Digital Commons Network^™

A Model For Predicting Coal Mining-Induced Surface Subsidence During Theinitial, Active, And Decline Stages, Zhang Liangliang, Liu Xiya, Cheng Hua, Du Shaoneng

Coal Geology & Exploration

Objectives and Methods Presently, there remains a lack of theoretical models for predicting the coal mining-induced surface subsidence during the initial, active, and decline stages. Given this, this study derived the time-varying exponential function of the ratio of maximum to dynamic surface subsidence first using measured data from seven coal mines. Accordingly, an improved Knothe time function model was established. Then, the impacts of the model parameters on dynamic surface subsidence W(t), subsidence velocity v(t), and subsidence acceleration a(t) were analyzed. Subsequently, based on the improved Knothe model and the critical …

Soil Microbial Biomass And Organic Carbon Fractions Under Different Natural Restoration Years In Arid Coal Mining Subsidence Areas In Xinjiang, China, Xiao Li, Bi Yinli, Wang Dongdong, Li Jianfeng, Gong Hanlin, Deng Aojuan, Hou Wensheng

Coal Geology & Exploration

Objective This study aims to elucidate the influence of the natural restoration process on changes in soil microbial biomass and organic carbon fractions in coal mining subsidence areas. This effort will provide a crucial scientific foundation for understanding the natural ecological restoration process and carbon accumulation dynamics in arid coal mining subsidence areas.Methods Arid coal mining subsidence areas in Xinjiang, China were investigated in this study. Using the space-for-time substitution approach, sample plots were selected from an unmined area and areas having undergone natural restoration for one, three, eight, and 12 years. Subsequently, systematic analyses were conducted on the …

A Method For Fine-Scale Identification Of Collapse Columns Based On Offset Vector Tile Domain Seismic Data, Zhang Guangzhong, Liu Song, Shan Rui, Cai Wenrui

Coal Geology & Exploration

Objectives and Methods The YQ mining area in the Qinshui Basin is characterized by complex seismic and geological conditions, as well as well-developed collapse columns and flexure structures. Consequently, conventional three-dimensional (3D) seismic exploration fails to meet the precision requirements for safe coal mining. By constructing a physical model based on the actual geological conditions of the study area, this study conducted forward modeling for the seismic responses of collapse columns under varying azimuths. Accordingly, the azimuthal anisotropy of the collapse columns were systematically analyzed. By employing a regular noise suppression technique based on curvelet transform, combined with prestack migration …

Application Of A Generative Adversarial Network To Super-Resolution Reconstruction Of Fracture Images In Logging-While-Drilling Electrical Resistivity Imaging, Han Sen, Shen Chuanhai, Xu Chen, Tian Yimeng, Zhao Biao, Wang Ze, Liu Yongkang, Kang Zhengming

Coal Geology & Exploration

Objective Logging-while-drilling electrical resistivity imaging (LWD-ERI) enables the intuitive presentation of geobodies near wellbores in images, representing an important approach to the fine-scale evaluation of stratigraphic parameters while also providing significant geological guidance during the drilling of fractured reservoirs. However, this technique faces the challenge of low image resolution in real-time data processing due to its limited well-to-surface data transmission rates, exerting adverse impacts on the qualitative identification of wellbore fractures and the quantitative evaluation of their parameters. To address this issue, this study proposed a super-resolution image reconstruction method based on a generative adversarial network (GAN), aiming to achieve …

A Surface Wave Inversion Method Incorporating Interface Constraints And Its Application In The Assessment Of Ground Vibrations Caused By Mining-Induced Seismicity, Li Cheng, Qian Changbao, Liu Ying, Cheng Yi, Ni Shengjun, Yao Huajian

Coal Geology & Exploration

Objective In mining areas of western China, underlying interfaces with significant fluctuations affect seismic exploration accuracy while also posing challenges to the assessment of ground vibrations triggered by dynamic hazards such as mining-induced seismicity. To enhance the characterization of shallow velocity structures and to provide support for dynamic hazard prevention and control in mining areas, this study developed an inversion method incorporating prior information about geological interfaces.Methods A dense array consisting of 489 single-component and 108 three-component seismometers was deployed within a mining area in Longkou Town, Junggar Banner, Inner Mongolia. Accordingly, continuous ambient noise data for about one …

Mould Risk Prevention In Healthcare Facilities In Hot And Humid Climates Through Acmv Air Supply Parameter Optimisation: Development And Validation Of A Multi-Objective Optimisation Framework, Jiang Kaiyun

Student Works (2020-2029)

Air conditioning mechanical ventilation (ACMV) supply parameters—such as airflow rate, temperature, and humidity—significantly influence indoor thermal and hygrometric conditions, influencing airflow patterns and mould proliferation. In healthcare facilities, mould poses significant health risks, particularly for immunocompromised patients, contributing to respiratory issues, allergic reactions, and infections. While ACMV systems are central to infection control and indoor air quality, conventional designs often fall short in hot and humid climates. Existing practices typically prioritise high air change rates (ACH) without sufficient dehumidification, underestimate humidity control, and assume spatial homogeneity, overlooking microclimates conducive to localised mould growth. To address these limitations, this research develops …

Secure Machine Learning In Networking Systems, Wenwei Zhao

USF Tampa Graduate Theses and Dissertations

With the rapid integration of Machine Learning (ML) into networking systems, ensuring the security and trustworthiness of these intelligent frameworks has become a paramount concern. While ML offers unprecedented capabilities in spectrum management and collaborative learning, it also introduces novel vulnerabilities that can be exploited by sophisticated adversaries. This dissertation investigates and addresses critical security challenges across three key dimensions of ML-driven networking: adversarial spectrum sensing, the security of privacy-preserving unlearning processes, and efficient post-attack model recovery.

First, we address the threat of adversarial spectrum attacks in cognitive radio networks, where malicious nodes manipulate sensing reports to disrupt spectrum access. …

Drone Based Operational Cloud Seeding, Jared Smith

Spring Runoff Conference

Cloud Seeding: Next Generation Operations and Validation

What is Winter Cloud Seeding? 

• The act of introducing favorable dust particles into a cloud to promote ice crystal nucleation 
• Requires naturally occurring clouds and cold temperatures 
• Aimed at enhancing winter snowpack

Great Salt Lake Basin Integrated Plan – Longterm Actions, Jake M. Serago

Spring Runoff Conference

GSL’s water level is in long-term decline. Water users face shortages and challenges. Increased temperatures, greater precipitation extremes and population changes are stressing water supplies in the basin. 84% of Utah residents think the Government is accountable for resolving issues facing GSL.

Agricultural Water Leasing Opportunities & Updates, Hannah Freeze

Spring Runoff Conference

The framework for this leasing program is based on depletion savings from conservation practices not surplus or tailwater

Pheasant Forever Loan Program, Will Benkelman

Spring Runoff Conference

Bear River Watershed Community Conservation Program

Our Mission: Pheasants Forever (PF) and Quail Forever’s (QF) mission is to conserve pheasants, quail, and other wildlife through habitat improvements, public access, education, and conservation advocacy.

Logan River Watershed Draft Environmental Impact Statement, Zan Murray

Spring Runoff Conference

Agenda:

Program Overview: PL-566 & NEPA

Project Need and Purpose

Project Alternatives

Preferred Alternative Costs and Benefits

NEPA Timeline/Current Schedule

Questions

Cache Water District Conservation Program, Autumn Matthews

Spring Runoff Conference

Conservation and Education Programs.

Conservation Goals:

Increase community awareness through outreach, workshops, and community programs that support water conservation.

Expand and improve programs that encourage water savings and more efficient water use across the community.

Help residents save money by promoting water efficiency and reducing unnecessary water use.

Water Supply Update, Jordan Clayton

Spring Runoff Conference

Snowpack and Water Supply Conditions.

>95% of the water we use in Northern Utah comes from snow. Therefore, it’s critically important to quantify how much water is stored in our snowpack.

Legislative Summary Panel, Brian Steed, Scott Sandall, Jill Koford, Joel Ferry

Spring Runoff Conference

Legislative updates provided at the Spring Runoff Conference 2026.

Water In 2026, Spencer Cox

Spring Runoff Conference

Presentation by Utah Governor Cox.

Rigorous Electromagnetic Beamforming Simulations For Realistic Vehicular-To-Infrastructure (V2i) Scenarios In 5g Systems, Mohanad Hussam Aldean Ahmed Almuzian

Theses and Dissertations

Millimeter-wave (mmWave) Vehicle-to-Infrastructure (V2I) communication is a key enabling technology for next-generation intelligent transportation systems, offering high data rates and low latency to support safety-critical and autonomous driving applications. However, mmWave communication at 28 GHz suffers from severe path loss, sensitivity to blockage, and strong dependence on antenna directivity and beam alignment, particularly in complex urban environments. As a result, advanced beamforming and multi-antenna techniques are essential to ensure reliable and high-capacity V2I links. This thesis investigates mmWave V2I communication performance using realistic electromagnetic modeling and beamforming techniques. Full-wave antenna simulations and deterministic ray-tracing are employed using Ansys Electronics Desktop, …

Marine Vehicle Dynamics Using Koopman Operator Theory With Hybrid Observables, Mikhalib A L Green

LSU Master's Theses

Accurate modeling of marine vehicle dynamics remains challenging due to strong nonlinear hydrodynamic effects, environmental disturbances, and sensitivity to configuration changes, particularly for small-scale platforms. Classical physics-based models require extensive parameter identification and often exhibit degraded performance outside narrow operating regimes, while purely data-driven approaches may lack structure or impose high computational cost. This thesis presents a data-driven Koopman operator framework with hybrid observables for modeling the dynamics of unmanned marine vehicles. The proposed approach combines structured monomial observables with a learned neural network embedding to construct a lifted state representation in which the nonlinear vehicle dynamics are approximated by …

Large-Scale File Fragment Classification Via Multi-View Learning, Samuel Hildebrand

LSU Master's Theses

File reassembly is one of the most fundamental tasks in digital forensics, enabling recovery of data from potentially damaged storage media even when file system metadata is unavailable. This thesis reviews more than two decades of work in the realm of file carving, with a particular focus on fragmented file carving, which remains a focus of research, and file fragment classification, a principal component of fragmented file carving. This thesis serves a literature review of both file carving and fragmented file carving, surveys the massive amounts of data needed for the task of fragment classification and the datasets that serve …

How Do Water Utilities Meet Growing Demand And Maintain Resilience Through Water Reuse? A Systems Thinking Approach, Elizabeth F. Vicario

USF Tampa Graduate Theses and Dissertations

Water and wastewater utility management is becoming increasingly complex due to factors like urbanization, climate change, new regulations, and rising costs. Utility leaders must balance competing political and financial pressures while managing aging infrastructure, rising demand, climate resilience planning, and customer concerns about affordability. Reuse of treated wastewater has emerged as a promising solution to address scarcity, declining source water quality, and new regulations on wastewater discharge in the United States. However, water reuse is not one-size-fits-all, and bespoke solutions are needed to optimize economic, environmental, and social returns from this finite resource. Despite growing interest, little is known about …

Critical Heavy Metal Contamination In The Tigris River, Baghdad: A Comprehensive Assessment Using The Metal Index (Mi), Talib Kamil Abed, Abass J. Kadhem, Muwafaq Hussein Al-Lami

AUIQ Technical Engineering Science

One of the most important rivers in Iraq is the Tigris River, which serves as the primary source of drinking water and irrigation for agricultural purposes. In recent events, researchers have identified growing concerns about heavy metal contamination in the river. To decide the status of the Tigris River, the metal index (MI) was used in this study. To conduct this study, three locations were chosen along the river, and eight likely harmful heavy metals were examined: iron (Fe), lead (Pb), nickel (Ni), zinc (Zn), chromium (Cr), cadmium (Cd), manganese (Mn), and copper (Cu). The results were worrying. The metal …

Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies, Kara Combs, Lance E. Champagne, Bruce A. Cox, Christine M. Schubert Kabban, Trevor Bihl, Grace Lemming

Faculty Publications

Analogical reasoning is an increasingly popular, lightweight solution to enable large language model (LLM)-level reasoning without computational complexity. Still, it has yet to be adopted due to its reliance on strictly hand-formatted data. Therefore, we propose Analogy2KG (“Analogy to Knowledge Graph”), as an automatic pipeline that transforms text into a KG format via a fine-tuned version of information extraction (IE) algorithms for long-text analogies. The need to verify that the complex underlying analogical structure of the data is maintained was done via paired samples tests in the creation and validation of this pipeline. Graph density was used to evaluate the …

Enhanced Cuckoo Search-Based Optimization For Single Distributed Generation Placement And Sizing In Radial Distribution Systems, Samson Oladayo Ayanlade, Abdulrasaq Jimoh, Richard Oladayo Olarewaju, Ignatius Kema Okakwu, Israel O. Adejumobi, Joseph B. Samson, Oluwadare A. Adebisi, Oluwadare O. Akinrogunde

Al-Bahir

This paper presents an Enhanced Cuckoo Search Algorithm (ECSA) to optimally place and size Distributed Generation (DG) in radial distribution systems to minimize real power loss within operating constraints. The proposed ECSA has exponentially decaying adaptive Lévy flights, constraint-aware solution repair with dynamic penalty coefficients, and diversity-directed stochastic replacement to enhance search robustness and convergence speed. It was tested with 30 independent runs on the IEEE 33-bus, IEEE 69-bus, and a practical Nigerian 32-bus distribution network. The simulations show that the ECSA lowers the active power loss of the IEEE 33-bus system from 201.58 kW to 102.75 kW (49.03%), and …

Identification Of Thruster Faults In Underwater Vehicles By Using Custom Encodings In Spiking Neural Networks, Donovan Gegg

LSU Master's Theses

Autonomous Underwater Vehicles (AUVs) are untethered robotic platforms used for tasks such as seafloor mapping, infrastructure inspection, and environmental monitoring. Recent technological advances have produced smaller, more affordable platforms, broadening access to research teams and small companies alike. This miniaturization comes at the cost of them handling drawbacks associated with a more compact machine such as reduced battery capacity as well as limited processing and sensing capabilities. These constraints make small-sized marine vehicle’s reliability critical as they can cause malfunctions, making the loss of a vehicle more likely. Actuator faults are particularly consequential as unintended and unstable control in an …

Graph-Based And Uncertainty-Aware Machine Learning For Academic Performance Prediction, Anca Olivia Muresan

Electronic Theses and Dissertations 2020 - Present

Early identification of students at risk of academic failure is essential for timely pedagogical interventions and reducing dropout rates. While Artificial Intelligence (AI) has significantly advanced predictive modeling in education, two primary challenges persist: effectively modeling the complex, evolving relationships within heterogeneous educational data, and ensuring the reliability of model outputs for high-stakes decision-making. This dissertation addresses these challenges by proposing a comprehensive framework for early and continuous student performance prediction applied to the Open University Learning Analytics (OULA) dataset. First, we introduce a Heterogeneous Graph Neural Network (HGNN) approach that utilizes metapath structures to capture latent interactions between diverse …

Documenting For Success: A Case Study Of A Graduate Writing Retreat, Elliott Rose, Denise Wetzel, Sara C. Kern, Katie O'Hara-Krebs, Laurin Davis, Salah Seoudi, Carmen Cole

Transforming Libraries for Graduate Students

Graduate students often find themselves balancing the demands of research and writing while managing complex academic and personal needs. Writing retreats provide an intentional space for graduate students to focus on their academic goals while supporting community-building, institutional belonging, and a welcoming environment. This proposal outlines a model for academic librarians and staff to plan and implement an effective graduate writing retreat designed to support graduate student academic activities through intentional collaboration and documentation.

Penn State University’s (PSU) Graduate Student Writing Retreat started as an event housed within the University Library’s Science, Technology, Engineering, and Math (STEM) department. The retreat …

Design And Verification Of Manned-Unmanned Collaborative Combat Capability System Based On Mbse, Fangbo Wang, Jian Guo, Chenglie Du, Yifan Liu, Pengpeng Zhang

Journal of System Simulation

Abstract: The traditional model-based systems engineering (MBSE) method has problems of failing to fully exhibit complex combat logics in manned-unmanned collaborative combat system modeling, neglecting the scenario constraints in interface modeling, and requiring long-term and costly algorithm verification. In order to solve the problems, a methodology and design tool based on MBSE was proposed. An integrated verification method of a system's operational logic, interface design, and algorithmic design was constructed, thus providing a digital and rapidly iterative verification approach for system simulation. A verification environment for multiple key algorithm simulations was established, effectively reducing the economic cost of building verification …

Review Of 3d Human Reconstruction Methods Empowering Vr/Ar, Lisha Zhang, Yuchi Huo, Qi Ye, Anjun Chen, Shihui Guo, Jiming Chen

Journal of System Simulation

Abstract: 3D human reconstruction is critical for VR/AR. Early methods relied on multi-view cameras and depth sensors but were costly. Mid-term approaches using parametric human models enabled efficient single-image reconstruction, while implicit neural representations improved fidelity yet suffered from low efficiency. Currently, 3D Gaussian Splatting achieves high accuracy and real-time rendering as a new paradigm. Challenges include detail distortion and limited generalization, and future development will focus on VR/AR integration.

Research On Performance Evaluation Of P300 Brain-Computer Interface Under Environment Modeling And Simulation, Xiaofei Ge, Jinling Lian, Jin Han, Xin'an Fan, Danmei Luo, Yuxiang Hua, Hao Liu, Lijian Zhang

Journal of System Simulation

Abstract: In the process of brain-computer interface(BCI) technology stepping from laboratory to practical application scenarios, it is difficult to make an accurate prediction and evaluation of the effect of real environment factors on the system performance. Therefore, a research method based on a multifactor simulation experiment was proposed. A controllable simulation experiment environment was constructed, and the parametric modeling of two key physical environmental factors, namely noise and light, was carried out. By taking the number of electroencephalogram channels as the system parameter, this paper systematically studied the influence mechanism of the aforementioned factors on the decoding performance of P300-BCI. …

Neural Radiance Fields Based On Explicit Feature Matching And Scaled Dot-Product Attention, Mingwei Cao, Fengna Wang, Zilong Wang, Haifeng Zhao

Journal of System Simulation

Abstract: To address the problems that neural radiance fields(NeRF) are prone to artifacts and texture blurring in novel view synthesis under sparse view input and complex scenes, this paper proposed neural radiance fields based on explicit feature matching and scaled dot-product attention(EMD-NeRF). A multiscale feature extraction network was used to extract multi-scale feature information from the input sparse views. A fusion dot-product module was utilized to calculate view interaction information as a shared branch. Cosine similarity was adopted as a matching clue for similarity embedding volume rendering. A regularization loss function was used to enhance the quality of the scene …