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MATLAB Seminar

MATLAB for Analyzing and Visualizing Geospatial Data

วันอังคารที่ 10 กันยายน 2562
ณ ห้อง Theater Room
ชั้น 2 หอสมุดป๋วย อึ๊งภากรณ์
มหาวิทยาลัยธรรมศาสตร์ ศูนย์รังสิต 
09:00 - 17:30

Exclusive Speaker Profile

Dr. Loren Shure

Loren has worked at MathWorks for over 30 years. For the first 27 of these years, Loren co-authored several MathWorks products in addition to adding core functionality to MATLAB, including major contributions to the design of the MATLAB language. She is currently part of the Application Engineering team, enabling Loren to spend more time and energy working with customers.

She graduated from MIT with a B.Sc. in physics and has a Ph.D. in marine geophysics from the University of California, San Diego, Scripps Institution of Oceanography. She is a Senior Member of IEEE.  Loren writes about MATLAB on her blog, The Art of MATLAB

Consulting Application Engineer, MathWorks

Topic Outline

Morning Session:

Topic 1: TurtleBot3 robot control and simulation with MATLAB/Simulink 

  • Overview of TurtleBot3 and Robotics Operating System (ROS)

  • ROS support package for MATLAB and Simulink

  • TurtleBot3 sensor reading and movement control using MATLAB command line

  • Building near real-time control GUI in MATLAB environment

  • Building ROS firmware using Simulink code generation

 Topic 2: IoT Based Monitoring and Control System with Waijung WebPage Designer

  • Overview of Waijung WebPage Designer (W2D)

  • Waijung blockset for MATLAB and Simulink

  • IoT Automatic Farming Monitoring & Control using WebPage Designer   

Afternoon Session:

Topic 1: What's New in MATLAB® 

MATLAB has changed significantly over the last 3 years to address the growing needs of our users, but we've noticed that even experienced MATLAB users aren't taking advantage of our latest and greatest features.

This seminar will cover the newest MATLAB features and show you how to utilize these features to simplify your work, save time, and increase your productivity.


  • MATLAB Foundation Updates

           o   Faster execution engine
           o   Graphics system
           o   Live Editor

  • Data handling and language enhancements

           o   Simpler data importing
           o   Improved datatypes
           o   Big data capabilities

  • App building

           o   App Designer
           o   Sharing apps and creating toolboxes

  • Hardware support

  • Other Toolbox enhancements

Topic 2: MATLAB® for Analyzing and Visualizing Geospatial Data

Accessing and visualizing data is a critical requirement for researchers trying to gain information about and insight from earthquakes. However, sometimes just connecting to and processing the data to prepare it for visualization and analysis can result in large hurdles and time sinks.

MATLAB has many capabilities for working with and visualizing data, including multiple new features that make handling and viewing geospatial data much easier and require much less coding. 

During this talk, I, a geophysicist by training and a MATLAB expert by day, will use MATLAB to demonstrate two different earthquake case studies. 



  • Access geospatial data from public sources 

  • Display web map data with layers superposed using the Mapping Toolbox

  • Work with big data

  • Reproduce and compare to results of previous research in the field

  • Speed up your MATLAB code with parallel and GPU computing using the Parallel Computing Toolbox, including accessing HPC resources at your site

  • Use the new MATLAB 2014b features, such as the new graphics system, date-times, and moreIn addition, I will show you how to find resources within the MATLAB, IRIS, and related seismic, geodetic, and broader geoscience communities, including where to get 

  • Sample code, such as irisfetch.m, 

  • Case studies 

  • Technical answers from the MATLAB geoscience community, and

  • Webinars, videos and product information for learning more about MATLAB capabilities


15.15 – 16.00
MATLAB: Tips and Tricks
15.00 – 15.15
15 minutes break
13.45 – 15.00
Workshop - Classification App
13.00 – 13.45
Feature extraction and feature selection
12.00 – 13.00
Lunch Break
10.30 – 12.00
Machine Learning and Classification App
10.15 – 10.30
15 minutes break
09.30 – 10.15
Introduction to Machine Learning and Regression App
09.00 – 09.30