Physical Sciences and Mathematics Commons^™

An Intelligent Ambulance Regulation Model Based On Online Reinforcement Learning Algorithm, Lei Zhang, Xuechao Zhang, Chao Wang, Xianglei Bo

Journal of System Simulation

Abstract: In emergency scenarios where ambulances are used to evacuate casualties, it is necessary to fully coordinate the rescue capability of the ambulance with the real-time status of the casualties in the scenario to achieve the best rescue results. Such problems are generally non-deterministic polynomial problems, and the traditional deterministic scheduling algorithms are less effective. This paper aimed at the modeling research of the real-time regulation of ambulances in emergency scenarios, an online reinforcement learning DNQ algorithm frameworks based on the data enhancement method is proposed and applied to the solution of the ambulances control model. To solve the problems …

City Regional Traffic Flow Prediction Based On Spatiotemporal Multi-View Attention Residual Network, Jing Chen, Guowei Yang, Zhaochong Zhang, Wei Wang

Journal of System Simulation

Abstract: However, efficiently and comprehensively capturing the complex spatiotemporal correlations within urban traffic flow presents a key challenge. Existing research methods struggle to fully capture these spatiotemporal dependencies. To address these issues, we propose a novel end-to-end deep learning framework called the spatiotemporal multi-view attention residual network (ST-MVAR) for predicting traffic flow in urban areas. we integrate the proximity, periodicity, trend, and external factors of traffic flow as inputs to the network. This network employs skip connections to form a multi-layer nested residual network structure. Additionally, we design a Multi-View Extension module to capture spatial dependencies of traffic flow at …

Tohf: A Feature Extractor For Resource-Constrained Indoor Vslam, Ruoqing Li, Yaochi Zhao, Zhuhua Hu, Wenlu Qi, Guangfeng Liu

Journal of System Simulation

Abstract: To address the issues of sensitivity to texture and lighting variations, excessive local dependence caused by feature point redundancy, and storage overhead under hardware resource constraints in existing VSLAM feature extractors in indoor environments, We propose the Texture- Oriented and Homogenized FAST Feature Extractor (TOHF), which integrates HVS (Human Visual System) for enhanced texture analysis. TOHF employs a two-stage thresholding strategy and dynamically adjusts feature point distribution, balancing computational efficiency and storage needs. We conducted experimental verification based on the ORB-SLAM3 framework on dataset from resource-limited device and the EuRoc dataset, focusing on matching rate, reprojection error, absolute trajectory …

Electric Vehicle Dispatching Strategy And Incentive Evaluation Based On Virtual Energy Storage, Shuo Chen, Hao Hu, Huimin Fang, Haiwei Wang, Xiaolong Chen, Chengcheng Mei, JiaʹNan Zhu, Qian Ai

Journal of System Simulation

Abstract: To address the multifaceted challenges arising from the widespread integration of electric vehicles into the power grid, harnessing the dispatchability features of electric vehicles becomes imperative. This paper based on a virtual energy storage aggregation model, optimizes the charging scheduling of electric vehicles and assesses their charging incentives through a composite weighting methodology. It establishes a framework for the participation of flexible loads in distribution network scheduling, formulates a second-order cone relaxation optimal power flow model, and develops dispatch strategies. By quantifying the contribution of electric vehicles concerning their flexibility and system stability, and simulating user charging preferences using …

Visual Slam Algorithm Based On Feature Point Selection In Dynamic Scenes, Limei Jiang, Xinwei Chen

Journal of System Simulation

Abstract: To address low positioning accuracy and robustness in traditional visual SLAM algorithms under dynamic conditions, this paper proposes an improved dynamic SLAM algorithm based on feature point selection. Built upon the ORB-SLAM3 framework, it incorporates dynamic region partitioning and feature point filtering. The dynamic region partitioning module utilizes an enhanced RT-DETR object detection algorithm to detect dynamic objects in the images and divides the dynamic regions based on the detection boxes. The feature point selection module utilizes epipolar constraints and optical flow methods to filter out feature points on moving objects, retaining stationary dynamic objects and background points within …

Reinforcement Learning Modeling Of Missile Penetration Decision Based On Combat Simulation, Bin Zhang, Yonglin Lei, Qun Li, Yuan Gao, Yong Chen, Jiajun Zhu, Chenlong Bao

Journal of System Simulation

Abstract: Penetration capability is a primary measure of missile systems. In response to the shortcomings of traditional knowledge-based decision-making methods that are difficult to adaptively evolve, an intelligent penetration decision-making based on combat simulation and DRL is proposed. A missile intelligent decision-making training environment is constructed based on the WESS system. Taking missile maneuver penetration decision-making as an example, a maneuver penetration decisionmaking network model is designed and trained based on the SAC-discrete algorithm and the test of intelligence is conducted. Experimental results show that the intelligent decision model derived from machine learning has a better combat outcome than traditional …

Research On Transformer Fault Diagnosis Method Based On Digital Twin, Lun Jiang, Dajiang Wang, Wenlei Sun, Shenghui Bao, Han Liu, Saike Chang

Journal of System Simulation

Abstract: Aiming at the inability of existing intelligent algorithms for transformer fault diagnosis to quickly and efficiently identify transformer faults, resulting in fault misdetection and untimely detection, this paper proposes a transformer fault diagnosis method using the improved sparrow optimization algorithm to optimize the two-layer fault diagnostic model of XGBoost combined with the digital twin technology. The method adopts advanced sensors to collect oil and gas data and temperature data of the transformer, uses 5G module to transmit the real-time data to the digital twin system. The system monitors the temperature data in real-time by setting the equipment alarm threshold; …

Multi-Strategy Hybrid Mountain Gazelle Optimizer For Robot Path Planning, Xu Jin, Yuanbin Mo

Journal of System Simulation

Abstract: Aiming at the problems of local optimum and premature convergence in the design of optimization path of robot navigation system, a multi-strategy hybrid MGO(HMGO) improved algorithm based on the mountain gazelle optimizer(MGO) is proposed. The algorithm uses the quasi-reverse learning strategy to optimize the population initialization ensuring its diversity, introduces the dynamic adaptive density factor to adjust the parameters of the optimization mechanism, and integrates arithmetic optimization and sine-cosine strategies for random perturbations. Through ablation experiments, 13 benchmark test functions, and simulation experiments on the solution of two-dimensional and threedimensional space robot path planning problems, the results demonstrate that …

Near Convexity And Generalized Differentiation, Nguyen Mau Nam, Nguyen Nang Thieu, Nguyen Dong Yen

Mathematics and Statistics Faculty Publications and Presentations

In this paper, we introduce the concept of nearly convex set-valued mappings and investigate fundamental properties of these mappings. Additionally, we establish a geometric approach for generalized differentiation of nearly convex set-valued mappings and nearly convex functions. Our contributions expand the current knowledge of nearly convex sets and functions, while providing several new results pertaining to nearly convex set-valued mappings.

Adaptive Resolution Of Fine Scales In Modes Of Microstructured Optical Fibers, Jay Gopalakrishnan, Jacob Grosek, Gabriel Pinochet-Soto, Pieter Vandenberge

Mathematics and Statistics Faculty Publications and Presentations

An adaptive algorithm for computing eigenmodes and propagation constants of optical fibers is proposed. The algorithm is built using a dual-weighted residual error estimator. The residuals are based on the eigensystem for leaky hybrid modes obtained from Maxwell equations truncated to a finite domain after a transformation by a perfectly matched layer. The adaptive algorithm is then applied to compute practically interesting modes for multiple fiber microstructures. Emerging microstructured optical fibers are characterized by complex geometrical features in their transverse cross section. Their leaky modes, useful for confining and propagating light in their cores, often exhibit fine-scale features. The adaptive …

Solving A Multi-Stage Mine Sequencing Model Encompassing Excavator Allocation Through Constraint Programming In A Bauxite Strip Mining Operation, Jorge Luiz Valença Mariz, Marcel Antonio Arcari Bassani, Rodrigo De Lemos Peroni, Octávio R. A. Guimarães, Flávio H. Tavares

Journal of Sustainable Mining

Sedimentary mineral deposits are generally tabular and sub-horizontal, composed of one or multiple well-defined seams, arranged over large extensions, and when close to the surface, they are mined by surface mining methods. These geometric characteristics make it suitable for the application of the strip mining method as an alternative to the traditional open-pit mining method, which allows the reduction of the truck haulage fleet and the costs associated with waste disposal. Consequently, it reduces the greenhouse gas emissions and carbon footprint associated with excavation and transportation processes. This article presents a two-stage mathematical model based on Integer Linear Programming to …

Distributed Tikhonov Regularization For Ill-Posed Inverse Problems From A Bayesian Perspective, D. Calvetti, E. Somersalo

Faculty Scholarship

In this article, we exploit the similarities between Tikhonov regularization and Bayesian hierarchical models to propose a regularization scheme that acts like a distributed Tikhonov regularization where the amount of regularization varies from component to component, and a computationally efficient numerical scheme that is suitable for large-scale problems. In the standard formulation, Tikhonov regularization compensates for the inherent ill-conditioning of linear inverse problems by augmenting the data fidelity term measuring the mismatch between the data and the model output with a scaled penalty functional. The selection of the scaling of the penalty functional is the core problem in Tikhonov regularization. …

Forb Diversity Globally Is Harmed By Nutrient Enrichment But Can Be Rescued By Large Mammalian Herbivory, Rebecca A. Nelson, Lauren L. Sullivan, Erika I. Hersch-Green, Eric W. Seabloom, Elizabeth T. Borer, Pedro M. Tognetti, Peter B. Adler, Lori Biederman, Miguel N. Bugalho, Maria C. Caldeira, Juan P. Cancela, Luísa G. Carvalheiro, Jane A. Catford, Chris R. Dickman, Aleksandra J. Dolezal, Ian Donohue, Anne Ebeling, Nico Eisenhauer, Kenneth J. Elgersma, Anu Eskelinen, Catalina Estrada, Magda Garbowski, Pamela Graff, Daniel S. Gruner, Nicole Hagenah, Sylvia Haider, W. Stanley Harpole, Yann Hautier, Anke Jentsch, Nicolina Johanson, Sally E. Koerner, Lucíola S. Lannes, Andrew S. Macdougall, Holly Martinson, John W. Morgan, Harry Olde Venterink, Devyn Orr, Brooke B. Osborne, Pablo L. Peri, Sally A. Power, Xavier Raynaud, Anita C. Risch, Mani Shrestha, Nicholas G. Smith, Carly J. Stevens, G. F. Ciska Veen, Risto Virtanen, Glenda M. Wardle, Amelia A. Wolf, Alyssa L. Young, Susan P. Harrison

Wildland Resources Faculty Publications

Forbs (“wildflowers”) are important contributors to grassland biodiversity but are vulnerable to environmental changes. In a factorial experiment at 94 sites on 6 continents, we test the global generality of several broad predictions: (1) Forb cover and richness decline under nutrient enrichment, particularly nitrogen enrichment. (2) Forb cover and richness increase under herbivory by large mammals. (3) Forb richness and cover are less affected by nutrient enrichment and herbivory in more arid climates, because water limitation reduces the impacts of competition with grasses. (4) Forb families will respond differently to nutrient enrichment and mammalian herbivory due to differences in nutrient …

Bayesian Spatio-Temporal Modeling Of African Co2 Emissions (1990–2020): A Hierarchical Approach To Identify Determinants, Regional Trends, And Local Dynamics, Ebenezer Afrifa-Yamoah, Prince Mensah Osei

Research outputs 2022 to 2026

Africa's unique position in global CO2 emissions demands rigorous analysis for effective climate policy development. Despite contributing only 4% to global emissions, the continent faces disproportionate climate impacts while undergoing rapid development and complex economic transitions. Current research lacks extensive continental analysis of the spatial dependencies, temporal evolution of emission patterns, and their key drivers, which is fundamental for evidence-based climate policy and sustainable development strategies. We applied Bayesian hierarchical spatio-temporal modeling to analyze CO2 emissions across African countries (1990–2020), integrating rotated empirical orthogonal function (REOF) analysis with spatial autocorrelation techniques (Local Moran's I and LISA) to capture complex emission …

Coupled Oscillators And Dielectric Function, T. Das, C. A. Ullrich, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

A generalized Sellmeier model, also referred to as the Lorentz-Dirac model, has been used for the description of the dielectric function of a number of technologically important materials in the literature. This model represents the frequency-dependent dielectric function as a sum over Green functions of classical damped harmonic oscillators, much in analogy with the functional form used for the dynamic polarizability of an atom, but with one important addition, namely, a complex-valued oscillator strength in the numerator. Here, we show that this generalized functional form can be justified based on the response function of coupled damped oscillators. The encountered analogies …

The Spice (Sustainable, Physics-Inspired Culinary Education) Lab – A Digestible Few-Nexus Educational Platform, Carla Ramsdell

National Collaborative for Research on Food, Energy, and Water Education (NC-FEW)

The SPICE (Sustainable, Physics-Inspired Culinary Education) Lab is a unique educational platform that enables participants from a wide disciplinary background to engage and become literate in the unique connections between food, energy and water. This small but mighty space allows for outreach education in many formats, including formal college courses, university-centered hands-on activities and public outreach.

The work performed in this space fills a unique need in the FEW-Nexus education opportunities because it is adaptable to many learners and learning opportunities and its focus on kitchen science makes these concepts approachable which can later be expanded to understand other critical …

System Change, Not Climate Change: Collaborative Development Of A Few Nexus Experiential Learning Course For A Justice-Centered Comparative Study Abroad Program, Sonya Ahamed

National Collaborative for Research on Food, Energy, and Water Education (NC-FEW)

The International Honors Program (IHP) on Climate Change: The Politics of Land, Water and Energy Justice has been offered by the School for International Training (SIT) since 2013. This thematic multidisciplinary program currently travels to Morocco, Nepal, and Ecuador for one month each, introducing students to local food, water, and energy challenges in the context of a changing climate. In updating the program following its relaunch in 2023, renewed attention was given to the food, energy, and water nexus from a comparative perspective across and within these countries. This presentation will focus on the development of experiential learning cycles for …

The Few-Nexus: Using Soil To Grow Meaning And Relevance In Undergraduate General Education Earth Science Courses, Katherine Mccarville

National Collaborative for Research on Food, Energy, and Water Education (NC-FEW)

Soils are central to human survival, through their critical roles in regulating water supplies and providing the medium for most agricultural productivity. Even as fewer and fewer students know where their water and food come from, and where their wastes go, soils tend to be under-emphasized in Earth science general education courses. Combining a place-based focus on soils with the FEW-Nexus model provides an integrating context for concepts and information that students sometimes perceive as disconnected and irrelevant to them. This approach can transform the experiences and learning of undergraduate students in the Earth science general education curriculum.

Artificial Intelligence And Communication Technologies In Academia: Faculty Perceptions And The Adoption Of Generative Ai, Aya Shata, Kendall Hartley

Hank Greenspun School of Journalism and Media Studies Faculty Research

Artificial intelligence (AI) is ushering in an era of potential transformation in various fields, especially in educational communication technologies, with tools like ChatGPT and other generative AI (GenAI) applications. This rapid proliferation and adoption of GenAI tools have sparked significant interest and concern among college professors, who are dealing with evolving dynamics in digital communication within the class-room. Yet, the effect and implications of GenAI in education remain understudied. Therefore, this study employs the Technology Acceptance Model (TAM) and the Social Cognitive Theory (SCT) as theoretical frameworks to explore higher education faculty’s perceptions, attitudes, usage, and motivations, as the underlying …

2024 Rmap Non-Residential Parcels Data Summary Report Silver Bow Creek/Butte Area Npl Site Bpsou, Environmental Standards, Inc., Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

“Smart Trap”: A Portable Device For Real-Time Mosquito Capturing And Classification Using Image-Based Analysis, Fahim Rahman

USF Tampa Graduate Theses and Dissertations

Capturing mosquitoes in real-time and taking high-quality images for classification with state-of-the-art methods is not only time-consuming but also expensive. Sometimes even carefully controlled environments and experimental setups fail to capture living mosquitoes. Catching live mosquitoes is necessary to be able to study aspects of their physiology and behavior that cannot be investigated by collections of resting mosquitoes and dead specimens, and to help estimate the local population numbers. My thesis introduces a “Smart Trap”, a small portable device that can attract mosquitoes in real-time, capture them, take high-quality images with dual cameras, and store those images in the cloud. …

The Sustainability Stones: Culturally Embedded Conservation Strategies And Their Vulnerability In Maupiti, French Polynesia, Russell Fielding, Fiona Gimenez

Honors College Faculty Publications

This paper explores culturally embedded conservation strategies through the lens of the traditional agroforestry and fisheries cycles in Maupiti, French Polynesia. By pairing certain breadfruit cultivars with specific fish species, the island’s community created a culinary system that regulates the seasonal consumption of marine resources, making the sustainable use of those resources more likely. While modern pressures such as reduced breadfruit diversity, competition with imported foods, and climate change have weakened these traditional practices, they remain an example of local ecological knowledge guiding conservation. The study highlights the threat of losing sustainable resource-use practices and biodiversity as both biodiversity and …

Examining Intersectional Queer Biases In Large Language Models: A Combined Statistical And Visual-Qualitative Approach For Quantification And Explanation, Huu Duong (Chip) Nguyen

Computer Science Senior Theses

Despite significant advancements in research on (intersectional) social biases in Large Language Models (LLMs), intersectional biases affecting subgroups within the LGBTQ+ community remain critically understudied. Existing bias detection methodologies often prioritize quantification but lack depth in explaining the specific stereotypes/biases that shape evaluation metrics. To address these gaps, this study proposes a combined statistical and visual-qualitative approach to quantify and identify persistent intersectional queer biases in five recent, state-of-the-art LLMs through a downstream story generation task. Findings from analysis uncover substantial evidence of stereotypes that perpetuate harmful, reductive narratives against intersectionally marginalized groups within the LGBTQ+ community. To promote public …

Indigenous Futures: Decolonizing Conservation And Restoring Ecological Sovereignty, Jasmine Beach

University Honors Theses

This study examines how members of Indigenous-led conservation organizations perceive the ecological and social implications of colonial conservation ideologies in the context of contemporary grassroots strategies. By analyzing the ongoing impact of conservation frameworks in Kenya, this research highlights the role of Indigenous-led initiatives in advancing sustainable, community-driven alternatives. Using a Two-Eyed Seeing approach, which integrates Traditional Ecological Knowledge (TEK) with Western scientific methods, the study employs qualitative, semi-structured interviews with leaders from Zawadisha, KENVO, Wildlife Works, and CER-Kenya. Findings indicate that these organizations, particularly those led by women, actively restore biodiversity, enhance climate resilience, and challenge exclusionary conservation policies. …

Refugium Amidst Ruins: Unearthing The Lost Flora That Escaped The End-Permian Mass Extinction, Huiping Peng, Wan Yang, Mingli Wan, Jun Liu, Feng Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Searching for land refugia becomes imperative for human survival during the hypothetical sixth mass extinction. Studying past comparable crises can offer insights, but there is no fossil evidence of diverse megafloral ecosystems surviving the largest Phanerozoic biodiversity crisis. Here, we investigated palynomorphs, plant, and tetrapod fossils from the Permian-Triassic South Taodonggou Section in Xinjiang, China. Our fossil records, calibrated by a high-resolution age model, reveal the presence of vibrant regional gymnospermous forests and fern fields, while marine organisms experienced mass extinction. This refugial vegetation was crucial for nourishing the substantial influx of surviving animals, thereby establishing a diverse terrestrial ecosystem …

Precision Phenotyping For Curating Research Cohorts Of Patients With Unexplained Post-Acute Sequelae Of Covid-19, Ingrid V Bassett, Douglas S Bell, Elmer V Bernstam, Maha R Farhat, Darren W Henderson, Emily S Lau, Michele Morris, Yevgeniy R Semenov, Virginia A Triant, Shyam Visweswaran, Zachary H Strasser, Jeffrey G Klann, Shawn N Murphy, Hossein Estiri

Faculty, Staff and Student Publications

BACKGROUND: Scalable identification of patients with post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms, which has led to suboptimal accuracy, demographic biases, and underestimation of the PASC.

METHODS: In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying cohorts of patients with PASC. We used longitudinal electronic health records data from over 295,000 patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to simultaneously exclude sequelae that prior conditions can explain and include infection-associated chronic conditions. We performed independent chart reviews …

Advancements In Near Real-Time Bolide Detection: Continuum Calibration, Altitude Estimation, And Velocity Approximation Using Noaa Goes Glm Data, Eric Mckinney, Ryan Frazier, John Pratt, Mike Larsen, Philip Nelson, Hans Gunther

Space Dynamics Laboratory Publications

• Bolides, also known as fireballs, are a class of meteoroids that explosively break up and release large amounts of energy as they enter the Earth’s atmosphere

• While inherently of scientific value, bolides that occur over populous areas can result in alarm and, on rare occasions, terrestrial damage

• Thus, rapid bolide detection and characterization systems are advantageous for the scientific community, public interest, and political de-escalation efforts

• Jenniskens et al. (2018) and Rumpf et al. (2019) showed that the Geostationary Lightning Mapper (GLM) sensor onboard the NOAA Geostationary Operational Environmental Satellite (GOES) satellites can detect bolide signatures

• This presentation complements a …

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Characterizing Rainfall Variability Within A Series Of Storms Over Northern California In February 2017, Parker Jan Malek

Dissertations and Theses

In February 2017, a series of storms with associated atmospheric rivers (ARs) made landfall in the US state of California, dropping large amounts of precipitation over the Sierra Nevada Mountains and their western foothills. The rainfall from these ARs, long, narrow bands of water vapor that transport large amounts of water vapor from the tropics to the mid-latitudes, instigated the near-failure of the Oroville Dam located at the southeastern edge of the Feather watershed outside the city of Oroville in the state's Central Valley. This case study provides a synoptic and mesoscale diagnosis of the drivers of rainfall pulses that …

Feature Manifold Transformer For Detection Of Differential Item Functioning: Visual Detection Of Categorical Feature Nonconformity Through Attention-Based Analysis, Derrick A. Cox, Tanvi Banerjee, William L. Romine

Computer Science and Engineering Faculty Publications

Methods for interpreting complex feature interactions in educational assessment data remain a critical challenge, with traditional statistical approaches often creating barriers to accessibility and interpretability. We introduce the Feature Manifold Transformer (FMT), a novel machine learning approach that leverages dimensionality reduction, representation learning, and transformer architectures to visualize and interpret feature relationships in categorical data. Using the Concept Inventory of Natural Selection (CINS) and Concept Assessment of Natural Selection (CANS) datasets as testbeds, we demonstrate the FMT’s ability to capture subtle relationships between student demographics and response patterns. Our methodology enables both global and local pattern analysis, providing interpretable visualizations …

Predicting Freshwater Spring Distribution Using Maxent Modeling: A Case Study In Groundwater Management Area 9 (Gma-9), Texas, Zayed Mallick

USF Tampa Graduate Theses and Dissertations

Freshwater springs are one of the most vital groundwater sources and they have been a reliable water source for mining, irrigation, drinking, and farming, particularly in hot and arid regions like Groundwater Management Area-9 (GMA-9), Texas. However, excessive groundwater extraction, climate change, and environmental degradation have created tremendous stress on the sustainability of freshwater springs and as a result, they might not be able to meet the future water demand. This study uses the Maximum Entropy (MaxEnt) model to predict the distribution of springs in GMA-9 and to identify the key topographic and climatic factors influencing their occurrence. This study …