modern e-commerce, but their efficiencydepends on overcoming a critical challenge: coordinating orders and racks effectively under dynamicorder arrivals, diverse delivery deadlines, and resource sharing among multiple stations. This papertackles the resulting dynamic order and rack scheduling problem and proposes an intelligentscheduling framework centred on deep reinforcement learning. At its core is TriNet-PPO, whichtrains a scheduling policy using TriNet, a tripartite graph neural network encoder tailored to capturethe many-to-many relationships among orders, racks, and items. Furthermore, we introduce IPCSA,an integer programming-based cooperative scheduling algorithm that maps station-level actionpreferences to conflict-free joint decisions …

Optimal Scheduling Of Virtual Power Plants Considering Photothermal Power Stations And Hydrogen Energy Utilization, Yousong Chen, Ruofa Cheng, Yi Liu, Yi Zhang, Zhihao Zuo

Journal of System Simulation

Abstract: To enhance the operational stability and low-carbon performance of virtual power plants (VPPs) with high shares of renewable energy, a coordinated dispatch model integrating concentrated solar power (CSP) plants with power-to-gas (P2G) and carbon capture is developed. An optimal VPP scheduling strategy is proposed, combining a stepped carbon trading mechanism with a compensation coefficient and dynamic hydrogen blending. To address multi-source uncertainties in wind power, CSP power, and loads, an envelope boundary model is used for simulation. Information gap decision theory (IGDT) is applied to provide customized solutions for decision-makers with different risk preferences. A bi-objective optimization model is …

Fault-Tolerant Control Method For All-Type Actuator Faults Of Evtol Aircraft, Juan Wang, Guorui Li, Zhiyong Fan, Huijie Chen

Journal of System Simulation

Abstract: To address all-type actuator faults, especially nonlinear distortion issues, in multi-rotor eVTOL aircraft, a novel fault-tolerant control method was proposed. A fault function was established at the rotor speed level, and a fault-tolerant control algorithm combining dynamic robust nonsingular fast integral terminal sliding mode with a high-order finite-time disturbance observer was designed to achieve fault-tolerant control through rotor redundancy allocation. The nonsingular fast integral terminal sliding mode algorithm was improved, and a dynamic system containing actuator faults and their derivatives was constructed via a dynamic surface to achieve system convergence within finite time, avoiding the singularity and chattering problems …

A Method For Assessing The Contribution Degree Of An Aviation Delivery System And Identifying Key Equipment, Xiaofeng Liu, Chengze Jiang, Xingyu Chen, Deyin Jiang, Bolin Shang, Bifeng Song

Journal of System Simulation

Abstract: Based on the delivery efficiency and delivery quality, a general aviation delivery system effectiveness evaluation model was constructed, and a calculation method of system contribution degree based on efficiency was given. By combining the system calculation experiment and simulation experiment based on agent-based modeling and simulation (ABMS), the design idea of the Monte Carlo simulation experiment for key equipment identification and equipment technology development trend analysis was sorted out, and the key equipment identification method based on ABMS and contribution evaluation was proposed. By taking the intercontinental long-range aviation delivery mission as an example, a variety of simulation experiments …

Optimization Of Node Deployment For Three-Dimensional Heterogeneous Wsn In Elongated Structural Space, Jiguang Yang, Jiuyuan Huo, Fang Cao, Cong Mu

Journal of System Simulation

Abstract: To achieve effective coverage of key monitoring points in an elongated structural space, a heterogeneous wireless sensor network(HWSN) deployment optimization method combining the virtual force algorithm(VFA) and multi-strategy improved whale optimization algorithm(MSIWOA), namely HVF-MSIWOA, was proposed. A dynamic adaptive weight mechanism and a t-distribution perturbation operator with heterogeneous degrees of freedom were designed, enabling the whale optimization algorithm(WOA) to balance global exploration and local exploitation and jump out of local optima; combining the topological characteristics of the elongated space and node density distribution, an adaptive virtual force distance threshold between heterogeneous nodes was constructed; the mapping relationship between network …

Three-Dimensional Gaussian Reconstruction Of Large-Scale Scenes Under Multi-View Geometry Constraints, Haohao Cui, Yanqiang Di, Qing Liu, Xianguo Meng

Journal of System Simulation

Abstract: To enhance the geometry reconstruction quality of the GS algorithm in large-scale scene reconstruction, an optimization method constrained by multi-view geometry reconstruction results was proposed. 2D Gaussian planes were used as geometric primitives to overcome depth anisotropy, and dense depth maps generated by DUSt3R and aligned by sparse point clouds were introduced as constraints. By designing a multi-stage optimization strategy that decouples geometry and rendering, the gradient conflict problem in multi-objective training was solved. Experiments on the MatrixCity dataset indicate that the method surpasses comparison methods in related indicators of geometry reconstruction quality and rendering quality in large-scale scenes. …

Aqqd: Annotated Quranic Qira’At Dataset, Linda Smail, Mohammed Lataifeh, Md Sohazur Islam Sozib, Arthur Diniz De Souza

All Works

AQQD (Annotated Quranic Qira'at Dataset) is an open audio dataset of Quranic recitations annotated across canonical Qira'at styles. The dataset is designed to support research in machine learning, speech and audio processing, computational linguistics, and Quranic studies. The current release contains 24,183 WAV audio files from 309 reciters and covers 70 selected Quranic Surahs segmented into representative verses and phonetic variation points. Of these, 23,111 recordings were collected from publicly available sources, including official reciter websites, the Midad repository, MP3Quran, and verified YouTube channels, while an additional controlled subset of 1,072 recordings was obtained from a single reciter recorded as …

Ultraviolet Imaging Of Sr 12 C With Hst/Wfc3: Accretion And Variability Of A Giant Planet At The End Stages Of Growth, Claire O. Finley, Brendan P. Bowler, Ya-Lin Wu, Adam L. Kraus, Yifan Zhou, Yuhiko Aoyama, William Best, Ian Czekala, Catherine C. Espaillat, Katherine B. Follette, Gregory J. Herczeg, Raquel A. Martinez, Connor E. Robinson, Quang H. Tran, K. Ward-Duong

Astronomy: Faculty Publications

Many details of the gas accretion phase during giant planet formation remain untested. We present new 0.2–0.7 μm UV-through-red optical imaging of the young, wide-orbit planetary-mass companion SR 12 c from the Wide Field Camera 3 (WFC3) instrument on board the Hubble Space Telescope. SR 12 c exhibits strong accretion-related continuum excess blueward of∼5000 Å and clear signs of the Balmer jump at 3646 Å. We derive a total accretion luminosity of1.65 ±0.19× 10⁻⁵L_⊙and a mass accretion rate of 8 ±2 × 10⁻¹² M_⊙yr⁻¹. Based on its mass and age,SR12 c …

A Simulation Assessment Of The 'Law Of One Price', Caleb Wilkins

Computational and Data Sciences (MS) Theses

The ‘law of one price’ is an appealing notion regarding pricing of tradeable commodities that are priced in different currencies. It states that the prices of the same good in different markets should be equal after adjustment for exchange rates and that equality should persist through exchange rate fluctuations.

My research simulates the market conditions that should precipitate the ‘law of one price.’ Data was obtained from the simulated trade between algorithmic artificial intelligence agents that operated under induced boundedly rational market behaviors. Trade took place in two initially separate markets, a high-price market with a higher equilibrium price and …

Spatial Prediction Under Uncertainty: Methodological And Computational Advances In Bayesian Maximum Entropy, Kinspride K. Duah

All Graduate Theses and Dissertations, Fall 2023 to Present

Environmental decisions such as infrastructure design, water management, and snow load estimation depend on spatial data that are often incomplete or uncertain. In many cases, measurements are not exact values but ranges, reflecting limitations in data collection methods. Traditional mapping techniques typically simplify these uncertain measurements, which can lead to less accurate predictions. This dissertation introduces improved statistical tools for making spatial predictions when data are uncertain or partially known. By utilizing a framework called Bayesian Maximum Entropy (BME), this research demonstrates how exact measurements and range-based data can be combined in a mathematically consistent way. The work demonstrates that …

Method Validation Of The Cdc Bottle Bioassay And A Historical Record Of Polycyclic Aromatic Hydrocarbons In Glacier National Park, Evah F. Peard

All Graduate Theses and Dissertations, Fall 2023 to Present

Certain contaminants can persist in the environment for long periods of time, build up within living tissues, travel far from their origin, and harm both ecosystems and organisms. This thesis focuses on two types of contaminants: insecticides and polycyclic aromatic hydrocarbons (PAHs). Insecticides are manufactured to control pests while PAHs are found in oil and gas products and can be produced by industry, vehicle engines, and wildfires. Understanding how harmful these contaminants are and where they end up in the environment is critical for protecting environmental health.

First, I evaluated a widely used test developed by the Centers for Disease …

Applications Of Machine Learning To Gas Plume Analysis In Longwave Infrared Hyperspectral Images, Scout C. Jarman

All Graduate Theses and Dissertations, Fall 2023 to Present

Each pixel from a hyperspectral camera measures the intensity of light over a continuous range of wavelengths, which is in contrast to traditional color cameras, which just measure the intensity of red, green, and blue wavelengths of light. Longwave infrared hyperspectral images can be used to detect gases from a distance by measuring how different materials emit and absorb heat. This makes them useful for applications such as monitoring industrial emissions or locating hazardous gas leaks. In practice, however, gas signatures in these hyperspectral images are often weak and easily obscured by variations in the background scene, making reliable identification …

Assessing Ecological Integrity Of Streams Across The Western U.S., Jennifer L. Courtwright

All Graduate Theses and Dissertations, Fall 2023 to Present

Large-scale assessments of stream health (ecological integrity) are required by policies such as the U.S. Clean Water Act and provide critical information needed to properly manage public lands. Our ability to quantify the ecological condition of streams in the western U.S. and identify the causes of degraded conditions has previously been impeded by a lack of standardized large-scale datasets, high natural temporal and spatial variability of ecological attributes, and poor-quality land use data. I compiled large-scale monitoring datasets and built models to predict the values of ecological attributes (metrics) at a given site in the absence of human impacts. In …

The Role Of Heterogeneity In Earthquake Rupture Dynamics: Insights From Friction Experiments On A 1-Meter Laboratory Fault, Alejandro Aguilar

All Graduate Theses and Dissertations, Fall 2023 to Present

Tectonic faults are made of many kinds of rocks and minerals, creating natural weak and strong zones along faults where earthquakes occur. These differences can affect how faults move, including whether slip occurs slowly and quietly or suddenly and destructively during an earthquake. However, it is not fully understood how these variations influence when earthquakes start, how fast they spread, and whether they stop or grow into large ruptures. This research studies how different fault materials interact during earthquake slip. Using a large laboratory machine that simulates fault movement under realistic conditions, we recreate earthquake processes and closely measure how …

Investigation Of Yy Production Methods For Invasive Channel Catfish Ictalurus Punctatus Population Management, Andrew M. Wisniewski

All Graduate Theses and Dissertations, Fall 2023 to Present

Aquatic invasive species are one of the leading causes of native fish declines in the Southwestern United States. Channel Catfish Ictalurus punctatus were introduced into the Colorado River Basin, including the San Juan River, New Mexico, Colorado, and Utah for fishery enhancement during the 20th century. This introduction has contributed to the decline of native species and despite intensive mechanical removal efforts, the Channel Catfish population has persisted in the San Juan River. The Trojan Sex Chromosome approach is a promising eradication strategy that proposes the production and release of Trojan sex chromosome carriers (YY) to skew a targeted population’s …

Understanding And Predicting Precipitation Characteristics In The United States Through Machine Learning, Numerical Modeling And Measurements, Cody Luther Ratterman

All Graduate Theses and Dissertations, Fall 2023 to Present

Precipitation is one of the most important yet uncertain variables in the climate system. It varies dramatically in terms of timing, accumulation, rate, and phase, depending on location, season, circulation patterns, and atmospheric conditions. Precipitation forecasts, especially snowfall, are essential to supporting drought mitigation and water management in the Intermountain West. Because rainfall and snowfall lead to opposite effects on snowpack, accurately partitioning rain and snow is important to estimate snowpack levels, winter recreation, mountain ecosystems and runoff. The research findings in this dissertation have advanced the understanding and prediction of precipitation and snowpack in the U.S. by addressing the …

A Finite Element Model To Analyze Crack-Tip Fields In A Transversely Isotropic Strain-Limiting Elastic Solid, Saugata Ghosh, Dambaru Bhatta, S. M. Mallikarjunaiah

School of Mathematical & Statistical Sciences Faculty Publications

This paper presents a finite element model for the analysis of crack-tip fields in a transversely isotropic strain-limiting elastic body. A nonlinear constitutive relationship between stress and linearized strain characterizes the material response. This algebraically nonlinear relationship is critical as it mitigates the physically inconsistent strain singularities that arise at crack tips. These strain-limiting relationships ensure that strains remain bounded near the crack tip, representing a significant advancement in the formulation of boundary value problems (BVPs) within the context of first-order approximate constitutive models. For a transversely isotropic elastic material containing a crack, the equilibrium equation, derived from the balance …

Prediction Of Pasture Condition In The Kimberley Rangelands Of Western Australia Using Simple Classification Tree Models, Ben Nestor, Kath Ryan, Charles Martin, Philip Thomas, Chris Hetherington, Matthew Fletcher, Robert Sudmeyer, Karyn Reeves

Natural Resources Research Articles

Pasture condition assessments assist pastoralists, regulators, and policy makers in making informed decisions around livestock production and the preservation of natural resources in the Kimberley rangelands of Western Australia (WA). Reliable qualitative assessments of pasture condition require assessors with extensive expertise, which means frequent and reproducible assessments can be difficult to achieve. To develop a quantitative approach that can complement existing qualitative assessment approaches in the Kimberley, we investigated the use of simple classification tree models to predict pasture condition using assessment data from the Western Australian Rangeland Monitoring System (WARMS). Quantitative traits were derived from WARMS observation data for …

Greenhouse Gas Flux Response In Biochar- And Compost-Amended Lawn Soils Under Simulated Water Saturation Conditions, Angel Salinas, Chu-Lin Cheng, Engil Pereira, Rafael M. Almeida, James Jihoon Kang

School of Earth, Environmental, & Marine Sciences Faculty Publications

Understanding greenhouse gas emission dynamics in lawn soils is important for improving climate change mitigation strategies in urban and suburban landscapes. In this greenhouse mesocosm study, carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes were measured from 12 turfgrass soil columns arranged in an unreplicated, completely randomized 4 × 3 factorial design. Four amendment treatments (biochar, compost, bio-com [1:1 volume ratio of biochar and compost], and unamended control) were combined with three water-table conditions (full saturation, half saturation, and unsaturated), with a single column representing each treatment combination. Columns were irrigated at 1 cm day−1 for 24 days, …