Digital Commons Network^™

Research On Control Of Coaxial Dual-Rotor Unmanned Aerial Vehicle Based On Improved Reaching Law, Xinhang Chen, Xiaodong Ling, Chengchang Lang, Shijun Zheng, Yiqi Tang

Journal of System Simulation

Abstract: To address the issues of significant chattering, slow convergence speed, and large overshoot in the control system of a coaxial dual-rotor unmanned aerial vehicle, a control method based on an improved double-power and hyperbolic function integral sliding mode reaching law was proposed. A novel reaching law was designed to achieve fast convergence when the system state is far from the sliding surface and smooth transition when approaching the sliding surface, thereby enhancing the overall convergence speed of the system and ensuring that the system reaches the sliding surface within a finite time. The saturation characteristic of the hyperbolic function …

Strategic Talent Management In Era Of Intelligence And Digitalization: Current Situation And Path Exploration, Chaoying Tang, Chunyuan Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The report of the 20th National Congress of the Communist Party of China emphasized “speed up efforts to build a contingent of personnel with expertise of strategic importance” to support China’s pursuit of high-level technological self-reliance and its goal of becoming a world-leading power in science and technology. The deep integration of digital and intelligent technologies is fundamentally transforming talent management paradigms and innovation processes, posing new demands on the knowledge structure, competency models, and management approaches of strategic talents. The study explores the concepts of strategic talent management in the digital intelligent era, establishes its logical framework, analyzes current …

Designing, Integrating, And Evaluating Blockchain Assignments In The Undergraduate Computer Science Program, Karol Lejmbach

Dissertations (1934 -)

Blockchains as a technology rely heavily on a wide range of computer science topics. These topics include: algorithms, data structures, network communication, cryptography and many more. These topics align nicely with topics often covered in undergraduate computer science course. Blockchain technology offers an interesting opportunity for computer science educa- tors. Blockchains rely heavily on a wide range of computer science topics. These topics include: cryptography, networking, data structures, and algorithms. Many of these top- ics are explored in undergraduate computer science programs either in core or elective classes. This offers an opportunity for teaching students about emerging technologies, such as …

Review On Optimization Of Simulation Modeling Strategies For Spacecraft Orbit Avoidance, Guozheng Li, Rui Wang, Shichao Fan, Xintong Cai, Xinyue Zhai

Journal of System Simulation

Abstract: The number of on-orbit spacecraft increases exponentially; the space environment becomes more complex, and the collision risk of on-orbit spacecraft increases significantly. On-orbit safety is thus severely threatened, posing higher requirements for orbit avoidance methods. The costs and risks of space activities are extremely high, making simulation an effective method to solve complex problems of orbit avoidance. The modeling, solution, and simulation methods for the two core issues of spacecraft orbit avoidance, "collision avoidance" and "pursuit-evasion games", were systematically reviewed, and the existing shortcomings were analyzed. The applications of technologies such as deep reinforcement learning in promoting orbit avoidance …

Vehicle Routing Optimization For Underground Mines Considering Fuzzy Demand And Time Tolerance, Guorong Wang, Haishun Deng, Ziming Kou, Xuanxuan Yan, Zhixiang Huang

Journal of System Simulation

Abstract: To solve the problem of material demand fluctuation and different time windows in auxiliary transportation of underground mines, a routing optimization method for material distribution considering fuzzy demand and time tolerance was proposed. Based on the fuzzy credibility theory, uncertain demand was constrained by fuzzy chance constraints, and a multi-objective routing optimization model for underground mine auxiliary transportation was constructed with the objectives of minimizing the total operating cost of vehicles and maximizing time tolerance. A multi-objective genetic algorithm with mixed dominance strength was designed to solve the model. By calculating the deviation difference of Pareto frontier solutions, …

Auv Path Planning Integrating Local-Global Strategies In Unknown Environments, Wenlong Meng, Yanbo Pu, Ya Gong

Journal of System Simulation

Abstract: Existing path planning algorithms often struggle to efficiently explore and generate high-quality trajectories. To address this issue, this paper proposes a path planning algorithm that integrates local-global strategies. By employing the rolling window technique, the global one-time path planning problem is transformed into an iterative process of multiple local planning stages. During the global exploration phase, the rolling window is used to determine high-level path branches and to identify branch waypoints, thereby refining the calculation of local paths. In the local exploration phase, an improved RRT-Connect algorithm is proposed, which combines adaptive circular sampling with dynamic step length to …

A Bilstm+Attention Method For Predicting The Intentions Of Air Combat Targets Based On Multi-Feature Continuous Time Series, Qiuni Li, Dong Wang, Chaozhe Wang, Zongcheng Liu

Journal of System Simulation

Abstract: To achieve advance prediction of enemy target intention, a three-layer air combat intention prediction method based on multi-feature continuous time series and BiLSTM+Attention, including trajectory prediction, threat assessment, and intention prediction was proposed. To prevent the onesidedness of intention prediction results caused by state information at a single moment, prediction was carried out from multiple state features and trajectory information in a continuous time series. An LSTM neural network was used to predict the trajectory of the target aircraft, and the threat assessment of the target aircraft before and after the prediction was conducted. The BiLSTM + Attention model …

Large-Scale Multi-Objective Evolutionary Algorithm Based On Multi-Region Dynamic Grouping, Binhao Liang, Jingxuan Wei, Fengqin Liang

Journal of System Simulation

Abstract: The decision variable dimension of large-scale multi-objective optimization problems can reach hundreds or even thousands. For existing large-scale multi-objective evolutionary algorithms based on decision variable analysis, which usually consume a large amount of computational resources for grouping and fail to consider the interactions between convergence-related variables and diversity-related variables, a large-scale multi-objective evolutionary algorithm based on multi-region adaptive dynamic grouping was proposed. The algorithm employed a Gaussian mixture model to partition the decision space into multiple regions; within each region, feature vectors were constructed for each decision variable, and spectral clustering was utilized to perform grouping. To validate …

Optimization Of Air Defense And Antimissile Firepower Resource Allocation Based On Adaptive Hybrid Evolution, Wei Liu, Delong Chen, Ze Liu, Rui Wang, Kaiwen Li, Tao Zhang

Journal of System Simulation

Abstract: Air defense and antimissile firepower resource allocation is a core optimization problem in modern defense systems. Under complex conditions such as spatiotemporal constraints and firepower resource limitations, this problem involves the optimal configuration of limited interceptors and belongs to the class of NP-hard multi-constrained combinatorial optimization problems. This paper established a comprehensive mathematical model encompassing range constraints, time window constraints, feasibility matrices, and interception probability models. To address the high-dimensional nonlinearity of the problem, an adaptive hybrid evolutionary algorithm (AHEA) was proposed. The algorithm integrated problem-aware initialization, adaptive parameter control, seven specialized neighborhood search operators, and an adaptive strategy …

Mechanism Analysis Of Parasitic Torque In Electric Loading Systems, Xiaozhe Sun, Zhenyu Fu, Zhaoke Xu, Jianxin Li

Journal of System Simulation

Abstract: To address the issues of sources and mechanisms of parasitic torque in electric loading systems for aircraft actuator loads, a functional model of the electric loading system was established. Numerical simulations and Monte Carlo methods were employed to analyze the sources of parasitic torque and its primary influencing factors. The influence mechanisms and degrees of the system's external inputs and internal disturbances on parasitic torque were analyzed and validated through single-parameter and multi-parameter analyses. The results indicate that parasitic torque is predominantly influenced by factors such as loading command frequency, sensor signal bias, and loading motor parameters. In particular, …

Simulation On Water Hammer Characteristics Of Bipropellant Attitude And Orbit Control Propulsion System, Xianwei Lang, Yantao Wang, Fang Zhang, Yizhen Zu, Xinyu Zhang, Weibin Xiang

Journal of System Simulation

Abstract: To address the water hammer problem in bipropellant attitude and orbit control propulsion systems during start-up, shutdown, and periodic operation, the water hammer characteristics under different operating conditions are investigated using simulation methods. The water hammer characteristics of annular and branched propellant delivery lines are compared, and the effects of multiengine interactions under various operating conditions, as well as the influence of water hammer on engine performance, are analyzed. The results show that the attenuation rate of pressure fluctuation in the annular pipeline system is significantly higher than that in the branch pipeline system. Under the condition of multi-cycle …

Intersection Positioning Algorithm With Spatial Translation Based On Sar Scene Matching, Cheng'en Pu, Yumin Lai, Rui Shi, Yan Liao, Kezi Meng, Lifeng Qu

Journal of System Simulation

Abstract: To address the problem that the positioning precision of the inertial navigation system cannot meet the requirements of autonomous positioning when the aircraft flies, an autonomous positioning method with spatial translation based on circular scanning scene matching of SAR was proposed. The spatial translation positioning model of the aircraft was established according to the position of the ground matching points obtained by single point and single circular scanning scene matching of SAR, the oblique distance between the matching points and the aircraft, and the inertial measurement information of the aircraft. The characteristic information of the matching point sequence was …

State Monitoring Of Nuclear Power Connection Sleeve Quality Inspection Equipment Driven By Digital Twin, Yandong Nan, Jinda Zhu, Xinbin Lu, Zhiying Qin, Dandan Qi, Zhiheng Ding

Journal of System Simulation

Abstract: To address the problems of delayed state perception, single monitoring dimension, and insufficient visualization in the quality inspection equipment for nuclear power connection sleeves, a state monitoring method driven by digital twin was proposed. A digital twin-based collaborative state monitoring framework for the inspection equipment was constructed. Based on the OPC UA technology, a multi-source information interconnection model was established. A finite state machine model was employed to discretize and logically drive the inspection process, and a hierarchical verification strategy was proposed to establish a multi-dimensional motion state monitoring mechanism. A surrogate model coupling the radial basis interpolation function …

Design And Application Of Collaborative Simulation System For Satellite Constellation Flight Missions, Dong Yan, Hanzhe Yang, Fangfang Jiang, Chengbao Liu, Peng Zhang

Journal of System Simulation

Abstract: To meet the requirements of the collaborative drill for the ground operation and control system of the satellite constellation, as well as the verification and evaluation of in-orbit complex missions, the design ideas and implementation methods of the collaborative simulation system for satellite constellation flight missions were proposed. By adopting the time correction mechanism of the time-scale distributor, the time synchronization problem among the simulation nodes and the operation and control simulation system was solved. By adopting the communication technology based on improved PDXP + UDP, the problem of cross-node data interface and inter-satellite communication simulation was resolved. A …

Modeling And Simulation Of Target Characteristic Architecture Of Target Missile Based On Dodaf, Tuo Zhao, Yuqiao Liu, Yuan Ma, Yun Cheng, Shen Li

Journal of System Simulation

Abstract: In view of the problems of incomplete elements and missing architecture in the research of target characteristics of target missiles, this paper introduced the panoramic view, operational view, and capability view models in the DoDAF from the perspective of system engineering. According to the view development sequence of "panoramic description, operational decomposition, and capability matching", a target characteristic architecture of the target missile was constructed, which included target elements such as maneuvering characteristics and infrared radiation characteristics. The mapping relationship among "operational layer, capability layer, and target characteristic layer" of the target missile was obtained, and the architecture was …

Overall Design Method Of Low Earth Orbit Communication Satellite Based On Mbse, Jiace Shang, Rui Zhang, Ya Dai, Hua Zhu, Siqi Hu, Linqiang Ge, Chenguang Shi

Journal of System Simulation

Abstract: Drawing on the model-centric design philosophy of model-based systems engineering (MBSE), this study constructs a model architecture suitable for the design and analysis of low Earth orbit communication satellites. This architecture adopts a multi-dimensional matrix approach. Vertically, it traverses the mission layer, system layer, satellite general design layer, and subsystem layer, achieving top-down hierarchical decoupling. Horizontally, it establishes a comprehensive view mapping mechanism covering the domains of requirements, functions, structure, and performance. Integrating the characteristics of product development, a modeling process covering the entire lifecycle—from mission demonstration and overall design to subsystem design and integration verification—has been established. The …

Dynamic Model-Driven Verification Framework For Modular Aerial Bomb Systems, Wenlong Li, Shuhan Sang, Yusheng Liu, Haiyan He, Zan Liang, Wenqiang Yuan, Biao Niu, Weifeng Luo

Journal of System Simulation

Abstract: To address the problems of high verification costs, difficulty in covering dynamic behaviors, and lack of quantitative closed loops in the design stage of modular complex equipment, a dynamic model-driven modular system verification framework was proposed. Based on model-based systems engineering (MBSE) modeling, a structural coupling quantification model was constructed using the number of interfaces, signal interaction frequency, and dependency intensity. Dynamic tests were conducted in high-fidelity virtual simulation to collect data; performance rating for indicators such as accuracy, response, and stability, as well as system's comprehensive rating, were obtained, and the rating feedback was used for iterative optimization. …

Reading The Room: A Structural Account Of Constraint-Based Processing And Its Limits In Artificial Systems, Griselda Poe

Publications and Research

This paper does not introduce a new structure.

It makes explicit a structural relation implied but not directly stated in prior work.

Human interpersonal processing is grounded in the co-presence of internal constraint and dependency.

These do not exist as separable components.

They form a single structural condition.

This paper shows that what is commonly described as “reading the room” is not a unitary function.

It differs across configurations in how this condition is processed.

In EF configurations, the effect of this condition is expressed through translation into self-return: outputs are evaluated in terms of how they return to the …

Extreme Cf: A Structural Account Of Processing Absence And Category Absence In Cf-Foregrounded Configurations, Griselda Poe

Publications and Research

Existing frameworks of cognition and intervention assume that processing occurs, meaning is available, and evaluation can be applied.

This paper describes a configuration in which this assumption does not hold.

In CF-foregrounded processing where modulation is absent, processing occurs only when coherence is satisfied. When coherence is not satisfied, processing does not occur. Under this condition, no representation is generated, no evaluation applies, and no action selection is produced.

Within single-layer cognitive models, EF and CF are not distinguished. Within such models, CF does not exist as a condition.

This configuration has not been represented as a category within existing …

Fairhiveframes-1k: A Public Fair Dataset Of 1265 Annotated Hive Frame Images With Preliminary Yolov8 And Yolov11 Baselines, Vladimir Kulyukin, Reagan Hill, Aleksey Kulyukin

Computer Science Faculty and Staff Publications

In precision apiculture, the portable digital camera is a cost-effective sensor for capturing hive images or videos used to quantify different colony variables. Openly accessible, well-annotated, interoperable cell-level image datasets are still the exception rather than the norm. This shortage constitutes a major barrier to AI-driven approaches aimed at automating image-based comb analysis. In this article, we present FAIRHiveFrames-1K, a publicly available dataset of 1265 annotated hive frame images (1920 × 1080 PNG) designed to facilitate research in AI-intensive image-based comb analysis automation. The dataset, derived from a 2013–2022 U.S. Department of Agriculture–Agricultural Research Service multi-sensor research reservoir, includes 124,669 …

The Digital Neuron: Neural Cellular Automata For Neural–Symbolic Translation, Nicole Assenza

SMU Data Science Review

A neural cellular automata (NCA) architecture, referred to as Pluto’s NCA, was developed to characterize bilateral communication and semantic reciprocity between symbolic representations and a spatially distributed update field. The architecture employs an encoder–automata–decoder pipeline that maps symbolic inputs into a multichannel state field and reconstructs them through agreement-driven attractor convergence within a stable semantic attractor landscape. System behavior was evaluated under controlled perturbations, including rhythmic desynchronization, graded ablations, correlated and independent noise, and percolation-based structural degradation. Quantities such as Agreement(t), internal coherence Aᵢ(t), the recovery time constant τ, and the critical percolation threshold pc were measured to assess stability, …

Phishing Restraint: University Simulated Phishing Campaigns, Alexander M. Abou Khir

Cybersecurity Undergraduate Research Showcase

Universities face heightened vulnerability to phishing attacks due to their open information-sharing culture and diverse user populations. This study examines how phishing exploits human factors within campus environments and evaluates three major training strategies: embedded phishing, microlearning, and role-based instruction to understand their individual and combined effectiveness. I explored studies that implement these strategies in pairs and use the strategies alone, identified trends in susceptibility reduction, behavioral reinforcement, and contextual relevance. I suggest that, while each method independently improves user awareness, multiple approaches offer stronger, more adaptable protection by addressing both psychological triggers and role-specific risks. The paper contributes a …

Hijacking The Prompt: A Survey Of Prompt Injection Attacks, Detection, And Defense In Large Language Models, Edward J. Griggs

Cybersecurity Undergraduate Research Showcase

Prompt injection attacks, ranked the number-one vulnerability in AI systems by OWASP's 2025 Top 10 for Large Language Model Applications, remain largely unsolved, and this survey examines why. As large language models (LLMs) are deployed across enterprise workflows, agentic systems, and consumer tools, their fundamental inability to distinguish trusted instructions from untrusted user data has created a persistent and expanding attack surface. This paper presents a structured taxonomy of prompt injection attack vectors, including direct injection, indirect injection, multimodal attacks, tool and agent exploitation, hybrid chained techniques, and autonomous propagating threats. These vectors are mapped across five impact categories (data …

A Backend Database Architecture For Persistent Epilepsy Classification Records, Attiksh A. Panda, Deep Desai, Artem Zabarov, Katrina D. Prantzalos, Satya S. Sahoo, Shuai Xu

Student Scholarship

Epilepsy affects over five million people globally each year, yet consistent clinical diagnosis remains a persistent challenge due to the lack of standardized classification workflows across medical institutions. The Four-Dimensional Epilepsy Classification (4D-EC) framework, developed by Lüders et al., provides a comprehensive structure for characterizing paroxysmal events across four dimensions: seizure semiology, epileptogenic zone, etiology, and comorbidities. Despite its clinical and educational value, no dedicated informatics platform existed to support its routine use until recently, limiting widespread adoption among clinicians and trainees. This project addresses that gap by implementing a full-stack web application that operationalizes the 4D-EC framework for clinical …

The Texture Of A Threat: Adversarial Training, Cnns, And Obfuscated Malware Detection, Kaelyn Haynie

Senior Honors Theses

Accurately detecting malicious programs is an expanding field of research for machine learning (ML), with a novel approach incorporating a bytecode-to-image pipeline that produces images representative of software. These images are provided to convolutional neural networks (CNNs) to be examined for malicious pattern indicators. However, CNNs struggle to generalize these patterns effectively while still being robust against adversarial data, an issue which this research addresses with adversarial training. In this paper, three unique CNN architectures (a DBFS-MC-inspired baseline, MIRACLE, and PSP-CNN) are trained for binary classification with 15,000 benign and malicious software samples encoded into images for Android, Windows, and …

Leveraging Convolutional Neural Networks For Through-The-Wall Radar Imaging: Challenges, Impacts, And Future Directions, Tumaini Edgar, Abdulla F. Ally, Abdi T. Abdalla

Tanzania Journal of Engineering and Technology (TJET)

Through-the-wall radar imaging (TWRI) is an essential technology for military and rescue applications; however, its performance in detecting and visualizing high-quality images of targets behind walls is significantly degraded by multipath reflections and signal attenuation. This paper reviews the current state of TWRI and its challenges, and explores the transformative potential of deep learning, particularly convolutional neural networks (CNNs), in addressing these challenges. Peer-reviewed articles published from 2018 to 2024 were analysed to examine CNN applications in addressing TWRI challenges. The analysis reveals that using CNNs, TWRI systems can be more effective by filtering wall distortions, reducing noise, lowering computational …

Writing Algorithm Demonstrations Using Ai, Caiden Sunlin, Connor Vachon

25th Annual A. Paul and Carol C. Schaap Celebration of Undergraduate Research and Creative Activity (2026)

We describe the design and development of interactive algorithm demonstrations for an online undergraduate algorithms textbook, created with the assistance of large language models, specifically ChatGPT. The work focused on browser-based, step-bystep visualizations that highlight algorithm behavior and intermediate states. We discuss how ChatGPT was used during ideation, implementation, and debugging, along with the limits of its usefulness and the kinds of human guidance that remained essential. Using concrete examples, we reflect on how AI tools can support student-centered educational software development without replacing domain expertise or instructional judgment.

A New Website For Aminoacids.Com, Camila Medrano, Gillian Donley

25th Annual A. Paul and Carol C. Schaap Celebration of Undergraduate Research and Creative Activity (2026)

Our client, AminoAcids.com, faced major issues with its previous website, including outdated design, poor accessibility, and unreliable order processing that often required manual intervention. Using the wireframes and content structure provided by the Center for Leadership, our team built a new website using WordPress as the content management system and WooCommerce to support e-commerce functionality. The new website provides a more stable infrastructure, minimizes order processing errors, and ensures a smoother user experience across all devices.

Umm (Ultimate Memory Manager): A Note–Taking App Built From Scratch, Caleb M. Early

ASPIRE 2026

For my honors project, I’m building UMM, an advanced note-taking application built entirely from scratch. I’m someone who takes many notes and primarily uses OneNote and Notion, but over time have found myself wanting something faster and more flexible than any note-taking application I could find. UMM is my attempt to create the note-taking app I wish I had, as well as learn how to create such a program.

Instead of relying on pre-made code, I built my own systems for how documents are structured, edited, saved, as well as how the cursor moves, text is formatted, and how selections …

Cybersecurity Integration In Research Stage Connected Devices Within Healthcare Environments, Klemens Koszarek

Master's Theses (2009 -)

The rapid growth of connected devices in healthcare environments has significantly expanded the cybersecurity threat landscape, extending the potential risks beyond traditional hospital networks. Regulatory guidance from the FDA and risk management frameworks such as the NIST Cybersecurity Framework (NIST CSF) provide an approach for managing cybersecurity risk in connected systems. However, these principles are not always applied during early stages of device development. As a result, security consideration may be deferred until later stages of development, allowing for vulnerabilities to persist in systems as they move toward clinical or commercial deployment. This study presents a structured method for integrating …