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Energy Systems Minor

...E E 555 Advanced Energy Distribution Systems E E 556 Power Electronic Systems E E...


...E, AGRON, A ECL, BIOL, CHEM, C E...538 , AGRON 553 , AGRON 556 , and PLBIO 513...

E E 556: Power Electronic Systems

(3-0) Cr. 3.

Prereq: E E 452
Converter topologies, AC/DC, DC/DC, DC/AC, AC/AC. Converter applications to do motor drives, power supplies, AC motor drives, power system utility applications (var compensators) and power quality.

A B E 556: GIS Programming and Automation

(Dual-listed with A B E 556). (Cross-listed with C R P). (3-0) Cr. 3. F.

Prereq: C R P 351
Introduction to automated geoprocessing in Geographic Information Systems using Python. Focus on learning scripting language and object-oriented programming, automation of custom-designed geoprocessing scripts, and application toward student research and/or interests.

AER E 556: Guidance and Navigation of Aerospace Vehicles

(3-0) Cr. 3. F.

Prereq: AER E 331
Principles of guidance systems for spacecraft, launch vehicles, homing and ballistic missiles. Optimal guidance. Interplanetary transfer guidance with low thrust. Principles of inertial navigation. Theory and applications of the Global Positioning System. Celestial navigation procedures. Application of Kalman filtering to recursive navigation theory.

C E 556: Transportation Data Analysis

(3-0) Cr. 3.

Prereq: C E 355, a Statistics course at the 300 level or higher
Statistical, econometric, and data science principles applied to real-world transportation data. Includes identification of data sources and limitations. Fundamentals of reproducibility and replicability, validation (including spatial and temporal validation), differences and purposes of inferential, descriptive, predictive, causal models, etc. Linear regression, count regression, and discrete choice models. Basic utility theory and decision making with applications in transportation. Emphasis is placed on practical applications, proper model development, assumption checking, and usability of results.

CPR E 556: Scalable Software Engineering

(3-0) Cr. 3.

Prereq: COM S 309
Design and analysis techniques scalable to large software, project-based learning of problem solving techniques, automation tools for high productivity and reliability of software, analysis-based measurement and estimation techniques for predictable software engineering.

M E 556: Machine Vision

(Dual-listed with M E 456). Cr. 3. Repeatable. Alt. F., offered odd-numbered years.

Prereq: MATH 207 or MATH 317 or Permission of Instructor
Practical imaging processing techniques, geometric optics, and mathematics behind machine vision, as well as the most advanced 3D vision techniques. Experience with practical vision system development and analysis. Assignments include individual bi-weekly homework; weekly readings and lectures; and a semester-long research project on design and experiment vision systems.

M S E 556: Biomaterials

(Dual-listed with MAT E 456). (3-0) Cr. 3. F.

Prereq: CHEM 178; (MAT E 216 or MAT E 273 or MAT E 392)
Presentation of the basic chemical and physical properties of biomaterials, including metals, ceramics, and polymers, as they are related to their manipulation by the engineer for incorporation into living systems. Role of microstructure properties in the choice of biomaterials and design of artificial organs, implants, and prostheses.