council curriculum committee january 23, 2019 2:30 p.m ... · 1/23/2019 · graduate council...

GraduateCouncilCurriculumCommitteeJanuary23,20192:30p.m.,ED306

Agenda

1. Welcomeandcalltoorder

2. ReviewofminutesfromJanuary9,2019

3. Generalbusiness

4. Courses

5. Adjournment Members of the Graduate Council Curriculum Committee ElsieOlan,Chair,CollegeofCommunityInnovationandEducationAndreGesquiere,ViceChair,CollegeofSciencesSoniaArellano,CollegeofArtsandHumanitiesMathildaVanNiekerk,RosenCollegeofHospitalityManagementArtWeeks,CollegeofEngineeringandComputerScienceJihe(Jackie)Zhao,CollegeofMedicineDianeAndrews,CollegeofNursingMercedehKhajavikhan,CollegeofOpticsandPhotonicsOlgaMolina,CollegeofHealthProfessionsandSciencesAlexRubenstein,CollegeofBusinessAdministrationTerrieSypolt,UniversityLibrariesWeiWei,RosenCollegeofHospitalityManagementKianaTerrell,GraduateStudentAssociationToshaDupras,CollegeofSciences,AdministratorJoellenEdwards,CollegeofNursing,AdministratorAliGordon,CollegeofEngineeringandComputerScience,AdministratorDavidHagan,CollegeofOpticsandPhotonics,AdministratorLynnHepner,CollegeofArtsandHumanities,AdministratorDevonJensen,GraduateStudies,AdministratorGlennLambie,CollegeofCommunityInnovationandEducation,AdministratorSalehNaser,CollegeofMedicine,AdministratorLindaRosa‐Lugo,CollegeofHealthProfessionsandSciences,AdministratorSevilSonmez,CollegeofBusinessAdministration,AdministratorYouchengWang,RosenCollegeofHospitalityManagement,Administrator

GraduateCouncilCurriculumCommitteeJanuary23,20192:30p.m.,ED306

CourseAgenda

1. CourseAdditions College of Engineering and Computer Science course additions

1. CAP 5250 Internet of Things Security and Privacy 2. CAP 5674 Artificial Intelligence for FinTech 3. CDA 5201 Foundations of Secure Execution Environment 4. CDA 6201 Advanced Topics in Secure Execution Environment 5. CIS 6615 Advanced Software Systems Security 6. COP 5150 Blockchains and Smart Distributed Contracts 7. COP 5562 Full Stack Development for FinTech 8. COT 5480 Computational Methods in FinTech I 9. COT 6481 Computational Methods in FinTech II 10. CWR 5999 Water First Seminar Series 11. EEL 5061 Cyber‐Physical Technologies for Smart Communities 12. EEL 5294 Introduction to Smart Grid (split level course) 13. EEL 6297 Attacks and Defenses in Secure Cyber‐Physical Systems 14. EEL 6675 Stochastic Control

College of Optics and Photonics course addition

1. OSE 6398 Infrared Detectors (special topic)

2. CourseContinuations College of Engineering and Computer Science continuations

1. EMA 5585 Materials Science of Thin Films 2. EMA 5705 High Temperature Materials

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UNIVERSITY OF CENTRAL FLORIDA

DEPARTMENT OF COMPUTER SCIENCE

Syllabus for CAP 5250: IoT Security and Privacy

FALL 2018

Instructor: Dr. Xinwen Fu Office: RB1 378 Phone: 407-823-5337 E-Mail: [email protected] Homepage: https://www.cs.ucf.edu/~xinwenfu/ Office Hours: TBD Course Name: CAP 5250: IoT Security and Privacy Credits: 3.00 Duration: One semester Time: TBD Location: TBD TA: TBD Email: TBD

COURSE DESCRIPTON

The Internet of Things (IoT) has broad application domains including healthcare, smart home, retail, manufacturing, agriculture, environmental monitoring and industrial automation. Given its ubiquitous use, IoT has raised grave concerns about security and privacy resulting from hacking. For example, the huge DDoS attack against Dyn DNS servers in 2016 exposed the weaknesses of current industry IoT practices. This course aims at developing a cybersecurity workforce that can secure the IoT infrastructures and fight threats against IoT. This course introduces full-stack IoT security and privacy issues, including hardware, software, network, and data. The key objectives include: understanding IoT frameworks, applications and security and privacy concerns; being familiar with IoT hardware security; mastering IoT system security; mastering IoT software security; mastering IoT network security; understanding the IoT data security and privacy.

COURSE OBJECTIVES

Upon completion of this unit: students will

Understand IoT frameworks, applications, security and privacy concerns. Be familiar with IoT hardware security Master IoT system security Master IoT software security Master IoT network security.

Commented [MOU1]: Fix this

COURSE PREREQUISITES

Operating systems: Linux and Windows Programming: Python, C, C++, etc. Networking

DESCRIPTION OF INSTRUCTIONAL METHODS

The course web site is located within Webcourse. Discussions, announcements, questions (and answers, etc. will be available through

Webcourse Lecturing is based on provided learning materials. Programming may be practiced in the lab. Students will be expected to be prepared for class, and must complete the assignments by the

due dates.

COURSE REQUIREMENTS

No textbook. Handouts will be offered if necessary.

Class Attendance Policy

Students should attend the class in the classroom.

Cheating and Plagiarism Policy

All forms of academic dishonesty will result in an F for the course and notification of the Academic Dishonesty Committee; Academic dishonesty includes (but is not limited to) plagiarism, copying answers or work done by another student (either on an exam or assignment), allowing another student to copy from you, and using unauthorized materials during an exam

Make-up Exams

Make-up exams will only be given in case of serious need and only when the instructor is notified prior to the exam time. Otherwise, the grade is automatically zero for that exam/quiz.

Written verification for the student s inability to take an exam will be required. The make-up exams will be different from those given to the class.

EVALUATION PROCEDURES (tentative)

Components of Course Grade:

Assignments 20% Midterm Exam 50% Term Project 30%

Grade Scale: A (4.00), A- (3.75), B+ (3.25), B (3.00), B- (2.75), C+ (2.25), C (2.00), C- (1.75),

D+ (1.25), D (1.00), D- (0.75), F (0.00)

A 90 ~ 100 A- 85 ~ 89.9

B+ 80 ~ 84.9 B 75 ~ 80 B- 70 ~ 74.9 C+ 65 ~ 69.9 C 60 ~ 64.9 D 50 ~ 59.9 F below 50

Homework Assignments

All assignments are to be turned in on or before the due date and time. If you try and cannot turn in an assignment electronically because the campus network is down, you will not be penalized.

An assignment turned in up to 24-hours late will be reduced by 10% of the assignment worth, more than 24 hours late will be reduced 100%.

The due date and time for each assignment will be specified on assignment postings. All assignments are expected to be individually and independently completed. Should

two or more students turn in substantially the same solution or program, in the judgment of the instructor, the assignment will be given a grade of zero. A second such incident will result in an F grade for the course.

Exams

Exams are based on textbooks, supplementary materials, and assignments.

Projects

There will be individual or group projects. Each member of this class is required to join a team of at least 2 persons and at most 3

persons. A team must have a team leader coordinating the communication with members and the instructor.

Each team must be formed within 2 weeks from the semester start and the team leader will report the list of members to the instructor once the team is formed.

Team work is encouraged since all members of a team will receive the same score based on the entire team s performance for team projects.

Some of the projects may be performed within a closed laboratory.

UNIVERSITY DEADLINES: Refer to Academic Calendar

EARLY ALERT STATEMENT

Academic Success Support

As a professor, the instructor is personally committed to supporting student academic success in this course. For that reason, if a student demonstrates any academic performance or behavioral problems which may impede their success, the instructor will personally discuss and attempt to resolve the issue with the student. If the situation persists, the instructor will forward his concern to the Student Development Office and the student’s academic advisor to seek their support and assistance in the matter. The instructor’s goal is to make student learning experience in this course as meaningful and successful as possible.

http://calendar.ucf.edu/2018/fall/registration

AMERICANS WITH DISABILITIES ACT (ADA) STATEMENT

TENTATIVE CLASS SCHEDULE

The schedule may be adjusted based on the actual progress in the semester. Some subtopics may span over multiple class meetings. The instructor reserves the right to change the topics.

Module Topics Subtopics

Module 1 Review of security and privacy concepts and techniques for IoT

Cryptography Network security

Module 2 IoT frameworks and applications

History of IoT systems Architectures of IoT systems IoT application domains

Module 3 IoT hardware security

Hardware interfaces such as JTAG, UART and SPI of IoT devices and their security pitfalls

Microcontroller (MCU) based IoT hardware platforms Microprocessor (MPU) based IoT hardware platforms

Module 4 IoT system security

IoT firmware security including secure boot, flash encryption, secure storage, and secure firmware upgrading.

MCU systems including Free-RTOS. MPU systems including OpenWRT.

Module 5 IoT software security

Attack sectors including code injection attack, buffer overflow attack and others

Defense measures including intrusion detection MCU applications vs MPU applications

Module 6 IoT network security Communication encryption Mutual authentication

Module 7 IoT big data analytics Data security Data privacy including differential analysis

https://med.ucf.edu/media/2017/06/Americans-with-Disabilities-Act.pdf

https://med.ucf.edu/media/2017/06/Americans-with-Disabilities-Act.pdf

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CAP 5674: Artificial Intelligence for FinTech Computer Science, CECS

3 hours

Course Syllabus

Instructor: Sumit K. Jha Term: Fall 2019 onwards Office Location: TBD Class Meeting Days: TBD Office Hours: TBD Class Meeting Time: TBD Phone: TBD Class Location: TBD Email: TBD Course Modality: P GTA(s): TBD Email: TBD Course Description Official course description: CAP 5674 (new course) Artificial Intelligence for FinTech. 3(3,0). PR: COT 5840: Computational Methods in FinTech – I Fundamentals of machine learning; deep learning; reinforcement learning; applications to customer service automation, personalization, biometrics, process automation, and fraud prevention. Detailed course description: Fundamentals of machine learning: supervised learning, model validation, regularized and nonparametric regression, support vector machines, tree-based methods, boosting and ensemble methods, clustering, mixture models, Markov decision processes, reinforcement learning, and neural networks; Customer service automation: natural language processing, recurrent neural networks, MS Bot, IBM Watson assistant; Personalization: user modeling & profiling, content-based methods, model-based methods, knowledge-based methods, collaborative filtering, hybrid methods, evaluation and attack resistance of recommender systems, process automation; Biometrics: face identification using deep convolutional neural networks, deep learning fingerprints, NIST reference fingerprinting system, iris identification; Fraud prevention: clustering, one-class SVMs, statistical outlier detection, decision trees, social network analysis, deep neural networks. Student Learning Outcomes

The students will develop an understanding of AI as it relates to financial technology, and will demonstrate this ability through a final examination. The students will be able to apply AI methods to design chat bots, personalization, fraud prevention and biometric security systems.

Enrollment Requirements

A grade of B- or higher in COT 5840: Computational Methods in FinTech – I is required for enrollment in this class. Course Activities

The following table illustrates the detailed content to be covered in a typical course offering: Week 1 Introduction to supervised machine learning Week 2 Model validation Week 3 Regression Week 4 Tree-based methods Week 5 Support vector machines Week 6 Boosting and ensemble methods Week 7 Markov decision processes and reinforcement learning Week 8 Neural networks with an emphasis on deep learning Week 9 NLP using recurrent neural networks, MS Bot, IBM Watson Assistant Week 10 Personalization: content based methods, model based methods, collaborative filtering Week 11 Biometrics: face identification Week 12 Biometrics: fingerprinting system and iris identification Week 13 Fraud prevention: clustering, 1-class SVM, statistical outliers Week 14 Deep learning for biometrics & fraud prevention Week 15 Hardware & software challenges in designing AI for FinTech

Final Exam

According to UCF policy, all courses should have a final examination or assessment and should meet during their designated final exam period. The final examination will be held at a date, time and location determined by the UCF registrar. Assessment and Grading Procedures

The final grade of the class will be computed using the following evaluation metric: Assessment Percent of Final Grade Assignments 10% Mid-term I 10% Mid-term II 10% Final 20% Project 50% 100%

Additional optional assignments may be provided to the class at the discretion of the instructor.

Grading Methods

The final grade for this class will be automatically computed using the following grading scale:

Grading Scale (%)

90 - 100 A 80 - 90 A- 70 - 80 B+ 60 - 70 B 50 - 60 B- 40 - 50 C+ 0 - 40 F

Make-up Exams and Assignments

No make up exams or assignments will be permitted without the approval of the department. If the Chair of the Computer Science department deems an absence to be excusable for any reason, the instructor shall allow the student to take a make-up exam or complete an alternate assignment. While every effort will be made to ensure that the exam or the assignment is of similar nature, it cannot be guaranteed that the performance of the student on the new exam or assignment will be the same as the original exam or assignment. Grade Dissemination

Graded tests and materials in this course will be managed using WebCourses. Please note that scores returned mid-semester are unofficial grades. If you need help accessing myUCF Grades, see the online tutorial: https://myucfgrades.ucf.edu/help/. Final grades will be posted to myUCF through the Registrar’s office. Course Materials and Resources

Required Texts and Materials

1. Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction. Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, and Steven Goldfeder. 1st Edition, Princeton University Press.

2. Additional reports, papers and documents related to the course will be provided via Webcourses. Policy Statements

Academic Integrity

The Center for Academic Integrity (CAI) defines academic integrity as a commitment, even in the face of adversity, to five fundamental values: honesty, trust, fairness, respect, and responsibility. From these values flow principles of behavior that enable academic communities to translate ideals into action. http://academicintegrity.org/

http://academicintegrity.org/

UCF Creed: Integrity, scholarship, community, creativity, and excellence are the core values that guide our conduct, performance, and decisions.

1. Integrity: I will practice and defend academic and personal honesty. 2. Scholarship: I will cherish and honor learning as a fundamental purpose of my membership in the

UCF community. 3. Community: I will promote an open and supportive campus environment by respecting the rights

and contributions of every individual. 4. Creativity: I will use my talents to enrich the human experience. 5. Excellence: I will strive toward the highest standards of performance in any endeavor I undertake.

The following definitions of plagiarism and misuse of sources come from the Council of Writing Program Administrators <http://wpacouncil.org/node/9> and have been adopted by UCF’s Department of Writing & Rhetoric. Plagiarism

In an instructional setting, plagiarism occurs when a writer deliberately uses someone else’s language, ideas, or other original (not common-knowledge) material without acknowledging its source. This definition applies to texts published in print or on-line, to manuscripts, and to the work of other student writers.

Responses to Academic Dishonesty, Plagiarism, or Cheating

UCF faculty members have a responsibility for your education and the value of a UCF degree, and so seek to prevent unethical behavior and when necessary respond to infringements of academic integrity. Penalties can include a failing grade in an assignment or in the course, suspension or expulsion from the university, and/or a "Z Designation" on a student's official transcript indicating academic dishonesty, where the final grade for this course will be preceded by the letter Z. For more information about the Z Designation, see http://goldenrule.sdes.ucf.edu/zgrade. For more information about UCF's Rules of Conduct, see http://www.osc.sdes.ucf.edu/.

Unauthorized Use of Class Materials

There are many fraudulent websites claiming to offer study aids to students but are actually cheat sites. They encourage students to upload course materials, such as test questions, individual assignments, and examples of graded material. Such materials are the intellectual property of instructors, the university, or publishers and may not be distributed without prior authorization. Students who engage in such activity are in violation of academic conduct standards and may face penalties.

Unauthorized Use of Class Notes

Faculty have reported errors in class notes being sold by third parties, and the errors may be contributing to higher failure rates in some classes. The following is a statement appropriate for distribution to your classes or for inclusion on your syllabus: Third parties may be selling class notes from this class without my authorization. Please be aware that such class materials may contain errors, which could affect your performance or grade. Use these materials at your own risk.

In-Class Recording Policy

Outside of the notetaking and recording services offered by Student Accessibility Services, the creation of an audio or video recording of all or part of a class for personal use is allowed only with the advance and explicit written consent of the instructor. Such recordings are only acceptable in the context of personal, private studying and notetaking and are not authorized to be shared with anyone without the separate written approval of the instructor.

http://wpacouncil.org/node/9

http://goldenrule.sdes.ucf.edu/zgrade

http://www.osc.sdes.ucf.edu/

Campus Safety Statement

Emergencies on campus are rare, but if one should arise in our class, we will all need to work together. Everyone should be aware of the surroundings and familiar with some basic safety and security concepts.

In case of an emergency, dial 911 for assistance. Every UCF classroom contains an emergency procedure guide posted on a wall near the door.

Please make a note of the guide’s physical location and consider reviewing the online version at http://emergency.ucf.edu/emergency_guide.html.

Familiarize yourself with evacuation routes from each of your classrooms and have a plan for finding safety in case of an emergency. (Insert class-specific details if appropriate)

If there is a medical emergency during class, we may need to access a first aid kit or AED (Automated External Defibrillator). To learn where those items are located in this building, see http://www.ehs.ucf.edu/AEDlocations-UCF (click on link from menu on left). (insert class specific information if appropriate)

To stay informed about emergency situations, sign up to receive UCF text alerts by going to my.ucf.edu and logging in. Click on “Student Self Service” located on the left side of the screen in the tool bar, scroll down to the blue “Personal Information” heading on your Student Center screen, click on “UCF Alert”, fill out the information, including your e-mail address, cell phone number, and cell phone provider, click “Apply” to save the changes, and then click “OK.”

If you have a special need related to emergency situations, please speak with me during office hours.

Consider viewing this video (https://youtu.be/NIKYajEx4pk) about how to manage an active shooter situation on campus or elsewhere.

Deployed Active Duty Military Students

If you are a deployed active duty military student and feel that you may need a special accommodation due to that unique status, please contact your instructor to discuss your circumstances. Financial Aid Requirement

In Fall 2018, we are required to document students' academic activity at the beginning of each course. In order to document that you began this course, please complete Assignment 0 by the end of the first week of classes, or as soon as possible after adding the course, but no later than the first week. Failure to do so will result in a delay in the disbursement of your financial aid. The assignment 0 requires you to briefly introduce your background in undergraduate algorithms and undergraduate discrete structures. This assignment is listed as due at the end of the first week. However, it will not close until Week 8 of the term in order to ensure that students whose aid is delayed are able to complete the assignment and receive late disbursement. University Writing Center

The University Writing Center (UWC) is a free resource for UCF undergraduates and graduates. At the UWC, a trained writing consultant will work individually with you on anything you're writing (in or out of class), at any point in the writing process from brainstorming to editing. Appointments are recommended, but not required. For more information or to make an appointment, visit the UWC website at http://www.uwc.ucf.edu, stop by MOD 608, or call 407.823.2197. Library Skills

Since this course requires reading several research papers, you are expected to know how to use the library's resources. If you are not familiar with using the library, please ask for assistance from the library's personnel, take workshops provided by the library, or visit the library's website (http://library.ucf.edu/).

http://emergency.ucf.edu/emergency_guide.html

http://www.ehs.ucf.edu/AEDlocations-UCF

http://my.ucf.edu/

https://youtu.be/NIKYajEx4pk

http://library.ucf.edu/

Course Accessibility Statement

The University of Central Florida is committed to providing access and inclusion for all persons with disabilities. This syllabus is available in alternate formats upon request. Students with disabilities who need specific access in this course, such as accommodations, should contact the professor as soon as possible to discuss various access options. Students should also connect with Student Accessibility Services (Ferrell Commons, 7F, Room 185, [email protected], phone (407) 823-2371). Through Student Accessibility Services, a Course Accessibility Letter may be created and sent to professors, which informs faculty of potential access and accommodations that might be reasonable. As a matter of principle, the instructor is committed to facilitating the participation of every student in the class, and every reasonable request related to accessibility needs will be accepted.

http://sas.sdes.ucf.edu/


mailto:[email protected]

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CDA 5201: Foundations of Secure Execution Environment

First offering in Spring 2019 or Spring 2020

Instructor: Dr. Yan Solihin Office: R1 335 Phone: 407-823-4191 E-Mail: [email protected]

Homepage: https://sites.google.com/site/arpersncsu/ Office Hours: TBD Course Name: Foundations of Secure Execution Environment Credits: 3.00 Duration: One Full Semester Time: TBD Location: TBD TA: TBD Email: TBD

COURSE DESCRIPTION

This class is a graduate course covering the foundations of secure execution environment. The course (1) equips students with foundational knowledge of threat models, root of trust, and types of attacks that can occur with the execution of programs in the cloud or at the edge nodes, and (2) equips students with principles of designing a secure execution environment, knowing what mitigation techniques are effective for specific attacks, and knowing how to reason about security-performance trade-offs.


Advanced Computer Architecture (CDA 5106) Basic programming skills in C/C++ Basic knowledge on cryptography, including encryption, authentication, and digital

signatures


Primarily face-to-face lectures in classroom, possibly augmented with videos for students to watch on their own


The course web site is located within Webcourse. Discussions, announcements, questions (and answers, etc. will be available through

Webcourse Take-home paper and programming assignments performed individually or in groups Exams will be given at midterm and at the end of semester Project, project write up, presentation, at the end of semester Students will be expected to be prepared for class, and must complete the assignments by

the due dates.

COURSE REQUIREMENTS

Lecture note handouts to be provided Papers for reading list to be assigned No required textbook Recommended textbooks may be listed




All forms of academic dishonesty will result in academic misconduct report filed according to the process outlined in http://goldenrule.sdes.ucf.edu. An appropriate penalty will be applied if the misconduct is confirmed.

Make-up Exams

Make-up exams will only be given in case of serious need and only when the instructor is notified prior to the exam time. Otherwise, the grade is automatically zero for that exam/quiz.


COURSE OBJECTIVES

- Foundational knowledge of threat models, root of trust, and types of attacks that can occur with the execution of programs in the cloud or at the edge nodes

- Principles of designing a secure execution environment - Mitigation techniques are effective for specific attacks - Reasoning skills about security-performance trade-offs.

EVALUATION PROCEDURES

http://goldenrule.sdes.ucf.edu/


Assignments (up to 6 homework and up to 3 programming assignments) 30% Exams (midterm and final) 50% Term Project and Presentation (Presentation 15%, Software/method/results 35%) 20%


D+ (1.25), D (1.00), D- (0.75), F (0.00)

A 90 ~ 100 A- 85 ~ 89.9 B+ 80 ~ 84.9 B 75 ~ 80 B- 70 ~ 74.9 C+ 65 ~ 69.9 C 60 ~ 64.9 D 50 ~ 59.9 F below 50


All assignments are to be turned in on or before the due date and time. An assignment submitted late by up to 24 hours will receive a 10 point penalty. Beyond

that, it will receive zero points. The due date and time for each assignment will be posted on the course website. All assignments are expected to be individually and independently completed, unless

explicitly stated otherwise. If copying or cheating is suspected, academic misconduct report will be filed according to the process outlined in http://goldenrule.sdes.ucf.edu. An appropriate penalty will be applied if the misconduct is confirmed.

Exams


Projects





Team work is encouraged since all members of a team will receive the same score based on the entire team’s performance for team projects.




Americans with Disabilities Act (ADA) Statement


The schedule may be adjusted based on the actual progress in the semester. Each topic is intended to be covered in one class meeting. The instructor reserves the right to change the topics.

Topics:

1. Introduction – the need for secure execution environment 2. Review of processor architecture 1 3. Review of processor architecture 2 4. Review of cache architecture 5. Review of memory system architecture 6. Review of cache coherence and memory consistency 7. Threat Models in the Cloud vs. at the Edge: Supply Chain vs. Physical vs. Logical attacks 8. Root of Trust 9. Access Control and Isolation 10. Memory Privacy: direct and counter-mode encryption 11. Memory Privacy Optimizations: split counter mode 12. Memory Integrity: Merkle Tree, replay attack, counter rollback attack 13. Memory Integrity Optimizations: Bonsai Merkle Tree, SGX Counter Tree 14. Attestation 15. On-chip key management 16. Case study 1: Intel SGX architecture 17. Case study 2: AMD Secure Encrypted Virtualization 18. Case study 3: ARM TrustZone 19. Side channel overview: memory access pattern, architectural, speculation 20. Memory access obfuscation: ORAM, ObfusMem 21. Architectural: Prime+Probe, Evict+Time, etc. 22. Defenses for architectural side channels 23. Speculative execution side channel: Spectre/Meltdown, etc. 24. Defenses for speculative execution side channels 25. Project Presentation 1 26. Project Presentation 2


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CDA 6201: Advanced Topics in Secure Execution Environment

Semester offered: TBD

Instructor: Dr. Yan Solihin Office: R1 335 Phone: 407-823-4191 E-Mail: [email protected]

Homepage: https://sites.google.com/site/arpersncsu/ Office Hours: TBD Course Name: Advanced Topics in Secure Execution Environment Credits: 3.00 Duration: One entire semester Time: TBD Location: TBD TA: TBD Email: TBD

COURSE DESCRIPTION

This class is a graduate course covering the advanced topics in secure execution environment. The course equips students with the knowledge of the taxonomy of state-of-the-art attacks in cloud/edge computing, taxonomy and constructions of attacks, principles of designing a secure execution environment, from the architecture, Operating System, and Programming Language and Compiler.


Foundations of Secure Execution Environment (CDA 5201) Proficiency in programming in C/C++ Knowledge on cryptography, computer architecture, and foundations of secure execution

environment


Primarily face-to-face lectures in classroom, possibly augmented with videos for students to watch on their own

The course web site is located within Webcourse.


Discussions, announcements, questions (and answers, etc. will be available through Webcourse

Take-home paper assignments performed individually or in groups Project, project write up, presentation, at the end of semester Students will be expected to be prepared for class, and must complete the assignments by

the due dates.

COURSE REQUIREMENTS

Lecture note handouts to be provided Papers for reading list to be assigned No required textbook Recommended textbooks may be listed




All forms of academic dishonesty will result in academic misconduct report filed according to the process outlined in http://goldenrule.sdes.ucf.edu. An appropriate penalty will be applied if the misconduct is confirmed.

COURSE OBJECTIVES

- Knowledge of threat models, root of trust, and types of attacks that can occur with the execution of programs in the cloud or at the edge nodes

- Taxonomy and constructions of attacks - Principles of designing a secure execution environment, from the architecture, Operating

System, and Programming Language and Compiler.

EVALUATION PROCEDURES


Presentation and class discussion 30% Term Project and Presentation (Presentation 15%, Software/method/results 35%) 70%


D+ (1.25), D (1.00), D- (0.75), F (0.00)

A 90 ~ 100


A- 85 ~ 89.9 B+ 80 ~ 84.9 B 75 ~ 80 B- 70 ~ 74.9 C+ 65 ~ 69.9 C 60 ~ 64.9 D 50 ~ 59.9 F below 50


All assignments are to be turned in on or before the due date and time. An assignment submitted late by up to 24 hours will receive a 10 point penalty. Beyond

that, it will receive zero points. The due date and time for each assignment will be posted on the course website. All assignments are expected to be individually and independently completed, unless

explicitly stated otherwise. If copying or cheating is suspected, academic misconduct report will be filed according to the process outlined in http://goldenrule.sdes.ucf.edu. An appropriate penalty will be applied if the misconduct is confirmed.

Exams


Projects




Team work is encouraged since all members of a team will receive the same score based on the entire team’s performance for team projects.




Americans with Disabilities Act (ADA) Statement




http://www.housing.ucf.edu/resources/health

The schedule may be adjusted based on the actual progress in the semester. Each topic is intended to be covered in one class meeting. The instructor reserves the right to change the topics.

Topics:

1. Introduction – why secure execution environment? 2. Review of computer architecture 3. Review of programming language/compiler 4. Review of secure execution environment 1 5. Review of secure execution environment 2 6. Review of virtual memory 7. Taxonomy of attacks 8. Attack construction methods on Intel SGX 9. Attack construction methods on ARM Trustzone 10. Attack construction methods on AMD SEV 11. Speculative execution side channels 1 12. Speculative execution side channels 2 13. Constant time algorithm 1 14. Constant time algorithm 2 15. Predicated execution 1 16. Predicated execution 2 17. Return Oriented Protection (ROP) 18. ROP and Control Flow Integrity (CFI) techniques 19. Intel Memory Protection eXtension (MPX) 20. Cache coherence attacks and mitigations 1 21. Cache coherence attacks and mitigations 2 22. Covert channel 1 23. Covert channel 2 24. Covert channel 3 25. Project Presentation 1 26. Project Presentation 2

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University of Central Florida

Department of Computer Science

CIS 6615: Advanced Software Systems Security (3 credits)

First Offering (tentative): Fall 2019 Course Information:

Instructor: Dr. Aziz Mohaisen / Dr. Xinwen Fu Office: R1 377 Phone: 407-823-1294 E-mail: [email protected] Homepage: https://www.cs.ucf.edu/~mohaisen Office Hours: TBD Course Name: Advanced Software Systems Security Credits: 3.0 Duration: One Semester Time: TBD Location: TBD TA: TBD Email: TBD

Textbook

No required textbook

Prerequisites

Operating Systems Systems Programming Object Oriented programming.

OS concepts are essential for understanding attacks and how to prevent them in software systems. The course will assume knowledge of OS concepts, basics of computer security (including cryptography), and computer architecture and networking. Those prerequisites are fulfilled by the appropriate coursework at the University of Central Florida (or equivalent): COP 4600 (Operating Systems) or CGS 3763 (Operating System Concepts), CIS 3360 (Security in Computing), CIS 4615 (Secure Software Development or equivalent).

Course Description

The course will cover advanced topics in the area of software systems security, with a special focus on vulnerabilities and attacks in software systems, and their mitigation, as well as verification and analysis of secure software systems. The course will cover the following topics: secure software development lifecycle, buffer overflow attacks, memory corruption, format strings, integer overflow and heap spray, non-control attacks, return oriented programming, runtime memory protection, runtime bounds checking, address-space layout randomization, static

and hybrid detection of overflows, inline reference monitors, system call interposition, UNIX security constructs, web security and attacks (including cross-site scripting, SQL injection, and cross-site request forgery), static detection of web vulnerabilities, access control and information flow security, and ethical issues.

Schedule

The following is a tentative schedule of the lectures throughout the semester. Quizzes are every other week, starting week 2, while assignments are every other week, starting week 3.

Week 1: secure software development lifecycle Week 2: buffer overflow attacks, memory corruption, Week 3: format strings, integer overflow and heap spray, Week 4: non-control attacks, return oriented programming, Week 5: runtime memory protection, runtime bounds checking, Week 6: address-space layout randomization, Week 7: static and hybrid detection of overflows, Week 8: midterm and projects presentations week 9: inline reference monitors, system call interposition, UNIX security constructs, Week 10 and 11: web security and attacks (cross-site scripting, SQL injection, and cross-site request forgery), Week 12: static detection of web vulnerabilities, Week 13: access control and information flow security, Week 14: ethical issues. week 15: finals and project presentations

Grading Policies

Individual works: All assignments, quizzes, and exams in this course are to be done individually. All exams are close book and open notes. While discussing the homework with other students is permitted, you should do your homework by yourself. Cite all sources you use in doing your homework.

Late submission policy: All assignments are due in 1 week after they are released (by midnight of the due date). Late submissions will be graded, but with the following penalties (exclusive): 0-24 hours: 12.5%, 24-48 hours: 25%, 48-72 hours: 50%. No late submissions are accepted beyond 72 hours.

Grade distribution: The following is breakdown of the graded components in this course

Quizzes 10% 5x2 Assignments 15% 5x3 Midterms 15% 1x15 Final 20% 1x20 Project 40% 1x40

Letter grades and curve: We do not grade on a curve, and your grade will independent

of how others performed in this course. However, adjustments will be made (e.g., dropping the lowest quiz, homework, dropping questions all or most students did not get right in an exam). With that in mind, the following is the letter grade for the corresponding points

90% A 85% A- 80% B+ 75% B 70% B- 65% C+ 60% C 55% C- 50% D+ 45% D 40 D- Less F

Course project

A large component of the course is a project. The project will be done by a group of 2-3 students. The research project should address a problem related to software systems security. The work presented as a project for this course has to be done solely for this course, and should not have been submitted for any prior course nor will be used for any future course. Literature surveys are not allowed as a course project.

Project selection. It is the responsibility of the students to select their projects and come up with a team. The instructor should be informed of the team members as soon as possible, and no later than the deadline for the project proposal. During the first two weeks of the course, and until the deadline of the project proposal, the students should feel free to use the instructor’s office hours to discuss potential ideas and topics for the project. Before submitting the proposal, make sure that the instructor is aware and approving of the project topic.

Project deliverables. Each project will have three (3) deliverables: a proposal, a midterm, and a final report (see below for grading). Each proposal has to be discussed with the instructor before its submission. Such discussion should optimally take place during the office hours. Beside the required deliverables, students have to meet at least three times during the semester (office hours) with the instructor to report progress. The three meetings are expected to align with the deliverables (proposal meeting, midterm meeting, and final meeting). Teams, project topics, and proposals will be posted online after the proposal deadline.

Grading. The first deliverable (proposal) is worth 2%, the second deliverable (midterm report) is worth 8%, and the final report (including presentation, code, data - if you are doing a user study, etc.) is worth 30%. Exceptional project will have up to 5% of extra points.

Course Learning Objectives

The objectives for this course are divided into two parts: a set of essential objectives, and a set of enrichment objectives. The essential objectives will be helpful for your career as a computer scientist or software engineer; hence they lead to the course's essential outcomes that we want to help you master. The enrichment objectives are less important for the course, but lead to enrichment outcomes that you are encouraged to explore both for their own sake and because learning more about those will help deepen your understanding of the essential objectives. This course's objectives are linked to the computer science program's learning objectives.

Essential Objectives: The course's main learning objective is to enable students to implement software that is resilient to attacks, and to use analysis techniques to demonstrate such resilience. In particular, the course provides the following essential objectives:

Implement a software component so that it correctly implements a specification and is not subject to known attacks that would compromise its security.

Use tools and other means to analyze software to prevent or demonstrate security problems.

Enrichment Objectives: Enrichment objectives could be multiplied without limit, but the following seems important enough to warrant discussion. The course's enrichment objectives are that you will be able to:

Explain how management can encourage/reward secure software engineering practices. Explore new avenues in secure software development and assurance.

Course Learning Outcomes

The essential outcomes are designed to support this course's essential learning objectives, and thus to be helpful for your career as a computer scientist or software engineer; hence we want to help you to master them. They also form the basis for grading and assessment of your learning. The enrichment outcomes are not used directly for assessment. However, you are encouraged to explore topics related to the enrichment outcomes both for their own sake and because learning more about those will help your performance relative to the essential outcomes. Attendance Policy

Attendance is mandatory. All lectures will be delivered in the classroom.

Make-up Exams

Make-up exams are given in case of serious need and only when the instructor is notified prior to the exam time. Otherwise, the grade is automatically zero for that exam/quiz.


Rules of Conduct

Students should make themselves aware of the relevant conduct rules available at OSC: in http://goldenrule.sdes.ucf.edu

Accommodations for Disabilities

We are happy to help with reasonable accommodations for disabilities. The procedure is outlined in the following statement (quoted from the faculty center for teaching and learning's web site): "The University of Central Florida is committed to providing reasonable accommodations for all persons with disabilities. This syllabus is available in alternate formats upon request. Students with disabilities who need accommodations in this course must contact the professor at the beginning of the semester to discuss needed accommodations. No accommodations will be provided until the student has met with the professor to request accommodations. Students who


need accommodations must be registered with Student Disability Services, Student Resource Center Room 132, phone (407) 823-2371, TTY/TDD only phone (407) 823-2116, before requesting accommodations from the professor."

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COP 5150: Blockchains and Smart Distributed Contracts

Computer Science, CECS 3 hours

Course Syllabus

Instructor: Sumit K. Jha Term: Fall 2019 onwards Office Location: TBD Class Meeting Days: TBD Office Hours: TBD Class Meeting Time: TBD Phone: TBD Class Location: TBD Email: TBD Course Modality: P GTA(s): TBD Email: TBD Course Description Official course description: COP 5150 (new course) Blockchains and Smart Distributed Contracts. 3(3,0). PR: COT 5840: Computational Methods in FinTech – I Introduction to blockchains; consensus and decentralization mechanisms; symmetric and public key cryptography; bitcoin protocols and APIs; alternatives to bitcoins; smart contracts; Ethereum virtual machine; Solidity programming language; Web3 API; Hyperledger; scalability and other challenges of blockchain systems. Detailed course description: The course will provide a graduate level introduction to blockchains and their applications in currencies as well as other smart contracts. The history and different features of blockchains will be covered along with a survey of different decentralization and consensus mechanisms. Symmetric cryptography will be introduced to discuss the basics of security services such as confidentiality and integrity. Public key cryptography with its application in digital signatures and hash functions will be presented. The first popular blockchain based currency, Bitcoin, will be studies with an emphasis on its network, wallets, protocols, trading mechanisms, payments, clients and APIs. Alternatives to Bitcoin will be briefly surveyed. The use of blockchains in designing smart contracts will be discussed. The principles underlying the design, architecture and operation of the Etheruem system will be introduced. Other related topics covered will include the Ethereum virtual machine, mining & support protocols, Ethereum development environment for smart contracts, Solidity programming language, Web3 API for developing decentralized applications and smart contracts, and the Hyperledger framework for blockchain projects from the Linux Foundation. The course will conclude with an investigation into the scalability and other challenges of blockchain systems.

Student Learning Outcomes

The students will develop a graduate level understanding of blockchains as well as smart distributed contracts, and will demonstrate this ability through a final examination. Given a real-world problem involving smart contracts or digital currencies, the students will be able to employ their knowledge of Ethereum, Solidity, Web3 API and Hyperledger to provide a practical solution to the problem. Enrollment Requirements

A grade of B- or higher in COT 5840: Computational Methods in FinTech – I is required for enrollment in this class. Course Activities

The following table illustrates the detailed content to be covered in a typical course offering: Week 1 History of blockchains, consensus mechanisms, and decentralization of processes Week 2 Symmetric cryptography - I Week 3 Symmetric cryptography - II Week 4 Public key cryptography - I Week 5 Public key cryptography - II Week 6 Bitcoin Week 7 Alternatives to Bitcoin Week 8 Smart contracts, Ricardian contracts and oracles Week 9 Ethereum: design & architecture, principles, features & components Week 10 Ethereum virtual machine and Ethereum development environment Week 11 Solidity programming language - I Week 12 Solidity programming language - II Week 13 Web3 API Week 14 Hyperledger Week 15 Scalability and other challenges of blockchain systems

Final Exam



Additional optional assignments may be provided to the class at the discretion of the instructor. Grading Methods


Grading Scale (%)

90 - 100 A 80 - 90 A- 70 - 80 B+ 60 - 70 B 50 - 60 B- 40 - 50 C+ 0 - 40 F





1. Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction. Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, and Steven Goldfeder. 1st Edition, Princeton University Press.


Academic Integrity
















Outside of the notetaking and recording services offered by Student Accessibility Services, the creation of an audio or video recording of all or part of a class for personal use is allowed only with the advance and explicit written consent of the instructor. Such recordings are only acceptable in the context of personal,




private studying and notetaking and are not authorized to be shared with anyone without the separate written approval of the instructor. Campus Safety Statement













Since this course requires reading several research papers, you are expected to know how to use the library's resources. If you are not familiar with using the library, please ask for assistance from the



http://my.ucf.edu/


library's personnel, take workshops provided by the library, or visit the library's website (http://library.ucf.edu/). Course Accessibility Statement






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COP 5562: Full Stack Development for FinTech Computer Science, CECS

3 hours

Course Syllabus

Instructor: Sumit K. Jha Term: Fall 2019 onwards Office Location: TBD Class Meeting Days: TBD Office Hours: TBD Class Meeting Time: TBD Phone: TBD Class Location: TBD Email: TBD Course Modality: P GTA(s): TBD Email: TBD Course Description Official course description: COP 5562 (new course) Full Stack Development for FinTech. 3(3,0). Co-requisite: COT 5480: Computational Methods in FinTech – I Fundamentals of web technologies; Front-end design using HTML5, CSS3 and ReactJS; SQL and NoSQL databases; Back-end design. Detailed course description: Fundamentals: Unix shell, Git management, HTTP servers and clients, sessions and cookies, DNS, Linux deployment using Apache web server; Front-end: HTML, CSS, jQuery, HTML5, CSS3, ReactJS, Redux; Databases: fundamentals, tables, keys, data types, SQL – select, insert, join, aggregate operations, reusable views, SQL databases using Python DB-API, NoSQL databases; Back-end: Web servers, Create-Read-Update-Delete patterns, connecting to database via HTTP, JSON, web applications, Flask framework, authentication & authorization via local databases and OAuth 2.0, RESTful APIs – concepts, remote APIs, creation of new APIs in Python, authentication, Javascript design patterns – model-view-controller, reactive front-end development using knockout.js, Node.js. Student Learning Outcomes

The students will gain a deep understanding of full stack development, and will demonstrate this ability through a semester-long class project involving both front-end and back-end development. The students will understand the fundamentals of databases, frond-end technologies, and back-end deployment, and demonstrate this knowledge via examinations.


COT 5480: Computational Methods in FinTech – I is a co-requisite for enrollment in this class. Course Activities

The following table illustrates the detailed content to be covered in a typical course offering: Week 1 Unix shell, Git management, HTTP servers and clients, sessions and cookies, DNS Week 2 HTML Week 3 CSS Week 4 jQuery Week 5 Databases: fundamentals, tables, keys, data types, NoSQL Databases, MongoDB Week 6 SQL – select, insert, join, aggregate operations, reusable views Week 7 Web servers, Create-Read-Update-Delete patterns, connecting to database via HTTP Week 8 Web applications, Flask framework, ReactJS Week 9 Node.js Week 10 RESTful APIs – concepts, remote APIs, creation of new APIs in Python, authentication Week 11 Javascript design patterns – model-view-controller, reactive front-end development Week 12 Authentication & authorization via local databases and OAuth 2.0 Week 13 ReactJS with Redux Week 14 Linux deployment using Apache web server, HTML5, CSS3 Week 15 Upcoming web technologies

Final Exam



Additional optional assignments may be provided to the class at the discretion of the instructor.

Grading Methods


Grading Scale (%)

90 - 100 A 80 - 90 A- 70 - 80 B+ 60 - 70 B 50 - 60 B- 40 - 50 C+ 0 - 40 F





1. Pro MERN Stack: Full Stack Web App Development with Mongo, Express, React, and Node. Vasan Subramanian. 1st Edition. Springer Science + Business Media ISBN: 9781484226520


Academic Integrity
















Outside of the notetaking and recording services offered by Student Accessibility Services, the creation of an audio or video recording of all or part of a class for personal use is allowed only with the advance and explicit written consent of the instructor. Such recordings are only acceptable in the context of personal, private studying and notetaking and are not authorized to be shared with anyone without the separate written approval of the instructor.

















Since this course requires reading several research papers, you are expected to know how to use the library's resources. If you are not familiar with using the library, please ask for assistance from the library's personnel, take workshops provided by the library, or visit the library's website (http://library.ucf.edu/).



http://my.ucf.edu/



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COT 5480: Computational Methods in FinTech - I Computer Science, CECS

3 hours

Course Syllabus

Instructor: Sumit K. Jha & Sharma Thankachan Term: Fall Office Location: TBD Class Meeting Days: TBD Office Hours: TBD Class Meeting Time: TBD Phone: TBD Class Location: TBD Email: TBD Course Modality: P GTA(s): TBD Email: TBD Course Description

Official course description: PR: No pre-requisites. Fundamentals of data structures; definition and analysis of algorithms; basic classes of algorithms; graph algorithms; algorithms for identity, privacy, anonymity and automation. Fall. Detailed course description: The course will provide a graduate level introduction to algorithms, data structures, and other computational methods employed in financial technologies. Fundamental concepts in computer science will be motivated by real-world use cases in finance. Fundamentals of data structures such as stacks, queues, lists, and search trees will be covered. The course will also include the definition and analysis of algorithms and discuss basic classes of algorithms e.g. divide & conquer, greedy and dynamic programming. Basic graph algorithms e.g. breadth-first and depth-first search will be covered. Basic algorithms for identity, privacy and anonymity will be discussed. Students will master Python mechanisms for implementing the algorithms and data structures with a focus on examples drawn from FinTech. Student Learning Outcomes

The students will develop a graduate level understanding of basic data structures and algorithms, and will demonstrate this ability through a final examination. Given an algorithm, the student will develop the ability to translate the algorithm into Python code. The capability will be measured via a semester-long class project.


No pre-requisite courses are required for this class. A background in any programming language and mathematical maturity will facilitate success in this class. Course Activities

The following table illustrates the detailed content to be covered in a typical course offering: Week 1 Introduction to Python Week 2 Stacks Week 3 Queues and Deques Week 4 Linked Lists Week 5 Trees Week 6 Priority Queues, Hash Tables Week 7 Search Trees Week 8 Graph Definitions Week 9 Graph Algorithms Week 10 Divide & Conquer Week 11 Greedy Week 12 Dynamic Programming - I Week 13 Dynamic Programming - II Week 14 Algorithms for identity and privacy Week 15 Algorithms for anonymity Students should actively engage with this hands-on course material by pursuing the following activities:

(i) Read the textbook (Data Structures and Algorithms in Python. Michael T. Goodrich, Roberto Tamassia, Michael Goldwasser.1st Edition, Pearson Education) and other material specified on Webcourses.

(ii) Submit the 3-2-1 assignments by 11:59pm on the day of the class. This is true for all students including those enrolled in the online section of the class; no exceptions will be made. This is the most important assignment in this class. The 3-2-1 assignment require you to write down three things you learnt in the class, two queries about the class material and one thing you enjoyed about the class.

(iii) Submit the class assignments including programming assignments. (iv) Attend and submit the mid-term I, mid-term II and final examinations. No discussions or

extraneous help is permitted during the exams. Any extraneous help or discussion (including conversation) will be reported to the university for disciplinary action.

(v) Develop and submit a group class project related to fundamentals of computing in FinTech. You are welcome to form groups of at most 6 students. Random student interviews or examinations may be conducted to verify that the student understands all aspects of the class project.

(vi) Complete the reviews of the articles or survey papers made available via Webcourses. Reviews will receive full points if there is evidence of the student having studied the paper. Random student interviews or open-book examinations may be conducted to verify that the student has read the paper.

You may be required to bring a laptop, blue exam book, or a scantron sheet to the class in order to access the online course-management system or write exams.

Final Exam


The final grade of the class will be computed using the following evaluation metric:

Assessment Percent of Final Grade Article reviews 3-2-1 Summaries

7% 28%

Assignments 25% Mid-term I 5% Mid-term II 5% Final 10% Project 20% 100%



Grading Scale (%)

90 - 100 A 80 - 90 A- 70 - 80 B+ 60 - 70 B 50 - 60 B- 40 - 50 C+ 0 - 40 F


No make up exams or assignments will be permitted without approval of the department. If the Chair of the Computer Science department deems an absence to be excusable for any reason, the instructor shall allow the student to take a make-up exam or complete an alternate assignment. While every effort will be made to ensure that the exam or the assignment is of similar nature, it cannot be guaranteed that the performance of the student on the new exam or assignment will be the same as the original exam or assignment.

Grade Dissemination



1. Data Structures and Algorithms in Python. Michael T. Goodrich, Roberto Tamassia, Michael Goldwasser.1st Edition, Pearson Education.

2. Additional seminal and/or recent papers on algorithms will be provided via Webcourses. Supplementary (Optional) Texts and Materials

1. Algorithms and Data Structures - The Basic Toolbox, Mehlhorn, Kurt, Sanders, Peter, 2008, XII,

300 p. 112 illus., Hardcover ISBN: 978-3-540-77977-3. http://libguides .lib.ucf.edu/content.php?pid=86092&sid=640675

2. Introduction to algorithms. T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein. 3rd edition, MIT press

Policy Statements

Academic Integrity

The Center for Academic Integrity (CAI) defines academic integrity as a commitment, even in the face of adversity, to five fundamental values: honesty, trust, fairness, respect, and responsibility. From these values flow principles of behavior that enable academic communities to translate ideals into action. http://academicintegrity.org/ UCF Creed: Integrity, scholarship, community, creativity, and excellence are the core values that guide our conduct, performance, and decisions.





In an instructional setting, plagiarism occurs when a writer deliberately uses someone else’s language, ideas, or other original (not common-knowledge) material without acknowledging its source. This



definition applies to texts published in print or on-line, to manuscripts, and to the work of other student writers.








Outside of the notetaking and recording services offered by Student Accessibility Services, the creation of an audio or video recording of all or part of a class for personal use is allowed only with the advance and explicit written consent of the instructor. Such recordings are only acceptable in the context of personal, private studying and notetaking and are not authorized to be shared with anyone without the separate written approval of the instructor. Campus Safety Statement






To stay informed about emergency situations, sign up to receive UCF text alerts by going to my.ucf.edu and logging in. Click on “Student Self Service” located on the left side of the screen in the tool bar, scroll down to the blue “Personal Information” heading on your Student Center





http://my.ucf.edu/

screen, click on “UCF Alert”, fill out the information, including your e-mail address, cell phone number, and cell phone provider, click “Apply” to save the changes, and then click “OK.”







Since this course requires reading several research papers, you are expected to know how to use the library's resources. If you are not familiar with using the library, please ask for assistance from the library's personnel, take workshops provided by the library, or visit the library's website (http://library.ucf.edu/). Course Accessibility Statement







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COT 6481: Computational Methods in FinTech - II Computer Science, CECS

3 hours

Course Syllabus

Instructor: Sumit K. Jha & Sharma Thankachan Term: Spring Office Location: TBD Class Meeting Days: TBD Office Hours: TBD Class Meeting Time: TBD Phone: TBD Class Location: TBD Email: TBD Course Modality: P GTA(s): TBD Email: TBD Course Description

Official course description: PR: COT 5480 Computational Methods in FinTech - I. Advanced data structures; advanced algorithms; automated accounting, risk management and tax automation; computer architectures and applications to financial technology; parallel programming on multiple processors and GPUs. Spring Detailed course description: The course will cover advanced data structures such as red-black trees, Kd trees, Fibonacci heaps, union-find, tries, compressed tries, suffix trees, hash tables and hash trees. Advanced algorithms such as A* search, backtracking and search pruning, linear programming, polynomials & FFT, approximate string matching and parsing languages based on context free grammars will also be surveyed. Applied algorithms such as those employed for automated accounting and financial planning, risk management, audit and tax automation will be discussed. The course will also include fundamentals of computer architecture including quantitative design & analysis, data-level parallelism, warehouse scale computing and domain-specific architectures. Students will employ multi-threaded, multi-processor and object-oriented Python mechanisms for implementing parallel algorithms and data structures with a focus on examples drawn from FinTech. Student Learning Outcomes

The students will develop a graduate level understanding of computer architecture, advanced data structures and algorithms, and will demonstrate this ability through a final examination. Given a problem, the student will develop the ability to design a computing system, including software and hardware components. The students will create parallel solutions to real-world problems in FinTech.


A grade of B- or better in COT 5480 Computational Methods in FinTech – I Course Activities

The following table illustrates the detailed content to be covered in a typical course offering: Week 1 Python – multiprocessor programming Week 2 Python – GPU programming Week 3 Red-black trees, Kd trees Week 4 Fibonacci heaps, union-find Week 5 Tries, compressed tries, suffix trees, hash tables and hash trees Week 6 A* search, backtracking and search pruning Week 7 Linear programming, polynomials & FFT Week 8 Approximate string matching, parsing grammars Week 9 Architecture: quantitative design & analysis Week 10 Data-level parallelism Week 11 Warehouse scale computing Week 12 Domain-specific architectures Week 13 Algorithms for automated accounting Week 14 Risk management algorithms Week 15 Tax automation algorithms Students should actively engage with this hands-on course material by pursuing the following activities:

(i) Read relevant chapters of the textbooks and other material specified on Webcourses. (ii) Submit the 3-2-1 assignments by 11:59pm on the day of the class. This is true for all students

including those enrolled in the online section of the class; no exceptions will be made. This is the most important assignment in this class. The 3-2-1 assignments require you to write down three things you learnt in the class, two queries about the class material and one thing you enjoyed about the class.

(iii) Submit the class assignments including programming assignments. (iv) Attend and submit the mid-term I, mid-term II and final examinations. No discussions or

extraneous help is permitted during the exams. Any extraneous help or discussion (including conversation) will be reported to the university for disciplinary action.

(v) Develop and submit a group class project related to fundamentals of computing in FinTech. You are welcome to form groups of at most 6 students. Random student interviews or examinations may be conducted to verify that the student understands all aspects of the class project.

(vi) Complete the reviews of the articles or survey papers made available via Webcourses. Reviews will receive full points if there is evidence of the student having studied the paper. Random student interviews or open-book examinations may be conducted to verify that the student has read the paper

Students may be required to bring a laptop, blue exam book, or a Scantron sheet to the class in order to access the online course-management system or write exams.

Final Exam


The final grade of the class will be computed using the following evaluation metric:

Assessment Percent of Final Grade Article reviews 3-2-1 Summaries

7% 28%

Assignments 25% Mid-term I 5% Mid-term II 5% Final 10% Project 20% 100%



Grading Scale (%)

90 - 100 A 80 - 90 A- 70 - 80 B+ 60 - 70 B 50 - 60 B- 40 - 50 C+ 0 - 40 F


No make up exams or assignments will be permitted without approval of the department. If the Chair of the Computer Science department deems an absence to be excusable for any reason, the instructor shall allow the student to take a make-up exam or complete an alternate assignment. While every effort will be made to ensure that the exam or the assignment is of similar nature, it cannot be guaranteed that the performance of the student on the new exam or assignment will be the same as the original exam or assignment.

Grade Dissemination



1. Introduction to Algorithms, Thomas Cormen, Charles Lieserson, Ronald Rivest, and Clifford Stein, 3rd Edition, MIT Press

2. Computer Architecture: A Quantitative Approach. John Hennessy and David Patterson, 6th Edition, Morgan Kaufmann Series.

3. Additional seminal and/or recent papers on algorithms will be provided via Webcourses.

Policy Statements

Academic Integrity

The Center for Academic Integrity (CAI) defines academic integrity as a commitment, even in the face of adversity, to five fundamental values: honesty, trust, fairness, respect, and responsibility. From these values flow principles of behavior that enable academic communities to translate ideals into action. http://academicintegrity.org/ UCF Creed: Integrity, scholarship, community, creativity, and excellence are the core values that guide our conduct, performance, and decisions.







UCF faculty members have a responsibility for your education and the value of a UCF degree, and so seek to prevent unethical behavior and when necessary respond to infringements of academic integrity. Penalties can include a failing grade in an assignment or in the course, suspension or expulsion from the university, and/or a "Z Designation" on a student's official transcript indicating academic dishonesty,



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University of Central Florida College of Engineering and Computer Science

Department of Electrical and Computer Engineering EEE 5061:

“Cyber-Physical Technologies for Smart Communities”

Fall 20xx – 3 Credit Hours

Instructor

Dr. Yaser Fallah HEC 355, 407-823-4182 [email protected]

Prerequisites

Graduate standing in CECS. Instructor permission or one of the following: Signals and Systems, Communication networks, Power Systems. Familiarity with Python or MATLAB (for course project).

Textbook The course is based on lecture notes and survey papers. Some

helpful textbooks are:

Course Description

Study of new technological advances in areas such as sensing, computing, device and communications that enable smart and connected communities - The above technologies and their use in smart grid, smart infrastructure and intelligent transportation systems will be described and analyzed. An overview of system building approaches using the new technologies will be offered. The role of IoT, sensor networks, autonomous vehicles, renewable energy sources and cooperative control will be discussed.

Learning Outcomes

Understand the new technologies and their role in enabling smart

communities concept. Learn system building approaches from a cyber physical systems

perspective Learn how technology impacts these complex systems and what

tools may be needed for system design and modeling. Apply their knowledge of components and technologies to sample

systems simulated in software tools

Grading

Seminars 40%

Quizzes 30%

Term Project Report 30%

Semester Grade

92 ≤ A ≤ 100

80 ≤ B < 90 A- >90, B+ >85

70 ≤ C < 80 B- >77

60 ≤ D < 70

F < 60


Tentative Lecture Topics

The course focuses on the emerging technologies that enable the concept of smart and connected communities (SCC) and its many components such as smart grid, smart infrastructure and intelligent transportation systems. The emphasis of this course is on sensing, computing, communication and device technologies. Specific technologies such as IoT, sensor networks, and autonomous vehicles will be discussed in detail, with more emphasis on the sensing and communication aspects. The objective of the course is to educate students on new technologies that enable SCCs through the design of complex cyber-physical systems. The course will be offered in two segments. In the first part of the course, details of cyber technologies (sensing, networking and computing) and their evolution and future trajectory will be discussed. Specific devices and protocols will be examined. In the second part of the course, system building and analysis of SCCs that are built using these technologies will be taught. The aim is to educate students on both the technical advances in sensing, communication and device technologies, as well as on the basic systems science that allows embedding technology in smart systems. Example applications and systems designed and modeled in software tools will be presented and offered as course projects and learning modules.

1. Introduction (Week 1-2)

a. Smart and Connected Communities

b. Energy, Transportation, and Infrastructure, how they interact

c. Cyber technology advances

2. Device Technologies (Week 3-4)

a. New devices enabling new architectures in smart infrastructure, smart grid,

renewable energy, solid state components

b. New transportation modes and components, autonomous and electric vehicles

c. Building technologies

3. Sensing Technologies (Week 5-8)

a. Sensor Types (simple to complex sensors), Cameras, radar, lidar

b. Internet of Things

c. Global Positioning Systems

d. Sensors for Autonomous Vehicles

e. Situational Awareness, Cooperative Perception, Systems perspective

4. Communications Technologies (Week 9-14)

a. Wired and Wireless Communication for Smart Grid, EMCS

b. Wireless Communication in intelligent transportation systems

c. V2V, V2I and V2X communications for Connected and Autonomous Vehicles (5G, LTE)

d. Sensor Networks (protocols, device and network types), network management

e. Communications as a component of the system vs networked systems

5. Computing Technologies (Week 14-16)

a. Embedded computing, microcontrollers and CPUs

b. Middleware architectures and new industrial tools

c. Cloud computing for smart systems

d. Software architectures, networked systems

e. System level design and analysis

Course format: Lectures every week, plus seminars presentations by students. Software based simulation and training will be utilized from week 8 to 16.

Class Policy

General: Attendance at lecture is expected. If you miss a class, you are responsible for all assignments and material covered. You are required to participate in all class discussions. You will be required to answer questions or discuss your solutions in class. You must maintain good class notes and should review all past materials covered before attending a class.

Homework Assignments: There will be 2-3 Homework assignments during the semester. Typically problems will be assigned in class. These exercises are to help you determine your level of mastery of knowledge presented in class.

Term Paper: The term paper will be a report on a project that each student is expected to complete during the semester. The grading will be based on the thoroughness of the work in several areas: search of research topics, understanding the technical papers, and exploring new solutions.

Seminars: Students are expected to present three 20-30 minute seminars in class. The aim is to evaluate their level of mastery of the research methods thought in class. Evaluation will not be based on presentation skills. The first seminar is expected to be on a general topic and include literature survey. The second and third seminars will focus on the term project, covering design methodologies, and evaluation and testing.

Help in Learning: If you attended the lectures and did not understand any material, see the instructor promptly – before the next lecture. If you did not attend the class, first obtain the notes from your classmates, review the material, and then promptly see your instructor.

Plagiarism: Plagiarism will be severely penalized according to UCF rules and may result in an F grade for the course or receive no credit for the specific test or project. Students are expected to exhibit the same level of professionalism and integrity that will distinguish them in their future careers. Both the person who reproduced in whole or in any part from the work of others and the person who allowed the work to be copied will be penalized. Consequences and procedures for dealing with cases of academic dishonesty are outlined in the UCF Student Code of Rights and Responsibilities.

Inclusivity: The University of Central Florida community is committed to creating and fostering a positive learning and working environment based on open communication, mutual respect, and inclusion. If you are a person with a disability and anticipate needing any type of accommodation in order to participate in this class, please advise me and make appropriate arrangements with the Office of Disability Services.

Note: This course may contain copyright protected materials such as audio or video clips, images, text

materials, etc. These items are being used with regard to the Fair Use doctrine in order to

enhance the learning environment. Please do not copy, duplicate, download or distribute these

items. The use of these materials is strictly reserved for this online classroom environment and

your use only. All copyright materials are credited to the copyright holder.

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1

EEL 4294: Introduction to Smart Grid

Department of Electrical and Computer Engineering

College of Engineering and Computer Science, University of Central Florida

COURSE SYLLABUS

Instructor: Dr. Wei Sun Term: Spring

Office: HEC 306 Class Meeting Days: Mon. and Wed.

Phone: (407) 823‐2344 Class Meeting Hours: 10:30AM‐11:45AM

E‐Mail: [email protected] Class Location: CB1 O117

Website: http://www.eecs.ucf.edu/~weisun Lab Location: N/A

Office Hours: TBD Teaching Assistant: TBA

I. University Course Catalog Description

Fundamentals of electric power systems, distributed generation and smart grid components, voltage control and VAR

compensation, demand response, leader‐follower optimization, resiliency. Spring.

II. Course Overview

This is an introductory course to smart grid and renewable energy. It covers topics of analysis and design of power

systems in presence of distributed generation with focus on modeling, control and protection systems. The course is

designed to equip students with the basic knowledge of smart grid, and prepare students for entry‐level power

engineering jobs as well as advanced study.

III. Course Objectives

This course builds up and addresses the following goals:

1) Explain the fundamental technology challenges associated with the use of energy storage such as

interconnection and operational configurations, regulatory and policy issues, cost models and economic

evaluations

2) Implement a grid control scheme using fundamental algorithms considering tradeoff between centralized and

distributed approaches

3) Apply data analytics to improve power systems performances

4) Explain how demand response can improve grid performance

5) Design protection systems for distribution grids that contain distributed energy resources

6) Name and explain standards that apply to grid interconnection of distributed energy resources

7) Assess some of the cyber security risks introduced by a distributed energy resource

IV. Course Prerequisites

(EEE 3307C and EEL 3657) or EEL 4216 or C.I.

V. Course Credits

3 credit hours

2

VI. Required/Supplementary Texts and Materials

All lecture notes and other materials (e.g., videos, papers, reports, etc.) will be posted on webcourses@ucf.

VII. Software

MATLAB SimPowerSystems and OpenDSS for homework and projects. VIII. Topics

1. Distributed generation characteristics and fundamental components

2. Modeling and simulation of distributed generation effects on power system operation

3. Role of energy storage 4. Control solution for distributed energy resources 5. Protection systems

6. Introduction to the standards for interconnecting distributed resources with electric power systems

7. The role of markets and policies

8. Cybersecurity in power systems

* Note: The topics are subject to revision

IX. Course Delivery

This course uses a combination of live, real‐time instruction as well as asynchronous student discussion board response via an online class management system (e.g., webcourses). Methods to be used include live lectures and discussions, “voice‐over PowerPoint” presentations, and written assignments.

Student‐to‐ Module‐Instructor Interaction: Students will listen/view lectures online (voice‐over PowerPoint) and interact with the module instructor through discussion board and emails. Module Coordinators and/or Instructors will post weekly prompt(s) and respond to student postings. The instructor will post weekly announcements, provide individual feedback to students, and hold online office hours.

Student‐to‐ Local‐Instructor Interaction: Students will meet (face to face) weekly with the local instructor to review the class material

Student‐to‐Student Interactions: Students will engage in discussions with other students, including throughout the FEEDER consortium, via the discussion board.

Student will work with students at other universities on the final project

Student to Content Interaction: Students will engage with course content by completing reading assignments, listening/viewing Module Instructor presentations, writing discussion boards postings, and completing homework assignments, and contribute to the work of a project team.

X. Basis for Final Grade

Assessment Percent of Final Grade

Homework 40%

Project 40%

Final Exam 20%

Total

100%

Grading Scale (%)

94‐100 A 74‐76 C

90‐93 A‐ 70‐73 C‐

87‐89 B+ 67‐69 D+

84‐86 B 64‐66 D

80‐83 B‐ 60‐63 D‐

77‐79 C+ 0 ‐ 59 F

1. Homework: Homework will be assigned each week, and submitted on webcourses. Problem solutions must show a clear and systematic method for arriving at the correct solution for full credit. Grading criteria, in the form of a rubric, will be provided for each assignment. Both undergraduate and graduate students will have the same homework, but undergraduate students may need additional reading to work on homework and will have more percentage of homework in the final grade.

3

2. Course Project: A group project will be assigned near the middle of the semester, due at the end of the semester. Each group will be composed of both undergraduate and graduate students. A group leader, usually a graduate student, will be responsible for group coordination and organization and reporting of the project. Undergraduate team members will be responsible for specific technical tasks. The project will be graded differently for undergraduate and graduate students to reflect the different requirements and responsibilities. Undergraduate students will have less percentage of project in the final grade.

3. Exams: The final exam is comprehensive. Unless you are otherwise informed by the instructor, all exams will be closed‐book, closed‐notes. Students will be allowed to use only writing instruments and a calculator. All other instruments or devices are prohibited. There are no make‐ups for the final exam. Both undergraduate and graduate students have same percentage of final exam in the final grade.

XI. Grade Dissemination

Graded tests and materials in this course will be returned individually only by request. You can access your scores at any time using "myUCF Grades" in the portal. Please note that scores returned mid‐semester are unofficial grades. If you need help accessing myUCF Grades, see the online tutorial: https://myucfgrades.ucf.edu/help/.

XII. Course Policies

Course Offering: Lecture slides will be posted on webcourses before each lecture. It is imperative to review the material to be covered in both slides and textbook. During class time, key points will be emphasized with example problems and/or quizzes. You are highly encouraged to participate in discussion during the class.

Attendance: Although there is no attendance check, you are expected to show up every class. It is imperative that you come to class and take notes.

Email: It is the student’s responsibility to check email often. When emailing instructor, in the email subject line, type: EEL4294 + additional, yet concise, useful/revealing info. Provide sufficient detail in the text message.

Financial Aid Requirement: All instructors/faculty are required to document students’ academic activity at the beginning of each course. In order to document that you began this course, please complete the following academic activity by the end of the first week of classes or as soon as possible after adding the course. Failure to do so may result in a delay in the disbursement of your financial aid.

Grades of "Incomplete": The current university policy concerning incomplete grades will be followed in this course. Incomplete grades are given only in situations where unexpected emergencies prevent a student from completing the course and the remaining work can be completed the next semester. Your instructor is the final authority on whether you qualify for an incomplete. Incomplete work must be finished by the end of the subsequent semester or the “I” will automatically be recorded as an “F” on your transcript.

XIII. Course Policies: Student Expectations

Disability Access: The University of Central Florida is committed to providing reasonable accommodations for all persons with disabilities. This syllabus is available in alternate formats upon request. Students who need accommodations must be registered with Student Disability Services, Ferrell Commons Room 185, phone (407) 823‐2371, TTY/TDD only phone (407) 823‐2116, before requesting accommodations from the professor.

Professionalism Policy: Per university policy and classroom etiquette; mobile phones, iPods, etc. must be silenced during all classroom and lab lectures. Those not heeding this rule will be asked to leave the classroom/lab immediately so as to not disrupt the learning environment. Please arrive on time for all class meetings. Students who habitually disturb the class by talking, arriving late, etc., and have been warned may suffer a reduction in their final class grade.

Academic Conduct Policy: Academic dishonesty in any form will not be tolerated. If you are uncertain as to what constitutes academic dishonesty, please consult The Golden Rule, the University of Central Florida's Student Handbook (http://www.goldenrule.sdes.ucf.edu/) for further details. As in all University courses, The Golden Rule Rules of Conduct will be applied. Violations of these rules will result in a record of the infraction being placed in your file and receiving a zero on the work in question AT A MINIMUM. At the instructor’s discretion,

4

you may also receive a failing grade for the course. Confirmation of such incidents can also result in expulsion from the University.

University Writing Center: The University Writing Center (UWC) is a free resource for UCF undergraduates and graduates. At the UWC, a trained writing consultant will work individually with you on anything you're writing (in or out of class), at any point in the writing process from brainstorming to editing. Appointments are recommended, but not required. For more information or to make an appointment, visit the UWC website at http://www.uwc.ucf.edu, stop by MOD 608, or call 407.823.2197.

1

EEL 5294: Introduction to Smart Grid



COURSE SYLLABUS

Instructor: Dr. Wei Sun Term: Spring

Office: HEC 306 Class Meeting Days: Mon. and Wed.

Phone: (407) 823‐2344 Class Meeting Hours: 10:30AM‐11:45AM

E‐Mail: [email protected] Class Location: CB1 O117

Website: http://www.eecs.ucf.edu/~weisun Lab Location: N/A

Office Hours: TBD Teaching Assistant: TBA


Fundamentals of electric power systems, distributed generation and smart grid components, voltage control and VAR

compensation, demand response, leader‐follower optimization, resiliency. Spring.

II. Course Overview

This is an advanced course to smart grid and renewable energy. It covers topics of analysis and design of power

systems in presence of distributed generation with focus on modeling, control and protection systems. The course is

designed to equip students with the basic knowledge of smart grid, and prepare students for power engineering jobs

as well as advanced study.

III. Course Objectives

This course builds up and addresses the following goals:

1) Explain the fundamental technology challenges associated with the use of energy storage such as, cost models

and economic evaluations, interconnection and operational configurations, regulatory and policy issues

2) Implement a grid control scheme using fundamental algorithms considering tradeoff between centralized and

distributed approaches

3) Apply data analytics to improve power systems performances

4) Explain how demand response can improve grid performance

5) Design protection systems for distribution grids that contain distributed energy resources

6) Name and explain standards that apply to grid interconnection of distributed energy resources

7) Assess some of the cyber security risks introduced by a distributed energy resource

8) Lead a team to design a distributed energy resources system considering regulatory, security and technical

constraints and present the results

9) Develop skills to communicate effectively through writing and presentation.

10) Prepare students for multidisciplinary research in power system area.


EEL4216 or C.I. Familiar with power system analysis methods at the level of standard text books, including the ones

by Bergen & Vittal, Grainger & Stevenson, and Glover & Sarma. Familiar with the topics of matrix algebra, calculus,

network analysis theory including electric power flow analysis, and basic optimization concepts.

2

V. Course Credits

3 credit hours

VI. Required/Supplementary Texts and Materials

All lecture notes and other materials (e.g., videos, papers, reports, etc.) will be posted on webcourses@ucf.

VII. Software

MATLAB SimPowerSystems and OpenDSS for homework and projects. VIII. Topics

1. Distributed generation characteristics and fundamental components

2. Modeling and simulation of distributed generation effects on power system operation

3. Role of energy storage 4. Control solution for distributed energy resources 5. Protection systems

6. Introduction to the standards for interconnecting distributed resources with electric power systems

7. The role of markets and policies

8. Cybersecurity in power systems

* Note: The topics are subject to revision

IX. Course Delivery

This course uses a combination of live, real‐time instruction as well as asynchronous student discussion board response via an online class management system (e.g., webcourses). Methods to be used include live lectures and discussions, “voice‐over PowerPoint” presentations, and written assignments.

Student‐to‐ Module‐Instructor Interaction: Students will listen/view lectures online (voice‐over PowerPoint) and interact with the module instructor through discussion board and emails. Module Coordinators and/or Instructors will post weekly prompt(s) and respond to student postings. The instructor will post weekly announcements, provide individual feedback to students, and hold online office hours.

Student‐to‐ Local‐Instructor Interaction: Students will meet (face to face) weekly with the local instructor to review the class material

Student‐to‐Student Interactions: Students will engage in discussions with other students, including throughout the FEEDER consortium, via the discussion board.

Student will work with students at other universities on the final project

Student to Content Interaction: Students will engage with course content by completing reading assignments, listening/viewing Module Instructor presentations, writing discussion boards postings, and completing homework assignments, and contribute to the work of a project team.

X. Basis for Final Grade


Homework 20%

Projects 60%

Final Exam 20%

Total

100%

Grading Scale (%)

94‐100 A 74‐76 C

90‐93 A‐ 70‐73 C‐

87‐89 B+ 67‐69 D+

84‐86 B 64‐66 D

80‐83 B‐ 60‐63 D‐

77‐79 C+ 0 ‐ 59 F

1. Homework: Homework will be assigned each week, and submitted on webcourses. Problem solutions must show a clear and systematic method for arriving at the correct solution for full credit. Grading criteria, in the

3

form of a rubric, will be provided for each assignment. Both undergraduate and graduate students will have the same homework, but graduate students should have already been familiar with the basics to work on homework and will have less percentage of homework in the final grade.

2. Course Projects: A group project will be assigned near the middle of the semester, due at the end of the semester. Each group will be composed of both undergraduate and graduate students. A group leader, usually a graduate student, will be responsible for group coordination and organization and reporting of the project. Undergraduate team members will be responsible for specific technical tasks. The project will be graded differently for undergraduate and graduate students to reflect the different requirements and responsibilities. Additional, one individual project will be assigned only for graduate students. It involves, propose a research topic on smart grid and renewable energy, develop and implement models/algorithms in software simulation, and submit a technical report. Graduate students will have more percentage of projects in the final grade.

3. Exams: The final exam is comprehensive. Unless you are otherwise informed by the instructor, all exams will be closed‐book, closed‐notes. Students will be allowed to use only writing instruments and a calculator. All other instruments or devices are prohibited. There are no make‐ups for the final exam. Both undergraduate and graduate students have same percentage of final exam in the final grade.

XI. Grade Dissemination

Graded tests and materials in this course will be returned individually only by request. You can access your scores at any time using "myUCF Grades" in the portal. Please note that scores returned mid‐semester are unofficial grades. If you need help accessing myUCF Grades, see the online tutorial: https://myucfgrades.ucf.edu/help/.

XII. Course Policies

Course Offering: Lecture slides will be posted on webcourses before each lecture. It is imperative to review the material to be covered in both slides and textbook. During class time, key points will be emphasized with example problems and/or quizzes. You are highly encouraged to participate in discussion during the class.

Attendance: Although there is no attendance check, you are expected to show up every class. It is imperative that you come to class and take notes.

Email: It is the student’s responsibility to check email often. When emailing instructor, in the email subject line, type: EEL5294 + additional, yet concise, useful/revealing info. Provide sufficient detail in the text message.


Grades of "Incomplete": The current university policy concerning incomplete grades will be followed in this course. Incomplete grades are given only in situations where unexpected emergencies prevent a student from completing the course and the remaining work can be completed the next semester. Your instructor is the final authority on whether you qualify for an incomplete. Incomplete work must be finished by the end of the subsequent semester or the “I” will automatically be recorded as an “F” on your transcript.

XIII. Course Policies: Student Expectations

Disability Access: The University of Central Florida is committed to providing reasonable accommodations for all persons with disabilities. This syllabus is available in alternate formats upon request. Students who need accommodations must be registered with Student Disability Services, Ferrell Commons Room 185, phone (407) 823‐2371, TTY/TDD only phone (407) 823‐2116, before requesting accommodations from the professor.


4

Academic Conduct Policy: Academic dishonesty in any form will not be tolerated. If you are uncertain as to what constitutes academic dishonesty, please consult The Golden Rule, the University of Central Florida's Student Handbook (http://www.goldenrule.sdes.ucf.edu/) for further details. As in all University courses, The Golden Rule Rules of Conduct will be applied. Violations of these rules will result in a record of the infraction being placed in your file and receiving a zero on the work in question AT A MINIMUM. At the instructor’s discretion, you may also receive a failing grade for the course. Confirmation of such incidents can also result in expulsion from the University.

University Writing Center: The University Writing Center (UWC) is a free resource for UCF undergraduates and graduates. At the UWC, a trained writing consultant will work individually with you on anything you're writing (in or out of class), at any point in the writing process from brainstorming to editing. Appointments are recommended, but not required. For more information or to make an appointment, visit the UWC website at http://www.uwc.ucf.edu, stop by MOD 608, or call 407.823.2197.

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1

EEL 6297: Attacks and Defenses in Secure Cyber-Physical Systems



COURSE SYLLABUS

Instructor: Dr. Junjian Qi Term:

Office: R1 150E Class Meeting Days:

Phone: (407) 823-1305 Class Meeting Hours:

E-Mail: [email protected] Class Location:

Website: http://www.ece.ucf.edu/~jqi/ Lab Location: N/A

Office Hours:


Topics to include basics of cyber-physical systems (CPSs), security challenges and issues for CPSs, and

defense approaches to enhance their security.

II. Course Overview

This is an advanced course to security of cyber-physical systems, designed to provide students with the

knowledge of security challenges and issues for CPSs and defense approaches to enhance their security.

Course content includes basics of cyber-physical systems, network security, key management in CPSs,

lightweight crypto and security, security vulnerabilities and challenges in IoT, detecting data integrity

attacks in smart grid, cyber attacks against smart grid wide-area control, cybersecurity of smart buildings,

and cybersecurity for distributed energy resources and smart inverters.

III. Learning Outcomes

By the end of this course, graduate students will be able to:

Describe basic concepts of the CPSs,

Acquire knowledge of security issues and challenges of CPSs,

Acquire knowledge of attacks and defenses in CPSs,

Develop skills to communicate effectively through writing and presentation,

Develop the ability to apply knowledge of cyber-physical systems,

Describe in a report, and build a math model based method to enhance the security of CPSs.


Course Prerequisites: EEL4294 Introduction to Smart Grid or equivalent or consent of instructor.

V. Course Credits

3 credit hours

2

VI. Required Texts and Materials

[1] H. Song, G. A. Fink, and S. Jeschke, Security and Privacy in Cyber-Physical Systems: Foundations,

Principles, and Applications, Wiley-IEEE Press, 2017.

VII. Supplementary (Optional) Texts and Materials

[2] Al-Sakib Khan Pathan, Securing Cyber-Physical Systems, CRC Press, 2015.

[3] Rajeev Alur, Principles of Cyber-Physical Systems, MIT press, 2015.

VIII. Topics

Basics on cyber-physical systems (CPSs)

Security issues in CPSs

Approaches to secure CPSs

Network security

National security concerns from CPSs

Legal considerations of CPSs and the Internet of Things (IoT)

Key management in CPSs

Lightweight crypto and security

Security issues, vulnerabilities, and challenges in IoT

Cyber-physical vulnerabilities of wireless sensor networks in smart cities

Detecting data integrity attacks in smart grid

Cyber attacks against smart grid wide-area control

Cybersecurity of smart buildings

Cybersecurity for distributed energy resources and smart inverters

IX. Course Evaluation

Project

At the beginning of the class, each student picks his/her own topic, and students are expected to conduct

in-depth research on that topic throughout the semester, including literature review, algorithm design,

implementation and case studies. Students are required to submit a midterm and a final written report.

Presentations

Students are required to give one topic presentation and one project presentation in the class. Each

presentation will last for 20 minutes. The topic presentation serves as a summary of the literature review.

It should cover background on the selected topics and a review of one selected method or algorithm that

you think innovative and creative. The project presentation will be held at the end of the course, and it

should cover details of your research journey (literature review, your methodology, implementation and

case studies).

Percent of Final Grade

Homework: 25%

Topic Presentation: 15%

Project Presentation: 15%

Midterm Project Report: 20%

Final Project Report: 25%

Grading Scale

3

A: 90-100

A-: 87-90

B+: 83-87

B: 80-83

B-: 77-80

C+: 73-77

C: 70-73

D: 60-70

F: 0-60

X. Course Policies


Late homework will not be accepted.

Report format: Competition and project report submission should follow IEEE journal format.

Plagiarism: It is not allowed and will be heavily penalized based on UCF student policies.

Email: It is the student’s responsibility to check email often. When emailing instructor, in the email subject line, type: EEL6XXX + additional, yet concise, useful/revealing information. Provide sufficient detail in the text message.

Attendance: You are highly encouraged to participate in discussion during the class. Although there is no attendance check, you are expected to show up every class. It is imperative that you come to class and take notes.

Disability Access: The University of Central Florida is committed to providing reasonable accommodations for all persons with disabilities. This syllabus is available in alternate formats upon request. Students who need accommodations must be registered with Student Disability Services, Ferrell Commons Room 185, phone (407) 823-2371, TTY/TDD only phone (407) 823-2116, before requesting accommodations from the professor.


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University of Central Florida College of Engineering and Computer Science


Course Stochastic Control EEL 6675 (3 Credit Hours)

Instructor: Dr. Chinwendu Enyioha HEC 416 407-823-0122 [email protected]

Office Hours TBD Pre-requisites

EEL 3657 (Linear Control Systems), EEL 4612 (Introduction to Modern and Robust Control); some background or working knowledge of EEL 5542 (Random processes), linear algebra and MATLAB (for the course project).

University Course Catalog Description

Concepts and practical aspects of stochastic control: MDPs and stochastic stability, dynamic programming, complete and partial information, Linear quadratic regulator and Kalman filtering.

Topics to be covered

The course will cover fundamental models and solution techniques for decision-making problems in the presence of uncertainty; optimal control of systems with stochastic dynamics; problems with perfect as well as imperfect state information; problems with large state spaces, the curse of dimensionality and approximation methods. The dynamic programming elements will focus on optimal control problems and solutions via the Calculus of variations and Hamilton-Jacobi-Bellman equations; stochastic principle of optimality for systems with perfect and imperfect measurements. Special topics will include stability of stochastic systems with some attention to other recent computational techniques.

Learning outcomes Upon successful completion of the course, students will be able to:

Formulate problems in stochastic systems for control Understand and utilize linear and Markov models to capture system dynamics and uncertainty Propose and design control strategies based and characterize the performance of the controlled

system Use stochastic dynamic programming theory and related topics to characterize solutions and

system stability. Proposed Textbooks

Dynamic Programming and Optimal Control, Vols. 1 and 2, 3rd ed, Athena Scientific (2007) by Bertsekas, D.P.

Lectures on Stochastic Programming: Modeling and Theory, SIAM (2009) by Shapiro, A., Dentcheva, D. and Ruszczynski, A.

Grade basis

Homework Assignments Assigned, not graded Exam 1 (35%) Exam 2 (35%) Project (30%)


Grading scale 90 – 100 A 80 – 89 B 70 – 79 C 60 – 69 D 50 – 59 E 0 – 49 F

General

Attendance at lecture is expected. If you miss a class, you are responsible for all assignments and materials covered. You are encouraged to participate in all class discussions. You may be required to answer questions or discuss your solutions in class. Students must maintain good class notes and should review all past materials covered before attending a class.

Announcements:

In addition to in-class notices made, correspondence in this course will be via Webcourses. Students are responsible for checking the announcement page at least daily.

Classroom policies:

Per university policy and classroom etiquette, mobile phone and electronic devices must be silence during all classroom lectures. Students who violate this policy may be asked to leave the classroom immediately to prevent further disruption of the learning environment. Students are encouraged to arrive on time for all class meetings.

Academic Conduct

Academic dishonesty in any form will not be tolerated. If you are uncertain as to what constitutes academic dishonesty, please consult The Golden Rule, the University of Central Florida's Student Handbook (http://www.goldenrule.sdes.ucf.edu/) for further details. As in all University courses, The Golden Rule Rules of Conduct will be applied. Violations of these rules will result in a record of the infraction being placed in your file and receiving a zero on the work in question AT A MINIMUM. At the instructor’s discretion, you may also receive a failing grade for the course. Confirmation of such incidents can also result in expulsion from the University.

Inclusivity

The University of Central Florida community is committed to creating and fostering a positive learning and working environment based on open communication, mutual respect and inclusion. If you are a person with a disability and anticipate needing any type of accommodation in order to participate in this class, please advise me and make appropriate arrangement with the Office of Disability Services.

Recording Academic Activity (for financial aid purposes):

Faculty members are required to document students’ academic activity at the beginning of each course. In order to document that you began this course, please complete Problem set 0 by the end of the first week of classes, or as soon as possible after adding the course. Failure to do so will could result in a delay in the disbursement of your financial aid.

Copyrighted materials

This course may contain copyright-protected materials such as audio, video clips, images, text materials etc. These items are being with regard to the Fair Use doctrine to enhance the learning environment. Please do not copy, duplicate, download or distribute these items. The use of these materials is strictly reserved for this online classroom environment and your use only. All copyright materials are credit to the copyright holder.

http://www.goldenrule.sdes.ucf.edu/)

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Special Topics: OSE 6938X

Infrared Detectors College of Optics and Photonics, University of Central Florida

COURSE SYLLABUS

Instructor: David Shelton Term: Spring 2019

Office: Class Meeting Days: Tuesdays

Phone: 407-920-4844 Class Meeting Hours: 5-8pm

E-Mail: [email protected] Class Location: UCF Main Campus

Website: Office Hours:

I. Welcome!

I hope you enjoy this course as much as I have enjoyed working in the area.

II. University Course Catalog Description

This class will review appropriate background including mathematics, radiometry, and solid-state physics necessary for the

design of infrared detectors. Major types of infrared detectors that will be covered include thermal, photoconductors,

photovoltaic, and photodiodes. Modern starring-infrared-focal-plane design will be emphasized. Design and measurement of

detector properties that contribute to detector sensitivity will be considered.

III. Course Overview

This course is presented in three sections. The first section will cover optical detection fundamentals and includes many topics that are not exclusive to infrared detection. This will include a review of some concepts from geometrical optics, radiometric calculations, probability and statistics for optical detection, and the develop of figures of merit for sensitivity which are used across the infrared systems industry. Optical detection mechanisms will be discussed, and the use of these detection mechanisms in infrared systems will be developed. In the second section, the design of infrared detectors based on critical material systems will be presented. Detector material systems to be considered include: mercury-cadmium-telluride, III-V compound strained-layer-superlattices, lead-salts, and vanadium-oxide. Solid-state physics required for detector design will be reviewed and design examples for detectors from the major material systems will be analyzed to enable modeling of detector sensitivity. Operating conditions for infrared detectors will be discussed. Finally the third section will cover an overview of practical tools and methods used to design, fabricate, and test infrared detectors. Topics closely related to starring infrared-focal-plane arrays will also be covered.

IV. Course Objectives and Outcomes

This is a graduate level course. The course is intended to provide a practical understanding of infrared detectors for those working with electro-optical sensors in the defense, security, industrial inspection, medical imaging, and similar industries. At the end of the course students will be expected to demonstrate proficiency in calculating the sensitivity, response rates, and other key performance factors for infrared detectors under a variety of operating conditions. Students will then be expected to select the proper detector and operating conditions for a given task while considering both performance and other issues such as cost, size, weight, power consumption, reliability, and technical risk. .

V. Course Prerequisites

It is expected that the student will have math background through calculus 2, a general working knowledge of electro-optical

sensors, and an undergraduate level understanding of solid-state physics consistent with most electrical-engineering and

physics programs. A review of these topics will be provided as relevant to course material. No formal prerequisite course is

required.

VI. Course Credits

3 (3,0)

VII. Required Texts and Materials

Infrared Detectors and Systems – E.L. Dereniak, G.D. Boreman

I will provide other papers and excerpts.

VIII. Topics Covered

Introduction Jan 8

Starring IR Focal Plane Arrays Jan 8

Radiometry Jan 15

Optical Detection Mechanisms Jan 22

Probability and Statistics Jan 22

Noise Jan 29

Figures of Merit Jan 29

Photovoltaics Feb 5

Photoconductors Feb 5

Photodiodes Feb 12

Thermal Detectors Feb 12

Exam 1 Feb 19

Solid State Physics Review Feb 19 after exam

Lead-Salt Detectors Feb 26

III-V Alloys Feb 26

Mercury Cadmium Telluride Mar 5

Spring-break, no class Mar 12

SLS Detectors Mar 19

Barrier Layer Detectors Mar 19

Microbolometers Mar 26

Exam 2 Apr 2

Infrared Detector Fabrication Apr 2

Infrared Detector Testing Apr 9

Readout Integrated Circuit Architectures Apr 16

Advanced Topics Apr 16

Final Exam Apr 30

IX. Basis for Final Grade


Exam 1: In Class Open Book / notes 20%

Exam 2: In Class Open Book / notes 20%

Exam 3: Final Exam Open Book / notes 40%

Homework 20%

100%

Grading Scale (%)

94-100 A

90-93 A-

87-89 B+

84-86 B

80-83 B-

77-79 C+

74-76 C

70-73 C-

67-69 D+

64-66 D

60-63 D-

0 – 59 F

X. Grade Dissemination

Graded tests and materials in this course will be returned individually only by request. You can access your scores at any time using "myUCF Grades" in the portal. Please note that scores returned mid-semester are unofficial grades. If you need help accessing myUCF Grades, see the online tutorial: https://myucfgrades.ucf.edu/help/.

XI. Course Policies: Grades

Late Work Policy:

There are no make-ups for in-class tests, or the final exam. Arrangements due to conflicts need to be worked out with me prior to the test(s) and will likely occur on campus. Take home assignments will be assigned with plenty of time to complete, and will not be accepted late. Extra Credit Policy: Generally, there is no extra credit. Grades of "Incomplete": The current university policy concerning incomplete grades will be followed in this course. Incomplete grades are given only in situations where unexpected emergencies prevent a student from completing the course and the remaining work can be completed the next semester. Your instructor is the final authority on whether you qualify for an incomplete. Incomplete work must be finished by the end of the subsequent semester or the “I” will automatically be recorded as an “F” on your transcript. Rewrite Policy:

Rewrites do not apply.

XII. Course Policies: Technology and Media

Email: Majority of interaction is expected during and after class. Email will be used on any issues related to participation.

Webcourses: Not used in this course. Laptop Usage: Laptops are not allowed in class. Classroom Devices: Cell phone and electronic devices must be turned off during class.

https://myucfgrades.ucf.edu/help/

1

Rachel Agerton-Franzetta

From: Eduardo MuccioloSent: Monday, December 17, 2018 8:08 AMTo: Rachel Agerton-FranzettaSubject: Re: Request for Overlap Comments/Approval for Special Topics Course

Hi Rachel, Our Graduate Curriculum committee looked into the syllabus and have no concerns or comments. Thanks for checking with us. Eduardo — Eduardo Mucciolo Professor and Chair Department of Physics University of Central Florida Orlando, FL 32816, USA (+1)407‐823‐1882 [email protected] www.physics.ucf.edu

From: Rachel Agerton‐Franzetta <[email protected]> Date: Thursday, December 13, 2018 at 3:34 PM To: Eduardo Mucciolo <[email protected]> Subject: Request for Overlap Comments/Approval for Special Topics Course Hello Eduardo, We are submitting a Special Topics class for approval: ST: Infrared Detectors Attached is the syllabus for your review and comment/Approval. Please respond to let me know if this is okay from the Physics perspective. Thanks for your help, Rachel Franzetta College of Optics and Photonics University of Central Florida 4304 Scorpius Street., Box 162700 Orlando, FL 32816‐2700 407‐823‐6986 [email protected]

Please note: Florida has a very broad open records law (F.S. 119). Emails may be subject to public disclosure.

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1

EMA 5585 – Materials Science of Thin Films Course Syllabus

Course Information

Course title: Materials Science of Thin Films

Course number: EMA 5585

Credit hours: 3

Semester: TBD

Prerequisites: Graduate standing or C.I.

Meeting times: TBD

Meeting location: TBD

Course modality: TBD

Website: Materials made available on UCF Webcourses system

Instructor

Dr. Kristopher O. Davis

Office location: Research I – 150H

Office hours: TBD

Office phone: (407) 823-2415

Email: [email protected] (preferred method of communication)

Course Description

Catalog description: Interaction of thin film processing techniques with the

structure and properties of the materials deposited.

Intended Student Learning Outcomes

The fundamental objective is to understand how to process thin films to have the

properties desired for various R&D and industrial applications.

To understand how thin film processing controls film microstructure.

To understand how film microstructure effects film properties.

To understand how to characterize thin films for both research and quality control

purposes.

To apply this knowledge to solve problems related to the application of thin films in

R&D and industry.

Graded Assessments of Student Learning

The following assessments will be used to evaluate student learning. The percentages

represent the fraction of the final grade.

Participation 5% – Graded discussions on Webcourses, online quizzes

Homework1 20% – Submitted via email to [email protected] as a PDF with

1 Late homework not accepted



2

the naming convention of LastName_FirstName_HWX.pdf

Midterm exam 25%

Report 20% – Submitted via email to [email protected] as a PDF with the

naming convention of LastName_FirstName_Report.pdf

Final exam 30% – Held on Wednesday, December 5, 2018 from 4:00PM-6:50PM

Grading Policy and Course Requirements

The following letter grading scale will be used with no plus-minus.

A 90-100%

B 80-90%

C 70-80%

D 60-70%

F 0-60%

Holidays

TBD

Textbook Required

M. Ohring, Materials Science of Thin Films. 2nd Edition (2001).

Textbooks - Optional

M. Grundmann, The Physics of Semiconductors. 2nd Edition (2010)

S.M. Sze, K. K. Ng. Physics of Semiconductor Devices. 3rd Edition (2016).

M. Fox, Optical Properties of Solids. (2001).

S. Kasap, Peter Capper (Eds.). Handbook of Electronic and Photonic Materials.

(2006).


3

Course Schedule

Unit Lesson Outline

1 Review of Materials Science




5 Vacuum Science

6 Evaporation

7 Plasmas

8 Sputtering

9 Chemical Vapor Deposition

10 Chemical Vapor Deposition

11 Substrate Surfaces

12 Film Nucleation

13 Review for Midterm

14 Midterm Exam

15 Epitaxy

16 Epitaxy

17 Microstructure

18 Diffusion

19 Mechanical Properties

20 Optical Properties

21 Optical Properties

22 Electrical Properties

23 Electrical Properties

24 Characterization

25 Characterization

26 Characterization

27 Review for Final Exam

28 Final Exam

4

Academic Integrity

The Center for Academic Integrity (CAI) defines academic integrity as a commitment,

even in the face of adversity, to five fundamental values: honesty, trust, fairness,

respect, and responsibility. From these values flow principles of behavior that enable

academic communities to translate ideals into action.


UCF Creed

Integrity, scholarship, community, creativity, and excellence are the core values that

guide our conduct, performance, and decisions.

1. Integrity: I will practice and defend academic and personal honesty.

2. Scholarship: I will cherish and honor learning as a fundamental purpose of my

membership in the UCF community.

3. Community: I will promote an open and supportive campus environment by

respecting the rights and contributions of every individual.

4. Creativity: I will use my talents to enrich the human experience.

5. Excellence: I will strive toward the highest standards of performance in any

endeavor I undertake.


UCF faculty members have a responsibility for your education and the value of a UCF

degree, and so seek to prevent unethical behavior and when necessary respond to

infringements of academic integrity. Penalties can include a failing grade in an

assignment or in the course, suspension or expulsion from the university, and/or a "Z

Designation" on a student's official transcript indicating academic dishonesty, where

the final grade for this course will be preceded by the letter Z. For more information

about the Z Designation, see http://goldenrule.sdes.ucf.edu/zgrade.

For more information about UCF's Rules of Conduct, see

http://www.osc.sdes.ucf.edu/.


There are many fraudulent websites claiming to offer study aids to students but are

actually cheat sites. They encourage students to upload course materials, such as test

questions, individual assignments, and examples of graded material. Such materials

are the intellectual property of instructors, the university, or publishers and may not be

distributed without prior authorization. Students who engage in such activity are in

violation of academic conduct standards and may face penalties.


Faculty have reported errors in class notes being sold by third parties, and the errors

may be contributing to higher failure rates in some classes. The following is a

statement appropriate for distribution to your classes or for inclusion on your syllabus:

Third parties may be selling class notes from this class without my authorization.




5

Please be aware that such class materials may contain errors, which could affect your

performance or grade. Use these materials at your own risk.


Outside of the notetaking and recording services offered by Student Accessibility

Services, the creation of an audio or video recording of all or part of a class for personal

use is allowed only with the advance and explicit written consent of the instructor. Such

recordings are only acceptable in the context of personal, private studying and

notetaking and are not authorized to be shared with anyone without the separate

written approval of the instructor.


The University of Central Florida is committed to providing access and inclusion for all

persons with disabilities. This syllabus is available in alternate formats upon request.

Students with disabilities who need specific access in this course, such as

accommodations, should contact the professor as soon as possible to discuss various

access options. Students should also connect with Student Accessibility Services

(Ferrell Commons, 7F, Room 185, [email protected], phone (407) 823-2371). Through

Student Accessibility Services, a Course Accessibility Letter may be created and sent

to professors, which informs faculty of potential access and accommodations that

might be reasonable.


Emergencies on campus are rare, but if one should arise in our class, we will all need

to work together. Everyone should be aware of the surroundings and familiar with some

basic safety and security concepts.

In case of an emergency, dial 911 for assistance.

Every UCF classroom contains an emergency procedure guide posted on a wall

near the door. Please make a note of the guide’s physical location and consider

reviewing the online version at

http://emergency.ucf.edu/emergency_guide.html.

Familiarize yourself with evacuation routes from each of your classrooms and

have a plan for finding safety in case of an emergency. (Insert class-specific

details if appropriate)

If there is a medical emergency during class, we may need to access a first aid

kit or AED (Automated External Defibrillator). To learn where those items are

located in this building, see http://www.ehs.ucf.edu/AEDlocations-UCF (click

on link from menu on left). (insert class specific information if appropriate)

To stay informed about emergency situations, sign up to receive UCF text alerts

by going to my.ucf.edu and logging in. Click on “Student Self Service” located

on the left side of the screen in the tool bar, scroll down to the blue “Personal

Information” heading on your Student Center screen, click on “UCF Alert”, fill

out the information, including your e-mail address, cell phone number, and cell

phone provider, click “Apply” to save the changes, and then click “OK.”





http://my.ucf.edu/

6

If you have a special need related to emergency situations, please speak with

me during office hours.

Consider viewing this video (https://youtu.be/NIKYajEx4pk) about how to

manage an active shooter situation on campus or elsewhere.


If you are a deployed active duty military student and feel that you may need a special

accommodation due to that unique status, please contact your instructor to discuss

your circumstances.


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1

University of Central Florida

Department of Materials Science and Engineering

EMA 5705

High Temperature Materials

Lectures：to be decided later

Instructor: Dr. Kausik Mukhopadhyay

Office: Research 1 Bldg., Room 278

Email: [email protected] . Office: 407-823-0738

Office Hours: 6 hours (to be decided later) COURSE CREDIT: 3 credit hours. PREREQUISITES (PR): EMA 5104 or Consent of the Instructor TEXTBOOK:

◼ The Superalloys: Fundamentals and Applications by Roger C. Reed Cambridge University Press, New York, NY, 2006 ISBN: 0-521-85904-2

REFFERENCE BOOKS:

• Materials for High Temperature Engineering Applications by G.W. Meetham and M.H. Van de Voorde. Springer, 2000.

COURSE ABSTRACT:

Physical and mechanical metallurgy of high temperature materials will be presented with topics

including strengthening mechanisms of alloys, alloy and process selection, alloy development,

design principles and environmental degradation related to high temperature applications.

Materials classes covered include Ni-base, Co-base and Fe-Ni-base superalloys, refractory

metals, titanium alloys, intermetallic compounds, ceramics and composites. Applications

discussed include propulsion and power generation gas turbines, rocket engines, chemical

processing and nuclear power generation.

Students successfully completing this course will demonstrate the following abilities: (1) Basic Concepts: Write and explain the basic principles related to the synthesis and

applications of the high temperature alloys and materials. (2) Problem Solving: Solve problems involving chemical and physical processes in materials

exposed to aggressive environments.


2

(3) Social and Economic Effects: Discuss the global environmental, social, and economic implications of high temperature materials.

Additional/Selected References: Materials Science and Engineering General

• Schaffer et al., The Science and Design of Engineering Materials, 2nd Ed., McGraw-Hill, 1999.

• M.F. Ashby, D.R.H. Jones, Engineering Materials, Pergamon Press, 1986. • W.D. Callister, Materials Science and Engineering: An Introduction, John Wiley &

Sons; 6th edition, 2002. • D.R. Askeland, The Science and Engineering of Materials, 3rd ed., PWS Publishing,

1994. • R.A. Flynn, P.K. Trojan, Engineering Materials and Their Applications, Houghton

Mifflin, 1990. • J.F. Shackelford, Introduction to Materials Science for Engineers, 3rd ed., Macmillan,

1992. • R.E. Reed-Hill, R. Abbaschian, Physical Metallurgy Principles 3rd ed, PWS

Publishing, 1991. • G.E. Dieter, Mechanical Metallurgy, McGraw-Hill, 1986. • R. Hertzberg, Deformation and Fracture Mechanics of Engineering Materials, John

Wiley, 1976. • D. Hull, Introduction to Dislocations, 3rd ed., Pergamon Press, 1984. • W.D. Kingery, Property Measurement at High Temperatures, John Wiley, 1959. • J. Marin, Mechanical Behavior of Engineering Materials, Prentice Hall, 1990. • Orowan, Fatigue and Fracture of Metals, MIT Press, 1950.

High Temperature Materials

• C.T. Sims, N.S. Stoloff, W.C. Hagel, Superalloys II, John Wiley & Sons, 1987 • M.H. Van de Voorde, G.W. Meetham, Materials for High Temperature

Engineering Applications, Springer Verlag, 2000. • M.J. Donachie, Superalloys – Source Book, ASM, 1984. • J.K. Tien, T. Caufield, Superalloys, Supercomposites and Superceramics, Academic

Press, 1989. • Various, High Temperature Ordered Intermetallic Alloys, Proc. MRS. • J.R. Davis, Heat Resistant Materials, ASM International, 1997. • C.T. Sims, W.C. Hagel, The Superalloys, J.W. Wiley, 1972. • G.W. Meetham, The Development of Gas Turbine Materials, Applied Science

Publishers, 1981.

• D. Coutsouradis et al., High Temperature Alloys for Gas Turbines, Applied Science Publishers, 1978.

• J.K. Tien, S. Reichman, Refractory Alloying Elements in Superalloys, ASM, 1984. • A.K. Koul et al., Advances in High Temperature Materials and Protective Coatings,

National Research Council of Canada, 1994.

3

Tentative Outline and Schedule: Week 1: Introduction

Applications (Turbines, Boilers, Nuclear Reactors) Requirements

Historical Perspective and Current Materials

Week 1 & 2: Critical Principles of Materials Engineering Crystal Structures Defects and Diffusion Strengthening Mechanisms Thermodynamics and Phase Diagrams

Mechanical Behavior of Materials (Stress, Strain, Deformation, Fracture, Fatigue) Thermo-Mechanical Behavior of Materials (Creep, Stress Rupture)

Week 3&4: Design Criteria of Materials for High Temperature Applications

Strengthening Mechanisms Creep and Stress Rupture Fatigue and Thermal Fatigue Environmental Effects and Surface Stability

Week 5&6: Materials for High Temperature Applications

Stainless Steel and Austenitic Steel Physical Metallurgy of Ni-Base Alloys Physical Metallurgy of Co-Base Alloys Physical Metallurgy of Fe-Ni-Base Alloys Titanium Alloys

Week 6: Mid-Term Examination

Week 7&8: Processing of Superalloys Casting Wrought Processing Powder Metallurgy Joining Processing Developmental Techniques

Week 9&10 Environmental Degradation Oxidation Hot Corrosion Protective Coatings

Week 11: Emerging Materials Intermetallics

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Refractory Metals Composites Ceramics

Week 12: Student Presentation and Final Examination GRADING:

Grading in this course will be based on: Grading Scale: Attendance: ..................... 10% 92% - 100%: A Homework: ...................... 15% 90% - 91%: A- Quizzes: .......................... 15% 87% - 89%: B+ Exam I: ............................ 15% 82% - 86%: B Mid-term Exam: .............. 15% 80% - 81%: B- Seminar Presentation: .... 10% 77% - 79%: C+ Final Exam: ..................... 20% (comprehensive) 72% - 76%: C 70% - 71%: C- 60% - 69%: D 59% and below: F NOTE: An "I" grade will not be given simply to avoid a failing grade. If you feel you cannot pass the course, it is your responsibility to withdraw by the appropriate deadline.

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GENERAL POLICIES & NOTES: • Canvas is to be used for submission of assignments, unless mentioned by the instructor.

When technical issues occur, you can contact Online@UCF Support to troubleshoot problems with Webcourses@UCF, or Panopto. They can be reached at 407-823-0407 or [email protected]. Visit: http://onlinesupport.cdl.ucf.edu/

• As of Fall 2014, there is a need to document students’ academic activity at the beginning of each course. In order to document that you began this course, please complete the assignment on Web Courses (titled Introduction) by the end of the first week of classes, or as soon as possible after adding the course. Failure to do so will result in a delay in the disbursement of your financial aid.

• Assignments and Homework Assignments submitted past the due date will be subject to a 10% penalty, unless there is a legitimate reason supported by an official documentation (e.g., notes from doctors, professors). Documentation submitted for this reason is subject to an independent verification by the instructor. Documentation submitted for this reason may be rejected by the instructor depending upon the source and content.

• Academic Integrity Students should familiarize themselves with UCF’s Rules of Conduct. According to Section 1, “Academic Misconduct,” Academic integrity will be upheld throughout the duration of this course. Students are highly encouraged to go through UCF’s website on Plagiarism and Cheating for details: http://www.fctl.ucf.edu/teachingandlearningresources/classroommanagement/academicintegrity/cheating.php

• Make-up Assignments (incl. authorized University events or Co-curricular activities)

Make up exams will only be given for University excused absences and must supported by an official documentation. Documentation submitted for this reason is subject to an independent verification by the instructor. Documentation submitted for this reason may be rejected by the instructor depending upon the source and content. It is also strongly recommended that make up examination be given prior to the official examination dates. Students who represent the university in an authorized event or activity (for example, student-athletes) and who are unable to meet a course deadline due to a conflict with that event must provide the instructor with documentation in advance to arrange a make-up. No penalty will be applied. For more information, see the UCF policy.

• Course Accessibility

The University of Central Florida is committed to providing access and inclusion for all persons with disabilities. Students with disabilities who need disability-related access in this course should contact the professor as soon as possible. Students should also connect with Student Accessibility Services (SAS) <http://sas.sdes.ucf.edu/> (Ferrell Commons 185,


http://onlinesupport.cdl.ucf.edu/

http://osc.sdes.ucf.edu/process/roc

http://www.fctl.ucf.edu/teachingandlearningresources/classroommanagement/academicintegrity/cheating.php

http://www.fctl.ucf.edu/teachingandlearningresources/classroommanagement/academicintegrity/cheating.php

http://policies.ucf.edu/documents/4-401.1MakeupAssignmentsForAuthorizedUniversityEventsOrCocurricularActivities.pdf

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[email protected], phone 407-823-2371). Through Student Accessibility Services, a Course Accessibility Letter may be created and sent to professors, which informs faculty of potential access and accommodations that might be reasonable. Determining reasonable access and accommodations requires consideration of the course design, course learning objectives and the individual academic and course barriers experienced by the student.

• Responses to Academic Dishonesty, Plagiarism, or Cheating

Students should also familiarize themselves with the procedures for academic misconduct in UCF’s student handbook, The Golden Rule. UCF faculty members have a responsibility for students’ education and the value of a UCF degree, and so seek to prevent unethical behavior and when necessary respond to academic misconduct. Penalties can include a failing grade in an assignment or in the course, suspension or expulsion from the university, and/or a “Z Designation” on a student’s official transcript indicating academic dishonesty, where the final grade for this course will be preceded by the letter Z. For more information about the Z Designation, click here.

• Religious Observances

Students must notify their instructor in advance if they intend to miss class for a religious observance. For more information, see the UCF policy.

• Campus Safety Statement

Emergencies on campus are rare, but if one should arise during class, everyone needs to work together. Students should be aware of their surroundings and familiar with some basic safety and security concepts. ▪ In case of an emergency, dial 911 for assistance. ▪ Every UCF classroom contains an emergency procedure guide posted on a wall near

the door. Students should make a note of the guide’s physical location and review the online version at http://emergency.ucf.edu/emergency_guide.html.

▪ Students should know the evacuation routes from each of their classrooms and have a plan for finding safety in case of an emergency.

▪ If there is a medical emergency during class, students may need to access a first-aid kit or AED (Automated External Defibrillator). To learn where those are located, see http://www.ehs.ucf.edu/workplacesafety.html (click on link from menu on left).

▪ To stay informed about emergency situations, students can sign up to receive UCF text alerts by going to ucf.edu and logging in. Click on “Student Self Service” located on the left side of the screen in the toolbar, scroll down to the blue “Personal Information” heading on the Student Center screen, click on “UCF Alert”, fill out the information, including e-mail address, cell phone number, and cell phone provider, click “Apply” to save the changes, and then click “OK.”

▪ Students with special needs related to emergency situations should speak with their instructors outside of class.

▪ To learn about how to manage an active-shooter situation on campus or elsewhere, consider viewing this video.

http://goldenrule.sdes.ucf.edu/docs/goldenrule.pdf


http://regulations.ucf.edu/chapter5/documents/5.020ReligiousObservancesFINALOct17.pdf


http://www.ehs.ucf.edu/workplacesafety.html

http://my.ucf.edu/


council curriculum committee january 23, 2019 2:30 p.m ... · 1/23/2019 · graduate council...

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