Courses tagged with "Nutrition" (212)
This is the second course in a two-semester sequence on astrophysics. Topics include galactic dynamics, groups and clusters on galaxies, phenomenological cosmology, Newtonian cosmology, Roberston-Walker models, and galaxy formation.
Should we be excited about the Higgs boson? Find out more about particle physics and understanding the universe.
This course is designed for anyone who is interested in learning more about modern astronomy. We will help you get up to date on the most recent astronomical discoveries while also providing support at an introductory level for those who have no background in science.
The fundamental concepts, and approaches of aerospace engineering, are highlighted through lectures on aeronautics, astronautics, and design. Active learning aerospace modules make use of information technology. Student teams are immersed in a hands-on, lighter-than-air (LTA) vehicle design project, where they design, build, and fly radio-controlled LTA vehicles. The connections between theory and practice are realized in the design exercises. Required design reviews precede the LTA race competition. The performance, weight, and principal characteristics of the LTA vehicles are estimated and illustrated using physics, mathematics, and chemistry known to freshmen, the emphasis being on the application of this knowledge to aerospace engineering and design rather than on exposure to new science and mathematics.
This course introduces the fundamental Lean Six Sigma principles that underlay modern continuous improvement approaches for industry, government and other organizations. Lean emerged from the Japanese automotive industry, particularly Toyota, and is focused on the creation of value through the relentless elimination of waste. Six Sigma is a quality system developed at Motorola which focuses on elimination of variation from all processes. The basic principles have been applied to a wide range of organizations and sectors to improve quality, productivity, customer satisfaction, employee satisfaction, time-to-market and financial performance.
This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.
A presentation of the fundamentals of modern numerical techniques for a wide range of linear and nonlinear elliptic, parabolic and hyperbolic partial differential equations and integral equations central to a wide variety of applications in science, engineering, and other fields. Topics include: Mathematical Formulations; Finite Difference and Finite Volume Discretizations; Finite Element Discretizations; Boundary Element Discretizations; Direct and Iterative Solution Methods.
This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5212 (Numerical Methods for Partial Differential Equations).
This course surveys a variety of reasoning, optimization and decision making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their application, taken from the disciplines of artificial intelligence and operations research.
Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, and machine learning. Optimization paradigms include linear programming, integer programming, and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes.
This course covers Lagrangian and Hamiltonian mechanics, systems with constraints, rigid body dynamics, vibrations, central forces, Hamilton-Jacobi theory, action-angle variables, perturbation theory, and continuous systems. It provides an introduction to ideal and viscous fluid mechanics, including turbulence, as well as an introduction to nonlinear dynamics, including chaos.
This course provides an overview of astrophysical cosmology with emphasis on the Cosmic Microwave Background (CMB) radiation, galaxies and related phenomena at high redshift, and cosmic structure formation. Additional topics include cosmic inflation, nucleosynthesis and baryosynthesis, quasar (QSO) absorption lines, and gamma-ray bursts. Some background in general relativity is assumed.
This course in crystal structure refinement examines the practical aspects of crystal structure determination from data collection strategies to data reduction and basic and advanced refinement problems of organic and inorganic molecules.
This course studies basic optimization and the principles of optimal control. It considers deterministic and stochastic problems for both discrete and continuous systems. The course covers solution methods including numerical search algorithms, model predictive control, dynamic programming, variational calculus, and approaches based on Pontryagin's maximum principle, and it includes many examples and applications of the theory.
This course provides an introduction to the transportation industry's major technical challenges and considerations. For upper level undergraduates interested in learning about the transportation field in a broad but quantitative manner. Topics include road vehicle engineering, internal combustion engines, batteries and motors, electric and hybrid powertrains, urban and high speed rail transportation, water vessels, aircraft types and aerodynamics, radar, navigation, GPS, GIS. Students will complete a project on a subject of their choosing.
This course was created for the "product development" track of MIT's System Design and Management Program (SDM) in conjunction with the Center for Innovation in Product Development. After taking this course, a student should be able to:
- Formulate measures of performance of a system or quality characteristics. These quality characteristics are to be made robust to noise affecting the system.
- Sythesize and select design concepts for robustness.
- Identify noise factors whose variation may affect the quality characteristics.
- Estimate the robustness of any given design (experimentally and analytically).
- Formulate and implement methods to reduce the effects of noise (parameter design, active control, adjustment).
- Select rational tolerances for a design.
- Explain the role of robust design techniques within the wider context of the product development process.
- Lead product development activities that include robust design techniques.
