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/ISEC49744.2020.9397839
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}
Pub Date : 2020-08-01DOI: 10.1109/ISEC49744.2020.9397811
Yeisson Chicas, Angel Isidro, Oscar Rodas
Industry 4.0 was first introduced in Germany in 2006. As leading countries of this initiative, we can mention various European and Asian countries and the United States. The main axis that Industry 4.0 has are Internet of Things (IoT), Virtual Reality, 3D Printing, Cloud Computing, among others. Guatemala is becoming a technology hub country. Various web development or BPO companies have migrated their technology departments to our country because people have well developed STEM skills. Their main activities involved web development, infrastructure and help desk collaborations. However, hardware development is not an economic pillar to develop our country yet. In Universidad Galileo we created academic and outreach programs based on IoT to change the mindset of young students and professionals to become technology producers and not only technology consumers or users. Our two-year research, the workshops developed, and the feedback obtained by participants in our technology events ensures that our STEM programs are building the correct skills in people to help develop Industry 4.0 in Guatemala.
{"title":"Development of low-cost IoT devices to encourage STEM skills in Guatemalan environments","authors":"Yeisson Chicas, Angel Isidro, Oscar Rodas","doi":"10.1109/ISEC49744.2020.9397811","DOIUrl":"https://doi.org/10.1109/ISEC49744.2020.9397811","url":null,"abstract":"Industry 4.0 was first introduced in Germany in 2006. As leading countries of this initiative, we can mention various European and Asian countries and the United States. The main axis that Industry 4.0 has are Internet of Things (IoT), Virtual Reality, 3D Printing, Cloud Computing, among others. Guatemala is becoming a technology hub country. Various web development or BPO companies have migrated their technology departments to our country because people have well developed STEM skills. Their main activities involved web development, infrastructure and help desk collaborations. However, hardware development is not an economic pillar to develop our country yet. In Universidad Galileo we created academic and outreach programs based on IoT to change the mindset of young students and professionals to become technology producers and not only technology consumers or users. Our two-year research, the workshops developed, and the feedback obtained by participants in our technology events ensures that our STEM programs are building the correct skills in people to help develop Industry 4.0 in Guatemala.","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":"123377093","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/isec49744.2020.9397823
Michael Z. Q. Chen, A. Dasanayake, Rohan Deb, Varun Deb, E. Zhao
Our poster seeks to provide a broad overview of the many wondrous properties of aerogel composites (which include hydrophobicity, low density, blue light scattering, and superb noise, heat, and electrical insulation), detail chronologically various methods of the material’s synthesis (such as sol-gel polymerization and seed growth method), and offer insight into its vast array of present and future applications (in fields such as fashion, aerospace, and construction). Research on our project began in May 2019 and is expected to be completed in March 2020. During the span of our research, we analyzed a wide selection of scientific papers detailing the fabrication processes, chemical and physical properties, and history of aerogel. To supplement our research, we performed live experiments (with the assistance of our AP Chemistry teacher) on a small monolith sample we purchased online. In one test, we placed the aerogel on a metal ring fixed to a stand above a Bunsen burner, lighted the burner, and then placed a match on top of the aerogel (the match remained unlit, demonstrating the material’s extraordinary heat-insulating capability). Though our poster seeks, in part, to exhibit our experience in the classroom in research and experimental design in the field of materials science, it most importantly seeks to instill within the viewer a curiosity and awe for the highly promising future of this novel material.
{"title":"Aerogel Composites: Historical and Novel Synthesis Methods and Applications","authors":"Michael Z. Q. Chen, A. Dasanayake, Rohan Deb, Varun Deb, E. Zhao","doi":"10.1109/isec49744.2020.9397823","DOIUrl":"https://doi.org/10.1109/isec49744.2020.9397823","url":null,"abstract":"Our poster seeks to provide a broad overview of the many wondrous properties of aerogel composites (which include hydrophobicity, low density, blue light scattering, and superb noise, heat, and electrical insulation), detail chronologically various methods of the material’s synthesis (such as sol-gel polymerization and seed growth method), and offer insight into its vast array of present and future applications (in fields such as fashion, aerospace, and construction). Research on our project began in May 2019 and is expected to be completed in March 2020. During the span of our research, we analyzed a wide selection of scientific papers detailing the fabrication processes, chemical and physical properties, and history of aerogel. To supplement our research, we performed live experiments (with the assistance of our AP Chemistry teacher) on a small monolith sample we purchased online. In one test, we placed the aerogel on a metal ring fixed to a stand above a Bunsen burner, lighted the burner, and then placed a match on top of the aerogel (the match remained unlit, demonstrating the material’s extraordinary heat-insulating capability). Though our poster seeks, in part, to exhibit our experience in the classroom in research and experimental design in the field of materials science, it most importantly seeks to instill within the viewer a curiosity and awe for the highly promising future of this novel material.","PeriodicalId":355861,"journal":{"name":"2020 IEEE Integrated STEM Education Conference (ISEC)","volume":"12 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":"123292801","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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