This course focuses on computational and experimental analysis of biological systems across a hierarchy of scales, including genetic, molecular, cellular, and cell population levels. The two central themes of the course are modeling of complex dynamic systems and protein design and engineering. Topics include gene sequence analysis, molecular modeling, metabolic and gene regulation networks, signal transduction pathways and cell populations in tissues. Emphasis is placed on experimental methods, quantitative analysis, and computational modeling.

This course presents the fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine. It covers principles and algorithms for processing both deterministic and random signals. Topics include data acquisition, imaging, filtering, coding, feature extraction, and modeling. The focus of the course is a series of labs that provide practical experience in processing physiological data, with examples from cardiology, speech processing, and medical imaging. The labs are done in MATLAB® during weekly lab sessions that take place in an electronic classroom. Lectures cover signal processing topics relevant to the lab exercises, as well as background on the biological signals processed in the labs.

This Project has been completed as part of a standard Calculus 3 synchronous online course during Spring 2021 Semester at MassBay Community College, Wellesley Hills, MA. 

A Brief Introduction to Engineering Computation with MATLAB is specifically designed for students with no programming experience. However, students are expected to be proficient in First Year Mathematics and Sciences and access to good reference books are highly recommended. Students are assumed to have a working knowledge of the Mac OS X or Microsoft Windows operating systems. The strategic goal of the course and book is to provide learners with an appreciation for the role computation plays in solving engineering problems. MATLAB specific skills that students are expected to be proficient at are: write scripts to solve engineering problems including interpolation, numerical integration and regression analysis, plot graphs to visualize, analyze and present numerical data, and publish reports.

Introduction to computer programming within a numerical computing environment (MATLAB or similar) including types of data representation, graphical display of data, and development of modular programs with application to engineering analysis and problem solving.

Tijdens de cursus Caleidoscoop worden verschillende aspecten belicht waarmee de eerstejaarsstudenten worden voorzien van basisvaardigheden en basiskennis die noodzakelijk zijn voor het succesvol volgen van een studie in de wiskunde.

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

This Project has been completed as part of a standard Calculus 3 synchronous online course during Spring 2021 Semester at MassBay Community College, Wellesley Hills, MA. 

Introduction to the dynamics and vibrations of lumped-parameter models of mechanical systems. Kinematics. Force-momentum formulation for systems of particles and rigid bodies in planar motion. Work-energy concepts. Virtual displacements and virtual work. Lagrange’s equations for systems of particles and rigid bodies in planar motion. Linearization of equations of motion. Linear stability analysis of mechanical systems. Free and forced vibration of linear multi-degree of freedom models of mechanical systems; matrix eigenvalue problems. Introduction to numerical methods and MATLAB® to solve dynamics and vibrations problems.

This class is an introduction to the dynamics and vibrations of lumped-parameter models of mechanical systems. Topics include kinematics; force-momentum formulation for systems of particles and rigid bodies in planar motion; work-energy concepts; virtual displacements and virtual work; Lagrange’s equations for systems of particles and rigid bodies in planar motion; linearization of equations of motion; linear stability analysis of mechanical systems; free and forced vibration of linear multi-degree of freedom models of mechanical systems; and matrix eigenvalue problems. The class includes an introduction to numerical methods and using MATLAB® to solve dynamics and vibrations problems.
This version of the class stresses kinematics and builds around a strict but powerful approach to kinematic formulation which is different from the approach presented in Spring 2007. Our notation was adapted from that of Professor Kane of Stanford University.

This course provides a review of physical, chemical, ecological, and economic principles used to examine interactions between humans and the natural environment. Mass balance concepts are applied to ecology, chemical kinetics, hydrology, and transportation; energy balance concepts are applied to building design, ecology, and climate change; and economic and life cycle concepts are applied to resource evaluation and engineering design. Numerical models are used to integrate concepts and to assess environmental impacts of human activities. Problem sets involve development of MATLAB® models for particular engineering applications. Some experience with computer programming is helpful but not essential.

This course provides a review of physical, chemical, ecological, and economic principles used to examine interactions between humans and the natural environment. Mass balance concepts are applied to ecology, chemical kinetics, hydrology, and transportation; energy balance concepts are applied to building design, ecology, and climate change; and economic and life cycle concepts are applied to resource evaluation and engineering design. Numerical models are used to integrate concepts and to assess environmental impacts of human activities. Problem sets involve development of MATLAB® models for particular engineering applications. Some experience with computer programming is helpful but not essential.

This half-semester course introduces computational methods for solving physical problems, especially in nuclear applications. The course covers ordinary and partial differential equations for particle orbit, and fluid, field, and particle conservation problems; their representation and solution by finite difference numerical approximations; iterative matrix inversion methods; stability, convergence, accuracy and statistics; and particle representations of Boltzmann’s equation and methods of solution such as Monte-Carlo and particle-in-cell techniques.

A gear is a simple machine that is very useful to increase the speed or torque of a wheel. In this activity, students learn about the trade-off between speed and torque when designing gear ratios. The activity setup includes a LEGO(TM) MINDSTORMS(TM) NXT pulley system with two independent gear sets and motors that spin two pulleys. Each pulley has weights attached by string. In a teacher demonstration, the effect of adding increasing amounts of weight to the pulley systems with different gear ratios is observed as the system's ability to lift the weights is tested. Then student teams are challenged to design a gear set that will lift a given load as quickly as possible. They test and refine their designs to find the ideal gear ratio, one that provides enough torque to lift the weight while still achieving the fastest speed possible.

This textbook provides an introduction to the MATLAB programming language for first-year mechanical engineering students enrolled in ME 160. Designed to follow the content taught in class, this book provides a supplement to in-class learning that is presented at a level that is understandable to a student with no experience coding before coming to Iowa State University.

Students use a hurricane tracking map to measure the distance from a specific latitude and longitude location of the eye of a hurricane to a city. Then they use the map's scale factor to convert the distance to miles. They also apply the distance formula by creating an x-y coordinate plane on the map. Students are challenged to analyze what data might be used by computer science engineers to write code that generates hurricane tracking models. Then students analyze a MATLAB® computer code that uses the distance formula repetitively to generate a table of data that tracks a hurricane at specific time intervals. Students come to realize that using a computer program to generate the calculations (instead of by hand) is very advantageous for a dynamic situation like tracking storm movements. Their inspection of some MATLAB code helps them understand how it communicates what to do using mathematical formulas, logical instructions and repeated tasks. They also conclude that the example program is too simplistic to really be a useful tool; useful computer model tools must necessarily be much more complex.

This course is intended to assist undergraduates with learning the basics of programming in general and programming MATLAB® in particular.

This is an accelerated introduction to MATLAB® and its popular toolboxes. Lectures are interactive, with students conducting sample MATLAB problems in real time. The course includes problem-based MATLAB assignments. Students must provide their own laptop and software. This is great preparation for classes that use MATLAB.

This course was offered as a non-credit program during the Independent Activities Period (IAP), January 2008. A more recent version is available as course 18.S997 Introduction To MATLAB Programming, including video lectures.
The course, intended for students with no programming experience, provides the foundations of programming in MATLAB®. Variables, arrays, conditional statements, loops, functions, and plots are explained. At the end of the course, students should be able to use MATLAB in their own work, and be prepared to deepen their MATLAB programming skills and tackle other languages for computing, such as Java, C++, or Python.
The course mostly follows the official MATLAB Manual, available from The MathWorks. We will cover material from chapters 2-5.

This activity introduces students to loading and plotting data in MATLAB. Students explore scalar and vector time series and profile data commonly used in the field of Oceanography using data sets from publicly available sources or that they collected in local waters.