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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ ³í¹®Áö

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ÇѱÛÁ¦¸ñ(Korean Title) ¸Ó½Å ·¯´× ¾Ë°í¸®ÁòÀ» ÀÌ¿ëÇÑ COVID-19 Risk ºÐ¼® ¹× Safe Activity Áö¿ø ½Ã½ºÅÛ
¿µ¹®Á¦¸ñ(English Title) COVID-19 Risk Analytics and Safe Activity Assistant Systemwith Machine Learning Algorithms
ÀúÀÚ(Author) ÀÌÁ¤½Ä   Á¶¼º¿µ   ¿ÀÇà·Ï   ÇÑ¸í¹¬   Jung-Sik Lee   Sung-Young Cho   Heang-Rok Oh   Myung-Mook Han   À¯Çý¿¬   ±è¹®Çö   ¹èº´Ã¶   Hye-Yeon Yu   Moon-Hyun Kim   Byung-Chull Bae   Àüµµ¿µ   ¼Û¸íÈ£   ±è¼öµ¿   DoYeong Jeon   Myeong Ho Song   Soo Dong Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 22 NO. 01 PP. 0065 ~ 0077 (2021. 02)
Çѱ۳»¿ë
(Korean Abstract)
ÃÖ±Ù COVID-19À¸·Î ÀÎÇÏ¿© Àü¼¼°èÀûÀ¸·Î ¼ö¸¹Àº °¨¿°ÀÚ¿Í »ç¸ÁÀÚ°¡ ¹ß»ýÇÏ¿´´Ù. ¾ÆÁ÷±îÁöµµ È¿°úÀûÀÎ COVID-19¿¡ ´ëÇÑ ¹é½ÅÀÇ °³¹ßÀº ¼º°øÇÏÁö ¸øÇÑ »óÅÂÀÌ´Ù. µû¶ó¼­ »ç¶÷µéÀºÀÌ Áúº´ÀÇ °¨¿°¿¡ Å©°Ô ¿ì·ÁÇÏ°í ÀÖ´Ù. ±×°£ Á¤ºÎ °ø°ø±â°üÀÌ Á¦°øÇÑ °¨¿° Á¤º¸´Â °ÅÀÇ ´Ü¼øÇÑ ÇÕ»ê ¹× Åë°è ¼ýÀÚ¿¡ ºÒ°úÇÏ´Ù. µû¶ó¼­, °³ÀÎÀ̳ª °³ÀÎÀÌ ÀÖ´Â Àå¼ÒÀÇ ±¸Ã¼ÀûÀÎ À§Çèµµ´Â ÆÇ´ÜÇϱ⠾î·Æ´Ù. º» ³í¹®¿¡¼­´Â ¸Ó½Å·¯´× ¾Ë°í¸®Áò ±â¹Ý COVID-19ÀÇ À§Çèµµ ºÐ¼®°ú ¾ÈÀü È°µ¿¿¡ ´ëÇÑ Á¤º¸ Á¦°ø¿¡ ´ëÇÑ ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. ÀÌ ³í¹®ÀºCOVID-19 °¨¿° ¹× »ç¸Á À§Çèµµ¿Í °ü·ÃµÈ Æ÷°ýÀûÀÎ ¸ÞÆ®¸¯ ü°è¸¦ Á¦¾ÈÇÏ°í, À̸¦ ÅëÇØ °³ÀÎ ¹× ±×·ì¿¡ ´ëÇÑ À§Çèµµ¸¦ Á¤·®ÀûÀ¸·Î Á¦°øÇÏ´Â ±â¹ýÀ» Á¦½ÃÇÑ´Ù. Á¦½ÃµÈ ½Ã½ºÅÛÀº °³ÀÎ ¹× Áö¿ª Á¤º¸¿Í Ư¼ºÀ» ¹Ý¿µÇÑ ÇÑ Å¬·¯½ºÅ͸µ ¾Ë°í¸®Áò µî È¿°úÀûÀÎ SW ±â¹ýµéÀ» È°¿ëÇÑ´Ù.
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(English Abstract)
COVID-19 has recently impacted the world with the large numbers of infected and deaths. The development of effective COVID-19 vaccine has not been successful. Hence, people have a high concern on the infection of this disease. The infection information from the governmantal public organizations are mainly based on simple summary statistics. Consequently, it is hard to assess the infection risks of individual person and the current location of the person. In this paper, we present a machine learning-based software system that analyzes COVID-19 infection risks and guidelines for safe activities.This paper proposes a suite of risk factors regarding COVID-19 infection and deaths and methods to quantitatively measure the individual and group risks using the proposed metrics. The proposed system utilizes a clustering algorithms and various software approaches that reflect the information and features of inviduals and their geograpical locations.
Å°¿öµå(Keyword) »çÀ̹ö ÁöÈÖÅëÁ¦Ã¼°è   »çÀ̹ö ųüÀÎ ¸ðµ¨   ¹æ¾î ¸ðµ¨   °ø°Ý ¸ðµ¨   À§Çù ºÐ·ù/ºÐ¼®/¿¹Ãø ÇÁ·¹ÀÓ¿öÅ©   Cyber Command Control System   Cyber Kill Chain Model   Defense Model   Attack Model   threat classification/analysis-   -/prediction framework   ÇàÀ§¼Ò ¸ðµ¨   µîÀåÀι° ¿ªÇÒ ÀνĠ  µîÀåÀι° °ü°è ±×·¡ÇÁ   °¨Á¤ È帧 ±×·¡ÇÁ   Actantial model   Character Role Recognition   Character Relationship Graph   Character Sentiment Flow Graph   COVID-19   ¸Ó½Å ·¯´×   Ŭ·¯½ºÅ͸µ   Risk ºÐ¼®   Safe Activity Áö¿ø   Machine Learning   Clustering   Risk Analytics   Safe Activity Assistance  
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