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TZID:Asia/Calcutta
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DTSTART:19451014T230000
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BEGIN:VEVENT
DTSTAMP:20220221T124445Z
UID:531051DD-0F63-46FE-A7C2-9360510459A6
DTSTART;TZID=Asia/Calcutta:20220128T000000
DTEND;TZID=Asia/Calcutta:20220129T000000
DESCRIPTION:Sarvajanik College of Engineering and Technology\, Surat in ass
 ociation with IEEE SPS SCET Student Branch Chapter\, GS and IEEE SCET Stud
 ent Branch organizes\, a national level project competition on ‘Data Sci
 ence Challenge.’\n\n|The goal is to turn data into information\, and inf
 ormation into insight.|\n\n- The competition is open for BE/BTech/BCA/B.Sc
 .(IT and CO)ME/MTech /MCA students.\n- Participants can form a team of 3 (
 maximum) and 1 mentor.\n- Problem statements will be given in two domains\
 , viz. Signal Processing and Image Processing.\n- All participating teams 
 will send a 3 minutes video clip on idea/work-out related to the given bro
 ad problem statement (mentioned below)\, in the corresponding category by 
 20th Jan 2022.\n- Qualified teams will participate in the Semi-final round
  on 28th Jan 2022 and will have to work with the exact problem statement p
 rovided in the domain of interest.\n- The final round will be on 29th Jan 
 2022 (Live Final to be conducted on Google Meet/ On Campus). Winners of th
 e final round will be decided on the basis of performance parameters like 
 accuracy\, F1-score\, time limit\, the computational complexity of the cod
 e\, use of hardware like Jetson Nano kit\, etc.\n- At least one member of 
 the team should have IEEE SPS membership (preferably\, a mentor should be 
 an IEEE SPS member). Else\, the participants have to pay INR 500 per team.
 \n\nGuidelines for 3 minutes video:\n\n- Work should be unique\n- Size of 
 video clip should not exceed 200 MB (SD resolution).\n- More than 30% plag
 iarism in the code/information/work may lead to the disqualification of th
 e team with disciplinary actions.\n- Video clip should clearly explain the
  work with the associated code and the results\n- Clearly mention the prob
 lem for which the problem is solved and the corresponding dataset used.\n-
  Time limit of 3 minutes has to be maintained\n- Video clip submission for
 mat: (.mp4)\n\nProblem Statements:\n\n1) Forecasting Problem - Time series
  forecasting can be framed as a supervised learning problem. Similarly\, t
 here are many areas like public health systems or crop diseases timely pre
 diction will save the damage or loss in future span.\n\n2) Biomedical Sign
 al Classification - Biomedical signals are signals primarily used to diagn
 ose or detect specific pathological or physiological conditions. There are
  different biomedical signals including the electroencephalogram (EEG)\, t
 he electrocardiogram (ECG)\, the electromyogram (EMG)\, the electroneurogr
 am\, the electroretinogram and so on.\n\n3) Optical Character Recognition 
 - Recognizing characters of any language has been a challenging task in th
 e field of Machine Learning.\n\n4) Digital Image Security - security of im
 ages containing critical personal information is utmost important. Typical
 ly\, an image can be secured with any of the mechanisms&#39; viz. cryptography
 \, steganography\, watermarking\, reversible watermarking.\n\nAgenda: \nBE
 /B-Tech/BCA/B.Sc.(IT) and CO)ME/MTech/MCA students are invited to compete 
 at the national level in a project competition. The competition&#39;s goal was
  to encourage aspiring technocrats to apply their technical knowledge to d
 evelop and demonstrate application-oriented working models in the field of
  Data Science.\n\nVirtual: https://events.vtools.ieee.org/m/299618
LOCATION:Virtual: https://events.vtools.ieee.org/m/299618
ORGANIZER:ieee.student.sb@gmail.com
SEQUENCE:8
SUMMARY:A National Level Project Competition on Data Science Challenge 1.0 
 (DSC1.0)
URL;VALUE=URI:https://events.vtools.ieee.org/m/299618
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;Sarvajanik College of Engineering and Tech
 nology\, Surat in association with IEEE SPS SCET Student Branch Chapter\, 
 GS and IEEE SCET Student Branch organizes\, a national level project compe
 tition on&lt;strong&gt;&amp;nbsp\;&amp;lsquo\;Data Science Challenge.&amp;rsquo\;&amp;nbsp\;&lt;/st
 rong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;em&gt;|The goal is to turn data into information\, and informa
 tion into insight.|&lt;/em&gt;&lt;/p&gt;\n&lt;ul&gt;\n&lt;li&gt;The competition is open for BE/BTe
 ch/BCA/B.Sc.(IT and CO)ME/MTech /MCA students.&lt;/li&gt;\n&lt;li&gt;Participants can 
 form a team of 3 (maximum) and 1 mentor.&lt;/li&gt;\n&lt;li&gt;Problem statements will
  be given in two domains\, viz. Signal Processing and Image Processing.&lt;/l
 i&gt;\n&lt;li&gt;All participating teams will send a 3 minutes video clip on idea/w
 ork-out related to the given broad problem statement (mentioned below)\, i
 n the corresponding category by &lt;strong&gt;20th Jan 2022&lt;/strong&gt;.&lt;/li&gt;\n&lt;li&gt;
 Qualified teams will participate in the Semi-final round on 28th Jan 2022 
 and will have to work with the exact problem statement provided in the dom
 ain of interest.&lt;/li&gt;\n&lt;li&gt;The final round will be on 29th Jan 2022 (Live 
 Final to be conducted on Google Meet/ On Campus). Winners of the final rou
 nd will be decided on the basis of performance parameters like accuracy\, 
 F1-score\, time limit\, the computational complexity of the code\, use of 
 hardware like Jetson Nano kit\, etc.&lt;/li&gt;\n&lt;li&gt;At least one member of the 
 team should have IEEE SPS membership (preferably\, a mentor should be an I
 EEE SPS member). Else\, the participants have to pay INR 500 per team.&amp;nbs
 p\;&lt;/li&gt;\n&lt;/ul&gt;\n&lt;p&gt;&lt;strong&gt;Guidelines for 3 minutes video:&lt;/strong&gt;&lt;/p&gt;\n
 &lt;ul&gt;\n&lt;li&gt;Work should be unique&lt;/li&gt;\n&lt;li&gt;Size of video clip should not ex
 ceed 200 MB (SD resolution).&lt;/li&gt;\n&lt;li&gt;More than 30% plagiarism in the cod
 e/information/work may lead to the disqualification of the team with disci
 plinary actions.&lt;/li&gt;\n&lt;li&gt;Video clip should clearly explain the work with
  the associated code and the results&lt;/li&gt;\n&lt;li&gt;Clearly mention the problem
  for which the problem is solved and the corresponding dataset used.&lt;/li&gt;\
 n&lt;li&gt;Time limit of 3 minutes has to be maintained&lt;/li&gt;\n&lt;li&gt;Video clip sub
 mission format: (.mp4)&amp;nbsp\;&lt;/li&gt;\n&lt;/ul&gt;\n&lt;p&gt;&lt;strong&gt;Problem Statements:&lt;
 /strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;1) Forecasting Problem - &lt;/strong&gt;Time series for
 ecasting can be framed as a supervised learning problem. Similarly\, there
  are many areas like public health systems or crop diseases timely predict
 ion will save the damage or loss in future span.&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;2) Biomed
 ical Signal Classification - &lt;/strong&gt;Biomedical signals are signals prima
 rily used to diagnose or detect specific pathological or physiological con
 ditions. There are different biomedical signals including the electroencep
 halogram (EEG)\, the electrocardiogram (ECG)\, the electromyogram (EMG)\, 
 the electroneurogram\, the electroretinogram and so on.&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;3)
  Optical Character Recognition - &lt;/strong&gt;Recognizing characters of any la
 nguage has been a challenging task in the field of Machine Learning.&lt;/p&gt;\n
 &lt;p&gt;&lt;strong&gt;4) Digital Image Security - &lt;/strong&gt;security of images contain
 ing critical personal information is utmost important. Typically\, an imag
 e can be secured with any of the mechanisms&#39; viz. cryptography\, steganogr
 aphy\, watermarking\, reversible watermarking.&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;&lt;br /&gt;&lt;b
 r /&gt;Agenda: &lt;br /&gt;&lt;p&gt;BE/B-Tech/BCA/B.Sc.(IT) and CO)ME/MTech/MCA students 
 are invited to compete at the national level in a project competition. The
  competition&#39;s goal was to encourage aspiring technocrats to apply their t
 echnical knowledge to develop and demonstrate application-oriented working
  models in the field of Data Science.&lt;/p&gt;
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