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Articles 1921 - 1950 of 292687
Full-Text Articles in Entire DC Network
Four-Dimensional Gradient Integration: Reform And Practice On Modeling And Simulation Courses For Management Disciplines, Bin Wu, Huagang Tong, Zhiyong Cui, Feiyi Yan
Four-Dimensional Gradient Integration: Reform And Practice On Modeling And Simulation Courses For Management Disciplines, Bin Wu, Huagang Tong, Zhiyong Cui, Feiyi Yan
Journal of System Simulation
In the process of course implementation, local universities generally face problems such as students' weak mathematical and physical foundations, disconnection between teaching content and technological frontiers, single teaching method, and fragmented cultivation of practical capability. Based on long-term teaching reform practice, a four-dimensional gradient integration teaching model of "value guidance, knowledge restructuring, scenario innovation, and capability progression" was proposed, and its theoretical logic, implementation path, and practical effect were systematically elaborated. This model can effectively stimulate students' intrinsic motivation for learning, promote the digital and intelligent updating of teaching content, expand the teaching scenario of industry-education integration, and realize …
Improved Nsga-Ii For Dual-Resource Flexible Job Shop Scheduling Considering Worker Load, Guohui Zhang, Yuan Ren, Changjun Wu, Xiaofei Kou
Improved Nsga-Ii For Dual-Resource Flexible Job Shop Scheduling Considering Worker Load, Guohui Zhang, Yuan Ren, Changjun Wu, Xiaofei Kou
Journal of System Simulation
For the dual-resource-constrained flexible job shop scheduling problem considering worker load, an evolutionary algorithm integrating reinforcement learning was proposed. A three-stage encoding conforming to the problem characteristics was designed, and three initialization methods were combined to improve the population quality; a left-insertion decoding method based on worker load was designed to ensure that the completion time of the operation is less than the maximum processable time of the worker on the current day; two neighborhood structures based on the critical path were constructed to enhance the local exploration ability of the population; reinforcement learning was integrated to enable the …
Parameter Identification Of Permanent Magnet Synchronous Motors Based On Igwo-Aekf, Lei Yao, Zijian Zheng, Tianhao Li, Yulun Chi
Parameter Identification Of Permanent Magnet Synchronous Motors Based On Igwo-Aekf, Lei Yao, Zijian Zheng, Tianhao Li, Yulun Chi
Journal of System Simulation
The accuracy of the traditional EKF in parameter identification of the PMSM tends to be degraded under load changes or abrupt changes in internal parameters of the motor. This paper proposes an IGWO adaptive interconnected Kalman filter observer, which constructs an adaptive mechanism that combines the innovation and residuals to achieve dynamic adjustment of the process noise matrix and system noise matrix, thereby avoiding the problem of reduced parameter identification accuracy due to reliance on fixed covariance matrices under operating condition changes. A multi-parameter interconnected coupling compensation identification model for PMSM is built to mitigate the effects of measurement noise …
Research On Control Strategy For Shortest Time Occupancy Of Auv Based On Improved Td3, Wenzhe Ren, Min Li, Xiangguang Zeng, Tao Zhang, Dijie Xie, Bei Peng
Research On Control Strategy For Shortest Time Occupancy Of Auv Based On Improved Td3, Wenzhe Ren, Min Li, Xiangguang Zeng, Tao Zhang, Dijie Xie, Bei Peng
Journal of System Simulation
Existing occupancy models fail to fully consider the interference of underwater time-varying ocean currents and task time constraints, and AUVs lacks real-time motion control. To address these issues, a shortest time occupancy method based on quantile regression and distributed TD3 was proposed. The Bayesian inference method was used to identify hydrodynamic parameters, and the kinematic and dynamic models of AUVs were established; the shortest time occupancy equation was constructed, and the occupancy target point and occupancy time were solved; a first-order Gauss-Markov process was introduced to simulate the time-varying ocean current environment, and the training of control strategy for AUV …
Impact Angle-Constrained Dive Maneuver Guidance Method For Hypersonic Vehicles, He Wang, Gang Lei, Shaopeng Li
Impact Angle-Constrained Dive Maneuver Guidance Method For Hypersonic Vehicles, He Wang, Gang Lei, Shaopeng Li
Journal of System Simulation
To address the impact angle control and maneuvering flight problem of hypersonic vehicles in the dive phase, this paper proposed a tracking guidance method integrating optimal Bézier curves and super-twisting sliding mode control. A three-dimensional Bézier curve trajectory satisfying the impact angle constraint was designed, and the maneuvering flight in dive phase was achieved by adding dynamic control points; to optimize impact velocity, a rapid calculation method for the impact velocity of the vehicle flying along the curve was derived, and the optimal reference trajectory was obtained by optimizing the control point parameters through sequential quadratic programming; to ensure …
Application Of Improved Multi-Objective Differential Algorithm In Robotic Arm Multi-Objective Trajectory Planning, Manqiang Liu, Ziqiang Shang
Application Of Improved Multi-Objective Differential Algorithm In Robotic Arm Multi-Objective Trajectory Planning, Manqiang Liu, Ziqiang Shang
Journal of System Simulation
It is difficult for single-objective trajectory planning methods to meet the requirements of precision, diversity and complexity of robotic arms. A trajectory planning model based on an improved multi-objective differential evolution algorithm (guided multi-objective differential evolution, GMODE) algorithm is proposed. Cubic polynomial interpolation and B-spline curves are employed to construct multi-objective functions, while GMODE is adopted to overcome the limitations of traditional algorithms, such as insufficient population diversity, the tendency to fall into local optima, and slow convergence. A grouping strategy, parameter generation mechanism, and elite mutation based on fuzzy Cmeans clustering are introduced to optimize B-spline control nodes. …
Robot Friction Force Compensation Algorithm Integrating Temperature And Speed Factors, Jinwang Lü, Ankai Ying, Ming Li, Tao Song, Jie Zhang, Fanghui Qiu, Changcheng Shi, Guokun Zuo, Jialin Xu
Robot Friction Force Compensation Algorithm Integrating Temperature And Speed Factors, Jinwang Lü, Ankai Ying, Ming Li, Tao Song, Jie Zhang, Fanghui Qiu, Changcheng Shi, Guokun Zuo, Jialin Xu
Journal of System Simulation
Insufficient friction force compensation accuracy degrades motion smoothness, stability, and assistive compliance of elbow joint rehabilitation robots. To address this issue, an improved Stribeck friction force model integrating temperature and speed factors was proposed. The model employed an exponentially decaying friction factor to describe the characteristic that the increase rate of friction force slowed down with the rise of the robot's operating speed and designed a viscous function considering temperature effects to suppress friction force fluctuations caused by temperature changes. Experimental results indicate that the model achieves stable friction force compensation under different operating states of the robot and has …
Current Status And Prospects Of Complex Scene Reconstruction Based On Gaussian Splatting, Hong'an Li, Jiale Yang, Qingfang Liu, Yu Shi
Current Status And Prospects Of Complex Scene Reconstruction Based On Gaussian Splatting, Hong'an Li, Jiale Yang, Qingfang Liu, Yu Shi
Journal of System Simulation
Three-dimensional Gaussian splatting (3DGS) provides an alternative approach for novel view synthesis from the perspective of explicit representation. By reconstructing scenes using 3D Gaussian primitives and replacing traditional ray integration with a point-based rasterization process, it not only improves training and rendering efficiency but also offers new insights for complex scene reconstruction. This paper divided 3DGS-based complex scene reconstruction methods into three major categories and elaborated on them around large-scale scenes, sparse views, and dynamic scenes. It reviewed the current development status of this field and pointed out possible future research directions.
Pattern Identification And Mechanism Analysis Of Nonlinear Oscillations In Grid-Connected Direct-Drive Wind Turbines, Libin Wen, Shaopu Tang, Xianfa Hu, Jinji Xi, Tongtong Zhang, Hong Hu, Weijie Zhang
Pattern Identification And Mechanism Analysis Of Nonlinear Oscillations In Grid-Connected Direct-Drive Wind Turbines, Libin Wen, Shaopu Tang, Xianfa Hu, Jinji Xi, Tongtong Zhang, Hong Hu, Weijie Zhang
Journal of System Simulation
Taking a grid-connected direct-drive wind turbine system as an example, a comprehensive model is developed that incorporates nonlinear elements such as prime mover control, machine-side and grid-side converter control, multiple limiters, and control switching. A nonlinear oscillation pattern identification method based on density clustering and manual identification is proposed. The results show that the proposed method can efficiently identify various typical patterns, including quasi-constant amplitude oscillations, period-doubling oscillations, and chaotic oscillations. Oscillations dominated by nonlinear factors such as control switching, limiter collision, and limiter saturation are essentially caused by the transition of the associated components from passive responses to …
Experimental And Simulation Study On Energy Release Of Extended Sources Influenced By Atmospheric Pressure Variation, Kai Guo, Feiyu Zhao, Hao Zhang, Liang Wang, Kai Zhang
Experimental And Simulation Study On Energy Release Of Extended Sources Influenced By Atmospheric Pressure Variation, Kai Guo, Feiyu Zhao, Hao Zhang, Liang Wang, Kai Zhang
Journal of System Simulation
To investigate the energy release characteristics of extended sources in low-pressure environments, a combined experiment and simulation approach was adopted. Four typical altitudecorresponding pressures were selected as experimental conditions. An infrared thermal imager was employed to monitor parameters such as combustion temperature, radiance, and combustion area during the combustion process of the extended source. When the pressure decreases from 101 kPa to 30 kPa, the ignition time of the extended source doubles; the total energy release attenuates by 44.78%, and the combustion area reduces by 45.95%, but the fluctuations of peak temperature and average temperature are less than 3%, …
Object Detection Networks And Their Interpretability In Rain, Fog, And Snow Scenarios, Yanji Jiang, Jiayu Cui, Hao Dong, Daqian Liu, Bowen Fei, Miao Yu, Jinshan Huang
Object Detection Networks And Their Interpretability In Rain, Fog, And Snow Scenarios, Yanji Jiang, Jiayu Cui, Hao Dong, Daqian Liu, Bowen Fei, Miao Yu, Jinshan Huang
Journal of System Simulation
To address the severe degradation of object detection performance under extreme weather conditions, a detection framework based on the Kolmogorov-Arnold theorem, termed KADet, is proposed. A dynamic Kolmogorov-Arnold Transformer is designed, which leverages learnable nonlinear activation functions to enhance the modeling capability for complex distortions introduced by weather degradation. A Kolmogorov-Arnold spatial-channel network is developed by integrating KAT convolution with spatial-channel convolution to strengthen feature learning of relationships between targets and backgrounds in degraded scenes. An improved loss function is introduced to guide the optimization of the activation functions, and interpretability is analyzed through visualization of their curves. …
Managing Prairie Dogs On Agricultural Lands, Cory Farnsworth, S. Nicole Frey
Managing Prairie Dogs On Agricultural Lands, Cory Farnsworth, S. Nicole Frey
All Current Publications
While prairie dogs are an important species in the region because their burrows provide shelter for many wildlife species, they are also preyed upon by many mammals and birds. However, because of the damage they can cause to cropping and range systems, their populations may occasionally need to be controlled. After you have identified which prairie dog species you are in conflict with and the scope of the damage, you will want to decide how to manage them. This fact sheet provides information on control options and the general ecology of the three prairie dog species in Utah.
Geothermal Energy In Utah: A Safe Technology With Limited Environmental Impacts, Joseph Harding, Kendall Becker, Logan Mitchell, Jennifer Bodine, Scott Hotaling
Geothermal Energy In Utah: A Safe Technology With Limited Environmental Impacts, Joseph Harding, Kendall Becker, Logan Mitchell, Jennifer Bodine, Scott Hotaling
All Current Publications
Geothermal energy has the potential to transform Utah’s electricity landscape, driving a future with improved air quality, lower carbon emissions, and fewer environmental impacts. In this fact sheet, we provide an overview of geothermal energy and its potential environmental implications in Utah. We highlight that recent geothermal projects in Utah do not use fresh water and that new well designs are expected to reduce the consumption of salty, brackish water. If these efforts are successful, geothermal energy would have lower water consumption, reduced seismic risk, and a similarly low land-use footprint compared to fossil fuel sources of electricity.
Frequency And Radiative Analysis Of Random Yagi-Uhf/Vhf Phased Array, Luis M. Bres, Luis A. Hernandez, Teviet Creighton
Frequency And Radiative Analysis Of Random Yagi-Uhf/Vhf Phased Array, Luis M. Bres, Luis A. Hernandez, Teviet Creighton
Physics & Astronomy Faculty Publications
This study investigates a phased array ground station capable of tracking multiple sources, multi-beamforming, electronic steering, easy scaling, and low cost. The project will develop a 20-pair dual-polarized Yagi-UHF/VHF phased array, comparing the parameters of random and uniform layouts. This study will be divided into two domains: frequency, and radiative domain. The frequency domain will explore the reception and transmission spectra analysis under several scenarios for our antennas. The radiative domain will explore the following: general side lobe analysis across both elevation and azimuth, antenna element sweep analysis, electronic beam steering analysis, electro-mechanical beam steering analysis, array density analysis, and …
A Mathematical Model Of The Interactions Between A Collagen Lattice, Fibroblasts, And Fixed Surfaces With Varying Topographies, Mary Jenkins
A Mathematical Model Of The Interactions Between A Collagen Lattice, Fibroblasts, And Fixed Surfaces With Varying Topographies, Mary Jenkins
Theses and Dissertations
Collagen is an important structural protein in the body, which plays a role in wound healing, particularly the contraction process. Collagen lattices have been studied for nearly 50 years to provide insight into wound contraction. In some cases, collagen interacts with surfaces that have fixed shapes, such as medical implants. Our model focuses on the interactions of a collagen lattice with such a fixed surface. We mathematically model a collagen lattice as a network of nodes connected by springs. We also model fixed surfaces that have various topographies. Our model includes fibroblast cells that connect to both surfaces and remodel …
Qualitative Analysis Of Solutions To A General Class Of Nonlinear Difference Equations With Applications, Osama Moaaz, Mohamed F. Abouelenein, Mona Anis
Qualitative Analysis Of Solutions To A General Class Of Nonlinear Difference Equations With Applications, Osama Moaaz, Mohamed F. Abouelenein, Mona Anis
Mathematical Modelling and Numerical Simulation with Applications
This work examines the qualitative behavior of a general class of difference equations. We establish criteria guaranteeing the stability, periodicity, and boundedness of the solutions of the equation under consideration. In addition, we identify its invariant intervals. The theoretical results are subsequently applied to various special cases, among them the May--Host model. Numerical simulations are presented to demonstrate the dynamics of the solutions and to validate the theoretical analysis.
An Analysis Of Heat Spread Through Smoldering Pine Needles, Timothy Keith
An Analysis Of Heat Spread Through Smoldering Pine Needles, Timothy Keith
Theses and Dissertations
The goal of this thesis is to calculate the average speed of flame spread through smoldering pine needles. We present two different models for doing this: the first is a very large system of ODEs meant to represent the spread of flame through individual needles, the second is a macroscopic model based on the porous medium PDE. Simulations are run for each of these models and compared to each other as well as to existing models and experimental results.
The Soil Crisis In Modern Food Systems: Rethinking Agricultural Land Use, Antonia Moure Richard
The Soil Crisis In Modern Food Systems: Rethinking Agricultural Land Use, Antonia Moure Richard
Journal of Food Law & Policy
Feeding a larger world while preserving the resource that makes agriculture possible—soil—poses a governance problem. By 2050, food systems must support 9.8 billion people even as prevailing practices continue to degrade soils that are non-renewable on human timescales. Technological fixes (e.g., vertical farming, hydroponics) may complement production, but they cannot substitute for soil at scale. The question that follows is simple: are current uses of soil compatible with the future needs of food systems? This article argues that without a shift in governance, short-run productivity gains are achieved by drawing down the soil asset, thereby undermining long-run food security and …
Supersymmetric Quantum Fields Via Quantum Probability, Radhakrishnan Balu
Supersymmetric Quantum Fields Via Quantum Probability, Radhakrishnan Balu
Journal of Stochastic Analysis
The super version of imprimitivity theorem is available now to describe global supersymmetry of systems using the representations of super Lie groups (SLG). This result uses the equivalence between super Harish- Chandra pairs and super Lie groups, at the categorical level, and is applicable to super Poincaré group and generalizes a smooth SI to super context. We apply the result to build supersymmetric quantum fields. Towards this end, we set up a super Fock space of a disjoint union of super Hilbert spaces which is equivalent to super tensoring of boson (even) part symmetrically and that of fermion (odd) part …
Convergence To Fractional Brownian Motion For Weighted Random Sums In Besov Space, Ibrahima Mendy
Convergence To Fractional Brownian Motion For Weighted Random Sums In Besov Space, Ibrahima Mendy
Journal of Stochastic Analysis
We consider infinite sums of weighted i.i.d. random variables, with finite variance and arbitrary distribution, and we derives conditions for the weak convergence in Besov space of normalized sums to fractional Brownian motion (fBm).
Pricing Variance Swaps Using Extended Heston Model, Semere Gebresilasie, Mulue Gebreslasie, Indranil Sengupta
Pricing Variance Swaps Using Extended Heston Model, Semere Gebresilasie, Mulue Gebreslasie, Indranil Sengupta
Journal of Stochastic Analysis
Abstract. In this study, we introduce a variance swap for the underlying asset utilizing the Heston model, incorporating a long-term variance that is treated as a stochastic function of time. We develop a closed-form solution for the variance swap under this framework, where the log returns are driven by a compound Poisson process. Our analysis of historical data reveals that long-term variance is not constant; instead, it fluctuates over time, reflecting market dynamics more accurately. By integrating this time-varying long-term variance into the model, we achieve an improvement in prediction performance of approximately 60%. Furthermore, we perform model calibration using …
Non-Euclidean Geometries And Fairness Constraints In Advanced Clustering, Arnab Seal
Non-Euclidean Geometries And Fairness Constraints In Advanced Clustering, Arnab Seal
Master’s Dissertations
A fundamental challenge in modern unsupervised learning is adapting classical clustering algorithms to handle complex, real-world data constraints. Traditional models often assume data resides in a flat, Euclidean space and optimize strictly for cluster cohesion, thereby failing to capture intrinsic hierarchical structures and ignoring sociotechnical demographic biases. This thesis addresses these critical limitations by extending generalized mean-shift dynamics into two novel clustering frameworks. First, to natively accommodate data with tree-like structures (e.g., taxonomies and social networks), we propose Hyperbolic Gaussian Blurring Mean Shift (HypeGBMS). By projecting data into the Poincar´e ball model and utilizing M¨obius vector space operations, HypeGBMS successfully …
Leveraging Spatial Statistics For Domain Adaptation Of Vision Language Models In Medical Vqa, Himanshu Raj
Leveraging Spatial Statistics For Domain Adaptation Of Vision Language Models In Medical Vqa, Himanshu Raj
Master’s Dissertations
Recent advances in Vision–Language Models (VLMs) have demonstrated strong performance in Medical Visual Question Answering (Medical VQA) task. Although they perform very well within their domains, these models often experience issues with their generalization ability on unknown clinical distribution data because of different imaging technologies and patient groups used in various medical facilities. Generalization problems faced by these models make their practical application in the field of VLM-based medical VQA systems rather difficult. To overcome this limitation we proposed our method named Spatial Semantics Aware Domain Adaptation (SSADA), which is an integrated framework that combines both finetuning and prompt-based in-context …
Predictive Importance Sampling Based Coverage Verification For Multi Uav Trajectory Planning, Snehashish Ghosh
Predictive Importance Sampling Based Coverage Verification For Multi Uav Trajectory Planning, Snehashish Ghosh
Master’s Dissertations
In next-generation wireless networks, unmanned aerial vehicle (UAV) networks are emerging as a promising solution for ultra-reliable low-latency communication (URLLC). A key challenge in millimeter-wave UAV networks is ensuring that mobile users are always in line-of-sight (LoS) coverage, since the current snapshot-based trajectory planning approach does not consider the mobility of the users during the decision interval, resulting in disastrous LoS gaps. For continuous coverage verification, standard uniform sampling is too computationally expensive, as it would need a large number of samples to estimate rare failure events that have latencies that are not suitable for real-time requirements. In this work, …
Re: Conditional Approval Letter For Butte Priority Soils Operable Unit Draft Final Leak Detection Monitoring Plan (Dated May 13, 2026), Emma Rott
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Movement Ecology And Population Dynamics Of Box-Nesting Black-Bellied Whistling-Ducks (Dendrocygna Autumnalis) In Louisiana, Katie E. Miranda
Movement Ecology And Population Dynamics Of Box-Nesting Black-Bellied Whistling-Ducks (Dendrocygna Autumnalis) In Louisiana, Katie E. Miranda
LSU Master's Theses
Understanding demographic and behavioral processes underlying population dynamics is essential for effective wildlife management, especially for species subject to harvest pressure or experiencing population shifts. Black-bellied Whistling-Ducks (Dendrocygna autumnalis) are currently undergoing a notable northward range expansion and are increasing in abundance across the southeastern United States, raising management concerns for both ecological and economic reasons. As a result, there is growing public support for a special Black-bellied Whistling-Duck-specific harvest season, yet little research has been conducted on this species, particularly within newly-established populations. To address this gap, I conducted this study with the goal of evaluating seasonal …
Learning Trajectories Of Online Batch Selection Methods, Luke Green
Learning Trajectories Of Online Batch Selection Methods, Luke Green
Theses and Dissertations
Modern deep neural networks achieve strong performance on large-scale datasets, but often require substantial training time. Online batch selection methods seek to reduce this cost by updating models on informative subsets of each batch rather than on all available examples. Recently introduced methods leverage teacher models and report substantial speedups, particularly in noisy-label settings. However, comparisons are often based on the number of epochs required to reach a target test accuracy, a coarse metric that is sensitive to implementation details and may obscure important differences in learning dynamics. In this thesis, we implement several online batch selection methods in a …
Advancing Data Usability, Activity Modeling, And Stability Optimization In Computational Enzyme Design, Spencer Gardiner
Advancing Data Usability, Activity Modeling, And Stability Optimization In Computational Enzyme Design, Spencer Gardiner
Theses and Dissertations
A grand challenge of computational biology is to computationally design, in a single pass, a protein sequence that catalyzes an arbitrary chemical reaction at a high rate under specified conditions [1]. This work details advances in three essential areas on the path to that goal: data quality, activity prediction and modeling, and stability optimization. The structure and implementation of the Allotrope Simple Model (a FAIR data format for many scientific instruments) was examined in [2], setting the stage for training deep learning models on high-quality experimental datasets from diverse sources. In [3], the limits of physics-based and deep learning tools …
Beyond Single Images: A Comprehensive Benchmark For Album-Level Vision-Language Understanding, Shawn Huang
Beyond Single Images: A Comprehensive Benchmark For Album-Level Vision-Language Understanding, Shawn Huang
Theses and Dissertations
Automatic album organization has been studied extensively over the past decades due to significant progress in digital photography. Recent Vision-Language Models (VLMs) have shown strong performance on multi-image understanding, making them natural candidates for automating album organization workflows. While VLMs’ abilities in multi-image understanding have been widely studied, their performance on album organization remains underexplored. To bridge this gap, we introduce AlbumBench, the first comprehensive benchmark for automatic album organization. Specifically, we (1) define album organization tasks as photo selection for album-specific user objectives, photo rating according to how well user intents are fulfilled, and album-specific photo grouping given a …
Long-Term Monitoring Of The Optical Performance Of The Primary Mirrors At The Coihueco And Loma Amarilla Sites Of The Pierre Auger Observatory, A. Abdul Halim, P. Abreu, M. Aglietta, M. Ahmed, I. Allekotte, K. Almeida Cheminant, B. Fick, K. Nguyen, D. Nitz, Et Al.
Long-Term Monitoring Of The Optical Performance Of The Primary Mirrors At The Coihueco And Loma Amarilla Sites Of The Pierre Auger Observatory, A. Abdul Halim, P. Abreu, M. Aglietta, M. Ahmed, I. Allekotte, K. Almeida Cheminant, B. Fick, K. Nguyen, D. Nitz, Et Al.
Michigan Tech Publications
This paper presents the results of an optical performance monitoring campaign for the primary mirrors installed in fluorescence telescopes at the Coihueco and Loma Amarilla sites at the Pierre Auger Observatory in Argentina. Since the end of 2003, this effort has developed into a unique long-term dataset that addresses the performance of the primary mirrors. We have focused on the scattering characteristics and specular reflectance of mirror segments, as well as their evolution over several years of operation. Despite being housed in climate-controlled buildings, dust accumulation, impurities, and natural aging — such as oxidation or other chemical or physical degradation …