Workshop in Computer Science: Smart
Agents & Physiological Monitoring
סדנה במדעי המחשב:
סוכנים
חכמים
במערכות מידע
ניטור
פיזיולוגי
0368-3500-46, Autumn 2013-14
Tuesday
13-15, Orenstein 110
Prof.
Nathan Intrator & Mr. Eddie Aronovich
Contact info
Nathan Intrator nin@post.tau.ac.il 03
640 7598
Eddie Aronovich eddiea@cs.tau.ac.il
03 640 6915
The workshop will include two main
topics:
·
Smart web agents and big data mining
·
Physiological monitoring
There are several goals for the
workshop:
·
Learn a new topic and be able to program novel
functions often assimilating a number of different modalities.
·
Learn to work on a project from design to validation,
writing documentation and presentation.
·
Learn to work as a team, synchronizing work
with another team member and collaborating.
·
Learn to consider all aspects of a project,
from defining the customers, their needs potential solutions and some business
aspects.
Students should assume that each such
project is a potential seed of a startup and focus on that in their final
presentation.
A key feature of the workshop is to
learn how to present your ideas: What is best to present, and how to do it in
the most concise, clear and persuasive manner.
Therefore, there will be emphasis on
the lectures of week 4-5 and week 12-13 where each group will be presenting to
the rest of the groups. Participations of all groups in the presentations of
the other groups is mandatory.
The grade will mostly be determined on
the quality of these two presentations and the ability to present them (so you
should rehearse and make sure they go smooth).
The presentations can be given in Hebrew, but the slides should be in
English.
Each PowerPoint presentation will be
accompanied with a Word document and code.
Code should be self-explanatory (lots
of comments) and in the smallest amount of files (preferably a single file with
multiple functions).
All presentation material will be
uploaded on a web page. One group will take upon themselves to be in charge of
the web page.
Participants of the workshop will
develop applications that utilize
·
Web crawlers.
·
Social networks API: Facebook, Google+,
Linkedin, Twitter (Youtube, flicker).
·
Extraction of data from web sources such as
NASDAQ, various government and research institutes (some will require
development of parser etc).
·
Text Analysis: parsing, sentiment analysis,
key words extraction etc.
·
Clustering and indexing methods.
·
Fast search tools.
·
Parallel processing e.g. Hadoop or Condor.
·
There may be a project in data collection and
analysis of physiological measurements
·
Medical and life-style monitoring applications
·
Psychophysical experiments and data collection
·
Attention and understanding monitoring during
e-learning
(Of course, not all groups will deal
with all above tools)
A good starting point for technical
reading is the Wikipedia page on Text mining
For some administrative general ideas,
see last
year’s workshop
Time line
·
Week 1-3: frontal lectures, brief review on
some tools
·
Week 2-3: splitting into groups and choosing a
topic
·
Week 4-5: Design review presentations
·
Week 8-9: Mid project progress
·
Week 12-13: Final Presentations
The projects will be based on the
individual background of each participant and will thus, vary in nature.
Projects will have an emphasis either on programming (Matlab, Java, C, Python,
etc) or will be more emphasizing the data mining aspect.
The projects will be done mainly in
couples and in rare cases in triples.
Each of the participants will be assigned a specific part and in the
first presentation, each will present their expected part in the project.
There is room to combine a project on
building a presentation that is optimized for a cell phone – Iphone (IOS),
Android, Windows-8 etc.
Design Review
·
15 min presentation for each group. All have to
participate
·
Problem description (The problem you are going
to solve)
·
Problem background: Size, severity, who are
the consumers and who is going to pay for your solution (how will you make
money out of your solution)
·
Current solution
·
Your solution (From the view point of the user
and the payer (in case these are different)
o
General Overview on your approach
o
The GUI the user see (data description
and screen information)
o
The data you will use
o
The algorithm
o
The code you need to write – describe the
off-the-shelf code and what you need to do to make this work. Other things you need to do, e.g. collect
data, obtain devices etc.
o
3 Milestones for the next 8 weeks (who does
what and when)
This Semester Projects
1.
Gal Arnon
& Ynon Flum – Heart rate monitoring using MIO Alpha & Android
a.
Literature:
heart rate monitoring, HRV, MIO Alpha, BLE Android communication &
programing
b.
Communicate
with mio-alpha (pairing) and read continuous data, address disconnections
c.
Implement
two (or more) algorithms from the literature for HRV (including adaptation)
d.
GUI
for sleep and for workout and alerts via sms and email to designated users
2.
Ram Kalendarev & Sergei + Sergey Panchenko -- SMI
eye tracker – facial (and other objects) familiarity: recognition vs. confusion
a.
Literature:
EEG in general, P300, face detection, EYE Tracker, BT,
b.
Code
for connecting the BT EEG to a PC
c.
Code for
connecting the EYE tracker to a PC
d.
Based
on the eye tracker, detect when a person
is looking at a face (or other object)
e.
At
that point analyze the EEG (row +
Processed) and obtain an output
3.
Ariel Bronner Ron Kirill Nataly
a.
-- Analysis
of music (MIDI) tag (cluster) via accord changes, comparison with human
clustering
b.
-- Electronic
trading : dynamic combination of technical experts for better prediction and
trend detection.
4.
Yuval Sarna
Saimon Michelson -- Sentiment analysis
on twits for market prediction.
5.
Nadine Farah & Hanen
Rashed
Suggested projects
Medical and Life-style - codes will be in python this year
1.
Attention during computer games
2.
Check this movie about attention while viewing
images: Paul Sajda
3.
Attention monitoring during e-learning
4.
Mobile EEG monitor – mobile side
a.
Real-time analysis of the quality of electrode
contact and 50/60Hz noise
b.
Quick reconnection of the BT after failure
(range problem)
c.
Easy acquisition
d.
Data analysis and feature detection
e.
Emphasis on slick GUI and neuro feedback
f.
Info emanation (sms etc)
5.
Mobile EEG and Pulse Monitor – Server side
a.
Enable packet sending off information to a
server
b.
Packets can be sent every second, every minute
of every 5 min.
c.
GUI on the server side with feature alerts
6.
EEG + Pulse + temperature + skin conductance +
accelerometer life style monitor
a.
Students can suggest ways to use this monitor
7.
Code for supporting two BT devices at the same
time
Big Data - Analytics
8.
Analyze earthquake data
a.
Code in python to replace the Matlab
b.
Code to download off line from iris.edu
9.
General Sentiment Analysis tool
a.
A general tool receiving a list of site to
extract information from
b.
A list of words to monitor, phrases, sentiment
c.
Produce easy to interpret graphical
representation
d.
Enable clustering of text based on contents,
sentiment
e.
Should be able to provide similar results to
the ones in the article
when given the right data base and keywords
f.
Should be
able to extract important words and associations
10.Analyze the social protest ("מחאה
חברתית") messages
exchange.
a.
Clicks in top management and boards of
Directors of public Companies.
11.A collection of projects around smart agents,
for example an agent that reserves place in a restaurant, based on your
preferences
12.Financial data: Volatility estimation
between periods. This project requires collecting and analyzing the volatility
and predicting the value of some indexes in the long run and in the short run.
It requires some statistical background.
Sensors
·
BlueTooth + A/D Roving
Networks (For the EEG sensor)
·
BlueTooth + A/D KC Wirefree (For EEG) (old KC-5100) User guide
firmware
·
EMANT380
Bluetooth DAQ (24Bit) for various applications
Examples
·
Heart rate Mio
Alpha
· NBT SMI Eye tracker
Lecture material
Slides about Unix
Tools Article on Data Mining (Oded
Netzer) TF-IDF
Good design and development practice
The following scheme suggests the right order and the necessary
steps required to obtain a good product or functioning unit. The process always
starts with understanding user needs. Too often the wrong problems are solved
and the wrong needs are addressed. The rest is self-explanatory. Please pay attention to each block in your
intermediate and final reports.
Free code
http://www.rocketdownload.com/freeware.php?q=arrhythmias+ecg