This art history video discussion examines Edvard Munch's "The Storm", 1893, oil on canvas (MoMA).
This course covers the derivation of symmetry theory; lattices, point groups, space groups, and their properties; use of symmetry in tensor representation of crystal properties, including anisotropy and representation surfaces; and applications to piezoelectricity and elasticity.
The goal of this task is to help students understand the commutative property of addition by examining the addition facts for single digit numbers. This is important as it gives students a chance, at a young age, to do more than memorize these arithmetic facts which they will use throughout their education.
A chronological survey of masterpieces of the symphonic literature, ranging from the mid-eighteenth to the early twenty-first century. Includes one work by each major figure. As a participatory subject, students give oral presentations concerning composers and their symphonies. Prior musical score-reading experience is helpful. Students attend two or three symphonic concerts during the term.
In this course we will discover how innovative technologies combined with profound hypotheses have given rise to our current understanding of neuroscience. We will study both new and classical primary research papers with a focus on the plasticity between synapses in a brain structure called the hippocampus, which is believed to underlie the ability to create and retrieve certain classes of memories. We will discuss the basic electrical properties of neurons and how they fire. We will see how firing properties can change with experience, and we will study the biochemical basis of these changes. We will learn how molecular biology can be used to specifically change the biochemical properties of brain circuits, and we will see how these circuits form a representation of space giving rise to complex behaviors in living animals. A special emphasis will be given to understanding why specific experiments were done and how to design experiments that will answer the questions you have about the brain. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current biological research in a highly interactive setting. Many instructors of the Advanced Undergraduate Seminars are postdoctoral scientists with a strong interest in teaching.
This course presents a comparison of different proposed architectures for the syntax module of grammar. The subject traces several themes across a wide variety of approaches, with emphasis on testable differences among models. Models discussed include ancient and medieval proposals, structuralism, early generative grammar, generative semantics, government-binding theory/minimalism, LFG, HPSG, TAG, functionalist perspectives and others.
Studies synthesis of polymeric materials, emphasizing interrelationships of chemical pathways, process conditions, and "microarchitecture" of molecules produced. Chemical pathways include traditional approaches such as anionic, radical condensation, and ring-opening polymerizations. New techniques, including stable free radicals and atom transfer free radicals, new catalytic approaches to well-defined architectures, and polymer functionalization in bulk and at surfaces. Process conditions include bulk, solution, emulsion, suspension, gas phase, and batch vs continuous fluidized bed. "Microarchitecture" includes tacticity, molecular-weight distribution, sequence distributions in copolymers, "errors" in chains such as branches, head-to-head addition, and peroxide incorporation.
This course focuses on general methods and strategies for the synthesis of complex organic molecules. Emphasis is on strategies for stereoselective synthesis, including stereocontrolled synthesis of complex acyclic compounds.
Covers principles and methods for technical System Architecture. Presents a synthetic view including: the resolution of ambiguity to identify system goals and boundaries; the creative process of mapping form to function; the analysis of complexity and methods of decomposition and re-integration. Industrial speakers and faculty present examples from various industries. Heuristic and formal methods are presented. Restricted to SDM students.
Introduction to axiomatic design. Theoretical basis for rational design. One-FR Design. Multi-FR design. System design. Software design. Product design. Materials and materials process design. Manufacturing system design. Complexities in design: time-independent real complexity, time-independent imaginary complexity, time-dependent combinatorial complexity, and time-dependent periodic complexity. Industrial case studies. This course studies what makes a good design and how one develops a good design. Students consider how the design of engineered systems (such as hardware, software, materials, and manufacturing systems) differ from the "design" of natural systems such as biological systems; discuss complexity and how one makes use of complexity theory to improve design; and discover how one uses axiomatic design theory (AD theory) in design of many different kinds of engineered systems. Questions are analyzed using Axiomatic Design Theory and Complexity Theory. Case studies are presented including the design of machines, tribological systems, materials, manufacturing systems, and recent inventions. Implications of AD and complexity theories on biological systems discussed.
Continuation of 15.871, emphasizing tools and methods needed to apply systems thinking and simulation modeling successfully in complex real-world settings. Uses simulation models, management flight simulators, and case studies to deepen the conceptual and modeling skills introduced in 15.871. Through models and case studies of successful applications students learn how to use qualitative and quantitative data to formulate and test models, and how to work effectively with senior executives to implement change successfully.
The purpose of this course is to learn how to specify the behavior of embedded systems and to experience the design
of a provably correct system. In this course you will learn how to formally
specify requirements and to prove (or disprove) them on the behaviour. With a practical assignment
you will experience how to apply the techniques in practice.
Subject focuses on project management principles, methods, and tools to effectively plan and implement successful developments. Material is divided into five major sections: project organization, planning, monitoring, control, and learning. Emphasis on new methodologies and tools such as deterministic, probabilistic and resource management, as well as project system dynamics and measurements. Topics are covered from strategic, tactical, and operational perspectives. Term projects analyze and evaluate past and ongoing projects in student's area of interest. Projects used to apply concepts discussed in class.
This course provides an in-depth technical and policy analysis of various options for the nuclear fuel cycle. Topics include uranium supply, enrichment fuel fabrication, in-core physics and fuel management of uranium, thorium and other fuel types, reprocessing and waste disposal. Also covered are the principles of fuel cycle economics and the applied reactor physics of both contemporary and proposed thermal and fast reactors. Nonproliferation aspects, disposal of excess weapons plutonium, and transmutation of actinides and selected fission products in spent fuel are examined. Several state-of-the-art computer programs are provided for student use in problem sets and term papers.
Introduction to quantitative methods and modeling techniques to address key questions in modern biology. Overview of quantitative modeling techniques in evolutionary biology, molecular biology and genetics, cell biology and developmental biology. Description of key experiments that validate models. Specific topics include: Evolutionary biology: theoretical models for evolution, evolution in test tube, evolution experiments with viruses and bacteria, complexity and evolution; Molecular biology and genetics: protein design, bioinformatics and genomics, constructing and modeling of genetic networks, control theory and genetic networks; Cell biology: forces and motion, cell motility, signal transduction pathways, chemotaxis and pheromone response; Development biology: pattern formation, self-organization, and models of Drosophila development.
Systems Engineering is an interdisciplinary approach and means to enable the realization of successful systems. It focuses on defining customer needs and required functionality early in the development cycle, documenting requirements, then proceeding with design synthesis and system validation while considering the complete problem including operations, performance, test, manufacturing, cost, and schedule. This subject emphasizes the links of systems engineering to fundamentals of decision theory, statistics, and optimization. It also introduces the most current, commercially successful techniques for systems engineering.
This course covers introductory microbiology from a systems perspective, considering microbial diversity, population dynamics, and genomics. Emphasis is placed on the delicate balance between microbes and humans, and the changes that result in the emergence of infectious diseases and antimicrobial resistance. The case study approach covers such topics as vaccines, toxins, biodefense, and infections including LegionnaireŰŞs disease, tuberculosis, Helicobacter pylori, and plague.
Upon successful completion of this course, students will be able to: * Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domains * Make quantitative estimates of model parameters from experimental measurements * Obtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methods * Obtain the frequency-domain response of linear systems to sinusoidal inputs * Compensate the transient response of dynamic systems using feedback techniques * Design, implement and test an active control system to achieve a desired performance measureMastery of these topics will be assessed via homework, quizzes/exams, and lab assignments.
A computational and application-oriented introduction to the modeling of large-scale systems in a wide variety of decision-making domains and the optimization of such systems using state-of-the-art optimization software. Application domains include transportation and logistics, pattern classification, structural design, financial engineering, and telecommunications system planning. Modeling tools and techniques covered include linear, network, discrete, and nonlinear programming, heuristic methods, sensitivity and postoptimality analysis, decomposition methods for large-scale systems, and stochastic programming.
Students are challenged to find a way to get school t-shirts up into the stands during sporting events. They work with a real client (if possible, such as a cheerleading squad, booster club or band) to determine the requirements and constraints that would make the project a success, including a budget constraint. They think “outside of the box” to come up with lots of ideas. Then they mock-up small-scale model(s) of their best, most feasible ideas for testing, before making full-scale usable devices that they further refine and then demonstrate and deliver to the client.