Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9397831
Gustavo Camero, Soheil Salehi, R. Demara
The emergence of advanced non-uniform Compressive Sensing (CS) signal processing techniques and spin-based devices has led to the development of novel Analog to Digital Converter (ADC) architectures. Herein, a novel interactive simulation framework is developed to provide widespread access to the ADC architecture designed using commercially-available 2terminal Magnetic Tunneling Junction (MTJ) devices. The proposed ADC simulation framework utilizes CS techniques to provide insights for educational and technical purposes. The proposed framework provides simulation results spanning from the energy consumption required by each sample and MTJ device to the switching behavior of each MTJ device. Additionally, the results demonstrate the type of signal used along with the bias voltage required to switch each MTJ device. However, currently, 2-terminal MTJ devices and advanced signal processing techniques are not part of the Electrical and Computer Engineering undergraduate curriculum. To mitigate this challenge, the proposed framework has an educational resource site companion to distribute the interactive tool and further provide insights into the modeled Spin-based ADC by showcasing the research it was based on. Finally, the educational resources site also includes video tutorials to further engage the students and teach undergraduates the fundamental behavior of MTJ devices and utilization of the interactive simulation framework.
{"title":"Behavioral Simulation Educational Framework for 2-Terminal MTJ-based Analog to Digital Converter","authors":"Gustavo Camero, Soheil Salehi, R. Demara","doi":"10.1109/ISEC49744.2020.9397831","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9397831","url":null,"abstract":"The emergence of advanced non-uniform Compressive Sensing (CS) signal processing techniques and spin-based devices has led to the development of novel Analog to Digital Converter (ADC) architectures. Herein, a novel interactive simulation framework is developed to provide widespread access to the ADC architecture designed using commercially-available 2terminal Magnetic Tunneling Junction (MTJ) devices. The proposed ADC simulation framework utilizes CS techniques to provide insights for educational and technical purposes. The proposed framework provides simulation results spanning from the energy consumption required by each sample and MTJ device to the switching behavior of each MTJ device. Additionally, the results demonstrate the type of signal used along with the bias voltage required to switch each MTJ device. However, currently, 2-terminal MTJ devices and advanced signal processing techniques are not part of the Electrical and Computer Engineering undergraduate curriculum. To mitigate this challenge, the proposed framework has an educational resource site companion to distribute the interactive tool and further provide insights into the modeled Spin-based ADC by showcasing the research it was based on. Finally, the educational resources site also includes video tutorials to further engage the students and teach undergraduates the fundamental behavior of MTJ devices and utilization of the interactive simulation framework.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131293210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9397834
Tianyue Cao
Machine learning is the study of how programmed algorithms can learn useful knowledge from data automatically. As a sub-field of machine learning, reinforcement learning (RL) focuses on problems that require sequential decision making. In particular, it is about interacting with the environment and taking action according to the environment information sequentially to maximizing some rewards. Reinforcement learning attracts many interests due to its recent successes in robotics as well as playing video games, GO, and poker. However, the fundamental challenges in reinforcement learning still limit its applications to real-world, cost and risk sensitive applications. One major challenge is relatively low sample efficiency in most systems. Sample efficiency is a term used to describe how well the samples are used to train the model. Because of low sample efficiency, it requires a huge number of samples to reach a certain level of performance. In most algorithms of reinforcement learning, methods such as experience replay are used to increase the sample efficiency. In the experience replay, a certain number of samples are saved in a buffer and new data will replace the oldest data in the set. When training, data will be randomly selected from the buffer. However, this will generate the problem of distribution mismatch, as the data chosen this way may not match the current model. In my research, methods are designed so that the samples collected from the past can reflect the current model. That will allow the model to use the data more effectively and thus increase its training efficiency.
{"title":"Study of sample efficiency improvements for reinforcement learning algorithms","authors":"Tianyue Cao","doi":"10.1109/ISEC49744.2020.9397834","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9397834","url":null,"abstract":"Machine learning is the study of how programmed algorithms can learn useful knowledge from data automatically. As a sub-field of machine learning, reinforcement learning (RL) focuses on problems that require sequential decision making. In particular, it is about interacting with the environment and taking action according to the environment information sequentially to maximizing some rewards. Reinforcement learning attracts many interests due to its recent successes in robotics as well as playing video games, GO, and poker. However, the fundamental challenges in reinforcement learning still limit its applications to real-world, cost and risk sensitive applications. One major challenge is relatively low sample efficiency in most systems. Sample efficiency is a term used to describe how well the samples are used to train the model. Because of low sample efficiency, it requires a huge number of samples to reach a certain level of performance. In most algorithms of reinforcement learning, methods such as experience replay are used to increase the sample efficiency. In the experience replay, a certain number of samples are saved in a buffer and new data will replace the oldest data in the set. When training, data will be randomly selected from the buffer. However, this will generate the problem of distribution mismatch, as the data chosen this way may not match the current model. In my research, methods are designed so that the samples collected from the past can reflect the current model. That will allow the model to use the data more effectively and thus increase its training efficiency.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115401297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9280574
Diego Calderón, Erick Petersen, Oscar Rodas
Programming courses can be hard for students, but also for teachers, because of the huge amount of time that takes to manually grade each student’s assignment and the different kind of valid solutions. Moreover, there are other problems related to manually grade assignments such as completely objective and homogeneous grading. In consequence, both students and teachers don’t get feedback as fast as they should in order to take action and reinforce the topics with lower performance on each assignment. Finally, the increasing popularity of MOOCs makes manually grading no longer viable. To this aim, a scalable autograder system is proposed in order to provide students with faster feedback and help teachers with the evaluation of assignments. Our proposal can be used for learning different programming languages like Java, Python, C, C# and Ruby.
{"title":"SALP: A Scalable Autograder System for Learning Programming - A Work in Progress","authors":"Diego Calderón, Erick Petersen, Oscar Rodas","doi":"10.1109/ISEC49744.2020.9280574","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9280574","url":null,"abstract":"Programming courses can be hard for students, but also for teachers, because of the huge amount of time that takes to manually grade each student’s assignment and the different kind of valid solutions. Moreover, there are other problems related to manually grade assignments such as completely objective and homogeneous grading. In consequence, both students and teachers don’t get feedback as fast as they should in order to take action and reinforce the topics with lower performance on each assignment. Finally, the increasing popularity of MOOCs makes manually grading no longer viable. To this aim, a scalable autograder system is proposed in order to provide students with faster feedback and help teachers with the evaluation of assignments. Our proposal can be used for learning different programming languages like Java, Python, C, C# and Ruby.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115063690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9280598
Md Mahmudur Rahman, Monir H. Sharker, Roshan Paudel
In this era of smart devices, new technologies, gadgets, apps, and numerous systems and services available over online, teaching an introductory programming course by traditional lecture method faces challenges to draw student’s attention; especially in their freshman year. In this work, we discuss our experience in teaching an introductory CS course by infusing both interactive and collaborative learning in pedagogy so that students can learn using interactive platforms, tools, technologies, systems, and services as available to them and collaboration within and among groups. For interactive learning, students used an interactive programming environment (e.g. repl. it classroom) as well as online eBooks. We designed several in-class exercises, assignments, small lab-based projects with example codes and expected outputs, and unit tests by using built-in unit tests library. We also, in the middle of semester, introduced collaborative learning through teamwork on well-defined projects during the learning time and submitted at the end. The collaborations include use of basic task management tools and multi-player tool of repl.it that the students can critic, supplement, improve peer works and learn. To evaluate the impact of this infusion, a pre- and post-survey were conducted on student cohort in two different semesters. The initial evaluation of the survey results and performances (final project and final grades) show evidence to conclude that the proposed pedagogical approach increased student motivation and engagement and facilitated learning to entry-level computer science students.
{"title":"Active and Collaborative Learning Based Dynamic Instructional Approach in Teaching Introductory Computer Science Course with Python Programming","authors":"Md Mahmudur Rahman, Monir H. Sharker, Roshan Paudel","doi":"10.1109/ISEC49744.2020.9280598","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9280598","url":null,"abstract":"In this era of smart devices, new technologies, gadgets, apps, and numerous systems and services available over online, teaching an introductory programming course by traditional lecture method faces challenges to draw student’s attention; especially in their freshman year. In this work, we discuss our experience in teaching an introductory CS course by infusing both interactive and collaborative learning in pedagogy so that students can learn using interactive platforms, tools, technologies, systems, and services as available to them and collaboration within and among groups. For interactive learning, students used an interactive programming environment (e.g. repl. it classroom) as well as online eBooks. We designed several in-class exercises, assignments, small lab-based projects with example codes and expected outputs, and unit tests by using built-in unit tests library. We also, in the middle of semester, introduced collaborative learning through teamwork on well-defined projects during the learning time and submitted at the end. The collaborations include use of basic task management tools and multi-player tool of repl.it that the students can critic, supplement, improve peer works and learn. To evaluate the impact of this infusion, a pre- and post-survey were conducted on student cohort in two different semesters. The initial evaluation of the survey results and performances (final project and final grades) show evidence to conclude that the proposed pedagogical approach increased student motivation and engagement and facilitated learning to entry-level computer science students.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124475251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9280597
Eric Nersesian, Jessica Ross-Nersesian, Adam Spryszynski, Michael J. Lee
Higher educational institutions formalize socialization for their incoming undergraduate student populations with traditional forms of physical classroom-based learning community (LC) skill-building environments; however, recent studies have shown that virtual LC environments can offer improved results over physical LC environments. This study examines whether incoming undergraduate science, technology, engineering, and math (STEM) students gain the same benefits to their academic performance regardless of whether they receive LC training in physical or virtual reality (VR) treatment. We found that either treatment of collaboration training improve the participants’ academic performance in comparison to the control treatment. In addition, we found that the VR participants gave more academic help in social settings to their peers throughout the semester than their control group counterparts. Upon interviewing the two treatment group participants, we found that virtualization of collaboration may impact perceptions on leadership roles, group functions, and thinking about the future. This research shows that virtualizing LCs has the potential to expand and supplement existing learning structures, and create new ones where they were not previously available, and aims to offer a better understanding of the strengths and limitations of introducing VR technologies in higher education.
{"title":"Virtual Collaboration Training for Freshman Undergraduate STEM Students","authors":"Eric Nersesian, Jessica Ross-Nersesian, Adam Spryszynski, Michael J. Lee","doi":"10.1109/ISEC49744.2020.9280597","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9280597","url":null,"abstract":"Higher educational institutions formalize socialization for their incoming undergraduate student populations with traditional forms of physical classroom-based learning community (LC) skill-building environments; however, recent studies have shown that virtual LC environments can offer improved results over physical LC environments. This study examines whether incoming undergraduate science, technology, engineering, and math (STEM) students gain the same benefits to their academic performance regardless of whether they receive LC training in physical or virtual reality (VR) treatment. We found that either treatment of collaboration training improve the participants’ academic performance in comparison to the control treatment. In addition, we found that the VR participants gave more academic help in social settings to their peers throughout the semester than their control group counterparts. Upon interviewing the two treatment group participants, we found that virtualization of collaboration may impact perceptions on leadership roles, group functions, and thinking about the future. This research shows that virtualizing LCs has the potential to expand and supplement existing learning structures, and create new ones where they were not previously available, and aims to offer a better understanding of the strengths and limitations of introducing VR technologies in higher education.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126781105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9397828
Eric Nersesian, Adam Spryszynski, Tracy Espiritu, Michael J. Lee
New curricula initiatives are growing to meet nearfuture, industrial demand for computer science (CS) graduates with Augmented and Virtual Reality (AR/VR) development knowledge. Universities are often at the forefront in developing these curricula to help prepare their students for industry jobs. High schools wanting to offer college aligned CS courses for their students typically work with local universities to adapt courses for their students’ needs. This paper presents such an effort along with results from a student survey showing the successful implementation of college-level courses through training of high school teachers. The curricula from this study are available for public use at artncoding.com and may be adapted as needed by educational programs to meet the emerging employment needs of their students in the AR/VR field.
{"title":"Pre-college Computer Science Initiative for Augmented and Virtual Reality Development","authors":"Eric Nersesian, Adam Spryszynski, Tracy Espiritu, Michael J. Lee","doi":"10.1109/ISEC49744.2020.9397828","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9397828","url":null,"abstract":"New curricula initiatives are growing to meet nearfuture, industrial demand for computer science (CS) graduates with Augmented and Virtual Reality (AR/VR) development knowledge. Universities are often at the forefront in developing these curricula to help prepare their students for industry jobs. High schools wanting to offer college aligned CS courses for their students typically work with local universities to adapt courses for their students’ needs. This paper presents such an effort along with results from a student survey showing the successful implementation of college-level courses through training of high school teachers. The curricula from this study are available for public use at artncoding.com and may be adapted as needed by educational programs to meet the emerging employment needs of their students in the AR/VR field.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121324523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9280740
Shahad A. Sultan, M. F. Ghanim
A biometric based authentication system is a security system that provide an automatic user authentication to access some areas, which require a certain level of security. Such a system is built based on some biometric traits possessed by the user. Although there are many authentic systems can be built based on different human biometrics such as face, fingerprints, iris, hand and finger geometry and voice etc. but all of these biometrics have their drawbacks and all of them can easily be forged. Human retina is a biometric trait that provides secure and reliable source of person recognition as it is unique, universal, lies at the rare end of the eye and hence it is unforgeable. Therefore, among all other biometrics human retina can be used to build a high-level security system. This paper makes an outlook on the commonly used biometric traits and states a comparison among them to prove that human retina is the best one for high level security areas.
{"title":"Outlook of Commonly used Biometrics and Assessment of Best Trait for High Level Security","authors":"Shahad A. Sultan, M. F. Ghanim","doi":"10.1109/ISEC49744.2020.9280740","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9280740","url":null,"abstract":"A biometric based authentication system is a security system that provide an automatic user authentication to access some areas, which require a certain level of security. Such a system is built based on some biometric traits possessed by the user. Although there are many authentic systems can be built based on different human biometrics such as face, fingerprints, iris, hand and finger geometry and voice etc. but all of these biometrics have their drawbacks and all of them can easily be forged. Human retina is a biometric trait that provides secure and reliable source of person recognition as it is unique, universal, lies at the rare end of the eye and hence it is unforgeable. Therefore, among all other biometrics human retina can be used to build a high-level security system. This paper makes an outlook on the commonly used biometric traits and states a comparison among them to prove that human retina is the best one for high level security areas.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125804104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9397848
Ronnel Ian A. Ambion, Rainier Santi C. De Leon, Alfonso Pio Angelo R. Mendoza, Reinier M. Navarro
Several scholars in the field of science instruction suggested that various challenges can hinder an individual in learning (Chin et al. [1]; Drinkwater et al. [2]; Huang et al. [3]). Furthermore, the help of other people enhances learning. This study applied the Feynman Technique and the practice of paired team teaching to identify the challenges of students in understanding the concept of evolution in a high school Biology class. The researchers tested 20 students from a Grade 10 Adult Night High School class of a private school in the Philippines. The control group took the class without the intervention while the experimental group was introduced to the intervention. Purposive sampling was used based on the student’s class standing before the experiment. A ten-item assessment on the evolution of horses was done after the experiment. The study revealed that there is not enough evidence to prove the existence of a significant difference in the results of the control group (M=6.646, SD=17.9) and the experimental group (M=6.653, SD=3.71) for the administered assessment; t (15) =1.75, p=0.05. It is recommended that the intervention should be tested in a larger population, regardless of grade level and a science subject. This is to validate what other variations of inputs can be created from the Feynman Technique.
科学教学领域的几位学者认为，各种各样的挑战会阻碍个人的学习(Chin et al. bbb;饮用水等[j];Huang et al.[10]。此外，他人的帮助能促进学习。本研究运用费曼技巧和配对小组教学的实践，找出学生在高中生物课上理解进化概念的挑战。研究人员对菲律宾一所私立学校10年级成人夜校班的20名学生进行了测试。对照组在没有干预的情况下上课，而实验组则被引入干预。目的抽样是基于学生在实验前的课堂站立情况。实验结束后，对马的进化进行了十项评估。研究发现，对照组(M=6.646, SD=17.9)与实验组(M=6.653, SD=3.71)在给药评估结果上没有足够的证据证明存在显著差异;T (15) =1.75, p=0.05。建议在更大的人群中测试干预措施，无论年级水平和科学科目如何。这是为了验证从费曼技术中可以创建哪些其他变量的输入。
{"title":"The Utilization of the Feynman Technique in Paired Team Teaching Towards Enhancing Grade 10 ANHS Students’ Academic Achievement in Science","authors":"Ronnel Ian A. Ambion, Rainier Santi C. De Leon, Alfonso Pio Angelo R. Mendoza, Reinier M. Navarro","doi":"10.1109/ISEC49744.2020.9397848","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9397848","url":null,"abstract":"Several scholars in the field of science instruction suggested that various challenges can hinder an individual in learning (Chin et al. [1]; Drinkwater et al. [2]; Huang et al. [3]). Furthermore, the help of other people enhances learning. This study applied the Feynman Technique and the practice of paired team teaching to identify the challenges of students in understanding the concept of evolution in a high school Biology class. The researchers tested 20 students from a Grade 10 Adult Night High School class of a private school in the Philippines. The control group took the class without the intervention while the experimental group was introduced to the intervention. Purposive sampling was used based on the student’s class standing before the experiment. A ten-item assessment on the evolution of horses was done after the experiment. The study revealed that there is not enough evidence to prove the existence of a significant difference in the results of the control group (M=6.646, SD=17.9) and the experimental group (M=6.653, SD=3.71) for the administered assessment; t (15) =1.75, p=0.05. It is recommended that the intervention should be tested in a larger population, regardless of grade level and a science subject. This is to validate what other variations of inputs can be created from the Feynman Technique.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134590321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9280736
Thomas Aldhizer, Austin Morock, K. Hughes, M. Lanzerotti, S. Christoff, S. Lintelmann, J. Capps
This research proposes an interdisciplinary collaboration to improve hoist stabilization for medical evacuation and successful rescues. This paper would include the collaborative efforts from a diverse range of fields to include Systems Engineering, Mechanical Engineering, Physics, and the Special Collections & Archives Division of the United States Military Academy Library. The research objective of this effort is to create an algorithm which could limit the displacement angle of a suspended individual below a helicopter. This would be accomplished by changing the relative length of the cable at different points within the swing of the slung mass. This could all be done while reeling in the hoisted individual to the helicopter by changing the rate at which the hoist is lessening its cable. Elements of the mathematical principles that this research is built on are illustrated through Edgar Allen Poe’s application of the pendulum in his short story “The Pit and the Pendulum”. Poe was an individual who attended, but did not graduate from, USMA; however, his education at the Military Academy and his subsequent writings are the birthplace of this research endeavor. It is a multi-semester goal, and this paper will present an initial proof of concept.
{"title":"Suspended Load Swing Stabilization","authors":"Thomas Aldhizer, Austin Morock, K. Hughes, M. Lanzerotti, S. Christoff, S. Lintelmann, J. Capps","doi":"10.1109/ISEC49744.2020.9280736","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9280736","url":null,"abstract":"This research proposes an interdisciplinary collaboration to improve hoist stabilization for medical evacuation and successful rescues. This paper would include the collaborative efforts from a diverse range of fields to include Systems Engineering, Mechanical Engineering, Physics, and the Special Collections & Archives Division of the United States Military Academy Library. The research objective of this effort is to create an algorithm which could limit the displacement angle of a suspended individual below a helicopter. This would be accomplished by changing the relative length of the cable at different points within the swing of the slung mass. This could all be done while reeling in the hoisted individual to the helicopter by changing the rate at which the hoist is lessening its cable. Elements of the mathematical principles that this research is built on are illustrated through Edgar Allen Poe’s application of the pendulum in his short story “The Pit and the Pendulum”. Poe was an individual who attended, but did not graduate from, USMA; however, his education at the Military Academy and his subsequent writings are the birthplace of this research endeavor. It is a multi-semester goal, and this paper will present an initial proof of concept.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129089763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9397839
A. Dominguez, Santa Tejeda, B. Ruiz
The need to understand better the actors and factors that influence students’ perceptions of pursuing an academic and professional future in STEM areas has been studied for over 30 years. In this work, we focus on students who are strongly oriented to science, technology, engineering, and mathematics to investigate what motivates them and who has been cultivating their inclinations to these careers. High school students who attended an international science contest on mathematics, physics, chemistry, biology, and computing (over 600 attendees) were invited to participate in a focus group. Thirteen students attended the call. The session lasted over 90 minutes and was video recorded. All the session was transcribed, and a group of researchers analyzed the data based on an adaptation of the expectancy-value theory. The results indicated that the students did not feel they had the expected support from their schools; instead, their primary support came from their family (particularly their parents). It was interesting to find that among this group of students, their conceptualization of STEM and interest in how science and technology could improve the world (or their world) proved to be a significant factor in keeping them motivated to pursue their goals.
{"title":"Influencing Factors to Choose STEM Areas: The Case of Strongly STEM-Oriented High School Students","authors":"A. Dominguez, Santa Tejeda, B. Ruiz","doi":"10.1109/ISEC49744.2020.9397839","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9397839","url":null,"abstract":"The need to understand better the actors and factors that influence students’ perceptions of pursuing an academic and professional future in STEM areas has been studied for over 30 years. In this work, we focus on students who are strongly oriented to science, technology, engineering, and mathematics to investigate what motivates them and who has been cultivating their inclinations to these careers. High school students who attended an international science contest on mathematics, physics, chemistry, biology, and computing (over 600 attendees) were invited to participate in a focus group. Thirteen students attended the call. The session lasted over 90 minutes and was video recorded. All the session was transcribed, and a group of researchers analyzed the data based on an adaptation of the expectancy-value theory. The results indicated that the students did not feel they had the expected support from their schools; instead, their primary support came from their family (particularly their parents). It was interesting to find that among this group of students, their conceptualization of STEM and interest in how science and technology could improve the world (or their world) proved to be a significant factor in keeping them motivated to pursue their goals.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115033730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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