Contribution: This study introduces a two-year, 180-h project-based learning (PBL) program in Internet of Things (IoT) education, developed through collaboration among industry, academia, and government. The program provides a scalable model for integrating real-world challenges into engineering curricula to enhance technical and professional competencies.Background: The growing demand for IoT professionals, especially in aging societies like Japan, highlights the need for long-term, interdisciplinary education. Traditional approaches often lack sufficient depth to prepare students for complex, real-world applications.Research Questions: How can a long-term, tri-sector PBL curriculum foster IoT engineers capable of addressing societal challenges? What educational outcomes result from sustained, authentic project engagement?Methodology: Students engaged in three consecutive PBL subjects addressing themes such as system development, social application, and business design. Teams created IoT solutions based on real issues proposed by local governments and industry partners. Faculty and peers evaluated each project on creativity, implementation, and technical quality.Findings: Teacher assessments improved steadily, while peer evaluations became more critical over time, reflecting students’ growth in skills and self-awareness. The results suggest that long-term, authentic PBL supported by cross-sector collaboration effectively enhances both technical ability and professional mindset.
{"title":"Long-Term Practical Project-Based Learning Education for Developing Advanced IoT Engineers on the Trinity Partnership: Industry–Academia–Government","authors":"Arata Yasuda;Tatsuyasu Ando;Hideki Hara;Katsuhiro Ajito","doi":"10.1109/TE.2025.3583755","DOIUrl":"https://doi.org/10.1109/TE.2025.3583755","url":null,"abstract":"Contribution: This study introduces a two-year, 180-h project-based learning (PBL) program in Internet of Things (IoT) education, developed through collaboration among industry, academia, and government. The program provides a scalable model for integrating real-world challenges into engineering curricula to enhance technical and professional competencies.Background: The growing demand for IoT professionals, especially in aging societies like Japan, highlights the need for long-term, interdisciplinary education. Traditional approaches often lack sufficient depth to prepare students for complex, real-world applications.Research Questions: How can a long-term, tri-sector PBL curriculum foster IoT engineers capable of addressing societal challenges? What educational outcomes result from sustained, authentic project engagement?Methodology: Students engaged in three consecutive PBL subjects addressing themes such as system development, social application, and business design. Teams created IoT solutions based on real issues proposed by local governments and industry partners. Faculty and peers evaluated each project on creativity, implementation, and technical quality.Findings: Teacher assessments improved steadily, while peer evaluations became more critical over time, reflecting students’ growth in skills and self-awareness. The results suggest that long-term, authentic PBL supported by cross-sector collaboration effectively enhances both technical ability and professional mindset.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 4","pages":"387-393"},"PeriodicalIF":2.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: Results and conclusions on the use of a hybrid Project-Based Learning (PBL) approach to teaching programming in a higher education computing department. Background: PBL is a pedagogical approach that facilitates “learning by doing” and can create compelling educational experiences that enhance a student’s intrinsic motivation. Engagement can increase because students design their own unique projects, which have personal meaning and importance. PBL facilitates working with industrial clients to solve problems, which can create powerful extrinsic motivation. However, PBL can fail when students lack the experience and confidence to work as independent learners. Research Questions: 1) Can a hybrid PBL approach mitigate these problems by using a range of additional initiatives? These include, a wide range of on-demand learning resources, student mentoring, students collaborating with teachers to grade their own work, regular feedback milestones and scaffolding of learning via streaming. In this case streaming means offering students pathways through projects that require more or less independent research and project management. Methodology: A mixed methods study of a new hybrid approach to teaching programming. Findings: This article summarizes the author’s experience of implementing hybrid PBL within a university computing department, associated with improved student attainment and describes best practice, the advantages and the pitfalls.
{"title":"Teaching Programming in Higher Education Using a Hybrid Project-Based Learning Approach","authors":"Mark Featherstone","doi":"10.1109/TE.2025.3577406","DOIUrl":"https://doi.org/10.1109/TE.2025.3577406","url":null,"abstract":"Contribution: Results and conclusions on the use of a hybrid Project-Based Learning (PBL) approach to teaching programming in a higher education computing department. Background: PBL is a pedagogical approach that facilitates “learning by doing” and can create compelling educational experiences that enhance a student’s intrinsic motivation. Engagement can increase because students design their own unique projects, which have personal meaning and importance. PBL facilitates working with industrial clients to solve problems, which can create powerful extrinsic motivation. However, PBL can fail when students lack the experience and confidence to work as independent learners. Research Questions: 1) Can a hybrid PBL approach mitigate these problems by using a range of additional initiatives? These include, a wide range of on-demand learning resources, student mentoring, students collaborating with teachers to grade their own work, regular feedback milestones and scaffolding of learning via streaming. In this case streaming means offering students pathways through projects that require more or less independent research and project management. Methodology: A mixed methods study of a new hybrid approach to teaching programming. Findings: This article summarizes the author’s experience of implementing hybrid PBL within a university computing department, associated with improved student attainment and describes best practice, the advantages and the pitfalls.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 4","pages":"377-386"},"PeriodicalIF":2.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Noemi V. Mendoza Diaz;Allison M. Esparza;Karen E. Rambo-Hernandez;Bimal Nepal
Enculturation into engineering refers to the process by which novices learn and internalize the content, practices, and values of the engineering profession. This study employs an enculturation model incorporating both intrinsic and extrinsic influences. Extrinsic influences stem from institutional frameworks, particularly first-year curricular standards set by ABET. The study aimed to operationalize and test this model through a survey conducted during the Spring 2022 with 626 students at two U.S. minority-serving institutions. The research addressed four questions: 1) How do enculturation dimensions vary across student classifications at each institution? 2) What is the relationship between enculturation and the impact of COVID-19? 3) How do these dimensions vary based on First-Generation Status and Race/Ethnicity at a Hispanic-Serving Institution (HSI)? 4) How does Exploratory Factor Analysis characterize enculturation, and how does it relate to self-efficacy? Findings indicate that students generally increase in enculturation dimensions as they advance in their programs, though differences exist across demographics and institutions. COVID-19 significantly impacted two dimensions, with effects varying by institution. First-Generation and minority students followed similar trends, often demonstrating disadvantage compared to majority peers. Finally, factor analyzes confirmed that enculturation and self-efficacy are distinct constructs. These promising results provide proof that the model of enculturation can potentially help attract and retain students in multiple engineering fields. The results also have wide implications for research and practice, specifically when pertaining to disadvantaged minority students.
{"title":"Enculturation of Students Into Engineering During COVID-19 in Minority Serving Institutions","authors":"Noemi V. Mendoza Diaz;Allison M. Esparza;Karen E. Rambo-Hernandez;Bimal Nepal","doi":"10.1109/TE.2025.3575749","DOIUrl":"https://doi.org/10.1109/TE.2025.3575749","url":null,"abstract":"Enculturation into engineering refers to the process by which novices learn and internalize the content, practices, and values of the engineering profession. This study employs an enculturation model incorporating both intrinsic and extrinsic influences. Extrinsic influences stem from institutional frameworks, particularly first-year curricular standards set by ABET. The study aimed to operationalize and test this model through a survey conducted during the Spring 2022 with 626 students at two U.S. minority-serving institutions. The research addressed four questions: 1) How do enculturation dimensions vary across student classifications at each institution? 2) What is the relationship between enculturation and the impact of COVID-19? 3) How do these dimensions vary based on First-Generation Status and Race/Ethnicity at a Hispanic-Serving Institution (HSI)? 4) How does Exploratory Factor Analysis characterize enculturation, and how does it relate to self-efficacy? Findings indicate that students generally increase in enculturation dimensions as they advance in their programs, though differences exist across demographics and institutions. COVID-19 significantly impacted two dimensions, with effects varying by institution. First-Generation and minority students followed similar trends, often demonstrating disadvantage compared to majority peers. Finally, factor analyzes confirmed that enculturation and self-efficacy are distinct constructs. These promising results provide proof that the model of enculturation can potentially help attract and retain students in multiple engineering fields. The results also have wide implications for research and practice, specifically when pertaining to disadvantaged minority students.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 4","pages":"367-376"},"PeriodicalIF":2.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: This research designs a student evaluation framework integrating the fuzzy-logic system that assesses the student’s performances in the soft boundary system for outcome-based education (OBE), measuring the course learning outcome (CLO) and program learning outcome (PLO). The framework fills the gap between conventional grading methods and offers insights into learning for course assessment and continuous development. Background: A well-established evaluation technique is a requirement to deliver a productive, skilled, worthy, and compatible student and faculty. Moreover, OBE, with a documented and structured academic curriculum, has to ensure the accreditation of an academic program. Research Questions: What are the drawbacks of traditional student evaluation techniques? Does the proposed system work as a better, more reliable, and meaningful student evaluation method? Methodology: To assess, it considers the final examination paper containing several questions and continuous assessment comprising a few items like class tests, quizzes, viva voce, homework, etc., where the course teachers and moderators assign marks on these questions and items considering the CLOs, learning methods, and Bloom’s taxonomy. Then, the framework records and tracks the ratio of earned marks to assigned marks for the fuzzification, while the defuzzification computes the values indicating the CLOs and PLOs earned by a student. Findings: The results study cases for 40 courses of a particular student and analyze statistics for 100 students from the consecutive eight semesters. This fuzzy-logic-based evaluation technique is fairer, reliable, and unbiased to the learners and greatly helps to get accreditation and recognition for the degree worldwide.
{"title":"A Fuzzy-Logic-Based Student Learning Assessment System for Outcome-Based Education","authors":"Abdul Aziz;Md. Asaf-uddowla Golap;M. M. A. Hashem","doi":"10.1109/TE.2025.3574202","DOIUrl":"https://doi.org/10.1109/TE.2025.3574202","url":null,"abstract":"Contribution: This research designs a student evaluation framework integrating the fuzzy-logic system that assesses the student’s performances in the soft boundary system for outcome-based education (OBE), measuring the course learning outcome (CLO) and program learning outcome (PLO). The framework fills the gap between conventional grading methods and offers insights into learning for course assessment and continuous development. Background: A well-established evaluation technique is a requirement to deliver a productive, skilled, worthy, and compatible student and faculty. Moreover, OBE, with a documented and structured academic curriculum, has to ensure the accreditation of an academic program. Research Questions: What are the drawbacks of traditional student evaluation techniques? Does the proposed system work as a better, more reliable, and meaningful student evaluation method? Methodology: To assess, it considers the final examination paper containing several questions and continuous assessment comprising a few items like class tests, quizzes, viva voce, homework, etc., where the course teachers and moderators assign marks on these questions and items considering the CLOs, learning methods, and Bloom’s taxonomy. Then, the framework records and tracks the ratio of earned marks to assigned marks for the fuzzification, while the defuzzification computes the values indicating the CLOs and PLOs earned by a student. Findings: The results study cases for 40 courses of a particular student and analyze statistics for 100 students from the consecutive eight semesters. This fuzzy-logic-based evaluation technique is fairer, reliable, and unbiased to the learners and greatly helps to get accreditation and recognition for the degree worldwide.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 4","pages":"346-366"},"PeriodicalIF":2.0,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144782018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: A novel undergraduate course design at the intersection of software engineering (SE) and machine learning (ML) based on industry-reported challenges.Background: ML professionals report that building ML systems is different enough that one needs new knowledge about how to infuse ML into software production. For instance, various experts need to be deeply involved with these SE projects, such as business analysts, data scientists, statisticians, and software engineers.Intended Outcomes: The creation of a table detailing and matching industry challenges with course learning objectives, course topics, instructional units, and other related activities.Application Design: Course content was derived from interviewing industry professionals with related experience as well as surveying undergraduate computer science and engineering students. The proposed course style is designed to emulate real-world ML-based SE.Findings: Experienced IT professionals testify that the synergy between ML and agile SE is maturing and now becoming the standard practice. Thus, industry-derived content for a pilot undergraduate course has been successfully crafted at the intersection of SE and ML.
{"title":"Teaching Machine Learning as Part of Agile Software Engineering","authors":"Steve Chenoweth;Panagiotis K. Linos","doi":"10.1109/TE.2025.3572355","DOIUrl":"https://doi.org/10.1109/TE.2025.3572355","url":null,"abstract":"Contribution: A novel undergraduate course design at the intersection of software engineering (SE) and machine learning (ML) based on industry-reported challenges.Background: ML professionals report that building ML systems is different enough that one needs new knowledge about how to infuse ML into software production. For instance, various experts need to be deeply involved with these SE projects, such as business analysts, data scientists, statisticians, and software engineers.Intended Outcomes: The creation of a table detailing and matching industry challenges with course learning objectives, course topics, instructional units, and other related activities.Application Design: Course content was derived from interviewing industry professionals with related experience as well as surveying undergraduate computer science and engineering students. The proposed course style is designed to emulate real-world ML-based SE.Findings: Experienced IT professionals testify that the synergy between ML and agile SE is maturing and now becoming the standard practice. Thus, industry-derived content for a pilot undergraduate course has been successfully crafted at the intersection of SE and ML.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 4","pages":"322-335"},"PeriodicalIF":2.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144782020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: This study advances the understanding of learner satisfaction in online education, particularly within higher education (HE) engineering programs. It develops a conceptual model categorizing key factors affecting satisfaction and provides empirical evidence on their impact, offering actionable recommendations for educators and institutions. Background: Online education has transformed traditional learning environments, increasing access and flexibility. However, HE programs, especially engineering, face significant challenges when transitioning from face-to-face formats to hybrid or fully online. Understanding the factors influencing student satisfaction in this context is crucial to enhance learning experiences. Research Questions: 1) What are the key barriers affecting learners’ satisfaction with online learning in higher engineering courses in Ireland? and 2) What is the degree of influence of these barriers on learner satisfaction? Methodology: Data were collected from 608 students enrolled in HE engineering courses in Ireland. The study used partial least squares structural equation modeling (PLS-SEM) to analyze the interaction between six key factors categorized into personal and technical domains. Findings: Learner motivation, online learning tools optimization, and addressing psychological well-being emerged as critical elements to improve student satisfaction. Contrary to expectations, increased use of asynchronous communication channels and greater Internet connectivity did not significantly contribute to higher satisfaction levels. These findings provide valuable insights for improving the online learning experience in HE engineering education.
{"title":"Breaking Barriers: Enhancing Student Satisfaction in Online Engineering Education","authors":"Suzana Sampaio;Kathryn Cormican","doi":"10.1109/TE.2025.3573603","DOIUrl":"https://doi.org/10.1109/TE.2025.3573603","url":null,"abstract":"Contribution: This study advances the understanding of learner satisfaction in online education, particularly within higher education (HE) engineering programs. It develops a conceptual model categorizing key factors affecting satisfaction and provides empirical evidence on their impact, offering actionable recommendations for educators and institutions. Background: Online education has transformed traditional learning environments, increasing access and flexibility. However, HE programs, especially engineering, face significant challenges when transitioning from face-to-face formats to hybrid or fully online. Understanding the factors influencing student satisfaction in this context is crucial to enhance learning experiences. Research Questions: 1) What are the key barriers affecting learners’ satisfaction with online learning in higher engineering courses in Ireland? and 2) What is the degree of influence of these barriers on learner satisfaction? Methodology: Data were collected from 608 students enrolled in HE engineering courses in Ireland. The study used partial least squares structural equation modeling (PLS-SEM) to analyze the interaction between six key factors categorized into personal and technical domains. Findings: Learner motivation, online learning tools optimization, and addressing psychological well-being emerged as critical elements to improve student satisfaction. Contrary to expectations, increased use of asynchronous communication channels and greater Internet connectivity did not significantly contribute to higher satisfaction levels. These findings provide valuable insights for improving the online learning experience in HE engineering education.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 4","pages":"336-345"},"PeriodicalIF":2.0,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Transactions on Education Information for Authors","authors":"","doi":"10.1109/TE.2025.3571241","DOIUrl":"https://doi.org/10.1109/TE.2025.3571241","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 3","pages":"C3-C3"},"PeriodicalIF":2.1,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11024062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: This article proposes the systematic integration of embedded systems into training hardware to bridge the gap in structured troubleshooting education. Traditional methods often rely on manual explanations, virtual simulations, or on-the-job training, which lack structured learning experiences. The proof-of-work module, developed based on the proposed framework, effectively simulates challenging scenarios, providing real-life troubleshooting experiences that significantly increase motivation for further learning. Background: Troubleshooting competence is typically acquired through experiential engagement and unforeseen challenges, rarely structured as a deliberate educational endeavor. Simulating real problematic conditions also poses challenges due to their complexity or potential dangers. Intended Outcome: A framework that facilitates the representation of real-life troubleshooting situations using hardware prototypes with multiple scenarios. A proven implementation, a ship’s electrical earth fault troubleshooting training hardware, exemplifies the utilization of embedded systems using the proposed framework. Application Design: Experiential Learning is commonly used to develop troubleshooting proficiency. Providing deliberate multiple scenarios through training hardware will give much more experience than unforeseen challenges in job training. Findings: The findings demonstrated statistically significant benefits of the new hardware with the embedded system in increasing user interest for further learning and product presentation, with a 95% confidence interval and significant differences adjusted p-values = 0.049. It provides evidence of embedded systems’ effectiveness and suggests their potential applications in engineering education, particularly in the electrical engineering field.
{"title":"Fostering Engineering Troubleshooting Proficiency: A Real-World Scenario-Based Electrical Training Hardware Using Embedded System","authors":"Rona Riantini;Mochamad Hariadi;Supeno Mardi Susiki Nugroho;Diah Puspito Wulandari;Wahyu Suci Rohqani","doi":"10.1109/TE.2025.3559953","DOIUrl":"https://doi.org/10.1109/TE.2025.3559953","url":null,"abstract":"Contribution: This article proposes the systematic integration of embedded systems into training hardware to bridge the gap in structured troubleshooting education. Traditional methods often rely on manual explanations, virtual simulations, or on-the-job training, which lack structured learning experiences. The proof-of-work module, developed based on the proposed framework, effectively simulates challenging scenarios, providing real-life troubleshooting experiences that significantly increase motivation for further learning. Background: Troubleshooting competence is typically acquired through experiential engagement and unforeseen challenges, rarely structured as a deliberate educational endeavor. Simulating real problematic conditions also poses challenges due to their complexity or potential dangers. Intended Outcome: A framework that facilitates the representation of real-life troubleshooting situations using hardware prototypes with multiple scenarios. A proven implementation, a ship’s electrical earth fault troubleshooting training hardware, exemplifies the utilization of embedded systems using the proposed framework. Application Design: Experiential Learning is commonly used to develop troubleshooting proficiency. Providing deliberate multiple scenarios through training hardware will give much more experience than unforeseen challenges in job training. Findings: The findings demonstrated statistically significant benefits of the new hardware with the embedded system in increasing user interest for further learning and product presentation, with a 95% confidence interval and significant differences adjusted p-values = 0.049. It provides evidence of embedded systems’ effectiveness and suggests their potential applications in engineering education, particularly in the electrical engineering field.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 3","pages":"303-311"},"PeriodicalIF":2.1,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Transactions on Education Information for Authors","authors":"","doi":"10.1109/TE.2025.3554092","DOIUrl":"https://doi.org/10.1109/TE.2025.3554092","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":"68 2","pages":"C3-C3"},"PeriodicalIF":2.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10971237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143856177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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