the Electrical Engineering section. Mr. Howie has worked ex- tensively in Information Assurance, Cyber Security, Information Technologies and Communications Sys- tems.Mr. Benjamin B Hannon, USCGA Benjamin Hannon is currently a cadet at the United States Coast Guard Academy and will be graduat- ing this May (2015). He is an Electrical Engineering Major and upon graduation, will report to USCGC RICHARD PATTERSON in San Juan, PR. He was born in Annapolis, MD and was a graduate of Broad- neck High School. Benjamin enjoys running Track and Field.Nicholas Williamson, United States Coast Guard Academy I am a cadet at the Coast Guard Academy graduating this year, 2015, and I am interested in being an active member of
afirst-year course. We believe that the pedagogical process used in this course is transferable toother educational contexts.References: 1. Allen, D., Allenby, B., Bridges, M., Crittenden, J., Davidson, C., Hendrickson, C., Matthews, S., Murphy, C., and Pijawka, D. (2008), Benchmarking sustainable engineering education: Final report. EPA Grant X3-83235101-0. 2. Wiggins, J., McCormick, M., Bielefeldt, A., Swan, C., and Paterson, K. (2011), “Students and sustainability: Assessing students’ understanding of sustainability from service learning experiences”, paper presented at the 2011 Annual American Society of Engineering Educators (ASEE) Conference and Exposition, 26-29 June 2011, Vancouver, Canada
follows [3]: 1. The Cloud Provider signs VM with its own private key. 2. The Cloud Provider sends the signed VM to the Verification Engine. 3. The Cloud Provider sends the public key to the Cloud Consumer. 4. The Cloud Consumer sends the public key to the Verification Engine. 5. The Verification Engine verifies the authentication of VM template. Figure 2. VM template authentication using digital signaturesThe potential issues of this approach are: a) The Cloud Provider needs to protect private key from unauthorized use and disclosure. b) The Cloud Provider needs to provide its own public key in a trusted way to each Cloud Consumer. c) The Cloud Consumer needs to protect private key from
]. It can also be used in Python scripts, web applications servers, or in combination with several GUI toolkits. 5. Example Compared with NumPy there is a colossal list of things one can do with SciPy. The following listing is what we use SciPy for in this instance. import numpy as np from scipy.fftpack import fft import matplotlib.pyplot as plt N = 600 T = 1.0/800.0 x = np.linspace(0.0, N*T,N) a = np.sin(50.0 * 2.0*np.pi*x) b = 0.5*np.sin(80.0 * 2.0*np.pi*x) y = a + b yf = fft(y) Y = 2.0/N * np.abs(yf[0:N/2]) X = np.linspace(0.0, 1.0/(2.0*T), N/2) import matplotlib.pyplot as plt plt.plot(x,y
its ability to: (a) collect detailed information from facultyregarding the projects they are offering, (b) present the projects to the students in a media-richand sortable format, and (c) solicit student preferences and accurately record project preferences.As a result, majority of the tasks that were managed by each engineering discipline wereeliminated and replaced by an automated process that ensured accuracy and consolidated pastmultiple data streams. It is envisioned, the current platform will necessitate limited interventionfrom faculty to yield a fair and satisfactory college-wide assignment output; preferably entirelyeliminating the need for discipline-managers. In the past, discipline-managers devotedsubstantial effort towards the
. V. Oorschot, and S. A. Vanstone, Handbook of Applied Cryptography, CRC Press, 1996.11. D. B. Nasr, H. M. Bahig, and S. S. Daoud, Visualizing Secure Hash Algorithm (SHA-1) on the Web, Proceedings of the 7th International Conference on Active Media Technology, pages 101-112. 2011.12. A. Salomaa, Public-Key Cryptography, Springer-Verlag, 1992.13. Schneier, Applied Cryptography: Protocols, Algorithms, and Source Code in C, John Wiley, 1995.14. D. Schweitzer and L. Baird, The Design and Use of Interactive Visualization Applets for Teaching Ciphers, IEEE Information Assurance Workshop, pages 69-75, 2006.15. J. Tao, J. Ma, M. Keranen, J. Mayo, and C.-K. Shene, DESvisual: A Visualization Tool for the DES Cipher, Journal of Computing
’ 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
Paper ID #13338Developing and Piloting a Quantitative Assessment Tool for CybersecurityCoursesDr. Richard Scott Bell, Northwest Missouri State University Scott Bell received his Ph.D. in Computer Science from Kansas State University in 2014 and his master’s degrees in Computer Science in 2000 from the Missouri University of Science and Technology. His B.S., in Geological Engineering, with a minor in Communications, is also from the Missouri University of Science and Technology (1994).Dr. Eugene Vasserman, Kansas State University Eugene Vasserman received his Ph.D. and master’s degrees in Computer Science in 2010 and 2008
Paper ID #12420Towards an integrated Hardware And SOftware Book (HASOB)Prof. Mohamed Abdelrahman, Texas A&M University-Kingsville Dr. Abdelrahman is currently the Associate Vice President for Research and Graduate Studies and a Professor of Electrical Engineering at Texas A&M University Kingsville. Dr. Abdelrahman has a diverse educational and research background. His research expertise is in the design of intelligent measurement systems, sensor fusion and control systems. He has been active in research with over 80 papers published in refereed journals and conferences. He has been the principal investigator on
Paper ID #12865A Toolkit to Facilitate the Development and Use of Educational Online Lab-oratories in Secondary SchoolsProf. Michael E. Auer, CTI Villach Dr. (mult.) Michael E. Auer is Professor of Electrical Engineering at the Faculty of Engineering and IT of the Carinthia University of Applied Sciences Villach, Austria and has also a teaching position at the Uni- versity of Klagenfurt. He is a senior member of IEEE and member of ASEE, IGIP, etc., author or co-author of more than 170 publications and leading member of numerous national and international organizations in the field of Online Technologies. His current
interaction scaffolding that specifies roles, sequences group activities, and provides question prompts for social interactions among student team members to effectively engage them in task-related social interaction. The other is the cognitive cooperation scaffolding that guides students’ cognitive processes relating to the specific learning tasks at hands. Detailed description of the two types of scaffolding can be retrieved from the previously published ASEE conference paper 21. Table 2 Different students’ team groups and corresponding instruction (input variables) Team Groups Instructional Materials Provided to Students A Collaborative learning requirements only B Collaborative
+ √y 2 =1 ( ab b2 −y 2 ) ( cb b2 −y 2 ) 2 x2 A2 + By 2 = 1 where √ √ A = ab b2 − y 2 , B = cb b2 − y 2 2 2 The elliptic disk Ax 2 + By 2 = 1 has the area of πAB. Thus the secondmoment with respect x − z plane, mxz , can be calculated as follows: +∞ +∞ +∞ +b mxz = y 2 dxdydz = πABy 2 dy = −∞ −∞ −∞ −b 2acπ +b
care, physicians can predict the future of a bacterial infectionor an allergic reaction. These types of sequences are harmful and need to be brought to anend as soon as possible. To do so, physicians recommend necessary treatments toterminate these undesirable sequences.Implementation ModelA multiway lexicographic search tree can be used to represent event sequences where anevent from the sequence of events determines a multiway branch at each step. If thesequence is constructed from the English alphabets, at the root of the tree there are 27possible branches. Similarly, there are 27 braches for each subsequent node of the tree.For the sake of simplicity, assume we have a text that its words are constructed from theletters a, b, and c. The
: Explanation 13 7 3 3 6 0 30.2% of a concept (3. b.) Conceptual: Identification 9 3 4 4 1 2 21.7% of a concept (3. c.) Total Writing Prompts in Chapter/Total End- 44/148 14/112 18/135 14/207 9/42 9/90 of-Chapter Problems Percentage of problems with 29.7% 12.5% 13.3% 6.8% 21.4% 10.0% writing prompts (%)a Total writing prompts: 44+14+18+12+9+9=106. Relative % given as sum of found promptsdivided by 106.Textbook Summaries and AnalysisAs part of our analysis, the research team also examined each textbook for features
comparative literature review.,” ACM Comput. Surv., vol. 38, no. 3 Article 7, 2006. [2] E. Lindsay and M. C. Good, “Effects of laboratory access modes upon learning outcomes,” Educ. IEEE Trans., vol. 48, no. 4, pp. 619–631, 2005.[3] J. E. Corter, J. V Nickerson, S. K. Esche, C. Chassapis, S. Im, and J. Ma, “Constructing reality: A study of remote, hands-on, and simulated laboratories,” ACM Trans. Comput. Interact., vol. 14, no. 2, p. 7, 2007.[4] B. Aktan, C. A. Bohus, L. A. Crowl, and M. H. Shor, “Distance learning applied to control engineering laboratories,” Educ. IEEE Trans., vol. 39, no. 3, pp. 320–326, 1996.[5] Labshare, “The
Expert Systems With Applications (pp. 9939-9945) Vol 39(2012) Elsevier6. http://decoda.univ-avignon.fr/projet.php7. Bechet, F., Maza, B., Bigouroux, N., Bazillon, T., El-Bèze, M., De Mori, R., & Arbillot, E. DECODA: a call-center human-human spoken conversation corpus.8. http://www.wsj.com/articles/metadata-can-expose-persons-identity-even-when-name-isnt-1422558349 Page 26.439.119. http://bits.blogs.nytimes.com/2015/01/29/with-a-few-bits-of-data-researchers-identify-anonymous-people/?_r=010. http://www.sciencemag.org/content/347/6221/536.full?intcmp=collection-privacy11. Speaker Identification by Speech
corporate CIS and engineering professionals will have a common vocabulary by which tomeet security challenges. Outlines of the modules with respect to student groups are as follows.A. Topics for CIS students: 1. ICS hardware a. Programmable Logic Controller (PLC) processor architecture b. PLC real-time operating systems c. Sensory input and actuator output buffers and interfaces 2. ICS software a. Human Machine Interfaces, GUI b. PLC programming languages, overview i. 981 ladder logic ii. IEC 61131-3 3. ICS networks a. Ethernet considerations in real-time networks b. Modbus/TCP and serial links i. RS-232 and RS-485 c. Proprietary
Paper ID #14106Automated Identification of Terminological Dissonance in IT and adjacentfieldsMs. Jessica Richards, BYU Graduate student in Information Technology with a background of interdisciplinary work between com- puting and media fields. Highly interested in streamlining the collaborating of technical and creative minds.Joseph J Ekstrom, Brigham Young University Dr. Ekstrom spent more than 30 years in industry as a software developer, technical manager, and en- trepreneur. In 2001 he helped initiate the IT program at BYU. He was the Program Chair of the Informa- tion Technology program from 2007-2013. His research
26.1295.5adequate performance (equivalent to a passing grade or C).Figure 1. Average sttudent perforrmance (0-10) in seven ttypes of proggramming coonceptassessmeents (first two categories in Bloom’s taxonomy). n = 62. Dasshed horizonntal line markks alevel of acceptable a peerformance.Figure 2. 2 Percent of students perrforming adeequately (>= = 7 which is equivalent too a passing Page 26.1295.6grade, 70 0% or C) in the t seven diffferent progrramming connceptual cateegories.Average values can be b distorted byb very good d performannce of some
platforms for teaching some IT concepts are strong.Trends in IT towards much more diverse computing platforms that are integrated into the realworld indicate that IT students should pay more attention to hardware systems.Hardware adds a significant dimension to the learning experience of IT students. Commonlyavailable systems provide the necessary elements for introducing hardware into IT courses. Thebenefits to students are clear. The framework we have developed leading to the use of widelystandardized systems has been demonstrated to be effective in multiple classes and will becontinued and extended.Bibliography1. B. M. Lunt, J. J. Ekstrom, S. Gorka, G. Hislop, R. Kamali, E. A. Lawson, R. LeBlanc, J. Miller, H. Reichgelt, and T. A. for C. M
mellifluously,” New YorkTimes, April 22, 2012.[2] Fox, Armando; Canny, John, “Autograding and online ed technology,”https://docs.google.com/document/d/11e7HzGGRAvAhTce6L7P33fyQUo67wO_Qbec6cGynrKo/edit#heading=h.vo90ekim8uj0, accessed Feb. 2, 2015[3] Beitzel, B. D.; Gonyea, N. E., “The rubric interview: a technique for improving the reliabilityof scoring written products,” Proc. 2014 Virginia Tech Conference on Higher EducationPedagogy, p. 242.[4] Edwards, S.H; Perez-Quiñones, M.A., “Web-CAT: automatically grading programmingassignments.” In Proceedings of the 13th annual conference on Innovation and technology incomputer science education (ITiCSE '08). ACM, New York, NY, USA, 328-328, 2008.DOI=10.1145/1384271.1384371 http
: Balanced designs for deeper learning in an online computer science course for middle school students. 2014, Stanford University.[6] Lahtinen, E., K. Ala-Mutka, and H.-M. Järvinen. A study of the difficulties of novice programmers. in ACM SIGCSE Bulletin. 2005. ACM.[7] Streveler, R.A., et al., Learning conceptual knowledge in the engineering sciences: Overview and future research directions. Journal of Engineering Education, 2008. 97(3): p. 279-294.[8] Barney, B., Introduction to parallel computing. Lawrence Livermore National Laboratory, 2010. 6(13): p. 10.[9] Nevison, C.H., Parallel Computing for Undergraduates. National Science Foundation and Colgate
Figure 1. Survey participant’s choices based on factors. 7References[1] Creswell, J. W. (2004). Educational research planning, conducting, and evaluating quantitative and qualitative research (2nd ed.). Columbus, Ohio: Merrill Prentice Hall.[2] Karel, B. (2010). Introducing The MDM Market’s Newest 800lb Gorilla: Informatica Acquires Siperian! . Retrieved from http://blogs.forrester.com/business_process/2010/01/introducing-the-mdm- markets-newest-800lb-gorilla-informatica-acquires-siperian.html.[3] Madhukar, N. (2009, June 24). Federated MDM data domains - A Perspective. Retrieved from http://www.infosysblogs.com/customer
– Geospatial LayoutHowever, the student’s initial feedback was that the diagram was not clear as the applications Page 26.929.7and locations used the same color and font. Consequently, in most of their homeworkassignments they used a coloring scheme such as shown in Figure 7. Figure 7: Student’s Diagram – Geospatial LayoutMoreover, other students realized that this sort of diagram is not scalable and will become veryunclear and messy if there are many applications and locations with complex mappingrequirements. They suggested the use of a matrix as shown in Figure 8 below. Building App. A App. B
collective intelligence factor in the performance of human groups. Science, 330, 686-688. doi: 10.1126/science.119314710. Bear, J. B., & Woolley, A. W. (2011). The role of gender in team collaboration and performance. Interdisciplinary Science Reviews , 36(2), 146-153. DOI 10.1179/030801811X1301318196147311. Joshi, A., & Roh, H. (2009). The role of context in work team diversity reasearch: A meta-analytic review. Academy of Management Journal, 52(3), 599-627. http://www.jstor.org/stable/4039030612. Forrest, C. (2014). Diversity Stats: 10 tech companies that have come clean. Retrieved from TechRepublic: http://www.techrepublic.com/article/diversity-stats-10-tech-companies-that-have-come-clean/13. Pepitone, J. (2014
Paper ID #13391Practical Data Mining and Analysis for System AdministrationTanner Lund, Brigham Young University Tanner Lund is a research assistant at Brigham Young University studying Information Technology. His fields of study include system administration and network management, with a specialization in dis- tributed computing and log analysis. He has a strong interest in machine learning and applying its princi- ples to network management.Hayden PanikeMr. Samuel MosesDr. Dale C Rowe, Brigham Young University Dr. Rowe has worked for nearly two decades in security and network architecture with a variety of
Design (CAD) of Recursive/Non-Recursive FiltersA b s t r a c t. Computer Tools are integral part of many engineering design courses, they shouldbe used in the right place, right time. Courses in the Digital Signal Processing/Filter areas(including speech, image and video processing) have been traditionally viewed by students to befairly mathematical subjects including many abstractions (e.g., spectrum, analysis/designmethods in time/frequency domains, SNR, bandwidth, white/pink noise, various transforms, etc.)The pedagogical value of this work is that, with the help of modern engineering tools,engineering educators can better help students visualize these apparently difficult (but important)concepts. We focus on the subject of designing digital
Paper ID #11155Factors influence data management model selections: IT Expert testimoniesDr. Gholam Ali Shaykhian, - Gholam Shaykhian has received a Master of Science (M.S.) degree in Computer Systems from University of Central Florida and a second M.S. degree in Operations Research from the same university and has earned a Ph.D. in Operations Research from Florida Institute of Technology. His research interests include knowledge management, data mining, object-oriented methodologies, design patterns, software safety, genetic and optimization algorithms and data mining. Dr. Shaykhian is a professional member of the
Paper ID #12938Game Design and Development Capstone Project Assessment Using ScrumJohn Glossner, Daniel Webster College Dr. John Glossner is Associate Professor of Computer Science at Daniel Webster College. He also serves as CEO of Optimum Semiconductor Technologies. Prior to joining OST John co-founded Sandbridge Technologies and served as EVP & CTO. Prior to Sandbridge, John managed both technical and business activities in DSP and Broadband Communications at IBM and Lucent/Starcore. John was also an adjunct professor at Lehigh University. John received a Ph.D. in Electrical and Computer Engineering from TU Delft