Digital Commons Network^™

Research On Completion Method For Trajectory Based On Image Representation And Collaborative Feature Perception, Ye Tao, Jinhui Tang, Chen Zhou, Chong Wang

Journal of System Simulation

To address the constraints imposed by missing trajectory data in surveillance systems on the efficacy of civil aviation safety monitoring, as well as the limitations on the development and application of advanced technologies within trajectory-based operational frameworks, a completion method for trajectory based on image representation and collaborative feature perception was proposed. A conversion strategy for trajectory image representation was designed to reformulate the trajectory completion task as a deterministic image completion problem, effectively circumventing the cumulative error problem of traditional time-series data caused by the limitation of recurrent neural network inference mechanisms.A regression model fusing a multi-kernel hybrid …

Capacity Market Trading Strategies Of Generators Based On Per-Maddpg Algorithm, Yanbin Li, Zhaolun Pan, Xinyue Ma, Minghao Song, Yujie Hu, Xiaoda Xue

Journal of System Simulation

Considering the issue of how power generators trade off their quantity and price bidding strategies to maximize profits in different capacity market environments, a capacity market bidding equilibrium model is constructed. Recognizing the limitations of traditional solution methods, which rely on the assumption of complete information and have low utilization of historical trading strategy information, a capacity market trading simulation method based on prioritized experience replay multi- agent deep deterministic policy gradient (PER-MADDPG) is proposed. The action space is constructed using quantity bidding strategy and price bidding strategy, and the state space is constructed using historical transaction strategies and winning …

Second Annual Advances In Business Education Conference 2026 Proceedings, Kelsey Metz

Advances in Business Education (ABE) Conference Proceedings

Conference Overview: The Second Annual Advances in Business Education (ABE) Conference was held on May 21–22, 2026, at Lincoln Memorial University in Harrogate, Tennessee. Hosted by the LMU School of Business, the ABE Conference exists to promote teaching excellence, scholarly inquiry, and regional engagement through innovation and collaboration in business education.

With a focus on fostering meaningful dialogue among educators, researchers, students, and industry professionals, the conference welcomed more than 70 attendees representing 11 institutions from across the Appalachian region and beyond.

The event was structured around four key tracks:

Pedagogy and Teaching Excellence: Showcasing innovative teaching methods, instructional technologies, …

Labor Market Responses To Ai: Measuring Wage Effects Across U.S. Occupations, Kaitlin Pham, Karla Rodriguez

Undergraduate Economics Working Paper Series

Artificial intelligence (AI) is rapidly changing economies around the world, with some experts predicting an impact greater than the Industrial Revolution. As AI becomes more common in daily life and business, questions have grown about how it might affect jobs, wages, and inequality. The rise of automation and highly capable AI models has made people wonder which occupations will benefit and which might be at risk. This study looks at how exposure to AI technologies affects wage trajectories in the United States. Using occupational-level data from O*NET and the U.S. Bureau of Labor Statistics, we build an AI exposure index …

The Current Status Of Utah Women & Girls: A Research Synopsis: 2026, Susan R. Madsen, Corinne Clarkson

Marketing and Strategy Faculty Publications

In 2025, U.S. News and World Report rated each state using 71 metrics across eight categories. Utah was rated the #1 “Best State Overall” for the third year in a row, ranking first in fiscal responsibility and third in both the economy and infrastructure categories and fourth in education.¹ Utah was also ranked number one for “Economic Outlook” by Rich States, Poor States in 2025, a forward-looking forecast that is based on 15 state policy variables.² WalletHub ranked Utah as the second “Most Charitable State” and the number one state for volunteering and service.³ In addition, ConsumerAffairs …

Robust Identification Of Black-Box Nonlinear Ssm Using Expectation-Maximization, Xiaonan Li, Tao Chao, Ping Ma, Ming Yang, Yuxuan Wang

Journal of System Simulation

To address the robust identification problem of nonlinear state space models (SSM) with outliers, missing observations, and unknown state equations, this paper proposes a modeling method based on eigenfunction expansion, Gaussian-process state-space models (GP-SSM), and Student-t distribution. The proposed approach consists of: modeling the state transition function using eigenfunctions and pre-encoding the priors of basis function coefficients via GP-SSM to enhance flexibility; modeling observations as a Student-t distribution with unknown parameters to enhance robustness against outliers; proposing the enhanced particle Gibbs with ancestor sampling (EPGAS) algorithm to adapt to state estimation in scenarios with missing observations; and deriving unknown model …

Topology Identification Of Complex Dynamical Networks Under Dynamical Saturation Inputs, Haoyu Wang, Yayong Wu, Guoping Jiang, Ying Zheng, Xuanxin Zhou

Journal of System Simulation

In view of the problem that the controller inputs in actual engineering systems are vulnerable to the constraints of dynamical saturation and delayed dynamical saturation, which makes it difficult for the topology identification of complex dynamical networks to adapt to real physical scenarios, a topology identification method based on the drive-response mechanism was proposed. A response network with the same dynamical characteristics and node scale as the original network was constructed, and the dynamical equation of synchronization error between the drive-response networks was established. A controller with dynamical saturation and delayed dynamical saturation and a topology identifier were designed, and …

Robust Two-Stage Mimo-Ofdm Channel Estimation Method Against Sensing Errors, Yi Peng, Jun Wang, Qingqing Yang, Jianming Wang, Hui Li

Journal of System Simulation

To address the challenges of performance degradation, high pilot overhead, and high computational complexity in traditi onal channel estimation methods for integrated sensing and communication (ISAC) assisted MIMO-OFDM systems when radar sensing information contains errors, this paper proposes a robust two-stage sparse channel estimation framework designed to be tolerant of sensing errors. In the first stage, a residual energy weighted simultaneous orthogonal matching pursuit (REW-SOMP) algorithm is designed. Leveraging locally adaptive dictionary expansion and a residual- weighted path selection mechanism, it accurately captures communication-associated paths even under sensing errors. The second stage introduces an adaptive penalty factor alternating direction method …

Dynamic Task Planning For Wargaming Based On Large Language Models, Yingang Liu, Ming Ma, Ronghua Zhang

Journal of System Simulation

To address the problems of great difficulty in intelligent decision-making and insufficient dynamism in task planning caused by the complex adversarial environment and strong uncertainty in wargaming tasks, this paper proposed a hierarchical Agent collaborative decision-making framework based on large and small model synergy.Through a multi-level structure, the hierarchical decoupling and dynamic coordination of battlefield tasks were achieved. A memory management module was constructed, and a query optimization mechanism driven by large language models was introduced to dynamically perceive the decision-making process and query intent, completing the semantic reconstruction and context completion of raw queries. A time-driven two-stage task …

Ultra-Short-Term Photovoltaic Power Prediction Based On Improved Patchtst Considering Data Drift, Huawei Mei, Penghui Yang, Yang Yu

Journal of System Simulation

Existing PV power prediction methods often suffer from limited accuracy and robustness due to three key shortcomings: relying on single-point mapping that cannot fully extract local temporal patterns; inadequate exploration of the global temporal dependencies in PV output, and failure to account for prevalent data drift phenomena. To overcome these limitations,an improved patch time series transformer (PatchTST) based approach is proposed for ultra-short-term PV power prediction. The methodology applies rough set theory for feature dimensionality reduction, effectively preserving critical decision information by analyzing both feature-label relationships and inter-feature correlations. An enhanced PatchTST model with a modified channel-independent mechanism extracts …

Modeling Of Penicillin Fermentation Process Based On A Multi-Stage Lhs-Eprcc Method, Quan Li, Peng Su, Haiying Wan, Chengxi Zhang, Zhijian He, Yiyang Ni

Journal of System Simulation

This paper focused on the modeling of microbial fermentation processes under varying production environments and proposed a novel approach. Considering that the dynamic characteristics of microorganism s differ across growth stages, we introduced the concept of multi-stage sensitivity analysis, in which each stage was investigated separately. The fuzzy C-means (FCM) algorithm was employed to cluster process data under nominal conditions, thereby dividing the penicillin fermentation process into distinct growth stages. Based on this division, the Latin hypercube sampling with partial rank correlation coefficient (LHS-EPRCC) method was applied to conduct sensitivity analysis for each stage, identifying an importance parameter set (IPS) …

Multi-Agent Reinforcement Learning Method For Wargame Simulation Based On Suboptimal Demonstration Guidance, Zicong Zhou, Junjie Zeng, Yue Hu, Zhengqiu Zhu, Quanjun Yin

Journal of System Simulation

To address issues such as fixed behavior patterns and insufficient adaptability in complex adversarial environments exhibited by traditional wargame agent decision-making models, this paper proposes a multi-agent reinforcement learning method based on suboptimal demonstrations (MARLSD). The proposed method integrates reward relabeling with a self-imitation learning mechanism, effectively improving the training efficiency of multi-agent reinforcement learning algorithms in environments with large state-action spaces and sparse rewards, even when only a small number of suboptimal demonstrations are available, while encouraging agents to explore better strategies. Experimental results show that, compared with baselines such as QMIX and MAGAIL, MARLSD significantly improves performance and …

Research On Calculation Model Of Excavation Resistance Under Heterogeneous Soil Conditions, Xin Zhang, Ping Zhang, Chen Zhang, Wei Liu, Boyang Han

Journal of System Simulation

To address the problem of insufficient prediction accuracy of excavation resistance in heterogeneous cohesive soil, a spatial calculation model of excavation resistance at each excavation stage under heterogeneous soil conditions was proposedbased on the cutting wedge model, comprehensively considering multi-dimensional factors such as bucket geometry, side plate effect, lateral force, and inertia. By taking a small crawler hydraulic excavator as the research object, a coupled simulation model of boom multi-body dynamics and soil-rock particle discrete element was established, and the theoretical model was validated through the co-simulation of excavation operations. The simulation results indicate that under the working …

Annotation-Free 6-Dof Grasp Detection Method Integrating Physical And Geometric Priors, Min Shi, Shisheng Guo, Suqin Wang, Zhaoxin Li, Dengming Zhu

Journal of System Simulation

To improve the stability and cross-category generalization capability of grasp pose estimation in complex stacked scenes, an annotation-free 6-DoF grasp detection method integrating physical rules and geometric structure priors was proposed. In the offline stage, a template library of feasible grasp poses was constructed based on multi-physical constraints, without relying on manual grasp annotations. In the network design, the modeling of structural symmetry of objects and spatial overlap relationships was introduced; a geometric guidance mechanism with occlusion perception and exposure modeling capabilities was designed, and robust pose alignment of target objects was achieved by combining keypoint regression. A multi-type stacked …

Detection Method For 3d Lanes Based On Graph Relationship Optimization Integrating Point And Lane Features, Yanji Jiang, Xingyi Xiao, Hao Dong, Miao Yu, Jinshan Huang, Daqian Liu, Bowen Fei

Journal of System Simulation

Under complex road conditions, the thin and elongated structure and small proportion of lanes lead to blurred visual features and insufficient positioning accuracy, which in turn threatens the road safety of autonomous driving. To address these issues, a 3D lane detection method or graph-based point and lane optimization network (GPLNet), based on graph relationship optimization integrating point and lane features, was proposed. Preliminary feature extraction was completed by the backbone network. 3D spatial positional coding with geometric constraints was obtained through a joint query embedding generation module. A graph relationship optimization network was utilized to perform graph relationship calculation and …

Multi-Level Digital Model Of Dynamic Earned Value Management For Complex Engineering Projects And Its Applications, Wei Wang, Dong Liu, Xinhao Cui, Bo Li, Yiyong Xiao, Yi Ren

Journal of System Simulation

The economic management of existing engineering projects is usually based on organizational structure, which presents problems such as complex processes and difficulty in clarifying main responsibilities when applied to complex engineering projects. In response to this limitation, a multi-level digital model of dynamic earned value management is proposed for complex engineering projects, which extends the traditional cost performance indicators to engineering resource utility indicators, thereby decomposing the earned value of costs into segmented earned values of different engineering resources. This enables managers to dynamically supervise projects based on traditional "schedule-cost" performance indicators and carry out more refined cost control …

Hierarchical Motion Planning Of Mobile Robot Based On Dynamic Corridor Inflation And Convex Optimization, Dingkun Zhang, Haizhao Liang

Journal of System Simulation

Motion planning for robots with Ackermann chassis in dynamic complex environments faces nonholonomic constraints and kinematic-dynamic coupling challenges. However, traditional methods suffer from path redundancy, random fluctuations, and local optimality. A hierarchical motion planning method based on dynamic corridor inflation and convex optimization is proposed. Topologically sparse paths are generated by fusing the Ramer-Douglas-Peucker (RDP) path compression operator with the A* algorithm to reduce redundant path points' interference with backend optimization. Dynamic corridor inflation strategies are designed considering Ackermann steering characteristics, and safe corridors satisfying kinematic constraints are constructed via convex decomposition. Corridor constraints are then transformed into linear inequalities …

Power Flow Calculation Based On Block-Encoded Adiabatic Quantum Newton-Raphson Method, Shengchao Jiang, Yunqing Pei, Hongying Zhai, Guojian Wu, Fang Gao

Journal of System Simulation

To overcome the efficiency bottleneck of the traditional Newton-Raphson (NR)method in high- dimensional power flow calculations for modern power systems and the constraints of variational quantum algorithm frameworks, this paper proposed a power flow calculation framework integrating block encoding technology and adiabatic quantum computing principles. Based on block encoding technology, adiabatic quantum theory, and the NR method, a block-encoded adiabatic quantum power flow calculation framework (BQ-NR) was constructed. The NR correction equations were mapped to a quantum system, and the quantum state encoding of the correction equations was realized by constructing an extended Hermitian matrix and a projection operator; a …

Hyperspectral Anomaly Detection Algorithm Based On Window Reconstruction And Collaborative Representation, Shuanghao Fan, Fang He, Jianwei Zhao, Haojie Hu, Fengchao Zhu, Xiangyang Li

Journal of System Simulation

Hyperspectral anomaly detection refers to identifying ground objects that deviate from normal background distributions and have low probability and small scales from scenes involving mixed multi- class ground objects, spectral feature overlaps, and noise interference. This technology has received extensive attention in recent years. Although collaborative representation-based anomaly detection algorithms demonstrate excellent performance in hyperspectral image anomaly detection, their time costs are too high to enable widespread application.To address this issue, this paper proposes a hyperspectral image anomaly detection algorithm based on window reconstruction and collaborative representation, which consists of two stages. Window reconstruction is performed on hyperspectral background …

Meeting Their Needs: Experiences Of Uc Berkeley International Graduate Students Navigating Financial Strain, Ryann M. Hirt

Master's Theses

Of prior research on student experiences with financial strain, little has specifically focused on international student experiences in higher education while studying in the U.S., in tandem with financial strain. This qualitative study, through utilization of narrative methodology, explores the ways in which international students–in particular, graduate students–experience and navigate financial strain during their studies at a large, R1: Doctoral university: the University of California, Berkeley. The research was guided by three questions: (a) What are UC Berkeley international students’ stories of navigating financial strain? (b) What are the experiences of UC Berkeley international students with external and internal (campus) …

Perception And Practice: A Multiple Case Study Exploration Of Teacher Beliefs Of Intelligence And Praise Practice Implementation In The Primary School Classroom, Johanna Rose Hall

Doctoral Dissertations

Possession of a fixed or growth mindset of intelligence has been shown to substantially influence student academic behaviors and achievement. Students who view intelligence as fixed are more likely to avoid academic challenges and learning opportunities, whereas students who view their intelligence as malleable are more likely to embrace challenges and persist through difficulty. Given the importance of fostering a growth mindset of intelligence in students, this study examines how primary school teachers’ beliefs about the malleability of intelligence influence the type of praise they use in the classroom. Specifically, this study explores how teachers’ internal and underlying beliefs shape …

Exploring The Use Of Nondigital And Digital Games In The Classroom Of Teaching Chinese As A Foreign Language For Adult Learners, Zheng George

Doctoral Dissertations

Game-based learning (GBL) has gained increasing attention as an instructional strategy in foreign language education due to its potential to enhance motivation, engagement, and language acquisition. However, most existing research has focused on young learners or on languages other than Chinese, leaving a gap in understanding of how games are used to teach Chinese as a Foreign Language (CFL) to adult learners. In addition, prior studies have primarily examined learners’ perspectives, with limited attention to teachers’ instructional practices when implementing game-based instruction. The purpose of this mixed-methods study was to explore how CFL teachers integrate nondigital and digital games in …

Beyond A Corrective Experience: Reimagining Liberation In Special Education, Erin Elise Macnabb

Doctoral Dissertations

This qualitative study establishes a critical bridge between special education and liberatory pedagogy, positioning these historically siloed fields as interdependent for systemic justice. While Special Education Teachers (SETs) daily work involves resisting systemic oppression, special education has been historically excluded from liberatory pedagogy and instead focused on medicalized models and deficit based assumptions. The separation of liberatory pedagogy and special education contributes to professional siloing and a culture of compliance that prioritizes bureaucratic processes over the meaningful and radical work of SETs.

The research utilizes a qualitative design rooted in Collaborative Critical Inquiry (CCI) where an intentional sample of veteran, …

The Effectiveness Of Mastery Learning On Student Achievement Across Stem Disciplines: A Meta-Analysis, Francis Siangco Estabillo

Doctoral Dissertations

Mastery learning has been one of the most extensively researched instructional strategies in education, studied continuously since the 1960s. Prior meta-analyses have consistently found positive effects of mastery learning on student learning outcomes, however, none have examined its effectiveness on student achievement explicitly within science, technology, engineering, and mathematics (STEM) disciplines.

This comprehensive meta-analysis investigated the effectiveness of the mastery-learning instructional strategy on student achievement across STEM disciplines in K-12 and higher-education contexts. A systematic literature search yielded 85 studies with combined sample sizes of 10,244 participants that met the inclusion criteria. Heterogeneity was assessed using Q,I^{2 …}

New Developments In Space-Filling Designs, Xiankui Yang

USF Tampa Graduate Theses and Dissertations

This dissertation presents three methodological advancements to improve the construction of space-filling designs for meeting different needs of computer experiments. Traditional space-filling designs focus on achieving uniform coverage in the input space, ensuring that design points are spread evenly throughout. However, in some scientific and engineering applications, varied density of design points may be desired for more efficient data collection when prior knowledge implies different emphases. In other cases, ensuring good coverage and/or spread of the response values allows better performance of fitted models in the next stage of applications. Many processes involve variation in response values. Therefore, incorporating variation …

Kebebasan Hakim Memutus Perkara Dalam Konteks Pancasila (Ditinjau Dari Keadilan “Substantif”), Ery Setyanegara

Jurnal Hukum & Pembangunan

Abstract

Asymmetric Opinion Formation Of Emotional Excitable Agents, Irene Ferri, Emanuele Cozzo, Aleix Nicolás-Olivé, Albert Díaz-Guilera, Luce Prignano

Northeast Journal of Complex Systems (NEJCS)

The bounded confidence model represents a widely adopted framework for modeling opinion dynamics wherein actors have a continuous-valued opinion and interact and approach their positions in the opinion space only if their opinions are within a specified confidence threshold. Here, we propose a novel framework where the confidence bound is determined by a decreasing function of their emotional arousal, an additional independent variable distinct from the opinion value. Additionally, our framework accounts for agents' ability to broadcast messages, with interactions influencing the timing of each other's message emissions. Our findings underscore the significant role of synchronization in shaping consensus formation. …

Indirectly Fired, Single-Chamber Parabolic Radiative Kiln, Natalie M. Durdle Miss

Defensive Publications Series

This disclosure describes a high-efficiency, multi-directional thermal enclosure consisting of a single-chamber, non-metallic refractory kiln characterized by a parabolic, catenary, or semi-spherical vaulted geometry. This document details a system configuration where a high-density masonry or clay enclosure functions sequentially as both an active combustion chamber and an indirect, passive radiant energy concentrator. By optimizing the internal radius of curvature of the vaulted shell, the system acts as a geometric infrared mirror, focusing and redistributing uniform multi-directional radiant heat flux to a centralized processing plane after the primary heat source is removed or extinguished. The thermodynamic principles, material properties, and physical …

Bio-Compatible Hardware Computing Framework, Natalie M. Durdle Miss

Defensive Publications Series

This disclosure details an entirely metal-free, biochemical, and biodegradable hardware computing architecture. It is the explicit intent of the authors to place the entirety of these concepts, material configurations, and geometric manufacturing methodologies into the public domain to establish a permanent barrier of prior art. The configurations disclosed herein utilize the inherent, predictable chemical and physical properties of processed natural feedstocks (such as regenerated plant cellulose, exfoliated organic carbon, and biological resins). While these elements are isolated and processed from raw botanical and graphitic sources, the final textile computing assemblies operate strictly via the unalterable, native physical laws governing electron …

Baffled Solid-Medium Thermal Energy Storage System, Natalie M. Durdle Miss

Defensive Publications Series

This disclosure describes a passive, high-efficiency, solid-medium sensible heat Thermal Energy Storage system constructed from high-density, non-metallic refractory materials (such as fired clay bricks, earthen masonry, or cast stone). This document details a mechanical design featuring a multi-stage, tortuous, baffled internal flue matrix (a smoke labyrinth) engineered to maximize convective heat transfer from high-velocity, high-temperature combustion exhaust gases into a surrounding high-thermal-mass storage body. The physical mechanics, structural geometry, and thermodynamic principles detailed herein are inherently enabled by centuries of Eastern and Central European human cultural heritage—specifically the historical technology known as the "Russian Pech" (Russian Oven) and related masonry …