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DTSTAMP:20260510T181709Z
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DTSTART;TZID=Europe/London:20260513T133000
DTEND;TZID=Europe/London:20260513T143000
DESCRIPTION:It is essential for researchers to consider human factors in re
 al-scale social simulations that take into account people living and worki
 ng in target communities. In order to do so\, researchers need to know att
 ributes of living and working people such as age\, sex\, race\, living pla
 ce\, occupation\, income and workplace. However those attributes are a kin
 d of privacy data that are not available to researchers. To tackle with su
 ch difficulty in accessibility\, data synthesis is getting attentions rece
 ntly. Data synthesis is a method to synthesize data based on the statistic
 al characteristics of collected data. The lecturer gives a talk how to syn
 thesize the population data using statistics\, and several applications of
  synthesized population data in real-scale social simulations including CO
 VID-19 counter-measures.\n\nCo-sponsored by: Ulster University\n\nSpeaker(
 s): Tadahiko\, \n\nRoom: BC-03-206\, Bldg: BC\, Ulster University Belfast 
 Campus\, Belfast\, Northern Ireland\, United Kingdom\, Virtual: https://ev
 ents.vtools.ieee.org/m/552578
LOCATION:Room: BC-03-206\, Bldg: BC\, Ulster University Belfast Campus\, Be
 lfast\, Northern Ireland\, United Kingdom\, Virtual: https://events.vtools
 .ieee.org/m/552578
ORGANIZER:h.zheng@ulster.ac.uk
SEQUENCE:38
SUMMARY:Real-Scale Social Simulations Using Societal Synthetic Populations 
 in Digital Twin
URL;VALUE=URI:https://events.vtools.ieee.org/m/552578
X-ALT-DESC:Description: <br /><p style="text-align: justify\;"><span style=
 "caret-color: rgb(33\, 33\, 33)\; color: rgb(33\, 33\, 33)\; font-family: 
 arial\, helvetica\, sans-serif\; font-size: 14.6667px\; font-style: normal
 \; font-variant-caps: normal\; font-weight: 400\; letter-spacing: normal\;
  text-align: start\; text-indent: 0px\; text-transform: none\; white-space
 : normal\; word-spacing: 0px\; -webkit-text-stroke-width: 0px\; text-decor
 ation: none\; display: inline !important\; float: none\;"> It is essential
  for researchers to consider human factors in real-scale social simulation
 s that take into account people living and working in target communities. 
 In order to do so\, researchers need to know attributes of living and work
 ing people such as age\, sex\, race\, living place\, occupation\, income a
 nd workplace. However those attributes are a kind of privacy data that are
  not available to researchers. To tackle with such difficulty in accessibi
 lity\, data synthesis is getting attentions recently. Data synthesis is a 
 method to synthesize data based on the statistical characteristics of coll
 ected data. The lecturer gives a talk how to synthesize the population dat
 a using statistics\, and several applications of synthesized population da
 ta in real-scale social simulations including COVID-19 counter-measures.</
 span></p>
END:VEVENT
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