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Articles 1741 - 1770 of 13938
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Intelligent Airport Crowd Management Technology Based On Digital Twin, Jinghui Zhong, Yutian Lin, Wenqiang Li, Wentong Cai
Intelligent Airport Crowd Management Technology Based On Digital Twin, Jinghui Zhong, Yutian Lin, Wenqiang Li, Wentong Cai
Journal of System Simulation
Abstract: Given the need for intelligent emergency control and management of airport crowds, a smart control scheme for airport crowds based on digital twin is proposed. The scheme constructs an integrated crowd control system framework with four dimensions, including digital layer, modeling layer, functional layer, and application layer. It discusses and demonstrates the application effect of five important application modules. By using a data-driven crowd simulation model and intelligent optimization algorithm, the proposed scheme realizes the dynamic prediction and control optimization of the airport crowd status. The scheme can effectively improve the efficiency and intelligence level of airport crowd control …
Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang
Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang
Journal of System Simulation
Abstract: A mathematical model of emergency material scheduling after earthquakes is built. The model evaluates the emergency degree of each disaster area based on the disaster situation and designs a method to split the demand of the disaster area, improving the efficiency of vehicle utilization. To solve the model, this paper proposes a discrete shuffled frog leaping algorithm with multi-resource learning. The multiple information sources introduced by the proposed algorithm can expand the search direction and reduce the assimilation speed of the population in the algorithm. Second, the worst individual in each subgroup can learn the effective information in the …
Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit, Yanbo Zhao, Yuanli Cai, Huaizhong Hu
Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit, Yanbo Zhao, Yuanli Cai, Huaizhong Hu
Journal of System Simulation
Abstract: Due to factors such as simplified assumptions or equipment characteristic deviation, modeling errors are inevitable in the mechanism modeling of thermal power units. To deal with the problem, this paper proposes a novel model refinement method based on recursive subspace for the digital twin of thermal power units. Firstly, the digital twin models are built based on mechanism analysis and combined with small sample data of typical conditions, ensuring interpretability and generalization performance. Secondly, based on the recursive subspace identification method, the refinement model is built and updated online in real time to compensate for the modeling error, improving …
Heterogeneous Multi-Ant Colony Algorithm Combining Competitive Interaction Strategy And Eliminatingreconstructing Mechanism, Chen Feng, Xiaoming You, Sheng Liu
Heterogeneous Multi-Ant Colony Algorithm Combining Competitive Interaction Strategy And Eliminatingreconstructing Mechanism, Chen Feng, Xiaoming You, Sheng Liu
Journal of System Simulation
Abstract: The traditional ant colony algorithm has many problems in convergence and diversity when solving the traveling salesman problem (TSP). Therefore, this paper proposes a heterogeneous multi-ant colony algorithm that combines the competitive interaction strategy and the eliminating-reconstructing mechanism (CEACO) to overcome these shortcomings. Firstly, the algorithm uses a competitive interaction strategy, which adjusts the interaction period adaptively according to the Hamming distance of different groups in different periods. Competition coefficients are adopted to differentiate matching interaction objects for interaction. The matched objects interact with each other through the optimal solution and pheromone matrix. This mechanism achieves a balance between …
Result Validation Method Of Simulation Models Based On Piecewise Feature Extraction, Yucheng Luo, Ming'en Zhang, Fei Liu, Yingbo Lu, Feng Ye
Result Validation Method Of Simulation Models Based On Piecewise Feature Extraction, Yucheng Luo, Ming'en Zhang, Fei Liu, Yingbo Lu, Feng Ye
Journal of System Simulation
Abstract: Verification, validation, and accreditation (VV&A) is a key means to ensure the credibility of simulation models, and model validation is the core link. In view of the unavailability of reference data, various sources of reference data, and strong subjectivity of expert validation in the result validation of the missile flight simulation model, a result validation method for the missile flight simulation model based on piecewise feature extraction of time series was proposed. Specifically, a comprehensive piecewise linear method for time series was first proposed. The method consisted of a linear piecewise algorithm based on the second-order derivative for extracting …
Obstacle Avoidance Motion In Mobile Robotics, Yunchao Tang, Shaojun Qi, Lixue Zhu, Xianrong Zhuo, Yunqi Zhang, Fan Meng
Obstacle Avoidance Motion In Mobile Robotics, Yunchao Tang, Shaojun Qi, Lixue Zhu, Xianrong Zhuo, Yunqi Zhang, Fan Meng
Journal of System Simulation
Abstract: The advancement of artificial intelligence technology has significantly enhanced the utilization of mobile robots in various fields such as industry, aerospace, and agriculture. The autonomous obstacle avoidance capability of these robots is crucial to the safety and efficiency of their operations in diverse settings. Path planning, a key technology in obstacle avoidance, plays an essential role in the overall performance of these systems. This paper presents a comprehensive review of path planning technology for mobile robots, categorizing the algorithms into global planning and local obstacle avoidance according to their operational requirements. Specific focus is given to the global planning …
Multi-Uav Collaborative Trajectory Planning Algorithm For Urban Ultra-Low-Altitude Air Transportation Scenario, Jie Cheng, Yuan Zheng, Chenglong Li, Bo Jiang
Multi-Uav Collaborative Trajectory Planning Algorithm For Urban Ultra-Low-Altitude Air Transportation Scenario, Jie Cheng, Yuan Zheng, Chenglong Li, Bo Jiang
Journal of System Simulation
Abstract: The rapid development of the drone industry has promoted the opening of low-altitude, forming a wave of ultra-low-altitude air transportation in cities sweeping over the world. However, the existing trajectory planning algorithms do not consider the division method and operating rules of the ultra-low-altitude airspace. They are not suitable for the collaborative trajectory planning of multiple UAVs in the urban ultra-low-altitude air transportation scenario, which may restrict the development of the ultra-low-altitude air transportation industry. This paper explores a multi-UAV collaborative trajectory planning method for urban ultra-low-altitude air transportation scenario based on the airspace flight altitude layer architecture. Specifically, …
Multi-View Depth Estimation Based On Adaptive Space Feature Enhancement, Dong Wei, Huan Liu, Xiaohan Zhang, Changkai Li, Tianyi Sun, Ziyou Zhang
Multi-View Depth Estimation Based On Adaptive Space Feature Enhancement, Dong Wei, Huan Liu, Xiaohan Zhang, Changkai Li, Tianyi Sun, Ziyou Zhang
Journal of System Simulation
Abstract: A multi-view depth estimation algorithm based on adaptive space feature enhancement (ASFE) is presented to improve the multi-view depth estimation accuracy. A multi-scale feature extraction module composed of an improved feature pyramid network (FPN) and ASFE is designed. This module obtains multi-scale feature maps with global context-aware information and coordinate information. The residual learning network is used to optimize the depth map to prevent the problem of blurred reconstructed edges in multiple convolution operations. The proposed algorithm constructs a focal loss function through the idea of classification to enhance the prediction ability of the network model. The experimental results …
Visual Monitoring System Of Digital Twin Workshop For Process Manufacturing, Yanchao Yin, Jiasheng Feng, Bin Yi, Wang Li, Qingwen Yin
Visual Monitoring System Of Digital Twin Workshop For Process Manufacturing, Yanchao Yin, Jiasheng Feng, Bin Yi, Wang Li, Qingwen Yin
Journal of System Simulation
Abstract: To solve the problem of poor real-time and accuracy of process manufacturing monitoring, this paper proposes a visual monitoring system architecture of digital twin workshop based on production factor data, production process, and multi-process equipment entity object amid the rapid development of digital twin technology and increasingly close integration with the manufacturing industry. Twin modeling is conducted on multi-process coupling production line entity objects from multiple dimensions such as element, state, and operation logic. Based on key technologies of data collection and transmission of OPC UA (OLE for process control unified archiecture) unified architecture and real-time drive of the …
Reentrant Hybrid Flow Shop Scheduling Problem Based On Moma, Hongbin Qin, Chenxiao Li, Hongtao Tang, Feng Zhang
Reentrant Hybrid Flow Shop Scheduling Problem Based On Moma, Hongbin Qin, Chenxiao Li, Hongtao Tang, Feng Zhang
Journal of System Simulation
Abstract: For the characteristics of multi-variety, large-scale and mixed-flow production of reentrant manufacturing systems, the reentrant hybrid flow shop scheduling problem with batch processors (BPRHFSP) is constructed, and an improved multi-objective mayfly algorithm (MOMA) is proposed for BPRHFSP. Firstly, decoding rules for single-piece processing stage and batch-processing stage are proposed. Then, a reverse learning initialization strategy based on logistic chaotic mapping is designed to improve the quality of the initial solution of the algorithm, also an improved mayfly mating strategy is designed to improve the local search ability of MOMA. Finally, a VND-based mayfly movement strategy is designed based on …
Research On Campus Epidemic Evolution Based On Multi-Scale Modeling And Simulation In Microscopic & Microscopic View, Mingwei Hu, Wenjie Yang
Research On Campus Epidemic Evolution Based On Multi-Scale Modeling And Simulation In Microscopic & Microscopic View, Mingwei Hu, Wenjie Yang
Journal of System Simulation
Abstract: High density of population leads to high possibility of cross-infection. It is necessary to focus on campus epidemic prevention and control. Basing on existing studies in macroscopic or microscopic view, this paper proposed a multi-scale means to analyze a short-term evolution of Corona virus disease 2019 (COVID-19) on campus and estimated the efficiency of prevention strategies. Macroscopic model was based on the susceptible-exposed-infections-recovered(SEIR) model, which exported the time curve of the number of asymptomatic patients and symptomatic patients. Microscopic model combined discrete event simulation modeling and agent-based modeling to simulate the behavior of campus students and the state evolution …
Multi-Model Soft Sensor Modeling Under Help-Training Strategy, Luosuyang He, Weili Xiong
Multi-Model Soft Sensor Modeling Under Help-Training Strategy, Luosuyang He, Weili Xiong
Journal of System Simulation
Abstract: Due to the strong nonlinearity, multi-stage coupling, and the small number of labeled samples in complex industrial processes, it is difficult for traditional global soft sensor models to accurately describe the whole process. Therefore, a multi-model soft sensor modeling method under the helptraining strategy is proposed. This method uses a fuzzy C-means (FMC) clustering algorithm to mine similar samples in the sample set and build several sub-models. By introducing the help-training strategy, a collaborative training framework based on main and auxiliary learners is formed, and a confidence evaluation mechanism is designed to eliminate error samples and expand the modeling …
Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang
Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang
Journal of System Simulation
Abstract: Based on the perfect performance of deep reinforcement learning (DRL) in strategy optimization, this paper proposes a strategy optimization method of action taking the multi-dimension projection action as the main research object. The method combines the simulation experiment method with the DRL method. After analyzing the current situation of strategy optimization research, the deep learning framework is selected according to the research problems, and a DRL multi-dimension projection strategy model based on the asynchronous advantage actor-critic (A3C) algorithm is constructed. Through simulation experiments, the interactive learning between the DRL model and the simulation of "out of the loop" is …
A Simulation Method Based On Multi-Source Sensors For Aircraft Type Identification, Shaozhu Gu, Yuxin Ying, Huajie Zhang, Yiqi Tong
A Simulation Method Based On Multi-Source Sensors For Aircraft Type Identification, Shaozhu Gu, Yuxin Ying, Huajie Zhang, Yiqi Tong
Journal of System Simulation
Abstract: Existing simulation methods for aircraft type identification mainly focus on a single sensor and a single target. They do not consider the joint acquisition of aircraft parameters by various sensor devices such as optoelectronics, radar, and electronic detection in real scenarios, leading to the simple simulation scenarios. This paper proposes a simulation platform based on multi-source sensors. Specifically, the platform includes an infrared image simulator that uses a cycleGAN network to generate infrared images of the aircraft, a flight simulator that adopts the three-degree-of-freedom flight control method to generate the movement trajectory of the aircraft, a radar simulator, that …
Integrated Computer-Aided Design, Experimentation, And Optimization Approach For Perovskites And Petroleum Packaging Processes, Swapana Subbarao Jerpoth
Integrated Computer-Aided Design, Experimentation, And Optimization Approach For Perovskites And Petroleum Packaging Processes, Swapana Subbarao Jerpoth
Theses and Dissertations
According to the World Economic Forum report, the U.S. currently has an energy efficiency of just 30%, thus illustrating the potential scope and need for efficiency enhancement and waste minimization. In the U.S. energy sector, petroleum and solar energy are the two key pillars that have the potential to create research opportunities for transition to a cleaner, greener, and sustainable future. In this research endeavor, the focus is on two pivotal areas: (i) Computer-aided perovskite solar cell synthesis; and (ii) Optimization of flow processes through multiproduct petroleum pipelines. In the area of perovskite synthesis, the emphasis is on the enhancement …
Flexural Behavior Of Pultruded Gfrp–Concrete Composite Beams Strengthened With Gfrp Stiffeners, Muataz I. Ali, Abbas A. Allawi, Ayman El-Zohairy
Flexural Behavior Of Pultruded Gfrp–Concrete Composite Beams Strengthened With Gfrp Stiffeners, Muataz I. Ali, Abbas A. Allawi, Ayman El-Zohairy
Faculty Publications
The utilization and incorporation of glass fiber-reinforced plastics (GFRP) in structural applications and architectural constructions are progressively gaining prominence. Therefore, this paper experimentally and numerically investigates the use of GFRP I-beams in conjunction with concrete slabs to form composite beams. The experimental design incorporated 2600 mm long GFRP I-beams which were connected compositely to concrete slabs with a 500 mm width and 80 mm thickness. The concrete slabs are categorized into two groups: concrete slabs cast using normal strength concrete (NSC), and concrete slabs prepared using high-strength concrete (HSC). Various parameters like the type of concrete (normal and high-strength concrete), …
Low Complexity Doa Estimation Of Multiple Coherent Sources Using A Single Direct Data Snapshot, Ahmed A. Hussain, Nizar Tayem, Abdel-Hamid Soliman
Low Complexity Doa Estimation Of Multiple Coherent Sources Using A Single Direct Data Snapshot, Ahmed A. Hussain, Nizar Tayem, Abdel-Hamid Soliman
Faculty Publications
The direction of arrival (DOA) estimation of multiple radio frequency (RF) coherent signals using conventional algorithms such as Multiple Signal Classification (MUSIC), Estimation of the Signal Parameters via the Rotational Invariance Technique (ESPRIT), and their variants is computationally complex and usually requires a large number of data snapshots for accurate estimation. As the number of antenna elements grows, particularly in massive MIMO systems, the complexity of real-time DOA estimation algorithms significantly rises, placing higher demands on computational power and memory resources. In this paper, we present an efficient approach that operates effectively with just a single snapshot for DOA estimation …
Taiwan’S Semiconductor Strategy: A Developmental State Model For Economic Growth, Christine Vuu
Taiwan’S Semiconductor Strategy: A Developmental State Model For Economic Growth, Christine Vuu
CISLA Senior Integrative Projects
No abstract provided.
Operations Research In Civil And Environmental Engineering, Nicholas Lownes
Operations Research In Civil And Environmental Engineering, Nicholas Lownes
Open Educational Resource
The purpose of this text is introduce fundamental operations research techniques to the civil and/or environmental engineering student, providing a broad background in linear programming, integer programming and network optimization. The material is presented in such a manner so that the student does not need an extensive background in operations research or or linear algebra. Applications include transportation engineering, project management and general civil and environmental engineering applications.
Exploring Clustering Patterns In Msmes And Large Enterprises In Maharashtra: Analyzing Industrial Dynamics Using Cluster Coefficient And Other Economic Indicators, Priyanshu Bist
2024 REYES Proceedings
The paper discusses an attempt to explore and assess the economic clustering in Maharashtra by focusing on the MSMEs (Micro, Small and Medium Enterprises) and large enterprises in six major districts, namely Konkan, Nashik, Pune, Aurangabad, Amravati, and Nagpur. Cluster coefficients, total number of workers, and other economic indicators of units were considered to understand how industries are spread and perform regionally. Our research was a combination of exploratory and descriptive research, ensuring the data to be garnered had already been collected from the reports and records of the governments concerned and of industries. This entails that we have a …
Exploring Service Quality Among Us Hajj Pilgrims In Compliance With Vision 2030 Objectives, Majid Abdulmalik Alshaibi
Exploring Service Quality Among Us Hajj Pilgrims In Compliance With Vision 2030 Objectives, Majid Abdulmalik Alshaibi
Graduate Thesis and Dissertation 2023-2024
Saudi Arabia is progressing with Vision 2030, an ambitious blueprint for economic variation, global connection, and improved quality of life. The Hajj pilgrimage is addressed by the Doyof Al Rahman Program (DARP), one of the vision's programs aiming to enhance the Hajj experience. The Hajj pilgrimage is one of the world's largest annual massive gatherings and it has already received increased attention from researchers combining elements of pilgrimage and tourism. This dissertation aims to explore Hajj service quality and pilgrims' satisfaction. To attain this objective, a narrative and systematic literature review was conducted to develop a framework with standardized …
A Simulation Model Analysis In The Us-Mexico Border, Carlo A. Zorola, Hiram Moya, Aditya Akundi
A Simulation Model Analysis In The Us-Mexico Border, Carlo A. Zorola, Hiram Moya, Aditya Akundi
Manufacturing & Industrial Engineering Faculty Publications
Supply Chain (SC) is the flow of goods or services between supply and demand points. New or innovative strategies in SC have been researched and developed to deal with disruptive events, such as COVID-19, hurricanes, geopolitical, and even climate change. These challenges create supply imbalances, logistical challenges, and policy restrictions for transborder commerce. The DHS has implemented the Free and Secure Trade (FAST) program in both the US-Mexico and US-Canada border. These lanes are dedicated queues for commercial vehicles. In 2022, the government of Nuevo León, México, opened a dedicated lane just for Tesla´s northbound commercial traffic. There has been …
Artificial Intelligence For Enhanced Flotation Monitoring In The Mining Industry: A Convlstm-Based Approach, Ahmed Bendaouia, El Hassan Abdelwahed, Sara Qassimi, Abdelmalek Boussetta, Intissar Benzakour, Oumkeltoum Amar, Oussama Hasidi
Artificial Intelligence For Enhanced Flotation Monitoring In The Mining Industry: A Convlstm-Based Approach, Ahmed Bendaouia, El Hassan Abdelwahed, Sara Qassimi, Abdelmalek Boussetta, Intissar Benzakour, Oumkeltoum Amar, Oussama Hasidi
Manufacturing & Industrial Engineering Faculty Publications
In the mining industry, accurate monitoring of the elemental composition in the flotation froth is crucial for efficient minerals separation. The hybrid deep learning algorithms offer powerful computational intelligence for real-time monitoring of froth quality in flotation processes. This soft sensor tool can provide valuable information for process control, including predictions of the elemental chemical composition. In this study, we propose a novel approach based on a Convolutional Long Short-Term Memory (ConvLSTM) neural network for real-time monitoring of chemical composition grades in flotation froth. The proposed model effectively extracts spatial and temporal patterns from video data, providing a better …
Models Of Information Diffusion And The Role Of Influence, Chathura Jj Don Dimungu Arachchige
Models Of Information Diffusion And The Role Of Influence, Chathura Jj Don Dimungu Arachchige
Graduate Thesis and Dissertation 2023-2024
Information diffusion is significant in fields such as propagation prediction and influence maximization, with applications in viral marketing and rumor control. Despite conceptual differences, existing diffusion models may not represent identical underlying generative structures. A classification of diffusion of information models is developed based on infection requirements and stochasticity. The study involves analyzing seven existing DOI models on directed scale-free networks. The distinctive properties of each model are identified through simulations and analysis of experimental results. Our analysis reveals that similarity in conceptual design does not imply similarity in behavior concerning speed, the final state of nodes and edges, and …
An Algorithm Based On Priority Rules For Solving A Multi-Drone Routing Problem In Hazardous Waste Collection, Youssef Harrath Dr., Jihene Kaabi Dr.
An Algorithm Based On Priority Rules For Solving A Multi-Drone Routing Problem In Hazardous Waste Collection, Youssef Harrath Dr., Jihene Kaabi Dr.
Research & Publications
This research investigates the problem of assigning pre-scheduled trips to multiple drones to collect hazardous waste from different sites in the minimum time. Each drone is subject to essential restrictions: maximum flying capacity and recharge operation. The goal is to assign the trips to the drones so that the waste is collected in the minimum time. This is done if the total flying time is equally distributed among the drones. An algorithm was developed to solve the problem. The algorithm is based on two main ideas: sort the trips according to a given priority rule and assign the current trip …
Fusion Et Validation De Modèles Musculosquelettiques De La Colonne Lombaire Pour La Prévention Et La Réadaptation Des Travailleurs, Christian Larivière, Farshid Ghezelbash, Amir Eskandari, Denis Gagnon, Hakim Mecheri, Navid Arjmand, Aboulfazl Shirazi-Adl
Fusion Et Validation De Modèles Musculosquelettiques De La Colonne Lombaire Pour La Prévention Et La Réadaptation Des Travailleurs, Christian Larivière, Farshid Ghezelbash, Amir Eskandari, Denis Gagnon, Hakim Mecheri, Navid Arjmand, Aboulfazl Shirazi-Adl
Rapports de recherche scientifique
Les charges imposées sur la colonne vertébrale lombaire constituent un facteur de risque important pour les maux de dos. Connaître la distribution de ces forces internes lors d’activités de travail est nécessaire autant en prévention qu’en réadaptation des travailleurs. La modélisation musculosquelettique (MS) de la colonne vertébrale est la seule approche non invasive permettant d’estimer les charges sur les structures internes de la colonne.
Deux modèles ont été développés au Québec, soient un modèle par éléments finis (MEF) guidé par le mouvement et un autre guidé par des mesures électromyographiques (EMG) d’activation musculaire (modèle MEMG). Ces modèles sont donc sensibles …
Developing Machine Learning And Time-Series Analysis Methods With Applications In Diverse Fields, Muhammed Aljifri
Developing Machine Learning And Time-Series Analysis Methods With Applications In Diverse Fields, Muhammed Aljifri
Theses and Dissertations
This dissertation introduces methodologies that combine machine learning models with time-series analysis to tackle data analysis challenges in varied fields. The first study enhances the traditional cumulative sum control charts with machine learning models to leverage their predictive power for better detection of process shifts, applying this advanced control chart to monitor hospital readmission rates. The second project develops multi-layer models for predicting chemical concentrations from ultraviolet-visible spectroscopy data, specifically addressing the challenge of analyzing chemicals with a wide range of concentrations. The third study presents a new method for detecting multiple changepoints in autocorrelated ordinal time series, using the …
Large Retail Logistics Warehouse Execution System, Michael Broughton
Large Retail Logistics Warehouse Execution System, Michael Broughton
Graduate Research Theses & Dissertations
In this study, integrated technical solutions designed for large retail logistics (LRL) material handling equipment (MHE) were integrated with advanced technical industry trends to create a warehouse execution/warehouse control system (WES/WCS) distribution center (DC) model. This model was executed using a distributor profitability framework. The resulting process metrics, financial elements, and forecasted financial drivers within the new model were tested against a standard warehouse management system (WMS) DC model without WES or integrated WCS technical solutions. The hypothesis was that using the WES/WCS DC model in automating store functionality would result in superior cost-effective solutions for the P&L/EBITDA lines of …
Investigating The Influence Of Container Design And A Bulge Reduction Technique In Corrugated Fiberboard Containers Under Static Compression, Jay Singh, Koushik Saha
Investigating The Influence Of Container Design And A Bulge Reduction Technique In Corrugated Fiberboard Containers Under Static Compression, Jay Singh, Koushik Saha
Industrial Technology and Packaging
This study explored the bulge effect in corrugated fiberboard boxes caused by excessive weight, leading to compromised stacking strength and potential product damage. It investigated how container design, specifically the height variations of regular slotted containers (RSCs), affects bulging under compression and its vulnerability to environmental conditions. Testing met ASTM standards, with samples conditioned according to ASTM and TAPPI protocols, revealing that changes in box height influence bulge displacement. Subsequent research examined the impact of top-to-bottom static compression loads on bulging in tape-reinforced RSC designs, evaluating bulge reduction and compression strength across various tape placements and environments. Notably, previous studies …
The Hazard Prediction Problem, Mary E. Helander, Brendan Smith, Sylvia Charchut, Erika Swiatowy, Calvin Nau, Gregory Cavaretta, Timothy Schuler, Adam Schunk, Héctor Ortiz-Peña
The Hazard Prediction Problem, Mary E. Helander, Brendan Smith, Sylvia Charchut, Erika Swiatowy, Calvin Nau, Gregory Cavaretta, Timothy Schuler, Adam Schunk, Héctor Ortiz-Peña
Social Science - All Scholarship
This work formulates the hazard prediction problem while addressing the research question: Can machine learning create a model to automatically recognize patterns that correspond to hazard state conditions during a mission-critical operation? Supervised learning models were trained and tested on data observed from mission simulators, which allowed for safe observation of dynamic system states and undesirable casualty events. The prediction task was formulated as a binary classification problem, producing the probability of being in a hazard state at time t and providing situational awareness of a possible imminent loss. Several modeling architectures were investigated: neural networks, logistic regression, a support …