Operations Research, Systems Engineering and Industrial Engineering Commons^™

Research On Detection Data Driven Calibration Method Of Traffic Simulation Parameters, Wenxin Ma, Ruimin Li

Journal of System Simulation

Abstract: To improve the accuracy of traffic simulation model and timely response of traffic demand and driving behavior changes, dynamic calibration method of simulation parameters based on detection data is proposed. Dynamic interaction between detection data and simulation platform is proposed. Intersection of Guanghua Road/Jintong East Road in Beijing and five consecutive intersections on Youyi Street in Baotou are Selected as study cases. Sensitivity analysis is conducted on initial parameter combinations. Based on the analysis results, parameters to be calibrated are selected. Models of cases are developed in VISSIM and driving behavior parameters are calibrated. Simulation results show that …

Weld Bead Size Prediction Of Wire And Arc Additive Manufacturing Based On Acs-Dbn, Dong Hai, Xiuxiu Gao, Mingqi Wei

Journal of System Simulation

Abstract: Welding pass overlap is the essence of wire and arc additive manufacturing (WAAM) technology. Appropriate process parameter selection is of great significance to control the welding pass geometry and improve the dimensional accuracy of the molded parts. A prediction model of deep beilef network (DBN) optimized by adaptive cuckoo search (ACS) algorithm is constructed. The welding width and residual height of the weld pass are predicted based on the four technological parameters of the given nozzle height, welding current, welding speed and wire feeding speed. The optimal number of hidden layers and hidden elements are determined based on the …

A Data-Driven Modeling Method For Game Adversity Agent, Zeng Bi, Fang Xiao, Deshuai Kong, Xiangxiang Song, Zhengxuan Jia, Tingyu Lin

Journal of System Simulation

Abstract: Aiming at the problems of collaborative modeling of formation behavior and intelligent generation of decision-making in complex confrontation scenarios, based on the serious game to simulate the confrontation scenarios of complex maritime equipment against the air, this paper proposes a data-driven modeling method for game agent and uses a distributed modeling technology of parallel adversarial scenarios and opportunistic decision making technology of smart targets to achieve agent modeling. It provides support for the further exploration of multi-objective collaborative modeling in complex confrontation scenarios. The simulation results show that deep reinforcement learning algorithms can provide a basis for the modeling …

Research On Usv Navigation Simulation Key Technologies, Jianhai Jin, Zexing Zhou, Zhang Bo, Yihong Chen, Xizhong Wei

Journal of System Simulation

Abstract: In order to solve the problems of long test time, high cost and high risk, a general framework of simulation system for autonomous navigation test and verification of USV(Unmanned Surface Vessel) has been developed, and some key simulation technologies such as complex scenario simulation, intelligent perception, navigation simulation and environmental effect modeling are researched. the dynamic equation, kinematics equation, wind load modeling, wave surface modeling, wave drift force modeling and ocean current modeling are designed and realized. The simulation system is proved to have high accuracy and fidelity by the real ship test on the lake, which can greatly …

Study On Prediction Of Crystal Properties Based On Deep Learning, Buwei Wang, Wang Min, Fan Qian, Ya'nan Wang, Hanwen Zhang, Yunliang Yue

Journal of System Simulation

Abstract: Predicting crystal properties using traditional machine learning methods requires complex feature engineering. In order to bypass time-consuming feature engineering, element network (ElemNet), representation learning from stoichiometry (Roost), compositionally-restricted attention-based network (CrabNet) and crystal graph convolution neural network (CGCNN) based on deep learning technology are used to simulate the formation energy, total energy per atom, band gap, and Fermi energy of crystal. The residual learning is introduced into CGCNN, and a crystal graph convolution residual neural network (CGCRN) is proposed. In the CGCRN, the number of hidden layers and the number of nodes in the hidden layers are increased, …

Kinematics Analysis And Simulation Of Automatically Tracking Dental Surgery Lamp, Zerui Jiang, Lijun Yang, Li Jun, Xiaolong Jiao, Zheng Hang

Journal of System Simulation

Abstract: In order to solve the problem that the oral surgical lamp cannot automatically adjust the irradiation posture of the surgical lamp according to the face direction and oral cavity position, a six-degree-of-freedom automatic tracking visual manipulator solution is proposed. Coordinate conversion is achieved through binocular vision to obtain three-dimensional information of oral cavity position and face normal vector. The geometric method is introduced into the kinematics calculation, and the closed solution of the inverse kinematics is obtained. The correctness is verified by the Maltab programming and the introduction of numerical values. Five-degree polynomial motion planning is performed …

Research On Digital Twin-Based Modeling And Monitoring Of Five-Axis Grinder, Xiao Tong, Haifan Jiang, Guofu Ding, Jiang Lei, Shuwen Ma

Journal of System Simulation

Abstract: Aiming at the poor virtual-real interaction ability, single data presentation mode, and hysteretic abnormality handling in CNC machine tool status monitoring, a visual monitoring method for machine tool process based on digital twin is proposed, Which realizes the mapping of three subsystems of machine tool, machinery, control and electrical to the information space from three dimensions of geometry, logic and data. The verification of instructions and CNC programs, real-time status monitoring and abnormality handling during operation are carried out. A digital twin-based machine tool modeling and monitoring system is designed and developed. Taking a five-axis CNC …

Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections, Zhao Dan, Xuejun Niu, Shuhao Zhang, Jiaxu Wei

Journal of System Simulation

Abstract: Contraflow left-turn is one of the traffic organization ways at intersections. By analyzing the setting parameters of the contraflow left-turn, the length and the range of the contraflow left-turn lane, the constrained conditions of the contraflow left-turn are determined, and the applicable conditions are determined from the road, traffic and signal control. VISSIM software is used to analyze a road intersection, simulate and evaluate the indicators related to the intersection entrance, optimize the timing plan of contraflow left-turn lane, and validate the feasibility and advantages of contraflow left-turn lane. The results show that the intersection delays are reduced by …

Improved Ant Colony Optimization Algorithm For Jamming Resource Allocation, Qingyun Wang, Dezhong Jiao, Shi Shuo, Genyan Peng, Junhua Sun, Yuxin Duan

Journal of System Simulation

Abstract: Ant Colony Optimization (ACO) is a new intelligence optimization algorithm. When applied to jamming resource allocation, the velocity of convergence in optimization process is slow and the probability of obtaining the global optimal solution is low. In order to raise the efficiency of jamming resource allocation and the probability of getting global optimal solution, the attenuation factor is improved to a variable that changes according to the exponential function in optimization process. The attenuation factor is taken as a relatively small value in the initial search phase, and increases monotonically and exponentially as the number of iterations increases. Simulation …

Research On Cloud Tool Integration And Management Methods, Tianying Zhang, Ji Hang, Junhua Zhou, Tao Luan

Journal of System Simulation

Abstract: In response to the application needs of using professional tools to develop complex products in the fields of aerospace, aviation, weapons, ships, etc., it is urgent to implement centralized management of cloud tools and cross-professional sharing of tools through tool service-oriented methods, so as to solve issues such as inconsistent tool versions, cross-professional resource barriers, and high thresholds for tool mastery during the traditional model development process. By studying the integration and calling methods of cross-professional and different versions of self-developed tools, as well as methods of tool server operation control, authority management, etc., and taking the local …

Research On Semi-Physical Simulation Model Of Special Vehicle Cockpit With Force Feedback, Liang Feng, Zhili Zhang, Xiangyang Li, Yihao Li, Wang Bei, Long Yong

Journal of System Simulation

Abstract: To improve the interaction and immersion of cockpit simulation training system, a semi-physical model of special vehicle cockpit with force feedback is studied. The important force feedback parts of the semi-physical simulation model are designed to provide more real operation experience for operators. The simulation training method of special vehicle cockpit based on dynamic model is studied to match the action input of operators with scene changes and provide a high fidelity visual experience. The driving simulation operation process of special vehicle is analyzed and verified. Simulation experiments show that the model has the characteristics of high precision, fast …

Special Vehicle Driving Training Simulation System Based On Integration Of Virtuality And Reality, Xiangyang Li, Wang Xiao, Zhili Zhang, Yihao Li, Long Yong

Journal of System Simulation

Abstract: Aiming at the actual demands of special vehicle driving training, special vehicle driving training simulation system is designed and developed based on the integration of virtuality and reality mode. Through building all kinds of mathematical models, functional modules, workflows and control software, and applying the cab that same as actual equipment with manipulating device, central control instrument and driving seat, immersive driving training environment with integration of virtuality and reality is established based on 6-DoF motion platform and its control system as well as multi-channel visual display device. It can provide the integrated support platform with “educating, training and …

Low Power Visual Odometry Technology Based On Monocular Depth Estimation, Ma Rong, Qiurui Chen, Zhang Han, Mei Zheng, Wang Rui, Wei Wei

Journal of System Simulation

Abstract: With the development of artificial intelligence, precision machinery and computing technology, micro-unmanned system will play an important role in the future battlefield. To solve the lack of monocular visual odometry scale, micro robot power consumption and load limits, the monocular depth estimation technology is introduced and a low view dataset is collected. A convolutional neural network to predict depth information from a single image is built, and the structure of neural network model is optimized. The depth estimation with monocular visual odometry are combined and deployed on JetsonNano. Experiments show that the combined monocular visual odometry can recover scale …

Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel, Feng Xiao, Zhang Hui, Zhou Rui, Qiao Lu, Wei Dong, Dandan Li, Yuyao Zhang, Guoqing Zheng

Journal of System Simulation

Abstract: In order to construct a maize kernel variety recognition model with high recognition accuracy and suitable for mobile phone application, a mobile phone is used to obtain maize kernel double-sided (embryonic and non-embryonic) images. Based on the lightweight convolutional neural network MobileNetV2 and transfer learning, a maize kernel image variety recognition model is constructed. In view of the existing research methods are mainly for single-sided recognition of maize kernel variety, the performance of single-sided and double-sided characteristics modeling and recognition is compared. The results show that the double-sided recognition accuracy of maize kernel double-sided characteristics modeling is 99.83%, which …

The Product Test Scheduling Problem, Megan Wydick Martin, Cliff Ragsdale, John Fico, Carlos G. Cajica-Sierra, Richard M. Fetcenko

International Journal of Applied Management and Technology

This research focused on product test scheduling in the presence of in-process and at-completion inspection constraints. Such testing arises in the context of the manufacture of products that must perform reliably in extreme environmental conditions. Often, these products must receive a certification from prescribed regulatory agencies at the successful completion of a predetermined series of tests. Operational efficiency is enhanced by determining the optimal order and start times of tests so as to minimize the makespan while ensuring that technicians are available when needed to complete in-process and at-completion inspections. We refer to this as the product test scheduling problem. …

Choosing Wearable Internet Of Things Devices For Managing Safety In Construction Using Fuzzy Analytic Hierarchy Process As A Decision Support System, Sharique Khalid

Theses, Dissertations and Capstones

Many safety and health risks are faced daily by workers in the field of construction. There is unpredictability and risk embedded in the job and work environment. When compared with other industries, the construction industry has one of the highest numbers of worker injuries, illnesses, fatalities, and near-misses. To eliminate these risky events and make worker performance more predictable, new safety technologies such as the Internet of Things (IoT) and Wearable Sensing Devices (WSD) have been highlighted as effective safety systems. Some of these Wearable Internet of Things (WIoT) and sensory devices are already being used in other industries to …

Clarity, Organization, Precision, Economy: A Technical Writing Guide For Engineers, David J. Adams, University Of New Haven

Civil Engineering Faculty Book Series

This fourth edition of COPE was sparked by my involvement with PITCH (Project to Integrate Technical Communication Habits) at the Tagliatela College of Engineering at the University of New Haven. This new edition contains additional material on data displays, as well as some additional material on writing about data—including how to avoid rhetorical shifts that undermine the precision of a technical report.

Launch Editorial, Jindong Qin, Xiaofang Chen, Lida Xu

Information Technology & Decision Sciences Faculty Publications

The digital economy is first and foremost a data economy, and data is the first element of the digital economy. Management System Engineering (MSE) is dedicated to the methodology of System Engineering (SE) and the practice of Management Decision Making. The digital economy is a network economy, and the Internet is the basic carrier of the digital economy. [Extracted from the article]

Data-Driven Semantic Modeling For Welding Assemblies, Fahim Ahmed

Wayne State University Dissertations

A significant information gap is prevalent between the design domain and the manufacturing domain. The designers lack manufacturing awareness as they have little knowledge regarding the manufacturability of their designs. The welding domain falls prey to this issue as designers lack manufacturing awareness and welding engineers lack weldability of the product assembly. Data-driven techniques have shown promising results in the analysis and understanding of complex welding processes. Data analytics play a significant role to turn data into valuable insights to assist in the weldability certification decision-making or weldability prediction for Resistance Spot Welding (RSW) as well. We have used machine …

Optimization-Based Uav Fleet Routing And Safety Assurance – Models, Algorithms, And Prototyping, Zhenyu Zhou

Wayne State University Dissertations

Unmanned aerial vehicles (UAVs), especially multi-rotor drones, have been increasingly used in various scenarios in the last decade. With the reduced hardware costs, improved battery life, and enhanced processor performance, we can eventually allow all kinds of drones to automatically travel through the low-altitude airspace. The large-scale application of drones will extend the basic transportation facilities from the ground to the air and form 3D transportation networks for the future. Compared to current ground-vehicle and aircraft traffic systems, multi-UAV systems are far from well-developed. Most current multi-UAV systems are human-operated or pre-programmed to perform specific tasks. The current application of …

Automotive Product Assortment Planning With Consideration Of Distribution Channel Dynamics, Madagedara Maduka Rushanjalee Balasooriya

Wayne State University Dissertations

Automotive original equipment manufacturers (OEMs) are putting a lot of effort into maintaining an efficient order catalog to offer better products to their customers in maketo-stock (MTS) markets. While product “assortment planning" research grows to more effectively identify the best assortments for OEMs, the existing configurable assortment planning literature ignores a significant dimension: the impact of distribution channels, especially dealer franchise networks. Dealers face unique challenges in trying to best satisfy the choice preferences of their local consumers by balancing their limited product configuration inventory with profitability. In many predominantly MTS automotive markets such as the U.S., the reality is …

Improving Or Operations Using Machine Learning Techniques, Tannaz Khaleghi

Wayne State University Dissertations

Recently, health care related studies are being widely conducted by researchers using unique and efficient techniques to increase system profitability, quality of care, and patient satisfaction. Surgery department is considered as the hospital's engine, and cost of surgical services has a huge impact on the overall profitability of the hospital. This thesis proposes novel approaches to improve the efficiency of surgical services by using machine learning concepts.

In the first part, this research investigates the prediction of the surgery durations and Current Procedural Terminology (CPT) Codes. Accurate prediction of the surgery duration will improve the utilization of indispensable surgical resources …

Agile Research - Getting Beyond The Buzzword, Trupti Narayan Rane

Engineering Management & Systems Engineering Faculty Publications

"Oh yeah, we're an Agile shop, we gave up Waterfall years ago." - product owners, managers, or could be anyone else. You will seldom have a conversation with a product or software development team member without the agile buzzword thrown at you at the drop of a hat. It would not be an oversell to say that Agile software development has been adopted at a large scale across several big and small organizations. Clearly, Agile is an ideology that is working, which made me explore more on its applicability in research. As someone who has been in the Information Technology …

Blockchain-Based Digital Trust Mechanism: A Use Case Of Cloud Manufacturing Of Lds Syringes For Covid-19 Vaccination, Trupti Rane, Jingwei Huang

Engineering Management & Systems Engineering Faculty Publications

Trust is essential in the digital world. It is a critical task to build digital trust for the ongoing digital engineering transformation. Aiming at developing a blockchain-based digital trust mechanism for Cloud Manufacturing or Manufacturing-as-a-Service (MaaS), in this paper, we use the manufacturing of low dead space (LDS) medical syringes through Cloud Manufacturing as a motivating scenario to develop a basic framework. To meet the need of optimally saving COVID-19 vaccine doses to save more lives, the medical device manufacturing community needs to make a swift move to meet the surged need for LDS syringes. Cloud Manufacturing is a form …

Adapting The Human Factors Analysis And Classification System For Commercial Fishing Vessel Accidents, Peter Zohorsky, Holly Handley, Ronald Boring (Ed.)

Engineering Management & Systems Engineering Faculty Publications

The commercial fishing industry is frequently described as one of the most hazardous occupations in the United States. The objective, to maximize the catch, is routinely challenged by a variety of elements due to the environment, the vessel, the crew, and how they interact with each other. This study developed and evaluated a version of Wiegmann and Shappell’s (2003) Human Factors Analysis and Classification System (HFACS), specifically for commercial fishing industry vessels (HFACS-FV), using data from ten years of fatal fishing vessel accidents. For this study, the accident investigation information was converted into the HFACS-FV format by independent raters and …

A Primer On The Human Readiness Level Scale (Ansi/Hfes 400-2021), Kelly Steelman, Holly Handley, Katie Plant (Ed.), Gesa Praetorius (Ed.)

Engineering Management & Systems Engineering Faculty Publications

"The Human Readiness Level (HRL) Scale is a simple 9-level scale for evaluating, tracking, and communicating the readiness of a technology for safe and effective human use. It is modeled after the well-established Technology Readiness Level (TRL) framework that is used throughout the government and industry to communicate the maturity of a technology and to support decision making about technology acquisition. Here we (1) introduce the ANSI/HFES 400-2021 Standard that defines the HRL scale and (2) provide concrete examples of evaluation activities to support the application of HRLs in the development of automated driving systems."

Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng

Engineering Management & Systems Engineering Faculty Publications

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords …

Theorizing The Initial Response Of Countries In Bringing Covid-19 Pandemic Under Control: The Effect Of Change Readiness Of Countries, M. Mahdi Moeini Gharagozloo, Farinaz Sabz Ali Pour, Chen Chen, Mozhgan Moeini Gharagozloo

Engineering Management & Systems Engineering Faculty Publications

Pandemic crises can bring the biggest and deepest shocks to countries around the world. In the first quarter of 2020, a global pandemic named “COVID-19” spread all over the world and not only took so many lives and created so much fear but also brought a tremendous financial pain as a result of shutting down economies to fight with this unknown contagious virus. This paper examines how countries’ change readiness enables them to bring the spread of an international crisis under control. We propose that higher levels of change readiness would help countries to cope with risks and uncertainties generated …

Acute Coronary Syndrome Prediction: A Data-Driven Machine Learning Modeling Approach In Emergency Care, Joshua Oluwatobiloba Emakhu

Wayne State University Dissertations

Healthcare facilities are faced with significant challenges all year round, with patients presenting to the emergency department (ED) with different health issues. Of these challenges, heart disease seems to be an outlier. With heart disease being the primary cause of mortality and morbidity in both developed and developing countries, clinical concerns for acute coronary syndrome (ACS) are one of emergency medicine’s most common patient encounters. Of the three sub-categories of ACS, non-ST-segment elevation myocardial infarction (NSTEMI) has a long-term impact on the well-being of patients if left untreated. Previous efforts in hospital management have applied machine learning algorithms in differentiating …

Learning And Decision Making In Social Media Networks, Zhecheng Qiang

Electronic Theses and Dissertations, 2020-2023

Social media is a virtual community where users share news, ideas, interests, and information. Learning the information diffusion dynamics and making decisions correspondingly, e.g., selecting the seed nodes to maximize the influence, have been widely applied to the areas of viral marketing and cyber security. In this dissertation, we study the problem of learning diffusion process, i.e., infection prediction, in social media networks utilizing both feature-based machine learning methods and mathematical model-based methods. For feature-based machine learning methods, the neighborhood information is treated as an important feature together with user profile and content similarity features. For model-based methods, two distinctive …