Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences Commons™

Open Access. Powered by Scholars. Published by Universities.®

Discipline
Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 3031 - 3060 of 63010

Full-Text Articles in Computer Sciences

Scene Generation Method For Maritime Target Recognition Based On Detection Parameters, Yuxuan Run, Dezhen Yang, Yeyang Liu, Wei Deng, Xiangyu Xing, Yi Ren Aug 2025

Scene Generation Method For Maritime Target Recognition Based On Detection Parameters, Yuxuan Run, Dezhen Yang, Yeyang Liu, Wei Deng, Xiangyu Xing, Yi Ren

Journal of System Simulation

Abstract: Traditional scene generation methods for maritime target recognition consider only the effects of different environments on the generated scene data, while overlooking the changes in scene information caused by sensor detection parameters, resulting in a lack of accuracy and authenticity in generated scenes. To address this issue, a detection parameter-based scene generation method for maritime target recognition was proposed. For the task of maritime target recognition, key detection parameters affecting scene generation quality and essential scene features were analyzed. An association relationship modeling method based on Bayesian networks was proposed to construct a mapping relationship model between scene features …

Go to article

Ship Fire Prediction Method Based On Evidence Theory With Fuzzy Reward, Chunyu Yang, Chuang Zhang, Xiaofan Zhang Aug 2025

Ship Fire Prediction Method Based On Evidence Theory With Fuzzy Reward, Chunyu Yang, Chuang Zhang, Xiaofan Zhang

Journal of System Simulation

Abstract: A multi-source information fusion approach based on the dempster-shafer (D-S) evidence theory with a fuzzy reward-penalty mechanism was proposed to address the issues of underreporting and false reporting in the early prediction of ship fires. PyroSim was utilized to construct a ship's laboratory model for fire simulation. Variations in carbon monoxide, temperature, and smoke concentration were recorded for data acquisition, followed by the application of a sigmf function for membership assignment. By leveraging the classical D-S theory, a reward-penalty mechanism was applied in weighted evidence fusion. Reward-penalty factors were utilized to differentiate various basic probability assignments, with unified belief …

Go to article

Research On Joint Simulation Of Special Vehicle Engine Operation Characteristics Based On Virtual Driving Scenarios, Xueyuan Xie, Chen Lin, Han Wu, Qinglan Zhao, Junfei Gao, Qiangguo Hao, Xinqian Zheng Aug 2025

Research On Joint Simulation Of Special Vehicle Engine Operation Characteristics Based On Virtual Driving Scenarios, Xueyuan Xie, Chen Lin, Han Wu, Qinglan Zhao, Junfei Gao, Qiangguo Hao, Xinqian Zheng

Journal of System Simulation

Abstract: The preliminary design of the overall operation performance of diesel engines cannot be guided by actual vehicle driving tests, which hinders the improvement of the power development level and efficiency of special vehicles. By using the virtual visual simulation engine Unity3D, two virtual driving scenario models were established: a flat road scenario and an undulating road scenario. Based on the speed characteristic parameters of the engine, a diesel engine's operation performance output model was constructed. Combined with the transmission system model and the longitudinal dynamics model of the vehicle's center of mass, a straight vehicle driving dynamics model was …

Go to article

Simulation And Optimization Of Support Processes For Aircraft Fleet Launch Under Limited Resources, Feng Gong, Tao Jiang, Qin Zhang, Yu Liu Aug 2025

Simulation And Optimization Of Support Processes For Aircraft Fleet Launch Under Limited Resources, Feng Gong, Tao Jiang, Qin Zhang, Yu Liu

Journal of System Simulation

Abstract: To address the scheduling problem of aircraft fleet support processes under limited resources, a fleet support process optimization model that covered multiple aircraft, activities, and resource constraints was developed. An activity node graph model was used to establish the temporal logic, resource competition, and other constraints in the fleet support process, forming a "time – activity – resource" multidimensional optimization model. A genetic algorithm based on priority encoding was proposed, incorporating a serial decoding strategy and a dynamic penalty function to handle the complex constraints in the model, efficiently solving the optimization problem under complicated temporal and resource constraints. …

Go to article

Short-Term Load Forecasting Based On Dual-Attention Temporal Convolutional Long Short-Term Memory Network, Lifen Li, Jinyue Zhang, Wangbin Cao, Huawei Mei Aug 2025

Short-Term Load Forecasting Based On Dual-Attention Temporal Convolutional Long Short-Term Memory Network, Lifen Li, Jinyue Zhang, Wangbin Cao, Huawei Mei

Journal of System Simulation

Abstract: In order to improve the accuracy of load forecasting and fully extract the hidden relationships between load and other characteristic factors, a load forecasting method based on dual-attention temporal convolutional LSTM network (DA-TCLSNet) was proposed. Correlation analysis was conducted on the dataset using the maximum information coefficient method to perform feature screening to reduce the computational cost of the model. The model input was constructed using a sliding window. The DATCLSNet forecasting model was constructed. The temporal convolutional layer extracted dependencies at different time scales and captured the nonlinear characteristics among variables such as load and weather. The multi-head …

Go to article

Research On 3d Visualization Of Safety Monitoring And Early Warning For Steel Continuous Casting Scenarios, Wei Zhang, Wei Sheng, Yidan Cao, Tingsheng Zhao Aug 2025

Research On 3d Visualization Of Safety Monitoring And Early Warning For Steel Continuous Casting Scenarios, Wei Zhang, Wei Sheng, Yidan Cao, Tingsheng Zhao

Journal of System Simulation

Abstract: In order to improve the visualization and integration of production safety monitoring and fault warning, a three-dimensional (3D) visualization model architecture for whole-process industrial production safety monitoring and early warning for steel continuous casting scenarios was designed. By using 3ds Max and Unity3D, a multi-dimensional and multi-scale model was built, and functional modules such as visualization display and multi-level early warning for safety monitoring data were developed. By combining WebGL technology and Node. js runtime environment, the visualization of whole-process industrial production safety monitoring based on Web terminal was realized. The alarm threshold determination method for whole-process industrial production …

Go to article

Optimal Scheduling Of An Integrated Energy System Considering Demand Response And Two-Stage P2g, Xinhui Duan, Zelong Cheng, Dongchao Zhang, Xiaochong Duan Aug 2025

Optimal Scheduling Of An Integrated Energy System Considering Demand Response And Two-Stage P2g, Xinhui Duan, Zelong Cheng, Dongchao Zhang, Xiaochong Duan

Journal of System Simulation

Abstract: In the context of carbon peaking and carbon neutrality goals, this study aims to improve the energy utilization rate and further explore the role of user-side flexible loads and P2G equipment in energy saving and emission reduction. An optimal scheduling model for integrated energy systems considering demand response and two-stage P2G was proposed. A regional integrated energy system coupled with electricity, heating, cooling, gas, storage, and hydrogen was taken as the research object. Models for system equipment and two-stage P2G were established. Based on load characteristics, a multi-load demand response model for electricity, heating, and cooling was constructed using …

Go to article

Storage Life Assessment Methods For Long-Term Storage Products Based On Multi-Scale Simulation: A Review, Hongmin Li, Xiao Han, Shuo Huang, Shengpeng Zhang, Shuanglong Rong, Hao Li, Cheng Qian Aug 2025

Storage Life Assessment Methods For Long-Term Storage Products Based On Multi-Scale Simulation: A Review, Hongmin Li, Xiao Han, Shuo Huang, Shengpeng Zhang, Shuanglong Rong, Hao Li, Cheng Qian

Journal of System Simulation

Abstract: Traditional experiment-based life assessment methods for long-term storage products suffer from drawbacks such as prolonged duration, high cost, and low prediction accuracy, greatly limiting the effectiveness of storage life assessment in practical applications. With the advancement of digital simulation technology, simulation analysis methods based on the physics of failure (PoF) have emerged as a research hotspot in the field of storage life assessment, as they can accurately characterize product aging behavior. The multi-scale characteristics of long-term storage products and their typical storage failure modes and mechanisms were analyzed. Multi-scale modeling and simulation analysis methods for storage failures of fundamental …

Go to article

Research On Digital Simulation Method For Cognitive Load Evaluation Of Pilots, Zeng Fan, Mingjun He, Xiangyu Xing Aug 2025

Research On Digital Simulation Method For Cognitive Load Evaluation Of Pilots, Zeng Fan, Mingjun He, Xiangyu Xing

Journal of System Simulation

Abstract: The operator's cognitive load constitutes a critical determinant of task performance. Pilots, as the primary operators of aircraft, must face an overwhelming volume of information during complex missions, which significantly heightens the risk of cognitive overload and operational errors. Evaluating cognitive load during tasks helps reduce human errors and improve system safety by optimizing design schemes. A simulation model was established to dynamically predict the pilots' cognitive load during tasks for multi-task scenarios. Based on the multiple resource theory, a method for quantifying cognitive load in multi-task conditions was established. By considering cognitive capacity, task time constraints, task priority, …

Go to article

Digital Testing And Evaluation: Current Status, Challenges, And Prospects, Bo Sun, Kai Zheng Aug 2025

Digital Testing And Evaluation: Current Status, Challenges, And Prospects, Bo Sun, Kai Zheng

Journal of System Simulation

Abstract: Digital testing and evaluation (DTE) represents a novel paradigm in the evolution of testing and evaluation methodologies within the digital era. It is achieved through the integration of multiple digital theories and technologies to conduct testing and evaluations in the digital domain. This paper analyzed the characteristics of test objects across different historical periods, reviewed the core features of testing and evaluation techniques in each stage, and unveiled the paradigm shifts within the testing and evaluation technology system. Building upon this foundation, it explored the new demands placed on testing by test objects in the information age, clarifying the …

Go to article

Dynamic Testing Architecture Of Intelligent Unmanned Systems Based On Parallel Battlefields, Dayong Liu, Zhiming Dong, Qisheng Guo, Wenjun Zhang, Jiancheng Gao Aug 2025

Dynamic Testing Architecture Of Intelligent Unmanned Systems Based On Parallel Battlefields, Dayong Liu, Zhiming Dong, Qisheng Guo, Wenjun Zhang, Jiancheng Gao

Journal of System Simulation

Abstract: To improve the inadequacy of traditional test and identification systems, this paper proposed an overall architecture for dynamic testing across the entire lifecycle based on the concept of parallel battlefield (integration of physical, virtual, and cognitive battlefields), meeting the new requirements for the testing of intelligent unmanned systems. This architecture included high-fidelity mapping between virtual and physical battlefields, red-blue adversarial deductions and model optimization, simulation to reality (Sim2Real), human-machine collaboration, and cloud-end integrated control, as well as multidimensional assessment and confidence analysis. Centered on the principles of "mutual driving between virtual and physical battlefields, dynamic closed-loop, human-machine collaboration, and …

Go to article

Adaptive Sampling And Ghost Multi-Scale Fusion For Lightweight Weld Defect Detection, Bin Lu, Xuan Yang, Zhenyu Yang, Xiaotian Gao Aug 2025

Adaptive Sampling And Ghost Multi-Scale Fusion For Lightweight Weld Defect Detection, Bin Lu, Xuan Yang, Zhenyu Yang, Xiaotian Gao

Journal of System Simulation

Abstract: To improve the accuracy and speed of welding defect detection and achieve lightweight models, a lightweight weld defect detection network based on YOLOv8, named light adaptive-weight sampling-YOLO (LAW-YOLO), was proposed. A lightweight adaptive weight sampling LAWS module was designed. It constructed an adaptive weight attention feature map by learning the interacting features within the receptive field. An optimized efficient weighted bidirectional feature pyramid network was adopted as the feature extraction backbone in LAW-YOLO. Furthermore, a ghost multi-scale sampling module was designed, and a hybrid attention mechanism was introduced to enhance the detection capability for small-scale defect targets. Experimental results …

Go to article

Optimization Of Product Oil Distribution With Multiple Trips And Multiple Due Dates Under Dynamic Demand, Yong Xie, Hailong Gao, Yutao Chen, Huanjiang Wang Aug 2025

Optimization Of Product Oil Distribution With Multiple Trips And Multiple Due Dates Under Dynamic Demand, Yong Xie, Hailong Gao, Yutao Chen, Huanjiang Wang

Journal of System Simulation

Abstract: In the case of dynamic demand, considering the order due date, vehicle transportation time window, and other factors, this paper developed an optimization model of periodic product oil distribution with multiple trips and multiple due dates to maximize the distribution revenue. The paper also designed a reinforcement learning-based large neighborhood search algorithm to solve the problem. The initial solution was constructed based on the forward insertion heuristic algorithm. Then, a deep reinforcement learning model for neighborhood operator selection was designed. By fitting the action value function through the double deep Q network, the optimal neighborhood operator was selected, and …

Go to article

Resource Allocation Method For Virus Spreading Control Based On Multi-Granularity Cooperative Coevolution, Xuanli Shi, Weineng Chen, An Song, Tianfang Zhao Aug 2025

Resource Allocation Method For Virus Spreading Control Based On Multi-Granularity Cooperative Coevolution, Xuanli Shi, Weineng Chen, An Song, Tianfang Zhao

Journal of System Simulation

Abstract: According to the principle of simplifying a complex problem into sub-problems for solution, a resource allocation method for virus spreading control based on multi-granularity cooperative coevolution (MGCC) was proposed. According to the characteristics of human's social network structures, MGCC decomposed the network into sub-networks with different scales according to different decomposition granularities. A contribution-based decomposition granularity selection strategy was proposed. Historical archives were used to record the contribution of different decomposition granularities to optimization, and the appropriate decomposition granularity was selected according to the optimization status. A projection-based constraint repairing strategy was designed to ensure the feasibility of solutions. …

Go to article

Research On Simulation Technology Of Fire Extinguishing In Engine Compartment Of Special Vehicle, Jianmin Niu, Yue Zhong, Feng Xu, Jindun Ma Aug 2025

Research On Simulation Technology Of Fire Extinguishing In Engine Compartment Of Special Vehicle, Jianmin Niu, Yue Zhong, Feng Xu, Jindun Ma

Journal of System Simulation

Abstract: In view of the difficulty of measuring the detection response time and evaluating fire extinguishing abilities of the fire extinguishing system after a fire accident in the engine compartment, the turbulence model was adopted, and numerical modeling of the fire propagation and the diffusion process of Halon fire extinguishing agent during the firefighting process was carried out. The development of fire and the fire extinguishing process at the corner and the middle position of the vehicle compartment was simulated, and the temperature changes during the occurrence and extinguishing of fires in different environments were collected, so as to obtain …

Go to article

Study On Semi-Physical Simulation Method Of Air Turbo Rocket Engine In Startup Process, Xuesen Yang, Wei Zhao, Binglong Zhang, Sanqun Ren, Xiaorong Xiang, Qingjun Zhao Aug 2025

Study On Semi-Physical Simulation Method Of Air Turbo Rocket Engine In Startup Process, Xuesen Yang, Wei Zhao, Binglong Zhang, Sanqun Ren, Xiaorong Xiang, Qingjun Zhao

Journal of System Simulation

Abstract: To satisfy the requirements for validating the control law of air turbo rocket (ATR) engines, a semi-physical simulation approach was proposed based on serial communication. This platform integrated a rapid prototype system, a supply system, a measurement and control system, a signal simulator, a fault injection system, and a real-time computer. A digital model of the engine was developed based on cross-compilation technology, enabling the coupling and semi-physical simulation of the engine control system and the supply system. A semi-physical simulation of the ATR engine in the startup process was carried out, and the fault handling strategy of the …

Go to article

Trajectory Planning And Tracking For Multi-Quadcopter In Dynamic Obstacle Environments, Haosheng Jiang, Fangfang Wu, Zexian Huang, Ziyue Ma, Chunyun Dong, Xubin Ping Aug 2025

Trajectory Planning And Tracking For Multi-Quadcopter In Dynamic Obstacle Environments, Haosheng Jiang, Fangfang Wu, Zexian Huang, Ziyue Ma, Chunyun Dong, Xubin Ping

Journal of System Simulation

Abstract: Multi-quadrotor UAV systems face challenges when performing complex tasks in dynamic obstacle environments. Therefore, a comprehensive particle swarm optimization-based task allocation method, a trajectory planning integrating the traditional Informed-RRT* and A* algorithms, and a trajectory tracking method based on model predictive control were designed. The multi-quadrotor task allocation problem was constructed as a classical multiple traveling salesman problem, and then, the particle swarm optimization was used to assign the task to multi-quadrotor UAVs. A fusion algorithm that combined the advantages of traditional Informed-RRT* and A* algorithms for quadrotor UAV trajectory planning was designed, so as to ensure that a …

Go to article

Multi-Robot Hierarchical Collaborative K-Robust Path Planning For Path Interference, Kaixiang Zhang, Jianlin Mao, Niya Wang, Zhihao Xu Aug 2025

Multi-Robot Hierarchical Collaborative K-Robust Path Planning For Path Interference, Kaixiang Zhang, Jianlin Mao, Niya Wang, Zhihao Xu

Journal of System Simulation

Abstract: To plan collision-free paths for multiple robots in interference environments, based on the multi-robot k-robust path planning, this paper designed a multi-robot hierarchical collaborative k-robust path planning framework. In the priority optimization layer, in response to the starting predicament caused by the solution sequence, the multi-robot path solving sequence was determined based on the closure factor. In the multi-robot robust coordination layer, with the goal of improving solution efficiency, a safety interval was introduced as the basis for the design of k-robustness and collision-free avoidance. A collision-free path constraint for multiple robots in the sense of k-robustness was given. …

Go to article

Research On Non-Singular Fast Integral Terminal Sliding Mode Trajectory Tracking Control Of Six-Axis Robotic Arm, Tao Chen, Lizhong Wang, Xiangjun Zou, Xiaojuan Li Aug 2025

Research On Non-Singular Fast Integral Terminal Sliding Mode Trajectory Tracking Control Of Six-Axis Robotic Arm, Tao Chen, Lizhong Wang, Xiangjun Zou, Xiaojuan Li

Journal of System Simulation

Abstract: To address the trajectory tracking control challenges caused by modeling parameter inaccuracies and disturbance uncertainties in robotic arms, a non-singular fast integral terminal sliding mode control scheme was developed. A new type of non-singular fast integral terminal sliding mode controller was designed. The non-singular fast terminal sliding mode ensured the rapid convergence of the system while avoiding the singularity during convergence. The integral term was used to enhance the suppression ability of disturbances and ensure the rapid response of the controller to errors. Lyapunov stability theory was applied to analyze the controller's convergence. The simulation results show that the …

Go to article

Lightweight Driver Face Object Detection Algorithm Based On Yolov8-Df, Mingyu Li, Jiaquan Lin Aug 2025

Lightweight Driver Face Object Detection Algorithm Based On Yolov8-Df, Mingyu Li, Jiaquan Lin

Journal of System Simulation

Abstract: The YOLOv8n detection algorithm has a large amount of computation and parameters in the driving environment. To address this issue, a lightweight driver facial object detection algorithm YOLOv8-DF was proposed. A lightweight multi-scale convolution module (LMCM) was proposed to replace the Conv module in the network, and the dual-channel design could reduce the computation and parameter quantity of the algorithm; the multi-scale design could enrich the feature information inside the network. The lightweight convolutional GhostConv, Fasterblock module, and C2f module were fused, and a dual-channel lightweight convolution module (DLCM) was fused with the SPPF module. The experimental results show …

Go to article

Towards Scalable Schema Mapping Using Large Language Models, Christopher Buss, Mahdis Safari, Arash Termehchy, David Maier, Stefan Lee Aug 2025

Towards Scalable Schema Mapping Using Large Language Models, Christopher Buss, Mahdis Safari, Arash Termehchy, David Maier, Stefan Lee

Computer Science Faculty Publications and Presentations

The growing need to integrate information from many diverse sources poses significant scalability challenges for data integration systems. These systems often rely on manually written schema mappings, which are complex and costly to maintain. While recent advances suggest that large language models (LLMs) can assist in automating schema mapping, key challenges remain. We motivate future research in schema mapping generation by highlighting key challenges, presenting a competitive bidirectional schema matching pipeline, and exploring the limitations of current methods for generating more complex mappings.

Go to article

Computer-Automated Systems And Methods For Using Language Models To Generate Text Based On Reading Errors, Scott Sosso, Siyu Chen, Ciara Figliuolo, Jack Mostow, Marlies Goes Aug 2025

Computer-Automated Systems And Methods For Using Language Models To Generate Text Based On Reading Errors, Scott Sosso, Siyu Chen, Ciara Figliuolo, Jack Mostow, Marlies Goes

AFIT Patents

A computer-implemented system and method generate personalized text based on statistics derived from input received from a user representing the user's attempts to decode graphemes into phonemes. Such statistics may be measured and recorded at the grapheme-phoneme level, and may include substitutions, insertions, deletions, and correct utterances of phonemes by the user when reading text. A language model may be trained based on characteristics of the user, such as the user's age and/or reading grade level, and the personalized text may be generated after such training of the language model. Generating the personalized text may include generating a text creation …

Go to article

Evaluating Adjustment And Proficiency Disparities In Virtual Reality, Mohammad Jahed Murad Sunny Aug 2025

Evaluating Adjustment And Proficiency Disparities In Virtual Reality, Mohammad Jahed Murad Sunny

Theses and Dissertations

The rapid integration of VR in various application domains necessitates a deeper understanding of how levels of user experience impact user performance and task efficiency. This study investigates the relationship between experience with VR, expertise in 3d computer gaming, and physiological skills across multiple performance metrics, such as task-completion time, task load, accuracy, manipulation speed, and related spatial requirements. In a comprehensive analysis of multiple levels of VR experience and 3d computer-game expertise, we identified key trends that indicate increased experience in both domains significantly enhances task efficiency while at the same time reduces perceived workload and improves task accuracy. …

Go to article

Machine Learning Research On Time Series Data, Zeyi Fan Aug 2025

Machine Learning Research On Time Series Data, Zeyi Fan

Lingnan Theses (MPhil & PhD)

Time series generated by complex systems, such as industrial IoT and user behavior systems, confront two core challenges: structured missingness (e.g., continuous or periodic gaps) that disrupt temporal dependencies, and the difficulty in effectively modeling dynamic long- and short-term temporal dependencies inherent in evolving patterns (e.g., user interests). Traditional approaches struggle to balance the preservation of local dependency continuity and the rational association of global long-range dependencies in structured missing scenarios, often incurring high computational costs. In temporal pattern modeling, the lack of adaptive mechanisms to fuse evolving long- and recent behavior trends (e.g., stable interest inertia vs. short-term preference …

Go to article

The Implications Of Insecure Use Of Fonts Against Pdf Documents And Web Pages, Junjie Xiong, Mingkui Wei, Xiao Han, Zhuo Lu, Yao Liu Aug 2025

The Implications Of Insecure Use Of Fonts Against Pdf Documents And Web Pages, Junjie Xiong, Mingkui Wei, Xiao Han, Zhuo Lu, Yao Liu

Computer Science Faculty Research & Creative Works

This paper identifies the importance of the safe use of fonts in web and document security. We find multiple attack surfaces that can be exploited by an adversary using malicious fonts. We conduct a comprehensive evaluation of Portable Document Format (PDF) documents collected from the real world to investigate how an attacker can bypass PDF signatures. We further evaluate the potential security threats that an attacker can bring to web-based emails. Our study shows that various security issues may be caused by the inappropriate use of fonts, which are nevertheless overlooked in the past years. As such, guidelines promoting the …

Go to article

Multimodal Representation Learning For Geospatial Soundscape Mapping, Subash Khanal Aug 2025

Multimodal Representation Learning For Geospatial Soundscape Mapping, Subash Khanal

McKelvey School of Engineering Graduate Student Theses & Dissertations

Sound is one of the fundamental senses that helps us reason about our environment. There exists an intricate relationship between the visual appearance of a location and the distribution of sounds present there. We propose leveraging this relationship to formulate the task of soundscape mapping—predicting the most probable distribution of sounds that could be perceived at a given geographic location, as observed in its overhead imagery. To support research on this task, we curated a comprehensive dataset, GeoSound, which consists of geotagged audio recordings from various sources, paired with both low- and high-resolution overhead imagery. We approach the soundscape mapping …

Go to article

Computational Imaging Under Incomplete Information, Weijie Gan Aug 2025

Computational Imaging Under Incomplete Information, Weijie Gan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Computational imaging is a pivotal field that synergizes physical measurement principles with advanced algorithms to generate visual information. An important task in this field is solving imaging inverse problems that aim to reconstruct high-quality images from observed measurements. Model-based deep learning (MBDL) has emerged as a particularly powerful tool for tackling these inverse problems by integrating machine learning (ML)-driven priors with knowledge of the imaging physics. This dissertation focuses on the pervasive challenge of informational incompleteness in computational imaging, arising from various practical and physical limitations, that hinder the widespread adoption of ML-driven computational imaging algorithms in practice. This includes: …

Go to article

Code Stories For Software Evolution, John Joseph Allen Aug 2025

Code Stories For Software Evolution, John Joseph Allen

McKelvey School of Engineering Graduate Student Theses & Dissertations

Programmers spend more than half of their time comprehending code, and in particular struggle to answer questions about the rationale, intent, and history behind software artifacts. Through this dissertation, I explore how history-aware tools can help programmers understand unfamiliar software artifacts. First, I investigated how providing additional context -- historical code changes grouped by the original developer's stated subgoals and the web foraging activity of the original developer impacted the process of code reuse. I found that programmers utilized these resources to 1) make better analogies between their reuse scenario and what code was already written, and 2) anchor into …

Go to article

Combining Code Analysis And Pedagogical Guidance: Automated Tools For Teaching Debugging In Introductory Programming, Yana Malysheva Aug 2025

Combining Code Analysis And Pedagogical Guidance: Automated Tools For Teaching Debugging In Introductory Programming, Yana Malysheva

McKelvey School of Engineering Graduate Student Theses & Dissertations

The ability to debug code is critical to being a programmer and represents a distinct skill from writing code. Yet debugging is rarely explicitly taught in introductory programming and Computer Science courses. Instead, novices typically develop their own debugging habits and strategies when they encounter bugs in their code, which are often less effective than those of expert programmers. When students do seek help with debugging, they traditionally turn to office hours conducted by Teaching Assistants (TAs) or, increasingly, to Large Language Models such as ChatGPT. However, both sources of assistance have limitations. TAs are often students themselves with limited …

Go to article

Towards Graph Foundation Models: Few-Shot And Zero-Shot Learning On Graphs, Hao Liu Aug 2025

Towards Graph Foundation Models: Few-Shot And Zero-Shot Learning On Graphs, Hao Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Graphs naturally model complex relationships and interactions across various domains, including social networks, biological systems, and recommender platforms. Graph Neural Networks (GNNs) have emerged as powerful tools for learning effective graph representations through iterative message passing, significantly improving performance in tasks such as node classification, link prediction, and graph classification. However, the success of GNNs largely depends on abundant labeled data, posing challenges in practical scenarios where labeled data is scarce or unavailable. This dissertation addresses these challenges by exploring few-shot and zero-shot learning within the graph domain. We first propose COLA, a self-supervised few-shot node classification method that exploits …

Go to article

First Prev Next Last