Operations Research, Systems Engineering and Industrial Engineering Commons^™

Barriers To Integrating Magnetic Resonance Imaging Systems In Emergency Medical Service Ambulances For Stroke Care, Arvind Kolangarakath

All Theses

Stroke is a life-threatening condition that can cause permanent damage by stopping blood flow in the brain. Quick and precise intervention is imperative, as every second lost increases tissue deterioration and impacts patient outcomes. Several technological advancements such as Magnetic Resonance Imaging (MRI), have revolutionized stroke care by enabling more accurate and quicker diagnoses in hospitals. Portable head MRI scanners with lower magnetic fields are a recent innovation capable of providing neuroimaging at the point of care within hospital settings. Integrating such a device into ambulances could potentially enhance stroke care during transit, facilitating prompt diagnosis and prognosis. However, few …

Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation. Such a problem involves the interplay among the operations that leads to NP-hard problems with complex constraints. Hence, existing methods for AGH are usually designed with massive domain knowledge but still fail to yield high-quality solutions efficiently. In this paper, we aim to enhance the solution quality and computation efficiency for solving AGH. Particularly, we first model AGH as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints including precedence, time windows, …

Automated Usability Evaluation Utilizing Log Files And Data Mining Techniques., Sima Shafaei

Electronic Theses and Dissertations

Usability evaluation is one of the essential aspects of software production. This evaluation should be done during the entire life cycle of a software application, from pre-production to production and post-production. However, the collection and evaluation of usability data can be a very challenging, time-consuming, and expensive task to be conducted manually, particularly for certain types of products and working conditions. These challenges may include the need to recruit participants fully engage and motivate them during evaluation, and factor in environmental conditions. Other challenges may include collecting data in real-world environments, especially when the users are geographically dispersed, minimizing evaluator …

A System Theoretic Process Analysis Framework And Model Based Approach For Resilient Space Architecture Design, Eric T. Sommer

Theses and Dissertations

As the capabilities provided by space-based systems offer significant contributions toward defense applications, potential adversaries stand to gain significant value in disrupting them. Therefore, the United States must pursue the development and operation of resilient space architectures, capable of delivering capabilities in the face of disruptions. To support this development, systems engineering methods require innovation to effectively ensure design of complex space architectures to meet their objectives. This thesis recommends and demonstrates a System-Theoretic Process Analysis (STPA) framework to qualitatively analyze space architectures. The analysis outputs identify design considerations, requirements, and constraints required for resilience. To enable a model-based systems …

Task Optimization Utilizing Digital Transformation Concepts - Automation Project Execution Via Agile Methodology, Anthony Steven Maiello

Theses and Dissertations

Task Optimization via the use of automated process improvements is becoming more widespread as more industries lean into the concepts surrounding digital transformation. This shift also necessitates a complementary adaptation in project management methodologies to support the rapid and ever-changing environment, requirements, and innovations. This thesis examines the effectiveness of Agile methodology in managing digital automation projects, with a specific focus placed on process improvements with systems engineering. It accomplished this by contrasting the original model, designed and derived utilizing traditional project management techniques, with the proposed model which is a direct result of the application of Agile project practices. …

Design Space Visualization And Exploration For Many Goal Problems Under Uncertainity, Niharika Balaji

Theses and Dissertations

ABSTRACT

Designing a complex engineered system is challenging due to many conflicting goals, uncertainties, and multiple interactions. Traditional optimization approaches often yield single-point solutions, which may not be suitable for early design stages due to their susceptibility to changes in conditions and uncertainties. To address this challenge, a satisficing approach is employed. This approach enables designers to effectively navigate the design space and identify satisficing solutions that balance conflicting goals in the face of uncertainties and changes in conditions. From a systems design perspective, we view design as an iterative process that involves making informed decisions based on available information …

A Multi-Objective Stochastic Programming Model For Resilient And Sustainable Supply Chains Under Uncertainty, Mohammad H. Majdfaghihi

Dissertations

Supply chain resilience (SCRES) and sustainable supply chain management (SSCM) have garnered significant attention in the field of Supply Chain Management (SCM) science. This heightened interest is largely attributable to the increasing frequency and severity of uncertainty and disruptions in global supply chains. Resilience is a beneficial approach to managing uncertainties and preparing for and mitigating the adverse consequences of Supply Chain (SC) disruptions. Sustainability is a key concept in SCM, driven by governmental regulations and heightened stakeholder and customer concerns for environmental and societal well-being. Studies on SCRES have traditionally focused on preparing for and reacting to disruptions and …

A Poisson-Based Distribution Learning Framework For Short-Term Prediction Of Food Delivery Demand Ranges, Jian Liang, Jintao Ke, Hai Wang, Hongbo Ye, Jinjun Tang

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic has caused a dramatic change in the demand composition of restaurants and, at the same time, catalyzed on-demand food delivery (OFD) services—such as DoorDash, Grubhub, and Uber Eats—to a large extent. With massive amounts of data on customers, drivers, and merchants, OFD platforms can achieve higher efficiency with better strategic and operational decisions; these include dynamic pricing, order bundling and dispatching, and driver relocation. Some of these decisions, and especially proactive decisions in real time, rely on accurate and reliable short-term predictions of demand ranges or distributions. In this paper, we develop a Poisson-based distribution prediction (PDP) …

An Improved Saliency Map With Trustworthiness For Localizing Abnormalities In Medical Imaging, Nolan C. Skelly

Theses and Dissertations

Saliency maps are a widely used methodology to make deep learning models more interpretable. They provide post-hoc explanations through identification of the most pertinent areas of an input medical image. These techniques have been assessed based on 1) localization utility, 2) sensitivity to model weight randomization, 3) repeatability, and 4) reproducibility. Ten saliency map techniques will be tested, Grad, Smooth Grad, Integrated Gradients, Smooth Integrated Gradients, XRAI, Grad-CAM, Guided Backpropagation, Guided GradCAM, GradCAM++, and ScoreCAM. The neural networks used to predict and read medical information require a reliable solution to provide medical practitioners intelligible results. Using the information of two, …

Federated Active Learning For Network Intrusion Detection, Matthew D. R. Sauer

Theses and Dissertations

This thesis addresses challenges with detecting attacks on computer networks within a Federated Learning (FL) framework, when labeled instances are few. We explore the integration of active learning (AL) and semi-supervised learning (SSL). AL efficiently uses data that would otherwise be wasted or require substantial time for labeling. SSL provides capacity to train models that have a limited amount of labeled data, by utilizing additional unlabeled data that is available. We show how FL combined with AL or SSL can realize a detection system that adapts and trains quickly to new networks, reducing the total amount of data labeling needed. …

Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu

Journal of System Simulation

Abstract: The definition and content of the virtual-real simulation are presented. According to different technical ideas, the development status and existing problems of virtual-real simulation are summarized from three aspects of digital twin, live-virtual-constructive (LVC) simulation, and parallel system. The similarities and differences, as well as the advantages and disadvantages of the three methods are analyzed and compared, and their main application fields are discussed. In order to deal with difficulties encountered in military training, operational tests, equipment development, and equipment maintenance, a solution based on virtual-real simulation is proposed by means of theoretical guidance, case comparison, and transfer and …

Research On Multi-Process Product Quality Prediction Based On Improved Bilstm, Tianrui Zhang, Yuting Liu, Yike Wang

Journal of System Simulation

Abstract: In response to the complex manufacturing process of multi-process products, a multi-process product quality prediction model based on the kernel principal component analysis (KPCA) - and improved sparrow search algorithm (ISSA) optimized bi-directional long short term memory (BiLSTM) was proposed to address the uncertain factors that affect product quality, while improving the capacity for each process and ensuring the stability, in multi-process production. Firstly, KPCA was used for data preprocessing, and a kernel function was established on the basis of principal component analysis together with kernel methods. As redundant features were removed through dimension reduction, an improved Gaussian mutation …

Adaptive Robust Trajectory Tracking Control For Nsv With Multiple Stochastic Disturbances, Xiaohu Yan, Yuwu Yao, Yuhua Wu, Jiangxin Xu

Journal of System Simulation

Abstract: A stochastic control scheme of adaptive robust trajectory tracking is proposed for near space vehicle (NSV) with stochastic noise input disturbances, Poisson random fluctuation disturbances, and control input saturation. The effective tracking of the height and speed reference signals is realized. For the outer loop trajectory control, the robust stochastic controller is designed for the height subsystem and the speed subsystem respectively. Additionally, the required attitude angle reference signals for the inner loop attitude control are obtained by converting the equivalent control input via numerical calculation. For the inner loop attitude control problems, an adaptive robust stochastic control scheme …

Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+, Weiping Zhao, Yu Chen, Song Xiang, Yuanqiang Liu, Chaoyue Wang

Journal of System Simulation

Abstract: Mainstream image semantic segmentation networks currently face problems such as incorrec segmentation, discontinuous segmentation, and high model complexity, which cannot be flexibly and efficiently deployed in practical scenarios. To this end, an image semantic segmentation network that optimizes the DeepLabv3+ model is designed by comprehensively considering the network parameters, prediction time, and accuracy. The lightweight EfficientNetv2 is adopted to extract backbone network features and improve parameter utilization. In the atrous spatial pyramid pooling module, the mixed strip pooling is utilized to replace the global average pooling, and a depthwise separable dilated convolution is introduced to reduce parameters and improve …

Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning, Jing Ni, Mengke Ma

Journal of System Simulation

Abstract: In order to solve the intercell scheduling problem of dynamic arrival of machining tasks and realize adaptive scheduling in the complex and changeable environment of the intelligent factory, a scheduling method based on a deep Q network is proposed. A complex network with cells as nodes and workpiece intercell machining path as directed edges is constructed, and the degree value is introduced to define the state space with intercell scheduling characteristics. A compound scheduling rule composed of a workpiece layer, unit layer, and machine layer is designed, and hierarchical optimization makes the scheduling scheme more global. Since double deep …

Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation Indicators, Quan Zou, Yixin Hua, Zhu Shao, Wenbi Zhao

Journal of System Simulation

Abstract: From the perspective of flight tests, how to evaluate the autonomous aerial refueling (AAR) capability and select key indicators for evaluation is a key problem to be solved for AAR trials. The standards requirements of aerial refueling and manned aircraft aerial refueling experience in China and abroad are analyzed. The total capability of AAR is studied, and key evaluation indicators in the AAR whole process including rendezvous, formation, docking, refueling, and disengagement are proposed. The evaluation method is demonstrated in both numerical simulation and hardware-in-loop test environments. Finally, the key indicators affecting the docking success of AAR are analyzed, …

Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning, Zhengxuan Jia, Tingyu Lin, Yingying Xiao, Guoqiang Shi, Hao Wang, Bi Zeng, Yiming Ou, Pengpeng Zhao

Journal of System Simulation

Abstract: Under the background of high-speed maneuvering target interception, an optimal guidance law generation method for head-on interception independent of target acceleration estimation is proposed based on deep reinforcement learning. In addition, its effectiveness is verified through simulation experiments. As the simulation results suggest, the proposed method successfully achieves head-on interception of high-speed maneuvering targets in 3D space and largely reduces the requirement for target estimation with strong uncertainty, and it is more applicable than the optimal control method.

A Cellular Automata Model For Simulating Ships Passing Through Waterways With Alternating Wide And Narrow Sections, Yulong Sun, Jianfeng Zheng, Jiaxuan Han, Chao Li

Journal of System Simulation

Abstract: For improving the traffic efficiency of wide and narrow alternating waterways, considering Kiel Canal as an example, according to the structural characteristics of Kiel Canal with alternating width and narrow sections, a two-way ship traffic flow cellular automata model is established, and the simulation of ships passing through Kiel Canal is studied. Cellular space is set up according to the actual structure of Kiel Canal, and the evolution rules are set up based on the fixed block theory and moving block theory. In particular, due to the structure of Kiel Canal, large ships cannot pass simultaneously in the narrow …

Rolling Bearing Fault Diagnosis Based On Weighted Domain Adaptive Convolutional Neural Network, Wenfeng Zhang, Zhichao Zhu, Dinghui Wu

Journal of System Simulation

Abstract: A rolling bearing fault diagnosis method based on a weighted domain adaptive convolutional neural network (WDACNN) is proposed to solve the problem that the data distribution of vibration signals of rolling bearings changes due to workload changes, which leads to poor generalization of fault diagnosis algorithm. In this method, the domain adaptation algorithm is embedded in the convolutional neural network to make the classifier based on the source domain achieve excellent generalization in the target domain, and the weight coefficient is introduced to weight the samples in the source domain to reduce the influence of the class weight deviation. …

Multi-Depot Half-Open Vehicle Routing Problem With Simultaneous Delivery-Pickup And Time Windows, Yingyu Zhang, Liyun Wu, Shengtai Jia

Journal of System Simulation

Abstract: To solve the multi-depot half-open vehicle routing problem with simultaneous delivery-pickup and time windows, this paper builds a mathematical model of a multi-depot half-open vehicle routing problem with simultaneous delivery-pickup and time windows by balancing the vehicle in and out of the distribution center and minimizing vehicle delivery distance as the goal. According to the characteristics of the problem, a brain storm algorithm based on chaotic mutation is designed to solve this problem,and the sequential crossover strategy is adopted to increase the population diversity. Meanwhile, the algorithm selects two chaotic maps for chaotic mutation operation, which employs the diversity, …

Charging Facility Layouts Based On Charging Selection Behavior, Lixiao Wang, Zhonghui Wang

Journal of System Simulation

Abstract: A charging facility layout method based on charging selection behavior is proposed for the current uncoordinated development of electric vehicles and charging infrastructure and the low utilization of public charging facilities. The influence of the charging selection behavior of electric vehicle users' trips on the charging facility layout is considered, and a charging selection behavior model is built and applied to the charging demand prediction. Based on the study of charging selection behavior and charging demands, a charging facility layout model with the minimization of total travel time as the objective function is built, and the reciprocal feedback between …

Uav-Enabled Task Offloading Strategy For Vehicular Edge Computing Networks, Feng Hu, Haiyang Gu, Jun Lin

Journal of System Simulation

Abstract: As intelligent vehicles are equipped with more and more sensors, the explosive growth of sensor data is generated, which brings severe challenges to vehicular communication and computing. In addition, the modern road presents a three-dimensional structure, and the system architecture of traditional vehicular networks cannot guarantee full coverage and seamless computing. A task offloading strategy for UAV-assisted and 6G-enabled (Sixth Generation) vehicular edge computing networks is proposed. Furthermore, a flexible and intelligent vehicular edge computing mode is composed by vehicles and UAVs, which provide three-dimensional edge computing services for delay-sensitive and computation-intensive vehicular tasks, and ensure timely processing and …

Development Of Combat Concept Of Intelligent Land Assault System Based On Dodaf, Can Wang, Haoran Ji, Qisheng Guo, Zhiming Dong, Yaxin Tan, Ge Mu

Journal of System Simulation

Abstract: In view of military demand traction in the development of land assault equipment, a combat concept of land assault systems for future intelligent combat is developed. Basedon the definition of relevant concepts and research boundaries, the combat concept model framework and modeling steps are proposed based on DoDAF, and the combat effect, combat process, combat nodes, resource interaction, system composition, and capability characteristics are analyzed in combination with the model description. The combat concept verification is carried out from the aspects of system combat efficiency and communication load by simulation experiments. The results show that the intelligent assault system …

Research On Operational Effectiveness Evaluation Method Of Space-Based Information Support Equipment System, Xiaolan Yu, Wei Xiong, Chi Han, Zhenwei Wu

Journal of System Simulation

Abstract: The operational effectiveness evaluation of space-based information support equipment systems has become a research hotspot in the military field. How to effectively deal with the nonlinear and confrontational problems of the operational effectiveness of the space-based information support equipment system has become a crucial issue in the development of the space-based information support equipment system. In this paper, a method for evaluating the operational effectiveness of the space-based information support equipment system based on the system dynamics (SD) model is presented. The SD flow rate basic tree entry modeling method is used to establish the basic tree entry model …

Requirements Of Parallel Combat System Based On Gqfd-Coupling Coordination Degree, Zhiming Dong, Bingshan Si, Liang Li

Journal of System Simulation

Abstract: In view of future intelligent unmanned combat characteristics, the concept of parallel combat is proposed and the model of parallel combat system is built based on OODA ring theory. Meanwhile, this paper builds a demand analysis model based on GQFD-coupling coordination degree to solve the low reliability, lack of objectivity, and single description perspective of the traditional quality function deployment (QFD) method and coupling coordination degree analysis during demand analysis. Additionally, the importance ranking of ability requirements in the parallel combat system is obtained by the house of quality of ability requirement analysis in the combat system based on …

Learning-Based Ant Colony Optimization Algorithm For Solving A Kind Of Complex 2-Echelon Vehicle Routing Problem, Xue Chen, Rong Hu, Hui Wang, Zuocheng Li, Bin Qian, Yixu Li

Journal of System Simulation

Abstract: Aiming at green 2-echelon vehicle routing problem with simultaneous pick-up and delivery, a learning-based ant colony optimization algorithm combined with clustering decomposition is proposed. The objective function to be minimized is total transportation cost wherein carbon emission cost is specially considered. Associated with the mutual coupling features of the 2-echelon vehicle routing problem, we propose a distance-based clustering method to decompose the original problem into a set of sub-problems. Then, a learning-based ant colony optimization algorithm is presented to find the solutions of the sub-problems based on which the solution of the original problem can be obtained. In the …

Comparison Of Different Weighting Scales When Measuring Mental Workload, Isabella Duque

Symposium of Student Scholars

Mental workload, a concept within the field of human factors and ergonomics, refers to the cognitive and perceptual demands that individuals experience while performing various tasks in the workplace. Assessing mental workload holds a significant role in designing occupational tasks, as inappropriate levels can impact job performance, employee well-being, and even workplace safety. By assessing and optimizing mental workload, organizations can enhance productivity, reduce errors, and foster a healthier work environment. The NASA Task Load Index (NASA-TLX) and the Surgery Task Load Index (SURG-TLX) are two tools used to subjectively assess mental workload. Both tools offer unweighted and weighted mental …

Kwad - Ksu All Weather Autonomous Drone, Nick Farinacci, Sebastian Gomez, Stewart Baker, Ed Sheridan

Symposium of Student Scholars

"KWAD" or "KSU all-Weather Autonomous Drone" project was sponsored by Ultool, LLC to the KSU Research and Service Foundation to create a lightweight drone capable of capturing HD video during all-weather operations. The conditions of all-weather operation include rainfall of one inch per hour and wind speeds of up to twenty miles per hour. In addition, a global minimum structural safety factor of two is required to ensure the system's integrity in extreme weather conditions. Potential mission profiles include autonomous aerial delivery, topological mapping in high moisture areas, security surveillance, search and rescue operations, emergency transportation of medical supplies, and …

The Static And Dynamic Behavior Of Steel Storage Tanks Over Different Types Of Clay Soil, Tarek N. Salem, Ayman El-Zohairy, Ahmed M. Abdelbaset

Faculty Publications

Steel storage tanks are widely used in different fields. Most of these tanks contain hazardous materials, which may lead to disasters and environmental damage for any design errors. There are many reasons which cause the failure of these tanks such as excessive base plate settlement, shear failure of soil, liquid sloshing, and buckling of the tank shell. In this study, five models of above-ground steel storage tanks resting over different types of clay soils (medium-stiff clay, stiff clay, and very stiff clay soils) are analyzed using the finite element program ADINA under the effect of static and dynamic loading. The …

Usu Army Rotc Cannon Assessment, Annalyn Jensen, Emma Sharp, Hunter Esplin, Spencer Fairbanks, Tannon Merrill

Biology Student Research

An assessment was conducted by students from the USU Industrial Hygiene Program on November 11th, 2023, to determine the noise exposure of USU Army ROTC Cadets involved in firing a 75 mm howitzer cannon at home football games. The assessment utilized personal dosimetry and sound level mapping to measure peak noise (Lzpk), average noise level (Lavg), and time-weighted average (TWA) levels. Findings indicate that two of the sampled Cadets were exposed above the Department of Defense (DOD) peak noise exposure limit and all three exceeded Lavg limits. The given recommendations include continuing the use of hearing protection devices (HPDs) and …