al., Editors. 2010, Springer Berlin / Heidelberg. p. 216-227.4. Soldani, D., M. Li, and R. Cuny, QoS and QoE management in UMTS cellular systems. 2006, Chichester: John Wiley and Sons. xxvii, 459 p.5. Kilkki, K., Quality of Experience in Communications Ecosystem. Journal of Universal Computer Science, 2008. 14(5): p. 615-624.6. Kist, A.A., A Framework to Evaluate Performance from an Application and User Perspective, in 2011 Australasian Telecommunication Networks and Applications Conference (ATNAC 2011) 2011: Melbourne, Australia.7. Brooks, P. and B. Hestnes, User measures of quality of experience: why being objective and quantitative is important. Network, IEEE, 2010. 24(2): p. 8-13.8
IEEE Multimedia Communications Technical Committee. He obtained the Ph.D. from the Department of Electrical Engineering at Stanford University.Prof. Thomas J. Hacker, Purdue University, West Lafayette Thomas J. Hacker is an Associate Professor of Computer and Information Technology at Purdue Univer- sity in West Lafayette, Indiana. His research interests include cyberinfrastructure systems, high perfor- mance computing, and the reliability of large-scale supercomputing systems. He holds a PhD in Computer Science and Engineering from the University of Michigan, Ann Arbor. He is a member of IEEE, the ACM, and ASEE.Dr. Carla B. Zoltowski, Purdue University, West Lafayette Carla B. Zoltowski, Ph.D., is Co-Director of
the vice president of Purdue Billiards Club since 2015.Mr. Zhuofan LiMr. Yudi WuDr. Carla B. Zoltowski, Purdue University Carla B. Zoltowski is an assistant professor of engineering practice in the Schools of Electrical and Com- puter Engineering and (by courtesy) Engineering Education at Purdue University. She holds a B.S.E.E., M.S.E.E., and Ph.D. in Engineering Education, all from Purdue. Prior to this she was Co-Director of the EPICS Program at Purdue where she was responsible for developing curriculum and assessment tools and overseeing the research efforts within EPICS. Her academic and research interests include the profes- sional formation of engineers, diversity and inclusion in engineering, human-centered
, 2011 618.70 823.48 Huntsville Vernal Equinox March 20, 2011 455.89 707.50 Huntsville Summer Solstice June 21, 2011 630.25 825.62 Huntsville Autumnal Equinox September 23, 2011 455.18 706.81 Huntsville Winter Solstice December 22, 2011 192.31 461.42 Table 4. The average amount of solar energy produced at Morogoro and Huntsville.Figure 4-1 (a) and (b) show the simulated solar energy collection versus time at Huntsville on thesummer solstice day, June 21, 2011. Similar trends, but of course different magnitude plots weregenerated for Morogoro and all other days. Table 4 lists the average value over the day lightperiod at
potential end userswho are the clients‟ representatives.Assessment of Team Project EffectivenessBoth formative and summative assessment techniques were utilized to assess the effectiveness ofthe project. Formative assessment included the bi-weekly managerial report see Appendix A ,managerial and team members‟ performance evaluations see Appendix B and C, timelines andgroup member‟s logs see Appendix D. In addition the instructor conducted interviews with thestudents on their perceptions of learning, collected by student performance and managerialreports and a Lessons Learned report. These instruments were used to obtain feedback on theteam project. Summative assessment focused on the grading of the final project including allsupporting materials of
the release of failure data. A more pragmatic approach for the purposes ofcontrasting cable reliability is to explore the actual causes of failure in cable.IV. Economies of Fiber Optic vs. Copper NetworkThe question must be asked, if fiber optic cable is so much more effective and reliable attransmitting data, why have telecommunication network providers adopted its use in every singlepossible area? The answer has much more to do with economics of network operations than itdoes in the effectiveness of it. It is simply not cost effective to deploy a Fiber to the Page 25.1300.3Home/Business (FTTH/B) end to end fiber optic network.As an example
the robot around. Tomove the robot, every button is assigned with an action listener and when they are pressed thecommand is send to the robot which has also been implemented using LEJOS API. Beforemoving the robot, the actuators of the robot needs to be initialized. As our robot has threemotors- A, B, C which are marked as left, right and back motors and all three motors needs to beinitialized before moving. left = con.ev3.createRegulatedMotor("A", 'L'); right =con.ev3.createRegulatedMotor("B", 'L'); back = con.ev3.createRegulatedMotor("C", 'L');After that, the robot is moved in different directions as follows © American Society for
are analyzed. Listed in thefollowing are the articulated benchmarks set to evaluate the attainment of each programoutcome:Metric 1: The percentage of the IT 495 students who receives a grade of 2 or higher (out of 3point) on the learning statements and supporting evidence for the designate program outcome.Metric 2: The percentage of the students who receive a grade of B or higher on two selectedcourse embedded assessments that measure the related program outcome. Page 23.1299.6Metric 3: The mean of the graduates’ perceptions of their achievement of the related programoutcomes (data collected from the exit survey).Metric 4 (Reference): The mean of
into a digital image. An RGB digital camera is commonly used for image acquisition especially if the desired object has a color contrast with respect to the background. Some applications require a special image acquisition system like a thermal camera or an infrared camera8. 3. Image processing acts as the brain of the machine vision and is typically composed of pre-processing, segmentation, and feature extraction. a. Pre-processing – modify and prepare the raw image to produce an image data that is suitable for subsequent operation. An example is increasing the intensity of the image pixels. b. Segmentation - the desired object is differentiated from the background. The
should demonstrate the following learning outcomes out of the course outcomes: a. Provide an understanding of how a computer draws the fundamental graphics primitives - lines and filled polygons in both 2-D and 3-D. b. Use the facilities provided by a standard API to express basic transformations such as scaling, rotation, and translation. c. Implement simple procedures that perform transformation and clipping operations on a simple 2-dimensional image. d. Discuss the 3-dimensional coordinate system and the changes required to extend 2D transformation operations to handle transformations in 3D. e. Explain the concept and applications of each of these techniques
monitors using the discussion threads. Students are instructedto first search the discussion board when they experience a problem with the lab because the sameproblem and its solution may already be posted.Discussion board thread samples:This section shows some samples of the discussion board threads that students’ use to discussany issues or seek support from the instructors or their class mates. Lab Access Discussion Forum: Ethernet Cable Unplugged in VM. Lab A Discussion Forum: Lab 2.1 Step 3 - Problems Downloading eicar.com File. Lab B Discussion Forum: Lab 6.3 - Can't generate certs. Lab C Discussion Forum: Lab 7.2 - WinRM Prevents Web Server IIS. Lab D Discussion Forum
. Boston: Academic Press, 2011.3. Bird, Robert. B.; Stewart, Warren E.; Lightfoot, Edwin N. Transport Phenomena, 2 nd edition. New York:J. Wiley, 2002.4. Borgnakke, Claus; Sonntag, Richard E. Fundamentals of Thermodynamics, 7 th edition. J. Wiley, 2008.5. Çengel, Yunus A.; Boles, Michael A. Thermodynamics an Engineering Approach, 6 th edition. NewYork: McGraw-Hill, 2008.6. Çengel, Yunus A.; Cimbala, John M.; Turner, Robert H. Fundamentals of Thermal-Fluid Science,4thedition.New York: McGraw-Hill, 2012.7. Çengel, Yunus A.; Cimbala, John M. Fluid Mechanics: Fundamentals and Applications, 2 nd. McGraw-Hill, 20108. Çengel, Yunus A.; Cimbala, John M. Fluid Mechanics Fundamentals and Applications, 3 rd edition.McGraw-Hill, 2013.9. Chi, M.T.H. (2005
laboratoryforteachingcomputernetworks.PaperpresentedattheOptimizationofElectrical andElectronicEquipment(OPTIM),201213thInternationalConferenceon.Fanelli,R.L.,&O’connor,T.J.(2010).Experienceswithpractice-focusedundergraduatesecurity education.PaperpresentedattheProc.ofthe3rdWorkshoponCyberSecurityExperimentation andTest,Washington,DC.Ferguson,B.,Tall,A.,&Olsen,D.(2014).NationalCyberRangeOverview.Paperpresentedatthe MilitaryCommunicationsConference(MILCOM),2014IEEE.Gavas,E.,Memon,N.,&Britton,D.(2012).WinningCybersecurityOneChallengeataTime.Security& Privacy,IEEE,10(4),75-79.Hoffman,L.,Burley,D.,&Toregas,C.(2012).HolisticallyBuildingtheCybersecurityWorkforce.Security &Privacy,IEEE,10(2),33-39.Justice,C.(2015,November3-5,2015
. Page 23.818.95. Davies, N. and Gellersen, H.-W. Beyond Prototypes: Challenges in Deploying Ubiquitous Systems. IEEEPervasive Computing(January-March 2002 2002).6. Edwards, S., Lavagno, L., Lee, E. A. and Sangiovanni-Vincentelli, A. Design of embedded systems: formalmodels, validation, and synthesis. Proceedings of the IEEE, 85, 3 1997), 366-390.7. Lunt , B. M., Ekstrom, J. J., Gorka, S., Hislop, G., Kamali, R., Lawson, E. A., LeBlanc, R., Miller, J. andReichgelt, H. Information Technology 2008: Curriculum Guidelines for Undergraduate Degree Programs inInformation Technology. ACM, IEEE-CS, 2008.8. Times, E. Embedded Market Study 2011. City, 2011.9. Anderson, L. W., Krathwohl, D. R. and Bloom, B. S. A taxonomy for learning, teaching, and
informative thus leading to reliable, safeand secure design of CPS in the near future.REFERENCES1. B. M. Mckay and P. A. Engineer, “Best practices in automation security.” Cement Industry Technical Conference, 2012 IEEE-IAS/PCA 53rd, pp. 1 - 15, 2012.2. N. Adam, "Workshop on Future Directions in Cyber-Physical Systems Security ", in Report on Workshop on Future Directions in Cyber-Physical Systems Security, January, 2010.3. B. Miller and D. Rowe, “A survey SCADA of and critical infrastructure incidents,” in Proceedings of the 1st Annual conference on Research in information technology - RIIT ’12, p. 51, 2012.4. ENISA, “Protecting Industrial Control Systems,” 2011.5. B. Schneier, “All Security Involves Trade-offs
’ actions and interact with them in the samelinguage that is used in social networks and from marketing systems focused in observe users behavior. Page 26.1044.6 B. Scenario II: In this second scenario, a virtual video lecture was administered to the students in a subject obligatory to all engineers, all basic Science classes in a Computer Science Course with an explanation of a theme of medium complexity, all in the form of a video in which the student could follow the material via power point slides. The theme of the class was the area of complex networks and the class evaluated in this example dealt with modeling
. (1991). Writing in the academic disciplines, 1870-1990: A curricular history. Carbondale, IL:Southern Illinois UP.8 Emig, J. (1977). Writing as a mode of learning. College Composition and Communication, 28, 122-128.9 Butler, D. & Winne, P. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educa-tional Research, 65, 245-281.10 Paretti, M. C. (2011). Theories of Language and Content Together: The Case for Interdisciplinarity. Across theDisciplines, 8(3).11 Paretti, M. C. (2009). When the Teacher is the Audience: Assignment Design and Assessment in the Absence of“Real” Readers, in Engaging Audience: Writing in an Age of New Literacies, A. Gonzalez, E. Weiser, and B. Feh-ler, Editors. 2009, NCTE Press
% 0.0% A B C D FFigure 13: Grade Distribution Between Flipped (n=27) and Non-Flipped (n=21) Course Sections Page 24.181.16Comparing the grade distribution of only summative assessments between the flipped and non-flipped courses might provide a more specific comparison, as shown in Figure 14. Flipped Classroom Non-Flipped Classroom 51.9% 52.4% 38.1% 25.9% 14.8% 7.4% 4.8
v3 requiredknowledge of IT professionals and support by management. Adopting and implementing aprescribed process model such as ITIL v3 depends on several factors such as leader’s supportand commitment, IT professional knowledge, and a joint business IT plan involve stafftraining. This study confirmed that successful ITIL adoption requires both business leadersand IT leaders to work together to form a joint plan that most suitable and benefits theorganization.References1. Andersen, B., & Fagerhaug, T. (2001, August). Advantages and disadvantages of using predefined process models. Proceedings from International Working Conference on Strategic Manufacturing, Aalborg, Denmark. Retrieved from http://www.prestasjonsledelse.net
clustering. The document sethas been simplified to only have 2 different words in each document. The values on the X and Yaxes are the word weights of those two words in the documents. Figure 5a shows the documentsarranged on 2-dimensional grid without any clustering information applied. Figure 5b and 5cdiffer in that the documents have been colored and circled to designate the different clusterswithin the set of documents. Figure 5b has been clustered using the K-means algorithm, while Page 25.1012.12with Figure 5c our genetic algorithm is used to find a clustering solution. Figure 5 a) Documents without clustering (left), b) K-means Clustering
collaborativeeffort between FIU, Florida A&M University (FAMU), Miami University (MU) and NorthDakota State University (NDSU) [13]. The NSF Course, Curriculum, and LaboratoryImprovement (CCLI) Phase I project (first version of WReSTT) had the following objectives: (a)create learning materials on testing tools, (b) increase the number of students who have access totesting tool tutorials, and (c) train instructors on how to use testing tools and WReSTT in theclassroom. WReSTT Home Page Testing Course
24.638.74. van den Berg-Emons, H. J. G., Saris, W. H. M., de Barbanson, D. C., Westerterp, K. R., Huson, A., & van Baak, M. A. (1995). Daily physical activity of schoolchildren with spastic diplegia and of healthy control subjects. The Journal of Pediatrics, 127(4), 578–584.5. Betker, A. L., Szturm, T., Moussavi, Z. K., & Nett, C. (2006). Video game–based exercises for balance rehabilitation: A single-subject design. Archives of Physical Medicine and Rehabilitation, 87(8), 1141– 1149.6. Bjornson, K. F., Belza, B., Kartin, D., Logsdon, R., & McLaughlin, J. F. (2007). Ambulatory physical activity performance in youth with cerebral palsy and youth who are developing typically. Physical Therapy, 87(3
These 2 equations are put in standard form: 9V1 – 4V2 = -280 V1 – 2 V2 = 35 With solutions obtained as V1 = -50 V , V2 = -42.5 V .At this time it is pointed out that the system of equations above can be put in matrix formAX = B and solved, for example, using Matlab:>> % Nodal Analysis, Spring 2017>> A=[9 -4;1 -2];>> B=[-280;35];>> inv(A)*Bans = -50.0000 -42.5000>>Once node voltages are computed, students can check the balance of power:Absorbed powers:P5Ω = 11.25 W (this is the 5Ω between nodes 1 and 2)P’5Ω = 361.25 W (the 5Ω resistor between node 2 and the ground)P4Ω = 625 WΣ Pabs. = 997.5 WP14A = (-14
in four main categories –system level design for the mobile platform (Android);API level security analysis (PID recognition); reverse engineering based security analysisincluding both static and dynamic analysis; traffic engineering. Table I. shows the overall list ofcurrent mobile computing labs and security analysis labs related to mobile and pervasivecomputing in the past two years. Each lab will be introduced in the following subsections. Eachlab contains the objectives, description, steps, and some sample code segments. Some labs had Figure 2. Snapshots for the information collection (a) and phone make lab (b)been updated based on past implementation.Information Collection Android AppThis is an Android app
sufficient online support provided by Google 1. Less robust network 1. Operating system is developing Disadvantages 2. Application development is not 2. Not very accurate touch screen open 3. Applications are not as diversified as Apple Store * evaluated early 2010 Page 22.927.3 (a) (b) Figure 1. Design of the interface for new Mobile technology application: (a) interface for the whole College of
effectiveness of the course contents and their placements in the framework. Bibliography 1. Armburst, A. Fox, R. Griffth, A.Joseph, R.Kaltz, G. Lee, D. Patterson, A. Rabkin, and M. Zaharia. “Above the Clouds: A Berkeley View of Cloud Computing”. http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS 200928.pdf 2. Escalante, B. F. (2010). “Cloud Computing Fundamentals”. In Handbook of Cloud Computing. Springer link. 3. Delic Walker. “Emergence of the academic computing clouds”. ACM publications, August 2008. http://portal.acm.org/citation.cfm?id=1414664 4. M. Chowdhury. “Cloud Computing: Facts, Security, & Challenges.” http://www.aipath.com/mchowdhury_law447b.pdf 5. Dias Marcos, Alexdandre, Buyya. “Evaluating the cost
&MUniversity (FAMU) [5]. The NSF Course, Curriculum, and Laboratory Improvement(CCLI) Phase I project had the following objectives: (a) create learning materials ontesting tools, (b) increase the number of students who have access to testing tool tutorials,and (c) train instructors on how to use testing tools and WReSTT in the classroom.WReSTT-CyLE is a NSF Transforming Undergraduate Education in Science (TUES) IIproject that aims to provide a cyberlearning environment that facilitates the improvementof students’ conceptual understanding and practical skills in software testing. The maingoals of this project are to create new learning materials and develop faculty expertise tosignificantly increase the number of undergraduate students that
locations and display similar locations. a) b) Figure 6: False detections of small landmarks on top of large landmarks. Although three main large landmarks are taken inside bounding boxes, many unnecessary small landmarks also appear inside large landmarks. a) Surface image, b) ROIs drawn on imageLRO imagery was retrieved from [18]. The multi-resolution Reduced Data Records (RDR) forthe LROC were downloaded as they provide preprocessed projected mosaics at relatively highresolution suitable for our study. An imagery pre-processor was developed, using GDAL andOpenCV, to construct image pyramids from the LRO imagery, suitable for display using WorldWind. Each tile in the pyramid is then
Paper ID #15358Leveraging Online Lab Development: A New Paradigm to Offer EducationalLab Infrastructure as a Cloud ServiceDanilo Garbi Zutin, Carinthia University of Applied Sciences Danilo G. Zutin is currently a Senior Researcher and team member of the Center of Competence in Online Laboratories and Open Learning (CCOL) at the Carinthia University of Applied Sciences (CUAS), Vil- lach, Austria, where he has been engaged in projects for the development of online laboratories, softtware architectures for online laboratories and online engineering in general. Danilo is author or co-author of more than 30 scientific papers
(the post-test surveys were different for the two groups).Both sections received three weeks worth of instruction on sorting and hashing, and then bothsections took the identical test.The pre-survey from both groups measured a) students’ experience with online tools, content,and assessment, b) students’ perceptions of their learning in a face-to-face course compared withonline/Web-based instruction, c) students’ experience with using technology or e-textbook as itrelates to accomplishing course work, and d) students’ preference for lecture courses versuscourses given in a lab setting.The post survey from the treatment group measured students’ perception, enjoyment, and satis-faction with the OpenDSA modules, as well as their preference for