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Articles 781 - 810 of 4777

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Spatio-Temporal Association Rule Mining Of Traffic Congestion In A Large-Scale Road Network Based On Trajectory Data, Qifan Zhou, Haixu Liu, Zhipeng Dong, Yin Xu Jan 2024

Spatio-Temporal Association Rule Mining Of Traffic Congestion In A Large-Scale Road Network Based On Trajectory Data, Qifan Zhou, Haixu Liu, Zhipeng Dong, Yin Xu

Journal of System Simulation

Abstract: A K neighbor-RElim (KNR) algorithm and a sequential KNbr-RElim (SKNR) algorithm are proposed to mine traffic congestion association rules and congestion propagation spatio-temporal association rules by vehicle trajectory data in a large-scale road network. The KNR algorithm extends the spatial topology constraint based on the RElim algorithm. The KNR can be used to mine the road links prone to congestion from the large-scale trajectory dataset in a large-scale road network and quantify the strength of association for congested road links. The SKNR algorithm expands the time dimension in the form of sliding window and can be applied for mining …

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Modeling And Analysing Of Complex Combat Systems Based On Symbiosis Theory, Xiangrui Tian, Jie Ying, Rui Yao, Xiaodong Wan Jan 2024

Modeling And Analysing Of Complex Combat Systems Based On Symbiosis Theory, Xiangrui Tian, Jie Ying, Rui Yao, Xiaodong Wan

Journal of System Simulation

Abstract: As the combat systems develop towards clustering, coordination, unmanned, and intelligent direction, traditional combat system modeling methods are unable to reflect the complexity and intelligence of the combat systems. By drawing on symbiosis theory, this paper models and analyzes complex combat systems, and decomposes the complex combat system into various subsystems according to combat missions. The combat units, interaction modes, and combat environments in the subsystems are analyzed. The paper builds mathematical models to capture the collaborative interaction relationships between combat units, finally constructing a symbiotic model of complex combat systems. By the symbiosis principles and methods, quantitative analysis …

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Action Recognition Model Of Directed Attention Based On Cosine Similarity, Chen Li, Ming He, Chen Dong, Wei Li Jan 2024

Action Recognition Model Of Directed Attention Based On Cosine Similarity, Chen Li, Ming He, Chen Dong, Wei Li

Journal of System Simulation

Abstract: Aiming at the lack of directionality of traditional dot product attention, this paper proposes a directed attention model (DAM) based on cosine similarity. To effectively represent the direction relationship between the spatial and temporal features of video frames, the paper defines the relationship function in the attention mechanism using the cosine similarity theory, which can remove the absolute value of the relationship between features. To reduce the computational burden of the attention mechanism, the operation is decomposed from two dimensions of time and space. The computational complexity is further optimized by combining linear attention operation. The experiment is divided …

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Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control System, Xiaofei Chang, Jiayue Jiao, Kang Chen, Wenxing Fu, Jie Yan Jan 2024

Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control System, Xiaofei Chang, Jiayue Jiao, Kang Chen, Wenxing Fu, Jie Yan

Journal of System Simulation

Abstract: Hardware-in-the-loop simulation system is a complex distributed simulation system, and its design and integration directly affect the system performance and construction goals. Based on years of experience, this paper first summarizes the design of the overall scheme and analyzes the performance requirements of real-time, compatibility, scalability, and security. Then, the paper describes the overall scheme of a typical hardware-in-the-loop simulation system, including the functional hierarchy, operation mechanism, and structural composition. Finally, it summarizes the contents and steps of the system integration testing, acceptance testing, and credibility evaluation method.

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Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang Jan 2024

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 …

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Combat Effectiveness Evaluation Method Of Homogeneous Cluster Equipment System Based On Rlomag+Eas, Guohui Zhang, Ang Gao, Ya'nan Zhang Jan 2024

Combat Effectiveness Evaluation Method Of Homogeneous Cluster Equipment System Based On Rlomag+Eas, Guohui Zhang, Ang Gao, Ya'nan Zhang

Journal of System Simulation

Abstract: The equipment system is the reflection of the combat system from the perspective of equipment. The research on the combat effectiveness evaluation of the equipment system is of great practical significance for the optimization, construction, and development of the equipment system. Cluster equipment combat system confrontation is characterized by large-scale, highly dynamic and strong confrontation, and it is difficult to directly evaluate combat effectiveness with traditional methods. Aiming at the single task homogeneous cluster equipment system (such as UAV reconnaissance swarm and ground unmanned platform fire assault cluster), this paper regards the confrontation process of equipment system as the …

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Optimization On Cold Chain Distribution Routes Considering Carbon Emissions Based On Improved Ant Colony Algorithm, Huifang Bao, Jie Fang, Jinsi Zhang, Chuansheng Wang Jan 2024

Optimization On Cold Chain Distribution Routes Considering Carbon Emissions Based On Improved Ant Colony Algorithm, Huifang Bao, Jie Fang, Jinsi Zhang, Chuansheng Wang

Journal of System Simulation

Abstract: As the comprehensive distribution cost is not considered comprehensively in the current cold chain distribution route optimization, this paper builds a path optimization model to minimize the comprehensive distribution cost. The model combines with the characteristics of fresh distribution, and comprehensively considers the transportation cost, carbon emission, refrigeration, cargo damage and time window constraints during cold chain transportation. Then, an improved ant colony algorithm is designed to solve this model. At the initial stage, the genetic algorithm is adopted to generate the initial pheromone, and then the ant colony algorithm is applied to conduct the subsequent optimization search. The …

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Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit, Yanbo Zhao, Yuanli Cai, Huaizhong Hu Jan 2024

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 …

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Driving Method Of Virtual Multi-Person Disassembly And Assembly Task For Aeroengine, Qiuwei Zeng, Zhaoyong Hu, Zhile Wang, Ruilin Zhang, Gang Zou Jan 2024

Driving Method Of Virtual Multi-Person Disassembly And Assembly Task For Aeroengine, Qiuwei Zeng, Zhaoyong Hu, Zhile Wang, Ruilin Zhang, Gang Zou

Journal of System Simulation

Abstract: To meet the needs of virtual multi-person collaborative disassembly and assembly system for different disassembly and assembly tasks, this paper proposes a data-driven method with configurable task sequence. Taking an aeroengine prototype as the research object, the paper studies the task elements of multi-person collaborative disassembly and assembly. It parameterizes and expresses the task based on JSON (JavaScript object notation) and drives the task sequence by JSON parametrical files, defining the interactive operation of each task step. The practice shows that this method is applied to the multi-person collaborative disassembly and assembly system, which makes the system configurable and …

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Result Validation Method Of Simulation Models Based On Piecewise Feature Extraction, Yucheng Luo, Ming'en Zhang, Fei Liu, Yingbo Lu, Feng Ye Jan 2024

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 …

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Obstacle Avoidance Motion In Mobile Robotics, Yunchao Tang, Shaojun Qi, Lixue Zhu, Xianrong Zhuo, Yunqi Zhang, Fan Meng Jan 2024

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 …

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Intelligent Airport Crowd Management Technology Based On Digital Twin, Jinghui Zhong, Yutian Lin, Wenqiang Li, Wentong Cai Jan 2024

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 …

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Multi-Uav Collaborative Trajectory Planning Algorithm For Urban Ultra-Low-Altitude Air Transportation Scenario, Jie Cheng, Yuan Zheng, Chenglong Li, Bo Jiang Jan 2024

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, …

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Multi-View Depth Estimation Based On Adaptive Space Feature Enhancement, Dong Wei, Huan Liu, Xiaohan Zhang, Changkai Li, Tianyi Sun, Ziyou Zhang Jan 2024

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 …

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Visual Monitoring System Of Digital Twin Workshop For Process Manufacturing, Yanchao Yin, Jiasheng Feng, Bin Yi, Wang Li, Qingwen Yin Jan 2024

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 …

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Reentrant Hybrid Flow Shop Scheduling Problem Based On Moma, Hongbin Qin, Chenxiao Li, Hongtao Tang, Feng Zhang Jan 2024

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 …

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Research On Campus Epidemic Evolution Based On Multi-Scale Modeling And Simulation In Microscopic & Microscopic View, Mingwei Hu, Wenjie Yang Jan 2024

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 …

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Heterogeneous Multi-Ant Colony Algorithm Combining Competitive Interaction Strategy And Eliminatingreconstructing Mechanism, Chen Feng, Xiaoming You, Sheng Liu Jan 2024

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 …

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Multi-Model Soft Sensor Modeling Under Help-Training Strategy, Luosuyang He, Weili Xiong Jan 2024

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 …

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Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang Jan 2024

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 …

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A Simulation Method Based On Multi-Source Sensors For Aircraft Type Identification, Shaozhu Gu, Yuxin Ying, Huajie Zhang, Yiqi Tong Jan 2024

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 …

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Data Driven Trade-Off Analysis For Cybersecurity, Goskel Kucukkaya, Murat Ozer, Murat Balci, Emrah Ugurlu Jan 2024

Data Driven Trade-Off Analysis For Cybersecurity, Goskel Kucukkaya, Murat Ozer, Murat Balci, Emrah Ugurlu

Engineering Management & Systems Engineering Faculty Publications

Trade-off analysis, a specialization of systems engineering, addresses design criteria like security, cost, performance, and compliance. Monte Carlo simulations are commonly employed to generate impact scenarios for trade-off analysis combined with solution alternatives that accommodate industry-specific considerations and uncertainties. In the cyber domain, this paper proposes a methodology for data-driven trade-off analysis in cybersecurity, leveraging industry reports as primary data sources using confidentiality, integrity, and availability as trade-off analysis objectives. Distribution functions are derived to manage and model uncertainties for various industries. The approach given in this study aims to facilitate informed choices and to enhance cybersecurity decision making and …

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Asem 4.0/5.0 - Evolving The Engineering Management Profession Through Industry 4.0/5.0 Collaborative Networks, T. Steven Cotter, Faisal Mahmud, Ziniya Zahedi Jan 2024

Asem 4.0/5.0 - Evolving The Engineering Management Profession Through Industry 4.0/5.0 Collaborative Networks, T. Steven Cotter, Faisal Mahmud, Ziniya Zahedi

Engineering Management & Systems Engineering Faculty Publications

The American Society for Engineering Management was created and matured under Industry 3.0 automation. The emergence of Industry 4.0 and 5.0 are forcing all organizational sectors to rethink their long-term strategy with respect to emerging horizontal/vertical cyber-physical systems integration. This leaves open the question of the directions in which ASEM should evolve into the 21st century. This paper reports an initial mapping of Industry 4.0 and 5.0 technologies and initiatives as goal-oriented, long-term strategic collaborative networks. The research method began with the Boston Consulting Group nine technologies of Industry 4.0 (2015) and the Industry 5.0 technologies within its human-centric, sustainability, …

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An Algorithm Based On Priority Rules For Solving A Multi-Drone Routing Problem In Hazardous Waste Collection, Youssef Harrath Dr., Jihene Kaabi Dr. Jan 2024

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 …

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The Hazard Prediction Problem, Mary E. Helander, Brendan Smith, Sylvia Charchut, Erika Swiatowy, Calvin Nau, Gregory Cavaretta, Timothy Schuler, Adam Schunk, Héctor Ortiz-Peña Jan 2024

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 …

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Integrative Machine Learning Approaches For Enhanced Classification Of Genomic Sequences: A Next-Generation Sequencing Perspective, Sujatha Alla, Nagesh Bheesetty, Sai Gireesh Komaragiri, Prasanthi Chidipudi, Joshit Mohanty, Sathish Kumar Chintala, Jubin Thomas, Jayapal Vummadi, Hemanth Volikatla, Navin Kamuni Jan 2024

Integrative Machine Learning Approaches For Enhanced Classification Of Genomic Sequences: A Next-Generation Sequencing Perspective, Sujatha Alla, Nagesh Bheesetty, Sai Gireesh Komaragiri, Prasanthi Chidipudi, Joshit Mohanty, Sathish Kumar Chintala, Jubin Thomas, Jayapal Vummadi, Hemanth Volikatla, Navin Kamuni

Engineering Management & Systems Engineering Faculty Publications

The advent of Next-Generation Sequencing (NGS) techniques has revolutionized genomic research by enabling the rapid sequencing of DNA and RNA. This data can be used for various applications, including genome sequencing, transcriptome profiling, metagenomics, and epigenetics studies. For this study, DNA classifier dataset was extracted from UCI repository of machine learning databases. This vast amount of genomic data necessitates the development of sophisticated machine learning (ML) models for effective classification and analysis. This study presents a comprehensive comparison of various ML models, including Support Vector Machines (SVM), Random Forests (RF), and Neural Networks (NNs), approaches, in classifying genomic data. We …

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Integrating Generative Artificial Intelligence With Systems Architecting Diagram Creation: Advancement, Challenges, Opportunities And Future Perspectives, Cansu Yalim, Holly H. Handley Jan 2024

Integrating Generative Artificial Intelligence With Systems Architecting Diagram Creation: Advancement, Challenges, Opportunities And Future Perspectives, Cansu Yalim, Holly H. Handley

Engineering Management & Systems Engineering Faculty Publications

Generative AI (GenAI) serves as a powerful tool that can create a wide range of content, including but not limited to text, speech, images, code, videos, and 3D models. ChatGPT stands out as a particularly appealing Generative Pretrained Transformer (GPT) model that offers supplementary capabilities through GPTs and plugins. These extensions enable users to engage with the chatbot and improve its functionality, surpassing mere content generation. Our study delves into the potential of ChatGPT, specifically GPT-4, to expedite the creation of diagrams to support the system architecting process. To this end, we explored the use of ChatGPT's Diagrams Show Me …

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‘I Know It When I See It’– Developing Quality Schedules Considering Subjective Or Unspecified Criteria, Douglas L. Moody Jan 2024

‘I Know It When I See It’– Developing Quality Schedules Considering Subjective Or Unspecified Criteria, Douglas L. Moody

Publications and Research

Most timetabling problems have a given objective function to measure the quality of a solution. However, users may have a “I know it when I see it” recognition of a quality schedule, without specifying the complete basis for their judgment. In this situation, the objective function cannot be exclusively used as a solution quality measurement. This work presents an AI based approach to aid in categorizing the solution’s quality when the users have not explicitly defined all factors used in their criteria.

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Abmscore: A Heuristic Algorithm For Forming Strategic Coalitions In Agent-Based Simulation, Andrew J. Collins, Gayane Grigoryan Jan 2024

Abmscore: A Heuristic Algorithm For Forming Strategic Coalitions In Agent-Based Simulation, Andrew J. Collins, Gayane Grigoryan

Engineering Management & Systems Engineering Faculty Publications

Integrating human behavior into agent-based models has been challenging due to its diversity. An example is strategic coalition formation, which occurs when an individual decides to collaborate with others because it strategically benefits them, thereby increasing the expected utility of the situation. An algorithm called ABMSCORE was developed to help model strategic coalition formation in agent-based models. The ABMSCORE algorithm employs hedonic games from cooperative game theory and has been applied to various situations, including refugee egress and smallholder farming cooperatives. This paper discusses ABMSCORE, including its mechanism, requirements, limitations, and application. To demonstrate the potential of ABMSCORE, a new …

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Learning Social Fairness Preferences From Non-Expert Stakeholder Opinions In Kidney Placement, Mukund Telukunta, Sukruth Rao, Gabriella Stickney, Venkata Sriram Siddardh Nadendla, Casey I. Canfield Jan 2024

Learning Social Fairness Preferences From Non-Expert Stakeholder Opinions In Kidney Placement, Mukund Telukunta, Sukruth Rao, Gabriella Stickney, Venkata Sriram Siddardh Nadendla, Casey I. Canfield

Computer Science Faculty Research & Creative Works

Modern kidney placement incorporates several intelligent recommendation systems which exhibit social discrimination due to biases inherited from training data. Although initial attempts were made in the literature to study algorithmic fairness in kidney placement, these methods replace true outcomes with surgeons' decisions due to the long delays involved in recording such outcomes reliably. However, the replacement of true outcomes with surgeons' decisions disregards expert stakeholders' biases as well as social opinions of other stakeholders who do not possess medical expertise. This paper alleviates the latter concern and designs a novel fairness feedback survey to evaluate an acceptance rate predictor (ARP) …

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