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Past Programs
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Keynote: Securing IT in Healthcare: Part III |
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Keynote: SITH3, Technology-Enabled Remote Monitoring and Support |
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Intersection of mHealth and Behavioral Health |
Newsletter
ISTS Information Pamphlet
This course will cover some basic concepts underlying the 'information superhighway.' The technologies of high-speed networking have stimulated much activity within the federal government, the telecommunications and computer industries, and even social science and popular fiction writing. The technical focus will be on communications technologies, information theory, and the communications requirements of video (standard and ATV), speech (and other audio), text data. Social economic and policy issues will be an integral part of the course.
This course will provide students with an introduction to the current and emerging technologies used in homeland security and the practitioners who use them. Topics covered in class include personal protective equipment, physical and cyber security systems, communications and information technologies, information assurance, WMD detection, robotics, simulation, exercise and training technologies. Students will gain a detailed understanding of the role technology plays in protecting the homeland. Enrollment limited to 50 students per section.
A study and analysis of important numerical and computational methods for solving engineering and scientific problems. The course will include methods for solving linear and nonlinear equations, doing polynomial interpolation, evaluating integrals, solving ordinary differential equations, and determining eigenvalues and eigenvectors of matrices. The student will be required to write and run computer programs.
Prerequisite: ENGS 20 or COSC 1 and COSC 10; ENGS 22 or MATH 23, or equivalent.
The application of statistical techniques and concepts to maximize the amount and quality of information resulting from experiments. After a brief introductory summary of fundamental concepts in probability and statistics, topics considered will include probability distributions, sampling distributions, estimation and confidence intervals for parameters of statistical distributions, hypothesis testing, design and analysis of variance for single and multiple-factor experiments, regression analysis, estimation and confidence intervals for parameters of non-statistical models, and statistical quality control.
Prerequisite: MATH 13 or equivalent
Web site: http://engineering.dartmouth.edu/academics/courses/engs104/
An introduction to various methods of optimization and their uses in modern engineering. Students will learn to formulate and analyze optimization problems and apply optimization techniques in addition to learning the basic mathematical principles on which these techniques are based. Topic coverage includes linear programming, nonlinear programming, dynamic programming, combinatorial optimization and Monte Carlo methods.
Prerequisite: MATH 022 and ENGS 027 or equivalents, or permission of instructor
This course covers current and emerging information technologies, focusing on their engineering design, performance, and application. General topics, such as distributed component and object architectures, wireless networking, web computing, and information security, will be covered. Specific subjects will include Java, CORBA, JINI public key cryptography, web search engine theory and technology, and communications techniques relevant to wireless networking such as Code Division Multiple Access protocols and cellular technology.
Prerequisite: ENGS 20, ENGS 27, and ENGS 93 or COSC 60; ENGS 93 can be taken concurrently
Web site: http://engineering.dartmouth.edu/academics/courses/engg177/
Making decisions under conditions of risk and uncertainty is a fundamental part of every engineer and manager's job, whether the situation involves product design, investment choice, regulatory compliance, or human health and safety. This course will provide students with both qualitative and quantitative tools for structuring problems, describing uncertainty, assessing risks, and reaching decisions, using a variety of case studies that are not always amenable to standard statistical analysis. Bayesian methods will be introduced, emphasizing the natural connections between probability, utility, and decision-making.
Prerequisite: ENGS 27, ENGS 93, or comparable background in probabilistic reasoning
Web site: http://engineering.dartmouth.edu/academics/courses/engm188/
Taking a good idea and turning it into a successful product and a profitable business poses a number of technical, managerial, and financial challenges. The solutions to many of the challenges of entrepreneurship in general, and to those of starting up a technologically based business in particular, are provided by the law. A grounding in the law of intellectual property, contractual transactions, business structures, debt and equity finance, and securities regulation, both in the U.S. and in an international context, will help inventors and entrepreneurs to manage this part of the process intelligently and with a high likelihood of success.
Prerequisite: None
Web site: http://engineering.dartmouth.edu/academics/courses/engg312/
Advanced study in any of the following or other topics may be pursued: information theory, coding, noise, random signals, extraction of signals from noise, pattern recognition, and modulation theory. Normally offered in alternate years.
Prerequisites: ENGS 93, ENGS 110, and permission of instructor
