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AC 2011-456: IPHONE/IPAD BASED INTERACTIVE LABORATORY FORSIGNAL PROCESSING IN MOBILE DEVICESJinru Liu, School of ECEE, SenSIP Center, Arizona State UniversityJayaraman J Thiagarajan, School of ECEE, SenSIP Center, Arizona State UniversityProf. Andreas S Spanias, Arizona State University, ECEE, SenSIP Center Andreas Spanias is Professor in the School of Electrical, Computer, and Energy Engineering at Arizona State University (ASU). He is also the founder and director of the SenSIP center and industry consortium (NSF I/UCRC). His research interests are in the areas of adaptive signal processing, speech processing, and audio sensing. He and his student team developed the computer simulation software Java-DSP (J- DSP - ISBN
10expect more than 40% of their courses to be blended18 by 2013.The third, on-line approach is essentially the computer and network-enabled transfer of skills andknowledge. In on-line learning, content is delivered via the Internet, audio or video tape, etc.,and includes media in the form of text, image, animation, streaming video and audio. By 2006,3.5 million students were participating in online learning at institutions of higher education in theUnited States.19 According to the Sloan Foundation reports, 20, 21 there has been an increase ofaround 12–14 % per year on average in enrollments for fully online learning over the five years2004–2009 in the US post-secondary system, compared with an average of approximately 2%increase per year in
Fellow of Biomimicry Institute. He has over 20 years of industrial, academic & entrepreneurial experience. Before joining Cal Poly Pomona, I also served as a faculty at Rowan University, NJ and Kettering University, MI. He is passionate about education and focuses on K-16 and STEM education. He writes columns for Huffington Post on issues related to K-12 & higher education.Dr. Paul Morrow Nissenson, California State Polytechnic University, Pomona Paul Nissenson (Ph.D. Mechanical & Aerospace Engineering, University of California, Irvine, 2009) is an Assistant Professor in the Department of Mechanical Engineering at California State Polytechnic University, Pomona. He teaches courses in fluid mechanics
of two lab sections.• Limited lab access: Students may only use equipment during scheduled lab times.• Limited resources to support students outside labs and the classroom: In many cases, no lab assistant support is available.• Limited equipment to support lab assignments: Because lab equipment is often expensive, students must often work in groups. For example, an industrial scale PLC—such as an Allen Bradley RSLogix 5550 processor and a set of I/O cards—costs about $8000. Page 13.779.2To help offset these obstacles, in recent years, a variety of computer and networkingtechnologies have been developed. For example, remote
, Page 25.938.3competitions, publications, and resources for students, parents, educators and professionalengineers. Table 1 shows a listing of engineering professional societies. The computer scienceand engineering technologies societies are included in this table because the computer scienceand engineering technology programs are often housed in the college of engineering. The tablealso includes architecture, because students may want to explore the differences between thisdiscipline and construction or civil engineering. Table 2 lists the engineering related honorsocieties. Table 3 lists other engineering-related societies, including science, mathematics,medical, and education societies. Table 4 lists engineering, technology, science and
delivered in a standardized way.Rieber [20] has shown, how animation can be beneficently integrated into the educationalprocess, providing recommendations for several different disciplines and Lawrence et al. [21]showed the effectiveness of animating algorithms for teaching. In the field of systemprogramming, there also exist work for animating different parts of an operating system, e.g. byJones and Newman [22], Suranauwarat [23], Kotainy and Spinczyk [24], and Zareie andNajaf-Zadeh [25]. They all provide animations for the different computer system components,visualizing the algorithmic behaviour, but lack on providing the dynamic relationships betweenthese components.Within this project, we therefore develop an extensive simulation framework
station viaconveyor belts. After preparation, the base parts and the outsourced shade parts are sent toassembly stations to be assembled. The assembled table lamps are then packaged and sent toshipping. The system includes inventories for the base part raw material and the outsourcedshades.The simulation model can be run on a regular computer where students can navigate through themodel, collect data such as the table lamps demand, processing times, and percentage ofdefective table lamps, observe the animation and the system performance measures, and makechanges to some of the system’s parameters such as the capacity of the resources and inventorypolicy. In addition, the model can be run on an Oculus Quest or Rift S virtual reality (VR)headsets
Paper ID #36761Work-in-Progress: Rapid Development of Advanced VirtualLabs for In-Person and Online EducationYiyang Li Yiyang Li received her B.S. degree Henan University of Economics and Law, Zhengzhou, China, in 2018, the M.S. degree from Old Dominion University, Norfolk, VA, in 2021. She is currently in her first year of her Ph.D. in Old Dominion University. From 2013 to 2015, she was a Senior Modeler, Rigging Technical Director, and group manager at Shiwei Animation, Luoyang, China. Her current research interests are computer-based learning tool development and virtual environment.Yuzhong Shen Yuzhong Shen
Outcomes: • Enhance creativity through the creation of a relevant and appropriate presentation. • Practice a systematic design process. • Design presentation with your audience in mind. • Create activities to stimulate audience interest and involvement. • Assess presentation (following classroom interaction) while focusing on strengths, areas of improvements, and insights gained. • Apply and strengthen Thermodynamic knowledge through teaching others. • Improve communication abilities through written, verbal, and graphical means. • Strengthen teamwork abilities.Scope and Details: • Design a presentation/demonstration for an identified target audience. • Create a relevant, interesting talk. • Include computer simulations
software applications (apps) is generating interest in several areas includingeducation. An increasing number of students and faculty are using smart phones and tablets toobtain content, books and other tools for their classes. To that end there have been reports thatsmart phones and tablets are being used more than computers by college students1. Althoughsome apps have been ported to mobile platforms including the mobile blackboard (mobile BB),the iOS Java-DSP8 (i-JDSP) mathematical simulations, and YouTubeTM education channels12,there are both technical deficiencies and lack of assessment. Technical issues include theinability of these apps to operate in a collaborative and seamless manner with regard toaccessibility, sharing of data, and
courses resumed in 2018.Description of EE110EE110 consists of basic electronics and weekly lab assignments. The introductory courseattempts to prepare students who will be entering either the electrical or computer engineeringprograms. Table 1 shows the deployment ofweekly F2F lab assignments.The College of Engineering recognized onlinelab assignments will be the challenging part ofthe program curriculum [3]. This insight wasverified and validated during a pilot programwhen the flipped classroom was implementedto mimic the online synchronous chatsessions. In this case, when students met inthe classroom, it simulated the online chatsession in two areas: (1) one chat session wasfor addressing student questions on the multimedia content, readings
is a co-founder of zyBooks.com.Prof. Roman Lysecky, University of Arizona Roman Lysecky is a Professor of Electrical and Computer Engineering at the University of Arizona. He received his Ph.D. in Computer Science from the University of California, Riverside in 2005. His research interests include embedded systems, runtime optimization, non-intrusive system observation methods, data-adaptable systems, and embedded system security. He has recently coauthored multiple textbooks, published by zyBooks, that utilize a web-native, interactive, and animated approach, which has shown notable increases in student learning and course grades. c American Society for Engineering Education, 2019
]. However, there are no examples of 3D visualization assistedteaching methods for EM theory. Computer visualization teaching techniques described for EMtheory in literature are actually limited to traditional 2D viewing settings (such as MATLABcodes demonstrating EM waves [7] and web-based applications that present concepts such asmagnetic fields [8]).Different than the existing approaches, our goal is to employ 3D visualization of EM fields tofacilitate student learning of complex mathematical concepts and several engineeringapplications of the EM physical phenomena. Specifically, students are presented with customdeveloped visualization scenes that are rendered in real-time and can be animated/modified on-demand with student/instructor input
Paper ID #21417Design of a Virtual Laboratory for Automation ControlMr. Zelin Zhu Zelin Zhu is a Software Development Engineer at ESRI in Redlands, California, USA. He holds dual master’s degrees in Electrical and Computer Engineering, and Modeling, Simulation and Visualization Engineering respectively from Old Dominion University and a bachelor’s degree in Electrical Engineer- ing and Automation from Nanjing University of Posts and Telecommunications. He is the first generation Microsoft HoloLens developer. His research interests include virtual reality and mobile application de- velopment.Prof. Yuzhong Shen, Old
Paper ID #33585Combining Immersive Technologies and Problem-based Learning inEngineering Education: Bibliometric Analysis and Literature ReviewMahgol Nowparvar, Pennsylvania State University Ms. Mahgol Nowparvar is a graduate student continuing her education in the field of data analytics at Penn State Great Valley. Ms. Nowparvar received her B.S. degree in Applied Mathematics from University of Wisconsin in May of 2020. Her interest is in simulation modeling using quantitative and qualitative analysis.Mr. Xing Chen, Pennsylvania State University Xing Chen is an undergraduate researcher and a BS in Computer Science major
students needed to do assigned tasks, including: watch videos, doassigned readings and homework, and do weekly quizzes before coming to class. Otherwise,they may have trouble doing the weekly lab experiments. Table 4 lists the lab assignments foreach week. When they came to class, there were no hour-long lectures in EE110. Classroomtime was reserved to address student questions on the multimedia content, homework or labassignments. Week # Lab Assignments Week01 Circuits Laboratory Introduction Week03 Digital I/O Circuits Week04 Basic Gates Verification Week05 Digital Simplification Week06 Ohms Law Week07 Complex Circuit Analysis Week08 RC Circuits Multisim Simulation Week09
registration information.An automated interactive online course can accompany the VE and serve as the backbone of thelearning environment (Figure 3). The course is delivered using text-to-speech technology bynear-photorealistic animated virtual tutors5. The course is organized into a hierarchical treeoutline of topics. The multimedia course items include pictures, movies, Flash animations,interactive Flash simulations, and virtual reality models to enhance the learning experience6. Atthe end of every course topic, the students are presented with a series of questions to test theircomprehension of the material that was covered (Figure 4). Based on how the student scores inthe post-topic questions and exercises, the tutor can either suggest that the
Paper ID #23210A Wearable Electrocardiograph as a Means to Combine Measurement andMakerspace Concepts in a Biomedical Instrumentation Course SequenceDr. Steve Warren, Kansas State University Steve Warren received a B.S. and M.S. in Electrical Engineering from Kansas State University in 1989 and 1991, respectively, followed by a Ph.D. in Electrical Engineering from The University of Texas at Austin in 1994. Dr. Warren is a Professor in the Department of Electrical & Computer Engineering at Kansas State University. Prior to joining KSU in August 1999, Dr. Warren was a Principal Member of the Technical Staff at Sandia
bothengineering degree and non-engineering degree learners, (2) provide personalized learning, (3)enable continuous and lifelong learning for an array of specialized topics, (4) and offer up-to-date content anywhere, anytime, and to anybody.20 Engineering classrooms have infusededucational technology through web-based course modules that enhance instruction,19 and alsothrough animations and simulations.13Pveducation.org Pveducation.org was originally developed as a CDROM resource, providing learnersinterested in photovoltaics access to an electronic photovoltaics text book. It fulfilled a niche; asuccinct and comprehensive resource for photovoltaics content was originally hard to come by.Since its original form, the content has been uploaded and
animals in elementary school. In 2012 7th Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1–6).[3] Braun, V., &Clarke,V.(2006). Using thematic analysis in psychology. Qualitative research in Psychology.[4] Bujak, K. R., Radu, I., Catrambone, R., MacIntyre, B., Zheng, R., & Golubski, G. (2013). A psychological perspective on augmented reality in the mathematics classroom. Computers & Education, 68, 536–544. doi:10.1016/j.compedu.2013.02.017[5] Chang, Y.-J., Chen, C.-H., Huang, W.-T., & Huang, W.-S. (2011). Investigating Students’ Perceived Satisfaction, Behavioral Intention, and Effectiveness of English Learning Using Augmented Reality. In Proceedings of the 2011 IEEE
Paper ID #23732Implementation of a 3D Interactive Mobile App for Practicing EngineeringLaboratory ExperimentMr. Shuo Ren, Old Dominion University Shuo Ren is a PhD Candidate and Research Assistant in the Department of Modeling, Simulation, and Visualization Engineering at Old Dominion University in Norfolk, Virginia, USA. He holds a M.S. in Modeling, Simulation and Visualization Engineering from Old Dominion University and a B.S. in Elec- trical Engineering from Virginia Tech. His research interests include virtual reality, immersive learning and human-computer interaction.Mr. Zelin Zhu, Old Dominion University Zelin
publication at the level appropriate for each target audience),the PowerPoint presentations for the topic, the teaching notes including instructions on themotivation of the topic, descriptions of active-learning exercises that can be conducted during thelecture, example quizzes, and the evaluation surveys to be completed at the end of the module. Inaddition, laboratory exercises and simulations (Flash and Java animations) are beingincorporated into the module.Examples of Knowledge and Application Module DescriptionsIn this section we offer two examples: one KM and one AM. These and other modules will beevaluated during the Spring 2010 semester in our Nanophotonics EE 459 course using methodswe have developed previously [5-6].KM: Plasmonics
simulation with the proposed dimensions,and (iv) open-ended questions about other possible causes and alternative solutions i ii iii ivFigure 3. Snapshots of the FD case study showing (i) the desalination plant with the inlet/outletpipe systems, (ii) the pump power determination for the inlet system, (iii) the relation betweenpipe/pump costs and inlet pipe diameter, and (iv) plot of pressure in the inlet system used todetermine danger of pipe cavitation and bursting. i
, virtual methodsemploy computer-based techniques such as 3D animations and simulations, virtual reality andaugmented reality tools 11 .Project DescriptionIn this project, we employed a tangible training model using the augmented reality technology tosupport students in enhancing their spatial skills. Augmented reality is a technology that allowscomputer-generate imagery (text, images, 3D models etc.) to be overlaid onto a live video streamof a real-world environment 12 . In AR, the real environment is extended with information andimagery coming in real-time from the mobile phone or tablet. The AR application monitors thecamera stream constantly to detect and track the marker (or target) image. As soon as it detectsthe marker image in real-world
offer power engineeringcurriculum at the undergraduate level, commonly use computer aided simulation techniques toenhance laboratory teaching. The use of a computer aided simulation package like PowerWorldis very effective at helping students learn the complex processes involved in power systemplanning. PowerWorld Simulator is a powerful visualization tool; the animation capabilities helpthe students understand the complexity of the power-flow problem.Students, in general, lose interest in a course that focuses entirely on computer simulationtechniques and computer software. Consequently at CSM, we have taken a very differentapproach to developing our Advanced Energy Systems Laboratory. A special feature of ouradvanced laboratory is the
lives.IntroductionTablet PCs are the latest technology in portable computing. Featuring pen-based entry where theuser writes “digital ink” directly on the computer screen, Tablet PCs typically offer thefunctionality of a laptop or notebook with less weight and added benefits. They are gainingacceptance in K-121,2 as well as college classrooms both for faculty presentations and studentnote-taking.3,4 In this paper, we are interested in the use of the Tablet PC for instructors in theirclassroom lectures. Tablet PCs offer numerous attractive features for faculty such as capturingcontent for instructor review, providing handouts for students, ability to incorporate multimediafeatures such as simulations, websites, or images, generating excitement among students by
animations in Pentagon, Associative Law and Sine Function components weredesigned to attract students’ attention and to provide striking displays of when and how errorsoccur. The colors were selected to easily track different computations. Students can save theresults of computations into *.txt or *.csv files for further studying with external tools orsoftware. They can choose their preferred colors in each component for differentiation andtracking.In the following subsections, we describe in detail each individual component and itsimplementation.3.1 Roots ComponentSolving a quadratic equation is a common problem in many fields of science and engineering.However, rounding and cancellation may affect the results5. Roots demonstrates their effect
the user front panels; e) linking to other availablesystems or software; f) inclusion of passwords to limit the access; g) animating the systemoperation; h) providing GUI that mimics the real instruments; and, i) playing a video10-13.Figure 1 illustrates a sample front panel of LabVIEW virtual instrument, and a sample blockdiagram that shows the simulation of a motor control drive in LabVIEW. As can be seen inFig. 1b, the modularity of LabVIEW programming allows the designer to simplify theprogramming structure by using sub-virtual instruments, which may require thousands oflines of codes in other programming software tools. The full-development LabVIEWsoftware comes with a number of additional tools that provide some exceptional features
between the master and remote computers will be secure and cannot be compromised.4. Integrate a solar position algorithm into the master controller computer so that the azimuth and elevation position of the Sun can be determined for any location on the Earth given that location’s current time, latitude and longitude. This information will be transmitted to the remote controller computer to adjust the remote solar tracker to the current Sun’s position in the sky relative to the remote location on the Earth.5. Simulate the physical hardware of the solar tracker by using animated computer software. The simulation will be used to test the operation of the whole system.6. This work has an educational value towards understanding the algorithm