Tech Talk 14 - May 17th 2018

Guest Speakers and subjects:

Tai Donovan, Robotics Director, American Heritage School - Watch Recording
High School Autonomous Agricultural Project

A group of 5-6 Students are working on an autonomous agricultural project with the goal of providing time sensitive data to the owner-operator/farmer/grower of a production farm. There are multiple challenges that will be addressed during the course of the project:
- Creating a robotics chassis that will be able to traverse the farmland and navigate autonomously.
- Collect data from the environment. (air temp, humidity, soil temp, and other environmental factor)
- Collect soil samples. The intention is to collect soil samples and label them for later analysis
- Collect Aerial Data. A drone will be employed to survey the land with use of NDVI cameras to help indicate the health of vegetation. When near infrared hits the leaf of a healthy plant it is reflected back into the atmosphere. As the amount of chlorophyll produced in a plant decreases, less near infrared light is reflected. This can be used to see the overall health of a crop.
Find out more about this project: https://support.dronedeploy.com/docs/ndvi-cameras-for-drones

Taiowa Donovan graduated with a B.S. in Early and Secondary Science Education from The State University of New York at Cortland and studied abroad at the London Metropolitan University, focusing on exceptional education, the British education system and teaching the inner city child. His teaching experience includes the George Junior Republic School; the Advent School in Boca Raton, where he taught science and served as Science Department Chair; and LeadAmerica in Boca Raton where he was the Director of the Engineering and Robotics program, helping to design the curriculum and manage the teaching staff. Mr. Donovan is currently the American Heritage Robotics Program Director at the Boca/Delray campus, as well as the FIRST Robotics Competition Team Coach and Founding Mentor.
Lorraine Chapman, Consulting Business Analyst, LexisNexis Risk Solutions Group - Watch Recording
Meet our summer interns

By the end of 2018, ten students will have completed projects as part of the HPCC Systems intern program. Find out about these students, including where and what they are studying, the projects they will be working on and the intern experience we provide to help them feel part of the team. Lorraine will also speak about how you can get involved with the program by being a mentor, or contributing a project idea for a new feature or enhancement to the HPCC Systems platform and/or Machine Learning Library.

Lorraine runs the HPCC Systems summer intern program. She also managed our involvement with Google Summer of Code (GSoC) in 2015, which prompted us to start our own student intern program in the same year. That year 2 students joined as a result of the GSoC program and 4 others became the first students to join our intern program, which has since flourished and is now entering its 4th year. Lorraine also works alongside the HPCC Systems platform team assisting with the release management process and acting as an interface between the developers and our open source community. She is an active blogger on the HPCC Systems website and manages various wiki's designed to help our users get the information they need about the HPCC Systems platform, new releases and features as well as the HPCC Systems Red Book, which provides workarounds and tips for easier adoption of new releases. She also contributes to the issue tracking and management process, acting as an advocate for users who are interested in specific features and fixes.
Richard Taylor, Chief Trainer, HPCC Systems, LexisNexis Risk Solutions Group - Watch Recording
ECL Tips and Cool Tricks - Current/Longest Event Sequence by Month

Richard will discuss processing event dates to discover for each event within a given time frame: the current number of sequential months the event occurred, and the longest contiguous month-by-month sequence. This topic is based on questions from one of our Statistical Modelers (new to ECL) regarding how to approach the problem in a non-procedural manner. The example code will make use of the GROUP and HAVING functions.