Courses tagged with "Nutrition" (421)

Traditionally, progress in electronics has been driven by miniaturization. But as electronic devices approach the molecular scale, classical models for device behavior must be abandoned. To prepare for the next generation of electronic devices, this class teaches the theory of current, voltage and resistance from atoms up. To describe electrons at the nanoscale, we will begin with an introduction to the principles of quantum mechanics, including quantization, the wave-particle duality, wavefunctions and Schrödinger's equation. Then we will consider the electronic properties of molecules, carbon nanotubes and crystals, including energy band formation and the origin of metals, insulators and semiconductors. Electron conduction will be taught beginning with ballistic transport and concluding with a derivation of Ohm's law. We will then compare ballistic to bulk MOSFETs. The class will conclude with a discussion of possible fundamental limits to computation.

This course is offered to undergraduates and introduces students to the formulation, methodology, and techniques for numerical solution of engineering problems. Topics covered include: fundamental principles of digital computing and the implications for algorithm accuracy and stability, error propagation and stability, the solution of systems of linear equations, including direct and iterative techniques, roots of equations and systems of equations, numerical interpolation, differentiation and integration, fundamentals of finite-difference solutions to ordinary differential equations, and error and convergence analysis. The subject is taught the first half of the term.

This subject was originally offered in Course 13 (Department of Ocean Engineering) as 13.002J. In 2005, ocean engineering became part of Course 2 (Department of Mechanical Engineering), and this subject was renumbered 2.993J.

This course offers an advanced introduction to numerical linear algebra. Topics include direct and iterative methods for linear systems, eigenvalue decompositions and QR/SVD factorizations, stability and accuracy of numerical algorithms, the IEEE floating point standard, sparse and structured matrices, preconditioning, linear algebra software. Problem sets require some knowledge of MATLAB®.

6.336J is an introduction to computational techniques for the simulation of a large variety of engineering and physical systems. Applications are drawn from aerospace, mechanical, electrical, chemical and biological engineering, and materials science. Topics include: mathematical formulations; network problems; sparse direct and iterative matrix solution techniques; Newton methods for nonlinear problems; discretization methods for ordinary, time-periodic and partial differential equations, fast methods for partial differential and integral equations, techniques for dynamical system model reduction and approaches for molecular dynamics.

This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5211 (Introduction to Numerical Simulation).

This course provides a complete introduction to programming for digital musicians and artists, in the real-time multimedia language ChucK. Rich with practical examples and pointers to additional web resources, it can be understood by novices wishing to learn to program interactive arts systems.

This course is an introduction to software engineering, using the Java™ programming language. It covers concepts useful to 6.005. Students will learn the fundamentals of Java. The focus is on developing high quality, working software that solves real problems.

The course is designed for students with some programming experience, but if you have none and are motivated you will do fine. Students who have taken 6.005 should not take this course. Each class is composed of one hour of lecture and one hour of assisted lab work.

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.

This course introduces the concepts, applications, algorithms, programming, and design of recommender systems--software systems that recommend products or information, often based on extensive personalization. Learn how web merchants such as Amazon.com personalize product suggestions and how to apply the same techniques in your own systems!

This course is about learning to program well: building programs that are elegant, well tested and easy to maintain. The course is designed for students with no programming experience at all. Nonetheless, former students who already knew how to program have said it made them better programmers.

6.101 is an introductory experimental laboratory that explores the design, construction, and debugging of analog electronic circuits. Lectures and six laboratory projects investigate the performance characteristics of diodes, transistors, JFETs, and op-amps, including the construction of a small audio amplifier and preamplifier. Seven weeks are devoted to the design and implementation, and written and oral presentation of a project in an environment similar to that of engineering design teams in industry. The course provides opportunity to simulate real-world problems and solutions that involve trade offs and the use of engineering judgment. Engineers from local analog engineering companies come to campus to help students with their design projects.

6.111 is reputed to be one of the most demanding classes at MIT, exhausting many students' time and creativity. The course covers digital design topics such as digital logic, sequential building blocks, finite-state machines, FPGAs, timing and synchronization. The semester begins with lectures and problem sets, to introduce fundamental topics before students embark on lab assignments and ultimately, a digital design project. The students design and implement a final digital project of their choice, in areas such as games, music, digital filters, wireless communications, video, and graphics. The course relies on extensive use of Verilog® for describing and implementing digital logic designs on state-of-the-art FPGA.

This course explores the history of private and public rights in scientific discoveries and applied engineering, leading to the development of worldwide patent systems. The classes of invention protectable under the patent laws of the U.S., including the procedures in protecting inventions in the Patent Office and the courts will be examined. A review of past cases involving inventions and patents in:

1. the chemical process industry and medical pharmaceutical, biological, and genetic-engineering fields;
2. devices in the mechanical, ocean exploration, civil, and/or aeronautical fields;
3. the electrical, computer, software, and electronic areas, including key radio, solid-state, computer and software inventions; and also
4. software protection afforded under copyright laws.

Periodic joint real-time class sessions and discussions by video-audio Internet conferencing, with other universities will also be conducted.

This course covers the development of programs containing a significant amount of knowledge about their application domain. The course includes a brief review of relevant AI techniques; case studies from a number of application domains, chosen to illustrate principles of system development; a discussion of technical issues encountered in building a system, including selection of knowledge representation, knowledge acquisition, etc.; and a discussion of current and future research. The course also provides hands-on experience in building an expert system (term project).

The course focuses on experimental investigations of speech processes. Topics include: measurement of articulatory movements, measurements of pressures and airflows in speech production, computer-aided waveform analysis and spectral analysis of speech, synthesis of speech, perception and discrimination of speechlike sounds, speech prosody, models for speech recognition, speech disorders, and other topics.

• Two 1-hour lectures per week
• Two labs per week
• Brief lab reports
• Term project, with short term paper
• No exams