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Old Dominion University

2015-2016 Catalog

Department of Modeling, Simulation and Visualization Engineering

http://www.odu.edu/msve

1300 Engineering and Computational Sciences Building
757-683-3720

Frederic (Rick) D. McKenzie, Chair
Yuzhong Shen, Graduate Program Director

Department Description:

The MSVE Department offers an undergraduate four-year degree program leading to the Bachelor of Science in Modeling and Simulation Engineering (BS-M&SE). The department also offers programs of graduate study leading to the degrees Master of Engineering, Master of Science, Doctor of Engineering, and Doctor of Philosophy with a major in Modeling and Simulation. The department's academic programs are coupled with a strong department research program conducted jointly with researchers from the Virginia Modeling, Analysis and Simulation Center (VMASC). Research activities range from investigation of fundamental modeling and simulation methods and technologies to applications of modeling and simulation in the domains of medicine and health care, transportation, education and gaming, science and engineering, homeland security and defense, and business enterprise decision support.

Special Facilities:

The MSVE Department is located on the first floor of the E. V. Williams Engineering and Computational Sciences Building on the Old Dominion University Norfolk Campus. In addition to the department and faculty offices, this facility also houses several instructional and research laboratories, a virtual reality theater, and a four-walled C.A.V.E. (Cave Automatic Virtual Environment).

Undergraduate Projects and Research Laboratory

The Undergraduate Projects and Research Laboratory, is mainly used for facilitating modeling and simulation projects-based instruction in both lower and upper division undergraduate levels. This also involves courses in the major with a significant laboratory component. The Laboratory can accommodate 24 students with laptop computers and provide 5 workstations for undergraduate labs and research. Each workstation contains a high performance computer and collaboration spaces. The lab also contains a Polycom Teleconference system to support distance learning. The lab is equipped with 3 digital projectors to support teaching.

Medical Simulations Laboratory

The Medical Simulations Laboratory is mainly used to support teaching and research activities related to medical simulations for planning, training, education, analysis and visualization. It contains 15 high performance PC workstations, 4 haptic devices, three 3D scanners, two 3D printers, 4 reach-in displays, 3 LCD TVs, 3 game consoles from Microsoft, Sony and Nintendo. The laboratory is also equipped with a large selection of software such as Autodesk Maya, Google SketchUp, Microsoft XNA Game Studio, Unity Game Engine, and ArcGIS.

Applied M&S Research Laboratory

The Applied M&S Research Laboratory is the third laboratory area. This graduate research laboratory contains PC workstations and spaces for 10 graduate students and also supports faculty/VMASC collaborative research activities. Several research topics are conducted in this laboratory including high performance computing, cyber security, simulation architectures, transportation systems, military M&S, digital manufacturing, and enterprise decision support. Visualization of these is also a significant part of these areas.

Collaborative Autonomous Systems Laboratory

The Collaborative Autonomous Systems Laboratory supports instructional and multidisciplinary research activities related to autonomous systems. This forth laboratory area is shared with the mechanical and aerospace department. MSVE maintains 4 PC workstations and 10 various types of robotic systems. The lab contains an area dedicated to cyber security research as related to collaborative autonomous systems.

The CAVE (CAVE Automated Virtual Environment)

The CAVE (Cave Automated Virtual Environment) Virtual Reality laboratory area contains several 3D visualization systems. The CAVE is a high-resolution projection-screen virtual reality system. The screens are arranged in a 10 foot cube with computer-generated images projected on three walls and a floor. The CAVE lab also contains a 3 meter Vision Dome projection system and an Immersa-Desk virtual reality display. Two 3D printers are also placed in the CAVE Lab.

Advanced Engineering Environments Laboratory

The Advanced Engineering Environments (AEE) laboratory serves as a focal point for the diverse research activities pertaining to Collaborative distributed Engineering Knowledge discovery and exploitation, intelligent synthesis, and advanced learning technologies, and their application to complex engineering systems. These activities include the synergistic coupling of modeling, visual simulations, intelligent agents, multimedia and synthetic environments, human-computer interactions, computational intelligence, computational, information and collaboration technologies in the multidisciplinary analysis, sensitivity studies, optimization, design and operation of complex engineering systems. The laboratory is located at the Old Dominion University Peninsula Higher Education Center in Hampton, Virginia and contains networked advanced 3D display and projection equipment (for collaborative distributed visualization research), virtual holography tablets, and 12 computing workstations and a variety of 3D display and projection equipment. The facility is supported by BCET in equipment and maintenance.

Associated Centers:

A significant resource to the department is the Virginia Modeling, Analysis and Simulation Center located adjacent to the University's Tri-Cities Higher Education Center in Suffolk, Virginia. VMASC occupies a two-story 60,000 square foot building designed to support state-of-the-art research in modeling, simulation and visualization. Some of the center's facilities are used in the department's educational programs; in addition, VMASC researchers teach courses and mentor students in the department's academic programs.

List of Degrees and Certificates

  • Master of Engineering - Modeling and Simulation
  • Master of Science, Engineering - Modeling and Simulation
  • Doctor of Engineering - Modeling and Simulation
  • Doctor of Philosophy, Engineering - Modeling and Simulation
  • Graduate Certificate in Modeling and Simulation Engineering
  • Advanced Engineering Certificate in Cyber Systems Security

Master of Engineering - Modeling and Simulation

The master's degree in modeling and simulation (M&S) emphasizes a strong, common subject core while providing the student with the flexibility to design a plan of study to meet each individual's study objectives and needs. The purpose of the program's subject core is to provide a common academic foundation for all simulation students. Thus, all students in this program will have grounding in the same methods, principles, and philosophy of simulation. This provides the mechanisms for the simulationist to work across disciplines and domains while maintaining a common frame of reference for communication, technical specialization, and advanced study and research. The Master of Engineering (ME) in Modeling and Simulation requires 30 hours of course credit. The ME program is focused on developing the practical skills and knowledge needed to solve problems requiring applications of modeling and simulation.

The program's subject core consists of:

  1. an overview of modeling and simulation;
  2. an in-depth exploration of specific simulation methodological approaches;
  3. simulation system modeling principles and techniques;
  4. an introduction to computer visualization and visual simulation; and,
  5. principles of stochastic analysis.

Most courses are offered in distance learning format. They are delivered to Old Dominion University's higher education centers and are available synchronously using video teleconferencing software. Additionally, the MSVE department is offering a Master of Engineering Online program.

Master of Engineering Admission Requirements

The Master’s Degree in Modeling and Simulation is designed for students having bachelor’s degrees in Engineering, Science or Mathematics, although students from other educational backgrounds may apply with appropriate leveling courses. Prerequisites for admission include: mathematics – two courses in differential and integral calculus and one course in calculus-based probability and statistics; and computer science – algorithmic problem solving using a high-level object-oriented programming language such as C++.

A minimum GPA of 2.80 overall and a minimum GPA of 3.0 in the undergraduate major are required. Students with notable deficiencies may be considered for provisional admission and will be required to complete prerequisite course requirements in addition to the graduate degree requirements. Job experience and training may be considered in evaluating prerequisite requirements.

Applicants should plan to submit a completed application form, transcripts from all colleges and universities attended, GRE scores (verbal, quantitative, and analytical writing - optional for ME appplicants with an undergraduate GPA of 2.80 or higher), a resume and personal statement of objectives, two letters of recommendation from former university instructors, and TOEFL scores if an international applicant.

Potential prerequisite courses for the master’s degrees in modeling and simulation include the following:

  1. Introductory differential and integral calculus equivalent to MATH 211 (Calculus I) and MATH 212 (Calculus II).
  2. Calculus-based probability and statistics; this material is available for graduate credit in ENMA 520, PSYC 727, or PSYC 728.
  3. Computer science fundamentals including an object-oriented programming language such as C++, algorithmic problem solving, and data structures.

Master of Engineering Degree Requirements

The Master of Engineering program requires completion of 10 three-credit courses; four core courses and six elective courses are required to complete the degree program.

MSIM 741Principles of Visualization3
MSIM 551Analysis for Modeling and Simulation3
or MSIM 751 Advanced Analysis for Modeling and Simulation
Advanced Modeling Course (see list below)3
Advanced Simulation Course (see list below)3

Advanced Modeling Course Examples (3 credits)

Machine Learning I
System Architecture and Modeling
Methods of Rational Decision Making
Simulation Formalisms
Modeling Global Events
Transportation Network Flow Models
Other courses with graduate program director's approval.

Advanced Simulation Course Examples (3 credits)

Finite Element Analysis
Cluster Parallel Computing
Principles of Combat Modeling and Simulation
Synthetic Environments
Simulation Modeling in Transportation Networks
Other courses with graduate program director's approval.

Students must take six electives, 3 credit hours each, in addition to the core courses.  Several electives are available covering topics such as system dynamics, social networks, graduate level statistics, and combat modeling.  Other courses must be approved by the graduate program director.

Certain students will need to take pre-requisite leveling courses that will count towards the six elective course requirement.  These courses are:  MSIM 510 Model Engineering; MSIM 541 Computer Graphics and Visualization; MSIM 602 Simulation Fundamentals; and, MSIM 603 Simulation Design.

For graduation, students must complete a comprehensive examination and the Responsible Conduct of Research Training for Engineers training online.

Master of Engineering Online Program

The MSVE department also offers an ME online degree in Modeling and Simulation via the Blackboard Academic Suite and WebEx that provides online lectures, homework submissions, examinations, discussion boards, wikis, video/audio collaboration sessions and grading. Students having access to reliable high speed internet service can connect and participate in engaging discussion and distributed asynchronous learning with the instructor and other students. All course materials are distributed and collected electronically.  Students located in the Hampton Roads region may utilize live courses to fulfill the elective course requirement with approval from the MSVE graduate program director.

Master of Science, Engineering - Modeling and Simulation

The master's degree in modeling and simulation (M&S) emphasizes a strong, common subject core while providing the student with the flexibility to design a plan of study to meet each individual's study objectives and needs. The purpose of the program's subject core is to provide a common academic foundation for all simulation students. Thus, all students in this program will have grounding in the same methods, principles, and philosophy of simulation. This provides the mechanisms for the simulationist to work across disciplines and domains while maintaining a common frame of reference for communication, technical specialization, and advanced study and research. The Master of Science (MS) in Modeling and Simulation requires six hours of thesis credit and 24 hours of course credit. The MS program is directed primarily at full-time students who are preparing for a career in advanced M&S research and/or academic positions.

The program's subject core consists of:

  1. an overview of modeling and simulation;
  2. an in-depth exploration of specific simulation methodological approaches;
  3. simulation system modeling principles and techniques;
  4. an introduction to computer visualization and visual simulation; and,
  5. principles of stochastic analysis.

Most courses are offered in distance learning format. They are delivered to Old Dominion University's higher education centers and are available synchronously using video teleconferencing software.

Master of Science Admission Requirements

The Master’s Degree in Modeling and Simulation is designed for students having bachelor’s degrees in Engineering, Science or Mathematics, although students from other educational backgrounds may apply with appropriate leveling courses. Prerequisites for admission include: mathematics – two courses in differential and integral calculus and one course in calculus-based probability and statistics; and computer science – algorithmic problem solving using a high-level object-oriented programming language such as C++.

A minimum GPA of 2.80 overall and a minimum GPA of 3.0 in the undergraduate major are required. Students with notable deficiencies may be considered for provisional admission and will be required to complete prerequisite course requirements in addition to the graduate degree requirements. Job experience and training may be considered in evaluating prerequisite requirements.

Applicants should plan to submit a completed application form, transcripts from all colleges and universities attended, GRE scores (verbal, quantitative, and analytical writing - required of all MS applicants), a resume and personal statement of objectives, two letters of recommendation from former university instructors, and TOEFL scores if an international applicant.

Potential prerequisite courses for the master’s degrees in modeling and simulation include the following:

  1. Introductory differential and integral calculus equivalent to MATH 211 (Calculus I) and MATH 212 (Calculus II).
  2. Calculus-based probability and statistics; this material is available for graduate credit in ENMA 520, PSYC 727, or PSYC 728.
  3. Computer science fundamentals including an object-oriented programming language such as C++, algorithmic problem solving, and data structures.

Master of Science Degree Requirements

The Master of Science program requires 12 hours of course credit in modeling and simulation foundation courses. These foundation courses include:

MSIM 741Principles of Visualization3
MSIM 551Analysis for Modeling and Simulation3
or MSIM 751 Advanced Analysis for Modeling and Simulation
Advanced Modeling Course (see list below)3
Advanced Simulation Course (see list below)3

Advanced Modeling Course Examples (3 credits)

Machine Learning I
System Architecture and Modeling
Methods of Rational Decision Making
Simulation Formalisms
Modeling Global Events
Transportation Network Flow Models
Other courses with graduate program director's approval.

Advanced Simulation Course Examples (3 credits)

Finite Element Analysis
Cluster Parallel Computing
Principles of Combat Modeling and Simulation
Synthetic Environments
Simulation Modeling in Transportation Networks
Other courses with graduate program director's approval.

The remaining course credits (12 credits) are elective course credits.  These courses are selected to achieve one or more program objectives or themes and must be approved by the student's advisor and/or graduate program director.  Elective courses outside the MSVE Department must be approved by the graduate program director.  The program concludes with 6 credit hours of thesis credit (MSIM 699) and a thesis defense.

Certain students will need to take pre-requisite leveling courses that will count towards the 12 credit hour elective course requirement.  These courses are:  MSIM 510 Model Engineering; MSIM 541 Computer Graphics and Visualization; MSIM 602 Simulation Fundamentals; and, MSIM 603 Simulation Design.

For graduation, students must successfully defend their thesis and complete the Responsible Conduct of Research for Engineers training online.

Doctor of Engineering - Modeling and Simulation

The D. Eng. in Modeling and Simulation program focuses on developing the advanced skills and knowledge to enable the graduate to conduct and lead advanced technical M&S projects in an engineering environment. It affords engineering practitioners the opportunity to achieve advanced graduate education beyond the master’s degree.

For complete information on admission requirements and core degree requirements, please refer to the Doctor of Engineering program information at:  /graduate/frankbattencollegeofengineeringandtechnology/#doctorofengineeringprogram

The program of study for the D.Eng. in M&S program is developed with the approval of the graduate program director and the student’s advisor. The program shall include a minimum of 18 credits of professional course work and 18 credits of technical core course work beyond the master’s degree distributed as follows:

Technical Core Courses18
Advanced Simulation Course from the list below
Simulation Formalisms
Synthetic Environments
Advanced Analysis for Modeling and Simulation
Two approved technical elective courses - 6 credits

Advanced Simulation Course Examples (3 credits)

Finite Element Analysis
Cluster Parallel Computing
Principles of Combat Modeling and Simulation
Simulation Modeling in Transportation Networks
Other courses with graduate program director's approval.

No more than three credits from course work satisfying foundation knowledge requirements may be included in the program of study for technical elective credit. At least three-fifths of the non-project coursework must be at the 800-level.

Certain students entering the program will be required to complete additional pre-requisite leveling courses.  These courses are:  MSIM 510 Model Engineering; MSIM 541 Computer Graphics and Visualization; MSIM 602 Simulation Fundamentals; and, MSIM 603 Simulation Design.

For graduation, students must complete the requirements for their final project and the Responsible Conduct of Research for Engineers training online.

Doctor of Philosophy, Engineering - Modeling and Simulation

The Ph.D. in Modeling and Simulation program focuses on developing the necessary skills and knowledge to enable the graduate to conduct and evaluate independent, original research in an area of modeling and simulation. The goal of the program is to prepare students for careers in teaching and research at academic institutions, as well as the conduct or leadership of research and development in public and private organizations.

Doctor of Philosophy Admission Requirements

Admission to the Ph.D. in M&S program is made in accordance with Old Dominion University and Batten College of Engineering and Technology requirements for doctoral programs as specified in this Catalog. Specific requirements for the modeling and simulation degree include the following:

  1. Completion of a master’s degree in an appropriate and closely related field is expected. However, students who have completed 24 credits of graduate courses in an appropriate field from an accredited institution may apply.
  2. A minimum GPA in graduate course work of 3.50 (out of 4.0) is required of most students. A student with a GPA greater than 3.25 and with evidence of a high level of professional capability in the field of modeling and simulation may be eligible for admission to the program upon submission of a petition to the graduate program director.
  3. Recent scores (typically, not more than five years old) on the Graduate Record Examination’s (GRE) verbal, quantitative, and analytical writing sections must be submitted by all applicants.
  4. Three letters of recommendation (typically at least two of which are from faculty in the highest degree program completed when the application is within five years of graduation from that degree program) are required.
  5. The applicant must submit a statement of purpose, goals, and objectives related to the program and a resume.

Applicants are expected to have the following foundation knowledge:

  1. Mathematics fundamentals including differential and integral calculus, ordinary differential equations, calculus-based probability and statistics, and linear algebra.
  2. Computer science fundamentals including an object-oriented programming language such as C++, algorithmic problem solving, and data structures.
  3. Knowledge of the content of the foundation courses required in the Modeling and Simulation Master’s Program.

Doctor of Philosophy Degree Requirements

The Ph.D. in modeling and simulation is offered in accordance with the general requirements for doctoral degrees as specified in the Requirements for Graduate Degrees Section of this Catalog. Specific program of study requirements for the concentration in modeling and simulation include the following:

  1. Completion of a minimum of 24 credits of course work beyond the master’s degree; and a minimum of 24 credits of dissertation research.
  2. Successful completion of a written diagnostic examination before completion of nine credits of advanced course work.
  3. Successful completion of a written and oral qualifying (candidacy) examination near the completion of the course work.
  4. Successful presentation of a dissertation research proposal at the beginning of the dissertation research.
  5. The successful completion and public defense of a dissertation representing independent, original research worthy of publication in a peer-reviewed scholarly journal.

The program of study for the Ph.D. in M&S program is developed with the approval of the graduate program director and the student’s advisor. The program shall include a minimum of 24 credit hours of course work beyond the master’s degree distributed as follows.

Common Core

Advanced Simulation Course (see the list below)3
MSIM 830Simulation Formalisms3
MSIM 842Synthetic Environments3
MSIM 851Advanced Analysis for Modeling and Simulation3
Total Hours12

Advanced Simulation Course Examples (3 credits)

Finite Element Analysis
Cluster Parallel Computing
Principles of Combat Modeling and Simulation
Simulation Modeling in Transportation Networks
Other courses with graduate program director's approval.

Electives - Minimum of 12 credits of elective courses that provide a basis for dissertation research. No more than six credits from course work satisfying foundation knowledge requirements may be included in the program of study for elective credit. At least three-fifths (15 credits) of non-dissertation course work must be at the 800-level.  Eleective courses outside the MSVE Department must be approved by the graduate program director.

Certain students entering the program will be required to complete additional pre-requisite leveling courses.  These courses are:  MSIM 510 Model Engineering; MSIM 541 Computer Graphics and Visualization; MSIM 602 Simulation Fundamentals; and, MSIM 603 Simulation Design.

For graduation, students must successfully defend their dissertation and complete the Responsible Conduct of Research for Engineers training online.

Graduate Certificate in Modeling and Simulation Engineering

The Graduate Certificate in Modeling and Simulation Engineering is designed for those who meet the admission requirements of the modeling and simulation master's program and wish to broaden their knowledge of modeling and simulation related principles and practices without pursuing a graduate degree. This is a 12 credit hour non-degree program offered by the Department of Modeling Simulation and Visualization Engineering. The certificate program is open to both degree-seeking and non-degree-seeking graduate students. Certain courses taken for the certificate program may later be applied to the master’s degree in modeling and simulation.  For complete information on the admission and certificate requirements, please refer to the Batten College of Engineering and Technology's section on graduate certificate programs at:  /graduate/frankbattencollegeofengineeringandtechnology/#interdisciplinarygraduatecertificateprograms
 

Advanced Engineering Certificate in Cyber Systems Security


The certificate program aims to provide a thorough understanding the cyber security threats faced by the stand-alone computer systems, networked systems, IT infrastructure, and cyber physical systems having embedded computer systems operated by individuals, small businesses and large enterprises along with the knowledge required to defend against these threats. The course will enable participants to learn state of the art techniques necessary for analyzing cyber security risks, preventing, detecting and recovering from cyber attacks through class room instructions and hands-on lab work. The program uniquely accommodates students from engineering, math and sciences as well as practicing engineers and managers. The course will make use of the ODUs multidisciplinary strengths in the fields of Cyber systems, Computer Engineering, Software Engineering and Modeling and Simulation. This program is designed both as a complement for students working on graduate degrees and for those personnel working on information and cyber systems used in industry, small businesses, healthcare, government, military and home land security. It is anticipated that students will complete the program in 2 semesters (full time enrollment) or 2 years (part-time enrollment or working to complement an existing graduate program). For complete information on the admission and certificate requirements, please refer to the Batten College of Engineering and Technology's section on graduate certificate programs at:  /graduate/frankbattencollegeofengineeringandtechnology/#interdisciplinarygraduatecertificateprograms
 

MODELING AND SIMULATION Courses

MSIM 506. Introduction to Distributed Simulation. 3 Credits.

An introduction to distributed simulation. Topics include motivation for using distributed simulation, distributed simulation architectures, time management issues, and distributed simulation approaches. Current standards for distributed simulation are presented.

MSIM 508. Introduction to Game Development. 3 Credits.

Requires an understanding of physics and either CS 361 or MSIM 331. An introductory course focused on game development theory and modern practices with emphasis on educational game development. Topics include game architecture, computer graphics theory, user interaction, audio, high level shading language, animation, physics, and artificial intelligence. The developed games can run on a variety of computer, mobile, and gaming platforms.

MSIM 510. Model Engineering. 3 Credits.

The goal of this course is to develop understanding of the various modeling paradigms appropriate for capturing system behavior and conducting digital computer simulation of many types of systems. The techniques and concepts discussed typically include UML, concept graphs, Bayesian nets, Markov models, Petri nets, system dynamics, Bond graphs, etc. Students will report on a particular technique and team to implement a chosen system model. (cross-listed with ECE 510).

MSIM 511. Networked System Security. 3 Credits.

Course presents an overview of theory, techniques and protocols that are used to ensure that networks are able to defend themselves and the end-systems that use networks for data and information communication. Course will also discuss industry-standard network security protocols at application, socket, transport, network, VPN, and link layers, popular network security tools, security, performance modeling and quantification and network penetration testing. Discussion will be based on development of system level models and simulations of networked systems. (Cross-listed with ECE 511 and ENMA 511).

MSIM 516. Cyber Defense Fundamentals. 3 Credits.

The objective of this course is to give an introduction of cyber hacking techniques, and defense mechanisms to detect and thwart cybercrime. Cyber attacks aim at compromising cyber systems to disclose information, alter data or operation, cause denial of service, etc. The course first reviews the attacks to wireless networks, such as WiFi and MANET, and the defense strategies and technologies developing system level models. Next, it reviews the attacks to general wired networks and information systems, and introduces the corresponding defense mechanisms. At last it discusses cyber defense security policies and architectures. (Cross-listed with ECE 516 and ENMA 516).

MSIM 517. Secure and Trusted Operating Systems. 3 Credits.

Course will review typical operating systems developing system models and identifying potential vulnerabilities. Course will discuss policies and their implementation required to fix such vulnerabilities to arrive at a secure and Trusted Computing Base. Course examines the security architecture Security Enhanced Linux (SELinux) Windows and Android OS. (Cross-listed with ECE 517 and ENMA 517).

MSIM 519. Cyber Physical Systems Security. 3 Credits.

Cyber Physical Systems (CPSs) integrate computing, networking, and physical processes. CPSs are known for their ability to monitor the physical environment; use the monitored data in detecting the state of the physical environment; control the physical environment; and use cyber communications to perform its monitoring, detection, and control operations . One of the biggest challenges to these systems is the security of its cyber space. This course will cover topics in CPS applications, design issues, and security based on development of a system level model. (Cross-listed with ECE 519 and ENMA 519).

MSIM 541. Computer Graphics and Visualization. 3 Credits.

The course provides a practical treatment of computer graphics and visualization with emphasis on modeling and simulation applications. It covers computer graphics fundamentals, visualization principles, and software architecture for visualization in modeling and simulation. Pre- or corequisites: CS 250 and MSIM 603.

MSIM 551. Analysis for Modeling and Simulation. 3 Credits.

An introduction to analysis techniques appropriate to the conduct of modeling and simulation studies. Topics include input modeling, random number generation, output analysis, variance reduction techniques, and experimental design. In addition, techniques for verification & validation are introduced. Course concepts are applied to real systems and data.

MSIM 562. Introduction to Medical Image Analysis. 3 Credits.

Introduction to basic concepts in medical image analysis. Medical image registration, segmentation, feature extraction, and classification are discussed. Basic psychophysics, fundamental ROC analysis and FROC methodologies are covered. Cross-listed with ECE 462/562.

MSIM 563. Design and Modeling of Autonomous Robotic Systems. 3 Credits.

Course focuses on autonomous robotics systems with emphasis on using modeling and simulation (M&S) for system level design and testing. Fundamental concepts associated with autonomous robotic systems are discussed. Course topics include: robotic control, architectures, and sensors as well as more advanced concepts such as error propagation, localization, mapping and autonomy. Design strategies that leverage M&S to accelerate the development and testing of sophisticated autonomous robotic algorithms for individual or teams of robots are covered. Pre- or corequisite: CS 150.

MSIM 570. Foundations of Cyber Security. 3 Credits.

Course provides an overview of theory, tools and practice of cyber security and information assurance through prevention, detection and modeling of cyber attacks and recovery from such attacks. Techniques for security modeling, attack modeling, risk analysis and cost-benefit analysis are described to manage the security of cyber systems. Fundamental principles of cyber security and their applications for protecting software and information assets of individual computers and large networked systems are explored. Anatomy of some sample attacks designed to compromise confidentiality, integrity and availability of cyber systems are discussed. Pre- or corequisites: MSIM 510 or permission of the instructor.

MSIM 595. Topics in Modeling and Simulation Engineering. 3 Credits.

Special topics of interest with emphasis placed on recent developments in modeling and simulation engineering.

MSIM 596. Topics in Modeling and Simulation Engineering. 1-3 Credits.

Special topics of interest with emphasis placed on the recent developments in modeling and simulation engineering. Prerequisites: permission of the instructor.

MSIM 597. Independent Study in Modeling and Simulation Engineering. 3 Credits.

Individual analytical, computational, and/or experimental study in an area selected by the student. Supervised and approved by the advisor.

MSIM 601. Introduction to Modeling and Simulation. 3 Credits.

Modeling and simulation (M&S) discipline surveyed at an overview level of detail. Basic terminology, modeling methods, and simulation paradigms are introduced. Applications of M&S in various disciplines are discussed. The course provides a general conceptual framework for those interested in using M&S and for further studies in M&S. Not open to MSVE degree seeking students. Prerequisites: graduate standing; undergraduate exposure to calculus and probability & statistics.

MSIM 602. Simulation Fundamentals. 3 Credits.

An introduction to the modeling and simulation discipline. Introduction to discrete event simulation (DES) including simulation methodology, input data modeling, output data analysis, and an overview of DES tools. Introduction to continuous simulation (CS) including simulation methodology, differential equation models, numerical solution techniques, and an overview of CS tools. Prerequisites: graduate standing; undergraduate preparation in calculus and probability & statistics; and computer literacy.

MSIM 603. Simulation Design. 3 Credits.

Course develops the computer software skills necessary for the design and development of simulation software. Topics covered include software architectures, software engineering, software design, object-oriented programming, abstract data types and classes, data structures, algorithms, and testing and debugging techniques. Software design and development of simulation systems (discrete-event, continuous, and Monte Carlo) are emphasized. Prerequisite: MSIM 602 and an introductory computer programming course.

MSIM 607. Machine Learning I. 3 Credits.

Course provides a practical treatment of design, analysis, implementation and applications of algorithms. Topics include multiple learning models: linear models, neural networks, support vector machines, instance-based learning, Bayesian learning, genetic algorithms, ensemble learning, reinforcement learning, unsupervised learning, etc. (Cross listed with ECE 607).

MSIM 660. System Architecture and Modeling. 3 Credits.

Students will learn the essential aspects of the system architecture paradigm through environment and analysis of multiple architecture framework and enterprise engineering, such as IDEFO, TOGAF, DODAF and OPM. Emphasis on system modeling and enterprise engineering. (Cross listed with ENMA 660).

MSIM 667. Cooperative Education. 1-3 Credits.

Available for pass/fail grading only. Student participation for credit based on academic relevance of the work experience, criteria, and evaluation procedures as formally determined by the program and the Cooperative Education/Career Management program prior to the semester in which the work experience is to take place.

MSIM 669. Practicum. 1-3 Credits.

Academic requirements will be established by the graduate program director and will vary with the amount of credit desired. Allows students an opportunity to gain short-duration career related experience. Student is usually employed–this is an additional project beyond the duties of the student’s employment.

MSIM 671. Cyber Systems Engineering. 3 Credits.

Course provides an overview of functioning of cyber systems including how a computer interacts with the outside world. The composition of critical infrastructure and functioning of different engineered systems that form critical infrastructure are discussed. Mutual dependence and interactions between cyber systems and other engineered systems and the resulting security risks are also explored. (Cross-listed with ENMA 671).

MSIM 672. Threat Modeling and Risk Analysis. 3 Credits.

Course discusses how to develop cyber threat models using attack graphs/trees, STRIDE, Universal Modeling Language (UML), attack graphs/trees and common of risk analysis tools. Course also discusses the need for quantitative security analysis and formal validation of security models and basic principles of formal model validation. (Cross-listed with ENMA 672).

MSIM 695. Topics in Modeling and Simulation. 3 Credits.

Special topics of interest with emphasis placed on recent developments in modeling and simulation.

MSIM 697. Independent Study in Modeling and Simulation. 3 Credits.

Individual study selected by the student. Supervised and approved by a faculty member with the approval of the graduate program director. Prerequisites: permission of instructor or graduate program director.

MSIM 699. Thesis. 1-6 Credits.

Research leading to the Master of Science thesis. Prerequisites: permission of instructor and graduate program director.

MSIM 702. Methods of Rational Decision Making. 3 Credits.

The course covers advanced methods in Operation Research and Optimization. Focus will be on developing models and their application in different domains including manufacturing and services. (Cross listed with ENMA 702/ENMA 802.).

MSIM 703. Optimization Methods. 3 Credits.

Covers advanced methods in Operations Research and Optimization. Focus will be on developing models and their applications in different domains including manufacturing and service. Modern optimization tools will be used to implement models for case studies, projects and research papers. The knowledge of programming and spreadsheets is expected. Contact instructor for more details. (Cross-listed with ENMA 703).

MSIM 711. Finite Element Analysis. 3 Credits.

Prerequisites: permission of the instructor. The purpose of the course is to provide an understanding of the finite element method (FEM) as derived from an integral formulation perspective. The course will demonstrate the solutions of (1-D and 2-D) continuum mechanics problems such as solid mechanics, fluid mechanics and heat transfer.

MSIM 715. High Performance Computing and Simulations. 3 Credits.

Introduction to modern high performance computing platforms including top supercomputers and accelerators. Discussion of parallel architectures, performance, programming models, and software development issues. Case studies of scientific and engineering simulations will be explored. Students will have an opportunity to work on parallelization of problems from their research areas. Project presentations are required.

MSIM 722. Cluster Parallel Computing. 3 Credits.

This course provides detailed numerical step-by-step procedures to exploit parallel and sparse computation under MPI (Message Passing Interface) computer environments. Large-scale engineering/science applications are emphasized. Simultaneous linear equations are discussed.

MSIM 725. Principles of Combat Modeling and Simulation. 3 Credits.

Principles of combat modeling and simulation. Introduction including history, basic definitions, and best practice. Algorithms for modeling movement, sensing effects and behavior. Overview of modern combat models. Interoperability and integration into operational environments. Prerequisites: MSIM 603.

MSIM 730. Simulation Formalisms. 3 Credits.

The focus of the course is on identification and investigation of mathematical and logical structures that form the foundation for computational simulation. Topics include: foundations of simulation theory in logic, discrete mathematics, and computability; simulation formalisms, including DEVS; interoperability protocols; and computational complexity.

MSIM 741. Principles of Visualization. 3 Credits.

Well-designed graphical media capitalizes on human facilities for processing visual information and thereby improves comprehension, memory, inference, and decision making. This course teaches techniques and algorithms for creating effective visualizations based on principles and techniques from graphic design, visual art, perceptual psychology and cognitive science. Both users and developers of visualization tools and systems will benefit from this course.

MSIM 742. Synthetic Environments. 3 Credits.

The course covers the theory and techniques for building effective and efficient synthetic environments for modeling and simulation applications. Topics include physics, artificial intelligence, virtual reality, and advanced modeling and rendering. The emphasis is on producing visually realistic synthetic environments based on effective approximations of physics and other related principles. Prerequisites: MSIM 541 or equivalent.

MSIM 751. Advanced Analysis for Modeling and Simulation. 3 Credits.

An introduction to stochastic dependence and Bayesian analysis techniques for conducting modeling and simulation studies. Topics include: measures of dependence, common multivariate distributions, sampling from multivariate distributions, elementary time series models and Bayesian statistics. Prerequisites: MSIM 451 or MSIM 551.

MSIM 762. Applied Medical Image Analysis. 3 Credits.

Course explores hands-on exposure to state-of-the-art algorithms in medical image analysis, which builds on open-source software (Insight Segmentation and Registration Toolkit - ITK), as well as the principles of medical image acquisition in the modalities of clinical interest. Medical imaging modalities - X-rays, CT, and MRI/ITK image pipeline; image enhancement, feature detection; segmentation - basic techniques, feature-based classification and clustering, graph cuts, active contour and surface models; surface and volume meshing; registration - transformations, similarity criteria; shape and appearance models are all explored and discussed in this course. Prerequisites: Knowledge of C++ and object-oriented programming.

MSIM 772. Modeling Global Events. 3 Credits.

Modeling Global Events introduces modeling and simulation as a tool for expanding our understanding of events that have shaped the global environment of the 21st century. Students will review real-world case studies and then analyze these case studies via system dynamics, agent-based, social network, and game theory modeling paradigms. This course is designed to develop empirical research skills, conceptual modeling expertise, and model construction. Students will understand how to analyze, verify, and validate a model.

MSIM 773. Networked System Security. 3 Credits.

Course presents an overview of theory, techniques and protocols that are used to ensure that networks are able to defend themselves and the end-systems that use networks for data and information communication. Modeling of threats to networked systems, attack modeling with attack trees/graphs, cyber physical systems survivability to attacks, and behavior modeling of malware are explored. Network simulation/emulation using tools such as Scalable Simulation Framework (SSFNet), OPNET, or NS3 are examined. Application of industry-standard security protocols, such as, Secure Socket Layer (SSL), Transport Layer Security (TLS), IP-Security (IPSec), Public Key Infrastructure (PKI), WEP, WPA, etc. for engineering the security of networked systems will also be discussed.

MSIM 774. Transportation Network Flow Models. 3 Credits.

This course provides a rigorous introduction to transportation network modeling, with special emphasis on network equilibrium problems. Topics include: elementary graph theory, shortest path problem nonlinear optimization, optimization of univariate functions, deterministic and stochastic user equilibrium. (Cross-listed with CEE 774 and MSIM 774).

MSIM 775. Computational Methods for Transportation Systems. 3 Credits.

Fundamental models and algorithms in optimization, stochastic modeling and parallel computing will be discussed and illustrated with transportation applications. (Cross-listed with CEE 775 and CEE 875).

MSIM 776. Simulation Modeling in Transportation Networks. 3 Credits.

Principles of simulation modeling, microscopic, mesoscopic, and macroscopic traffic simulation models. Course explores diver behavior in networks, calibration and validation of traffic simulation models, and use of traffic simulation software.

MSIM 795. Topics in Modeling and Simulation. 3 Credits.

Special topics of interest with emphasis placed on recent developments in modeling and simulation.

MSIM 797. Independent Study in Modeling and Simulation. 3 Credits.

Individual study selected by the student. Supervised and approved by a faculty member with the approval of the graduate program director. Prerequisites: permission of instructor or graduate program director.

MSIM 802. Methods of Rational Decision Making. 3 Credits.

The course covers advanced methods in Operation Research and Optimization. Focus will be on developing models and their application in different domains including manufacturing and services. (Cross listed with ENMA 702/ENMA 802.).

MSIM 803. Optimization Methods. 3 Credits.

Covers advanced methods in Operations Research and Optimization. Focus will be on developing models and their applications in different domains including manufacturing and service. Modern optimization tools will be used to implement models for case studies, projects and research papers. The knowledge of programming and spreadsheets is expected. Contact instructor for more details. (Cross-listed with ENMA 803).

MSIM 811. Finite Element Analysis. 3 Credits.

Prerequisites: permission of the instructor. The purpose of the course is to provide an understanding of the finite element method (FEM) as derived from an integral formulation perspective. The course will demonstrate the solutions of (1-D and 2-D) continuum mechanics problems such as solid mechanics, fluid mechanics and heat transfer.

MSIM 815. High Performance Computing and Simulations. 3 Credits.

Introduction to modern high performance computing platforms including top supercomputers and accelerators. Discussion of parallel architectures, performance, programming models, and software development issues. Case studies of scientific and engineering simulations will be explored. Students will have an opportunity to work on parallelization of problems from their research areas. Project presentations are required.

MSIM 822. Cluster Parallel Computing. 3 Credits.

This course provides detailed numerical step-by-step procedures to exploit parallel and sparse computation under MPI (Message Passing Interface) computer environments. Large-scale engineering/science applications are emphasized. Simultaneous linear equations are discussed.

MSIM 825. Principles of Combat Modeling and Simulation. 3 Credits.

Principles of combat modeling and simulation. Introduction including history, basic definitions, and best practice. Algorithms for modeling movement, sensing effects and behavior. Overview of modern combat models. Interoperability and integration into operational environments. Prerequisites: MSIM 603.

MSIM 830. Simulation Formalisms. 3 Credits.

The focus of the course is on identification and investigation of mathematical and logical structures that form the foundation for computational simulation. Topics include: foundations of simulation theory in logic, discrete mathematics, and computability; simulation formalisms, including DEVS; interoperability protocols; and computational complexity.

MSIM 841. Principles of Visualization. 3 Credits.

Well-designed graphical media capitalizes on human facilities for processing visual information and thereby improves comprehension, memory, inference, and decision making. This course teaches techniques and algorithms for creating effective visualizations based on principles and techniques from graphic design, visual art, perceptual psychology and cognitive science. Both users and developers of visualization tools and systems will benefit from this course.

MSIM 842. Synthetic Environments. 3 Credits.

The course covers the theory and techniques for building effective and efficient synthetic environments for modeling and simulation applications. Topics include physics, artificial intelligence, virtual reality, and advanced modeling and rendering. The emphasis is on producing visually realistic synthetic environments based on effective approximations of physics and other related principles. Prerequisites: MSIM 541 or equivalent.

MSIM 851. Advanced Analysis for Modeling and Simulation. 3 Credits.

An introduction to stochastic dependence and Bayesian analysis techniques for conducting modeling and simulation studies. Topics include: measures of dependence, common multivariate distributions, sampling from multivariate distributions, elementary time series models and Bayesian statistics. Prerequisites: MSIM 451 or MSIM 551.

MSIM 862. Applied Medical Image Analysis. 3 Credits.

Course explores hands-on exposure to state-of-the-art algorithms in medical image analysis, which builds on open-source software (Insight Segmentation and Registration Toolkit - ITK), as well as the principles of medical image acquisition in the modalities of clinical interest. Medical imaging modalities - X-rays, CT, and MRI/ITK image pipeline; image enhancement, feature detection; segmentation - basic techniques, feature-based classification and clustering, graph cuts, active contour and surface models; surface and volume meshing; registration - transformations, similarity criteria; shape and appearance models are all explored and discussed in this course.

MSIM 872. Modeling Global Events. 3 Credits.

Modeling Global Events introduces modeling and simulation as a tool for expanding our understanding of events that have shaped the global environment of the 21st century. Students will review real-world case studies and then analyze these case studies via system dynamics, agent-based, social network, and game theory modeling paradigms. This course is designed to develop empirical research skills, conceptual modeling expertise, and model construction. Students will understand how to analyze, verify, and validate a model.

MSIM 873. Networked System Security. 3 Credits.

Course presents an overview of theory, techniques and protocols that are used to ensure that networks are able to defend themselves and the end-systems that use networks for data and information communication. Modeling of threats to networked systems, attack modeling with attack trees/graphs, cyber physical systems survivability to attacks, and behavior modeling of malware are explored. Network simulation/emulation using tools such as Scalable Simulation Framework (SSFNet), OPNET, or NS3 are examined. Application of industry-standard security protocols, such as, Secure Socket Layer (SSL), Transport Layer Security (TLS), IP-Security (IPSec), Public Key Infrastructure (PKI), WEP, WPA, etc. for engineering the security of networked systems will also be discussed.

MSIM 874. Transportation Network Flow Models. 3 Credits.

This course provides a rigorous introduction to transportation network modeling, with special emphasis on network equilibrium problems. Topics include: elementary graph theory, shortest path problem nonlinear optimization, optimization of univariate functions, deterministic and stochastic user equilibrium. (Cross-listed with CEE 774 and CEE 874).

MSIM 875. Computational Methods for Transportation Systems. 3 Credits.

Fundamental models and algorithms in optimization, stochastic modeling and parallel computing will be discussed and illustrated with transportation applications. (Cross-listed with CEE 775 and CEE 875).

MSIM 876. Simulation Modeling in Transportation Networks. 3 Credits.

Principles of simulation modeling, microscopic, mesoscopic, and macroscopic traffic simulation models. Course explores driver behavior in networks, calibration and validation of traffic simulation models, and use of traffic simulation software.

MSIM 892. Doctor of Engineering Project. 1-9 Credits.

Directed individual study applying advanced level technical knowledge to identify, formulate and solve a complex, novel problem in Modeling and Simulation.

MSIM 895. Topics in Modeling and Simulation. 3 Credits.

Special topics of interest with emphasis placed on recent developments in modeling and simulation.

MSIM 897. Independent Study in Modeling and Simulation. 1-3 Credits.

Individual study selected by the student. Supervised and approved by a faculty member with the approval of the graduate program director. Prerequisites: permission of the instructor or graduate program director.

MSIM 898. Research in Modeling and Simulation. 1-12 Credits.

Supervised research prior to passing Ph.D. candidacy exam. Prerequisites: permission of the instructor and graduate program director.

MSIM 899. Dissertation. 1-12 Credits.

Prerequisites: permission of the instructor and graduate program director. Directed research for the doctoral dissertation.

MSIM 999. Doctoral Graduate Credit. 1 Credit.

This course is a pass/fail course doctoral students may take to maintain active status after successfully passing the candidacy examination. All doctoral students are required to be registered for at least one graduate credit hour every semester until their graduation.