Physical Sciences and Mathematics Commons^™

Research On Virtual Simulation Testing Technology For Intelligent Navigation Collision Avoidance Decision-Making And Planning, Jialun Liu, Fan Yang, Lingli Xie, Shijie Li, Tengfei Wang

Journal of System Simulation

Abstract: This paper studies virtual simulation testing technology for intelligent navigation collision avoidance decision-making and planning. The application requirements of intelligent navigation in cargo ships are introduced, and the current research status of collision avoidance decision-making strategies, path planning algorithms and decision-making planning testing technology are analyzed. For the intelligent navigation collision avoidance decision-making and planning capabilities of cargo ships, an intelligent navigation collision avoidance decision-making and planning algorithm is proposed based on the encounter situation division in the collision avoidance rules, combined with the quaternary ship field and Bezier curve interpolation theory. A simulation testing method for decision-making planning …

Parametric Identification Of Ship Maneuvering Motion Response Model Based On Square Root Cubature Kalman Filtering, Qinghao Li, Junsheng Ren, Yan Hua

Journal of System Simulation

Abstract: The system identification algorithm, based on the square root cubature Kalman filter (SRCKF) is proposed to address issues such as low accuracy, poor robustness, and weak generalization ability encountered by the extended Kalman filter (EKF) algorithm in parameters identification of ship maneuvering motion models. This algorithm, within the framework of CKF, replaces the original covariance matrix with its root mean square and utilizes triangular decomposition for prediction and update to enhance identification stability. The EKF is used as a comparison algorithm to identify the parameters of the second-order nonlinear response model of a ship with rudder angles that comply …

Section Point Cloud Denoising Method Based On Enhanced Dbscan And Distance Consensus Evaluation, Chengpeng Ge, Dong Zhao, Rui Wang, Qinghua Ma

Journal of System Simulation

Abstract: A denoising method based on the improved DBSCAN(density-based spatial clustering of applications with noise) algorithm is proposed to address the problem of removing noise points in point cloud data. The statistical filtering method is applied to pre-screen isolated outliers and remove largescale noise from the point cloud. The DBSCAN algorithm is optimized to reduce computational time complexity and achieve adaptive parameter adjustment, thereby dividing the point cloud into normal clusters, suspected clusters and abnormal clusters, and immediately removing abnormal clusters. Distance consensus assessment is applied, and suspect clusters are further evaluated. By calculating the distance between the suspected point …

Parallax-Tolerant Image Stitching With Geometric Structure Protection For Unmanned Ship Visual Perception, Zhilin Yang, Yong Yin, Rukai Zhang, Qianfeng Jing, Sen Jiang, Wenfeng Zhu

Journal of System Simulation

Abstract: In order to address the artifacts caused by misalignment in maritime image stitch with low texture and large parallax, a geometric structure parallax-tolerant image stitch algorithm based on point-line feature registration and optimal seam fusion is proposed. Line segment features are introduced into the traditional homography transformation based on point features, and potential coplanar local line segments are merged into global line segments to provide accurate alignment conditions for seam line fusion. In the image fusion stage, the energy function of seam cutting method is designed by using the color difference and gradient difference of tanh measure and introducing …

A Method Based On Deep Learning For Assisting Sins/Dvl Integrated Navigation, Xinghong Kuang, Aowei Huang

Journal of System Simulation

Abstract: The navigation and positioning accuracy of an Autonomous Underwater Vehicle (AUV) affects the efficiency of the AUV to a certain extent, and since GNSS cannot be used underwater, the integrated navigation system of Strapdown Inertial Navigation System/ Doppler Velocity Log (SINS/DVL) has been widely favored. However, DVL will fail in some cases, and if DVL is isolated directly, the system will become a pure inertial navigation system, which seriously affects the accuracy of navigation and positioning. In order to cope with the situation that DVL is missing in some beams, a DLinear-Informer assisted integrated navigation algorithm is proposed. Through …

High-Resolution Image Reconstruction Of Ect Region Of Interest Based On Finite Element Simulation, Lifeng Zhang, Da Chen

Journal of System Simulation

Abstract: High-resolution image reconstruction of interest region is one of the research hotspots of electrical capacitance tomography (ECT) technology. The ECT model with uniform electrode distribution only has a high sensitivity coefficient at the boundary position of the reconstructed field and is not suitable for imaging regions of interest. In order to improve the sensitivity distribution in the region of interest and improve image resolution, a high-resolution image reconstruction method of ECT region of interest based on finite element simulation is proposed, and the electrode distribution is optimized according to the conformal transformation theory. Simulation experiments are conducted, and the …

Dynamic Data Driven Simulation: An Overview, Xu Xie, Xiaogang Qiu, Yizheng Bao, Kai Xu

Journal of System Simulation

Abstract: Dynamic data driven simulation is a simulation paradigm which integrates simulation and data together. This paradigm continuously feeds real-time data into the simulation, enabling the simulation be dynamically adjusted by the data, which thus improves the simulation-based estimation and prediction capability. Due to this integration, the dynamic data driven simulation can estimate system states and predict future state evolution more accurately. This paper reviews the origins and basic concept of dynamic data driven simulation, and introduces several simulation paradigms originated from the idea of "integrating models with data", and identifies the linkages and differences among them. The particle filterbased …

Uav Dynamic Path Planning Algorithm Combined With Dynamic Window Approach, Bin Liu, Ying Lan, Wentao Huang, Qinqin Fan

Journal of System Simulation

Abstract: To solve the problem of the poor search for optimal performance and obstacle avoidance ability of path planning algorithms in complex dynamic environments, a UAV dynamic path planning algorithm combined with dynamic window approach (UAV-DPPA-DWA) is proposed. In the UAVDPPA- DWA algorithm, a novel elliptic tangent graph algorithm based on the evaluation of offset degree and obstacle distance is proposed to obtain the optimal guidance path for the UAV in static environments. If the UAV detects moving obstacles, a localized obstacle avoidance trajectory will be generated using the dynamic window method with adaptive parameters. Otherwise, the UAV will continue …

A Highly Robust Target Tracking Algorithm Merging Cnn And Transformer, Peijin Liu, Xuefeng Fu, Haofeng Sun, Lin He, Shujie Liu

Journal of System Simulation

Abstract: To address the performance degradation of target tracking algorithms caused by target object deformation, scale variation, fast motion, and occlusion, a highly robust target tracking algorithm that Merging a CNN and Transformer is proposed based on siamese network architecture. In the feature extraction stage, standard convolutions are employed to extract shallow local feature information, while a convolution-like Transformer module is designed in the deep network to model global information. The pixel values in the Transformer are computed using a sliding window significantly reducing computational complexity. In the feature aggregation stage, a multi-head cross-attention module is utilized to construct a …

Fusion Of Improved A* And Dynamic Window Approach For Mobile Robot Path Planning, Rongshen Lai, Lei Dou, Zhiyong Wu, Shuai Sun

Journal of System Simulation

Abstract: The traditional A* algorithm is computationally simple and has short planning paths, but it still suffers from redundancy of inflection points, low search efficiency and zigzagging planning paths. Aiming at the above problems, a fusion algorithm combining the improved A* algorithm and the improved dynamic window approach is proposed for the path planning of mobile robots. For the problem of redundant inflection points, the key nodes are extracted to effectively remove the useless inflection points; for the problem of low search efficiency, a dynamic weighting factor is introduced into the heuristic function of the evaluation function, which changes the …

Study On Robust Chance Constrained Optimization Of Multi-Energy Supply System Based On Wind And Solar Power Combined Output Simulation, Zhe Bao, Wei Li, Xiaofang Zhang, Zongyuan An, Ye Xu

Journal of System Simulation

Abstract: In order to effectively avoid potential imbalance between supply and demand caused by the uncertainty of wind and solar power outputs, and promote the sustained development of the multi-energy supply system, a robust chance-constrained optimization model is developed for identifying optimal operation strategies under complexities and uncertainties through incorporating Copula theory, chance-constrained programming, and robust programming within a general framework. The results show that this model can not only accurately characterize the distribution probability of combined outputs of wind and solar power and formulate the operational strategies under low default risk conditions, but also reduce the proportion of highrisk …

Hybrid Evolutionary Multi-Objective Optimization Algorithm For Vehicle Routing Problem With Simultaneous Delivery And Pickup, Wenqiang Zhang, Xiaomeng Wang, Xiaoxiao Zhang, Guohui Zhang

Journal of System Simulation

Abstract: In order to provide reasonable and effective decision support for logistics enterprises in vehicle distribution route planning, a hybrid evolutionary multi-objective optimization algorithm combining a multi-region mixed-sampling strategy for global search and a local search based on individual route sequence differences is proposed for the problem. A reasonable mathematical model is constructed and the global search strategy is used to make the population individuals to converge quickly to the Pareto front from multiple directions, and the local search strategy is employed to guide the poorly performing individuals in the population to evolve towards the direction of better performing individuals, …

Digital Twin-Driven Structural Thermal Deformation Compensation System For Radio Telescopes, Zhen Lei, Yuhua Liu, Kai Ding, Haoxiang Chen, Dongwei Li

Journal of System Simulation

Abstract: The structural thermal deformation of large-scale radio telescopes under solar thermal load cannot be measured in real-time and compensated dynamically. To solve this problem, a digital twin-driven structural thermal deformation compensation method and system is studied. Based on the fusion of measured data and simulation data, a temperature field modeling method is proposed. A simulation and prediction model of structural thermal deformation is established, and a dynamic compensation model of structural thermal deformation is built. A digital twin-driven dynamic structural thermal deformation compensation system for radio telescopes is developed. A micro-experimental model is studied to verify the effectiveness of …

Gpu Parallel Acceleration Framework For Heuristic Optimization Algorithm, Dongjie Wang, Sixin Wen, Wanzhi Meng, Di Wu

Journal of System Simulation

Abstract: Heuristic optimization algorithm are a type of algorithm that uses large-scale populations for iterative calculations and are widely used to solve all kinds of complex optimization problems. However, such algorithm have the disadvantages of large calculation and long time consumption. To solve this problem, heuristic optimization algorithms are parallelized using GPU and compute unified device architecture (CUDA) to substantially improve computational efficiency. A GPU parallel framework for heuristic optimization algorithm is proposed, which designs an information interaction framework and algorithm parallel optimization strategy with a parallel logical structure, and solves the problem of the dissimilarity of the logical structure …

Research On Digital Twins Technology In Cyberspace Security, Qiankun Ren, Xinli Xiong, Jingju Liu, Qian Yao

Journal of System Simulation

Abstract: Combined with digital twins and cyber-space modeling and simulation, the network digital twins (NDT) technology with in-deep research can enable the development of diverse techniques of cyber security. The basic concept and research history of NDT are summarized, and a taxonomy is proposed to survey applications of NDT. A cyber security-oriented network digital twin model (CyS-NDT) is concluded through the literature. The relationship between the internal security problem of NDT and the method of enabling network security technology is discussed to prospect further challenges and opportunities.

An Improved Cat Swarm Optimization For Heterogeneous Multiple Mobile Robots, Liang Kang, Yi Du, Lihua Yin

Journal of System Simulation

Abstract: At present, it is difficult to achieve the real homogeneity of the members of the multiple mobile robots. The existing swarm intelligence algorithm is also difficult to accommodate the heterogeneity of the team. Focusing on the heterogeneous cooperation of multiple mobile robots, the concept of mother and child robots is proposed. In order to realize the application of swarm intelligence algorithm in heterogeneous multiple mobile robots, the basic cat swarm algorithm is improved. The subdomain and neighborhood of cat swarm are defined, and eight improvements of cat swarm algorithm are proposed, including priority of search direction, extended trajectory tracking …

Research On Path Optimization Algorithm In Dynamic Routing Environment, Xin Xie, Xiaobing Hu, Hang Zhou

Journal of System Simulation

Abstract: In a real dynamic routing environment, static path optimization (SPO) and traditional dynamic path optimization (DPO) tend to encounter issues such as detours, reversals and high computational complexity due to frequent real-time optimization calculation. To address these problems, a novel restart co-evolutionary path optimization (RCEPO) method based on the ripple-spreading algorithm (RSA) is proposed. This method integrates the path optimization process with the dynamic changes of the routing network environment to enhance the effectiveness of path optimization. Moreover, the path reoptimization calculation is performed only when the dynamic changes in the routing environment exceed the predicted range, thereby reducing …

Climate Change And Its Impact On Health: A Global Collaborative Learning Model, Harriet Okatch, Patricia Remshifski, Anita Fennessey, Haley Campbell, Sivia Barnoy, Jason Friedman, Stephen Kern, Rosemary Frasso, Cecilia Sorensen, Tami Bar-Shalita, Louis Hunter

College of Population Health Faculty Papers

To address the health effects of climate change, leaders in healthcare have called for action to integrate climate adaptation and mitigation into training programs for health professionals. However, current educators may not possess sufficient climate literacy and the expertise to effectively include such content in their respective healthcare curricula. We, an international and interprofessional partnership, collaborated with experts to develop and deploy curriculum to increase health educators' and graduate health profession students' knowledge and competencies on climate change. In a tri-step process, the first phase included recruiting interested faculty members from two institutions and varying health professions. In phase two, …

Impact Of Shale Oil And Gas Exploration In The Permian Basin: Public Finances, House Prices, Migration, And Household Income, Bamadou Ouattara

Economics ETDs

This dissertation examines the impacts of shale oil and gas exploration in the Permian Basin, focusing on housing, socio-demographics, petroleum exploration, and environmental effects. It addresses three key research areas: New Mexico's public finances, inter-county migration and household income, and the influence on house prices.

The introductory chapter reviews the boomtown impact model and advocates for its adaptation to current social, economic, and financial landscapes. The second chapter analyzes New Mexico's public finances from 2010-2021, emphasizing oil and gas tax revenues and the need for financial prudence due to industry volatility.

The third chapter uses causal effect techniques to assess …

2024 August 15 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Annual Operations And Maintenance Report Butte Treatment Lagoon System – 2023 (Dated May 28, 2024), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Dynamics Of Dissolved And Particulate Trace Metals In A Snowmelt-Dominated Stream, Provo River, Utah, Usa, Kendra Louise Caskey

Theses and Dissertations

Trace element concentrations vary substantially during snowmelt runoff, with changes in the dissolved versus particulate fractions potentially impacting their movement at the catchment scale. To investigate trace element behavior in a snowmelt dominated stream, we measured concentrations in different size fractions in the Provo River (northern Utah, USA). We sampled the river at three locations during water years 2016-2018 and 2021-2023 for trace metal and major ion concentrations. During the final year, we collected three fractions (unfiltered, <0.45 µm filtered, and <0.22 µm filtered) for trace metal chemistry and calculated the particulate concentration as the difference between the unfiltered and 0.45 µm fraction. Stream measurements included pH, discharge, turbidity, and fluorescent dissolved organic matter (fDOM). We also sampled water sources (soil water, ephemeral streams, and snowpack) to compare trace metal concentrations across the watershed with the stream. Trace metal (Al, Be, Fe, Pb) and rare earth element (REE +Y) concentrations had the highest particulate and dissolved concentrations during snowmelt runoff. In contrast, major cations were primarily found in the dissolved fraction with lowest concentrations during snowmelt runoff. Major cation and particulate metal concentrations increased from upstream to downstream. The increased trace metal and REE + Y concentrations during snowmelt relative to baseflow may be explained by increased discharge and associated increased turbidity and fDOM. A comparison with water sources suggests that dissolved and particulate trace metals in the stream are sourced from flushed soil water, as trace metal transport through the watershed is facilitated by suspended sediment and dissolved organic matter. For most of the trace metals and REE +Y, concentrations were similar in the <0.45 µm and <0.22 µm fractions. Yet Al tended to have higher concentrations in the <0.45 µm fraction, suggesting a colloidal form of Al between 0.22 µm and 0.45 µm may exist. Differences from upstream to downstream may be related to changes in pH, from ~7 at the upper site to ~8 at the lower sites, which would change sorption capacity, saturation indices, or speciation. Our study demonstrates that trace metal concentrations are variable during snowmelt as the metals interact with suspended particles or dissolved organic matter and are influenced by changing water chemistry, with implications for understanding water quality impairments in snowmelt-dominated streams.

Approximation Algorithms For High Multiplicity Strip Packing, Thief Orienteering, And K-Median, Andrew Bloch-Hansen

Electronic Thesis and Dissertation Repository

This thesis investigates three research objectives on three different problems: (1) algorithm design for problems in which the input can be grouped into a small number of classes, demonstrated on the high multiplicity strip packing problem; (2) algorithm design for problems with multiple interdependent sub-problems, demonstrated on the thief orienteering problem; and (3) algorithm design using neural networks with few layers, demonstrated on the k-median problem.

(1) The two-dimensional strip packing problem consists of packing in a rectangular strip of width $1$ and minimum height a set of $n$ rectangles, where each rectangle has width $0 < w \leq 1$ and height $0 < h \leq h_{max}$. We consider the high-multiplicity version of the problem in which there are only $K$ different types of rectangles. For the case when $K = 3$, we give an algorithm that produces solutions requiring at most height $\frac{3}{2}h_{max} + \epsilon$ plus the height of an optimal solution, where $\epsilon$ is any positive constant. For the case when $K = 4$, we give an algorithm yielding solutions of height at most $\frac{7}{3}h_{max} + \epsilon$ plus the height of an optimal solution. For the case when $K > 3$, we give an …

A Sensitivity Equation Framework For Parameter Estimation In Dynamical Systems, Joshua Newey

Theses and Dissertations

We present a new framework for understanding parameter estimation in dynamical systems. The approach is developed within the modeling approach of continuous data assimilation. We outline the basic assumptions that lead to our derivation. Under these assumptions we show that the parameter estimation turns into a finite dimensional nonlinear optimization problem. We show that our derivation reproduces and extends the algorithm originally developed in [9]. We then implement these methods in three example systems: the Lorenz '63 model, the two-layer Lorenz '96 model, and the Kuramoto Sivashinsky equation. So as to remain sufficiently general, our derivations are largely formal; we …

An Introduction To Category Theory, Joseph Kopp

Electronic Proceedings of Undergraduate Mathematics Day

Category theory is a relatively new field of mathematics that has grown much in popularity in recent years. It is a general theory of mathematical structure that lends itself to making overarching, yet deep, connections between many branches of mathematics. This power to make such wide-reaching statements is what has drawn many to study it. However, category theory has also been criticized for being "abstract nonsense," in that some believe the theory to be too abstract to carry meaning, much less be applied to the real world. The goal of this paper is to introduce the main ideas of category …

Derivation Of The Sliding Catenary Curve Via Calculus Of Variations, Ethan Shade

Electronic Proceedings of Undergraduate Mathematics Day

Using the calculus of variations this paper derives the general equation for the "sliding catenary curve" — a hanging chain with terminal links free to slide along two poles, one tilted and one vertical. By applying physical assumptions along with the Euler-Lagrange equation, the Beltrami identity, the Legendre-Clebsch condition, the transversality condition, Lagrange multipliers, and the isoperimetric constraint, we derive the general equation for the sliding catenary curve through a functional that measures the potential energy of the hanging chain. This general equation is then compared to a real-life construction of a sliding catenary curve. Additionally the paper explores a …

Mathematical Modeling, Analysis, And Simulation Of Patient Addiction Journey, Adan Baca, Diego Gonzalez, Alonso G. Ogueda, Holly C. Matto, Padmanabhan Seshaiyer

CODEE Journal

This paper aims to develop a mathematical model to study the dynamics of addiction as individuals go through their detox journey. The motivation for this work is three fold. First, there has been a significant increase in drug overdose and drug addiction following the COVID-19 pandemic, and addiction may be interpreted as a infectious disease. Secondly, the dynamics of infectious disease could be modeled via compartmental models described by differential equations and one can therefore leverage the existing analytical and numerical methods to model addiction as a disease. Finally, the work helps to inform how mathematical models governed by differential …

Northern Fur Ssal Vibrissae Organochlorine Contaminant Concentrations, Dimitri Giarikos, Amy Hirons, Courtney White

SECLER Data

The eastern Pacific stock of northern fur seals (Callorhinus ursinus) on the Pribilof Islands has experienced population declines since 1980. The decline may be due to anthropogenic persistent organic pollutants (POPs) which bioaccumulate, are toxic, and persistent. This study conducted a comparison of 21 organochlorine (OC) and 39 polybrominated diphenyl ether (PBDE) analyte concentrations utilizing archived vibrissae (whiskers) from individual fur seals sampled in 1993 (n=30) and 2013 (n=41). The PBDEs had values five times greater than the legacy status OCs. There were no significant mean concentration differences between 1993 and 2013 for total organochlorines (ΣOCs), or total …

Northern Fur Seal Vibrissae Polybrominateddiphenylether Concentrations, Dimitri Giarikos, Amy Hirons, Courtney White

SECLER Data

The eastern Pacific stock of northern fur seals (Callorhinus ursinus) on the Pribilof Islands has experienced population declines since 1980. The decline may be due to anthropogenic persistent organic pollutants (POPs) which bioaccumulate, are toxic, and persistent. This study conducted a comparison of 21 organochlorine (OC) and 39 polybrominated diphenyl ether (PBDE) analyte concentrations utilizing archived vibrissae (whiskers) from individual fur seals sampled in 1993 (n=30) and 2013 (n=41). The PBDEs had values five times greater than the legacy status OCs. There were no significant mean concentration differences between 1993 and 2013 for total organochlorines (ΣOCs), or total …

Re: Butte Priority Soils Operable Unit (Bpsou) Revised Draft Final Insufficiently Reclaimed Sites Field Sampling Plans (Fsps) And Responses To Agency Comments, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.