| author | Madhusudan.C.S <madhusudancs@gmail.com> |
| Thu, 09 Dec 2010 20:24:32 +0530 | |
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{% extends "base.html" %}
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{% block content %}
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<h1 class="title">SciPy.in 2010 Conference Schedule</h1> |
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<h2 id="sec-1">Day 1 </h2> |
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<table border="2" cellspacing="0" cellpadding="6" rules="groups" frame="hsides"> |
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<caption></caption> |
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<colgroup><col class="right" /><col class="left" /><col class="left" /> |
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</colgroup> |
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<thead> |
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<tr><th scope="col" class="right">Time</th><th scope="col" class="left">Speaker</th><th scope="col" class="left">Title</th></tr> |
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</thead> |
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<tbody> |
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<tr><td class="right">09:00-09:30</td><td class="left"></td><td class="left">Inauguration</td></tr> |
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<tr><td class="right">09:30-10:30</td><td class="left">Perry Greenfield</td><td class="left"><b>Keynote</b>: <a href="#sec-3_1">How Python Slithered into Astronomy</a></td></tr> |
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<tr><td class="right">10:30-10:45</td><td class="left"></td><td class="left">Tea Break</td></tr> |
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<tr><td class="right">10:45-11:30</td><td class="left">Fernando Perez</td><td class="left"><b>Special Talk</b>: <a href="#sec-3_2">IPython : Beyond the Simple Shell</a></td></tr> |
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<tr><td class="right">11:30-11:50</td><td class="left">Farhat Habib</td><td class="left"><a href="#sec-4_1">Python as a Platform for Scientific Computing Literacy for 10+2 Students: Weighing the Balance</a></td></tr> |
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<tr><td class="right">11:50-12:10</td><td class="left">Jayesh Gandhi</td><td class="left"><a href="#sec-4_14">Microcontroller experiment and its simulation using Python</a></td></tr> |
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<tr><td class="right">12:10-12:40</td><td class="left">Vaidhy Mayilrangam</td><td class="left"><a href="#sec-4_17">Natural Language Processing Using Python</a></td></tr> |
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<tr><td class="right">12:40-13:10</td><td class="left">Georges Khaznadar</td><td class="left"><a href="#sec-4_10">Live media for training in experimental sciences</a></td></tr> |
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<tr><td class="right">13:10-14:10</td><td class="left"></td><td class="left">Lunch</td></tr> |
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<tr><td class="right">14:10-14:20</td><td class="left">Shubham Chakraborty</td><td class="left"><a href="#sec-4_11">Use of Python and Phoenix-M interface in Robotics</a></td></tr> |
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<tr><td class="right">14:20-14:30</td><td class="left">Erroju Rama Krishna</td><td class="left"><a href="#sec-4_8">Simplified and effective Network Simulation using ns-3</a></td></tr> |
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<tr><td class="right">14:30-14:40</td><td class="left"></td><td class="left">More Lightning Talks</td></tr> |
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<tr><td class="right">14:40-15:10</td><td class="left">Asokan Pichai</td><td class="left"><b>Invited Talk</b>: <a href="#sec-3_3">Teaching Programming with Python</a></td></tr> |
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<tr><td class="right">15:10-15:30</td><td class="left">Hemanth Chandran</td><td class="left"><a href="#sec-4_19">Performance Evaluation of HYBRID MAC for 802.11ad: Next Generation Multi-Gbps Wi-Fi using SimPy</a></td></tr> |
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<tr><td class="right">15:30-15:50</td><td class="left">Karthikeyan selvaraj</td><td class="left"><a href="#sec-4_9">PyCenter</a></td></tr> |
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<tr><td class="right">15:50-16:10</td><td class="left"></td><td class="left">Tea Break</td></tr> |
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<tr><td class="right">16:10-16:40</td><td class="left">Satrajit Ghosh</td><td class="left"><b>Invited Talk</b>: <a href="#sec-3_6">Nipype: Opensource platform for unified and replicable interaction with existing neuroimaging tools</a></td></tr> |
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<tr><td class="right">16:40-17:00</td><td class="left">Nek Sharan</td><td class="left"><a href="#sec-4_7">Parallel Computation of Axisymmetric Jets</a></td></tr> |
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<tr><td class="right">17:00-17:20</td><td class="left">pankaj pandey</td><td class="left"><a href="#sec-4_20">PySPH: Smooth Particle Hydrodynamics with Python</a></td></tr> |
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</tbody> |
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</table> |
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<h2 id="sec-2">Day 2 </h2> |
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<table border="2" cellspacing="0" cellpadding="6" rules="groups" frame="hsides"> |
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<caption></caption> |
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<colgroup><col class="right" /><col class="left" /><col class="left" /> |
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</colgroup> |
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<thead> |
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<tr><th scope="col" class="right">Time</th><th scope="col" class="left">Speaker</th><th scope="col" class="left">Title</th></tr> |
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</thead> |
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<tr><td class="right">09:00-10:00</td><td class="left">John Hunter</td><td class="left"><b>Special Talk</b>: <a href="#sec-3_4">matplotlib: Beyond the simple plot</a></td></tr> |
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<tr><td class="right">10:00-10:45</td><td class="left">Prabhu Ramachandran</td><td class="left"><b>Invited Talk</b>: <a href="#sec-3_5">Mayavi : Bringing Data to Life</a></td></tr> |
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<tr><td class="right">10:45-11:00</td><td class="left"></td><td class="left">Tea</td></tr> |
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<tr><td class="right">11:00-11:45</td><td class="left">Stéfan van der Walt</td><td class="left"><b>Invited Talk</b>: <a href="#sec-3_7">In Pursuit of a Pythonic PhD</a></td></tr> |
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<tr><td class="right">11:45-12:15</td><td class="left">Dharhas Pothina</td><td class="left"><a href="#sec-4_6">HyPy & HydroPic: Using python to analyze hydrographic survey data</a></td></tr> |
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<tr><td class="right">12:15-12:35</td><td class="left">Prashant Agrawal</td><td class="left"><a href="#sec-4_18">A Parallel 3D Flow Solver in Python Based on Vortex Methods</a></td></tr> |
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<tr><td class="right">12:35-13:05</td><td class="left">Ajith Kumar</td><td class="left"><a href="#sec-4_12">Python in Science Experiments using Phoenix</a></td></tr> |
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<tr><td class="right">13:05-14:05</td><td class="left"></td><td class="left">Lunch</td></tr> |
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<tr><td class="right">14:05-14:15</td><td class="left">Arun C. H.</td><td class="left"><a href="#sec-4_2">Usb Connectivity Using Python</a></td></tr> |
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<tr><td class="right">14:15-14:25</td><td class="left">Arun C. H.</td><td class="left"><a href="#sec-4_3">Automation of an Optical Spectrometer</a></td></tr> |
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<tr><td class="right">14:25-14:35</td><td class="left"></td><td class="left">More Lightning Talks</td></tr> |
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<tr><td class="right">14:35-14:55</td><td class="left">Krishnakant Mane</td><td class="left"><a href="#sec-4_22">Convincing Universities to include Python</a></td></tr> |
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<tr><td class="right">14:55-15:15</td><td class="left">Shantanu Choudhary</td><td class="left"><a href="#sec-4_4">"Python" Swiss army knife for Prototyping, Research and Fun.</a></td></tr> |
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<tr><td class="right">15:15-15:35</td><td class="left">Puneeth Chaganti</td><td class="left"><a href="#sec-4_21">Pictures, Songs and Python</a></td></tr> |
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<tr><td class="right">15:35-15:55</td><td class="left">Hrishikesh Deshpande</td><td class="left"><a href="#sec-4_5">Wavelet based denoising of ECG using Python</a></td></tr> |
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<tr><td class="right">15:55-16:10</td><td class="left"></td><td class="left">Tea-Break</td></tr> |
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<tr><td class="right">16:10-16:40</td><td class="left">Jarrod Millman</td><td class="left"><b>Invited Talk</b></td></tr> |
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<tr><td class="right">16:40-17:00</td><td class="left">Ramakrishna Reddy Yekulla</td><td class="left"><a href="#sec-4_13">Building and Packaging your Scientific Python Application For Linux Distributions</a></td></tr> |
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<tr><td class="right">17:00-17:20</td><td class="left">Yogesh Karpate</td><td class="left"><a href="#sec-4_16">Automatic Proteomic Finger Printing using Scipy</a></td></tr> |
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<tr><td class="right">17:20-17:40</td><td class="left">Manjusha Joshi</td><td class="left"><a href="#sec-4_15">SAGE for Scientific computing and Education enhancement</a></td></tr> |
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<tr><td class="right">To be scheduled</td><td class="left">Karuna and/or Mangala</td><td class="left"><a href="#sec-4_23">Python based Galaxy workflow integration on GARUDA Grid</a></td></tr> |
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</tbody> |
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</table> |
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<p>Perry Greenfield |
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</p> |
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<h4 id="sec-3_1_1">Talk/Paper Abstract </h4> |
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<p>I will talk about how Python was used to solve our problems for |
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the Hubble Space Telescope. From humble beginnings as a glue |
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element for our legacy software, it has become a cornerstone of |
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our scientific software for HST and the next large space |
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telescope, the James Webb Space Telescope, as well as many other |
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astronomy projects. The talk will also cover some of the history |
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of essential elements for scientific Python and where future |
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work is needed, and why Python is so well suited for scientific |
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software. |
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</p> |
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<h3 id="sec-3_2">IPython : Beyond the Simple Shell </h3> |
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<p>Fernando Perez |
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</p> |
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<p>IPython is a widely used system for interactive computing in |
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Python that extends the capabilities of the Python shell with |
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operating system access, powerful object introspection, |
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customizable "magic" commands and many more features. It also |
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contains a set of tools to control parallel computations via |
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high-level interfaces that can be used either interactively or |
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in long-running batch mode. In this talk I will outline some of |
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the main features of IPython as it has been widely adopted by |
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the scientific Python user base, and will then focus on recent |
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developments. Using the high performance ZeroMQ networking |
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library, we have recently restructured IPython to decouple the |
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kernel executing user code from the control interface. This |
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allows us to expose multiple clients with different |
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capabilities, including a terminal-based one, a rich Qt client |
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and a web-based one with full matplotlib support. In conjunction |
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with the new HTML5 matplotlib backend, this architecture opens |
|
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the door for a rich web-based environment for interactive, |
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collaborative and parallel computing. There is much interesting |
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development to be done on this front, and I hope to encourage |
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participants at the sprints during the conference to join this |
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effort. |
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</p> |
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<h3 id="sec-3_3">Teaching Programming with Python </h3> |
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<p>Asokan Pichai |
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</p> |
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<h4 id="sec-3_3_1">Talk/Paper Abstract </h4> |
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<p>As a trainer I have been engaged a lot for teaching fresh |
166 |
Software Engineers and software job aspirants. Before starting |
|
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on the language, platform specific areas I teach a part I refer |
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to as Problem Solving and Programming Logic. I have used Python |
|
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for this portion of training in the last 12+years. In this talk |
|
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I wish to share my experiences and approaches. This talk is |
|
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intended at Teachers, Trainers, Python Evangelists, and HR |
|
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Managers [if they lose their way and miraculously find |
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themselves in SciPy :-)] |
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</p> |
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<h3 id="sec-3_4">matplotlib: Beyond the simple plot </h3> |
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<p>John Hunter |
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</p> |
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| 281 | 189 |
<h4 id="sec-3_4_1">Talk/Paper Abstract </h4> |
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| 281 | 192 |
<p>matplotlib, a python package for making sophisticated |
193 |
publication quality 2D graphics, and some 3D, has long supported |
|
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a wide variety of basic plotting types such line graphs, bar |
|
195 |
charts, images, spectral plots, and more. In this talk, we will |
|
196 |
look at some of the new features and performance enhancements in |
|
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matplotlib as well as some of the comparatively undiscovered |
|
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features such as interacting with your data and graphics, and |
|
199 |
animating plot elements with the new animations API. We will |
|
200 |
explore the performance with large datasets utilizing the new |
|
201 |
path simplification algorithm, and discuss areas where |
|
202 |
performance improvements are still needed. Finally, we will |
|
203 |
demonstrate the new HTML5 backend, which in combination with the |
|
204 |
new HTML5 IPython front-end under development, will enable an |
|
205 |
interactive Python shell with interactive graphics in a web |
|
206 |
browser. |
|
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</p> |
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<h3 id="sec-3_5">Mayavi : Bringing Data to Life </h3> |
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215 |
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216 |
<p>Prabhu Ramachandran |
|
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217 |
</p> |
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| 281 | 219 |
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<h4 id="sec-3_5_1">Talk/Paper Abstract </h4> |
|
222 |
||
223 |
||
224 |
<p>Mayavi is a powerful 3D plotting package implemented in |
|
225 |
Python. It includes both a standalone user interface along with |
|
226 |
a powerful yet simple scripting interface. The key feature of |
|
227 |
Mayavi though is that it allows a Python user to rapidly |
|
228 |
visualize data in the form of NumPy arrays. Apart from these |
|
229 |
basic features, Mayavi has some advanced features. These |
|
230 |
include, automatic script recording, embedding into a custom |
|
231 |
user dialog and application. Mayavi can also be run in an |
|
232 |
offscreen mode and be embedded in a sage notebook |
|
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(<a href="http://www.sagemath.org">http://www.sagemath.org</a>). We will first rapidly demonstrate |
|
234 |
these key features of Mayavi. We will then discuss some of the |
|
235 |
underlying technologies like enthought.traits, traitsUI and TVTK |
|
236 |
that form the basis of Mayavi. The objective of this is to |
|
237 |
demonstrate the wide range of capabilities that both Mayavi and |
|
238 |
its underlying technologies provide the Python programmer. |
|
239 |
</p> |
|
240 |
||
241 |
||
242 |
||
243 |
||
244 |
||
245 |
<h3 id="sec-3_6">Nipype: Opensource platform for unified and replicable interaction with existing neuroimaging tools </h3> |
|
246 |
||
247 |
||
248 |
<p>Satrajit Ghosh |
|
249 |
</p> |
|
250 |
||
251 |
||
252 |
||
253 |
<h4 id="sec-3_6_1">Talk/Paper Abstract </h4> |
|
254 |
||
255 |
||
256 |
<p>Current neuroimaging software offer users an incredible |
|
257 |
opportunity to analyze their data in different ways, with |
|
258 |
different underlying assumptions. However, this has resulted in |
|
259 |
a heterogeneous collection of specialized applications without |
|
260 |
transparent interoperability or a uniform operating |
|
261 |
interface. Nipype, an open-source, community-developed |
|
262 |
initiative under the umbrella of Nipy, is a Python project that |
|
263 |
solves these issues by providing a uniform interface to existing |
|
264 |
neuroimaging software and by facilitating interaction between |
|
265 |
these packages within a single workflow. Nipype provides an |
|
266 |
environment that encourages interactive exploration of |
|
267 |
neuroimaging algorithms from different packages, eases the |
|
268 |
design of workflows within and between packages, and reduces the |
|
269 |
learning curve necessary to use different packages. Nipype is |
|
270 |
creating a collaborative platform for neuroimaging software |
|
271 |
development in a high-level language and addressing limitations |
|
272 |
of existing pipeline systems. |
|
273 |
</p> |
|
274 |
||
275 |
||
276 |
||
277 |
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278 |
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282 |
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<h3 id="sec-3_7">In Pursuit of a Pythonic PhD </h3> |
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284 |
|
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285 |
|
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286 |
<p>Stéfan van der Walt |
|
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|
287 |
</p> |
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|
288 |
|
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289 |
|
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290 |
|
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<h4 id="sec-3_7_1">Talk/Paper Abstract </h4> |
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|
292 |
|
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|
293 |
|
|
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294 |
<p>In May of 2005, I started a pilgrimage to transform myself into |
|
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diff
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|
295 |
a doctor of engineering. Little did I know, then, that my |
|
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|
296 |
journey would bring me in touch with some of the most creative, |
|
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297 |
vibrant and inspiring minds in the open source world, and that |
|
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|
298 |
an opportunity would arise to help realise their (and now my) |
|
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299 |
dream: a completely free and open environment for performing |
|
8d56bd800a81
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|
300 |
cutting edge science. In this talk, I take you on my journey, |
|
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301 |
and along the way introduce the NumPy and SciPy projects, our |
|
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302 |
community, the early days of packaging, our documentation |
|
8d56bd800a81
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|
303 |
project, the publication of conference proceedings as well as |
|
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diff
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|
304 |
work-shops and sprints around the world. I may even tell you a |
|
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diff
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bit about my PhD on super-resolution imaging! |
|
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|
306 |
</p> |
|
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|
307 |
|
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|
308 |
|
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|
309 |
|
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|
310 |
|
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|
311 |
|
| 281 | 312 |
|
313 |
<h2 id="sec-4">Submitted Talks </h2> |
|
314 |
||
315 |
||
316 |
||
317 |
||
318 |
||
319 |
||
|
338
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|
320 |
<h3 id="sec-4_1">Python as a Platform for Scientific Computing Literacy for 10+2 Students: Weighing the Balance </h3> |
| 281 | 321 |
|
322 |
||
|
338
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|
323 |
<p>Farhat Habib |
| 281 | 324 |
</p> |
325 |
||
326 |
||
327 |
||
328 |
<h4 id="sec-4_1_1">Talk/Paper Abstract </h4> |
|
329 |
||
330 |
||
|
338
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|
331 |
<p>The use of Python as a language for introducing computing is |
|
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|
332 |
becoming increasingly widespread. Here we report out findings |
|
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|
333 |
from two years of running an introduction to computing course |
|
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|
334 |
with Python as the programming language, and building upon it, |
|
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|
335 |
using SciPy as a scientific computing language in a course on |
|
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|
336 |
scientific computing. |
| 281 | 337 |
</p> |
338 |
||
|
338
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|
339 |
<p> |
|
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|
340 |
The course is designed as a general computing course for |
|
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|
341 |
introducing computing to first year undergraduate students of |
|
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|
342 |
science. We find that a large majority of our incoming students |
|
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|
343 |
have no prior exposure to programming and none of the students |
|
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|
344 |
had any exposure to Python. Thus, the design of the course is |
|
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|
345 |
such that it allows everybody to be brought up to speed with |
|
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|
346 |
general programming concepts. Later, the students will later |
|
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|
347 |
specialize in varied topics from Biology to pure Mathematics, |
|
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|
348 |
thus, the course emphasizes general computing concepts over |
|
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specialized techniques. At a second course in Scien- tific |
|
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parents:
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|
350 |
Computing numerical methods are introduced with the aid of |
|
5b0a6b71fd64
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parents:
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diff
changeset
|
351 |
Scipy. The introduction to computing course has been taught |
|
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parents:
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diff
changeset
|
352 |
twice in Fall 2009 and 2010 to batches of around 100 students |
|
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Changed schedule of Day-1 to include Farhat.
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parents:
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diff
changeset
|
353 |
each. In this paper we report our experience with teaching |
|
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Changed schedule of Day-1 to include Farhat.
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parents:
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diff
changeset
|
354 |
Python and student and faculty feedback related to the course. |
|
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diff
changeset
|
355 |
</p> |
| 281 | 356 |
|
357 |
||
358 |
||
359 |
||
360 |
||
361 |
||
|
289
91aeddac8b80
Capitalized USB CONNECTIVITY.
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diff
changeset
|
362 |
<h3 id="sec-4_2">Usb Connectivity Using Python </h3> |
| 281 | 363 |
|
364 |
||
365 |
<p>Arun C. H. |
|
366 |
</p> |
|
|
227
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diff
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|
367 |
|
| 281 | 368 |
|
369 |
||
370 |
<h4 id="sec-4_2_1">Talk/Paper Abstract </h4> |
|
371 |
||
372 |
||
373 |
<p>Host software using Python interpreter language to communicate |
|
374 |
with the USB Mass Storage class device is developed and |
|
375 |
tested. The <sub>usic18F4550</sub>.pyd module encapsulating all the |
|
376 |
functions needed to configure USB is developed. The Python |
|
377 |
extension .pyd using C/C++ functions compatible for Windows make |
|
378 |
use of SWIG, distutils and MinGW. SWIG gives the flexibility to |
|
379 |
access lower level C/C++ code through more convenient and higher |
|
380 |
level languages such as Python, Java, etc. Simplified Wrapper and |
|
381 |
Interface Generator (SWIG) is a middle interface between Python |
|
382 |
and C/C++. The purpose of the Python interface is to allow the |
|
383 |
user to initialize and configure USB through a convenient |
|
384 |
scripting layer. The module is built around libusb which can |
|
385 |
control an USB device with just a few lines. Libusb-win32 is a |
|
386 |
port of the USB library to the Windows operating system. The |
|
387 |
library allows user space applications to access any USB device on |
|
388 |
Windows in a generic way without writing any line of kernel driver |
|
389 |
code. A simple data acquisition system for measuring analog |
|
390 |
voltage, setting and reading the status of a particular pin of the |
|
391 |
micro controller is fabricated. It is interfaced to PC using USB |
|
392 |
port that confirms to library USB win32 device. The USB DAQ |
|
393 |
hardware consists of a PIC18F4550 micro-controller and the |
|
394 |
essential components needed for USB configuration. |
|
395 |
</p> |
|
396 |
||
397 |
||
398 |
||
399 |
||
400 |
||
401 |
||
402 |
||
403 |
||
404 |
<h3 id="sec-4_3">Automation of an Optical Spectrometer </h3> |
|
405 |
||
406 |
||
407 |
<p>Arun C. H. |
|
408 |
</p> |
|
409 |
||
410 |
||
411 |
||
412 |
<h4 id="sec-4_3_1">Talk/Paper Abstract </h4> |
|
413 |
||
414 |
||
415 |
<p>This paper describes the automation performed for an Optical |
|
416 |
Spectrometer in order to precisely monitor angles, change |
|
417 |
dispersing angle and hence measure wave length of light using a |
|
418 |
data logger, necessary hardware and Python. Automating instruments |
|
419 |
through programs provides great deal of power, flexibility and |
|
420 |
precision. Optical Spectrometers are devices which analyze the |
|
421 |
wave length of light, and are typically used to identify |
|
422 |
materials, and study their optical properties. A broad spectrum of |
|
423 |
light is dispersed using a grating and the dispersed light is |
|
424 |
measured using a photo transistor. The signal is processed and |
|
425 |
acquired using a data logger. Transfer of data, changing angle of |
|
426 |
diffraction are all done using the Python. The angle of |
|
427 |
diffraction is varied by rotating the detector to pick up lines |
|
428 |
using a stepper motor. The Stepper motor has 180 steps or 2 |
|
429 |
degrees per step. A resolution of 0.1 degree is achieved in the |
|
430 |
spectrometer by using the proper gear ratio. The data logger is |
|
431 |
interfaced to the computer through a serial port. The stepper |
|
432 |
motor is also interfaced to the computer through another serial |
|
433 |
port. Python is chosen here for its succinct notation and is |
|
434 |
implemented in a Linux environment. |
|
435 |
</p> |
|
436 |
||
437 |
||
438 |
||
439 |
||
440 |
||
441 |
||
442 |
||
443 |
||
444 |
<h3 id="sec-4_4">"Python" Swiss army knife for Prototyping, Research and Fun. </h3> |
|
445 |
||
446 |
||
447 |
<p>Shantanu Choudhary |
|
448 |
</p> |
|
449 |
||
450 |
||
451 |
||
452 |
<h4 id="sec-4_4_1">Talk/Paper Abstract </h4> |
|
453 |
||
454 |
||
455 |
<p>This talk would be covering usage of Python in different scenarios which helped me through my work: |
|
456 |
</p><ul> |
|
457 |
<li> |
|
458 |
Small mlab(Mayavi) scripts which helped in better understanding |
|
459 |
of problem statement. |
|
460 |
</li> |
|
461 |
<li> |
|
462 |
Python3.0 and its blender API's for writing plugins which are |
|
463 |
used for Open Source Animation movie project |
|
464 |
Tube(tube.freefac.org) |
|
465 |
</li> |
|
466 |
<li> |
|
467 |
PyOpenCL Python's interfacing for OpenCL which helped in |
|
468 |
prototyping and speed up of application. |
|
469 |
</li> |
|
470 |
</ul> |
|
471 |
||
472 |
||
473 |
||
474 |
||
475 |
||
476 |
||
477 |
||
478 |
||
479 |
<h3 id="sec-4_5">Wavelet based denoising of ECG using Python </h3> |
|
480 |
||
481 |
||
482 |
<p>Hrishikesh Deshpande |
|
|
227
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|
483 |
</p> |
|
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parents:
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diff
changeset
|
484 |
|
| 281 | 485 |
|
486 |
||
487 |
<h4 id="sec-4_5_1">Talk/Paper Abstract </h4> |
|
488 |
||
489 |
||
490 |
<p>The python module "RemNoise" is presented. It allows user to |
|
491 |
automatically denoise one-dimensional signal using wavelet |
|
492 |
transform. It also removes baseline wandering and motion |
|
493 |
artifacts. While RemNoise is developed primarily for biological |
|
494 |
signals like ECG, its design is generic enough that it should be |
|
495 |
useful to applications involving one-dimensional signals. The |
|
496 |
basic idea behind this work is to use multi-resolution property of |
|
497 |
wavelet transform that allows to study non-stationary signals in |
|
498 |
greater depth. Any signal can be decomposed into detail and |
|
499 |
approximation coefficients, which can further be decomposed into |
|
500 |
higher levels and this approach can be used to analyze the signal |
|
501 |
in time-frequency domain. The very first step in any |
|
502 |
data-processing application is to pre-process the data to make it |
|
503 |
noise-free. Removing noise using wavelet transform involves |
|
504 |
transforming the dataset into wavelet domain, zero out all |
|
505 |
transform coefficients using suitable thresholding method and |
|
506 |
reconstruct the data by taking its inverse wavelet transform. This |
|
507 |
module makes use of PyWavelets, Numpy and Matplotlib libraries in |
|
508 |
Python, and involves thresholding wavelet coefficients of the data |
|
509 |
using one of the several thresholding methods. It also allows |
|
510 |
multiplicative threshold rescaling to take into consideration |
|
511 |
detail coefficients in each level of wavelet decomposition. The |
|
512 |
user can select wavelet family and level of decompositions as |
|
513 |
required. To evaluate the module, we experimented with several |
|
514 |
complex one-dimensional signals and compared the results with |
|
515 |
equivalent procedures in MATLAB. The results showed that RemNoise |
|
516 |
is excellent module to preprocess data for noise-removal. |
|
517 |
</p> |
|
518 |
||
519 |
||
520 |
||
521 |
||
522 |
||
523 |
||
524 |
||
525 |
||
526 |
<h3 id="sec-4_6">HyPy & HydroPic: Using python to analyze hydrographic survey data </h3> |
|
527 |
||
528 |
||
529 |
<p>Dharhas Pothina |
|
530 |
</p> |
|
531 |
||
532 |
||
533 |
||
534 |
<h4 id="sec-4_6_1">Talk/Paper Abstract </h4> |
|
535 |
||
536 |
||
537 |
||
538 |
<p> |
|
539 |
The Texas Water Development Board(TWDB) collects hydrographic |
|
540 |
survey data in lakes, rivers and estuaries. The data collected |
|
541 |
includes single, dual and tri-frequency echo sounder data |
|
542 |
collected in conjunction with survey grade GPS systems. This raw |
|
543 |
data is processed to develop accurate representations of |
|
544 |
bathymetry and sedimentation in the water bodies surveyed. |
|
545 |
</p> |
|
546 |
<p> |
|
547 |
This talk provides an overview of how the Texas Water Development |
|
548 |
Board (TWDB) is using python to streamline and automate the |
|
549 |
process of converting raw hydrographic survey data to finished |
|
550 |
products that can then be used in other engineering applications |
|
551 |
such as hydrodynamic models, determining lake |
|
552 |
elevation-area-capacity relationships and sediment contour maps, |
|
553 |
etc. |
|
554 |
</p> |
|
555 |
<p> |
|
556 |
The first part of this talk will present HyPy, a python module |
|
557 |
(i.e. function library) for hydrographic survey data |
|
558 |
analysis. This module contains functions to read in data from |
|
559 |
several brands of depth sounders, conduct anisotropic |
|
560 |
interpolations along river channels, apply tidal and elevation |
|
561 |
corrections, apply corrections to boat path due to loss of GPS |
|
562 |
signals as well as a variety of convenience functions for dealing |
|
563 |
with spatial data. |
|
564 |
</p> |
|
565 |
<p> |
|
566 |
In the second part of the talk we present HydroPic, a simple |
|
567 |
Traits based application built of top of HyPy. HydroPic is |
|
568 |
designed to semi-automate the determination of sediment volume in |
|
569 |
a lake. Current techniques require the visual inspection of images |
|
570 |
of echo sounder returns along each individual profile. We show |
|
571 |
that this current methodology is slow and subject to high human |
|
572 |
variability. We present a new technique that uses computer vision |
|
573 |
edge detection algorithms available in python to semi-automate |
|
574 |
this process. HydroPic wraps these algorithms into a easy to use |
|
575 |
interface that allows efficient processing of data for an entire |
|
576 |
lake. |
|
577 |
</p> |
|
578 |
||
579 |
||
580 |
||
581 |
||
582 |
||
583 |
||
584 |
<h3 id="sec-4_7">Parallel Computation of Axisymmetric Jets </h3> |
|
585 |
||
586 |
||
587 |
<p>Nek Sharan |
|
588 |
</p> |
|
589 |
||
590 |
||
591 |
||
592 |
<h4 id="sec-4_7_1">Talk/Paper Abstract </h4> |
|
593 |
||
|
227
091f3896c5e8
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Kadambari Devarajan <kadambari.devarajan@gmail.com>
parents:
222
diff
changeset
|
594 |
|
| 281 | 595 |
<p>Flow field for imperfectly expanded jet has been simulated using |
596 |
Python for prediction of jet screech frequency. This plays an |
|
597 |
important role in the design of advanced aircraft engine nozzle, |
|
598 |
since screech could cause sonic fatigue failure. For computation, |
|
599 |
unsteady axisymmetric Navier-Stokes equation is solved using fifth |
|
600 |
order Weighted Essentially Non-Oscillatory (WENO) scheme with a |
|
601 |
subgrid scale Large-Eddy Simulation (LES) model. Smagorinsky’s |
|
602 |
eddy viscosity model is used for subgrid scale modeling with |
|
603 |
second order (Total Variation Diminishing) TVD Runge Kutta time |
|
604 |
stepping. The performance of Python code is enhanced by using |
|
605 |
different Cython constructs like declaration of variables and |
|
606 |
numpy arrays, switching off bound check and wrap around etc. Speed |
|
607 |
up obtained from these methods have been individually clocked and |
|
608 |
compared with the Python code as well as an existing in-house C |
|
609 |
code. Profiling was used to highlight and eliminate the expensive |
|
610 |
sections of the code. |
|
611 |
</p> |
|
612 |
<p> |
|
613 |
Further, both shared and distributed memory architectures have |
|
614 |
been employed for parallelization. Shared memory parallel |
|
615 |
processing is implemented through a thread based model by manual |
|
616 |
release of Global Interpreter Lock (GIL). GIL ensures safe and |
|
617 |
exclusive access of Python interpreter internals to running |
|
618 |
thread. Hence while one thread is running with GIL the other |
|
619 |
threads are put on hold until the running thread ends or is forced |
|
620 |
to wait. Therefore to run two threads simultaneously, GIL was |
|
621 |
manually released using "with nogil" statement. The relative |
|
622 |
independence of radial and axial spatial derivative computation |
|
623 |
provides an option of putting them in parallel threads. On the |
|
624 |
other hand, distributed memory parallel processing is through MPI |
|
625 |
based domain decomposition, where the domain is split radially |
|
626 |
with an interface of three grid points. Each sub-domain is |
|
627 |
delegated to a different processor and communication, in the form |
|
628 |
of message transmission, ensures update of interface grid |
|
629 |
points. Performance analyses with increase in number of processors |
|
630 |
indicate a trade-off between computation and communication. A |
|
631 |
combined thread and MPI based model is attempted to harness the |
|
632 |
benefits from both forms of architectures. |
|
633 |
</p> |
|
634 |
||
635 |
||
636 |
||
637 |
||
638 |
||
639 |
||
640 |
||
641 |
||
642 |
<h3 id="sec-4_8">Simplified and effective Network Simulation using ns-3 </h3> |
|
643 |
||
644 |
||
645 |
<p>Erroju Rama Krishna |
|
646 |
</p> |
|
647 |
||
648 |
||
649 |
||
650 |
<h4 id="sec-4_8_1">Talk/Paper Abstract </h4> |
|
651 |
||
652 |
||
|
227
091f3896c5e8
Added titles and abstracts of Prabhu, Asokan and Fernando.
Kadambari Devarajan <kadambari.devarajan@gmail.com>
parents:
222
diff
changeset
|
653 |
|
| 281 | 654 |
<p> |
655 |
Network simulation has great significance in the research areas of |
|
656 |
modern networks. The ns-2 is the popular simulation tool which |
|
657 |
proved this, in the successive path of ns-2 by maintaining the |
|
658 |
efficiency of the existing mechanism it has been explored with a |
|
659 |
new face and enhanced power of python scripting in ns-3. Python |
|
660 |
scripting can be added to legacy projects just as well as new |
|
661 |
ones, so developers don't have to abandon their old C/C++ code |
|
662 |
libraries, but in the ns-2 it is not possible to run a simulation |
|
663 |
purely from C++ (i.e., as a main() program without any OTcl), ns-3 |
|
664 |
does have new capabilities (such as handling multiple interfaces |
|
665 |
on nodes correctly, use of IP addressing and more alignment with |
|
666 |
Internet protocols and designs, more detailed 802.11 models, etc.) |
|
667 |
</p> |
|
668 |
<p> |
|
669 |
In ns-3, the simulator is written entirely in C++, with optional |
|
670 |
Python bindings. Simulation scripts can therefore be written in |
|
671 |
C++ or in Python. The results of some simulations can be |
|
672 |
visualized by nam, but new animators are under development. Since |
|
673 |
ns-3 generates pcap packet trace files, other utilities can be |
|
674 |
used to analyze traces as well. |
|
675 |
</p> |
|
676 |
<p> |
|
677 |
In this paper the efficiency and effectiveness of IP addressing |
|
678 |
simulation model of ns-3 is compared with the ns-2 simulation |
|
679 |
model,ns-3 model consisting of the scripts written in Python which |
|
680 |
makes the modeling simpler and effective |
|
681 |
</p> |
|
682 |
||
683 |
||
684 |
||
685 |
||
686 |
||
687 |
||
688 |
||
689 |
<h3 id="sec-4_9">PyCenter </h3> |
|
690 |
||
691 |
||
692 |
<p>Karthikeyan selvaraj |
|
693 |
</p> |
|
694 |
||
695 |
||
696 |
||
697 |
<h4 id="sec-4_9_1">Talk/Paper Abstract </h4> |
|
698 |
||
|
227
091f3896c5e8
Added titles and abstracts of Prabhu, Asokan and Fernando.
Kadambari Devarajan <kadambari.devarajan@gmail.com>
parents:
222
diff
changeset
|
699 |
|
| 281 | 700 |
<p>The primary objective is defining a centralized testing |
701 |
environment and a model of testing framework which integrates all |
|
702 |
projects in testing in a single unit. |
|
703 |
</p> |
|
704 |
<p> |
|
705 |
The implementation of concurrent processing systems and adopting |
|
706 |
client server architecture and with partitioned server zones for |
|
707 |
environment manipulation, allows the server to run test requests |
|
708 |
from different projects with different environment and testing |
|
709 |
requests. The implementation provides features of auto-test |
|
710 |
generation, scheduled job run from server, thin and thick clients. |
|
711 |
</p> |
|
712 |
||
713 |
<p> |
|
714 |
The core engine facilitates the management of tests from all the |
|
715 |
clients with priority and remote scheduling. It has an extended |
|
716 |
configuration utility to manipulate test parameters and watch |
|
717 |
dynamic changes. It not only acts as a request pre-preprocessor |
|
718 |
but also a sophisticated test bed by its implementation. It is |
|
719 |
provided with storage and manipulation segment for every |
|
720 |
registered project in the server zone. The system schedules and |
|
721 |
records events and user activities thereby the results can be |
|
722 |
drilled and examined to core code level with activates and system |
|
723 |
states at the test event point. |
|
724 |
</p> |
|
725 |
<p> |
|
726 |
The system generates test cases both in human readable as well as |
|
727 |
executable system formats. The generated tests are based on a |
|
728 |
pre-defined logic in the system which can be extended to adopt new |
|
729 |
cases based on user requests. These are facilitated by a template |
|
730 |
system which has a predefined set of cases for various test types |
|
731 |
like compatibility, load, performance, code coverage, dependency |
|
732 |
and compliance testing. It is also extended with capabilities like |
|
733 |
centralized directory systems for user management with roles and |
|
734 |
privileges for authentication and authorization, global mailer |
|
735 |
utilities, Result consolidator and Visualizer. |
|
736 |
</p> |
|
737 |
<p> |
|
738 |
With the effective implementation of the system with its minimal |
|
739 |
requirements, the entire testing procedure can be automated with |
|
740 |
the testers being effectively used for configuring, ideating and |
|
741 |
managing the test system and scenarios. The overhead of managing |
|
742 |
the test procedures like environment pre-processing, test |
|
743 |
execution, results collection and presentation are completely |
|
744 |
evaded from the testing life cycle. |
|
745 |
</p> |
|
746 |
||
747 |
||
748 |
||
749 |
||
750 |
||
751 |
||
752 |
||
753 |
||
754 |
<h3 id="sec-4_10">Live media for training in experimental sciences </h3> |
|
755 |
||
756 |
||
757 |
<p>Georges Khaznadar |
|
|
227
091f3896c5e8
Added titles and abstracts of Prabhu, Asokan and Fernando.
Kadambari Devarajan <kadambari.devarajan@gmail.com>
parents:
222
diff
changeset
|
758 |
</p> |
|
091f3896c5e8
Added titles and abstracts of Prabhu, Asokan and Fernando.
Kadambari Devarajan <kadambari.devarajan@gmail.com>
parents:
222
diff
changeset
|
759 |
|
|
091f3896c5e8
Added titles and abstracts of Prabhu, Asokan and Fernando.
Kadambari Devarajan <kadambari.devarajan@gmail.com>
parents:
222
diff
changeset
|
760 |
|
| 281 | 761 |
|
762 |
<h4 id="sec-4_10_1">Talk/Paper Abstract </h4> |
|
763 |
||
764 |
||
765 |
<p>A system for distance learning in the field of Physics and |
|
766 |
Electricity has been used for three years with some success for 15 |
|
767 |
years old students. The students are given a little case |
|
768 |
containing a PHOENIX box (see |
|
769 |
<a href="http://www.iuac.res.in/~elab/phoenix/">http://www.iuac.res.in/~elab/phoenix/</a>) featuring electric analog |
|
770 |
and digital I/O interfaces, some unexpensive discrete components |
|
771 |
and a live (bootable) USB stick. |
|
772 |
</p> |
|
773 |
<p> |
|
774 |
The PHOENIX project was started by Inter University Accelerator |
|
775 |
Centre in New Delhi, with the objective of improving the |
|
776 |
laboratory facilities at Indian Universities, and growing with the |
|
777 |
support of the user community. PHOENIX depends heavily on Python |
|
778 |
language. The data acquisition, analysis and writing simulation |
|
779 |
programs to teach science and computation. |
|
780 |
</p> |
|
781 |
<p> |
|
782 |
The hardware design of PHOENIX box is freely available. |
|
783 |
</p> |
|
784 |
<p> |
|
785 |
The live bootable stick provides a free/libre operating system, |
|
786 |
and a few dozens educational applications, including applications |
|
787 |
developed with Scipy to drive the PHOENIX box and manage the |
|
788 |
acquired measurements. The user interface has been made as |
|
789 |
intuitive as possible: the main window shows a photo of the front |
|
790 |
face of the PHOENIX acquisition device, its connections behaving |
|
791 |
like widgets to express their states, and a subwindow displays in |
|
792 |
real time the signals connected to it. A booklet gives |
|
793 |
general-purpose hints for the usage of the acquisition device. The |
|
794 |
educational interaction is done with a free learning management |
|
795 |
system. |
|
796 |
</p> |
|
797 |
<p> |
|
798 |
The talk will show how such live media can be used as powerful |
|
799 |
training systems, allowing students to access at home exactly the |
|
800 |
same environment they can find in the school, and providing them a |
|
801 |
lot of structured examples. |
|
802 |
</p> |
|
803 |
<p> |
|
804 |
This talk addresses people who are involved in education and |
|
805 |
training in scientific fields. It describes one method which |
|
806 |
allows distance learning (however requiring a few initial lessons |
|
807 |
to be given non-remotely), and enables students to become fluent |
|
808 |
with Python and its scientific extensions, while learning physics |
|
809 |
and electricity. This method uses Internet connections to allow |
|
810 |
remote interactions, but does not rely on a wide bandwidth, as the |
|
811 |
complete learning environment is provided by the live medium, |
|
812 |
which is shared by teacher and students after their beginning |
|
813 |
lessons. |
|
814 |
</p> |
|
815 |
||
816 |
||
817 |
||
818 |
||
819 |
||
820 |
||
821 |
||
822 |
<h3 id="sec-4_11">Use of Python and Phoenix-M interface in Robotics </h3> |
|
823 |
||
824 |
||
825 |
<p>Shubham Chakraborty |
|
826 |
</p> |
|
827 |
||
828 |
||
829 |
||
830 |
<h4 id="sec-4_11_1">Talk/Paper Abstract </h4> |
|
831 |
||
832 |
||
833 |
<p>In this paper I will show how to use Python programming with a |
|
834 |
computer interface such as Phoenix-M to drive simple robots. In my |
|
835 |
quest towards Artificial Intelligence (AI) I am experimenting with |
|
836 |
a lot of different possibilities in Robotics. This one is trying |
|
837 |
to mimic the working of a simple insect's autonomous nervous |
|
838 |
system using hard wiring and some minimal software usage. This is |
|
839 |
the precursor to my advanced robotics and AI integration where I |
|
840 |
plan to use an new paradigm of AI based on Machine Learning and |
|
841 |
Self Consciousness via Knowledge Feedback and Update process. |
|
842 |
</p> |
|
843 |
||
844 |
||
845 |
||
846 |
||
847 |
||
848 |
||
849 |
||
850 |
||
851 |
<h3 id="sec-4_12">Python in Science Experiments using Phoenix </h3> |
|
852 |
||
853 |
||
854 |
<p>Ajith Kumar |
|
855 |
</p> |
|
856 |
||
857 |
||
858 |
||
859 |
<h4 id="sec-4_12_1">Talk/Paper Abstract </h4> |
|
860 |
||
861 |
||
862 |
<p>Phoenix is a hardware plus software framework for developing |
|
863 |
computer interfaced science experiments. Sensor and control |
|
864 |
elements connected to Phoenix can be accessed using Python. Text |
|
865 |
based and GUI programs are available for several |
|
866 |
experiments. Python programming language is used as a tool for |
|
867 |
data acquisition, analysis and visualization. |
|
868 |
</p> |
|
869 |
<p> |
|
870 |
Objective of the project is to improve the laboratory facilities |
|
871 |
at the Universities and also to utilize computers in a better |
|
872 |
manner to teach science. The hardware design is freely |
|
873 |
available. The project is based on Free Software tools and the |
|
874 |
code is distributed under GNU General Public License. |
|
875 |
</p> |
|
876 |
||
877 |
||
878 |
||
879 |
||
880 |
||
881 |
||
882 |
<h3 id="sec-4_13">Building and Packaging your Scientific Python Application For Linux Distributions </h3> |
|
883 |
||
884 |
||
885 |
<p>Ramakrishna Reddy Yekulla |
|
886 |
</p> |
|
887 |
||
888 |
||
889 |
||
890 |
<h4 id="sec-4_13_1">Talk/Paper Abstract </h4> |
|
891 |
||
892 |
||
893 |
<p>If you are an Independent Researcher, Academic Project or an |
|
894 |
Enterprise software Company building large scale scientific python |
|
895 |
applications, there is a huge community of packagers who look at |
|
896 |
upstream python projects to get those packages into upstream |
|
897 |
distributions. This talk focuses on practices, making your |
|
898 |
applications easy to package so that they can be bundled with |
|
899 |
Linux distributions. Additionally this talk would be more hands |
|
900 |
on, more like a workshop. The audience are encouraged to bring as |
|
901 |
many python applications possible, using the techniques showed in |
|
902 |
the talk and help them package it for fedora. |
|
903 |
</p> |
|
904 |
||
905 |
||
906 |
||
907 |
||
908 |
||
909 |
||
910 |
||
911 |
||
912 |
<h3 id="sec-4_14">Microcontroller experiment and its simulation using Python </h3> |
|
913 |
||
914 |
||
915 |
<p>Jayesh Gandhi |
|
916 |
</p> |
|
917 |
||
918 |
||
919 |
||
920 |
<h4 id="sec-4_14_1">Talk/Paper Abstract </h4> |
|
921 |
||
922 |
||
923 |
<p>Electronics in industrial has been passing through revolution due |
|
924 |
to extensive use of Microcontroller. These electronic devices are |
|
925 |
having a high capability to handle multiple events. Their |
|
926 |
capability to communicate with the computers has made the |
|
927 |
revolution possible. Therefore it is very important to have |
|
928 |
trained Personnel in Microcontroller. In the present work |
|
929 |
experiments for study of Microcontrollers and its peripherals with |
|
930 |
Simulation using Python is carried out. This facilitates the |
|
931 |
teachers to demonstrate the experiments in the classroom sessions |
|
932 |
using simulations. Then the same experiments can be carried out in |
|
933 |
the labs (using the same simulation setup) and the microcontroller |
|
934 |
hardware to visualize and understand the experiments. Python is |
|
935 |
selected due to its versatility and also to promote the use of |
|
936 |
open source software in the education. |
|
937 |
</p> |
|
938 |
<p> |
|
939 |
Here we demonstrate the experiment of driving seven segment |
|
940 |
displays by microcontroller. Four seven segment displays are |
|
941 |
interfaced with the microcontroller through a single BCD to seven |
|
942 |
segments Display Decoder/Driver (74LS47) and switching |
|
943 |
transistors. The microcontroller switches on the first transistor |
|
944 |
connected to the first display and puts the number to be displayed |
|
945 |
on 74LS47. Then it pause a while, switches off the first display |
|
946 |
and puts the number to be displayed on the second display and |
|
947 |
switches it on. A similar action is carried out for all the |
|
948 |
display and the cycle is repeated again and again. Now we can |
|
949 |
control the microcontroller action using the serial port of the |
|
950 |
computer through python. Simulating the seven segment display |
|
951 |
using VPYTHON module and communicating the same action to the |
|
952 |
microcontroller, we can demonstrate the switching action of the |
|
953 |
display at a very slow rate. It is possible to actually see each |
|
954 |
display glowing individually one after another. Now we can |
|
955 |
gradually increase the rate of switching the display. You see each |
|
956 |
display glowing for a few milliseconds. Finally the refresh rate |
|
957 |
is taken very high to around more than 25 times a second we see |
|
958 |
that all the display glowing simultaneously. |
|
959 |
</p> |
|
960 |
<p> |
|
961 |
Hence it is possible to simulate and demonstrate experiments and |
|
962 |
understand the capabilities of the microcontroller with a lot of |
|
963 |
ease and at a very low cost. |
|
964 |
</p> |
|
965 |
||
966 |
||
967 |
||
968 |
||
969 |
||
970 |
||
971 |
||
972 |
<h3 id="sec-4_15">SAGE for Scientific computing and Education enhancement </h3> |
|
973 |
||
974 |
||
975 |
<p>Manjusha Joshi |
|
976 |
</p> |
|
977 |
||
978 |
||
979 |
||
980 |
<h4 id="sec-4_15_1">Talk/Paper Abstract </h4> |
|
981 |
||
982 |
||
983 |
||
984 |
<p> |
|
985 |
Sage is Free open source software for Mathematics. |
|
986 |
</p> |
|
987 |
<p> |
|
988 |
Sage can handle long integer computations, symbolic computing, |
|
989 |
Matrices etc. Sage is used for Cryptography, Number Theory, Graph |
|
990 |
Theory in education field. Note book feature in Sage, allow user |
|
991 |
to record all work on worksheet for future use. These worksheets |
|
992 |
can be publish for information sharing, students and trainer can |
|
993 |
exchange knowledge, share, experiment through worksheets. |
|
994 |
</p> |
|
995 |
<p> |
|
996 |
Sage is an advanced computing tool which can enhance education in |
|
997 |
India. |
|
998 |
</p> |
|
999 |
||
1000 |
||
1001 |
||
1002 |
||
1003 |
||
1004 |
||
1005 |
||
1006 |
||
1007 |
||
1008 |
<h3 id="sec-4_16">Automatic Proteomic Finger Printing using Scipy </h3> |
|
1009 |
||
1010 |
||
1011 |
<p>Yogesh Karpate |
|
1012 |
</p> |
|
1013 |
||
1014 |
||
1015 |
||
1016 |
<h4 id="sec-4_16_1">Talk/Paper Abstract </h4> |
|
1017 |
||
1018 |
||
1019 |
<p>The idea is to demonstrate the PyProt (Python Proteomics), an |
|
1020 |
approach to classify mass spectrometry data and efficient use of |
|
1021 |
statistical methods to look for the potential prevalent disease |
|
1022 |
markers and proteomic pattern diagnostics. Serum proteomic pattern |
|
1023 |
diagnostics can be used to differentiate samples from the patients |
|
1024 |
with and without disease. Profile patterns are generated using |
|
1025 |
surface-enhanced laser desorption and ionization (SELDI) protein |
|
1026 |
mass spectrometry. This technology has the potential to improve |
|
1027 |
clinical diagnostic tests for cancer pathologies. There are two |
|
1028 |
datasets used in this study which are taken from the FDA-NCI |
|
1029 |
Clinical Proteomics Program Databank. First data is of ovarian |
|
1030 |
cancer and second is of Premalignant Pancreatic Cancer .The Pyprot |
|
1031 |
uses the high-resolution ovarian cancer data set that was |
|
1032 |
generated using the WCX2 protein array. The ovarian cancer dataset |
|
1033 |
includes 95 controls and 121 ovarian cancer sets, where as |
|
1034 |
pancreatic cancer dataset has 101 controls and 80 pancreatic |
|
1035 |
cancer sets. There are two modules designed and implemented in |
|
1036 |
python using Numpy , Scipy and Matplotlib. There are two different |
|
1037 |
kinds of classifications implemented here, first to classify the |
|
1038 |
ovarian cancer data set. Second type focuses on randomly |
|
1039 |
commingled study set of murine sera. it explores the ability of |
|
1040 |
the low molecular weight information archive to classify and |
|
1041 |
discriminate premalignant pancreatic cancer compared to the |
|
1042 |
control animals. |
|
1043 |
</p> |
|
1044 |
<p> |
|
1045 |
A crucial issue for classification is feature selection which |
|
1046 |
selects the relevant features in order to focus the learning |
|
1047 |
search. A relaxed setting for feature selection is known as |
|
1048 |
feature ranking, which ranks the features with respect to their |
|
1049 |
relevance. Pyprot comprises of two modules; First includes |
|
1050 |
implementation of feature ranking in Python using fisher ratio and |
|
1051 |
t square statistical test to avoid large feature space. In second |
|
1052 |
module, Multilayer perceptron (MLP) feed forward neural network |
|
1053 |
model with static back propagation algorithm is used to classify |
|
1054 |
.The results are excellent and matched with databank results and |
|
1055 |
concludes that PyProt is useful tool for proteomic finger |
|
1056 |
printing. |
|
1057 |
</p> |
|
1058 |
||
1059 |
||
1060 |
||
1061 |
||
1062 |
||
1063 |
||
1064 |
||
1065 |
||
1066 |
||
1067 |
||
1068 |
<h3 id="sec-4_17">Natural Language Processing Using Python </h3> |
|
1069 |
||
1070 |
||
1071 |
<p>Vaidhy Mayilrangam |
|
1072 |
</p> |
|
1073 |
||
1074 |
||
1075 |
||
1076 |
<h4 id="sec-4_17_1">Talk/Paper Abstract </h4> |
|
1077 |
||
1078 |
||
1079 |
<p>The purpose of this talk is to give a high-level overview of |
|
1080 |
various text mining techniques, the statistical approaches and the |
|
1081 |
interesting problems. |
|
1082 |
</p> |
|
1083 |
<p> |
|
1084 |
The talk will start with a short summary of two key areas – namely |
|
1085 |
information retrieval (IR) and information extraction (IE). We |
|
1086 |
will then discuss how to use the knowledge gained for |
|
1087 |
summarization and translation. We will talk about how to measure |
|
1088 |
the correctness of results. As part of measuring the correctness, |
|
1089 |
we will discuss about different kinds of statistical approaches |
|
1090 |
for classifying and clustering data. |
|
1091 |
</p> |
|
1092 |
<p> |
|
1093 |
We will do a short dive into NLP specific problems - identifying |
|
1094 |
sentence boundaries, parts of speech, noun and verb phrases and |
|
1095 |
named entities. We will also have a sample session on how to use |
|
1096 |
Python’s NLTK to accomplish these tasks. |
|
1097 |
</p> |
|
1098 |
||
1099 |
||
1100 |
||
1101 |
||
1102 |
||
1103 |
||
1104 |
||
1105 |
<h3 id="sec-4_18">A Parallel 3D Flow Solver in Python Based on Vortex Methods </h3> |
|
1106 |
||
1107 |
||
1108 |
<p>Prashant Agrawal |
|
1109 |
</p> |
|
1110 |
||
1111 |
||
1112 |
||
1113 |
<h4 id="sec-4_18_1">Talk/Paper Abstract </h4> |
|
1114 |
||
1115 |
||
1116 |
<p>A 3D flow solver for incompressible flow around arbitrary 3D |
|
1117 |
bodies is developed. The solver is based on vortex methods whose |
|
1118 |
grid-free nature makes it very general. It uses vortex particles |
|
1119 |
to represent the flow-field. Vortex particles (or blobs) are |
|
1120 |
released from the boundary, and these advect, stretch and diffuse |
|
1121 |
according to the Navier-Stokes equations. |
|
1122 |
</p> |
|
1123 |
<p> |
|
1124 |
The solver is based on a generic and extensible design. This has |
|
1125 |
been made possible mainly by following a universal theme of using |
|
1126 |
blobs in every component of the solver. Advection of the |
|
1127 |
particles is implemented using a parallel fast multipole |
|
1128 |
method. Diffusion is simulated using the Vorticity Redistribution |
|
1129 |
Technique (VRT). To control the number of blobs, merging of nearby |
|
1130 |
blobs is also performed. |
|
1131 |
</p> |
|
1132 |
<p> |
|
1133 |
Each component of the solver is parallelized. The boundary, |
|
1134 |
advection and stretching algorithms are based on the same parallel |
|
1135 |
velocity algorithm. Domain decomposition for parallel velocity |
|
1136 |
calculator is performed using Space Filling Curves. Diffusion, |
|
1137 |
which requires knowledge of each particle's neighbours, uses a |
|
1138 |
parallelized fast neighbour finder which is based on a bin data |
|
1139 |
structure. The same neighbour finder is used in merging also. |
|
1140 |
</p> |
|
1141 |
<p> |
|
1142 |
The code is written completely in Python. It is well-documented |
|
1143 |
and well-tested. The code base is around 4500 lines long. The |
|
1144 |
design follows an object oriented approach which makes it |
|
1145 |
extensible enough to add new features and alternate algorithms to |
|
1146 |
perform specific tasks. |
|
1147 |
</p> |
|
1148 |
<p> |
|
1149 |
The solver is also designed to run in a parallel environment |
|
1150 |
involving multiple processors. This parallel implementation is |
|
1151 |
written using mpi4py, an MPI implementation in Python. |
|
1152 |
</p> |
|
1153 |
<p> |
|
1154 |
Rigorous testing is performed using Python's unittest module. Some |
|
1155 |
standard example cases are also solved using the present solver. |
|
1156 |
</p> |
|
1157 |
<p> |
|
1158 |
In this talk we will outline the overall design of the solver and |
|
1159 |
the algorithms used. We discuss the benefits of Python and also |
|
1160 |
some of the current limitations with respect to parallel testing. |
|
1161 |
</p> |
|
1162 |
||
1163 |
||
1164 |
||
1165 |
||
1166 |
||
1167 |
||
1168 |
||
1169 |
<h3 id="sec-4_19">Performance Evaluation of HYBRID MAC for 802.11ad: Next Generation Multi-Gbps Wi-Fi using SimPy </h3> |
|
1170 |
||
1171 |
||
1172 |
<p>Hemanth Chandran |
|
1173 |
</p> |
|
1174 |
||
1175 |
||
1176 |
||
1177 |
<h4 id="sec-4_19_1">Talk/Paper Abstract </h4> |
|
1178 |
||
1179 |
||
1180 |
<p>Next generation Wireless Local Area Networks (WLAN) is targeting |
|
1181 |
at multi giga bits per second throughput by utilizing the |
|
1182 |
unlicensed spectrum available at 60 GHz, millimeter wavelength |
|
1183 |
(mmwave).Towards achieving the above goal a new standard namely |
|
1184 |
the 802.11ad is under consideration. Due to the limited range and |
|
1185 |
other typical characteristics like high path loss etc., of these |
|
1186 |
mmwave radios the requirement of the Medium Access Control (MAC) |
|
1187 |
are totally different. |
|
1188 |
</p> |
|
1189 |
<p> |
|
1190 |
The conventional MAC protocols tend to achieve different |
|
1191 |
objectives under different conditions. For example, the (Carrier |
|
1192 |
Sense Multiple Access / Collision Avoidance) CSMA/CA technique is |
|
1193 |
robust and simple and works well in overlapping network |
|
1194 |
scenarios. It is also suitable for bursty type of traffic. On the |
|
1195 |
other hand CSMA/CA is not suitable for power management since it |
|
1196 |
needs the stations to be awake always. Moreover it requires an |
|
1197 |
omni directional antenna pattern for the receiver which is |
|
1198 |
practically not feasible in 60 GHz band. |
|
1199 |
</p> |
|
1200 |
<p> |
|
1201 |
A Time Division Multiple Access (TDMA) based MAC is efficient for |
|
1202 |
Quality of Service (QoS) sensitive traffic. It is also useful for |
|
1203 |
power saving since the station knows their schedule and can |
|
1204 |
therefore power down in non scheduled periods. |
|
1205 |
</p> |
|
1206 |
<p> |
|
1207 |
For 60 GHz usages especially applications like wireless display, |
|
1208 |
sync and go, and large file transfer, TDMA appears to be a |
|
1209 |
suitable choice. Whereas for applications that require low latency |
|
1210 |
channel access (e.g. Internet access etc.)TDMA appears to be |
|
1211 |
inefficient due to the latency involved in bandwidth reservation. |
|
1212 |
</p> |
|
1213 |
<p> |
|
1214 |
Another choice is the polling MAC which is highly efficient for |
|
1215 |
the directional communication in the 60 GHz band. This provides an |
|
1216 |
improved data rates with directional communication as well as acts |
|
1217 |
as an interference mitigation scheme. On the contrary polling may |
|
1218 |
not be efficient for power saving and also not efficient to take |
|
1219 |
advantage of statistical traffic multiplexing. This technique also |
|
1220 |
leads to wastage of power due to polling the stations without |
|
1221 |
traffic to transmit. |
|
1222 |
</p> |
|
1223 |
<p> |
|
1224 |
Having the above facts in mind and considering the variety of |
|
1225 |
applications involved in the next generation WLAN systems |
|
1226 |
operating at 60 GHz, it can be concluded that no individual MAC |
|
1227 |
scheme can support the traffic requirements. |
|
1228 |
</p> |
|
1229 |
<p> |
|
1230 |
In this paper we use SimPy to do a Discrete Event Simulation |
|
1231 |
modeling of a proposed hybrid MAC protocol which dynamically |
|
1232 |
adjusts the channel times between contention and reservation based |
|
1233 |
MAC schemes, based on the traffic demand in the network. |
|
1234 |
</p> |
|
1235 |
<p> |
|
1236 |
We plan to model the problem of admission control and scheduling |
|
1237 |
using DES using SimPy. SimPy v2.1.0 is being used for the |
|
1238 |
simulation purposes of the proposed Hybrid MAC. We are new to |
|
1239 |
using Python for scientific purposes and have just begun using |
|
1240 |
this powerful tool to get meaningful and useful results. We plan |
|
1241 |
to share our learning experience and how SimPy is increasingly |
|
1242 |
becoming a useful tool (apart from regular modeling tools like |
|
1243 |
Opnet / NS2). |
|
1244 |
</p> |
|
1245 |
||
1246 |
||
1247 |
||
1248 |
||
1249 |
||
1250 |
||
1251 |
||
1252 |
||
1253 |
||
1254 |
<h3 id="sec-4_20">PySPH: Smooth Particle Hydrodynamics with Python </h3> |
|
1255 |
||
1256 |
||
1257 |
<p>pankaj pandey |
|
1258 |
</p> |
|
1259 |
||
1260 |
||
1261 |
||
1262 |
<h4 id="sec-4_20_1">Talk/Paper Abstract </h4> |
|
1263 |
||
1264 |
||
1265 |
||
1266 |
<p> |
|
1267 |
We present a python/cython implementation of an SPH framework |
|
1268 |
called PySPH. SPH (Smooth Particle Hydrodynamics) is a numerical |
|
1269 |
technique for the solution of the continuum equations of fluid and |
|
1270 |
solid mechanics. |
|
1271 |
</p> |
|
1272 |
<p> |
|
1273 |
PySPH was written to be a tool which requires only a basic working |
|
1274 |
knowledge of python. Although PySPH may be run on distributed |
|
1275 |
memory machines, no working knowledge of parallelism is required |
|
1276 |
of the user as the same code may be run either in serial or in |
|
1277 |
parallel only by proper invocation of the mpirun command. |
|
1278 |
</p> |
|
1279 |
<p> |
|
1280 |
In PySPH, we follow the message passing paradigm, using the mpi4py |
|
1281 |
python binding. The performance critical aspects of the SPH |
|
1282 |
algorithm are optimized with cython which provides the look and |
|
1283 |
feel of python but the performance near to that of a C/C++ |
|
1284 |
implementation. |
|
1285 |
</p> |
|
1286 |
<p> |
|
1287 |
PySPH is divided into three main modules. The base module provides |
|
1288 |
the data structures for the particles, and algorithms for nearest |
|
1289 |
neighbor retrieval. The sph module builds on this to describe the |
|
1290 |
interactions between particles and defines classes to manage this |
|
1291 |
interaction. These two modules provide the basic functionality as |
|
1292 |
dictated by the SPH algorithm and of these, a developer would most |
|
1293 |
likely be working with the sph module to enhance the functionality |
|
1294 |
of PySPH. The solver module typically manages the simulation being |
|
1295 |
run. Most of the functions and classes in this module are written |
|
1296 |
in pure python which makes is relatively easy to write new solvers |
|
1297 |
based on the provided functionality. |
|
1298 |
</p> |
|
1299 |
<p> |
|
1300 |
We use PySPH to solve the shock tube problem in gas dynamics and |
|
1301 |
the classical dam break problem for incompressible fluids. We also |
|
1302 |
demonstrate how to extend PySPH to solve a problem in solid |
|
1303 |
mechanics which requires additions to the sph module. |
|
1304 |
</p> |
|
1305 |
||
1306 |
||
1307 |
||
1308 |
||
1309 |
||
1310 |
||
1311 |
<h3 id="sec-4_21">Pictures, Songs and Python </h3> |
|
1312 |
||
1313 |
||
1314 |
<p>Puneeth Chaganti |
|
1315 |
</p> |
|
1316 |
||
1317 |
||
1318 |
||
1319 |
<h4 id="sec-4_21_1">Talk/Paper Abstract </h4> |
|
1320 |
||
1321 |
||
1322 |
<p>The aim of this talk is to get students, specially undergrads |
|
1323 |
excited about Python. Most of what will be shown, is out there on |
|
1324 |
the Open web. We just wish to draw attention of the students and |
|
1325 |
get them excited about Python and possibly image processing and |
|
1326 |
may be even cognition. We hope that this talk will help retain |
|
1327 |
more participants for the tutorials and sprint sessions. |
|
1328 |
</p> |
|
1329 |
<p> |
|
1330 |
The talk will have two parts. The talk will not consist of any |
|
1331 |
deep research or amazing code. It's a mash-up of some weekend |
|
1332 |
hacks, if they could be called so. We reiterate that the idea is |
|
1333 |
not to show the algorithms or the code and ideas. It is, to show |
|
1334 |
the power that Python gives. |
|
1335 |
</p> |
|
1336 |
<p> |
|
1337 |
The first part of the talk will deal with the colour Blue. We'll |
|
1338 |
show some code to illustrate how our eyes suck at blue (1), if |
|
1339 |
they really do. But, ironically, a statistical analysis that we |
|
1340 |
did on "Rolling Stones Magazine's Top 500 Songs of All time" (2), |
|
1341 |
revealed that the occurrences of blue are more than twice the |
|
1342 |
number of occurrences of red and green! We'll show the code used |
|
1343 |
to fetch the lyrics and count the occurrences. |
|
1344 |
</p> |
|
1345 |
<p> |
|
1346 |
The second part of the talk will show some simple hacks with |
|
1347 |
images. First, a simple script that converts images into ASCII |
|
1348 |
art. We hacked up a very rudimentary algo to convert images to |
|
1349 |
ASCII and it works well for "machine generated images." Next, a |
|
1350 |
sample program that uses OpenCV (3) that can detect faces. We wish |
|
1351 |
to show OpenCV since it has some really powerful stuff for image |
|
1352 |
processing. |
|
1353 |
</p> |
|
1354 |
<p> |
|
1355 |
(1) <a href="http://nfggames.com/games/ntsc/visual.shtm">http://nfggames.com/games/ntsc/visual.shtm</a> |
|
1356 |
(2) <a href="http://web.archive.org/web/20080622145429/www.rollingstone.com/news/coverstory/500songs">http://web.archive.org/web/20080622145429/www.rollingstone.com/news/coverstory/500songs</a> |
|
1357 |
(3) <a href="http://en.wikipedia.org/wiki/OpenCV">http://en.wikipedia.org/wiki/OpenCV</a> |
|
1358 |
</p> |
|
1359 |
||
1360 |
||
1361 |
||
1362 |
||
1363 |
||
|
286
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Added talk tags for special and invited talks.
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|
1364 |
|
|
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|
1365 |
|
|
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Added talk tags for special and invited talks.
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diff
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|
1366 |
|
|
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Added talk tags for special and invited talks.
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diff
changeset
|
1367 |
|
|
285
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diff
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|
1368 |
<h3 id="sec-4_22">Convincing Universities to include Python </h3> |
|
b8f0cdfe8007
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parents:
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diff
changeset
|
1369 |
|
|
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Added Krishnakant's talk abstract
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parents:
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diff
changeset
|
1370 |
|
|
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Added Krishnakant's talk abstract
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parents:
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diff
changeset
|
1371 |
<p>Krishnakant Mane |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
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parents:
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diff
changeset
|
1372 |
</p> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
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parents:
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diff
changeset
|
1373 |
|
|
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Added Krishnakant's talk abstract
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parents:
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diff
changeset
|
1374 |
|
|
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Added Krishnakant's talk abstract
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parents:
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diff
changeset
|
1375 |
|
|
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Added Krishnakant's talk abstract
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parents:
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diff
changeset
|
1376 |
<h4 id="sec-4_22_1">Talk/Paper Abstract </h4> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
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diff
changeset
|
1377 |
|
|
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Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
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diff
changeset
|
1378 |
|
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1379 |
<p>Python has been around for a long enough time now that it needs |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1380 |
serious attention from the educational institutes which teach |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1381 |
computer science. Today Python is known for its simple syntax |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1382 |
yet powerful performance (if not the fastest performance which |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1383 |
is any ways not needed all the time ). From Scientific computing |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1384 |
till graphical user interfaces and from system administration |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1385 |
till web application development, it is used in many |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1386 |
domains. However due to Industrial propaganda leading to |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1387 |
promotion of other interpreted languages (free or proprietary)? |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1388 |
Python has not got the justice in educational sector which it |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1389 |
deserves. This paper will talk on methodologies which can be |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1390 |
adopted to convince the universities for including Python in |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1391 |
their curriculum. The speaker will provide an insight into his |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1392 |
experience on success in getting Python included in some |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1393 |
Universities. A case of SNDT University will be discussed where |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1394 |
the curriculum designers have decided to have Python in their |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1395 |
courses from the next year. The speaker will share his ideas |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1396 |
which led to this inclusion. these will include, |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1397 |
</p> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1398 |
<ul> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1399 |
<li> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1400 |
Begin by doing series of Python workshops |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1401 |
</li> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1402 |
<li> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1403 |
Provide information and opportunities for python based projects |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1404 |
</li> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1405 |
<li> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1406 |
make the faculties aware of teaching ease |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1407 |
</li> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1408 |
<li> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1409 |
clear the FUD regarding jobs |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1410 |
</li> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1411 |
</ul> |
|
b8f0cdfe8007
Added Krishnakant's talk abstract
Puneeth Chaganti <punchagan@fossee.in>
parents:
281
diff
changeset
|
1412 |
|
|
338
5b0a6b71fd64
Changed schedule of Day-1 to include Farhat.
Puneeth Chaganti <punchagan@fossee.in>
parents:
295
diff
changeset
|
1413 |
|
|
355
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1414 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1415 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1416 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1417 |
<h3 id="sec-4_21">Python based Galaxy workflow integration on GARUDA Grid</h3> |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1418 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1419 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1420 |
<p>Karuna and/or Mangala |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1421 |
</p> |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1422 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1423 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1424 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1425 |
<h4 id="sec-4_23">Talk/Paper Abstract </h4> |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1426 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1427 |
<p> |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1428 |
Bioinformatics applications being complex problem involving multiple |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1429 |
comparisons, alignment, mapping and analysis can be managed better using |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1430 |
workflow solutions. Galaxy is an open web based platform developed in |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1431 |
Python for genomic research. Python is a light weight dynamic language |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1432 |
making Galaxy to be modular and expandable. Bioinformatics applications |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
339
diff
changeset
|
1433 |
being compute and data intensive scale well in grid computing |
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
parents:
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diff
changeset
|
1434 |
environments. In this paper we describe bringing the Galaxy workflow to |
|
bce85144acd5
Added a talk to be given by CDAC people.
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|
1435 |
the Garuda Grid computing infrastructure for enabling bioinformatics |
|
bce85144acd5
Added a talk to be given by CDAC people.
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changeset
|
1436 |
applications. GAURDA grid is an aggregation of heterogeneous resources and |
|
bce85144acd5
Added a talk to be given by CDAC people.
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|
1437 |
advanced capabilities for scientific applications. Here we present the |
|
bce85144acd5
Added a talk to be given by CDAC people.
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parents:
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|
1438 |
integration of galaxy workflow tool with GARUDA grid middleware to enable |
|
bce85144acd5
Added a talk to be given by CDAC people.
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|
1439 |
computational biologists to perform complex problems on the grid |
|
bce85144acd5
Added a talk to be given by CDAC people.
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|
1440 |
environment through a web browser. |
|
bce85144acd5
Added a talk to be given by CDAC people.
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changeset
|
1441 |
</p> |
|
bce85144acd5
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changeset
|
1442 |
|
|
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|
1443 |
|
|
bce85144acd5
Added a talk to be given by CDAC people.
Madhusudan.C.S <madhusudancs@gmail.com>
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079c29b18517
Made sprints page, tutorials page and conference schedule page.
Anoop Jacob Thomas<anoop@fossee.in>
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{% endblock content %}
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