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1st Workshop on Large Foundation Models for Educational Assessment

作者： Gao, Rujun Guo, Xiaosu Li, Xiaodi Narayanan, Arun Balajiee Lekshmi Thomas, Naveen Srinivasa, Arun R. J. Mike Walker’66 Department of Mechanical Engineering Texas A&M University United States Computer Science Department University of Texas Dallas United States Intelligent Systems Program University of Pittsburgh United States Department of Artificial Intelligence and Informatics Mayo Clinic United States

This study explores the feasibility of using large language models (LLMs), specifically GPT-4o (ChatGPT), for automated grading of conceptual questions in an undergraduate Mechanical engineering course. We compared the grading performance of GPT-4o with that of human teaching assistants (TAs) on ten quiz problems from the MEEN 361 course at Texas A&M University, each answered by approximately 225 students. Both the LLM and TAs followed the same instructor-provided rubric to ensure grading consistency. We evaluated performance using Spearman’s rank correlation coefficient and Root Mean Square Error (RMSE) to assess the alignment between rankings and the accuracy of scores assigned by GPT-4o and TAs under zero- and few-shot grading settings. In the zero-shot setting, GPT-4o demonstrated a strong correlation with TA grading, with Spearman’s rank correlation coefficient exceeding 0.6 in seven out of ten datasets and reaching a high of 0.9387. Our analysis reveals that GPT-4o performs well when grading criteria are straightforward but struggles with nuanced answers, particularly those involving synonyms not present in the rubric. The model also tends to grade more stringently in ambiguous cases compared to human TAs. Overall, ChatGPT shows promise as a tool for grading conceptual questions, offering scalability and consistency. © 2024 R. Gao1, X. Guo2, X. Li4, A.B.L. Narayanan3, N. Thomas1 & A.R. Srinivasa1.

关键词： Mean square error

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High Gain and Wide Band mm- Wave Antenna Incorporating Metasurfaces and Conical PEC Walls

High Gain and Wide Band mm- Wave Antenna Incorporating Metas...

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European Conference on Antennas and Propagation, EuCAP

作者： A. Khairy Shaker Alkaraki Hussein Attia Electrical Engineering Department KFUPM Interdisciplinary Research Center for Communication Systems and Sensing Dhahran Saudi Arabia Department of Electrical and Electronic Engineering George Green Institute for Electromagnetic Research University of Nottingham Nottingham United Kingdom

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This work presents a novel slotted patch antenna design featuring high gain and wide bandwidth, based on the Fabry-Perot approach. Advanced techniques are incorporated to enhance both gain and bandwidth. The proposed design utilizes a partially reflective surface (PRS), an artificial magnetic conductor (AMC), and conical PEC walls to improve gain and radiation characteristics. The conical PEC walls enhance gain and directivity by minimizing back radiation and concentrating radiated power. Additionally, it prevents side radiation leakage by reflecting it back onto the PRS. The proposed antenna achieves a maximum realized gain of 13 dB, with a wide 3-dB gain bandwidth of 27%, ranging from 28.6 GHz to 37.6 GHz. Optimized for fifth-generation (5G) high-frequency bands, the design also achieves a −10-dB bandwidth from 27 to 39 GHz.

关键词： Wireless communication Surface impedance 5G mobile communication Patch antennas Bandwidth Metasurfaces Broadband antennas Impedance Gain Wideband

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Motion Measurement Methods for Nonlinear Analysis of Electrostatic MEMS Resonators 20

Motion Measurement Methods for Nonlinear Analysis of Electro...

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20th International Conference on Smart Technologies, EUROCON 2023

作者： Ghommem, Mehdi Alattar, Basil Lherbette, Michael Elhady, Alaaeldin Abdel-Rahman, Eihab American University of Sharjah Department of Mechanical Engineering Sharjah26666 United Arab Emirates Mechatronics Graduate Program American University of Sharjah Sharjah26666 United Arab Emirates SmarAct Metrology Rohdenweg Oldenburg Germany Systems Design Engineering University of Waterloo Waterloo Ontario Canada

ISBN: (纸本)9781665463973

In this paper, we compare two measurement techniques to analyze the dynamic response of a MEMS resonator, made of a microcantilever beam, that is electrostatically actuated via a side electrode. The first method is based on a combination of Michelson interferometry, knife-edge analysis, and stroboscopic imaging, and is used to dissect the in-plane and out-of-plane motions of the resonator. The second approach follows the motion-induced current method and is based on a transduction mechanism that converts the movement of the resonator to a current signal. The third harmonic of said current is directly related to the in-plane motion of the resonator. Motion-induced current measurements enable the detection of the nonlinear dynamics associated with the motion of the resonator when actuated with high excitation voltages. The optical and electrical measurements show similar nonlinear features in terms of the location of the cyclic-fold bifurcation in the parameter space and the hysteretic region associated with it. These dynamic features can be exploited for sensing purposes. © 2023 IEEE.

关键词： Interferometry

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Automated Sewer Pipe Defect Classification Using Inspection Robot Imagery and Deep Neural Network

Automated Sewer Pipe Defect Classification Using Inspection ...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Saleh Goharinezhad Alireza Hadi Sayeh Mirzaei Department of Mechatronics Advanced Service Robots Laboratory School of Intelligent Systems Engineering College of Interdisciplinary Science and Technology University of Tehran Tehran Iran School of Engineering Science College of Engineering University of Tehran Tehran Iran

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

Sewer systems play a critical role in transporting wastewater. Efficient maintenance requires accurate identification of sewer pipe defects, traditionally performed through manual interpretation of Closed-Circuit Television (CCTV) images from robot inspections. This manual process is time-consuming, labor-intensive, and susceptible to human error. While conventional computer vision methods (machine learning methods) have been explored, they often involve extensive image pre-processing and intricate feature extraction. In this study, we propose an automated approach for classifying sewer pipe defects in Iran using deep learning, specifically leveraging the ResNet50 architecture for defect classification. We applied this deep convolutional neural network (CNN) model to automatically detect three common defect types as root intrusions, deposits, and open joints within a dataset 4630 images extracted from CCTV inspection videos of sewer pipes. Our model achieved an average testing accuracy of 96%, highlighting its potential for automating the interpretation of sewer CCTV footage.

关键词： Adaptation models Accuracy TV Manuals Inspection Robustness Convolutional neural networks Wastewater Videos Testing

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Microgrids Provision of Frequency Response to Low-Inertia Grids

Microgrids Provision of Frequency Response to Low-Inertia Gr...

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2023 IEEE International Conference on Environment and Electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Awda, Youssef Alowaifeer, Maad Abido, Mohammed King Fahd University of Petroleum and Minerals Electrical Engineering Department Dhahran Saudi Arabia King Fahd University of Petroleum and Minerals Electrical Engineering Department SDAIA-KFUPM Joint Research Canter for Artificial Intelligence Dhahran Saudi Arabia King Fahd University of Petroleum and Minerals Electrical Engineering Department Interdisciplinary Research Center for Renewable Energy and Power Systems K.A. CARE Energy Research & Innovation Center Dhahran Saudi Arabia

ISBN: (纸本)9798350347432

This paper analyzes the ability of microgrids to provide ancillary services, and in particular frequency response, to low inertia grids. Frequency response in power grids is highly dependent on the total available inertia. As the penetration of renewable energy resources is increased, the inertia of the grid reduces making the task of frequency control more difficult. Microgrids equipped with inverter-based resources (IBRs) can provide frequency response to assist low-inertia grids in stabilizing the frequency and hence, facilitating the penetration of more renewables. We compare two types of inverters in terms of their ability to support the frequency: 1) grid-following (GFL) inverters, and 2) grid-forming (GFM) inverters. The support of frequency is measured under multiple microgrid sizes and multiple levels of grid inertia. Three frequency deviation metrics are used in the comparison which are: 1) maximum frequency over/undershoot, 2) maximum rate of change of frequency, and 3) frequency settling time. The analysis is conducted through time-domain simulation in MATLAB/Simulink. © 2023 IEEE.

关键词： Frequency response

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Enhancing Safety Measures in a Steel Manufacturing Facility;Factory X Case Study

Enhancing Safety Measures in a Steel Manufacturing Facility;...

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Decision Aid Sciences and Application (DASA), International Conference on

作者： Mariam Ali Sally S. Kassem Sherif A. Elatriby Industrial Engineering Program Smart Engineering Systems Research Center Nile University Giza Egypt Operations Research and Decision Support Department Faculty of Computers and Artificial Intelligence Cairo Univesityt Giza Egypt Faculty of Engineering Helwan University Helwan Cairo Egypt Industrial Engineering Program Smart Engineering Systems Research Center Nile University Giza Egypt

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

Productivity and safety of the workers have been issues in most manufacturing facilities in Egypt and all over the world, as the main aim of any manufacturing facility is to increase profit and limit costs as much as possible. Through analysis and simulation, this paper aims to create a safe workplace for the worker; risk assessment and Failure Mode and Effect Analysis (FMEA) and the basics of the international standards ISO 31000 and ISO 45001 have been conducted to evaluate different hazards and potential risks. Moreover, lean tools such as 6S and Visual Management are proposed solutions to enhance workplace safety and decrease the possibility or severity of potential risks. Therefore, a new workplace design, an example of a high-level hazard in industry in Egypt's local market, has been established for the steel manufacturing facility under consideration using Sketch Up. The results of the proposed solutions, such as new frameworks, worker safety training, equipment replacements, and applying lean tools, have shown a practically acceptable percentage of safety improvements and a decreasing risk priority number (RPN). The percentage decrease for (RPN) ranges between 31.43% to 90.47% for different potential risks.

关键词： Training Productivity Visualization ISO Standards Employment Materials handling Production facilities Hazards Loss measurement Steel

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Board 118: systems engineering Initiative for Student Success (SEISS) Framework for Transforming Organizational Designs

Board 118: Systems Engineering Initiative for Student Succes...

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2023 ASEE Annual Conference and Exposition - The Harbor of engineering: Education for 130 Years, ASEE 2023

作者： Pennathur, Arunkumar Pennathur, Priyadarshini Blosser, Emily Bowman, Nicholas A. Department of Industrial Manufacturing and Systems Engineering University of Texas El Paso United States Department of Sociology University of Louisiana Lafayette United States Higher Education and Student Affairs Program College of Education University of Iowa United States

In this paper, we present the systems engineering Initiative for Student Success (SEISS) framework we are developing for enabling educational organizations to scan, evaluate and transform their operations to achieve their diversity, equity, and inclusion goals in student recruitment, retention, and graduation. The underlying structure and logic in our SEISS framework is that an organization such as a college of engineering is a sociotechnical system (STS) consisting of a social subsystem and a technical subsystem. The social subsystem consists of people, their roles and is a model of who talks to whom about what. The technical subsystem consists of all the activities, programs, policies, and operations that help the organization achieve its goals. In a sociotechnical system, the social and technical subsystems are interdependent in their functioning, and they must be jointly optimized from an organizational design perspective. Our SEISS framework which views a college or a similar organizational unit as a sociotechnical system lends the organizational designer a unique systems lens with which to view, analyze and design the operations and organize the capacities and resources in the college. The systems lens views an organizational unit, its sub-systems, components, and its corresponding capacities not in isolation, but as entities that interact with each other. With support from an NSF IUSE grant, we have been developing the SEISS framework and have piloted the framework in a predominantly white college of engineering to identify existing and potential technical and social system capacities for underrepresented minority (URM) students to succeed in the college. Preliminary results from our qualitative analyses of URM student interviews reveal the utility of the SEISS framework and the STS lens in unearthing the barriers and enablers for these students in the social and technical subsystems in the college. We also model the interactions between the social and techni

关键词： Students

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Distributionally Robust Performative Optimization

arXiv

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arXiv 2024年

作者： Jia, Zhuangzhuang Wang, Yijie Dong, Roy Hanasusanto, Grani A. Department of Industrial and Enterprise Systems Engineering University of Illinois Urbana-Champaign United States Graduate Program in Operations Research and Industrial Engineering The University of Texas Austin United States Department of Industrial and Enterprise Systems Engineering University of Illinois Urbana-Champaign United States Department of Industrial and Enterprise Systems Engineering University of Illinois Urbana-Champaign United States

In this paper, we propose a general distributionally robust framework for performative optimization, where the selected decision can influence the probabilistic distribution of uncertain parameters. Our framework facilitates safe decision-making in scenarios with incomplete information about the underlying decision-dependent distributions, relying instead on accessible reference distributions. To tackle the challenge of decision-dependent uncertainty, we introduce an algorithm named repeated robust risk minimization. This algorithm decouples the decision variables associated with the ambiguity set from the expected loss, optimizing the latter at each iteration while keeping the former fixed to the previous decision. By leveraging the strong connection between distributionally robust optimization and regularization, we establish a linear convergence rate to a performatively stable point and provide a suboptimality performance guarantee for the proposed algorithm. Finally, we examine the performance of our proposed model through an experimental study in strategic classification. © 2024, CC BY.

关键词： Optimization

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How engineering Faculty, Staff and Administrators Enact and Experience Diversity programs

How Engineering Faculty, Staff and Administrators Enact and ...

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2023 ASEE Annual Conference and Exposition - The Harbor of engineering: Education for 130 Years, ASEE 2023

作者： Blosser, Emily Gwen Pennathur, Arunkumar Pennathur, Priyadarshini Bowman, Nicholas A. Department of Sociology University of Louisiana Lafayette United States Department of Industrial Manufacturing and Systems Engineering University of Texas El Paso United States Higher Education and Student Affairs Program College of Education University of Iowa United States

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DEEP-LEARNING-BASED MAGNETIC RESONANCE SIMULTANEOUS MULTISLICE IMAGING USING HOLOGRAPHIC IMAGE DECODING

arXiv

引用

arXiv 2024年

作者： Ito, Satoshi Sato, Yuki Endo, Naoya Ouchi, Shohei Graduate Program in Information Electrical and Electronic Systems Engineering Utsunomiya University Japan Department of Innovative Electrical and Electronic Engineering National Institute of Technology Oyama Japan

Simultaneous multislice (SMS) imaging is a one of the acceleration technique of magnetic resonance imaging. SMS requires accurate sensitivity distributions in the slice plane for each receiving coil. This requirement is difficult to satisfy in practice, limiting the applications of this imaging technique. Here, images are reconstructed by applying deep learning and amplitude modulation to each slice image. Simulation experiments show that image reconstruction can be achieved for both real- and complex-valued images. Image quality tends to decrease with increasing number of simultaneously acquired images. It is also shown that a larger difference in the phase modulation coefficients between slices tends to increase the quality of the reconstructed images. Simulation experiments and initial MR imaging experiments show promising results for this method. Copyright © 2024, The Authors. All rights reserved.

关键词： Holography

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