Difference between revisions of "Training"

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(→‎Local and Timetable: Na sessão de Novembro de 2019, as aulas terminam às 16h30.)
 
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The course will take place twice a year at IST / Alameda campus during Spring and Fall. Classes will take place at Room 7 (pending confirmation), North Garden Pavilion.
 
The course will take place twice a year at IST / Alameda campus during Spring and Fall. Classes will take place at Room 7 (pending confirmation), North Garden Pavilion.
  
<strong> Spring  2018: 19 to 23 March </strong>
+
<!--
 +
<strong> Spring  2019: 18 to 22 March </strong>
 
 
 
{| border="1" style="text-align: center;"
 
{| border="1" style="text-align: center;"
|+ March 2018 Course Timetable
+
|+ March 2019 Course Timetable
 
|-
 
|-
 
! scope="col" | Time
 
! scope="col" | Time
! scope="col" | Monday 19/3<br />  
+
! scope="col" | Monday 18/3<br />  
! scope="col" | Tuesday 20/3<br />  
+
! scope="col" | Tuesday 19/3<br />  
! scope="col" | Wednesday 21/3<br />  
+
! scope="col" | Wednesday 20/3<br />  
! scope="col" | Thursday 22/3<br />  
+
! scope="col" | Thursday 21/3<br />  
! scope="col" | Friday 23/3<br />  
+
! scope="col" | Friday 22/3<br />  
 
|-
 
|-
 
|9h30
 
|9h30
Line 60: Line 61:
 
|Introduction to e-lab
 
|Introduction to e-lab
 
H. Fernandes
 
H. Fernandes
|Plasma probes <br />
+
|Python Lab
 
J. Loureiro
 
J. Loureiro
|Behind the scene
+
|e-lab data processing<br />
???
+
A. Duarte
|The e-lab framework<br />  
+
|The e-lab framework
R. Neto
 
|Commercial available sensors<br />
 
 
R. Neto
 
R. Neto
 +
|Presentations - TBD
 +
H. Fernandes
  
 
|-
 
|-
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12h30
 
12h30
 
|Fitteia – an on-line data fitting  
 
|Fitteia – an on-line data fitting  
P. Sebastião
+
M. Beira
|Data Analysis I - Python
+
|Data analysis
L. Gil
+
B. Carvalho
|Data analysis II
+
|Behind the scene
C. Silva
+
M. Santos
 
|IoT - Smart Devices
 
|IoT - Smart Devices
J. Fortunato
+
F. Carrola & M. Santos
|Presentations evaluation<br />  
+
| Presentations <br />  
 
H. Fernandes
 
H. Fernandes
 
|-
 
|-
Line 93: Line 94:
 
16h
 
16h
 
|Applied e-lab experience:<br />  
 
|Applied e-lab experience:<br />  
J. Fortunato<br />
+
A. Duarte<br />  
R. Santos<br />  
+
|Python Lab
|Advanced data fittings<br />
+
J. Loureiro & A. Duarte
A. Duarte
 
 
|e-lab data processing
 
|e-lab data processing
J. Oliveira <br />
+
R. Cardoso<br />
|Presentations elaboration<br />
+
|Presentations elaboration<br />  
M. Santos
+
M. Santos <br />
|Presentation evaluation
+
|Presentations<br />
 
H. Fernandes
 
H. Fernandes
 
|-
 
|-
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18h
 
18h
 
|Applied e-lab experience:<br />
 
|Applied e-lab experience:<br />
R. Santos<br />
+
R. Cardoso<br />
M. Santos<br />
+
D. Neto<br />
|e-lab data processing <br />  
+
|Advanced data fittings <br />  
 
A. Duarte<br />  
 
A. Duarte<br />  
 
|IST Visit  
 
|IST Visit  
|Presentations elaboration<br />
+
|Rehearsal
M. Santos <br />
+
--
 
|**\/**
 
|**\/**
 
|-
 
|-
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!Course ends
 
!Course ends
 
|}
 
|}
 +
-->
  
<!-- <strong> Fall 2017: 13 to 17 November </strong>
+
<strong> Fall 2019: 18-22 November</strong>
  
 
{| border="1" style="text-align: center;"
 
{| border="1" style="text-align: center;"
|+ November 2017 Course Timetable
+
|+ November 2019 Course Timetable
 
|-
 
|-
 
! scope="col" | Time
 
! scope="col" | Time
! scope="col" | Monday, 13<br />  
+
! scope="col" | Monday 18/11<br />  
! scope="col" | Tuesday, 14<br />  
+
! scope="col" | Tuesday 19/11<br />  
! scope="col" | Wednesday, 15<br />  
+
! scope="col" | Wednesday 20/11<br />  
! scope="col" | Thursday, 16<br />  
+
! scope="col" | Thursday 21/11<br />  
! scope="col" | Friday, 17<br />  
+
! scope="col" | Friday 22/11<br />  
 
|-
 
|-
 
|9h30
 
|9h30
Line 140: Line 141:
 
|Introduction to e-lab
 
|Introduction to e-lab
 
H. Fernandes
 
H. Fernandes
|Plasma probes <br />
+
|Data analysis
J. Loureiro
+
R. Coelho
|The e-lab framework
+
|e-lab data processing<br />
R. Neto
+
A. Duarte
|Commercial available sensors<br />  
+
|Presentations elaboration<br />
R. Neto
+
D. Neto
|Presentation evaluation
+
|Presentations - TBD
 
H. Fernandes
 
H. Fernandes
 +
 
|-
 
|-
 
|11h
 
|11h
 
12h30
 
12h30
 
|Fitteia – an on-line data fitting  
 
|Fitteia – an on-line data fitting  
P. Sebastião
+
M. Beira
|Applied e-lab experience:<br />
+
|Python Lab
Langmuir probe<br /> 
+
B. Carvalho
J. Loureiro
+
|Behind the scene
|Advanced data fittings<br />
+
M. Santos
A. Duarte
+
|IoT - Smart Devices
|Behind the scene<br />
+
F. Carrola
J. Fortunato
+
| Presentations <br />  
|Presentations evaluation<br />  
 
 
H. Fernandes
 
H. Fernandes
 
|-
 
|-
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|-
 
|-
 
|14h
 
|14h
16h
+
16h30
|Data analysis I
+
|Applied e-lab experience:<br />
B. Carvalho
+
A. Duarte<br />
|Data analysis II
+
|Python Lab
A. Duarte
+
R. Cardoso
 
|e-lab data processing
 
|e-lab data processing
A. Duarte <br />  
+
R. Cardoso<br />
|Presentations elaboration
+
|Presentations elaboration<br />
J. Lopes
+
M. Santos <br />
|Presentation evaluation
+
|Presentations<br />
 
H. Fernandes
 
H. Fernandes
|-
 
|16h
 
17h30
 
|Applied e-lab experience:
 
Colisione<br />
 
Inertia momentum<br />
 
J. Loureiro <br />
 
|e-lab data processing <br />
 
J. Loureiro<br />
 
|e-lab Visit
 
J. Fortunato
 
|Presentations elaboration<br />
 
J. Lopes
 
|**\/**
 
 
|-
 
|-
|17h30
+
|16h30
 
!Adjourn
 
!Adjourn
 
!Adjourn
 
!Adjourn
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!Adjourn
 
!Adjourn
 
!Course ends
 
!Course ends
|}  
+
|}
-->
 
  
 
==Instructors==
 
==Instructors==
 
André Duarte<br/>
 
André Duarte<br/>
<!--Bernardo Carvalho <br/>-->
+
Bernardo Carvalho <br/>
Carlos Silva<br/>
+
<!--Carlos Silva<br/>-->
 
Horácio Fernandes<br/>
 
Horácio Fernandes<br/>
João Fortunato<br/>
+
<!--João Loureiro<br/>-->
João Loureiro<br/>
+
Francisco Carrola<br/>
<!--Josué Lopes<br/>-->
 
Luís Gil<br/>
 
 
Manuel Santos<br/>
 
Manuel Santos<br/>
 
Pedro Lourenço<br/>
 
Pedro Lourenço<br/>
 
Pedro Sebastião<br/>
 
Pedro Sebastião<br/>
<!--Ruben Marques<br/>-->
+
Maria Beira<br/>
<!--Rui Coelho<br/>-->
+
Ruben Cardoso<br/>
<!--Rui Figueiredo<br/>-->
+
Rui Coelho<br/>
 
Rui Neto<br/>
 
Rui Neto<br/>
<!--Samuel Balula<br/>-->
+
David Neto<br/>
<!--Fabian Chavez<br/>-->
+
Luis Gil<br/>
 +
Maria Beira<br/>

Latest revision as of 15:26, 19 November 2019

Athens Programme

At IST it is offered some training courses where you can learn more about e-lab in a college environment. If you are an european student, you can apply to come for one week to Lisbon and follow the Athens course.

Please have a look at the ATHENS Programme courseware list under IST6 or check IST ATHENS site.

Hoping to see you in Lisbon.

Objectives

This course is intended to provide to students all the knowledge in how to execute experiments in the e-lab laboratory and to use several techniques and software tools to analyze and process the acquired data.

It is expected that students will acquired basic skills in Octave or MatLab, namely FFT, SVD (singular value decomposition) and advanced fitting techniques. This will be a 1-week course organized within the ATHENS programme.

At the end of the course the students should know:

(i) Run and acquire data from a remote experiment; (ii) Handle data and do their data analysis; (iii) How video is broadcast through a multicast unit; (iv) Understand how a physic apparatus could be converted in a remote laboratory.

We are promoting thematic experiments such as Plasma Physics, energy conservation and others.

The course has a total duration of 35 hours divided in 4 major blocks. Theoretical classes will be laboratory oriented as most of the course will be practice. Some topics will be given as seminars.

Programme to be followed

The syllabus covers the following topics:

  • Remote controlled laboratories (RCL) in context;
  • Introduction to e-lab and available experiments;
  • Data fitting and analysis tool;
  • The physics behind each experiment: an applied e-lab experience
  • Introduction to data analysis (FFT, SVD and advanced data fittings);
  • Transducers and sensors behind RCLs;
  • Experiments automation;
  • Impact of video broadcast.

Classes are imminently practical as the assessment, consisting on the exploitation of several remote physical apparatus and interpretation the data through data modelling.

Assessment

The student’s assessment consists in two different tasks:

(i) Each group of two students shall do a presentation based on an experimental chosen apparatus, and show how the apparatus works, how to gather data and study all the data analysis and processing done based on the acquired data.

(ii) Also each group of two students shall choose another experimental apparatus and produce a media content that they find relevant and interesting for that experiment, which can be included in an online wiki-style site.

Local and Timetable

The course will take place twice a year at IST / Alameda campus during Spring and Fall. Classes will take place at Room 7 (pending confirmation), North Garden Pavilion.


Fall 2019: 18-22 November

November 2019 Course Timetable
Time Monday 18/11
Tuesday 19/11
Wednesday 20/11
Thursday 21/11
Friday 22/11
9h30

11h

Introduction to e-lab

H. Fernandes

Data analysis

R. Coelho

e-lab data processing

A. Duarte

Presentations elaboration

D. Neto

Presentations - TBD

H. Fernandes

11h

12h30

Fitteia – an on-line data fitting

M. Beira

Python Lab

B. Carvalho

Behind the scene

M. Santos

IoT - Smart Devices

F. Carrola

Presentations

H. Fernandes

12h30 Lunch Lunch Lunch Lunch Lunch
14h

16h30

Applied e-lab experience:

A. Duarte

Python Lab

R. Cardoso

e-lab data processing

R. Cardoso

Presentations elaboration

M. Santos

Presentations

H. Fernandes

16h30 Adjourn Adjourn Adjourn Adjourn Course ends

Instructors

André Duarte
Bernardo Carvalho
Horácio Fernandes
Francisco Carrola
Manuel Santos
Pedro Lourenço
Pedro Sebastião
Maria Beira
Ruben Cardoso
Rui Coelho
Rui Neto
David Neto
Luis Gil
Maria Beira