Computer Sciences Commons^™

Uc-086-235 Student Performance Pattern Mining, Cesar Arevalo Colocho

C-Day Computing Showcase

This project applies data mining techniques to explore patterns in a student performance dataset. The analysis focuses on discovering natural groupings of students and frequent associations among academic, social, and lifestyle attributes. Clustering and association rule mining are used to identify meaningful structures in the data, emphasizing pattern discovery and interpretation rather than outcome prediction.

Uc-087-236 Early Prediction Of Player Performance, Grady Freeman, Hien Truong, Jackson Mayo

C-Day Computing Showcase

This study examines whether early-season performance metrics can support player evaluation under the NCAA’s shortened transfer window. Using data from Conference USA and the Mid-American Conference, we modeled offensive (UASE) and defensive (DAR) efficiency with multiple predictive methods. Across both full-season and 9-game datasets, DAR was more predictable, with higher R² and lower RMSE values. Linear Regression consistently performed best for DAR, while KNN and Random Forest performed best for UASE depending on the dataset. Results show that meaningful performance patterns can be identified early in the season, even with limited data. These findings suggest analytics can help programs make …

Uc-098-187 Zero-Inflated Poisson Modeling Of Ncaa Postseason Awards, Charles Lane, Kyle Bresko, Kaleb Treang

C-Day Computing Showcase

Our project focuses on predicting postseason awards for NCAA Men's College Basketball which can be difficult to model given that less than 15% of players in a given season win awards. After evaluating basic models, we selected a Zero-Inflated Poisson (ZIP) model to account for most players receiving zero awards. We identified free-throw attempts as being the best predictor for the structural zeros present in who can win an award. The final ZIP model produced better evaluation metrics than other basic models. Accounting for structural zeros allowed us to better model how on court statistics can translate into postseason awards.

Uc-099-189 Spectre, Alexander Tobal, Chris Higgins Jr, Jaylin Reeves, Logan Leichter

C-Day Computing Showcase

Spectre consists of four levels, where players complete various objectives and fight off ghosts while doing so. Our tutorial level introduces players to the mechanics, such as shooting, rear view mirror shooting, walking and jumping. With the rest of the levels focusing on completing objectives in order to progress. The final level culminates in a boss fight, ending the journey. While players explore and complete objectives, enemies drop a currency that players can spend to obtain upgrades. Getting hit by enemies not only reduces the players’ health but also applies debuffs to them making players more cautious of their surroundings. …

Uc-117-213 Haunted Owl Hotel – A 3d Horror Maze Chase Game, Carter Griffin, Rin Egl, Kcyana Redmon, Jose Portillo, Alana Nesbit

C-Day Computing Showcase

“Haunted Owl Hotel” is a horror Pac-Man-inspired, 3D maze chase game. You play as a cute owl named Sappy trying to escape the scary hotel, but suddenly your elevator breaks down. Navigate the spooky halls to collect the candles left behind on each floor to reactivate the elevator, but be careful, after grabbing each candle, the darkness left behind will follow you. Ghosts lurk around every corner hoping to make you their next victim. Descend through each floor without losing all 3 lives to escape the haunted owl hotel and win the game.

Uc-121-133 Head In The Clouds, Hunter Osborne, Jane Day, Chase Bell

C-Day Computing Showcase

Head in the Clouds is a video game that puts the player in the shoes of a child with ADHD (Attention Deficit Hyperactivity Disorder). Rain, the protagonist, is told by their mother to take out the trash, but keeps getting distracted and daydreaming instead. The player must beat platforming challenges to get Rain back on task. The narrative and gameplay is meant to represent the difficulties of having ADHD.

Uc-122-135 Mutatio Mentis, Isaac Alderman, Braden Mizell, Collin Sutton

C-Day Computing Showcase

Mutatio Mentis is a first person, narrative heavy, puzzle-lite RPG that follows the story of a renaissance era plague doctor and their attempt to alter the minds of three subjects; a gardener, a street urchin, and a priest. The narrative is set in 1637 Florence, Italy, in the wake of the Great Plague of Milan, and draws heavily from renaissance culture. Each of the three subjects have progressively more complex personal conflicts, which present through the gameplay aesthetics of each act, as the gameplay changes to reflect the problems of each subject. Our focus is on tackling mental and emotional …

Uc-131-162 Physical 8-Bit Cpu, Samuel Hoerner, Aryan Merchant, John Dislen, Kyran Day

C-Day Computing Showcase

This isn’t an app - it’s the machine behind it. A fully functional 8-bit CPU, built from scratch, turning raw signals into real computation. The system combines our custom assembly-to-run, FPGA-driven control unit (CU), discrete transistor Arithmetical Logical Unit (ALU), external memory, and 5 registers to execute programs through a fetch-execute cycle. The result is a tangible computing platform that bridges low-level digital logic with high-level system behavior.

Uc-135-129 Fishgame: Mobile Hyper-Casual Fishing Game, Lauren Rousell, Lisbeth Martinez, Jacob Portillo, Jacob Miller

C-Day Computing Showcase

fishGame is a strategy-driven hyper-casual mobile game that combines the accessibility of traditional mobile gameplay with the progression depth of a roguelike. The project was developed over a three-month period using Unity 6.3 and related production tools. Following the completion of an alpha build, testing was conducted through gameplay sessions and a detailed follow-up survey to gather feedback on player experience, clarity, and engagement. Results indicated that fishGame was well received, with players reporting low levels of confusion and strong replayability. These findings suggest a clear interest in mobile games that offer greater depth while preserving the immediacy and simplicity …

Uc-136-132 Gamma Guardian: Teaching About Hlh, Lauren Rousell, Logan Leichter, Jacob Portillo, James Lock

C-Day Computing Showcase

Gamma Guardian is an educational strategy game for children ages 6 to 12 that introduces Hemophagocytic Lymphohistiocytosis (HLH) and immune-system balance through interactive gameplay. The game places players inside the human body, where they use touch controls, antibody shields, and immune-response management to defend against interferon gamma, bacteria, and pathogens. Development used Unity 6.3 and followed a level-based design with educational feedback, AI-driven enemies, and a simple visual style to support learning. The result is a fully functional game with five levels, integrated educational content, and multi-platform support, exceeding the original goal of producing only a demo.

Uc-137-237 The House Watches, Lisbeth Martinez, Lauren Rousell, Jaime Mcbride, Karizma Quiroz, Aidan Kleine

C-Day Computing Showcase

The House Watches is a horror-puzzle game about a boy and a dog trying to reunite after mysterious supernatural creatures, called duendes, invade their home. The game consists of two levels, each with a different mode of gameplay; level one is a more traditional item-collection horror experience, and level 2 is based around puzzles that must be completed in a limited time frame. The House Watches includes original art, music, and models, as well as a dynamic gameplay system that increases the difficulty of each level over time.

Uc-142-177 Multiplayer Spsu Tub Racing Video Game, William Pitts, William Urvan, Thomas Powell, Joshua Young

C-Day Computing Showcase

Multiplayer Bathtub Racing revives a well-known Southern Polytechnic State University tradition through a digital multiplayer experience built in Unity. The project extends a prior single-player tub racing game by adding online multiplayer

Uc-144-182 Paracosm, Va'quez Friday

C-Day Computing Showcase

Paracosm is a gothic horror game revolving around a tattoo artist, named Villain, who discovers that his art has suddenly come to life. Despite this phenomenon, Villain insists on finishing his tasks before three Am, due to his superstitious nature. What he doesn’t know yet is that if he doesn’t finish by that time, then he will be forever stuck in his shop with no escape. He will also learn that not all of his lively drawings are friendly, and that the not-so friendly drawings of his will stop at nothing to make sure he fails-Knowing that if he fails, …

Temperature-Induced Uncertainty In Fixed-Context Retrieval-Augmented Generation, Steven Zeng, Murat Kuzlu

Cybersecurity Undergraduate Research Showcase

This study examines how decoding temperature affects output uncertainty in a fixed-context retrieval-augmented generation (RAG) system. We define uncertainty as the semantic dispersion among repeated answers under the same fixed retrieved context, with greater dispersion interpreted as higher uncertainty. To isolate this answer-generation variability from retrieval drift, each question was paired with a fixed retrieved context, and repeated generations differed only in temperature. The experiment used nine questions drawn from a machine-learning textbook corpus, with three questions each at easy, moderate, and hard difficulty. Each question was evaluated at five temperatures (0.0, 0.25, 0.5, 0.75, and 1.0) over 30 iterations, …

Histopathology Image Classification Using Machine Learning, Mohammed H. Alali

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Histopathology image classification is a critical component of cancer diagnosis. However, the gigapixel scale of Whole-Slide Images (WSIs) and the high variability in tissue staining and scanner quality across medical centers present significant computational challenges. This dissertation proposes a comprehensive machine learning framework to address these challenges, bridging the gap between theoretical models and practical clinical deployment.

First, to manage the massive dimensionality and noise inherent in WSIs, this research develops a robust feature extraction methodology. The pipeline implements a stringent tile filtering technique to eliminate physical artifacts and resolve severe class imbalances. It integrates ConvNeXt alongside an attention-based pooling …

Spatial Computing With The Apple Vision Pro In Minimally Invasive Procedure Simulation: A Randomized Crossover Feasibility Study, Sydney Cooper, Aaron Kyle Jones, Rahul Anil Sheth, Koustav Pal, Bruno Odisio, Mark Blaylock, Shelita Kimble, Justin Bird, David Rice, Daniel Shoenthal, Emil Patel, Vipin Kamath, Sanjay Gupta, Jeffrey Siewerdsen, Joshua Kuban

Advances in Cancer Education and Quality Improvement

Purpose: This study aimed to evaluate the feasibility of wearing the Apple Vision Pro (AVP), a mixed-reality headset that integrates augmented and virtual reality, while performing minimally invasive procedures. While studies have demonstrated that spatial computing technology can improve surgical precision and reduce the risks of surgical complications, to our knowledge, no studies have specifically addressed the impact of the AVP on task performance during simulated image-guided procedures.

Materials and Methods: Thirteen diagnostic and interventional radiology residents performed image-guided central venous catheter placement, thoracentesis, and paracentesis on simulation models. Each participant completed a non-timed practice followed by the procedures once …

Inc3vits Model: A Hybrid Architecture To Accelerate And Reduce Complexity For The Deepvariant Model For Variant Calling, Mustafa Al-Saffar, Sura Z. Al Rashid

Karbala International Journal of Modern Science

Deep learning has revolutionized genomic variant calling, yet the computational cost of current systems continues to limit scalability. We present a controlled efficiency study of DeepVariant-style pileup architectures under identical training and inference conditions, comparing architectural downsizing with a hybrid CNN–local attention design. Inc3ViTs pairs a streamlined InceptionV3 stem with a lightweight local attention head based on patch tokenization and windowed self-attention, enabling a direct comparison with a CNN-only reduced Inception baseline. Across whole-genome and whole-exome short-read datasets, Inc3ViTs reduces training time by ~40–50% and reduces inference runtime relative to the original DeepVariant. The CNN-only baseline indicates that most speedups …

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 …

Modelling Method Of Unmanned Vehicle Dynamics Based On Neural Network, Jun Wang, Min Liu, Xiaochuan Zhang, Yishan Ding, Juhui Feng, Ye Zhuang

Journal of System Simulation

Abstract: To address the challenges of high data acquisition costs of test data on dynamic characteristics between tires and soft terrain and low speed of numerical calculation for unmanned vehicles in complex terrestrial environments, a modeling method of unmanned vehicle dynamics based on a neural network was proposed. Tire-terrain contact dynamics models were built by using discrete element method (DEM) simulations for tire-terrain contact and experimental data, thereby creating a dataset of tire contact forces for various tire materials in terrestrial environments. The neural network was applied to regressively learn the dataset, and a nonlinear neural network tire model was …

Method For Testing And Evaluating Intelligence Level Of Virtual Forces Based On Operational Experiments, Dayong Liu, Zhiming Dong, Weidong Zhang, Wenjun Zhang, Jiancheng Gao

Journal of System Simulation

Abstract: The intelligence level of virtual forces is a key factor affecting the credibility and effectiveness of tactical confrontation simulations. To address the current lack of a testing and evaluation system, a method for testing and evaluating the intelligence level of virtual forces based on operational experiments is proposed. Guided by operational experiment theory, the method stimulates the intelligent behavior of virtual forces by constructing dynamic confrontation environments, and collects, calculates, analyzes, and evaluates their intelligence performance data according to a systematic process. The overall architecture, logical functional modules, and basic evaluation process of the method are designed. A "4M" …

Northern Rainstorm Belt And Response Strategies, Jianping Huang, Xiaodan Guan, Xiaohuang Liu, Xiaohan Shen, Xiaojie Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the summer of 2025, the Northern Rainstorm Belt stretching from eastern Northwest China to the Northeast region exhibited a significant increase in summer precipitation and rainfall frequency over northern China. Cities in the north were frequently struck by extreme rainstorms, resulting in prominent disasters such as “floods in drylands and urban waterlogging”. Northern China spans a vast territory, serving not only as a major grain-producing area and a densely populated region but also as an ecological security barrier that connects the farming-pastoral ecotone and the Loess Plateau. Its stability has nationwide implications. Therefore, comprehensively enhancing flood control capacity, strengthening …

Model-Based System Verification: Theoretical Framework, Key Technologies, And Future Prospects, Bo Sun, Yi Ren, Silin Wang, Qi Liu, Zhidong Li

Journal of System Simulation

Abstract: Traditional system verification methods face significant challenges in terms of efficiency, coverage, and traceability. To address these issues, this paper introduced model-based system verification (MBSV), which deeply integrated verification activities within the model-based systems engineering model system and evolution process. It presented the foundational logic of MBSV and proposed a multiview unified verification modeling strategy based on system modeling language (SysML), integrating requirements, structure, behavior, and constraints. The paper discussed the algorithms for selecting representative paths and reducing equivalent classes to enhance verification efficiency, the principles of test path search, as well as the intelligent path search mechanism based …

Large Language Model For X Language Simulation: Architecture, Key Technologies, And Typical Applications, Laichunyang Peng, Fei Ye, Xiaoming Guo, Jinglin Zhou

Journal of System Simulation

Abstract: General-purpose large language models lack training on X language-specific corpora, and traditional fine-tuning methods lack targeted adaptation to the interdisciplinary integration and multimodule coupling of X language, resulting in problems such as non-standard syntax and semantic deviation in generated code. To address these issues, this paper systematically proposed the definition and integrated architecture of a large language model for X language simulation. Modeling subclasses were defined according to the disciplines and classes of X language, and dedicated adapters were constructed for each subclass. By merging their weights during the inference phase, the incremental integration of multi-domain modeling skills was …

Space-Ground Integrated Collaborative Positioning Algorithm And Simulation For Trajectory Enhancement, Juhui Wei, Xinyong Zhang, Jiongqi Wang, Xuanying Zhou, Zhangming He

Journal of System Simulation

Abstract: To address the challenges of low credibility, weak consistency, and poor accuracy in the information of trajectory results from space-based and ground-based passive time difference positioning simulation systems, a space-ground integrated collaborative positioning method was proposed for trajectory enhancement. By analyzing the operating principle of the time difference positioning system, the influencing factors that measure positioning accuracy in different feature dimensions were obtained; spline smoothing was employed for data alignment between space-based and ground-based systems; a spline-constrained parametric trajectory model was proposed to further enhance the stability; an error-sensitive feature selection framework for improving simulation consistency was constructed to …

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 …

Intelligent Competition Platform And Mode Driven By Cloud-Native Simulation, Long Qin, Hesong Huang, Lujia Yin, Chuan Ai, Qi Zhang, Xinmeng Li

Journal of System Simulation

Abstract: To solve the problems faced by the adversarial competition mode of agents, including difficult development and deployment, low resource utilization, poor reusability, and difficulty in accessing reinforcement learning algorithms, a new agent simulation training platform was designed. The software components of the competition platform were decoupled based on cloud-native technology; a high-performance simulation engine for the competition environment was proposed; a new method of an embedded reinforcement learning model for an intelligent control terminal was designed, with multiple online and offline policy-based reinforcement learning algorithms set. The experiment demonstrates that the development and deployment of the system is efficient, …

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 …

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. …

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 …