29 graduate courses in the Spring 2013 Graduate Calendar, from Waterloo’s archived copy.
Review of mathematical and computational preliminaries; sources of error in floating-point arithmetic; solution of linear equations, eigen value problems, singular value decomposition, non-linear equations, ordinary differential equations and issues in designing mathematical software. The emphasis in this course will be on solution techniques rather than modelling and equation formulation.
LEC · Course ID 003143Archived pageSYDE 621 today
The course outlines fundamentals of intelligent systems design using tools of computational intelligence and soft computing. These include fuzzy logic, neural networks, genetic algorithms and other hybrid techniques such as neuro fuzzy systems and fuzzy-generated algorithms.
LEC · Course ID 003146Archived pageSYDE 625 today
The theory and application of time-series modelling are presented for describing phenomena measured at discrete points in time. The types of time-series models include stationary auto regressive moving average (ARMA), nonstationary, special families of seasonal, transfer function-noise (multiple inputs-single output), intervention, and multivariate (multiple inputs-multiple output) models. Applications are used for explaining how the foregoing models are fitted to both natural and socio-economic time series by following the identification, estimation and diagnostic check stages of model construction. Other topics include simulation in engineering design, forecasting in the operation of large-scale projects, and environmental impact assessment.
LEC · Course ID 003147Archived pageSYDE 631 today
This course is intended to give a broad treatment of the subject of practical optimization. Emphasis will be given to understanding the motivation and scope of various optimization techniques for constrained and unconstrained problems. The methods discussed include, but are not limited to: Newton's method and its variants, secant methods and conjugate gradient methods for unconstrained problems; active set methods, penalty methods and Lagrangian methods for constrained problems. In order to use, adapt and modify these methods, details that affect their performance will be discussed.
LEC · Course ID 003148Archived pageSYDE 632 today
A survey of modern quantitative remote sensing using optical, infrared, and microwave radiation. The principles and technologies for acquiring and understanding remotely sensed image data are discussed. Physical principles of EM propagation and interaction between the radiation and terrestrial and atmospheric materials. Principles and operation of sensor systems. Principles of pattern recognition and image processing techniques unique to remote sensing. Applications of remote sensing to monitoring vegetation, soil, oceans, and inland waters, and snow and ice.
Antireq: SYDE 730 Tpc 2
LEC · Course ID 014482Archived pageSYDE 633 today
This course examines the fundamentals of modern perspectives on interface design for complex systems using current methods in cognitive engineering. We discuss Cognitive Work Analysis, Brunswick's' Lens Model, Goal Directed Task Analysis, Situation Awareness Oriented Design, Naturalistic Decision Making, Contextual Inquiry, Macro-cognitive Methods, Activity Theory, Concept Mapping, Cognitive Task Analysis, Social Network Analysis and their application to different types of human engineering problems. Students in this course will learn multiple methods in cognitive engineering with an emphasis on knowing the differences in foundation, assumptions and appropriate application of the methods. Students will be expected to apply the methods in a realistic research context, applying for ethics clearance and working with actual participants. Examples of appropriate topics may include understanding how people work with complex or automated systems models. Finally this course discusses aspects of the current research environment in cognitive engineering, with the objective of developing successful future researchers in this area.
Instructor Consent Required
LEC · Course ID 003149Archived pageSYDE 642 today
Interaction of humans with technological systems often takes place within the broader context of a collaborative setting. Therefore, there is an increasing trend for the design of these systems to incorporate and support group interactions. This course will emphasize the study of collaboration from an interdisciplinary perspective and the derivation of system design criteria. Topics will include group theories, collaboration requirements (including communication, coordination, team awareness), quantitative and qualitative research methods (including laboratory studies, surveys, ethnographic research methods), data analysis, and collaboration technologies.
Antireq: SYDE 740 Tpc 9
LEC · Course ID 014495Archived pageSYDE 643 today
The focus of the course is on in-depth explorations of primary methods of data collection used in human factors engineering research and product design. We will begin with various philosophical positions regarding human factors for testing and evaluation as they relate to both industrial and research applications. We will discuss the applications and implications of data collection involving human participants; the limitations of statistical analyses; and the potential application of human factors research as guidelines for product or system design. Students will be encouraged to explore human factors methods related to their own area of research.
Antireq: SYDE 740 Tpc 2
LEC · Course ID 014497Archived pageSYDE 644 today
In this course, linear graph theory is used to model the topology of 2-d and 3-d systems of rigid bodies connected by mechanical joints, springs, dampers, and actuators. Graph-theoretic methods are then used to systematically derive the kinematic and dynamic equations; the numeric solution of these equations provides a simulation of the system's motion. Topics include: review of kinematics, dynamics and graph theoretic (GT) methods; application to one-dimensional mechanical systems; GT representation of two-dimensional components and systems; formulation and solution of governing system equations; extension to three dimensional mechanical systems with flexible bodies and mechatronic components; application to kinematic and dynamic analysis of mechanisms, robotic manipulators, vehicles and satellites.
LEC · Course ID 003151Archived pageSYDE 652 today
This course extends material in SY DE 551 to include complex systems, systems with uncertainty and systems design issues. Material covered includes: non-linear systems models, their formulations and solutions; higher-order sensitivity models and solutions; second moment analysis and robust design methods for systems with probabilistic components. Examples are taken from electro-mechanical disciplines.
LEC · Course ID 003153Archived pageSYDE 654 today
This course is intended to provide an understanding of the principles of optimal control and how they are used in various engineering applications. Dynamic programming, variational approach and Pontryagin's Minimum Principle, linear quadratic optimal control, discrete-time optimal control, constrained optimal control systems and model predictive control are introduced. Numerical methods for optimal control problems are also discussed briefly.
Antireq: SYDE 750 Tpc 22
LEC · Course ID 014498Archived pageSYDE 655 today
Robust design encompasses the theories and methodologies that make performance measures (responses, critical times, energy, etc.) invariant to uncertainties in design variables (environmental conditions, manufacturing processes, material dimensions and properties, etc.). In this course you will learn how robust design methods and mathematical models of engineering systems help find improved designs at a lower cost. Topics include: the building of simple, efficient, meta-models through computer experiments to replace traditional mechanistic models. Performance measures and their design specifications. Sensitivity and importance analysis to select design variables. Second moment methods using Taylor series to provide parameter (mean) design. Probabilistic methods combined with manufacturing and scrap costs to perform simultaneous parameter design and tolerance allocation. Desirability functions and loss functions to deal with multiple competing performance measures. Integrated design by constrained optimization. Examples come from industrial processes, as well as hydraulic, electrical and mechatronic systems. Mathematics required: Total derivatives, Matrix calculus, Kronecker product, singular value decomposition. Matlab serves as the computing tool. Course notes are available.
Antireq: SYDE 750 Tpc 21
LEC · Course ID 014490Archived pageSYDE 661 today
This course is intended to provide insights into advanced topics in image processing. The topics discussed include but are not limited to: multi-scale and probabilistic image respresentation and analysis, image restoration, invariant image representation, image reconstruction, image fusion, otical flow, image segmentation, and image registration. Recent research papers and review papers from the field will be sued as complimentary material to weekly lectures.
Antireq: SYDE 770 Tpc 14
LEC · Course ID 014499Archived pageSYDE 671 today
Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. Where these images are acquired from a microscope, telescope, satellite, or medical imaging device there is a statistical image processing task: the interference of something - an artery, a road, a DNA marker, an oil spill - from imagery, possibly noisy, blurry, or incomplete. The goal of this course is to address methods for solving multidimensional statistical problems, emphasizing theory, mathematical modeling, and algorithms. Specific topics of interest include inverse problems, multidimensional modeling, random fields, and hierarchical methods.
Antireq: SYDE 770 Tpc 4
LEC · Course ID 014491Archived pageSYDE 672 today
This course introduces methods to acquire state (both spatial and temporal) estimations from video streams. Video streams are analyzed as dynamic systems, linear and non-linear. If the system can be approximated as linear and Gaussian in terms of the dynamic noise in the process and measurement, then Kalman filter techniques are used. This refers to sequential state estimation. For nonlinear dynamical systems, the EFK (Extended Kalman filter) can be used by a liberalization of the stat space model. Particle filters are used to address state estimation problems where the systems are non-linear and non-Gaussian. Particle Filters are rooted in Bayesian estimation and Monte Carlo procedures. The course builds upon these techniques in studying visual tracking and the components of Visual SLAM (Simultaneous Localization and Mapping) procedures.
Antireq: SYDE 770 Tpc 7
LEC · Course ID 014492Archived pageSYDE 673 today
This course focuses on 3D computer-vision and camera/optical-based 3D shape-measurement techniques. Topics include stereo-camera 3D measurement, structures-light techniques, laser-camera range-sensing, fringe-projection phase shifting methods, curve and surface representation, surface fitting, and range-image registration. The measurement methods will include setup of measurement systems and calibration of instrumentation. Techniques will be demonstrated and practical exercises will be given. Biomedical applications will be discussed. Students will complete an individual course project with written report and oral presentation in class.
Antireq: SYDE 770 Tpc 9
LEC · Course ID 014493Archived pageSYDE 674 today
Pattern recognition addresses the problem of detecting and classifying patterns in data, a process of machine perception in which objects are assigned to classes to which they are most similar. This course introduces the three modern approaches to pattern recognition: statistical, structural and neural. Specific topics include distance and probability based approaches in multidimensional feature spaces, feature extraction, clustering and performance measures; pattern grammars, syntax analysis and grammatical inference; connectionist models, pattern associators, back propagation and self-organizing networks.
LEC · Course ID 003154Archived pageSYDE 675 today
This course introduces the fundamental concepts for medical imaging which include medical image formation (X-ray, CT, MRI, sonography); storage and formats (DICOM, DICOM RT, PACS); visualization, detection and analysis (enhancement, segmentation, registration, compression); safety and regulations for imaging devices & software (IEEE standards, Health Canada Licensing, FDA Clearance).
LEC · Course ID 003156Archived pageSYDE 677 today
This course provides specific knowledge in microelectromechanical systems (MEMS) and devices including microactuators, microsensors, micro-domain forces, microfabrication, and their actuation principles. Application domains of MEMS in RF, optics, and biosensing will be discussed. Specific topics include MEMS actuation mechanisms such as electrostatic, electromagnetic, thermal, and piezoelectric; and sensing mechanisms such a peizoresistive, capacitve, optical, and bio-transducer. Topics such as lithography, thin-film deposition methods, etching techniques will be taught. The course covers practical examples, device architecture, fabrication design rules and fabrication procedures.
LEC · Course ID 012235Archived pageSYDE 682 today
This course involves the rigorous grounding in the theory and practice of MEMS design as well as ways of extending MEMS (micro-electro-mechanical systems) to apply to the design of NEMS (nano-electro-mechanical systems). Modeling and simulation processes as they apply to MEMS and NEMS are presented. Concepts covered include basics of statics and dynamics necessary to construct lumped-mass models, an introduction to the use of reduced-order models in MEMS/NEMS design, the use of these modeling techniques with the use of commercial FEM software (COMSOL, ANSYS, and Coventor) in the simulation and design of MEMS/NEMS, and discussing the most effective uses and limitations of each of these approaches. The course involves building effective MEMS by design not by trial and error. Analytical tools for exploring the possibilities of nano-electro-mechanical systems (NEMS) are introduced.
Antireq: SYDE 750 Tpc 24
LEC · Course ID 014494Archived pageSYDE 683 today
The course covers fundamental topics of biocompatibility of materials in medicine (polymers, ceramics, metals, composites, bioengineered materials). Fundamental principles of materials science (bonding, atomic/molecular structure) as well as interfacial engineering of materials will be reviewed. Materials response to biological systems such as corrosion, degradation, leaching and fracture will be studied in the context of specific biomedical applications. The host response to materials (immune, inflammatory response and coagulation) will also be treated. Specific examples of material interactions with biological systems such as bone, blood, skin and the eye will be studied.
Antireq: SYDE 780 Tpc 2
LEC · Course ID 014500Archived pageSYDE 684 today
Instructor Consent Required
RDG · Course ID 003163Archived pageSYDE 710 today
Instructor Consent Required
RDG · Course ID 003173Archived pageSYDE 720 today
Instructor Consent Required
RDG · Course ID 003183Archived pageSYDE 730 today
Instructor Consent Required
RDG · Course ID 010502Archived pageSYDE 740 today
Instructor Consent Required
SEM, TUT · Course ID 003199Archived pageSYDE 750 today
Instructor Consent Required
RDG · Course ID 003209Archived pageSYDE 760 today
Instructor Consent Required
LEC · Course ID 003214Archived pageSYDE 770 today
Instructor Consent Required
RDG · Course ID 003224Archived pageSYDE 780 today