Open Access. Powered by Scholars. Published by Universities.®
Operations Research, Systems Engineering and Industrial Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- China Simulation Federation (3880)
- Singapore Management University (407)
- Old Dominion University (115)
- Air Force Institute of Technology (97)
- Missouri University of Science and Technology (87)
-
- University of Dar es Salaam (29)
- University of Nevada, Las Vegas (28)
- University of Arkansas, Fayetteville (14)
- Wayne State University (7)
- Embry-Riddle Aeronautical University (6)
- Kennesaw State University (5)
- University of New Haven (5)
- Clemson University (4)
- Loyola University Chicago (4)
- Purdue University (4)
- University of Malaya (4)
- University of South Florida (4)
- University of Texas at El Paso (4)
- California State University, San Bernardino (3)
- City University of New York (CUNY) (3)
- Dartmouth College (3)
- Indiana State University (3)
- New Jersey Institute of Technology (3)
- Prairie View A&M University (3)
- Rochester Institute of Technology (3)
- Southern Methodist University (3)
- Walden University (3)
- Western Michigan University (3)
- Bucknell University (2)
- California Polytechnic State University, San Luis Obispo (2)
- Keyword
-
- Simulation (143)
- Path planning (76)
- Deep learning (57)
- Genetic algorithm (54)
- Reinforcement learning (53)
-
- Optimization (46)
- Virtual reality (45)
- Numerical simulation (44)
- Digital twin (43)
- Multi-objective optimization (42)
- Modeling and simulation (41)
- Deep reinforcement learning (39)
- Modeling (35)
- Particle swarm optimization (35)
- Machine learning (33)
- Scheduling (33)
- Attention mechanism (30)
- Fault diagnosis (29)
- UAV (27)
- Vehicle routing problem (27)
- Neural network (26)
- Simulation model (25)
- Artificial intelligence (24)
- Visualization (24)
- Uncertainty (23)
- Complex network (22)
- System simulation (22)
- System dynamics (21)
- Virtual simulation (20)
- DRL (19)
- Publication Year
- Publication
-
- Journal of System Simulation (3880)
- Research Collection School Of Computing and Information Systems (399)
- Theses and Dissertations (88)
- Electrical and Computer Engineering Faculty Research & Creative Works (54)
- Engineering Management & Systems Engineering Theses & Dissertations (35)
-
- Engineering Management & Systems Engineering Faculty Publications (34)
- Tanzania Journal of Engineering and Technology (TJET) (29)
- Separations Campaign (TRP) (25)
- Faculty Publications (14)
- Engineering Management and Systems Engineering Faculty Research & Creative Works (12)
- Graduate Theses and Dissertations (12)
- Doctoral Dissertations (10)
- VMASC Publications (8)
- Computer Science Faculty Research & Creative Works (6)
- Engineering Technology Faculty Publications (6)
- Masters Theses (6)
- Dissertations and Theses Collection (Open Access) (5)
- Electrical & Computer Engineering Theses & Dissertations (5)
- Computational Modeling & Simulation Engineering Theses & Dissertations (4)
- Computer Science: Faculty Publications and Other Works (4)
- Dissertations (4)
- Graduate Student Government Association Research Conference (4)
- Information Technology & Decision Sciences Faculty Publications (4)
- Master's Theses (4)
- USF Tampa Graduate Theses and Dissertations (4)
- Wayne State University Dissertations (4)
- All-Inclusive List of Electronic Theses and Dissertations (3)
- Applications and Applied Mathematics: An International Journal (AAM) (3)
- Computer Science Technical Reports (3)
- Electronic Theses and Dissertations (3)
- Publication Type
- File Type
Articles 481 - 510 of 4777
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Decision Modeling And Solution Based On Game Adversarial Complex Systems, Jiachen Jiang, Zhengxuan Jia, Zhao Xu, Tingyu Lin, Pengpeng Zhao, Yiming Ou
Decision Modeling And Solution Based On Game Adversarial Complex Systems, Jiachen Jiang, Zhengxuan Jia, Zhao Xu, Tingyu Lin, Pengpeng Zhao, Yiming Ou
Journal of System Simulation
Abstract: In view of the complex situation of the current game which will be large-scale, high-intensity, not omniscient, and strong confrontation, and in response to the lack of flexibility and long iteration cycles in traditional game decision-making, the model of the unmanned complex game system is built according to the background of the unmanned red and blue game. Based on deep reinforcement learning technology, intelligent decision-making algorithms are studied in the background of unmanned red and blue games. With the help of deep neural networks and Bellman's optimal principle, the search of the huge solution space is more efficient, and …
Uav Path Planning In Complex Environments And Its Improved Artificial Rabbits Optimization Algorithm, Anlin Yin, Zhuhong Zhang
Uav Path Planning In Complex Environments And Its Improved Artificial Rabbits Optimization Algorithm, Anlin Yin, Zhuhong Zhang
Journal of System Simulation
Abstract: The work probes into the model design of reliable and effective UAV path planning in complex obstacle environments and its related optimization algorithm. In the model design, a weight coefficient method and cylindrical coordinate system-based single-objective path planning model is developed to solve the UAV's flight path, in which the distance, angle, height and threat cost are taken as performance indices and obstacles in the ground and spatial regions are regarded as constraints. In the algorithm design, the SPM chaotic mapping is used to improve the initial population distribution of the artificial rabbit optimization algorithm in view of the …
Performance Evaluation Technology For Low Earth Orbit Satellite Internet, Xiaofeng Wang, Yi Zhang, Guoxiu Zhang
Performance Evaluation Technology For Low Earth Orbit Satellite Internet, Xiaofeng Wang, Yi Zhang, Guoxiu Zhang
Journal of System Simulation
Abstract: Performance evaluation can provide strong support for new technology verification of low earth orbit(LEO) satellite internet. Aiming at the characteristics of flexible networking and large spacetime scale of satellite internet, a performance evaluation architecture of satellite internet is designed. Aiming at the characteristics of various performance elements, a performance evaluation index system is designed under the premise of multi-dimensional comprehensive consideration. Aiming at the problem of frequent switching of satellite-ground links caused by high-speed movement, an algorithm for satelliteground link switching is proposed, which provides support for subsequent collection work. Aiming at the multi-dimensional problem of indicators, a multi-mode …
Research On Mixed-Model Assembly Line Balancing Optimization Based On Hybrid Genetic Tabu Search Algorithm, Ke Wang, Sijia Guan, Xiyan Yin, Xixing Li, Hongtao Tang
Research On Mixed-Model Assembly Line Balancing Optimization Based On Hybrid Genetic Tabu Search Algorithm, Ke Wang, Sijia Guan, Xiyan Yin, Xixing Li, Hongtao Tang
Journal of System Simulation
Abstract: Aiming at the problem of unbalanced running load caused by idle or blocked workstations in the assembly line of mixed-flow hydraulic pump, a hybrid genetic tabu search algorithm solution and computer simulation verification method are proposed. A hybrid genetic tabu search algorithm with strong local search capability is designed with the optimization objectives of minimizing the production beats of the mixed-flow assembly line, the operational loads distributed among different workstations and the operational load smoothing indices of different products within the same workstation. The algorithm incorporates multi-fragment crossover and fragmentation of feasible solutions through Hamming distance mutation operations. The …
Research And Implementation Of Digital Twin System For Mine Drainage Monitoring, Qinghui Wu, Yaqing Bao, Zhongxin Zhao, Xu Huang, Yuchen Wei
Research And Implementation Of Digital Twin System For Mine Drainage Monitoring, Qinghui Wu, Yaqing Bao, Zhongxin Zhao, Xu Huang, Yuchen Wei
Journal of System Simulation
Abstract: The conventional mine drainage monitoring system faces problems such as poor visualization, insufficient linkage, and monotonous real-time monitoring methods for mine drainage in dynamic environments. Combining digital twin technology, a digital twin system for mine drainage monitoring has been developed. Through the construction of digital space, virtual real interaction layer structure framework, and three-dimensional visualization system data architecture, combined with fluid mechanics, using Unity3D development engine and five dimensional model ideas, a three-dimensional visualization system architecture for mine drainage is constructed, achieving various application functions such as real-time monitoring, fault warning, and virtual real mixed control. The feasibility of …
Research On Path Planning Method For Autonomous Underwater Vehicles Based On Improved Informed Rrt, Bensheng Qi, Yan Li, Hongxia Miao, Jialin Chen, Chenglin Li
Research On Path Planning Method For Autonomous Underwater Vehicles Based On Improved Informed Rrt, Bensheng Qi, Yan Li, Hongxia Miao, Jialin Chen, Chenglin Li
Journal of System Simulation
Abstract: In response to the autonomous underwater vehicle (AUV) path planning problem in complex underwater environments, an improved path planning algorithm based on Informed rapidly-exploring random trees (RRT) is proposed in this study. A target-biased sampling strategy and a target-biased extension strategy are employed to address the issue of lack of goal orientation in the sampling process, ensuring that target nodes become sampling points during random sampling. During path points extension, non-target sampling points are guided in the direction of the target point, thereby enhancing the algorithm's ability to search for the target during random sampling and extension processes. A …
Path Planning Of Mobile Robot Based On The Integration Of Multi-Scale A* And Optimized Dwa Algorithm, Jianmin Xu, Lei Song, Dongdong Deng, Yaoruo Chen, Wei Yang
Path Planning Of Mobile Robot Based On The Integration Of Multi-Scale A* And Optimized Dwa Algorithm, Jianmin Xu, Lei Song, Dongdong Deng, Yaoruo Chen, Wei Yang
Journal of System Simulation
Abstract: In order to solve the problems of sharply increasing computational and time costs, as well as poor flexibility of the traditional A* algorithm and dynamic window approach (DWA) in the face of largescale complex environmental path planning, a fusion algorithm based on the A* algorithm of the multiscale map approach(MMA) and the improved DWA algorithm is proposed. A multi-scale map set is established and an obstacle proportion factor is added to the heuristic function of the A* algorithm. The A* algorithm is used to calculate the optimal path on the coarse-scale map, and the optimal path is mapped onto …
Cooperative Control Method Of Mixed Traffic At Signalized Intersection, Qiushi Huang, Yanyang Wang, Changliang Wu, Junfu Huang, Shenggen Zhang, Haoxuan Luo
Cooperative Control Method Of Mixed Traffic At Signalized Intersection, Qiushi Huang, Yanyang Wang, Changliang Wu, Junfu Huang, Shenggen Zhang, Haoxuan Luo
Journal of System Simulation
Abstract: A hierarchical decoupling cooperative control method for signal light mixed traffic platoon is designed with the goal of improving the traffic environment at signalized intersections. In the research of upper layer signal control, a calculation model for vehicle delay time at intersections is selected, with the goal of minimizing the average delay time of vehicles. A genetic algorithm based upper layer control strategy for intersection signal lights is proposed and verified; in the research of lower layer mixed platoon control, a "1+N" form is used to establish a dynamic model of the mixed platoon. A vehicle energy consumption model …
Driverless Vehicles Distribution Problem In Communities In Cooperation Of Storage Points, Xiaolong Diao
Driverless Vehicles Distribution Problem In Communities In Cooperation Of Storage Points, Xiaolong Diao
Journal of System Simulation
Abstract: With the development of smart communities, the distribution of driverless vehicles in communities has become a focus of government, operators and researchers. The joint cooperation of storage points in communities is designed to balance the the distribution of each storage point and avoid the high input cost of driverless vehicles, which means that driverless vehicles can travel between different storage points. The driverless vehicle distribution problem proposed in this paper includes the unloading subproblem and the driverless vehicle scheduling subproblem. For the unloading subproblem, the unloading scheme of vehicles at storage points is optimized with the aim of minimizing …
Performance Evaluation Of Free Space Optical Communication In Dar Es Salaam: Impact Of Scintillation And Modulation Schemes, Mustafa H. Mohsini
Performance Evaluation Of Free Space Optical Communication In Dar Es Salaam: Impact Of Scintillation And Modulation Schemes, Mustafa H. Mohsini
Tanzania Journal of Engineering and Technology (TJET)
Free space optical communication (FSO) holds significant relevance in the modern communication system as it offers high and unlimited data rates, enhanced security, rapid deployment, and low cost for installation. However, the performance of FSO transmission is greatly affected by harsh atmospheric conditions such as wind, temperature, and humidity, which induce scintillation. With the rapid growth of internet users and Dar es Salaam being a business city in Tanzania, higher and unlimited bandwidth for communication is highly demanded. This study primarily aims to evaluate the performance of FSO transmission in Dar es Salaam, Tanzania, by investigating the impact of atmospheric …
Improved Minimum Variance Channel Estimation Techniques For Ofdm Systems, Kwame S. Ibwe
Improved Minimum Variance Channel Estimation Techniques For Ofdm Systems, Kwame S. Ibwe
Tanzania Journal of Engineering and Technology (TJET)
Orthogonal frequency division multiplexing (OFDM) systems face challenges in channel estimation due to noise, variability, and the doubly dispersive nature of wireless channels, which degrade performance. To address these challenges, a multichannel minimum variance double dispersive channel estimator is proposed. The method employs a hybrid approach that combines subspace and minimum variance techniques, optimizing the filter bank output power under a signal-to-noise ratio (SNR) constraint. This design preserves the desired signal while effectively suppressing disturbances, achieving robust performance with reduced computational complexity compared to existing methods. Simulation results demonstrate that the proposed estimator outperforms subspace and asymptotic methods in terms …
Improving System-Level Outcomes Via Artificial Intelligence Decision Support In Kidney Utilization, Casey I. Canfield, Cihan H. Dagli, Daniel Burton Shank, Krista Lentine, Mark Schnitzler, Henry Randall, V. Sriram Siddhardh Nadendla, Brendon Cummiskey
Improving System-Level Outcomes Via Artificial Intelligence Decision Support In Kidney Utilization, Casey I. Canfield, Cihan H. Dagli, Daniel Burton Shank, Krista Lentine, Mark Schnitzler, Henry Randall, V. Sriram Siddhardh Nadendla, Brendon Cummiskey
Engineering Management and Systems Engineering Faculty Research & Creative Works
Transplantation provides patients suffering from end-stage kidney disease a better quality of life and long-term survival. However, over 20% of deceased donor kidneys are not utilized and never transplanted. While this is sometimes medically appropriate, this also reflects missed opportunities. We are designing Artificial Intelligence decision support for the kidney offer process to support both demand at the transplant center and supply at the organ procurement organization. This includes (1) developing deep learning models, (2) evaluating the effect of explainable interfaces, (3) improving fairness in the model output, (4) identifying factors that influence adoption decisions, and (5) conducting a randomized …
Integrating Data Management Plans Into The Unified Architecture Framework Standards Views, Cansu Yalim, Holly A. H. Handley
Integrating Data Management Plans Into The Unified Architecture Framework Standards Views, Cansu Yalim, Holly A. H. Handley
Engineering Management & Systems Engineering Faculty Publications
System Architecting translates an operational concept into a model of the system to be realized. There is a need for a Data Management Plan (DMP) to be included in the overall system engineering process with the advent of Digital Engineering. Data longevity, accessibility, and integrity can all be improved throughout the system's lifecycle by a well-defined DMP. System engineers use an architecture framework to arrange the system data into several sets of viewpoints. Incorporating a DMP at this point specifies the procedures for gathering, storing, retrieving, and maintaining data to ensure that all interested parties have access to current, correct …
Optimal Control Of Queueing Systems With Error-Prone Servers, Junqi Hu, Sigrún Andradóttir, Hayriye Ayhan
Optimal Control Of Queueing Systems With Error-Prone Servers, Junqi Hu, Sigrún Andradóttir, Hayriye Ayhan
Information Technology & Decision Sciences Faculty Publications
Consider a Markovian tandem line with finite intermediate buffers and an equal number of stations and servers. Servers are flexible but noncollaborative, so that a job can be processed by at most one server at any time. When a job is being processed, it can be damaged and wasted depending on the proficiency of the server. We identify the dynamic server assignment policy that maximizes the long-run average throughput of the system with two stations and two servers. We find that the optimal policy is either a single or a double threshold policy on the number of jobs in the …
Are We Ready For Synchronous Conceptual Modeling In Augmented Reality? A Usability Study On Causal Maps With Hololens 2, Anish Shrestha, Philippe J. Giabbanelli
Are We Ready For Synchronous Conceptual Modeling In Augmented Reality? A Usability Study On Causal Maps With Hololens 2, Anish Shrestha, Philippe J. Giabbanelli
VMASC Publications
(1) Background: Participatory modeling requires combining individual views to create a shared conceptual model. While remote collaboration tools have enabled synchronous online modeling, they are limited to desktop settings. Augmented reality (AR) offers a new approach by potentially providing the sense of presence found in physical collaboration, which may better support participants in achieving the sense of presence found in physical locations, thus supporting them in negotiating meaning and building a shared model. (2) Methods: Building on prior works that developed technology, we performed a usability study with pairs of modelers to examine their ability at performing key conceptual modeling …
Zero Trust Architecture As A Risk Countermeasure In Small-Medium Enterprises And Advanced Technology Systems, Ahmed M. Abdelmagid, Rafael Diaz
Zero Trust Architecture As A Risk Countermeasure In Small-Medium Enterprises And Advanced Technology Systems, Ahmed M. Abdelmagid, Rafael Diaz
Engineering Management & Systems Engineering Faculty Publications
The growing sophistication of cyberattacks exposes small- and medium-sized businesses (SMBs) to a widening range of security risks. As these threats evolve in complexity, the need for advanced security measures becomes increasingly pressing. This necessitates a proactive approach to defending against potential cyber intrusions. Emerging technologies, such as blockchain, artificial intelligence, and Zero Trust security framework, offer crucial tools for strengthening the digital infrastructure of SMBs. The Zero Trust architecture (ZTA) holds significant promise as a critical strategy for protecting SMBs. While existing literature explores the implementation of ZTA in various business settings, discussions specifically addressing the financial, human resource, …
Age Of Information-Based Optimal Scheduling With Energy Cost Trade-Off For Smart Warehouse: A Deep Reinforcement Learning-Based Approach, Sandip Roy, Abhishek Bisht, Ashok Kumar Das, Sachin Shetty
Age Of Information-Based Optimal Scheduling With Energy Cost Trade-Off For Smart Warehouse: A Deep Reinforcement Learning-Based Approach, Sandip Roy, Abhishek Bisht, Ashok Kumar Das, Sachin Shetty
VMASC Publications
Recent advances in the integration of high-speed mobile networks and real-time IoT devices have facilitated in building of smart warehouses, where a set of beacons and Internet of Things (IoT) devices (or source nodes) can monitor the status of various physical processes in a time-critical way. In real-time status monitoring systems, like smart warehouses, quantifying the freshness of the Internet of Things (IoT) data based on the age of information (AoI) metrics becomes quite crucial. As source nodes are battery-constrained, a balanced trade-off between AoI minimization and preservation of source node battery energy is essential. In this paper, in a …
Physics-Informed Deep Learning With Kalman Filter Mixture For Traffic State Prediction, Niharika Deshpande, Hyoshin (John) Park
Physics-Informed Deep Learning With Kalman Filter Mixture For Traffic State Prediction, Niharika Deshpande, Hyoshin (John) Park
Engineering Management & Systems Engineering Faculty Publications
Accurate traffic forecasting is crucial for understanding and managing congestion for efficient transportation planning. However, conventional approaches often neglect epistemic uncertainty, which arises from incomplete knowledge across different spatiotemporal scales. This study addresses this challenge by introducing a novel methodology to establish dynamic spatiotemporal correlations that captures the unobserved heterogeneity in travel time through distinct peaks in probability density functions, guided by physics-based principles. We propose an innovative approach to modifying both prediction and correction steps of the Kalman Filter (KF) algorithm by leveraging established spatiotemporal correlations. Central to our approach is the development of a novel deep learning model …
A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu
A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu
Engineering Technology Faculty Publications
The global energy sector is undergoing a significant transformation driven by decarbonization and digitalization, leading to the emergence of Distributed Ledger Technology (DLT) — particularly blockchain — as a promising tool for enhancing transparency, security, and efficiency in modern power systems. This study aims to provide a comprehensive academic and industrial survey of blockchain applications in the energy sector and develop a robust decision-making framework to identify and prioritize the most promising real-world use cases based on multidisciplinary criteria. A three-stage methodology was adopted: (i) a literature and market review encompassing over 300 academic publications and commercial blockchain initiatives in …
5g-Enabled Iot Gateway For Educational Purposes, Murat Kuzlu
5g-Enabled Iot Gateway For Educational Purposes, Murat Kuzlu
Engineering Technology Faculty Publications
The project aims to develop and implement a 5G-IoT gateway for efficient management and interconnection of IoT devices through advanced sensing and communication technologies. Sensing technologies encompass modern approaches for detecting and measuring physical properties with high accuracy across manufacturing, smart grids, healthcare, smart cities, and other domains. Communication technologies represent the latest developments in high-speed data transmission, offering enhanced reliability and network capacity. This 5G-IoT gateway functions as an educational platform, providing students and educators with hands-on experience in emerging technologies. The system creates opportunities for practical learning and research in telecommunication technologies by enabling direct engagement with 5G …
Leveraging Transformer-Based Ocr Model With Generative Data Augmentation For Engineering Document Recognition, Wael Khallouli, Mohammad Shahab Uddin, Andres Sousa-Poza, Jiang Li, Samuel Kovacic
Leveraging Transformer-Based Ocr Model With Generative Data Augmentation For Engineering Document Recognition, Wael Khallouli, Mohammad Shahab Uddin, Andres Sousa-Poza, Jiang Li, Samuel Kovacic
Engineering Management & Systems Engineering Faculty Publications
The long-standing practice of document-based engineering has resulted in the accumulation of a large number of engineering documents across various industries. Engineering documents, such as 2D drawings, continue to play a significant role in exchanging information and sharing knowledge across multiple engineering processes. However, these documents are often stored in non-digitized formats, such as paper and portable document format (PDF) files, making automation difficult. As digital engineering transforms processes in many industries, digitizing engineering documents presents a crucial challenge that requires advanced methods. This research addresses the problem of automatically extracting textual content from non-digitized legacy engineering documents. We introduced …
Quantifying The Transfer Effectiveness Of An Artificial Intelligence-Based Simulator Pre-Training Program For Student Pilots, Ryan Guthridge
Quantifying The Transfer Effectiveness Of An Artificial Intelligence-Based Simulator Pre-Training Program For Student Pilots, Ryan Guthridge
Journal of Aviation/Aerospace Education & Research
Since the airline pilot shortage was initially studied in 2016, the pilot hiring model has been significantly impacted, with airlines hiring qualified pilots at unprecedented rates. The COVID-19 pandemic has slowed this hiring rate, however it is expected that airline hiring will soon increase to a rate higher than initially expected (Bureau of Transportation Statistics, 2022). With this dynamic, certified flight instructors are often the most qualified recruits for airlines, due to the number of hours and experience they have gained in the flight training organization. In turn, certified flight instructors are in short supply for flight training organizations worldwide. …
Sampling Balanced High-Quality Data To Train An Automatic Mesh Generator, Jie Pan, Jingwei Huang, Gengdong Cheng, Yong Zeng
Sampling Balanced High-Quality Data To Train An Automatic Mesh Generator, Jie Pan, Jingwei Huang, Gengdong Cheng, Yong Zeng
Engineering Management & Systems Engineering Faculty Publications
In real-world scenarios, high-quality data are often scarce and imbalanced, yet it is essential for the optimal performance of data-driven algorithmic models. Data synthesis methods are commonly used to address this issue; however, they typically rely heavily on the original dataset, which limits their ability to significantly improve performance. This article presents a quality function-based method for directly generating high-quality data and applies it to a mesh generation algorithm to demonstrate its efficiency and effectiveness. The proposed approach samples input-output pairs of the algorithm based on their feature spaces, selects high-quality samples using a defined quality function that evaluates the …
Leveraging Synthetic Data For Efficient Training Of Ai Models For Real-World Object Detection, Reinaldo A. Moraga
Leveraging Synthetic Data For Efficient Training Of Ai Models For Real-World Object Detection, Reinaldo A. Moraga
Graduate Research Theses & Dissertations
Modern computer vision (CV) systems largely depend on real-world data for training, which is costly in terms of time, materials, and resources. As industries push toward automation and Artificial Intelligence (AI) -driven solutions, the need for enabling more efficient model training is growing. The primary aim of this work is to explore a framework tailored for industrial applications that uses synthetic images generated from 3D models to train a CV model capable of real-world object detection. This approach seeks to reduce the time, cost, and resources typically required for training AI models with real-world data. This work presents a method …
Bi-Objective Dynamic Tugboat Scheduling With Speed Optimization Under Stochastic And Time-Varying Service Demands, Xiaoyang Wei, Hoong Chuin Lau, Zhe Xiao, Xiuju Fu, Xiaocai Zhang, Zheng Qin
Bi-Objective Dynamic Tugboat Scheduling With Speed Optimization Under Stochastic And Time-Varying Service Demands, Xiaoyang Wei, Hoong Chuin Lau, Zhe Xiao, Xiuju Fu, Xiaocai Zhang, Zheng Qin
Research Collection School Of Computing and Information Systems
With the growing emphasis on green shipping to reduce the environmental impact of maritime transportation, optimizing fuel consumption with maintaining high service quality has become critical in port operations. Ports are essential nodes in global supply chains, where tugboats play a pivotal role in the safe and efficient maneuvering of ships within constrained environments. However, existing literature lacks approaches that address tugboat scheduling under realistic operational conditions. To fill the research gap, this is the first work to propose the bi-objective dynamic tugboat scheduling problem that optimizes speed under stochastic and time-varying demands, aiming to minimize fuel consumption and manage …
Digital Twin And Cybersecurity In Additive Manufacturing, Lidong Wang
Digital Twin And Cybersecurity In Additive Manufacturing, Lidong Wang
Journal of Cybersecurity Education, Research and Practice
Additive manufacturing (AM) has been applied to automotive, aerospace, medical sectors, etc., but there are still challenges such as parts’ porosity, cracks, surface roughness, intrinsic anisotropy, and residual stress because of the high level of thermal gradient. It is significant to conduct the modeling and simulation of the AM process and achieve quality products. Digital Twin (DT) can help AM with forecasting defects/errors through simulation and real-time process monitoring. DT is a concept of Industry 4.0, and its digital structure reflects the real-time behaviors of a cyber-physical or physical system. This paper introduces the progress of DT applications in AM, …
Simulation Of Cascade Failure In Urban Rail Transit Hypernetworks Based On Hypergraph Theory, Zijin Han, Mingjun Qian, Xixian Wang, Kaiyue Zhang
Simulation Of Cascade Failure In Urban Rail Transit Hypernetworks Based On Hypergraph Theory, Zijin Han, Mingjun Qian, Xixian Wang, Kaiyue Zhang
Journal of System Simulation
Abstract: In order to enhance the resilience of urban rail transit networks to ensure stable operations and passenger safety in the face of emergencies, hypergraph theory is introduced to construct a hypergraph based urban rail transit hypernetwork model, and a nonlinear load-capacity cascading failure model based on passenger flow weighting is established. In response to the passenger evacuation process at actual transportation network stations, a load redistribution mechanism is proposed, taking into consideration both the network level and the importance of passenger flow. To address scenarios where stations in actual traffic networks can still accommodate loads during shutdowns, a node …
A Fast Federated Learning-Based Crypto-Aggregation Scheme And Its Simulation Analysis, Boshen Lü, Xiao Song
A Fast Federated Learning-Based Crypto-Aggregation Scheme And Its Simulation Analysis, Boshen Lü, Xiao Song
Journal of System Simulation
Abstract: To solve the problem of increased computation and communication costs caused by using homomorphic encryption (HE) to protect all gradients in traditional cryptographic aggregation (cryptoaggregation) schemes, a fast crypto-aggregation scheme called RandomCrypt was proposed. RandomCrypt performed clipping and quantization to fix the range of gradient values and then added two types of noise on the gradient for encryption and differential privacy (DP) protection. It conducted HE on noise keys to revise the precision loss caused by DP protection. RandomCrypt was implemented based on a FATE framework, and a hacking simulation experiment was conducted. The results show that the proposed …
Critical Node Identification Method For Unmanned Aerial Vehicle Cluster Considering Localized Features, Chenglong Shi, Xiang Hua, Dong Wang, Jinjin Zhang, Tianqi Jiang, Yuanzhang Dang
Critical Node Identification Method For Unmanned Aerial Vehicle Cluster Considering Localized Features, Chenglong Shi, Xiang Hua, Dong Wang, Jinjin Zhang, Tianqi Jiang, Yuanzhang Dang
Journal of System Simulation
Abstract: Aiming at the problem that the UAV cluster critical node identification methods focus on the global network and ignore the correlation between nodes and their local features, a critical nodes identification method for unmanned aerial vehicle cluster considering local features is proposed. An unmanned aerial vehicle cluster network model is constructed based on complex network theory. The Laplacian energy is introduced to evaluate the importance of node within two hops, and information entropy is combined to evaluate the importance of node in a specific motif to comprehensive identify the critical nodes. Simulation results demonstrate that this method identifies critical …
Optimization Of Urban Agglomeration Transportation Network Evacuation Paths, Bowei He, Chengbing Li, Shida Nie, Jialin Wang
Optimization Of Urban Agglomeration Transportation Network Evacuation Paths, Bowei He, Chengbing Li, Shida Nie, Jialin Wang
Journal of System Simulation
Abstract: Given the complexity of the internal transportation network structure within urban agglomerations and the presence of numerous alternative routes, this paper proposes an enhanced ant colony algorithm to address the evacuation path problem of urban agglomeration transportation networks. A comprehensive urban agglomeration transportation network model is constructed, in which the issue of virtual transfer edges within the urban scope is considered and a weighting function is constructed taking into account the travelling time cost and the transferring time cost. Optimizations are applied to the ant colony algorithm, constructing an adaptive adjustment of state transitions and an information pheromone update …