Physical Sciences and Mathematics Commons^™

Research On The Resilience Of Integrated Urban Passenger Transport Network In Urban Agglomerations Considering The Intra-Urban Service Network, Shida Nie, Chengbing Li, Bowei He, Xintao Li

Journal of System Simulation

Abstract: In order to solve the problem of insufficient comprehensiveness and refinement of the urban agglomeration passenger transport network model, Space L modelling method in complex network theory is adopted to construct a comprehensive urban passenger transport network model considering the urban internal service network. A comprehensive urban passenger transport network composed of intercity networks and intra-city service networks is built, and time-dependent edge weights in the network is considered. A time-weighted network efficiency model is proposed to evaluate the network resilience. The results show that under a random attack strategy, the relative time efficiency of the network fluctuates less, …

A Multi-Robot Collaborative Path Planning Algorithm With Chain Working Mode, Zhigang He, Dayan Li, Niya Wang, Jianlin Mao, Ning Wang

Journal of System Simulation

Abstract: In order to solve the problem that the traditional MAPF algorithms can lead to a large number of repeated paths and thus non-essential energy loss in application scenarios where multiple robots have a common goal point, a multi-robot chain work mode with a tractor is proposed, which divides the robots with common target points into subgroups for multi robot collaborative path planning, and a collaborative dynamic priority SIPP with tractor (Co-DPtSIPP) algorithm is given. The polygonal Fermat point principle and other methods are used to obtain the serial connection areas of each collaborative group robot; considering the sequence of …

Traffic Signal Detection Based On Improved Yolov7, Lanyue Zheng, Yujie Zhang

Journal of System Simulation

Abstract: An improved YOLOv7 is proposed to address the problem of low recognition accuracy in general object detection algorithms for traffic signal detection. The algorithm removes the 20×20 detection scale and adds a 160×160 detection scale to increase shallow features while making the model lightweight. It combines the bi-level routing attention (BRA) proposed in BiFormer with axial attention, and innovatively proposes axially-guided BRA (ABRA). This module is specifically designed for the characteristics of traffic signal positions. To address the issue of object size sensitivity to the IoU metric, the normalized wasserstein distance (NWD) measurement is introduced to improve object location …

Research On Dual-Layer Path Planning Method For Lunar Rover Based On Slip Prediction, Zhang Xingyu, Baolei Wu, Jun Wang, Miaoying Hong, Jiahui Wang, Yongqiang Qi

Journal of System Simulation

Abstract: In response to the challenges faced by lunar rovers in the process of path planning, such as safe obstacle avoidance and target deviation caused by complex terrain, a dual-layer path planning based on slip prediction is proposed. In this approach, flat terrain is adaptively selected to reduce the wheel slip of the lunar rover. The overall complexity of the terrain is calculated using digital elevation information, and a Q-learning algorithm with a three-level reward mechanism is designed to navigate around highslip areas, achieving global path planning. A depth camera is used to perceive obstacles, a dynamic window method based …

An Intelligent Tracking Control Method For Unmanned Vehicles With Time-Varying Disturbances, Jie Huang, Jie Huang

Journal of System Simulation

Abstract: An intelligent policy iteration tracking control method is proposed for the tracking control problem with bounded time-varying disturbances. An adaptive disturbance compensator is designed to counteract the bounded disturbance and guarantee the validity of the Hamilton-Jacobi-Bellman (HJB) equation. An identifier network is proposed to estimate the unknown vehicle dynamics, and a new HJB equation is derived using the reconstructed identifier tracking error. An online optimal tracking control strategy for unmanned vehicles is obtained in the state of identifier estimation with the assistance of actor-critic network. Based on Lyapunov theory, it is demonstrated that the identifier tracking error, identifier approximation …

Design Of Distributed Multi-Functional Integrated Signal-Level Confrontation Simulation System In Local Area, Weiqian Li, Tianyu Yang, Zongyang Li, Jianjun Chen

Journal of System Simulation

Abstract: In order to study the resources management and self-organized collaborative application method of multiple multi-functional integrated electronic equipment in the region, we build a signal-level digital simulation system that supports multiple distributed multi-functional integrated electronic equipment within a region to carry out cooperation or confrontation. A joint time advancing mechanism named "variable-step time advancing method based on frame scheduling" and "independent event driven time advancing method " is proposed. It can not only ensure the integrity of each frame of radar simulation data for each equipment, but also enable multiple equipment in the simulation system to advance simultaneously and …

Digital Twin Framework For The Generation And Optimization Of Security Policies For Tsn Industrial Control Systems, Huimai Zhang, Xiaoya Hu, Chunjie Zhou

Journal of System Simulation

Abstract: The characteristic of multi-service flow integration in TSN industrial control systems makes it very difficult to establish an accurate mathematical model. In order to ensure the coordination between the security policy and the real-time operation of the system, a four-layer double-closed-loop digital twin framework of "physical layer-data layer-twin layer-service layer" serving the generation and optimization of security policies is proposed. The optimal security policy generation is achieved through the internal closed loop composed of iterative optimization between the initial security policy generation at the service layer and the deployment verification at the twin layer. The deterministic communication process between …

Uav Path Planning Based On Improved Deep Deterministic Policy Gradients, Sen Zhang, Qiangqiang Dai

Journal of System Simulation

Abstract: Aiming at the problems of poor convergence and invalid exploration when UAVs perform path planning in complex environments, an improved deep deterministic policy gradient(DDPG) algorithm is proposed. Using a dual experience pooling mechanism to store success and failure experiences separately, the algorithm is able to use the success experience to strengthen the strategy optimization and learn from the failure experience to avoid the wrong path; an APF method is introduced to add a bootstrap term to the planning, which is combined with the exploration of noisy actions in a randomized sampling process to dynamically integrate the selected actions; multi-objective …

Optimization Of Vehicle Routing For Cross-Infection Risk In The Epidemic, Xiaodong Shi, Yongcheng Guo, Mingqi Ma, Jiarui Pan

Journal of System Simulation

Abstract: In view of the safety risks associated with logistics distribution route optimization during public health emergencies, this paper investigates the vehicle routing problem by incorporating the risk of cross-infection, integrates the cross-infection risk caused by logistics activities in the epidemic area into the logistics distribution model, and establishes a logistics vehicle distribution model with the goal of cross-infection risk and cost. An improved genetic algorithm is designed for model optimization and solution. Based on the integration of chaos initialization population and adaptive crossover and mutation operations, a neighbor exclusion operator is further proposed to enhance the global search ability …

Research On Economic Dispatching Strategy Of Chp Units Based On Srl, Xin Wang, Chenggang Cui, Xiangxiang Wang, Ping Zhu

Journal of System Simulation

Abstract: In addressing the challenge of the DRL algorithm in the optimization of combined heat and power (CHP) units, lacking safety and stability guarantees, a scheduling optimization method based on SRL is proposed. Utilizing Dymola platform, a district heating system model is constructed with the CHP unit as the heat source. A MDP model for the economic dispatching of CHP units is designed, incorporating control barrier functions (CBF) to guide safe exploration in DRL. Simulation results show that the CBF-DRL method, in complex and nonlinear district heating systems, not only accelerates the convergence of DRL algorithms but also efficiently utilizes …

Remote Sensing Small Object Detection Based On Cross-Stage Two-Branch Feature Aggregation, Jie Li, Yang Liu, Liang Li, Bengan Su, Jialong Wei, Guangda Zhou, Yanmin Shi, Zhen Zhao

Journal of System Simulation

Abstract: Aiming at YOLOv8's leakage and false detection problems caused by target scale difference and complex background in remote sensing small target detection, this paper proposes a remote sensing image small target detection method based on cross-stage two-branch feature aggregation. The global shared weights in the convolution operator and the context-aware weights of specific tokens in the attention are fused to obtain high-frequency local information and low-frequency global information; the global remote dependencies are captured using a lightweight MLP, and the parallel cross-stage learnable vision center mechanism is designed to capture the information of the local corner regions of the …

Mobile Robot Path Planning Based On Search-Step Optimized A* Algorithm, Die Yu, Baizhong Bao, Yan Si, Jian Duan, Xiaobin Zhan, Tielin Shi

Journal of System Simulation

Abstract: A search-step optimized A* algorithm is proposed to address the issues with the traditional A* algorithm in robot path planning tasks, such as the high time consumption in large-scale high-resolution maps and the poor paths qualitys. Based on the cubic Hermite curve, a set of search steps (the path edges connecting the current node to its successors) is constructed, which can match the size of the robot and satisfy the dynamic constraints of the robot. More accurate cost functions are established based on the length and maximum absolute curvature value of the curve. Experimental results show that compared with …

Signal Timing Optimization Via Reinforcement Learning With Traffic Flow Prediction, Ming Xu, Jinye Li, Dongyu Zuo, Jing Zhang

Journal of System Simulation

Abstract: In response to the existing reinforcement learning-based traffic signal control methods that do not consider the changing trends in traffic flow, leading to congestion and inability to adapt to complex and variable road conditions, we propose a traffic signal timing optimization reinforcement learning method based on flow prediction. A phase timing amplitude control model is introduced. This model analyzes the spatiotemporal characteristics of historical traffic data to predict the flow for the next time slot and calculates a reasonable range for phase timing based on the prediction results. The H-PPO algorithm is employed to control the signal phase while …

Capability Dependency Analysis Based On Kill Chain And Fdna, Yushuai Wang, Guangya Si

Journal of System Simulation

Abstract: To better support the operation SoS analysis, deeply analyze the impact of dependency relationship during mission accomplishment, and accurately grasp the deep logic of SoS capability generation, the capability dependency analysis method based on the kill chain and function dependency network analysis(FDNA) is proposed. Combined with the analysis of the characteristics of the capability dependency relationship, the kill chain closure and the kill web formation process are abstracted from the perspective of operational interaction, a capability dependency network modeling method for the SoS is proposed, and a specific process covering the identification of capability dependency, calculation of operability, solving …

A Radar Countermeasure Modeling Method Incorporating Cognitive Bias, Rui Wang, Xiangyang Li, Dong Wang, Hongguang Ma, Zhili Zhang

Journal of System Simulation

Abstract: Cognitive bias, stemming from electronic measurement error and variability in human perception, exists in cognitive electronic warfare and affects the outcomes of conflicts. In this paper, the dynamic game approach is employed to develop a model for cognitive bias induced by incomplete information and measurement errors in cognitive radar countermeasures. The payoffs for both parties are calculated using the radar's anti-jamming strategy matrix A and the jammer's jamming strategy matrix B. With perfect Bayesian equilibrium, a dynamic radar countermeasure model is established, and the impact of cognitive bias is analyzed. Drawing inspiration from the cognitive bias analysis method used …

Seg-Swin: A Dual-Attention Transformer Model For Advanced Amd Classification And Lesion Detection Using Color Fundus Imaging, Niveen Nasr El-Den, Mohamed Elsharkawy, Ibrahim Saleh, Ali H. Mahmoud, Mohammed Ghazal, Ashraf Khalil, Ashraf Sewelam, Hani Mahdi, Ayman El-Baz

All Works

Age-related macular degeneration (AMD) is a prevalent retinal disorder in the elderly, often leading to significant vision impairment. The diagnosis of AMD is confirmed through various medical imaging modalities, with color fundus photography (CFP) being a primary tool. The detection and staging of AMD-severity depend on several factors, including the number and size of drusen, the presence of pigmentary changes, geographic atrophy, and neovascularization, all of which are identifiable through CFP. In this study, we introduce an innovative dual-vision transformer-based network designed to automatically detect AMD and classify its severity into either dry AMD or wet AMD using CFP. Early …

Research Week 2025, Michael Schueth

Research Week

Welcome to Undergraduate Research Week at Collin College!

This week celebrates the innovative research and scholarly work of our undergraduate students across all disciplines. From our informative webinars to Cultivating Scholars, our student poster presentation, the week offers opportunities to explore new ideas, share discoveries, and connect with fellow researchers and faculty mentors.

We invite all students, faculty, and staff to participate in these events designed to highlight the importance of undergraduate research in academic and professional development. Whether you're presenting your work or simply curious about your peers' projects, your engagement helps foster our college's culture of inquiry and …

Cultivating Scholars 2025, Elizabeth Hamner

Research Week

Cultivating Scholars is an interdisciplinary event promoting undergraduate students and their special interest topics. It is a research-based setting meant to imitate a professional conference. Students work with Faculty Mentors to conduct a high-quality project and present it to the community.

Date: April 24, 2025, 5:30-7:30 p.m.

Place: Collin College, Frisco Campus Conference Center

So Much More Than Summer Camp: The Importance Of Environmental Education At Nature Centers, Olivia P. Upton

Student Scholar Showcase

In conjunction with my Westover Honors Thesis, my Bonner Legacy Project focused on the development of environmental education curriculum and programming at Camp Kum-Ba-Yah Nature Center [CKBY]. Informed by a review of current climate education, lesson plans and activities were modified in collaboration with CKBY staff to be more climate-focused and aid in the development of systems thinking skills. Activities were compiled and edited to teach concepts, such as food webs, feedback loops, and the greenhouse effect, while also promoting team-building and critical thinking. Educational kits for each activity were created, which include all materials needed as well as a …

Climate Change Adaptation Through Economic Democracy, Shriraksha Mohan

Best Integrated Writing

Mohan investigates and combines three different areas of literature and social movements to discuss the problem of climate change and economic adaptation. The value of this work is that it can be used to communicate among three independent types of social movements and inquiries. This can strengthen and connect dispersed yet overlapping efforts in addressing work issues, resource utilization, economic governance and participation, and ecological problems economies face today.

So Much More Than Summer Camp: The Importance Of Environmental Education At Nature Centers, Olivia P. Upton

Student Scholar Showcase

Education in the U.S. currently faces a deficit in the promotion and proper teaching of climate change curriculum. Oftentimes caused by a lack of clear teaching standards for environmental education, the American political machine stirring up controversy, or teacher preferences, there are obvious gaps in the teaching of climate change curriculum. As climate change is considered one of the greatest threats facing humanity today, there is a need to educate people, especially younger generations, in order to navigate future challenges and make informed decisions. Nature centers offer the ideal location for the promotion of climate change education based on their …

Breaking Down Terminology Of Clojure Error Messages For Beginner Programmers, John Walbran, Jaydon Stanislowski, Tristan Kalvoda

Undergraduate Research Symposium 2025

The Clojure programming language has educational potential for beginner programmers due to its clean, simple syntax and its strong focus on functional programming, an important aspect of CSci education. However, one weakness of Clojure lies in its error messages, which are messages that programmers receive when a program goes wrong. The terminology and shorthands used to convey necessary information for understanding the error are often confusing to novices. The issue is exacerbated by the fact that the error messages are phrased in terms of the underlying programming language – Java – which beginner programmers may typically be unfamiliar with. A …

Water Quality Of The Inner Puno Bay Of Lake Titicaca, Zoe Hoaglund

Undergraduate Research Symposium 2025

Lake Titicaca straddles the border between Bolivia and Peru and is the highest lake in the world. The Lake has held great significance, particularly to the Incan empire for the last five thousand years as a source of drinking water, for agricultural use, and is the primary source for protein from native and more recently from non-native species of fish. It currently supports a growing fish farming industry for both Bolivia and Peru. Puno is one of the major urban centers on Lake Titicaca and supports a population of about 1.3 million people which derive their drinking water and a …

Evaluating Water Quality Upstream And Downstream From A Proposed Restoration Project On The Pomme De Terre River In Morris, Mn, Payton Prieve

Undergraduate Research Symposium 2025

The recent push to restore natural river conditions provides opportunities to investigate the effects of dam removal and channel modification, particularly if data are collected before such projects are initiated. The MN DNR plans to modify the Pomme de Terre River channel at the Crissy Lake dam (Morris, MN) by constructing and directing water flow over stone arch rapids to remove the barrier to fish, restore flow, and enhance river conditions. We aim to characterize the Pomme de Terre River upstream and downstream from the project site before construction to provide data to compare with river conditions after the project …

Elder Fraud Metrics And Preventative Measures Of Chesapeake, Virginia, Joey J. Whitmore Jr.

Cybersecurity Undergraduate Research Showcase

Geriatric crime continues to escalate in the digital era, where older individuals are disproportionately being targeted because of their low digital literacy and high susceptibility to online frauds. In this paper, we examine the breadth of elder fraud in Chesapeake, Virginia using FBI Internet Crime Complaint Center (IC3) data and state-level cybersecurity initiatives and survey responses. Older adults aged 60 and up have reported losses of over $3.4 billion in 2023 alone, underscoring the importance of proactive measures. It assesses the public awareness from traditional and AI-based perspectives revealing significant gaps in digital safety literacy and fraud reporting mechanism among …

Ligo Detector Characterization In The First Half Of The Fourth Observing Run, S. Soni, B. K. Berger, D. Davis, F. Di Renzo, A. Effler, T. Ferreira, E. Goetz, Francisco Llamas Villarreal, Volker Quetschke, J. Glanzer

Physics & Astronomy Faculty Publications

Progress in gravitational-wave (GW) astronomy depends upon having sensitive detectors with good data quality. Since the end of the Laser Interferometer Gravitational-Wave Observatory-Virgo-KAGRA third Observing run in March 2020, detector-characterization efforts have lead to increased sensitivity of the detectors, swifter validation of GW candidates and improved tools used for data-quality products. In this article, we discuss these efforts in detail and their impact on our ability to detect and study GWs. These include the multiple instrumental investigations that led to reduction in transient noise, along with the work to improve software tools used to examine the detectors data-quality. We end …

Pursuing Sustainability In Campus Dining Services, Nick Ventrola, Emily Zito

Sustainability Research & Practice Seminar Presentations

Nick Ventrola, WCU Dining Services Resident District Manager, and Emily Zito, WCU Dining Services Registered Dietitian, present "Pursuing Sustainability in Campus Dining Services".

Rewiring An Enzyme: K135f Mutation In Malate Dehydrogenase, Lauren Ratz, Kaci Schmoll

Undergraduate Research Symposium 2025

Malate Dehydrogenase (MDH) is an enzyme that catalyzes the reaction of malate to oxaloacetate by reducing the cofactor NAD+ to NADH in the citric acid cycle, playing a crucial role in cellular metabolism. Alterations in the MDH structure have been linked to metabolic diseases and cancers, though its overall structure remains poorly characterized. To better understand MDH, we manipulated its structure by inserting a point mutation into the flexible loop region at position 135, exchanging a lysine (Lys) to a phenylalanine (Phe). We hypothesized that mutating a positively charged amino acid (Lys) to an aromatic amino acid (Phe) would cause …

The Hidden Carbon Footprint Of Ai Models: Gpu-Aware Carbon Modeling, Youzhi Li

Undergraduate Research Symposium 2025

The rapid growth of AI technology has sparked transformative innovations but also increased carbon emissions. Recent research found that computer systems' carbon emissions are shifting from operational carbon to embodied carbon, but they did not fully capture the rapidly evolving AI landscape. Most recent research focused on operational carbon, neglecting the long-term environmental impact of embodied carbon. We found two gaps that persist in recent research. First, current carbon modeling focused on Central Processing Units (CPUs), neglecting the carbon modeling of Graphical Processing Units (GPUs). Second, it focused on primary components, neglecting significant contributions from peripheral components to the embodied …

Analyzing Musical Emotions: A Multi-Dataset Approach To Sentiment And Mood Classification In Songs, Mahad Syed

SPARK Symposium Presentations

Music evokes a wide range of emotions, yet most music recommendation systems focus on sound and listening patterns rather than the meaning of lyrics. This project enhances lyric-based emotion recognition by applying Natural Language Processing (NLP) and Machine Learning (ML) to classify song lyrics into emotional categories.

I used eight datasets from Kaggle, including collections of lyrics, emotion labels, and audio features, providing a strong foundation for analysis. Our approach combines traditional NLP techniques (like TF-IDF and Word2Vec) with advanced deep learning models (such as BERT and XLNet) to classify lyrics into categories like happy, sad, angry, calm, romantic, and …