Physical Sciences and Mathematics Commons^™

Utilizing Deep Learning And Object-Based Image Analysis To Search For Low-Head Dams In Indiana, Usa, Brian M. Crookston, Caitlin R. Arnold

Publications

Although low-head dams in the USA provide water supply, irrigation, and recreation opportunities, many are unknown by regulators. Unfortunately, hundreds of drownings occur each decade at these dams from an entrapment current that can form immediately downstream. To explore the ability of deep learning to scan large areas of terrain to identify the locations of low-head dams, ArcGIS Pro and embedded deep learning models for object-based image analysis were investigated. The State of Indiana low-head dam dataset was selected for model training and validation. Aerial imagery (leaf-off conditions) captured from 2016 to 2018 for the nearly 94,000 km² area …

International Expert Consensus On The Current Status And Future Prospects Of Artificial Intelligence In Metabolic And Bariatric Surgery, Mohammad Kermansaravi, Sonja Chiappetta, Shahab Shahabi Shahmiri, Julian Varas, Chetan Parmar, Yung Lee, Jerry T. Dang, Asim Shabbir, Daniel Hashimoto, Amir Hossein Davarpanah Jazi, Ozanan R. Meireles, Edo Aarts, Hazem Almomani, Aayad Alqahtani, Ali Aminian, Estuardo Behrens, Dieter Birk, Felipe J. Cantu, Ricardo V. Cohen, Maurizio De Luca, Nicola Di Lorenzo, Bruno Dillemans, Mohamad Hayssam Elfawal, Daniel Moritz Felsenreich, Michel Gagner, Hector Gabriel Galvan, Carlos Galvani, Khaled Gawdat, Omar M. Ghanem, Et Al

School of Medicine Faculty Publications

Artificial intelligence (AI) is transforming the landscape of medicine, including surgical science and practice. The evolution of AI from rule-based systems to advanced machine learning and deep learning algorithms has opened new avenues for its application in metabolic and bariatric surgery (MBS). AI has the potential to enhance various aspects of MBS, including education and training, decision-making, procedure planning, cost and time efficiency, optimization of surgical techniques, outcome and complication prediction, patient education, and access to care. However, concerns persist regarding the reliability of AI-generated decisions and associated ethical considerations. This study aims to establish a consensus on the role …

Solar Flare Prediction Using Multivariate Time Series Of Photospheric Magnetic Field Parameters: A Comparative Analysis Of Vector, Time Series, And Graph Data Representations, Onur Vural, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi

Computer Science Student Research

The purpose of this study is to provide a comprehensive resource for the selection of data representations for machine learning-oriented models and components in solar flare prediction tasks. Major solar flares occurring in the solar corona and heliosphere can bring potential destructive consequences, posing significant risks to astronauts, space stations, electronics, communication systems, and numerous technological infrastructures. For this reason, the accurate detection of major flares is essential for mitigating these hazards and ensuring the safety of our technology-dependent society. In response, leveraging machine learning techniques for predicting solar flares has emerged as a significant application within the realm of …

A Deep Sparse Capsule Network For Non-Invasive Blood Glucose Level Estimation Using A Ppg Sensor, Narmatha Chellamani, Saleh Ali Albelwi, Manimurugan Shanmuganathan, Palanisamy Amirthalingam, Emad Muteb Alharbi, Hibah Qasem Salman Alatawi, Kousalya Prabahar, Jawhara Bader Aljabri, Anand Paul

School of Public Health Faculty Publications

Diabetes, a chronic medical condition, affects millions of people worldwide and requires consistent monitoring of blood glucose levels (BGLs). Traditional invasive methods for BGL monitoring can be challenging and painful for patients. This study introduces a non-invasive, deep learning (DL)-based approach to estimate BGL using photoplethysmography (PPG) signals. Specifically, a Deep Sparse Capsule Network (DSCNet) model is proposed to provide accurate and robust BGL monitoring. The proposed model’s workflow includes data collection, preprocessing, feature extraction, and predictions. A hardware module was designed using a PPG sensor and Raspberry Pi to collect patient data. In preprocessing, a Savitzky–Golay filter and moving …

Raising Awareness About Hydrographic Careers Through Sea-Going Opportunities, Juliet Kinney, Rochelle Wigley, Sara Cardigos, Fahima Bellabad, Larissa Marques Freguette

Center for Coastal and Ocean Mapping

There is a worldwide shortage of hydrographic personnel (van Wegen, 2021, Hydro International 2008).  Calls for action to address this issue include the IHO’s Hydrography at Sea opportunities, while intiatiative such as Seabed 2030 are bringing broader attention to the field and helping to catalyze new discussions and partnerships in hydrography (IHO, 2024).  The global sea floor mapping community needs to develop a broader workforce pipeline.  We would like to highlight the importance of providing time at sea and leadership opportunities in developing a robust workforce.  We start with an overview of a selection of current exchange and training programs …

How Does Honey Make Gold Nanoparticles? Optical Analysis Of The Effects Of Temperature And Composition, Lydia Alvarnaz, Davon Ferrara Phd

SPARK Symposium Presentations

In recent years, with an increasing interest in green chemistry, there has been an effort to find and understand synthesis methods using biologically-produced reducing and capping agents to produce stable gold nanoparticles (GNPs). Previous research using honey has shown this substance is a viable reducing agent in the formation of nanoparticles but have not looked at the stability of the colloidal gold nanoparticles. In this work, gold nanoparticles were reduced from an aqueous solution of gold chloroauric acid and a solution of varying concentrations of honey and water. The formation of NPs was analyzed using UV-Visible transmission spectroscopy to confirm …

An Operator Information Quantity Of A Semigroup And Associated Differential Equations, Kimiaki Saito, Ryo Inayoshi

Journal of Stochastic Analysis

No abstract provided.

Evidence Of Substorm-Driven Penetration Electric Field Contributions To Low-Latitude Phenomena: Enhanced Upward Drifts, Plasma Bubble Development And Severe Scintillation, J. Sousasantos, F. S. Rodrigues, B. G. Fejer, R. W. Eastes, A. O. Moraes

All Physics Faculty Publications

In this work, it is demonstrated that substorm-driven penetration electric fields can efficiently enhance the upward plasma transport, favoring the development and structuring of plasma irregularities and the occurrence of scintillation on L-band signals. While most previous studies focus on investigating penetration electric fields during intense geomagnetic storms, here, the period used (April 01–05, 2020) was under very mild geomagnetic activity (−27 nT ≤ SYM-H ≤ 6 nT), so that interplanetary and disturbance dynamo contributions are minimized. This period comprised the same seasonal and solar flux conditions, while undergoing multiple short-lived substorms, making it well-suited to evaluate unequivocally: (a) to …

Fine-Grained Traffic Flow Inference Model Based On Dynamic Back Projection Network, Ming Xu, Guangyao Qi, Geqi Qi

Journal of System Simulation

Abstract: To solve the problem of large errors in the inference results of existing fine-grained urban flow inference models in complex traffic areas, a fine-grained traffic flow inference model based on dynamic back-projection network is proposed. The multi-dimensional interaction between the input coarse-grained traffic flow and external factors is calculated, and the interaction results are dynamically and adaptively fused with the coarse-grained traffic flow, so that the features can interact and adjust each other to assist model reasoning. Combining deep convolution and self-attention mechanism to learn local information and global information, and improve the understanding of input data by subsequent …

Biquandle Power Brackets Of Oriented Links, Nesli̇han Gügümcü, Sam Nelson

Turkish Journal of Mathematics

In this paper, we introduce biquandle power brackets, an infinite family of invariants of oriented links containing the classical skein invariants and the quandle and biquandle 2-cocycle invariants as special cases. Biquandle power brackets are generalizations of biquandle brackets in which the values of Kauffman states also depend on the biquandle colors they admit. We provide example computations and discuss the relationship between these new invariants and the previous cases.

Order Structure Of Order-To-Topological Continuous Operator, Gül Si̇nem Keleş, Bahri̇ Turan, Bi̇rol Altin

Turkish Journal of Mathematics

Let J be a vector lattice, and W be a topological vector space. An operator K: J → W is called an order-to-topological continuous operator if u_α → 0 in J implies K(u_α) → 0 in W for each net (u_α) in J. In this study, we examine the order structure of the space of order-to-topological continuous operators in general and the order structure of order-to-norm continuous operators in particular. We study the relationships between order-to-topology continuous operators and other classes of operators, such as order weakly compact and order continuous operators. Moreover, we give …

Fractional Equivalent Of Fourth-Order Laguerre And Chebyshev Polynomials, Zahra Kavousi, Kazem Ghanbari

Turkish Journal of Mathematics

Orthogonal polynomials have very useful properties in the solution of mathematical and physical problems. In the last few years, there has been considerable interest in the properties of orthogonal polynomials satisfying differential equations (DE) of order greater than two, their connection to singular boundary value problems, their generalizations, and their classification as solutions of second-order DE. In this paper, we develop a fractional analog of the fourth-order Laguerre differential equation on the interval [0, ∞) and, in addition, we develop a fractional analog of the fourth-order Chebyshev differential equation on a symmetric interval [−α, α], where α is the order …

Continuous Dependence Of Thermoelasticity Problem, Müge Meyvaci, Şevket Gür

Turkish Journal of Mathematics

The current study considers the initial boundary value problem for the thermoelastic model. The model in which heat conduction is given by Green and Naghdi's theory is called Type II. It is increasingly accepted that studying the structural stability of the initial boundary value problem is crucial. This is because even minor changes in the equation or its coefficients can lead to significant variations in the solution of the problem. From this point of view, we analyze the structural stability of the solutions, specifically examining the continuous dependence of the solutions on all the coefficients of the thermoelastic system, using …

03.17.2025 Ored Connect, Liz Williamson

ORED Newsletter

SPA director Andrea Rich

ARC Nomination Deadline Extended

Development Of S(Vi) And S(Iv) Chemistry: From Asymmetric Synthesis To Covalent Reactive Groups, Chuan Shan

USF Tampa Graduate Theses and Dissertations

This dissertation mainly covers the development of synthetic methodologies related to several heteroatom functional groups, including phosphonates P(V), sulfoximines S(VI), sulfonimidamides S(VI), sulfonimidoyl fluorides S(VI), and sulfinamides S(IV). The interests in these functionalities are not only out of chemistry curiosity but also due to their pharmaceutical importance indicated by the existing drug molecules that contain these functional groups. The first chapter introduced the importance of phosphonates in biochemistry and organic synthesis, also provided some essential background of our synthetic efforts. The second chapter described the phosphonate synthesis from commercially available starting materials, with the purpose to obtain heterocyclic phosphonates in …

Enhancement Of Hardware-In-Loop Simulation Ability For Homing Guidance Through Adaptive Field-Of-View Method, Shizheng Wan, Yu Cheng, Xu Zhang, Xuwei Fan

Journal of System Simulation

Abstract: Considering homing guidance test in the hardware-in-loop simulation, commands of flight simulator and antenna array are likely to exceed their ranges when the target vehicle maneuvers with a large cross range. To solve this problem, the adaptive field-of-view method is proposed to enhance simulation ability in laboratory. Inflight aircraft attitudes and missile-target line-of-sight angles are chosen as state parameters, and the optimal performance function can be established with maximum servo angle of both flight simulator and antenna array. Gradient descent algorithm is applied to acquire the optimal bias angles between the laboratory coordinate system and the launch inertial coordinate …

Research On Pedestrian Avoidance Strategy For Agv Based On Deep Reinforcement Learning, He Wang, Jianing Xu, Guangyu Yan

Journal of System Simulation

Abstract: To ensure the safety and comfort of pedestrians during Automated Guided Vehicle (AGV) obstacle avoidance in smart factory environments, a deep reinforcement learning-based end-to-end obstacle avoidance method is proposed. The YOLOv8 module is introduced to extract pedestrian pose information, and a visual-based state space is designed. A reinforcement learning mechanism is formulated based on personal space theory, penalizing AGV behaviors such as entering pedestrian comfort space and collisions. A virtual simulation system is constructed, utilizing PPO algorithm along with LSTM network layer for obstacle avoidance strategy training and simulation experiments. Simulation results indicate that this obstacle avoidance strategy, under …

Economic Optimal Scheduling Of Microgrid Considering Elastic Recovery, Jianghong Chen, Kanghao Shi, Jiahui Hu, Xiaohan Zhao

Journal of System Simulation

Abstract: To enhance the ability of microgrids (MGs) to withstand extreme disaster events, this paper proposes a multi-objective scheduling model considering resilience restoration and economic performance, based on the traditional concepts of power system resilience and reliability. Resilience is specifically quantified. The model integrates energy storage into the objective function and includes reliability indicators as constraints, building on traditional microgrid economic dispatch. The optimization problem is solved using an improved white shark optimizer (WSO) and multi-objective fuzzy programming, where different weights are assigned to each objective function, and the optimal weights are determined through case studies. A microgrid scheduling scheme …

Parallel Task Transmission And Processing Optimization Scheme For Uav-Assisted Internet Of Vehicles, Chao Yang, Ruiqun Zheng, Zhen Li, Hongwei Zhang, Yanqun Tang, Dongze Li

Journal of System Simulation

Abstract: To address the increasing of computation demands of internet of vehicles (IoV) users due to the sudden traffic congestion, unmanned aerial vehicles (UAVs) are introduced to the intelligent transportation systems (ITS) to construct an UAV-assisted IoV network. The UAV limited energy and computing resources lead to the current traditional UAV coverage strategy with one by one less efficiency. We propose a parallel task transmission and processing optimization strategy, considering the line-of-sight communication links and fast moving characteristics of UAV. After receiving the tasks from vehicles in the service point, UAV can fly to the next point and perform task …

Three-Way Decision Clustering Algorithm Fusion Of Mutant Fireflies Algorithm, Zhaobin Li, Jun Ye, Haoyan Zhou, Yixin Wang, Yuzhen Han

Journal of System Simulation

Abstract: To address problems such as the premature phenomenon in the three-way clustering algorithm caused by the random selection of initial cluster centers and the need for repeated experiments to determine the value of q in the q-nearest neighbor concept, a three-way clustering algorithm optimized by a variant of the firefly algorithm is proposed. The firefly algorithm is employed to solve the problem of sensitivity to initial cluster centers. The target function value is taken as the brightness intensity of firefly to search the clustering center point, and the optimal solution is taken as the clustering center of the algorithm …

Research On Improved A* Algorithm Path Planning Based On Global Key Point Extraction, Guijuan Lin, Zihan Li, Yu Wang

Journal of System Simulation

Abstract: To address the limitations of the traditional A* algorithm in large and complex scenes, including traversing a large number of nodes, long computation times, and susceptibility to U-shaped traps, this paper proposes an improved A* algorithm incorporating the jump point search (JPS) concept and image processing techniques to extract key points from the global map. The proposed method preprocesses the global map to identify corner points located one grid diagonally from obstacles, constructs a key point list, and replaces the nodes traditionally traversed by the A* algorithm with these global key points, significantly reducing computational overhead. The neighbor nodes …

Real-Time Nonlinear Economic Model Predictive Control Of Wind Energy Conversion System, Wenwen Wang, Xiangjie Liu, Xiaobing Kong

Journal of System Simulation

Abstract: To address the new challenges of economic control and real-time requirements in wind energy conversion systems (WECS), this study proposes a nonlinear economic model predictive control (NEMPC) strategy. This strategy aims to maximize power generation and while reducing fatigue loads on critical structures, such as towers and gearboxes. Additionally, a moving horizon estimator (MHE) has been designed to provide an effective initialization for optimization. By exploiting the similarity of nonlinear programs between adjacent sampling moments, the algorithm achieves real-time iterative (RTI) solutions. Using a 5 MW wind turbine as the research object, the proposed strategy is implemented in the …

Research On Robot Path Planning Based On Improved Harris Hawks Algorithm, Yuxin Bai, Zhenya Chen, Ruitao Shi, Weitao Su, Zhuoqiang Ma, Shangjin Yang

Journal of System Simulation

Abstract: In order to improve the convergence accuracy of the HHO algorithm, this paper proposes a GSHHO(gold sine harris hawks optimization) algorithm based on multi-strategies. An infinite iterative chaotic map is used to initialize the population, and an elite reverse learning strategy is used to improve population quality; A convergence factor adjustment strategy is used to recalculate prey energy, balancing the global exploration and local development capabilities of the algorithm; In the development phase of Harris Eagle, the golden sine strategy was introduced to replace the original position update method and improve the local development ability of the algorithm; Experiments …

Research On Air Target Threat Assessment Technology Based On Deep Learning, Dawei Jiang, Yangyang Dong, Lidong Zhang, Xiao Lu, Chunxi Dong

Journal of System Simulation

Abstract: In order to realize the effective assessment of air combat targets, a deep learning-based air target threat assessment method is proposed. According to threat characteristics of the air target, the threat attributes of air target faced by electronic countermeasure operation are analyzed from the two perspectives of platform layer and equipment layer, the air target threat assessment index system is constructed, and the air target threat assessment index data set is established. Based on convolutional neural network, a residual structure is introduced to optimize the network, a threat assessment model is established, and the threat ranking of air targets …

Artificial Intelligence For Better In-Game Nfl Performance, Christopher Mcmanus

Honors Theses

In this thesis I examined the use of AI modeling for the use in the modern-day NFL, both for improving in-game play calling, and creating better recovery plans for players all around the league. When finding articles detailing these models, I only focused on works involving the current day NFL, and models used widely around the league to this day. The literature detailed in this thesis mainly describes modeling used by Amazon Web Services (AWS, 2024, The NFL’s partner for all things analytics, and data modeling. My main objective for this literature review was to show the impact AI modeling …

Design And Verification Of Display And Control System Based On Mbse And Vaps For Civil Helicopter, Xi Cao, Bo Liu, Bingzhi Su, Tao Nie

Journal of System Simulation

Abstract: Aiming at the challenges of difficulties in tracing requirements, detecting interaction design defects, and achieving early system design verification, this paper proposes a design and verification for the display and control system (DCS) of civil helicopters based on model-based systems engineering (MBSE) and VAPS. The method begins with capturing stakeholder requirements to form system requirements, followed by the allocation of these requirements to system use cases. Black-box activity diagrams and sequence diagrams are constructed to conduct "requirement-function analysis" from the top down, describing the functional flow of the DCS. A running black-box statechart diagram is further established to verify …

Cae Simulation Optimization Method Based On Dynamic Coupling Model, Xue Chen, Jianwen Cao

Journal of System Simulation

Abstract: In order to solve the optimization problem of designing complex equipment under multi-factor coupling scene, a CAE simulation optimization method based on dynamic coupling model and multibranch parallel inference strategy is proposed. The dynamic hierarchical DEVS model is used to construct the automatic coupling model from pre-processing, numerical solution and post-processing phases of CAE software adaptively. Aiming at the key parameters of CAE model, multi-branch instance models with multi-factor constraints are constructed based on greedy algorithm. The multi-task parallel inference strategy is used to compute the multi-branch simulation results efficiently. The scheme optimization is realized based on the evaluation …

A Note On A Novel Type Of Alster Covering Property In Bitopological Setting, Necati̇ Can Açikgöz, Ceren Sultan Elmali

Turkish Journal of Mathematics

In this paper, we introduce a new type of Alster covering property in bitopological setting. We investigate its relations with other existing covering properties. By giving counterexamples, we indicate that our new property is different than other mentioned properties. We also construct some conditions for equivalences of those properties with the corresponding property. We also consider the preservation of this new form of bitopological Alster covering property. We investigate the productivity of bitopological nearly Lindelöfness and bitopological nearly Mengerness.

Improving Upper Bounds Of Berezin Number Inequalities Using Convex Function, Sana Khan, Mehmet Gürdal, Muhammad Saeed Akram

Turkish Journal of Mathematics

In this research article, new upper bounds are established for the Berezin number of bounded linear operators within the context of functional Hilbert space using the convex function. These bounds are achieved by exploiting an extension of Furuta's inequality and an extension of Kato's inequality. These Berezin number bounds are refinements of already existing bounds found in the literature.

Vibration Simulation And Multivariate Statistical Analysis Method Of Composite Structures, Bo Guo, Ming Tie, Wenhui Fan

Journal of System Simulation

Abstract: To investigate the natural frequency characteristics of composite laminates under parametric uncertainties and the different degree of influence of these parameters on the natural frequency under different boundary conditions and different vibration orders, a two-dimensional anisotropic medium-thick plate material model and a three-dimensional anisotropic cylindrical thin-shell material vibration model are established. Aiming at the uncertainty of structural parameters of these composite materials, the composite material vibration simulation and multivariate statistical analysis software are developed to simulate the structural vibration of composite materials. A multivariate statistical analysis method for natural frequency uncertainty of composite materials is presented. Through principal component …