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13:50 - 15:30
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10:30 - 12:10
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10:30 - 12:10
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10:30 - 12:10
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10:30 - 12:10
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10:30 - 12:10
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10:30 - 12:10
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10:30 - 12:10
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14:10 - 15:30
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14:10 - 15:30
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14:10 - 15:30
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15:30 - 15:50
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¥¢¥Ö¥¹¥È¥é¥¯¥È¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤ä¥¿¥Ö¥ì¥Ã¥È·¿Ã¼Ëö¤ÎÉáµÚ¤Ë¤è¤Ã¤Æ¡¤ÍÍ¡¹¤Ê¾ìÌ̤ǰÌÃÖ¤¬³èÍѤµ¤ì¤ë¤è¤¦¤Ë¤Ê¤Ã¤¿¡¥²æ¡¹¤ÎÌÜŪ¤Ï¸íº¹¿ôcm¤Î¥¹¥Þ¡¼¥È¥Õ¥©¥ó°ÌÃÖ¾ðÊó¤Ë´ð¤Å¤¤¤¿¿·¤¿¤Ê¥µ¡¼¥Ó¥¹¤ÎÁϽФǤ¢¤ë¡¥²æ¡¹¤Ï¤³¤ì¤Þ¤Ç¡¤²óž¼§ÀÐ¥Þ¡¼¥«¤òÍѤ¤¤¿¥¹¥Þ¡¼¥È¥Õ¥©¥ó°ÌÃÖ¿äÄê¼êË¡¤ò¸¦µæ¤·¤Æ¤­¤¿¡¥²óž¼§ÀÐ¥Þ¡¼¥«¤È¤Ï¶¯ÎϤʼ§ÀФò²óž¤µ¤»¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Î¼§µ¤¥»¥ó¥µ¤Ç¸¡ÃβÄǽ¤ÊưŪ¼§µ¤¤òȯÀ¸¤µ¤»¤ëÁõÃ֤Ǥ¢¤ë¡¥²æ¡¹¤Ï°ÊÁ°¤Î¸¦µæ¤Ç¡¤²óž¼§ÀÐ¥Þ¡¼¥«¤òÍѤ¤¤¿¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Î°ÜÆ°·ÐÏ©¿äÄê¼êË¡¤òÄó°Æ¤·¤¿¡¥¤³¤Î°ÊÁ°¤Î¸¦µæ¤Ç¤Ï¡¤¥Ù¥ë¥È¥³¥ó¥Ù¥¢¤òÍѤ¤¤Æ¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤ò°ÜÆ°¤µ¤»¤¿·ë²Ì¡¤²óž¼§ÀÐ¥Þ¡¼¥«¤«¤é1mÎ¥¤ì¤¿Ä¾Àþ·ÐÏ©¤òÊ¿¶Ñ¸íº¹10cm°Ê²¼¤Ç¿äÄꤷ¤¿¡¥Ëܸ¦µæ¤Ç¤Ï¡¤¿Í¤¬¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤ò»ý¤Ã¤Æ°ÜÆ°¤·¤Æ¤¤¤ë¾ì¹ç¤Ë¤Ä¤¤¤Æ¡¤Æ±ÍͤμêË¡¤òÍѤ¤¤Æ°ÜÆ°·ÐÏ©¤ò¿äÄꤷ¡¤¤½¤Î¿äÄêÀºÅÙ¤òɾ²Á¤·¤¿¡¥É¾²Á¼Â¸³¤Î·ë²Ì¡¤²óž¼§ÀÐ¥Þ¡¼¥«¤«¤é¤Îµ÷Î¥¤¬1m¤ÎľÀþ·ÐÏ©¤òÊ⤤¤¿¾ì¹ç¡¤°ÜÆ°·ÐÏ©¤òÊ¿¶Ñ¸íº¹19cm¤Ç¿äÄê¤Ç¤­¤¿¡¥¤Þ¤¿¡¤Äó°Æ¼êË¡¤Î¥í¥Ð¥¹¥ÈÀ­¤òÄ´¤Ù¤ë¤¿¤á¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤ò¥Ý¥±¥Ã¥È¤Ë¼ýǼ¤·¡¤Æ±¤¸·ÐÏ©¤Ç°ÜÆ°·ÐÏ©¤ò¿äÄꤷ¤¿¡¥¤½¤Î·ë²Ì¡¤²óž¼§ÀÐ¥Þ¡¼¥«¤«¤é¤Îµ÷Î¥¤¬1m¤ÎľÀþ·ÐÏ©¤òÊ⤤¤¿¾ì¹ç¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Î½é´ü°ÌÃÖ¤òÊ¿¶Ñ¸íº¹21cm¤Ç¿äÄê²Äǽ¤Ç¤¢¤Ã¤¿¡¥°Ê¾å¤Î¸¡Æ¤¤«¤é¡¤Êâ¹Ô¼Ô¤¬¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤ò½ê»ý¤·¤Æ¤¤¤ë¾ì¹ç¤Ë¤Ä¤¤¤Æ¡¤°ÊÁ°²æ¡¹¤¬Äó°Æ¤·¤¿¼êË¡¤òÍѤ¤¤Æ°ÜÆ°·ÐÏ©¤ò¿äÄê¤Ç¤­¤ë¤³¤È¤ò³Îǧ¤·¤¿¡¥

1B-4 (»þ´Ö: 14:50 - 15:10)
Âê̾¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯¤òÍѤ¤¤¿Â絬ÌÏ¥¤¥Ù¥ó¥È¸þ¤±BLE²°Æâ°ÌÃÖ¿äÄê¤ÎÈæ³Óɾ²Á
Ãø¼Ô*±ºÌî ·òÂÀ, ×¢°æ ·Å, ÊÆß· ÂóϺ (̾¸Å²°Âç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), ²Ï¸ý ¿®É× (̾¸Å²°Âç³Ø̤Íè¼Ò²ñÁϤµ¡¹½)
¥Ú¡¼¥¸pp. 29 - 35
¥­¡¼¥ï¡¼¥ÉBLE, °ÌÃÖ¿äÄê, LSTM
¥¢¥Ö¥¹¥È¥é¥¯¥ÈËܹƤǤϡ¤°ÜÆ°¤¹¤ëBLE¥¿¥°¤«¤é¤Î¥Ñ¥±¥Ã¥È¤ò´Ä¶­Æâ¤ÎÊ£¿ô¤Î¥¹¥­¥ã¥Ê¤Ç¼õ¿®¤·¡¤¼õ¿®¿®¹æ¶¯ÅÙ¤ò»È¤¦BLE²°Æâ°ÌÃÖ¿äÄê¤Ë¤ª¤¤¤Æ¡¤¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯¤òÍѤ¤¤¿¼êË¡¤ò¹Í¤¨¤ë¡¥ÌµÀþÅÅÇȤò»È¤¦°ÌÃÖ¿äÄê¤Ç¤Ï¡¤¼õ¿®¿®¹æ¶¯ÅÙ¤ÎÉÔ°ÂÄꤵ¤¬ÀºÅ٤˱ƶÁ¤¹¤ë¡¥¤½¤³¤Ç¡¤Fingerprint¤ä»°ÅÀ¬°Ì¤ËÂå¤ï¤ê¡¤¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯¤ÎÍøÍѤ¬»î¤ß¤é¤ì¤Æ¤ª¤ê¡¤ÀºÅ٤βþÁ±¤¬Êó¹ð¤µ¤ì¤Æ¤¤¤ë¡¥°ìÊý¤Ç¡¤Â¿¿ô¤Î¿Í¤¬¤¤¤ë¼Â´Ä¶­¤Ø¤ÎÂбþ²ÄǽÀ­¤Ï½½Ê¬¸¡¾Ú¤µ¤ì¤Æ¤¤¤Ê¤¤¡¥¤½¤³¤ÇËܹƤǤϡ¤(1)¥Ç¥Î¥¤¥¸¥ó¥°¥ª¡¼¥È¥¨¥ó¥³¡¼¥À¤È´û¸¼êË¡¤òÁȤ߹ç¤ï¤»¤¿°ÌÃÖ¿äÄê¤È¡¤(2)¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯¤Ë¤è¤ëEnd-to-end¤Î°ÌÃÖ¿äÄê¤òÈæ³Ó¤·¡¤¹âÀºÅ٤˿äÄê¤Ç¤­¤ë¼êË¡¤ò¸¡Æ¤¤¹¤ë¡¥(1)¤Ç¤Ï¡¤¼õ¿®¿®¹æ¶¯ÅÙ¤«¤é¥Î¥¤¥º½üµî¤ä·ç»ÃͤÎÊä´°¤ò¹Ô¤¤´û¸¼êË¡¤Ç°ÌÃÖ¿äÄê¤ò¹Ô¤¦¡¥(2)¤ÏÁ´·ë¹çÁؤÈLSTMÁؤ«¤é¤Ê¤ê¡¤¼õ¿®¿®¹æ¶¯Å٤λþ·ÏÎó¤òÍѤ¤¤Æ°ÌÃÖ¿äÄê¤ò¹Ô¤¦¡¥¥Í¥Ã¥È¥ï¡¼¥¯¤Î³Ø½¬»þ¤Ï¡¤Ã±½ã¤Ê¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤ÇÀ¸À®¤·¤¿¥Ç¡¼¥¿¤Ç¤Î³Ø½¬¤Î¸å¡¤¼Â´Ä¶­¤Ç¼ý½¸¤·¤¿¥Ç¡¼¥¿¤ÇÄɲäγؽ¬¤ò¹Ô¤¦¡¥Â絬ÌÏŸ¼¨²ñ¤Ç¤Î¼Â¸³¥Ç¡¼¥¿¤Ç¤Îɾ²Á¤Ç¤Ï¡¤¥Ç¥Î¥¤¥¸¥ó¥°¥ª¡¼¥È¥¨¥ó¥³¡¼¥À¤È´û¸¼êË¡¤ÎÁȹç¤ï¤»¤ÏÀºÅÙ¤ÇÎô¤ê¡¤End-to-end¤Î¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯¤Î¤Û¤¦¤¬Îɤ¤ÀºÅ٤ǿäÄê¤ò¹Ô¤¨¤¿¡¥

1B-5 (»þ´Ö: 15:10 - 15:30)
Âê̾RSSI-based Localization of BLE-attached HVACs by Utilizing Peak Detection
Ãø¼Ô*Nathavuth Kitbutrawat (Graduate School of Information Science and Technology, Osaka University), Chuanhsin Chen (DAIKIN INDUSTRIES, LTD.), Shugo Kajita, Hirozumi Yamaguchi, Teruo Higashino (Graduate School of Information Science and Technology, Osaka University)
¥Ú¡¼¥¸pp. 36 - 43
¥­¡¼¥ï¡¼¥Élocalization, BLE, RSSI
¥¢¥Ö¥¹¥È¥é¥¯¥ÈNowadays, there is a concern about how to use energy efficiently. Energy management is one of the technologies which play an important role to reduce energy consumption in buildings. For building energy management, there are several technologies which make the resident feel comfortable by controlling HVAC and lighting through IoT. The critical information, which enables such management in a building, is the location of IoT devices. However, the manual location identification manner requires a significant labor effort for a large number of IoT devices deployed in the building. Although the wired network has reliable, low-delay and secured characteristics, it has no property to be used for the localization technique in the physical environment. Hence, Bluetooth Low Energy (BLE) is one of the most popular wireless network modules for IoT devices because it can provide a cost-effective and easy-deployment network. As a signal strength of wireless technology is related to the distance between receiver and transmitter, the BLE modules can be used to generate the signal fingerprint to estimate their locations. In this paper, it is assumed to attach a BLE module to each HVAC individually, and then the location of HVACs can be estimated by observing the signal strength of BLE. We propose a survey mechanism to collect signal propagation. We provide a method to estimate the location of BLE without visiting every place by analyzing the change in signal strength of every BLE. Our method requires the floorplan and physical location of HVAC. We request one tester to carry the smartphone and walk around the building for collecting the signal strength of every BLE. After that our method generates the candidate list of the BLEs to each physical location. We evaluate our algorithm by deploying 26 BLEs in an office building. The results show that the average number of matching BLE candidates for each location is 2.17, which is useful to identify BLEs which cannot be identified by network-based localization.


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Æü»þ: 2019ǯ7·î3Æü(¿å) 13:50 - 15:30
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1C-1 (»þ´Ö: 13:50 - 14:10)
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¥Ú¡¼¥¸pp. 44 - 49
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1C-2 (»þ´Ö: 14:10 - 14:30)
Âê̾ºÙγÅÙ¤ÎÁø¶øÍúÎò¤È¿ä°ÜÀ­¤òÍѤ¤¤¿ÃÙ±äÂÑÀ­¥Í¥Ã¥È¥ï¡¼¥¯¤Î·ÐÏ©À©¸æ¼êË¡
Ãø¼Ô*ÀÐÌî ·òÂÁ, ËÌ¿Ü²ì µ±ÌÀ (¹­ÅçÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 50 - 56
¥­¡¼¥ï¡¼¥ÉÃÙ±äÂÑÀ­¥Í¥Ã¥È¥ï¡¼¥¯, ·ÐÏ©À©¸æ, ¥â¥Ð¥¤¥ë¥³¥ó¥Ô¥å¡¼¥Æ¥£¥ó¥°
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1C-3 (»þ´Ö: 14:30 - 14:50)
Âê̾¼Â¹Ô²ÄǽÀ­¤Î¸¡Æ¤¤òÌÜŪ¤È¤·¤¿¸½¼ÂŪ¤Ê¥È¥Ý¥í¥¸¤Ë¤ª¤±¤ëLow-rate DDoS¹¶·â¤Î¥·¥ß¥å¥ì¡¼¥·¥ç¥ó
Ãø¼Ô*üⶶ ͤÂÀ (¸øΩ¤Ï¤³¤À¤Æ̤ÍèÂç³ØÂç³Ø±¡ ¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ²Ê), °ð¼ ¹À, Ãæ¼ ²Åδ (¸øΩ¤Ï¤³¤À¤Æ̤ÍèÂç³Ø ¥·¥¹¥Æ¥à¾ðÊó²Ê³ØÉô)
¥Ú¡¼¥¸pp. 57 - 63
¥­¡¼¥ï¡¼¥ÉLow-rate DDoS¹¶·â, ¥Í¥Ã¥È¥ï¡¼¥¯¥·¥ß¥å¥ì¡¼¥·¥ç¥ó, TCPíÕíÔÀ©¸æ, ¥Í¥Ã¥È¥ï¡¼¥¯¥»¥­¥å¥ê¥Æ¥£, ¥Í¥Ã¥È¥ï¡¼¥¯¥È¥Ý¥í¥¸
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1C-4 (»þ´Ö: 14:50 - 15:10)
Âê̾ͥÀèÅÙ¤ò¹Íθ¤·¤¿Á÷¿®À©¸æ¤¬²Äǽ¤ÊP-MQTT¤Î³«È¯¤Èɾ²Á
Ãø¼Ô*Æ⻳ ¿Î (ÀŲ¬Âç³ØÂç³Ø±¡Áí¹ç²Ê³Øµ»½Ñ¸¦µæ²Ê), ÊöÌî Çî»Ë (ÀŲ¬Âç³Ø³Ø½Ñ±¡¾ðÊó³ØÎΰè)
¥Ú¡¼¥¸pp. 64 - 70
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1D-1 (»þ´Ö: 13:50 - 14:10)
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1D-2 (»þ´Ö: 14:10 - 14:30)
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1D-3 (»þ´Ö: 14:30 - 14:50)
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1D-4 (»þ´Ö: 14:50 - 15:10)
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1D-5 (»þ´Ö: 15:10 - 15:30)
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1E-3 (»þ´Ö: 14:30 - 14:50)
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1F-1 (»þ´Ö: 13:50 - 14:10)
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1F-2 (»þ´Ö: 14:10 - 14:30)
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Ãø¼Ô*µÜºê ¶¬¹Ô, ËÒÅÄ ³ÙÂç (Ä»¼èÂç³ØÂç³Ø±¡ »ý³À­¼Ò²ñÁÏÀ¸²Ê³Ø¸¦µæ²Ê), ¹â¶¶ ·ò°ì, Àî¼ ¾°À¸, ¿û¸¶ °ì¹¦ (Ä»¼èÂç³Ø ¹©³ØÉôÉÕ°¥¯¥í¥¹¾ðÊó²Ê³Ø¸¦µæ¥»¥ó¥¿¡¼)
¥Ú¡¼¥¸pp. 151 - 157
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1G-1 (»þ´Ö: 13:50 - 14:10)
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1G-2 (»þ´Ö: 14:10 - 14:30)
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¥Ú¡¼¥¸pp. 164 - 169
¥­¡¼¥ï¡¼¥ÉVR, ¿¨³Ð, ¥Ï¥×¥Æ¥£¥¯¥¹, ÎϳÐ, µ¤Î®
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1G-3 (»þ´Ö: 14:30 - 14:50)
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¥Ú¡¼¥¸pp. 170 - 175
¥­¡¼¥ï¡¼¥É²¾ÁÛ¶õ´Ö, Ê£¹ç¸½¼Â, µ¼»÷¿¨³Ð, Pseudo-haptics, ÎϳÐÄó¼¨
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1G-4 (»þ´Ö: 14:50 - 15:10)
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¥Ú¡¼¥¸pp. 176 - 179
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1G-5 (»þ´Ö: 15:10 - 15:30)
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¥Ú¡¼¥¸pp. 180 - 185
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1H-1 (»þ´Ö: 13:50 - 14:10)
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2A-3 (»þ´Ö: 16:50 - 17:10)
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2A-4 (»þ´Ö: 17:10 - 17:30)
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¥­¡¼¥ï¡¼¥É´Ñ¸÷, ´¶¾ð, Ä󼨼êË¡, SNS
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Æü»þ: 2019ǯ7·î3Æü(¿å) 15:50 - 17:30
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2B-1 (»þ´Ö: 15:50 - 16:10)
Âê̾¥ß¥êÇÈÂӤˤª¤±¤ë360ÅÙ±ÇÁüÅÁÁ÷¤Ë´Ø¤¹¤ë¸¡Æ¤
Ãø¼Ô*YuJun Lu (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), ¾®ÎÓ ¿¿ (¹­Åç»ÔΩÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), Æ£¶¶ ÂîÌé, ±îÅÏ ½Ó²ð, ÅÏÊÕ ¾° (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê)
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¥­¡¼¥ï¡¼¥É360-degree video, 60 GHz mmWave, MIMO, HMD
¥¢¥Ö¥¹¥È¥é¥¯¥ÈWith the explosive growth in mobile data demand, wireless multimedia technologies are developing towards providing an immersive experience for the users. 360-degree video delivery, i.e., omnidirectional video delivery, over wireless links is one of the new multimedia techniques to provide an omnidirectional view of three-dimensional scenes for wireless virtual reality applications. Since the resolution and frame rate of 360-degree video are even high, conventional schemes on 360-degree video delivery use digitalbased video compression for traffic reduction. However, a large computation time in the digital-based video compression may degrade the quality of immersive experience because such immersive contents require an extremely low end-to-end latency between the content server and client to realize a good immersion. To realize high-quality and low-delay wireless 360-degree video delivery, this paper proposes a novel system of wireless 360-degree video delivery over millimeter wave (mmWave) networks. Specifically, the proposed system divides the uncompressed 360-degree video into multiple tiles and then assigns the tiles to multiple 60 GHz mmWave antennas placed around the Head Mounted Display (HMD) user based on the user¡Çs direction. Finally, each mmWave antenna sends the assigned tiles to the user based on the 60 GHz channel state information (CSI) and the user¡Çs watching tile. It is demonstrated that our system can provide a sufficient data rate even for 360-degree video with 8K resolution at 60 frames/second (fps) without video compression.

2B-2 (»þ´Ö: 16:10 - 16:30)
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Ãø¼Ô*±üËÜ Íµ²ð (´ØÀ¾Âç³ØÂç³Ø±¡Íý¹©³Ø¸¦µæ²Ê), ÂìÂô ÂÙµ× (´ØÀ¾Âç³Ø´Ä¶­ÅÔ»Ô¹©³ØÉô)
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¥­¡¼¥ï¡¼¥É¥Í¥Ã¥È¥ï¡¼¥¯, MIMO, 5G
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2B-3 (»þ´Ö: 16:30 - 16:50)
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2B-4 (»þ´Ö: 16:50 - 17:10)
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2B-5 (»þ´Ö: 17:10 - 17:30)
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2C-1 (»þ´Ö: 15:50 - 16:10)
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2C-2 (»þ´Ö: 16:10 - 16:30)
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2C-3 (»þ´Ö: 16:30 - 16:50)
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2C-4 (»þ´Ö: 16:50 - 17:10)
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2C-5 (»þ´Ö: 17:10 - 17:30)
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2D-1 (»þ´Ö: 15:50 - 16:10)
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2D-2 (»þ´Ö: 16:10 - 16:30)
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2D-3 (»þ´Ö: 16:30 - 16:50)
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2D-4 (»þ´Ö: 16:50 - 17:10)
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2D-5 (»þ´Ö: 17:10 - 17:30)
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2E-1 (»þ´Ö: 15:50 - 16:10)
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
2E-2 (»þ´Ö: 16:10 - 16:30)
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¥Ú¡¼¥¸pp. 376 - 383
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Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
2E-3 (»þ´Ö: 16:30 - 16:50)
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2E-4 (»þ´Ö: 16:50 - 17:10)
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2E-5 (»þ´Ö: 17:10 - 17:30)
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2F-1 (»þ´Ö: 15:50 - 16:10)
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2F-2 (»þ´Ö: 16:10 - 16:30)
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2H-1 (»þ´Ö: 15:50 - 16:10)
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2H-2 (»þ´Ö: 16:10 - 16:30)
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2H-3 (»þ´Ö: 16:30 - 16:50)
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2H-4 (»þ´Ö: 16:50 - 17:10)
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¥Ú¡¼¥¸pp. 495 - 504
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3A-1 (»þ´Ö: 17:50 - 18:30)
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3A-2 (»þ´Ö: 18:30 - 18:50)
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3A-3 (»þ´Ö: 18:50 - 19:10)
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Æü»þ: 2019ǯ7·î3Æü(¿å) 17:50 - 19:10
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3B-1 (»þ´Ö: 17:50 - 18:10)
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3B-3 (»þ´Ö: 18:10 - 18:30)
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¥Ú¡¼¥¸pp. 530 - 536
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3B-4 (»þ´Ö: 18:30 - 18:50)
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¥Ú¡¼¥¸pp. 537 - 542
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Æü»þ: 2019ǯ7·î3Æü(¿å) 17:50 - 19:10
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3C-1 (»þ´Ö: 17:50 - 18:10)
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3C-2 (»þ´Ö: 18:10 - 18:30)
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¥Ú¡¼¥¸pp. 549 - 558
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3C-3 (»þ´Ö: 18:30 - 18:50)
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Ãø¼Ô*ԢΩ Ã齨 (ÌðºêÁí¶È µ»½Ñ¸¦µæ½ê/ÂçºåÂç³Ø Âç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), ÌÚ²¼ ÏÂɧ (ÆÁÅçÂç³Ø Âç³Ø±¡¼Ò²ñ»º¶ÈÍý¹©³Ø¸¦µæÉô), ÅÏÊÕ ¾° (ÂçºåÂç³Ø Âç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 559 - 564
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Í¥½¨ÏÀʸ¾Þ / Paper Awards
3C-4 (»þ´Ö: 18:50 - 19:10)
Âê̾NOMA¤òÍѤ¤¤¿BackscatterÄÌ¿®·¿¥»¥ó¥µ¥Í¥Ã¥È¥ï¡¼¥¯¤Î¸¡Æ¤
Ãø¼Ô*Àîºê »ü±Ñ (ÂçºåÂç³ØÂç³Ø±¡ ¾ðÊó²Ê³Ø¸¦µæ²Ê), ¾®ÎÓ ¿¿ (¹­Åç»ÔΩÂç³ØÂç³Ø±¡ ¾ðÊó²Ê³Ø¸¦µæ²Ê), ±îÅÏ ½Ó²ð, ÅÏÊÕ ¾° (ÂçºåÂç³ØÂç³Ø±¡ ¾ðÊó²Ê³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 565 - 572
¥­¡¼¥ï¡¼¥ÉBackscatterÄÌ¿®, NOMA (Non-orthogonal Multiple Access), ̵Àþ¥»¥ó¥µ¥Í¥Ã¥È¥ï¡¼¥¯
¥¢¥Ö¥¹¥È¥é¥¯¥È¤¢¤ê¤È¤¢¤é¤æ¤ë¥â¥Î¤ò¥Í¥Ã¥È¥ï¡¼¥¯¤Ë¤Ä¤Ê¤°¤¿¤á¤Ë¤Ï¡¤ÌµÀþ¥»¥ó¥µ¥Í¥Ã¥È¥ï¡¼¥¯¤Ë¤ª¤±¤ëÅŸ»ÌäÂê¤Î²ò·è¤¬É¬¿Ü¤Ç¤¢¤ë¡¥É®¼Ô¤é¤ÏÈù¾®¤ÊÅÅÎϤÇÄÌ¿®¤ò¹Ô¤¦BackscatterÄÌ¿®¤È¹±¾ïŪ¤Ë¾®¤µ¤¤ÅÅÎϤò¥»¥ó¥µ¤Ë¶¡µë½ÐÍè¤ëÅÅÇÈȯÅŤòÁȤ߹ç¤ï¤»¤ë¤³¤È¤ÇÅŸ»ÌäÂê¤Î²ò·è¤òÌܻؤ·¤Æ¤¤¤ë¡¥¤·¤«¤·¤Ê¤¬¤é¡¤BackscatterÄÌ¿®¤Ë¤ÏÄÌ¿®ÈϰϤ¬¶¹¤¤¤È¤¤¤¦ÌäÂê¤È¾×ÆͲóÈò¤ÎÌäÂ꤬¸ºß¤¹¤ë¡¥¤³¤ì¤é¤ÎÌäÂê¤ò²ò·è¤¹¤ë¤¿¤á¤Ë¡¤Ê£¿ô¤Î¥¢¥¯¥»¥¹¥Ý¥¤¥ó¥È¤Ç¥¢¥Ã¥×¥ê¥ó¥¯NOMA (Non-orthogonal Multiple Access)¤òÍøÍѤ¹¤ë¤³¤È¤Ç¹­ÈϰϤǤâ¥Ñ¥±¥Ã¥È¥¨¥é¡¼Î¨¤¬Ä㤯¡¤¥¹¥ë¡¼¥×¥Ã¥È¤¬¹â¤¤BackscatterÄÌ¿®·¿¥»¥ó¥µ¥Í¥Ã¥È¥ï¡¼¥¯¤òÄó°Æ¤¹¤ë¡¥¶ñÂÎŪ¤Ë¤Ï¡¤Ê£¿ô¤Î¥¢¥¯¥»¥¹¥Ý¥¤¥ó¥È¤òʬ»¶¤µ¤»¤ÆÀßÃÖ¤¹¤ë¤³¤È¤ÇBackscatterÄÌ¿®¤ÎÄÌ¿®ÈϰϤÎÌäÂê¤ò²ò·è¤·¤Æ¡¤Ê£¿ô¤Î¥¢¥¯¥»¥¹¥Ý¥¤¥ó¥È¤¬¥Ç¡¼¥¿¤ò¶¦Í­¤·¤Ê¤¬¤é¥¢¥Ã¥×¥ê¥ó¥¯NOMA¤ò¹Ô¤¦¤³¤È¤Ç¾×ÆͲóÈò¤ÎÌäÂê¤ò²ò·è¤¹¤ë¡¥·×»»µ¡¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤Î·ë²Ì¡¤NOMA¤òŬÍѤ·¤Æ¤¤¤Ê¤¤Ã±°ì¤Î¥¢¥¯¥»¥¹¥Ý¥¤¥ó¥È¤Î¥·¥¹¥Æ¥à¤ÈÈæ³Ó¤·¤ÆÌó4ÇܤΥ¹¥ë¡¼¥×¥Ã¥È¤òãÀ®¤¹¤ë¤³¤È¤ò³Îǧ¤·¤¿¡¥


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Æü»þ: 2019ǯ7·î3Æü(¿å) 17:50 - 19:10
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ºÂĹ: ´ßÌî ¹¯·Ã (NTT)

3D-2 (»þ´Ö: 17:50 - 18:10)
Âê̾´Ç¸î¶È̳Ééô¤ÎÄêÎÌŪ·×¬¤Ë¸þ¤±¤¿¥¦¥§¥¢¥é¥Ö¥ë¶ÚÅŰ̷׬¤Î´ðÁø¡¾Ú
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¥Ú¡¼¥¸pp. 573 - 578
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3D-3 (»þ´Ö: 18:10 - 18:30)
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Ãø¼Ô*±ÝË٠ͥ (̾¸Å²°Âç³ØÂç³Ø±¡ ¾ðÊó³Ø¸¦µæ²Ê), º£°æ ÎÊ (̾¸Å²°Âç³Ø ¹©³ØÉô Åŵ¤ÅŻҡ¦¾ðÊ󹩳زÊ), ¿¹ÅÄ ½ãºÈ (ÀŲ¬Âç³Ø ¾ðÊó³ØÉô ¹ÔÆ°¾ðÊó³Ø²Ê), »³¸ý ͦ¿Í, ³á ÍÎδ (¥È¥è¥¿¼«Æ°¼Ö³ô¼°²ñ¼Ò ̤ÍèÁÏÀ¸¥»¥ó¥¿¡¼), ´ÖÀ¥ ·òÆó (̾¸Å²°Âç³ØÂç³Ø±¡ ¾ðÊó³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 579 - 586
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3D-4 (»þ´Ö: 18:30 - 18:50)
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Ãø¼Ô*Àî°æ ÌÀ (¼¢²ìÂç³Ø¥Ç¡¼¥¿¥µ¥¤¥¨¥ó¥¹³ØÉô), ë¸ý ¿­°ì, Íû ·ÅÎï (¼¢²ìÂç³ØÂç³Ø±¡·ÐºÑ³Ø¸¦µæ²Ê), ÏÂÀô »ÖÄÅ·Ã (¼¢²ìÂç³Ø¥Ç¡¼¥¿¥µ¥¤¥¨¥ó¥¹³ØÉô)
¥Ú¡¼¥¸pp. 587 - 594
¥­¡¼¥ï¡¼¥É¹âÎð¼Ô, ¿ÈÂάÎÌ, Kinect, Scratch
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¥»¥Ã¥·¥ç¥ó 3E  ¥¹¥Þ¡¼¥È´Ä¶­
Æü»þ: 2019ǯ7·î3Æü(¿å) 17:50 - 19:10
Éô²°: Í·Éñ¡¦¸Þ¤ÎÍ·
ºÂĹ: ¸¶ ľ (²¬»³Âç³Ø)

3E-1 (»þ´Ö: 17:50 - 18:10)
Âê̾A Privacy Control Method based on K-Anonymity for Smart Home
Ãø¼Ô*Sopicha Stirapongsasuti, Wataru Sasaki, Keiichi Yasumoto (Nara Institute of Science and Technology)
¥Ú¡¼¥¸pp. 595 - 600
¥­¡¼¥ï¡¼¥ÉSmart home, Privacy Control, K-anonymity
¥¢¥Ö¥¹¥È¥é¥¯¥ÈSmart home equipped with various smart devices (sensors, connected appliances, etc) is attracting attention thanks to its ability to provide smart services like automatic life logging, elderly monitoring and smart appliance control. It is very useful for a service provider to automatically identify daily living activities from sensor/appliance data in a home to provide such smart services, but at the same time it is risky for each home dweller (user) to upload all the data generated in a home because the high-privacy information might be exposed to malicious attackers. In this paper, we define a threat model for smart home users where a malicious attacker(s) can access all or part of the smart home data uploaded to the untrusted cloud server (service provider) and at the same time can physically observe part of the activities from outside through lighting over window, water/power meter counter, and so on, hence the attacker can identify the association between the data in the cloud server and the home by matching the uploaded data and the physically observed data. Then, we propose a privacy control method for smart home users to take measures to the threat. The proposed method is based on k-anonymity which is a well-known property of the data often used for protecting location privacy and guarantees that the attacker cannot narrow down the number of applicable people within k when trying to identify the person from the data. In the proposed method, targeting a residential area with a number of smart homes, for each pair (a,t) of an activity a and a time period t, the number of the homes/users which/who are doing a at t is computed as k and the value of k is shown to the inhabitant doing a at t for making decision on if he/she may upload the data of (a,t) to the cloud or not. In order to know an appropriate threshold of k for upload/no-upload for each pair (a, t), we computed values of k from the existing smart home dataset and asked 15 participants to answer upload/no-upload for each pair of activity and time period by showing the computed value of k. As a result, we confirmed that our method based k-anonymity can help privacy control for activities data generated in smart home.

3E-2 (»þ´Ö: 18:10 - 18:30)
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Ãø¼Ô*º´Ìî ¾ÄÆó (¶âÂô¹©¶ÈÂç³Ø¹©³ØÉô), »ûÅÄ ÅØ, ÄÍËÜ ¾»É§ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 601 - 607
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3E-3 (»þ´Ö: 18:30 - 18:50)
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3E-4 (»þ´Ö: 18:50 - 19:10)
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3F-1 (»þ´Ö: 17:50 - 18:10)
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3F-2 (»þ´Ö: 18:10 - 18:30)
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¥Ú¡¼¥¸pp. 629 - 636
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Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
3F-3 (»þ´Ö: 18:30 - 18:50)
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¥Ú¡¼¥¸pp. 637 - 643
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¥Ú¡¼¥¸pp. 644 - 648
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Æü»þ: 2019ǯ7·î3Æü(¿å) 17:50 - 19:10
Éô²°: Í·Éñ¡¦°ì¤ÎÍ·
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3G-1 (»þ´Ö: 17:50 - 18:10)
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Ãø¼Ô*Ê¡Åç Âó, »³º¬ ͥʹ (Âçºå¹©¶ÈÂç³Ø), ¢±Ê Æ· (¼¢²ìÂç³Ø)
¥Ú¡¼¥¸pp. 649 - 655
¥­¡¼¥ï¡¼¥É´¶¼ÕÆüµ­, ¹¬Ê¡´¶, ¶¦Í­
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
3G-2 (»þ´Ö: 18:10 - 18:30)
Âê̾ÂÐÏäˤª¤±¤ë¾å¼ê¤¤Ë«¤áÊý¤Î¥â¥Ç¥ê¥ó¥°¤Î´ðÁø¡Æ¤
Ãø¼Ô*ÂçÀ¾ ½Óµ±, ¼ÆÅÄ ËüΤÆá (ÆüËÜÂç³ØʸÍý³ØÉô), ¸â ·òϯ (ÆüËÜÂç³ØÂç³Ø±¡Áí¹ç´ðÁòʳظ¦µæ²Ê), Àаæ μ, ÉÙÅÄ ½àÆó (ÆüËÜÅÅ¿®ÅÅÏóô¼°²ñ¼Ò NTT¥á¥Ç¥£¥¢¥¤¥ó¥Æ¥ê¥¸¥§¥ó¥¹¸¦µæ½ê), µÜÅÄ ¾Ï͵ (ÆüËÜÂç³ØʸÍý³ØÉô)
¥Ú¡¼¥¸pp. 656 - 662
¥­¡¼¥ï¡¼¥É¥³¥ß¥å¥Ë¥±¡¼¥·¥ç¥ó, ¥Þ¥ë¥Á¥â¡¼¥À¥ë¥¤¥ó¥¿¥é¥¯¥·¥ç¥ó, ÂÐÏÃ¥³¡¼¥Ñ¥¹, Ë«¤á¤ë
¥¢¥Ö¥¹¥È¥é¥¯¥ÈÂÐÏäˤª¤¤¤ÆË«¤á¤ë¤³¤È¤Ï½ÅÍפǤ¢¤ë¡¥Ë«¤á¤ë¤³¤È¤ÇÁê¼ê¤¬¿´¤ò³«¤­¡¤Ïä¬ÃƤߡ¤¤½¤Î¸å¤Î¿Í´Ö´Ø·¸¤¬±ß³ê¤Ë¤Ê¤ë¤³¤È¤¬´üÂÔ¤µ¤ì¤ë¡¥¤·¤«¤·¡¤ÂÐÏäˤª¤¤¤ÆÁê¼ê¤ò¾å¼ê¤¯Ë«¤á¤ë¤¿¤á¤Ë¡¤È¯ÏÃÆâÍÆ¡¤À¼¿§¡¤É½¾ð¡¤»ÑÀª¡¤¥¸¥§¥¹¥Á¥ã¤È¤¤¤Ã¤¿Â¿Íͤʥâ¥À¥ê¥Æ¥£¤ò¤É¤Î¤è¤¦¤ËÍѤ¤¤ì¤ÐÎɤ¤¤«ÌÀ¤é¤«¤Ë¤Ï¤µ¤ì¤Æ¤¤¤Ê¤¤¡¥Ëܸ¦µæ¤Ç¤Ï¡¤¤³¤ì¤é¤Î¿Íͤʥâ¥À¥ê¥Æ¥£¤òÍѤ¤¤¿¾å¼ê¤¤Ë«¤áÊý¤ò¥â¥Ç¥ê¥ó¥°¤¹¤ë¼êË¡¤Î³ÎΩ¤òÌܻؤ¹¡¥¼êË¡¤Î³ÎΩ¤Ë¤¢¤¿¤ê¡¤Ë«¤áÊý¤Î¾å¼ê¤µ¤Îɾ²Á¤ò¡¤¶ñÂÎŪ¤Ë¤É¤Î¤è¤¦¤ÊÍ×ÁǤǬ¤ë¤Ù¤­¤«¡¤¤É¤ÎÍ×ÁǤò¤É¤ÎÄøÅٽŻ뤹¤Ù¤­¤«¤òÌÀ¤é¤«¤Ë¤¹¤ë¤³¤È¤¬½ÅÍפǤ¢¤ë¡¥¾å¼ê¤¤Ë«¤áÊý¤Ë½ÅÍפÊÍ×ÁǤϷи³Åª¤Ë¼¨¤µ¤ì¤ë¤³¤È¤¬¤¢¤ë¤¬¡¤¤½¤ì¤é¤Ï¤¢¤¯¤Þ¤Ç¤âÄêÀ­Åª¤Ë¼¨¤µ¤ì¤¿¤â¤Î¤Ç¤¢¤ë¤¿¤á¡¤¤É¤ì¤¯¤é¤¤½ÅÍפǤ¢¤ë¤Î¤«ÄêÎÌŪ¤Ë¼¨¤¹¤³¤È¤Ï¹Ô¤ï¤ì¤Æ¤¤¤Ê¤¤¡¥¤è¤Ã¤ÆËܹƤǤϡ¤ÄêÀ­Åª¤Ë¼¨¤µ¤ì¤¿¾å¼ê¤¤Ë«¤áÊý¤Ë½ÅÍפÊÍ×ÁǤˤĤ¤¤Æ¡¤¤½¤ì¤éÍ×ÁǤ¬¤É¤ÎÄøÅÙ½ÅÍפǤ¢¤ë¤Î¤«¤òÄêÎÌŪ¤Ë¸¡¾Ú¡¤²òÌÀ¤¹¤ë¼è¤êÁȤߤò¹Ô¤Ã¤¿¡¥¶ñÂÎŪ¤Ë¤Ï¡¤20̾ʬ¡Ê·×100ʬ´Ö¡Ë¤Î2¼ÔÂÐÏÃ¥³¡¼¥Ñ¥¹¤ò¹½ÃÛ¤·¡¤¾å¼ê¤¯Ë«¤á¤ë¤¿¤á¤Ë¤Ï¡¤¤É¤ÎÍ×ÁǤò¤É¤ÎÄøÅٽŻ뤹¤Ù¤­¤«¤òɾ²Á¤¹¤ë¤³¤È¤Ç¡¤ÄêÎÌŪ¤ËÌÀ¤é¤«¤Ë¤·¤¿¡¥ÄêÎÌŪ¤ËÌÀ¤é¤«¤Ë¤¹¤ë¼êË¡¤È¤·¤Æ¡¤¾å¼ê¤¯Ë«¤á¤ë¥¹¥³¥¢¤ÈÍ×ÁǤÎÁê´ØʬÀϤȽŲóµ¢Ê¬ÀϤòÍѤ¤¤¿¡¥·ëÏÀ¤È¤·¤Æ¡¤ÍѤ¤¤¿Í×ÁǤϤɤì¤âÁê¼ê¤ò¾å¼ê¤¯Ë«¤á¤ë¤Ë¤ÏÍ­¸ú¤Ç¤¢¤ê¡¤Æäˡ¤Ä¾ÀÜÀ­¡¤É¬Í×À­¡¤É½¾ð¤ÎË­¤«¤µ¤¬½ÅÍפǤ¢¤ë¤³¤È¤¬Ê¬¤«¤Ã¤¿¡¥

3G-3 (»þ´Ö: 18:30 - 18:50)
Âê̾ÉÔÌû²÷¤µ¤òÍѤ¤¤¿ÆþÎÏÂ¥¿Ê¥·¥¹¥Æ¥à¤Î´Ê°×¼Â¸³
Ãø¼Ô*¼ò°æ ¹ÌÊ¿ (Ä»¼èÂç³ØÂç³Ø±¡ »ý³À­¼Ò²ñÁÏÀ¸²Ê³Ø¸¦µæ²Ê), ¾¾±Ê ¿ò½¨, ¹â¶¶ ·ò°ì, Àî¼ ¾°À¸, ¿û¸¶ °ì¹¦ (Ä»¼èÂç³ØÂç³Ø±¡ ¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 663 - 669
¥­¡¼¥ï¡¼¥ÉÆþÎÏÂ¥¿Ê, ÉÔÌû²÷
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3G-4 (»þ´Ö: 18:50 - 19:10)
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Ãø¼Ô*º´Æ£ ̯, ÀÄÌÚ ÎÉÊå (NTT¥µ¡¼¥Ó¥¹¥¨¥Ü¥ê¥å¡¼¥·¥ç¥ó¸¦µæ½ê), ¾®°Â ½¡ÆÁ, ¼Äùõ °ì·Ä, ÂçÅç ľ¼ù, ÉðÀî ľ¼ù (ÅìµþÅŵ¡Âç³Ø), ÅÏÉô ÃÒ¼ù, ¸¤Æ¸ ÂóÌé (NTT¥µ¡¼¥Ó¥¹¥¨¥Ü¥ê¥å¡¼¥·¥ç¥ó¸¦µæ½ê)
¥Ú¡¼¥¸pp. 670 - 675
¥­¡¼¥ï¡¼¥É¹ÔÆ°ÊÑÍÆ, ¹ÔÆ°ÊÑÍÆ¥¹¥Æ¡¼¥¸¥â¥Ç¥ë, ǧÃÎŪÉÔ¶¨ÏÂ, ¥á¥Ã¥»¡¼¥¸À¸À®
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¥»¥Ã¥·¥ç¥ó 3H  ¥»¥­¥å¥ê¥Æ¥£¿´Íý³Ø¡¦¶µ°é
Æü»þ: 2019ǯ7·î3Æü(¿å) 17:50 - 19:10
Éô²°: ³ÚÉñ¡¦°ì¤Î³Ú
ºÂĹ: ¶â²¬ ¹¸ (ÅìË®Âç³Ø)

3H-1 (»þ´Ö: 17:50 - 18:10)
Âê̾´í¸±²óÈò¤Î¤¿¤á¤ÎŬÀÚ¤ÊÉÔ²÷´¶¤ò¹Íθ¤·¤¿ÉÔ²÷¤Ê¥¤¥ó¥¿¥Õ¥§¡¼¥¹¤Î¼ÂÁõ
Ãø¼Ô*À¾²¬ Âç (´ä¼ê¸©Î©Âç³Ø¥½¥Õ¥È¥¦¥§¥¢¾ðÊó³ØÉô), ¾®À¥Àî Êâ¼Â (´ä¼ê¸©Î©Âç³Ø ¥½¥Õ¥È¥¦¥§¥¢¾ðÊó³ØÉô), óîÆ£ µÁ¶Ä (´ä¼ê¸©Î©Âç³Ø¥½¥Õ¥È¥¦¥§¥¢¾ðÊó³ØÉô)
¥Ú¡¼¥¸pp. 676 - 681
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3H-2 (»þ´Ö: 18:10 - 18:30)
Âê̾¥ª¥ó¥é¥¤¥ó¥·¥ç¥Ã¥Ô¥ó¥°¥µ¥¤¥È¤òÂоݤˤ·¤¿¾ðÊ󥻥­¥å¥ê¥Æ¥£¤ËÂФ¹¤ë°Â¿´´¶¤ò²Ä»ë²½¤¹¤ë¡Ö°Â¿´¥á¡¼¥¿¡×¤Î³«È¯
Ãø¼Ô*Â绳 ¿µÌé (´ä¼ê¸©Î©Âç³ØÂç³Ø±¡ ¥½¥Õ¥È¥¦¥§¥¢¾ðÊó³Ø¸¦µæ²Ê), µÆÆâ Åí»Ò (´ä¼ê¸©Î©Âç³Ø¥½¥Õ¥È¥¦¥§¥¢¾ðÊó³ØÉô), óîÆ£ µÁ¶Ä, À¾²¬ Âç (´ä¼ê¸©Î©Âç³ØÂç³Ø±¡ ¥½¥Õ¥È¥¦¥§¥¢¾ðÊó³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 682 - 687
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
3H-3 (»þ´Ö: 18:30 - 18:50)
Âê̾¾ðÊ󥻥­¥å¥ê¥Æ¥£Âкö¹Ô°Ù¤¬¿Í¤ËµÚ¤Ü¤¹ÈèÏ«¤Î¸¦µæ
Ãø¼Ô*Ê¡±Ê ²Æ³¤, Çò°æ ãÌé, ¶â°æ ÆØ (Ë¡À¯Âç³Ø), ȪÅç δ (NTT¥»¥­¥å¥¢¥×¥é¥Ã¥È¥Õ¥©¡¼¥à¸¦µæ½ê), ëËÜ ÌÐÌÀ (ÀéÍÕ¹©¶ÈÂç³Ø)
¥Ú¡¼¥¸pp. 688 - 694
¥­¡¼¥ï¡¼¥É¾ðÊ󥻥­¥å¥ê¥Æ¥£ÈèÏ«, Security Fatigue, ¥ê¥¹¥¯¥¢¥»¥¹¥á¥ó¥È
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Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
3H-4 (»þ´Ö: 18:50 - 19:10)
Âê̾¾®³Ø¹»¹â³Øǯ¤òÂоݤȤ·¤¿SNS¶µ°é¥²¡¼¥à¤Î³«È¯¡Ê¤½¤Î2¡Ë
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¥Ú¡¼¥¸pp. 695 - 702
¥­¡¼¥ï¡¼¥ÉSNS, ¥²¡¼¥ß¥Õ¥£¥±¡¼¥·¥ç¥ó, ¶µ°é, ¾®³Ø¹»¹â³Øǯ
¥¢¥Ö¥¹¥È¥é¥¯¥È¿Æ¤«¤éÍ¿¤¨¤é¤ì¤¿¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤ò»È¤Ã¤ÆSNS ¤òÍøÍѤ¹¤ë¾®³Ø¹»¹â³Øǯ¤Î³ä¹ç¤¬Áý²Ã¤·¤Æ¤¤¤ë¡¥SNS ¤òÍøÍѤ¹¤ëºÝ¤Ë¤Ï¾ðÊó¥â¥é¥ë¡ÊÎÑÍý¡¤Ë¡¤ÎÍý²ò¤È½å¼é¡¤¾ðÊ󥻥­¥å¥ê¥Æ¥£¤ÎÃμ±¤Èµ»Ç½¡Ë¤¬É¬ÍפǤ¢¤ë¤³¤È¤«¤é¡¤Ê¸Éô²Ê³Ø¾Ê¤Ï³Ø½¬»ØƳÍ×ÎΤòÄ̤·¤Æ¾ðÊó¥â¥é¥ë¶µ°é¤ò¿ä¿Ê¤·¤Æ¤¤¤ë¡¥°ìÊý¡¤¶µ°é¸½¾ì¤Ç»ÈÍѤµ¤ì¤Æ¤¤¤ë¶µºà¤Î¤Û¤È¤ó¤É¤Ïºý»Ò¤äDVD ¤Ç¤¢¤ë¤¿¤á¡¤Í×ÎΤΥ³¥ó¥»¥×¥È¤Ç¤¢¤ë¡Ö¼çÂÎŪ¡¦ÂÐÏÃŪ¤Ç¿¼¤¤³Ø¤Ó¡×¤¬¼Â¸½¤Ç¤­¤Æ¤¤¤ë¤È¤Ï¸À¤¤¤Ë¤¯¤¤¡¥Ëܸ¦µæ¤Ç¤Ï¡¤¼ÂÁ©Åª¤«¤Ä¡Ö¼çÂÎŪ¡¦ÂÐÏÃŪ¤Ç¿¼¤¤³Ø¤Ó¡×¤ò¼Â¸½¤¹¤ë¤¿¤á¤ËSNS ¶µ°é¥²¡¼¥à¤ò³«È¯¤¹¤ë¡¥Åö³º¥²¡¼¥à¤Ï¡¤¾®³Ø¹»¹â³Øǯ¤ÎÆÃħ¡¤´û¸¶µ°é¥²¡¼¥à¤ÎÆÃĹ¤È²ÝÂê¤òƧ¤Þ¤¨¤Ä¤Ä¡Ö¼çÂÎŪ¡¦ÂÐÏÃŪ¤Ç¿¼¤¤³Ø¤Ó¡×¤ò¼Â¸½¤¹¤ë6 ¤Ä¤Î¾ò·ï¤òËþ¤¿¤¹¤è¤¦¤ËÀ߷פ¹¤ë¡¥Ãø¼Ô¤é¤Ï¡¤¥Î¥Ù¥ë¥²¡¼¥à³«È¯¥½¥Õ¥È¥¦¥§¥¢¤ò»È¤Ã¤Æ´ðËÜŪ¤Ê¶µ°é¥²¡¼¥à¤òºîÀ®¤·¤¿¡¥



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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 8:30 - 10:10
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ºÂĹ: ½ÅÌî ´² (·ÄØæµÁ½ÎÂç³Ø)

4A-1 (»þ´Ö: 8:30 - 9:10)
Âê̾(¾·ÂÔ¹Ö±é) ¼«Æ°±¿Å¾¥í¥¸¥Ã¥¯¤Î³«È¯¡¦É¾²Á¤ò¤É¤¦¤¹¤ë¤« ¡Á³Ø½¬¡¦É¾²ÁÍÑÁö¹Ô¥Ç¡¼¥¿¥Ù¡¼¥¹¤Î¹½ÃÛ¡Á
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¥Ú¡¼¥¸pp. 703 - 712
¥­¡¼¥ï¡¼¥É¼«Æ°±¿Å¾, ɾ²Á, ¥Ç¡¼¥¿¥Ù¡¼¥¹
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Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
4A-2 (»þ´Ö: 9:10 - 9:30)
Âê̾¥»¥ë¥éV2X¤ÈDSRC¤òÊ»ÍѤ·¤¿¼Ö¼Ö´ÖÄÌ¿®¤Ë¤è¤ë¶¹°èƻϩ¡¦¸òÄ̾ðÊó¤Î¸úΨŪ¤ÊÇÛ¿®Êý¼°¤ÎÄó°Æ¤Èɾ²Á
Ãø¼Ô*¹âÁðÌÚ À¯»Ë, Åò ÁÇ²Ú (Åŵ¤ÄÌ¿®Âç³Ø/Âç³Ø±¡¾ðÊóÍý¹©³Ø¸¦µæ²Ê), ¾åÌî ¹âÌÀ, Âç´ß ÃÒɧ (³ô¼°²ñ¼ÒKDDIÁí¹ç¸¦µæ½ê/¥³¥Í¥¯¥Æ¥£¥Ã¥É¥«¡¼£²¥°¥ë¡¼¥×), ¾®²Ö ÄçÉ× (Åŵ¤ÄÌ¿®Âç³Ø/Âç³Ø±¡¾ðÊóÍý¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 713 - 719
¥­¡¼¥ï¡¼¥É¼Ö¼Ö´ÖÄÌ¿®, ¥»¥ë¥éV2X, DSRC
¥¢¥Ö¥¹¥È¥é¥¯¥È700MHz°ÂÁ´±¿Å¾»Ù±ç¥·¥¹¥Æ¥à¤ä5.8GHzÀìÍѶ¹°èÄÌ¿®¡ÊDSRC¡Ë¤Ï¡¤½¾Í褫¤é¼ç¤¿¤ë¼Öξ¥Í¥Ã¥È¥ï¡¼¥¯¤È¤·¤Æ¸¡Æ¤¤µ¤ì¤Æ¤¤¤ë¤¬¡¤¶áǯÏÃÂê¤È¤Ê¤Ã¤Æ¤¤¤ë¥»¥ë¥éV2X(LTE support for V2X services)¤Ë¤è¤ë¼Ö¼Ö´ÖÄÌ¿®¤Ç¤Ï¡¤¼ÖξƱ»Î¤¬Ä¾ÀÜÄÌ¿®¤ò¹Ô¤¦¥µ¥¤¥É¥ê¥ó¥¯Êý¼°¤È¡¤´ðÃ϶ɤò·Ðͳ¤·¤Æ¹­ÈÏ°Ï¤Ë¥Ö¥í¡¼¥É¥­¥ã¥¹¥È¤¹¤ë2Êý¼°¤¬¸¡Æ¤¤µ¤ì¤Æ¤¤¤ë¡¥ËÜȯɽ¤Ç¤Ï¡¤Ã»¤¤µ÷Î¥¤ØÁÇÁ᤯¾ðÊó¤òÆϤ±¤ë DSRC(IEEE802.11p)¤È´ðÃ϶ɤò·Ðͳ¤·¤Æ¹­ÈϰϤ˾ðÊó¤òÆϤ±¤ë¥»¥ë¥éV2X¤Ë¤ª¤±¤ë¥Ö¥í¡¼¥É¥­¥ã¥¹¥È¤òÊ»ÍѤ·¤Æ¶¹°èƻϩ¡¦¸òÄ̾ðÊó¤òÄãÃٱ䡦¹â¿®Íê¤ËÇÛ¿®¤¹¤ë´ðËÜÊý¼°¤òÄó°Æ¤¹¤ë¡¥¤µ¤é¤Ë¤¹¤Ù¤Æ¤Î¾ðÊó¤ò¥¨¥ê¥¢Á´°è¤ØÇÛ¿®¤¹¤ëºÝ¤ÎÈó¸úΨÌäÂê¤È¶áÎÙ¼Öξ´Ö¤ÇƱ¤¸¥¤¥Ù¥ó¥È¤ËÂФ¹¤ë½ÅÊ£ÇÛ¿®ÌäÂê¤ò¤½¤ì¤¾¤ìÇÛÉÛÈÏ°ÏÀ©¸æ¤È½ÅÊ£ÇÛ¿®À©¸æ¤òÍѤ¤¤ÆÇÛ¿®¸úΨ¤ò¸þ¾å¤µ¤»¤ë³ÈÄ¥Êý¼°¤òÄó°Æ¤¹¤ë¡¥É¾²Á¤Î·ë²Ì¡¤´ðËÜÄó°ÆÊý¼°¤Î¤¦¤ÁDSRC¤òÍѤ¤¤¿Êý¼°¤Ï´ðÃ϶ɷÐͳÇÛ¿®¤ÈÈæ³Ó¤·¤ÆÃÙ±ä»þ´Ö¤òºÇÂç75%ºï¸º¤·¡¤³ÈÄ¥Äó°ÆÊý¼°¤Ï´ðËÜÄó°ÆÊý¼°¤ÈÈæ³Ó¤·¤Æ¥¤¥Ù¥ó¥È¼õ¿®À®¸ùΨ¤òºÇÂç11%¸þ¾å¤µ¤»¤ë¤³¤È¤¬¤ï¤«¤Ã¤¿¡¥

4A-3 (»þ´Ö: 9:30 - 9:50)
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Ãø¼Ô*¸¶ ·½ÈÏ (¿ÀÆàÀ²ÊÂç³ØÂç³Ø±¡ À¶¸¶¸¦µæ¼¼), À¶¸¶ ÎÉ»° (¿ÀÆàÀ²ÊÂç³Ø)
¥Ú¡¼¥¸pp. 720 - 726
¥­¡¼¥ï¡¼¥ÉITS, ÆóÎؼÖ, ¸òÄÌή, ¥Þ¥ë¥Á¥¨¡¼¥¸¥§¥ó¥È¥·¥ß¥å¥ì¡¼¥¿, V2X
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 8:30 - 10:10
Éô²°: ²ÖÉñ¡¦°ì¤Î²Ö
ºÂĹ: Àî¾å ÊþÌé (NAIST)

¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
Í¥½¨ÏÀʸ¾Þ / Paper Awards
4B-1 (»þ´Ö: 8:30 - 8:50)
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Ãø¼Ô*Ĺ ͵ÉÒ, »³¼¼ ·ò, Æ⻳ ´²Ç· (ÆüËÜÅÅ¿®ÅÅÏà ¥½¥Õ¥È¥¦¥§¥¢¥¤¥Î¥Ù¡¼¥·¥ç¥ó¥»¥ó¥¿)
¥Ú¡¼¥¸pp. 727 - 733
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4B-2 (»þ´Ö: 8:50 - 9:10)
Âê̾´°Á´½àƱ·¿°Å¹æ¤òÍѤ¤¤¿ÉѽХѥ¿¡¼¥ó¥Þ¥¤¥Ë¥ó¥°¤Î¼ÂÁõ¼êË¡¤Ë¤è¤ëÈæ³Ó
Ãø¼Ô*¼ï¼ ¿¿Í³»Ò, ¾®¸ý Àµ¿Í (¤ªÃã¤Î¿å½÷»ÒÂç³Ø)
¥Ú¡¼¥¸pp. 734 - 739
¥­¡¼¥ï¡¼¥É´°Á´½àƱ·¿°Å¹æ, ÉѽХѥ¿¡¼¥ó¥Þ¥¤¥Ë¥ó¥°, FP-growth
¥¢¥Ö¥¹¥È¥é¥¯¥È¥Ó¥Ã¥°¥Ç¡¼¥¿¤Ê¤É¡¤Â絬ÌϤʥǡ¼¥¿¤Î¼ý½¸¡¦Ê¬ÀϤˤè¤ëÍø³èÍѤ¬¥Ó¥¸¥Í¥¹¤Ê¤É¤ÎʬÌî¤Ç¿Ê¤ó¤Ç¤¤¤ë¡¥Â絬ÌϤʥǡ¼¥¿¤ò°·¤¦·×»»¤Ë¤Ï¡¤½èÍýǽÎϤι⤤·×»»µ¡¥·¥¹¥Æ¥à¤¬É¬ÍפȤʤ뤿¤á¡¤³°Éô¤Î¥µ¡¼¥Ð¤Ë½èÍý¤ò°ÑÂ÷¤¹¤ë¤³¤È¤¬¸½¼ÂŪ¤Ç¤¢¤ë¡¥¤·¤«¤·¡¤Æä˸Ŀ;ðÊóÅù¤Îµ¡Ì©¥Ç¡¼¥¿½èÍý¤Î°ÑÂ÷¤Ë´Ø¤·¤Æ¤Ï¡¤¾ðÊó¤Îϳ¤¨¤¤Âкö¤¬½ÅÍפȤʤ롥¥×¥é¥¤¥Ð¥·¡¼Êݸî¤Î¤¿¤á¤Ë¤Ï¡¤¥Ç¡¼¥¿¤Îƿ̾²½²Ã¹©¤Ê¤ÉÍÍ¡¹¤ÊÊýË¡¤¬¤¢¤ë¤¬¡¤Ëܸ¦µæ¤Ç¤Ï¡¤¥Ç¡¼¥¿¤Îµ¡Ì©À­Êݸî¤ÎÊýË¡¤È¤·¤Æ¡¤°Å¹æ²½¤·¤¿¾õÂ֤Ƿ׻»¤¬²Äǽ¤Ê´°Á´½àƱ·¿°Å¹æ¡ÊFHE¡Ë¤ò»ÈÍѤ¹¤ë¡¥Àè¹Ô¸¦µæ¤È¤·¤Æ¡¤FHE¤òApriori¥¢¥ë¥´¥ê¥º¥à¤Ë¤è¤ëÉѽХѥ¿¡¼¥ó¥Þ¥¤¥Ë¥ó¥°¤ò¹Ô¤¦¥¯¥é¥¤¥¢¥ó¥È¡¦¥µ¡¼¥Ð·¿¤Î¥·¥¹¥Æ¥à¤Ë¤Ä¤¤¤ÆŬÍѤ·¤¿P3CC¤¬¤¢¤ë¡¥¤³¤Î¥·¥¹¥Æ¥à¤Ë¤Ä¤¤¤Æ¡¤Apriori¥¢¥ë¥´¥ê¥º¥à¤òFP-growth¥¢¥ë¥´¥ê¥º¥à¤ËÊѹ¹¤·¤¿¤â¤Î¤ò¼ÂÁõ¤·¡¤Apriori¥¢¥ë¥´¥ê¥º¥à¤òÍѤ¤¤¿´û¸¼êË¡¤È¤ÎÈæ³Ó¤ò¹Ô¤¦¡¥

4B-3 (»þ´Ö: 9:10 - 9:30)
Âê̾·ÚÎÌN¥Ñ¡¼¥Æ¥£ÈëÆ¿´Ø¿ô·×»»¤Îʸ»úÎ󸡺÷³ÈÄ¥
Ãø¼Ô*Âì ͺÂÀϺ (ÀéÍÕ¹©¶ÈÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), Æ£ÅÄ ÌÐ (ÀéÍÕ¹©¶ÈÂç³Ø¾ðÊó²Ê³ØÉô¾ðÊ󹩳زÊ), µÜÀ¾ ÍÎÂÀϺ (³ô¼°²ñ¼Ò¥¢¥¤¥¨¥¹¥¤¡¼¥¨¥à), ÈõÃÏ Àµ¹À (ÅìËÌÂç³ØÂç³Ø±¡·ÐºÑ³Ø¸¦µæ²Ê), ÇòÄ» §Ϻ (Ãæ±ûÂç³Ø¸¦µæ³«È¯µ¡¹½)
¥Ú¡¼¥¸pp. 740 - 742
¥­¡¼¥ï¡¼¥ÉÈë̩ʬ»¶, ÈëÌ©·×»»
¥¢¥Ö¥¹¥È¥é¥¯¥ÈËܹƤǤÏ``·ÚÎÌN¥Ñ¡¼¥Æ¥£ÈëÆ¿´Ø¿ô·×»»''¤ËÂФ·Ê¸»úÎ󸡺÷½èÍý¤Î³ÈÄ¥¤ò¹Ô¤¦¡¥ ¤³¤Îʸ»úÎ󸡺÷¤Î¤¿¤á¤Ë¡¤Ê¸»úÎó¤Î¥Ï¥Ã¥·¥å²½¤ò¹Ô¤¤¤½¤Î·ë²Ì¤òʬ³ä¡¦Ê¬»¶¤¹¤ë¡¥ ËܹƤηë²Ì¤è¤ê½¾Íè¤Ç¤ÏÀ°¿ôÃÍ·¿¤Î¤ß¤Ç¤¢¤Ã¤¿ÈëÆ¿´Ø¿ô·×»»¤Î¥Ç¡¼¥¿¸¡º÷¤ò ʸ»úÎ󷿤ò¤â´Þ¤á¤ë¤³¤È¤¬²Äǽ¤È¤Ê¤ë¡¥ ¤³¤Î·ë²Ì¡¤¥·¥¹¥Æ¥àÀß·×¼Ô¤Ïʸ»úÎó¤òÈë̩ʬ»¶¤µ¤ì¤¿¾õÂ֤Ǹ¡º÷²Äǽ¤Ë¤Ê¤ë¤¿¤á¡¤ ÍøÊØÀ­¤¬¸þ¾å¤¹¤ë¡¥

ºÇÍ¥½¨ÏÀʸ¾Þ / Best Paper Awards
4B-4 (»þ´Ö: 9:30 - 9:50)
Âê̾¥°¥é¥Õ¤òÍѤ¤¤¿NMF¤ÎÃÏ°èʬ»¶¹â®²½
Ãø¼Ô*±ÛÄÍ µ£ (ÅìµþÍý²ÊÂç³ØÍý¹©³ØÉô¾ðÊó²Ê³Ø²Ê), ÃÝÆâ ¹§, ¾¾ÎÓ Ã£»Ë, ß·ÅÄ ¹¨ (ÆüËÜÅÅ¿®ÅÅÏà ( ³ô )NTT ¥³¥ß¥å¥Ë¥±¡¼¥·¥ç¥ó²Ê³Ø´ðÁø¦µæ½ê)
¥Ú¡¼¥¸pp. 743 - 751
¥­¡¼¥ï¡¼¥Éʬ»¶¥¢¥ë¥´¥ê¥º¥à, ÈóÉéÃ͹ÔÎó°ø»Òʬ²ò, ÃÏ°èÀ­, ¹â®²½
¥¢¥Ö¥¹¥È¥é¥¯¥ÈËܸ¦µæ¤Ç¤ÏÃÏ°èÀ­¤Ê¤É¤ÎʪÍýŪ¤Ë´Ø·¸À­¤ò¤â¤Ä½¸·×¥Ç¡¼¥¿¤Ë¾ÇÅÀ¤òÅö¤Æ, °ø»Òʬ²ò¤ò¹Ô¤¦rNMF(Regional Non-negative Matrix Factorization)¤òÄó°Æ¤¹¤ë.rNMF¤Ï, ʪÍýŪ¤Ëµ÷Î¥¤Î¶á¤¤ÃÏ°è¤Î¥Ç¡¼¥¿¤ÏƱÍͤÎÆÃħ¶õ´Ö¤Çɽ¸½¤·, ʬÀÏ·ë²Ì¤ò¤è¤êľ´¶Åª¤Ë¤ï¤«¤ê¤ä¤¹¤¤¤â¤Î¤È¤¹¤ë.ʬÀÏÂоݤΥǡ¼¥¿¤¬Â絬ÌϤʹÔÎó¤Ç¤¢¤Ã¤Æ¤â, ʬ»¶¥·¥¹¥Æ¥à¾å¤Ç¹â®¤Ë½èÍý¤ò¹Ô¤¨¤ë. rNMF¤Ï, Ãϰ褴¤È¤Î´Ñ¬¹ÔÎó¤ÎºÆ¹½À®¸íº¹¤ÎºÇ¾®²½¤ÈƱ»þ¤Ë, ʪÍýŪ¤Ëµ÷Î¥¤Î¶á¤¤ÃÏ°è¤Î¹ÔÎ󤫤é¤ÏƱÍͤδðÄì¹ÔÎó¤¬ÆÀ¤é¤ì¤ë¤è¤¦, ÂоݤΠ´ðÄì¹ÔÎó´Ö¤Îµ÷Î¥¤òºÇ¾®²½¤¹¤ë.ÃÏ°è¤Î°ÌÃÖ´Ø·¸¤Ï¥°¥é¥Õ¤Ë¤è¤Ã¤ÆÍ¿¤¨¤ë. ¥°¥é¥Õ¤ÎºÌ¿§ÌäÂê¤ò¶á»÷Ū¤Ë²ò¤¯¤³¤È¤Ç, ʬ»¶¥·¥¹¥Æ¥à¾å¤ÇÊÂÎó¤Ë½èÍý¤¹¤ë¤³¤È¤¬²Äǽ¤Ç¤¢¤ë.ËܹƤǤÏ, ¤Þ¤ºrNMF¤ÎÄê¼°²½¤ò¹Ô¤¦.¤½¤·¤Æ, ºÆ¹½À®¸íº¹¤È´ðÄì¹ÔÎó´Ö¸íº¹¤ËFrobenius¥Î¥ë¥à¤È°ìÈ̲½KL¥À¥¤¥Ð¡¼¥¸¥§¥ó¥¹¤òÍѤ¤¤¿¾ì¹ç¤Î¥Ñ¥é¥á¡¼¥¿¹¹¿·Ë¡¤ò¼¨¤¹.Ãϰ褴¤È¤Ë½¸·× ¤µ¤ì¤¿¼Â¥Ç¡¼¥¿¤òÍѤ¤¤¿¼Â¸³¤Ç¤Ï, rNMF¤òÍѤ¤¤ë¤³¤È¤Ç, ÎÙÀܤ·¤¿ÃÏ°è¥Ç¡¼¥¿¤ò¶¦Ä̤·¤¿ÆÃħ¶õ´Ö¤Çɽ ¸½¤Ç¤­¤ë¤³¤È, ½¾Íè¤Î NMF ¤ËÂФ·¤ÆÈƲ½À­Ç½¤¬°­²½¤·¤Ê¤¤¤³¤È, ʬ»¶¥·¥¹¥Æ¥à¾å¤Ç¹â®¤ËÆ°ºî¤¹¤ë¤³¤È¤ò¼¨¤¹.

4B-5 (»þ´Ö: 9:50 - 10:10)
Âê̾Division-based Video Data Access Method for Hot/Cold Tiered Storage Systems
Ãø¼Ô*Dong Ling (Osaka University), Shuuichirou Murata (Acutus Software, Inc.), Ying-Feng Hsu, Tomoki Yoshihisa, Morito Matsuoka (Osaka University)
¥Ú¡¼¥¸pp. 752 - 758
¥­¡¼¥ï¡¼¥É¥¹¥È¥ê¡¼¥ß¥ó¥°¥Ç¡¼¥¿, ¥Ç¡¼¥¿¥»¥ó¥¿¡¼, ¾ÃÈñÅÅÎϺ︺, ¥Ó¥Ç¥ª¥ª¥ó¥Ç¥Þ¥ó¥É
¥¢¥Ö¥¹¥È¥é¥¯¥ÈDue to the recent prevalence of video-on-demand services, data centers for them store a large number of video files, and some data centers adopt hot/cold tiered storage systems. Hot/cold tiered storage systems achieve low power consumption and low monetary cost by storing some data to cold storages, of which price per data unit is lower than that of hot storages. One of their drawbacks is slow data access speeds of cold storages. This is a very large problem for video-on-demand services since long interruption times of video playbacks occur when clients do not receive each video data segment by the time to play it. However, conventional hot/cold tiered storage systems are designed for general services and lack a chance to further reduce total playback interruption times for video-on-demand services. In this paper, we design a novel data access method for video-on-demand services using hot/cold tiered storage systems. In our method, each video file is divided into some video file segments so that the clients can finish receiving subsequent segments while playing received segments. By storing the first segment into the hot storage and others into the cold storage, our method achieves lower power consumption and lower monetary cost while reducing total playback interruption times.


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¥»¥Ã¥·¥ç¥ó 4C  ¹ÔÆ°¡¦¾õÂÖǧ¼±
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 8:30 - 10:10
Éô²°: ²ÖÉñ¡¦»°¤Î²Ö
ºÂĹ: Æ⻳ ¾´ (ÂçºåÂç³Ø)

¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
4C-1 (»þ´Ö: 8:30 - 8:50)
Âê̾¥¹¥È¥ì¥¹¤ÈÃí°Õµ¡Ç½¤ÎÁê¸ßºîÍѤò¹Íθ¤·¤¿¥¹¥Þ¡¼¥È¥Õ¥©¥ó¥í¥°¤«¤é¤Î¥¹¥È¥ì¥¹¿äÄê¼êË¡
Ãø¼Ô*ßÀë ¾°»Ö, Íî¹ç ·Ë°ì, »³ËÜ Ä¾¼ù, ¿¼ß· ͤ²ð, ÌÚËÜ ¾¡ÉÒ (NTT¥É¥³¥â), ̸À¸ ϼù, ¾åÀ¾ ¹¯Ê¿, ÂÀÅÄ ½ç (ÅìµþÂç³Ø), »ûß· ͪÍý, ²­Â¼ ºË, Á°ÅÄ µ®µ­ (·ÄØæµÁ½ÎÂç³Ø)
¥Ú¡¼¥¸pp. 759 - 769
¥­¡¼¥ï¡¼¥É¥¹¥Þ¡¼¥È¥Õ¥©¥ó, ¥¹¥È¥ì¥¹, Ãí°Õµ¡Ç½, Áê¸ßºîÍÑ, µ¡³£³Ø½¬¥¢¥ë¥´¥ê¥º¥à
¥¢¥Ö¥¹¥È¥é¥¯¥ÈÀº¿À¼À´µ¤Î´µ¼Ô¿ô¤Ïǯ¡¹Áý²Ã·¹¸þ¤Ë¤¢¤ê¡¤¸¶°ø¤È¤Ê¤ë¥¹¥È¥ì¥¹¤Î¾õÂÖ¤òÇÄ°®¤·Í½ËɤËÅؤá¤ë¤³¤È¤¬½ÅÍפǤ¢¤ë¡¥Ëܸ¦µæ¤Ç¤Ï¥æ¡¼¥¶¤¬Æü¡¹ÍøÍѤ¹¤ë¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤ËÃåÌܤ·¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Ç¼èÆÀ²Äǽ¤Ê¥»¥ó¥µÃͤª¤è¤ÓüËöÍøÍÑ¥í¥°¤òÍѤ¤¤Æ¥æ¡¼¥¶¤Î¥¹¥È¥ì¥¹¾õÂÖ¤ò¿äÄꤹ¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡¥Äó°Æ¼êË¡¤Ç¤Ï¥¹¥È¥ì¥¹¤ÈÁê¸ßºîÍѤò¤â¤ÄÃí°Õµ¡Ç½¤ËÃåÌܤ·¡¤Ãí°Õµ¡Ç½¤Î¾õÂÖ¤ò¹Íθ¤¹¤ë¤³¤È¤Ç¥¹¥È¥ì¥¹¿äÄêÀºÅ٤θþ¾å¤ò¿Þ¤ë¡¥¼ÂºÝ¤Ë32¿Í¤Î²ñ¼Ò°÷¤«¤é¼ý½¸¤·¤¿¤Î¤Ù554Æü¤Î¥Ç¡¼¥¿¥»¥Ã¥È¤òÍѤ¤¤Æɾ²Á¤ò¹Ô¤Ã¤¿·ë²Ì¡¤Ãí°Õµ¡Ç½¤ò¹Í褻¤º¤Ë¥¹¥È¥ì¥¹¤ò¿äÄꤹ¤ëÊý¼°¤ÈÈæ³Ó¤·¤Æ¡¤Äó°Æ¼êË¡¤Ë¤è¤ê¥¹¥È¥ì¥¹¤Î¿äÄêÀºÅÙ¤òÊ¿¶Ñ5.4%¹â¤á¤é¤ì¤ë¤³¤È¤ò³Îǧ¤·¡¤¥¹¥È¥ì¥¹¤Î¿äÄê¤Ë¤ª¤¤¤ÆÃí°Õµ¡Ç½¤È¤ÎÁê¸ßºîÍѤò¹Íθ¤¹¤ë¤³¤È¤¬Í­¸ú¤Ç¤¢¤ë¤³¤È¤¬Ê¬¤«¤Ã¤¿¡¥

4C-2 (»þ´Ö: 8:50 - 9:10)
Âê̾Preliminary Investigation on Recognizing Environment-dependent Human Actions using a Fusion of Wi-Fi Based Place Clustering and Motif Detection from Accelerometer Data
Ãø¼Ô*Thilina Dissanayake, Takuya Maekawa, Takahiro Hara (Graduate School of Information Science and Technology, Osaka University)
¥Ú¡¼¥¸pp. 770 - 776
¥­¡¼¥ï¡¼¥ÉWearable, Clustering, Motif detection
¥¢¥Ö¥¹¥È¥é¥¯¥ÈThis paper presents a novel method to estimate a location label of a user using sensor data from his/her smart devices (smartwatch and smartphone) without using labeled training data collected in his/her environments. Specifically, we attempt to predict the user's location semantics, i.e., location classes such as restroom and meeting room. We propose a novel matrix operation method that automatically finds acceleration data motifs specific to a certain location class, e.g., brushing teeth action observed at bathroom, based on the idea of Gini coefficient. We evaluated the proposed method in 4 real environments.

4C-3 (»þ´Ö: 9:10 - 9:30)
Âê̾µ¡³£³Ø½¬¤È¥ª¥ó¥È¥í¥¸¡¼¿äÏÀ¤òÁȤ߹ç¤ï¤»¤¿¹âÎð¼Ô¤ÎFIMºÎÅÀ¥·¥¹¥Æ¥à¤ÎÄó°Æ
Ãø¼Ô*ÂçÀÐ ¿­Ç·, ¾ÂÈø ²íÇ· (Åŵ¤ÄÌ¿®Âç³ØÂç³Ø±¡ ¾ðÊ󡦥ͥåȥ¥¯¹©³ØÀ칶)
¥Ú¡¼¥¸pp. 777 - 784
¥­¡¼¥ï¡¼¥É¹Ôưǧ¼±, µ¡³£³Ø½¬, ¥ª¥ó¥È¥í¥¸¡¼, FIM, ADL
¥¢¥Ö¥¹¥È¥é¥¯¥È¿Í´Ö¤Î·ò¹¯¤ä¥¦¥§¥ë¥Í¥¹¤Î¤è¤êÎɤ¤¥Þ¥Í¥¸¥á¥ó¥È¤ò¼Â¸½¤¹¤ë¤¿¤á¤Ë¡¤¤³¤ì¤Þ¤ÇÆü¾ïÀ¸³èÆ°ºî (ADL) ǧ¼±¤ËÂФ·¤ÆÍÍ¡¹¤Ê¥¢¥×¥í¡¼¥Á¤¬Äó°Æ¤µ¤ì¤Æ¤­¤¿¡¥ËܹƤǤϡ¤¹ÔÆ°¥¯¥é¥¹¤Î¼±Ê̤«¤é¹¹¤ËƧ¤ß¹þ¤ß¡¤¹âÎð¼Ô¤ÎÆü¾ïÀ¸³è¤Ë¤ª¤±¤ëµ¡Ç½Åª¼«Î©ÅÙ¤ò¬Äꤹ¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡¥µ¡Ç½Åª¼«Î©Å٤άÄê¤Ï¡¤µ¡Ç½Åª¼«Î©ÅÙɾ²ÁË¡ (FIM: Functional Independence Measure) ¤Ë½¾¤Ã¤Æ¹Ô¤¦¡¥Äó°Æ¼êË¡¤Ï¡¤ADL/FIM¥É¥á¥¤¥ó¥ª¥ó¥È¥í¥¸¡¼¤òÆȼ«¤Ë¹½ÃÛ¤·¡¤µ¡³£³Ø½¬¤È¥ª¥ó¥È¥í¥¸¡¼¤Ë´ð¤Å¤¯ÏÀÍýŪ¿äÏÀ¤È¤¤¤¦°Û¤Ê¤ë2¤Ä¤Î¥¢¥×¥í¡¼¥Á¤òÁȤ߹ç¤ï¤»¤ë¡¥2¤Ä¤Î°Û¤Ê¤ë¼êË¡¤òÁȤ߹ç¤ï¤»¤ë¤Ë¤¢¤¿¤ê¡¤¥»¥Þ¥ó¥Æ¥£¥Ã¥¯¥³¥ó¥Æ¥­¥¹¥È¤òÃæ´ÖÁؤȤ·¤ÆÄêµÁ¤·¡¤¤µ¤é¤ËǤ°Õ¥³¥ó¥Æ¥­¥¹¥È¤ò¿·¤¿¤ËƳÆþ¤¹¤ë¤³¤È¤ÇÉÔ´°Á´¤Ê¥Ç¡¼¥¿¤«¤é¤Î¿äÏÀ¤ò²Äǽ¤Ë¤¹¤ë¡¥Ãø¼Ô¤é¤Î¼Â¸³¼¼´Ä¶­¤Ç¼ý½¸¤µ¤ì¤¿¥Ç¡¼¥¿¤òÍѤ¤¤¿É¾²Á¼Â¸³¤è¤ê¡¤Äó°Æ¼êË¡¤ÎÍ­¸úÀ­¤¬¼¨¤µ¤ì¤¿¡¥

¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
4C-4 (»þ´Ö: 9:30 - 9:50)
Âê̾´Ñ¸÷Ãæ¤Î»ÅÁð¤Ë´ð¤Å¤¯´¶¾ð¡¦Ëþ­Å٤οäÄê¤Ë¤ª¤±¤ë´Ñ¸÷µÒ°À­¤Î±Æ¶ÁʬÀÏ
Ãø¼Ô*¾¾ÅÄ Íµµ® (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø/Íý²½³Ø¸¦µæ½ê ³×¿·ÃÎǽÅý¹ç¸¦µæ¥»¥ó¥¿¡¼¡ÊAIP¡Ë), Dmitrii Fedotov (Ulm University), ¹ÓÀî Ë­ (¶å½£Âç³Ø/JST¤µ¤­¤¬¤±), ¿Ûˬ Çîɧ (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø/Íý²½³Ø¸¦µæ½ê ³×¿·ÃÎǽÅý¹ç¸¦µæ¥»¥ó¥¿¡¼¡ÊAIP¡Ë), Wolfgang Minker (Ulm University), °ÂËÜ ·Ä°ì (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø/Íý²½³Ø¸¦µæ½ê ³×¿·ÃÎǽÅý¹ç¸¦µæ¥»¥ó¥¿¡¼¡ÊAIP¡Ë)
¥Ú¡¼¥¸pp. 785 - 791
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4C-5 (»þ´Ö: 9:50 - 10:10)
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¥Ú¡¼¥¸pp. 792 - 799
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 8:30 - 10:10
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ºÂĹ: Guillaume Lopez (ÀÄ»³³Ø±¡Âç³Ø)

4D-1 (»þ´Ö: 8:30 - 8:50)
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Ãø¼ÔµÜÁ° µ®Âç, Áи« µþ²ð, *¼Èø ÏÂºÈ (Ω̿´ÛÂç³Ø¾ðÊóÍý¹©³ØÉô)
¥Ú¡¼¥¸pp. 800 - 807
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
4D-2 (»þ´Ö: 8:50 - 9:10)
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Ãø¼Ô*¶ÍÌî¹¾ ¹âÂÀ, »ûÅÄ ÅØ, ÄÍËÜ ¾»É§ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 808 - 816
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Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
4D-3 (»þ´Ö: 9:10 - 9:30)
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Ãø¼Ô*·Ã¼ ·òÂÀϺ, »ûÅÄ ÅØ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), °ë»³ ľÌé (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø), ÄÍËÜ ¾»É§ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 817 - 824
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
4D-4 (»þ´Ö: 9:30 - 9:50)
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Ãø¼Ô*Haomin Mao (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²ÊÅŵ¤ÅŻҹ©³ØÀ칶), °ë»³ ľÌé (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø), »ûÅÄ ÅØ, ÄÍËÜ ¾»É§ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²ÊÅŵ¤ÅŻҹ©³ØÀ칶)
¥Ú¡¼¥¸pp. 825 - 829
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¥»¥Ã¥·¥ç¥ó 4E  °ÜÆ°
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 8:30 - 10:10
Éô²°: Í·Éñ¡¦¸Þ¤ÎÍ·
ºÂĹ: µÜÅÄ ¾Ï͵ (ÆüËÜÂç³Ø)

Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
4E-1 (»þ´Ö: 8:30 - 8:50)
Âê̾¥æ¡¼¥¶¤Î¥ê¥½¡¼¥¹¾ÃÈñ¤ò¹Íθ¤·¤¿°Õ»×·èÄê»Ù±ç¤Î¤¿¤á¤ÎÊ£¿ô´Ñ¸÷·ÐÏ©Ä󼨼êË¡
Ãø¼Ô*Ê¿Ìî ÍÛÂç, ¿Ûˬ Çîɧ, °ÂËÜ ·Ä°ì (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø/Íý²½³Ø¸¦µæ½ê)
¥Ú¡¼¥¸pp. 830 - 839
¥­¡¼¥ï¡¼¥É¥Ê¥Ó¥²¡¼¥·¥ç¥ó¥·¥¹¥Æ¥à, °äÅÁŪ¥¢¥ë¥´¥ê¥º¥à, ·Ðϩõº÷, ¿ÌÜŪºÇŬ²½, °Õ»×·èÄê
¥¢¥Ö¥¹¥È¥é¥¯¥È°ìÈÌŪ¤Ë¡¤´Ñ¸÷¤Î¼çÌÜŪ¤ÏËþ­ÅÙ¤òÆÀ¤ë¤³¤È¤Ë¤¢¤ê¡¤¤½¤Î¤¿¤á¤Ë¥æ¡¼¥¶¤Ï¿¤¯¤ÎÍ×Áǡʲó¤ë´Ñ¸÷ÃϤ䥳¥¹¥È¤Ê¤É¡Ë¤äÀ©Ìó¡Ê»È¤¨¤ë»þ´Ö¡¤Í½»»¤Ê¤É¡Ë¤òƱ»þ¤Ë¹Íθ¤·¤Æ·×²è¤òΩ¤Æ¤ëɬÍѤ¬¤¢¤ë¤¬¡¤¤³¤ì¤Ï¥æ¡¼¥¶¤Ë¤È¤Ã¤ÆÉéô¤ÎÂ礭¤¤ºî¶È¤Ç¤¢¤ë¡¥¤³¤Î´Ñ¸÷·ÐÏ©ÌäÂê¤òº¤Æñ¤Ë¤·¤Æ¤¤¤ë¸¶°ø¤Î°ì¤Ä¤Ë¡¤´Ñ¸÷¤Ë¤è¤Ã¤ÆÆÀ¤é¤ì¤ëËþ­Å٤ȡ¤¥æ¡¼¥¶¤¬°ÜÆ°¤ä´Ñ¸÷ÃϤǾÃÈñ¤¹¤ë¥ê¥½¡¼¥¹¡Ê¶âÁ¬¡¦»þ´Ö¡¦ÂÎÎϡˤΥȥ졼¥É¥ª¥Õ¤ò¹Í¤¨Ìµ¤±¤ì¤Ð¤Ê¤é¤º¡¤Ã±°ì¤ÎºÇŬ²ò¤òµá¤á¤é¤ì¤Ê¤¤¤³¤È¤¬¤¢¤²¤é¤ì¤ë¡¥ºÇ½ªÅª¤Ê¥æ¡¼¥¶¤Î°Õ»×·èÄê¤Î¼ê½õ¤±¤ò¹Ô¤¦¤¿¤á¤Ë¤Ï¡¤¤³¤ì¤é¤Î¥È¥ì¡¼¥É¥ª¥Õ¤ò¤¹¤Ù¤Æ¹Íθ¤·¤¿¾å¤Ç¡¤¥æ¡¼¥¶¤ËÊ£¿ô¤Î²ò¡Ê¥Ä¥¢¡¼¥×¥é¥ó¡Ë¤òÄ󼨤¹¤ë¤³¤È¤¬Ë¾¤Þ¤·¤¤¤¬¡¤²æ¡¹¤ÎÃΤë¸Â¤ê¤Ç¤Ï¤³¤Î¤è¤¦¤Ê¥·¥¹¥Æ¥à¤Ï¸ºß¤·¤Ê¤¤¡¥ ËÜÏÀʸ¤Ç¤Ï¡¤¤Ï¤¸¤á¤Ë´Ñ¸÷·Ðϩõº÷ÌäÂê¤ò¶âÁ¬¡¦»þ´Ö¡¦ÂÎÎϤνé´üÃͤòÆþÎϤȤ·¤¿Â¿ÌÜŪºÇŬ²½ÌäÂê¤È¤·¤ÆÄê¼°²½¤¹¤ë¡¥¤³¤ÎÌäÂê¤ÏNPº¤Æñ¤Ç¤¢¤ë¤¿¤á¡¤¥Ò¥å¡¼¥ê¥¹¥Æ¥£¥Ã¥¯¥¢¥ë¥´¥ê¥º¥à¤Î°ì¤Ä¤Ç¤¢¤ë°äÅÁŪ¥¢¥ë¥´¥ê¥º¥àNSGA-II¤ò¥Ù¡¼¥¹¤Ë¤·¤¿¡¤½à¥Ñ¥ì¡¼¥ÈºÇŬ²ò¤ò¿×®¤Ëõº÷¤¹¤ë¤¿¤á¤Î¥¢¥ë¥´¥ê¥º¥à¤ÎÄó°Æ¤ò¹Ô¤¦¡¥ºÇ¸å¤Ë¡¤¥¢¥ë¥´¥ê¥º¥à¤ÎÍ­¸úÀ­¤òɾ²Á¤¹¤ë¤¿¤á¤Ë¡¤µþÅÔ»ÔÅ컳¶è¤Ë¤¢¤ë30¥õ½ê¤Î´Ñ¸÷ÃϤòÂоݤËÄó°Æ¥¢¥ë¥´¥ê¥º¥à¤òŬÍѤ¹¤ë¤³¤È¤Ç¡¤½ÐÎϤµ¤ì¤ë²ò¤¬Í­°Õ¤Ç¤¢¤ê¸½¼ÂŪ¤Ê·×»»»þ´Ö¤Ç»»½Ð¤Ç¤­¤ë¤³¤È¤ò¼¨¤¹¡¥

4E-3 (»þ´Ö: 8:50 - 9:10)
Âê̾¿Í¤Î²óÈò¹ÔÆ°¤ò¹Íθ¤·¤¿°ÜÆ°¥í¥Ü¥Ã¥È¤Î·ÐÏ©·×²èË¡¤Î¸¡Æ¤
Ãø¼Ô*Àõ°æ ͪͤ (̾¸Å²°Âç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), ×¢°æ ·Å, ÊÆß· ÂóϺ, ²Ï¸ý ¿®É× (̾¸Å²°Âç³Ø̤Íè¼Ò²ñÁϤµ¡¹½)
¥Ú¡¼¥¸pp. 840 - 845
¥­¡¼¥ï¡¼¥É¿Í, ·ÐÏ©·×²è, RVO2, ¥í¥Ü¥Ã¥È, °ÜÆ°ÂÎ
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4E-4 (»þ´Ö: 9:10 - 9:30)
Âê̾GPS¥Ç¡¼¥¿¤Ë´ð¤Å¤¯Æü¾ïÀ¸³è¤Ë¤ª¤±¤ëÆÃÊ̤ʹÔÆ°¤Î¸¡½Ð
Ãø¼Ô*¾®ÎÓ À¿ (²¬»³Âç³Ø Âç³Ø±¡¥Ø¥ë¥¹¥·¥¹¥Æ¥àÅý¹ç²Ê³Ø¸¦µæ²Ê), ¸¶ ľ (²¬»³Âç³Ø Âç³Ø±¡¼«Á³²Ê³Ø¸¦µæ²Ê), °¤Éô ¶©¿­ (²¬»³Âç³Ø Âç³Ø±¡¥Ø¥ë¥¹¥·¥¹¥Æ¥àÅý¹ç²Ê³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 846 - 853
¥­¡¼¥ï¡¼¥É¥é¥¤¥Õ¥í¥°, »×¤¤½Ð¿¶¤êÊÖ¤ê, GPS¥Ç¡¼¥¿, Æü¾ï¤ÎÃæ¤ÎÈóÆü¾ï, ³°¤ìÃ͸¡½Ð
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¥»¥Ã¥·¥ç¥ó 4F  À¸³è¹ÔÆ°
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 8:30 - 10:10
Éô²°: Í·Éñ¡¦»°¤ÎÍ·
ºÂĹ: ¿Àºê ±Ç¸÷ (Å纬Âç³Ø)

4F-1 (»þ´Ö: 8:30 - 8:50)
Âê̾¥â¥ó¥Æ¥«¥ë¥íÌÚõº÷¤Ë¤è¤ë¥æ¡¼¥¶¸Ä¿Í¤ÎÓϹ¥¤ò¹Íθ¤·¤¿·ÐÏ©¿äÁ¦¼êË¡¤È¤½¤Îɾ²Á
Ãø¼Ô*Àкê ͺÂÀ (Áá°ðÅÄÂç³Ø), ¹â»³ ÉÒŵ (¥¼¥ó¥ê¥ó¥Ç¡¼¥¿¥³¥à), ¸ÍÀî ˾ (Áá°ðÅÄÂç³Ø)
¥Ú¡¼¥¸pp. 854 - 862
¥­¡¼¥ï¡¼¥É·ÐÏ©¿äÁ¦, ¥â¥ó¥Æ¥«¥ë¥íÌÚõº÷, UCT, SVM
¥¢¥Ö¥¹¥È¥é¥¯¥È¥¹¥Þ¡¼¥È¥Õ¥©¥ó¡¤¥¿¥Ö¥ì¥Ã¥È¤ÎÉáµÚ¤Ë¤è¤Ã¤Æ¡¤·ÐÏ©¿äÁ¦¡¦°ÆÆ⥵¡¼¥Ó¥¹¤Ï°ìÈÌŪ¤Ê¤â¤Î¤È¤Ê¤Ã¤¿¡¥ ½¾Íè¤Î¥¤¥ó¥¿¡¼¥Í¥Ã¥È¾å¤ÇÄ󶡤µ¤ì¤Æ¤­¤¿·ÐÏ©¿äÁ¦¡¦°ÆÆ⥵¡¼¥Ó¥¹¤Ç¤Ï¡¤·ÐϩĹ¡¦½êÍ×»þ´Ö¡¦ÎÁ¶â¤ÎÅÀ¤ÇºÇŬ²½¤·¤¿·ÐÏ©¤ò¿äÁ¦¤¹¤ë¥µ¡¼¥Ó¥¹¤¬¼çή¤Ç¤¢¤ë¡¥ ¤³¤ì¤é¤Î¥µ¡¼¥Ó¥¹¤Ç¤Ï°Û¤Ê¤ë¥æ¡¼¥¶¤Ç¤âƱ°ì¤Î·ÐÏ©¤¬¿äÁ¦¤µ¤ì¤ë¤³¤È¤Ë¤Ê¤ë¤¬¡¤³Æ¥æ¡¼¥¶¤Ï°ÂÁ´À­¤ä²÷ŬÀ­¤ÎÌ̤«¤é¿¼ï¿ÍͤÊÓϹ¥¤òÍ­¤·¤Æ¤¤¤ë¡¥ ¥æ¡¼¥¶¸Ä¿Í¤ÎÓϹ¥¤ò·ÐÏ©¿äÁ¦¤ËÈ¿±Ç¤µ¤»¡¤¤½¤Î¥æ¡¼¥¶¹¥¤ß¤Î·ÐÏ©¤ò¿äÁ¦¤¹¤ë¤³¤È¤¬¶¯¤¯Ë¾¤Þ¤ì¤ë¡¥ °ìÊý¤Ç¡¤¥æ¡¼¥¶¸Ä¿Í¤ÎÓϹ¥¤Ï¶Ë¤á¤ÆÛ£Ëæ¤ÇÊ£»¨¤Ê¤¿¤á¡¤¤½¤Îɾ²Á¤¬º¤Æñ¤Ç¤¢¤ë¤È¤¤¤Ã¤¿²ÝÂ꤬¤¢¤ë¡¥ ËܹƤǤϡ¤¥â¥ó¥Æ¥«¥ë¥íÌÚõº÷¤ò¥Ù¡¼¥¹¤Ë¥æ¡¼¥¶¸Ä¿Í¤ÎÓϹ¥¤ò¹Íθ¤·¤¿·ÐÏ©¿äÁ¦¼êË¡(P-UCT¼êË¡)¤òÄó°Æ¤¹¤ë¡¥ Äó°Æ¼êË¡¤Ç¤Ï¡¤¤Þ¤º½é¤á¤Ë¡¤¥æ¡¼¥¶¤Î·ÐÏ©¿äÁ¦ÍúÎò¤«¤éÆÃħÎ̤òÃê½Ð¤·¡¤Support Vector Machine (SVM)¤Çɾ²Á´ï¤òºîÀ®¤¹¤ë¡¥ ¤½¤Î¸å¡¤¥â¥ó¥Æ¥«¥ë¥íÌÚõº÷¤Ç½ÐȯÃÏÅÀ¤«¤éÌÜŪÃÏÅÀ¤Þ¤Ç¤Î¥é¥ó¥À¥à¤Ê·ÐÏ©¤òÀ¸À®¤·¤Æ¡¤¤½¤ì¤é¤Î·ÐÏ©¤¬¤É¤ÎÄøÅ٥桼¥¶¤ÎÓϹ¥¤ËŬ¹ç¤·¤Æ¤¤¤ë¤«¤òɾ²Á´ï¤Ë¤è¤Ã¤ÆȽÃǤ¹¤ë¡¥ ¤³¤Î¥é¥ó¥À¥à·ÐÏ©¤ÎÀ¸À®¡¦É¾²Á¤ò·«¤êÊÖ¤·¼Â»Ü¤¹¤ë¤³¤È¤Ç¡¤ºÇ½ªÅª¤Ë¡¤¥æ¡¼¥¶¤ÎÓϹ¥¤ËºÇ¤â¶á¤¤¤Èɾ²Á¤µ¤ì¤¿·ÐÏ©¤¬½ÐÎϤµ¤ì¤ë¡¥ ¼Â¸³¤Î·ë²Ì¡¤´û¸¼êË¡¤ÈÈæ³Ó¤·¤Æ¡¤Äó°Æ¼êË¡¤¬¿äÁ¦¤·¤¿·ÐÏ©¤ÎÊ¿¶Ñɾ²ÁÅÀ¤¬¾å²ó¤ë·ë²Ì¤È¤Ê¤Ã¤¿¡¥

4F-2 (»þ´Ö: 8:50 - 9:10)
Âê̾¥¹¥Þ¡¼¥È¥á¡¼¥¿¡¼¤ÈHEMS¤òÍøÍѤ·¤¿¼Â½»Âð¤Ç¤ÎÀ¸³è¹ÔÆ°¿äÄê
Ãø¼Ô*º´Ìî ˧¼ù, ¾¾Êý ľ¼ù, ¼ò°æ µ®ÍÎ, ÁýÅÄ Î¦, ßÀËÜ Ë¾³¨, ¿ù¼ Çî, °ì¿§ ÀµÃË (¿ÀÆàÀ²ÊÂç³Ø)
¥Ú¡¼¥¸pp. 863 - 868
¥­¡¼¥ï¡¼¥É¹ÔÆ°¿äÄê, HEMS, ECHONET Lite, ¥¹¥Þ¡¼¥È¥á¡¼¥¿¡¼, IoT²ÈÅÅ
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4F-3 (»þ´Ö: 9:10 - 9:30)
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¥Ú¡¼¥¸pp. 869 - 873
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4G-1 (»þ´Ö: 8:30 - 8:50)
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4G-2 (»þ´Ö: 8:50 - 9:10)
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4G-3 (»þ´Ö: 9:10 - 9:30)
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4G-4 (»þ´Ö: 9:30 - 9:50)
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4H-2 (»þ´Ö: 8:50 - 9:10)
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¥Ú¡¼¥¸pp. 923 - 927
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4H-3 (»þ´Ö: 9:10 - 9:30)
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¥Ú¡¼¥¸pp. 928 - 934
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4H-4 (»þ´Ö: 9:30 - 9:50)
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¥Ú¡¼¥¸pp. 935 - 941
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5A-1 (»þ´Ö: 10:30 - 11:10)
Âê̾(¾·ÂÔ¹Ö±é) ËüÍ­¾ðÊóÌÖ ¡Á¥Ç¥¸¥¿¥ëµ»½Ñ¤ÇÊÑÍƤ¹¤ë¥â¥Î¤È¶õ´Ö¡Á
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¥Ú¡¼¥¸p. 942

Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
5A-2 (»þ´Ö: 11:10 - 11:30)
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¥Ú¡¼¥¸pp. 943 - 949
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5A-3 (»þ´Ö: 11:30 - 11:50)
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¥Ú¡¼¥¸pp. 950 - 956
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¥»¥Ã¥·¥ç¥ó 5B  IoT (2)
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 10:30 - 12:10
Éô²°: ²ÖÉñ¡¦°ì¤Î²Ö
ºÂĹ: ²ÃÆ£ ͳ²Ö (Åìµþ½÷»ÒÂç³Ø)

5B-1 (»þ´Ö: 10:30 - 10:50)
Âê̾UAV¶¨Ä´·¿¥»¥ó¥·¥ó¥°¤Ë¤ª¤±¤ëõº÷¸úΨ¤Î¸þ¾å¤Ë¤Ä¤¤¤Æ
Ãø¼Ô*°ËÆ£ ÂÀÀ¶ (Å纬Âç³ØÂç³Ø±¡¼«Á³²Ê³Ø¸¦µæ²ÊÍý¹©³ØÀ칶), ¿Àºê ±Ç¸÷ (Å纬Âç³Ø³Ø½Ñ¸¦µæ±¡Íý¹©³Ø·Ï)
¥Ú¡¼¥¸pp. 957 - 962
¥­¡¼¥ï¡¼¥ÉUAV, ¥»¥ó¥·¥ó¥°, °ÜÆ°À©¸æ, ̵ÀþÄÌ¿®
¥¢¥Ö¥¹¥È¥é¥¯¥ÈËܹƤǤϡ¤Â絬ÌϺҳ²È¯ºÒľ¸å¤Ë¤ª¤¤¤Æ¡¤¤µ¤Þ¤¶¤Þ¤Êµ¡´Ø¤ª¤è¤Ó¸Ä¿Í¤Î½êÍ­¤¹¤ë¥É¥í¡¼¥ó¤Ê¤É¤ÎUAV¡ÊUnmanned Aerial Vehicle¡Ë¤òÀѶËŪ¤ËÍø³èÍѤ·¤ÆÈïºÒÃϤÎõº÷¤ò¹Ô¤¦UAV¶¨Ä´·¿¥»¥ó¥·¥ó¥°¤Ë¤ª¤¤¤Æ¡¤É®¼Ô¤é¤Î¸¦µæ¥°¥ë¡¼¥×¤Ë¤ª¤¤¤ÆÄó°Æ¤·¤¿¼êË¡¤Î³ÈÄ¥¤ò¹Ô¤¤¡¤Ãµº÷¸úΨ¤ò¸þ¾å¤µ¤»¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡¥Äó°Æ¼êË¡¤Ç¤Ï¡¤³Æõº÷ÃÏÅÀ¤Îõº÷ÉÑÅÙ¤ò¼¨¤¹¿·¤¿¤Ê»Øɸ¤òƳÆþ¤·¡¤¤Þ¤¿UAV¤¬ÈïºÒÃÏ°èÆâ¤òõº÷¤¹¤ë°ÜÆ°·ÐÏ©¤òÄê¤á¤ëȽÃÇ´ð½à¤Ë²þÎɤò²Ã¤¨¤ë¤³¤È¤Ë¤è¤ê¡¤Ãµº÷ÂоÝÎΰèÁ´ÂΤòÉÑÈˤˡ¤¤«¤ÄÊФê¤Ê¤¯Ãµº÷¤¹¤ë¡¥¤µ¤é¤ËËܹƤǤϡ¤¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¼Â¸³¤Ë¤è¤êÄó°Æ¼êË¡¤ÎÍ­ÍÑÀ­¤ò³Îǧ¤¹¤ë¡¥

5B-2 (»þ´Ö: 10:50 - 11:10)
Âê̾¼Ò²ñ¥»¥ó¥µ¥Ç¡¼¥¿À¸À®¡¦¶¦Í­´ðÈפˤª¤±¤ë¥Ç¡¼¥¿À¸À®»þ´Öû½Ì¤Î¤¿¤á¤Î¼Ò²ñ¥»¥ó¥µ¼Â¹Ô»þ¹ï·èÄê¼êË¡
Ãø¼Ô°¦¹Ã Á±Ç·½õ, *µÁµ× ÃÒ¼ù, ¸¶ δ¹À (ÂçºåÂç³Ø)
¥Ú¡¼¥¸pp. 963 - 970
¥­¡¼¥ï¡¼¥É¥¹¥È¥ê¡¼¥à½èÍý, ¥¹¥È¥ê¡¼¥à¥Ç¡¼¥¿
¥¢¥Ö¥¹¥È¥é¥¯¥È¶áǯ¡¤·ÈÂÓ·¿Ã¼Ëö¤ÎÉáµÚ¤Ë¤è¤ê¡¤SNS¡ÊSocial Networking Service¡Ë¤¬¹­¤¯ÍøÍѤµ¤ì¤Æ¤¤¤ë¡¥É®¼Ô¤é¤Î¸¦µæ¥°¥ë¡¼¥×¤Ç¤Ï¡¤SNS Åù¡Ê³°Éô¥Ç¡¼¥¿¥½¡¼¥¹¡Ë¤ËÅê¹Æ¤µ¤ì¤¿Ã»Ê¸¤ä¼Ì¿¿¤Î²òÀÏ¥×¥í¥°¥é¥à¤È¡¤²òÀÏ·ë²Ì¤Î¥Ç¡¼¥¿¡Ê¼Ò²ñ¥»¥ó¥µ¥Ç¡¼¥¿¡Ë¤ò´ØÏ¢ÉÕ¤±¤Æ¶¦Í­¤¹¤ë¤¿¤á¤Î¥×¥é¥Ã¥È¥Õ¥©¡¼¥à¡¤S3 ¥·¥¹¥Æ¥à¤ò¸¦µæ³«È¯¤·¤Æ¤­¤¿¡¥S3 ¥·¥¹¥Æ¥à¤Ë¤ª¤¤¤Æ¡¤³°Éô¥Ç¡¼¥¿¥½¡¼¥¹¤Ë¥Ç¡¼¥¿¤òÍ׵ᤷ¤Æ¤«¤é¼Ò²ñ¥»¥ó¥µ¥Ç¡¼¥¿¤ÎÀ¸À®¤ò´°Î»¤¹¤ë¤Þ¤Ç¤Ë¤«¤«¤ë»þ´Ö¡Ê¼þ²óÆâ¼Ò²ñ¥»¥ó¥µ¥Ç¡¼¥¿À¸À®»þ´Ö¡Ë¤¬Ã»¤¤¤Û¤É¡¤¥ê¥¢¥ë¥¿¥¤¥àÀ­¤Î¹â¤¤¼Ò²ñ¥»¥ó¥µ¥Ç¡¼¥¿¤òÀ¸À®¤Ç¤­¤ë¡¥¤·¤«¤·¡¤³Æ¼Ò²ñ¥»¥ó¥µ¤Î¼Â¹Ô´Ö³Ö¤¬Ã»¤¹¤®¤ë¤È¡¤Æ±»þ¤ËÊ£¿ô¤Î¼Ò²ñ¥»¥ó¥µ¤¬¼Â¹Ô¤µ¤ì¤ë¤³¤È¤Ë¤Ê¤Ã¤Æ¼Ò²ñ¥»¥ó¥µ¥Ç¡¼¥¿¤ÎÀ¸À®¤Ë¤«¤«¤ë»þ´Ö¤¬Ä¹¤¯¤Ê¤ë¡¥¤½¤³¤ÇËܸ¦µæ¤Ç¤Ï¡¤¸úΨŪ¤Ë¼Ò²ñ¥»¥ó¥µ¤ò¼Â¹Ô¤¹¤ë¤¿¤á¤Î¼Â¹Ô»þ¹ï·èÄê¼êË¡¤òÄó°Æ¤¹¤ë¡¥Äó°Æ¼êË¡¤Ç¤Ï¡¤³Æ¼Ò²ñ¥»¥ó¥µ¤Î¼Ò²ñ¥»¥ó¥µ¼Â¹Ô´Ö³Ö¤Ë¾å¸Â¤òÀߤ±¡¤¸å¤Î¼þ²ó¤Ç¼Â¹Ô¤·¤Æ¤â¾å¸ÂÆâ¤Ë¼Â¹Ô¤Ç¤­¤ë¼Ò²ñ¥»¥ó¥µ¤Î¼Â¹Ô¤òÃæ»ß¤¹¤ë¡¥É¾²Á¤Î·ë²Ì¡¤¼Ò²ñ¥»¥ó¥µ¼Â¹Ô´Ö³Ö¤È¼þ²óÆâ¼Ò²ñ¥»¥ó¥µ¥Ç¡¼¥¿À¸À®»þ´Ö¤òû½Ì¤Ç¤­¤ë¤³¤È¤ò³Îǧ¤·¤¿¡¥

5B-3 (»þ´Ö: 11:10 - 11:30)
Âê̾»ÑÀª¿äÄê¤È RNN ¤òÍѤ¤¤¿Æ°²èÆ°ºî¼±Ê̼êË¡¤ÎÄ´ºº
Ãø¼Ô*¹âºê ÃÒ¹á»Ò (¤ªÃã¤Î¿å½÷»ÒÂç³Ø), ÃÝ˼ ¤¢¤Ä»Ò (¹ñΩ¾ðÊó³Ø¸¦µæ½ê), ÃæÅÄ ½¨´ð (»º¶Èµ»½ÑÁí¹ç¸¦µæ½ê), ¾®¸ý Àµ¿Í (¤ªÃã¤Î¿å½÷»ÒÂç³Ø)
¥Ú¡¼¥¸pp. 971 - 978
¥­¡¼¥ï¡¼¥Éµ¡³£³Ø½¬, ¿¼Áسؽ¬, ʬ»¶½èÍý, OpenPose, Keras

5B-4 (»þ´Ö: 11:30 - 11:50)
Âê̾An Implementation of Video Surveillance Systems with Progressive Quality Improvement Approach
Ãø¼Ô*Chaxiong Yukonhiatou (Graduate School of Information Science and Technology, Osaka University), Tomoya Kawakami (Nara Institute of Science and Technology), Tomoki Yoshihisa (Cybermedia Center, Osaka University), Yuuichi Teranishi (National Institute of Information and Communications Technology/Cybermedia Center, Osaka University), Shinji Shimojo (Cybermedia Center, Osaka University)
¥Ú¡¼¥¸pp. 979 - 984
¥­¡¼¥ï¡¼¥ÉStream data collection, Video processing, Data analysis, Image quality, Camera system
¥¢¥Ö¥¹¥È¥é¥¯¥ÈDue to the widespread of video surveillance, real-time detection systems for humans or cars are deployed in many places such as airports, banks, and parking spaces. In many of these systems, the cameras continuously send their original quality images to the processing computers via networks such as hight resolution images. However, the high quality images require high performance or large communication traffic to be processed and cause serious problems to the processing computers and networks. The quality improvement is one of approaches to reduce the communication traffic in the surveillance systems. For example, the number of installed cameras can be increased as the communication traffic decreases or the processing computer can faster to find a thief recorded in image data got from cameras with a faster transmitting image data from cameras to the processing computers. Therefore, we have proposed the method which reduces the communication time and traffic based on progressive quality improvement (PQI) approach. In this paper, we describe our system implementation and performance experiment of our proposed method.

5B-5 (»þ´Ö: 11:50 - 12:10)
Âê̾¥¯¥é¥¦¥É¤È¥»¥ó¥µ¤ÎÅý¹ç¥·¥¹¥Æ¥à´ÉÍýÊý¼°
Ãø¼Ô*¶úÅÄ ¹â¹¬ (Åìµþ¹©²ÊÂç³Ø¥³¥ó¥Ô¥å¡¼¥¿¥µ¥¤¥¨¥ó¥¹³ØÉô)
¥Ú¡¼¥¸pp. 985 - 991
¥­¡¼¥ï¡¼¥É¥¯¥é¥¦¥É, ¥»¥ó¥µ, IoT, ¥·¥¹¥Æ¥à´ÉÍý
¥¢¥Ö¥¹¥È¥é¥¯¥È¥¯¥é¥¦¥É¤Ï¡¤ IT ¤Ç¼«Æ°²½¤ä¾ÊÎϲ½¤Ë¤ª¤¤¤ÆÃæ¿´¤Î¥µ¡¼¥Ó¥¹¤È¤·¤Æ°ÌÃ֤Ť±¤é¤ì¤Æ¤¤¤ë¡¥¤Þ¤¿¡¤ IoT¤Ç¤Ï¡¤¥»¥ó¥µ¤ò»È¤Ã¤¿Â¿¤¯¤Î¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤ä¥½¥ê¥å¡¼¥·¥ç¥ó¤Î¼ÂÍÑŪ¤ÊÍøÍѤ¬¤Ï¤¸¤Þ¤Ã¤Æ¤¤¤ë¡¥¥¯¥é ¥¦¥É¤Ë¤ª¤¤¤Æ¡¤¥»¥ó¥µ¤ò¥×¥í¥À¥¯¥·¥ç¥ó¡¦¥·¥¹¥Æ¥à¤Î°ìÉô¤È¤·¤ÆÍøÍѤ¹¤ë¤È¤­¡¤¥»¥ó¥µ¡¦¥Ç¡¼¥¿¤Î¿®ÍêÀ­¤ò³ÎÊݤ¹¤ë´ÉÍý¤ä¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤ä¥½¥ê¥å¡¼¥·¥ç¥ó¤«¤é¥¢¥¯¥»¥¹¤òÍưפ˲Äǽ¤Ë¤¹¤ë¤¿¤á¤Î¥¤¥ó¥¿¡¼¥Õ¥§¥¤¥¹¤¬É¬Íפˤʤ롥¤³¤ÎÏÀʸ¤Ç¤Ï¡¤¥¯¥é¥¦¥É¤Î³ÈÄ¥µ¡Ç½¤È¤·¤Æ¡¤¥»¥ó¥µ¤Î´ÉÍý¤òÅý¹ç¤¹¤ë¤³¤È¤Ë¤è¤Ã¤Æ¥¯¥é¥¦¥É¾å¤Ç¥»¥ó¥µ¤ò°·¤¤¤ä¤¹¤¯¤¹¤ë¤¿¤á¤ÎÅý¹ç´ÉÍý¥¢¡¼¥­¥Æ¥¯¥Á¥ã¤È¡¤¤½¤Î¼ÂÁõÊý¼°¤Ë¤Ä¤¤¤Æ½Ò¤Ù¤ë¡¥¥¯¥é¥¦¥É¡¦¥æ¡¼¥¶¤Ï¡¤Äó°ÆÊý¼°¤ò»È¤¦¤³¤È¤Ç¥»¥ó¥µ¤ò¥×¥í¥À¥¯¥·¥ç¥ó¡¦¥·¥¹¥Æ¥à¤ËÍøÍѤ¹¤ë¤³¤È¤¬¤Ç¤­¤ë¡¥


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¥»¥Ã¥·¥ç¥ó 5C  ¥»¥ó¥·¥ó¥°
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 10:30 - 12:10
Éô²°: ²ÖÉñ¡¦»°¤Î²Ö
ºÂĹ: °ð¼ ¹À (¸øΩ¤Ï¤³¤À¤Æ̤ÍèÂç³Ø)

5C-1 (»þ´Ö: 10:30 - 10:50)
Âê̾³ØÀ¸¤Î¼«¸ÊÄ´À°³Ø½¬¤ò»Ù±ç¤¹¤ë¥»¥ë¥Õ¥â¥Ë¥¿¥ê¥ó¥°¥·¥¹¥Æ¥à¸¡Æ¤
Ãø¼Ô*¾®°Â ½¡ÆÁ (ÅìµþÅŵ¡Âç³Ø/¾ðÊó´Ä¶­³Ø¸¦µæ²Ê), ¼Äùõ °ì·Ä (ÅìµþÅŵ¡Âç³Ø/¾ðÊó´Ä¶­³ØÉô), º´Æ£ ̯, ÀÄÌÚ ÎÉÊå, Í­²ì Îè»Ò, ÅÏÉô ÃÒ¼ù, ¸¤Æ¸ ÂóÌé (ÆüËÜÅÅ¿®ÅÅÏóô¼°²ñ¼Ò/NTT¥µ¡¼¥Ó¥¹¥¨¥Ü¥ê¥å¡¼¥·¥ç¥ó¸¦µæ½ê), ÂçÅç ľ¼ù, ÉðÀî ľ¼ù (ÅìµþÅŵ¡Âç³Ø/¥·¥¹¥Æ¥à¥Ç¥¶¥¤¥ó¹©³Ø²Ê)
¥Ú¡¼¥¸pp. 992 - 999
¥­¡¼¥ï¡¼¥É¼«¸ÊÄ´À°³Ø½¬, ¥»¥ë¥Õ¥â¥Ë¥¿¥ê¥ó¥°, ICT
¥¢¥Ö¥¹¥È¥é¥¯¥È²æ¡¹¤Ï¸¦µæ³èÆ°¤ò¹Ô¤Ã¤Æ¤¤¤ëÂç³ØÀ¸¤Î¼«¸ÊÄ´À°³Ø½¬¤ò¡¤¥»¥ë¥Õ¥â¥Ë¥¿¥ê¥ó¥°¤ò»ÈÍѤ·¤Æ»Ù±ç¤ò¹Ô¤¦¤³¤È¤òÌܻؤ·¤Æ¤¤¤ë¡¥¼«¸ÊÄ´À°³Ø½¬¤ËÉÔ´·¤ì¤ÊÂç³ØÀ¸¤ÎÆÃħ¤òÌÀ³Î²½¤¹¤ë°Ù¡¤17̾¤Î³ØÀ¸¤òʬÀϤ·¤¿¡¥Ê¬ÀϤ·¤¿³ØÀ¸¤ÎÀ­³Ê¤«¤é¡¤¼«¸ÊÃøÀ½³Ø½¬¤ËÉÔ´·¤ì¤ÊÂç³ØÀ¸¤Î¥Ú¥ë¥½¥Ê¤ò2¼ïÎàÃê½Ð¤·¡¤¸¦µæ³èÆ°¤Ë¤ª¤±¤ë¥¹¥Æ¥Ã¥×¤Î²¾Àâ¤ò¹½ÃÛ¤·¤¿¡¥¹½ÃÛ¤·¤¿²¾À⤫¤é¡¤³ØÀ¸¤Ë¸¦µæ³èÆ°¤òÂ¥¿Ê¤¹¤ë¥»¥ë¥Õ¥â¥Ë¥¿¥ê¥ó¥°¤òÂ¥¤¹¡¤ÄÌÃÎ¥·¥¹¥Æ¥à¤ò¹½ÃÛ¤·¤¿¡¥ÄÌÃÎÊýË¡¤ÏÂç³Ø¹½Æâ¤Ç¤ÎÂں߾ì½ê¤ò´ð¤ËÄÌÃΤò¹Ô¤¤¡¤¥»¥ë¥Õ¥â¥Ë¥¿¥ê¥ó¥°¤µ¤»¤ë¤â¤Î¤Ç¤¢¤ë¡¥Âç³ØÀ¸4̾¤ËÂФ·¤Æ1½µ´Ö¤Î¥æ¡¼¥¶¥Æ¥¹¥È¤ò¹Ô¤Ã¤¿¡¥¤½¤Î·ë²Ì¡¤¥»¥ë¥Õ¥â¥Ë¥¿¥ê¥ó¥°¤Î²óÅú·ë²Ì¤«¤é¡¤¡ÉÏÀʸĴºº¡É¤Ê¤É¤Î½àÈ÷Ãʳ¬¤Î¿äÄ꤬¼¨º¶¤µ¤ì¤¿¡¥¤Þ¤¿¡¤¥»¥ë¥Õ¥â¥Ë¥¿¥ê¥ó¥°¤ò¹Ô¤ï¤»¤ë¤³¤È¤Ç¡¤¸¦µæ¤Ë¤«¤«¤ï¤ë¹ÔÆ°¤È¸¦µæ¤ò¹Ô¤¦°Õ¼±¤òÂ¥¿Ê¤¹¤ë¤³¤È¤¬¼¨º¶¤µ¤ì¤¿¡¥

5C-2 (»þ´Ö: 10:50 - 11:10)
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¥Ú¡¼¥¸pp. 1000 - 1010
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5C-3 (»þ´Ö: 11:10 - 11:30)
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¥Ú¡¼¥¸pp. 1011 - 1020
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5C-4 (»þ´Ö: 11:30 - 11:50)
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Ãø¼Ô*ÎÓ ·òÂÀ, ÀÐÅÄ ÈË̦ (¶å½£Âç³Ø¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ±¡), ÅÄƬ ÌÐÌÀ (´ØÀ¾Âç³ØÁí¹ç¾ðÊó³ØÉô), Ê¡ÅÄ ¹¸ (¶å½£Âç³Ø¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ±¡)
¥Ú¡¼¥¸pp. 1021 - 1026
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5C-5 (»þ´Ö: 11:50 - 12:10)
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¥Ú¡¼¥¸pp. 1027 - 1034
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 10:30 - 12:10
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ºÂĹ: Àи¶ ¿Ê (ÀŲ¬Âç³Ø)

Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
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5D-1 (»þ´Ö: 10:30 - 10:50)
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¥Ú¡¼¥¸pp. 1035 - 1043
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5D-2 (»þ´Ö: 10:50 - 11:10)
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Ãø¼Ô*Âç°æ µ®À², ËÌÂô ¾»Âç, ÄÍÅÄ ³Ø, Íî¹ç ½¨Ìé, ¹¾ºê ¹À (ÅìµþÂç³ØÂç³Ø±¡¾ðÊóÍý¹©³Ø·Ï¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1044 - 1050
¥­¡¼¥ï¡¼¥ÉITS, Proxy CAM, ¥ë¡¼¥Æ¥£¥ó¥°
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5D-3 (»þ´Ö: 11:10 - 11:30)
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Ãø¼Ô*ĹÅè ½¨¹¬, ÄÍÅÄ ³Ø, Íî¹ç ½¨Ìé, ¹¾ºê ¹À (ÅìµþÂç³ØÂç³Ø±¡¾ðÊóÍý¹©³Ø·Ï¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1051 - 1056
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5D-4 (»þ´Ö: 11:30 - 11:50)
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Ãø¼Ô*´ßÅÄ ¿µÇ·²ð, ±Ñ æÆ»Ò, º´Æ£ ·òºÈ (Ʊ»Ö¼ÒÂç³ØÂç³Ø±¡ Íý¹©³Ø¸¦µæ²Ê ¾ðÊ󹩳ØÀ칶)
¥Ú¡¼¥¸pp. 1057 - 1061
¥­¡¼¥ï¡¼¥ÉITS, V2XÄÌ¿®, ¥â¥Ð¥¤¥ë¥Í¥Ã¥È¥ï¡¼¥¯, LTE
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5D-5 (»þ´Ö: 11:50 - 12:10)
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Ãø¼Ô*¾¾¸¶ ¹ä (ÅìµþÂç³ØÃϵå´Ñ¬¥Ç¡¼¥¿ÅýÍ»¹çÏ¢·È¸¦µæµ¡¹½), ¶â¿ù ÍÎ, ¼Æºê μ²ð (ÅìµþÂç³Ø¶õ´Ö¾ðÊó²Ê³Ø¸¦µæ¥»¥ó¥¿¡¼)
¥Ú¡¼¥¸pp. 1062 - 1065
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 10:30 - 12:10
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5E-1 (»þ´Ö: 10:30 - 10:50)
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Ãø¼Ô*Íû ²Èδ, Áêß· ÏÂÌé (Áá°ðÅÄÂç³Ø), Å¢ ¸²»Ö, ÏÉºê ¹°µ¹, ËÜ°ÌÅÄ ¿¿°ì (Áá°ðÅÄÂç³Ø/¹ñΩ¾ðÊó³Ø¸¦µæ½ê)
¥Ú¡¼¥¸pp. 1066 - 1067
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5E-2 (»þ´Ö: 10:50 - 11:10)
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Ãø¼Ô*ß·Ìî μÂÀ, ¼Èø ÏÂºÈ (Ω̿´ÛÂç³Ø¾ðÊóÍý¹©³ØÉô)
¥Ú¡¼¥¸pp. 1068 - 1076
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
5E-3 (»þ´Ö: 11:10 - 11:30)
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Ãø¼Ô*µÈÅÄ ¹Òµ±, ¼Èø ÏÂºÈ (Ω̿´ÛÂç³Ø¾ðÊóÍý¹©³ØÉô)
¥Ú¡¼¥¸pp. 1077 - 1085
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5E-4 (»þ´Ö: 11:30 - 11:50)
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¥Ú¡¼¥¸pp. 1086 - 1091
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¥»¥Ã¥·¥ç¥ó 5F  ǧ¼±
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 10:30 - 12:10
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5F-1 (»þ´Ö: 10:30 - 10:50)
Âê̾»þ·ÏÎó¥Ç¡¼¥¿¤«¤é¤ÎÍ×Ìóʸ¤Î¼«Æ°À¸À®
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¥Ú¡¼¥¸pp. 1092 - 1098
¥­¡¼¥ï¡¼¥É¼«Á³¸À¸ì½èÍý, ¼«Á³¸À¸ìÀ¸À®, Linguistic Descriptions of Data(LDD)
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5F-2 (»þ´Ö: 10:50 - 11:10)
Âê̾Historical information Acquisition System (HAS) ¤Î¼ÂÁõ
Ãø¼Ô*ÂçÃÝ ±É°ì (°¦Ã驶ÈÂç³ØÂç³Ø±¡·Ð±Ä¾ðÊó²Ê³Ø¸¦µæ²Ê), ±óÆ£ ÀµÎ´, ÃæÅè ͵°ì, »°±º ůϺ (³ô¼°²ñ¼Ò¥ê¥ª), É©ÅÄ Î´¾´ (°¦Ã驶ÈÂç³Ø¾ðÊó²Ê³ØÉô)
¥Ú¡¼¥¸pp. 1099 - 1102
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5F-3 (»þ´Ö: 11:10 - 11:30)
Âê̾¥Ñ¥Ã¥·¥ÖRFID¥¿¥°¥¢¥ì¥¤¤òÍѤ¤¤¿Deep Learning¤Ë¤è¤ëÎسԲèÁü¤ÎÉü¸µ¼êË¡¤Î¸¡Æ¤
Ãø¼Ô*ÂçÅè À¯¿Æ, ¾ÂÈø ²íÇ· (Åŵ¤ÄÌ¿®Âç³ØÂç³Ø±¡ ¾ðÊóÍý¹©³Ø¸¦µæ²Ê ¾ðÊ󡦥ͥåȥ¥¯¹©³ØÀ칶)
¥Ú¡¼¥¸pp. 1103 - 1108
¥­¡¼¥ï¡¼¥ÉRFID, ¿¼Áسؽ¬, ²èÁüǧ¼±, ¹Ôưǧ¼±
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5F-4 (»þ´Ö: 11:30 - 11:50)
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¥Ú¡¼¥¸pp. 1109 - 1115
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 10:30 - 12:10
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
5G-1 (»þ´Ö: 10:30 - 10:50)
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5G-2 (»þ´Ö: 10:50 - 11:10)
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Ãø¼Ô*±öß· ½¨ÏÂ, ¾¾ËÜ Í´°Í (¶ÌÀîÂç³Ø¹©³ØÉô¥½¥Õ¥È¥¦¥§¥¢¥µ¥¤¥¨¥ó¥¹³Ø²Ê)
¥Ú¡¼¥¸pp. 1125 - 1130
¥­¡¼¥ï¡¼¥É¥×¥í¥°¥é¥ß¥ó¥°¶µ°é, AR, ¥¿¥ó¥¸¥Ö¥ë¥×¥í¥°¥é¥ß¥ó¥°, ¥í¥Ü¥Ã¥È¥×¥í¥°¥é¥ß¥ó¥°
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5G-3 (»þ´Ö: 11:10 - 11:30)
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¥Ú¡¼¥¸pp. 1131 - 1137
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5G-4 (»þ´Ö: 11:30 - 11:50)
Âê̾TransEmotion:²¾ÁÛ¸ý¿°¤Ë¤è¤ë´¶¾ðº¹¤·Âؤ¨¥Þ¥¹¥¯¤ÎÄó°Æ
Ãø¼Ô*·§ùõ ο²í (Åìµþ¹©²ÊÂç³Ø ¥Ð¥¤¥ª¡¦¾ðÊó¥á¥Ç¥£¥¢¸¦µæ²Ê¥³¥ó¥Ô¥å¡¼¥¿¥µ¥¤¥¨¥ó¥¹À칶), °æ¾å μʸ (Åìµþ¹©²ÊÂç³Ø ¥³¥ó¥Ô¥å¡¼¥¿¥µ¥¤¥¨¥ó¥¹³ØÉô)
¥Ú¡¼¥¸pp. 1138 - 1143
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¥»¥Ã¥·¥ç¥ó 5H  ǧ¾Ú
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 10:30 - 12:10
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
5H-1 (»þ´Ö: 10:30 - 10:50)
Âê̾¾¸Ìæǧ¾Ú¤Ë¤ª¤±¤ëÀ¸Âθ¡ÃμêË¡¤Ë´Ø¤¹¤ë°ì¸¡Æ¤
Ãø¼Ô*¿ùËÜ ºÌ²Î (ÀŲ¬Âç³Ø), ¾å¾¾ À²¿®, ±ü°æ Àë¹­ (KDDIÁí¹ç¸¦µæ½ê), ÂçÌÚ Å¯»Ë (ÀŲ¬Âç³Ø), »°Âð Í¥ (KDDIÁí¹ç¸¦µæ½ê), À¾³À Àµ¾¡ (ÀŲ¬Âç³Ø)
¥Ú¡¼¥¸pp. 1144 - 1148
¥­¡¼¥ï¡¼¥É¾¸Ìæǧ¾Ú, À¸Âθ¡ÃÎ
¥¢¥Ö¥¹¥È¥é¥¯¥È¿¤¯¤Î¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Ë¤Ï¾¿Í¤Ë¤è¤ëÉÔÀµ»ÈÍѤòËɻߤ¹¤ë¤¿¤á¤ËÀ¸ÂÎǧ¾Úµ¡Ç½¤¬ÅëºÜ¤µ¤ì¤Æ¤¤¤ë¡¥¿ÈÂÎŪÆÃħ¤Î1¤Ä¤È¤·¤Æ¾¸Ìæ¤òÍøÍѤ·¤¿Ç§¾ÚÊý¼°¤¬Äó°Æ¤µ¤ì¤Æ¤¤¤ë¡¥¾¸Ìæ¤Ï¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Î¥«¥á¥é¤Ê¤É¤ÇÆÃħ¤¬¼èÆÀ¤Ç¤­¤ë¤¿¤á¡¤ÆÃÊ̤ÊÁõÃÖ¤òɬÍפ»¤º¤Ëǧ¾Ú¤¬¹Ô¤¨¤ë¡¤°ìÊý¤Ç¡¤¥æ¡¼¥¶¤¬SNS¤Ê¤É¤Ë·ÇºÜ¤·¤¿¼«¿È¤Î¼Ì¿¿¤Ê¤É¤ò¤â¤È¤Ë¡¤¤Ê¤ê¤¹¤Þ¤·¤¬¹Ô¤ï¤ì¤ë²ÄǽÀ­¤¬¤¢¤ë¡¥ËܹƤǤϡ¥¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Ç»£±Æ¤ò¹Ô¤¦¾¸Ìæǧ¾Ú¤Ë¤ª¤±¤ë¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¹¶·â¤ËÂФ¹¤ëÀ¸Âθ¡ÃμêË¡¤ò¸¡Æ¤¤¹¤ë¡¥¿È¶á¤ÊÇÞÂΤòÍѤ¤¤¿¤Ê¤ê¤¹¤Þ¤·¤òÁÛÄꤷ¡¤°õºþ²èÁü¤Ê¤é¤Ó¤Ë¥Ç¥£¥¹¥×¥ì¥¤É½¼¨²èÁü¤òÍѤ¤¤¿¹¶·â¤ò¹Í¤¨¤ë¡¥¹¶·â²èÁü¡Ê°õºþ²èÁü¤ä¥Ç¥£¥¹¥×¥ì¥¤²èÁü¡Ë¤Ë¤ª¤¤¤Æ¤Ï¡¤¥¤¥ó¥¯¤ÎÞú¤ß¤Ë¤è¤ë²òÁüÅÙ¤ÎÎô²½¡¤¹¶·â²èÁü¤Î»£±Æ¤Ë¤è¤ë¥â¥¢¥ì¡Ê´³¾Ä¼Ê¡Ë¤¬À¸¤¸¤ë¤È¤¤¤¦ÆÃħ¤ËÃíÌܤ·¤¿¡¥

5H-2 (»þ´Ö: 10:50 - 11:10)
Âê̾¥Ñ¥¹¥ï¡¼¥É¤ËÍð¿ô¤òÁȤ߹ç¤ï¤»¤ë¥æ¡¼¥¶Ç§¾ÚÊý¼°
Ãø¼Ô*ÅÏîµ Íª²í, ÎëÌÚ ½¨Ï (̾¾ëÂç³Ø), ÆâÆ£ ¹î¹À (°¦Ã驶ÈÂç³Ø), ÅÏî´ ¹¸ (̾¾ëÂç³Ø)
¥Ú¡¼¥¸pp. 1149 - 1154
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5H-3 (»þ´Ö: 11:10 - 11:30)
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Ãø¼Ô*ÅÏÊÕ °ì¼ù, Ĺͧ À¿ (¿ÀÆàÀ²ÊÂç³Ø), ÌýÅÄ ·òÂÀϺ, ²¬ºê ľÀë (µÜºêÂç³Ø), ËÑ Èþ̼ (¿ÀÆàÀ²ÊÂç³Ø)
¥Ú¡¼¥¸pp. 1155 - 1160
¥­¡¼¥ï¡¼¥ÉÊâ¹Ôǧ¾Ú, µ¡³£³Ø½¬, ²Ã®ÅÙ¥»¥ó¥µ, ¥¹¥Þ¡¼¥È¥í¥Ã¥¯, ¥¦¥§¥¢¥é¥Ö¥ëüËö
¥¢¥Ö¥¹¥È¥é¥¯¥ÈÅÅ»ÒŪ¤Ë¸°¤Î³«ÊĤò¹Ô¤¦¥¹¥Þ¡¼¥È¥í¥Ã¥¯¤È¸Æ¤Ð¤ì¤ëIoT(Internet of Things)À½Éʤ¬¤¢¤ë¡¥¤½¤Î¥¹¥Þ¡¼¥È¥í¥Ã¥¯¤Îǧ¾ÚÊý¼°¤È¤·¤Æ¡¤½¾Íè¤Î¥Ñ¥¹¥ï¡¼¥ÉÊý¼°¤Ç¤Ï¥æ¡¼¥¶¤Îµ­²±Éé²Ù¤ä¥Ñ¥¹¥ï¡¼¥Éϳ±Ì¤Ê¤É¤Î´í¸±À­¤¬¤¢¤ë¡¥¤Þ¤¿¡¤´éǧ¾ÚÊý¼°¤Ç¤Ï²È¤ÎÁ°¤Ç¿ôÉôÖΩ¤Á»ß¤Þ¤ëɬÍפ¬¤¢¤ê¡¤¥Þ¥¹¥¯¤ä¥µ¥ó¥°¥é¥¹¤Ê¤É¤ò¿È¤ËÉÕ¤±¤Æ¤¤¤ì¤Ð¤½¤ì¤é¤ò³°¤¹É¬Íפ¬¤¢¤ë¡¥¤½¤³¤Ç¡¤²æ¡¹¤ÏÊâ¹Ô¾õÂ֤ιÔưŪÆÃħ¤òÍѤ¤¤ëÊâ¹Ôǧ¾Ú¤ËÃåÌܤ·¤¿¡¥¤³¤ì¤Þ¤Ç¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤«¤éÆÀ¤é¤ì¤ë²Ã®ÅÙ¤ä³Ñ®Å٥ǡ¼¥¿¤ò¤â¤È¤Ëµ¡³£³Ø½¬¤ÎʬÎà¤òÍѤ¤¤¿Êâ¹Ôǧ¾Ú¤Î¸¦µæ¤¬¹Ô¤ï¤ì¤Æ¤­¤¿¤¬¡¤¶µ»Õ¤¢¤ê³Ø½¬¤ÎʬÎà¤òÍѤ¤¤¿Ç§¾Ú¤ò¹Ô¤Ã¤Æ¤¤¤ë¤¿¤á̤ÃΤΥǡ¼¥¿¤ËÂФ·¤ÆÍ­¸ú¤Êǧ¾ÚÊý¼°¤È¤Ï¸À¤¨¤Ê¤¤¡¥Ëܸ¦µæ¤Ç¤Ï¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤È¥¦¥§¥¢¥é¥Ö¥ëüËö¤ÎÆó¤Ä¤ÎüËö¤Î²Ã®ÅÙ¥»¥ó¥µ¤«¤é¥Ç¡¼¥¿¤ò¼èÆÀ¤·¡¤µ¡³£³Ø½¬¤Î°Û¾ï¸¡ÃΤòÍѤ¤¤Æ¼±ÊÌ´ï¤òºîÀ®¤¹¤ë¤³¤È¤Ç̤ÃΤΥǡ¼¥¿¤ËÂФ·¤ÆÍ­¸ú¤ÊÊâ¹Ôǧ¾Ú¤Î¥·¥¹¥Æ¥à¥â¥Ç¥ë¤òÄó°Æ¤¹¤ë¡¥¤Þ¤¿¡¤¥·¥¹¥Æ¥à¥â¥Ç¥ë¤ÎFAR(False Acceptance Rate)¤äFRR(False Rejection Rate)¤ò³Îǧ¤¹¤ë¼Â¸³¤ò¹Ô¤Ã¤¿·ë²Ì¡¤°Û¾ï¸¡ÃÎ¥¢¥ë¥´¥ê¥º¥à¤ËIsolationForset¤òÍѤ¤¤¿¾ì¹ç¡¤Ê¿¶ÑFAR¤¬8.3%¡¤Ê¿¶ÑFRR¤¬9.5%¤Ç¤¢¤Ã¤¿¡¥¤µ¤é¤Ë¡¤³ÆÈ︳¼Ô¤ÎFAR¤ÈFRR¤ò»»½Ð¤·¡¤È︳¼Ô¤Ë¤è¤Ã¤ÆFAR¤äFRR¤¬Ä㤯¤Ê¤ë°Û¾ï¸¡ÃÎ¥¢¥ë¥´¥ê¥º¥à¤¬°Û¤Ê¤ë¤³¤È¤ò³Îǧ¤·¤¿¡¥

5H-5 (»þ´Ö: 11:30 - 11:50)
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Ãø¼Ô*ÀÐ°æ ·òÂÀϺ (À콤Âç³Ø)
¥Ú¡¼¥¸pp. 1161 - 1167
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 14:10 - 15:30
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6A-1 (»þ´Ö: 14:10 - 14:50)
Âê̾(¾·ÂÔ¹Ö±é) Ķ¸ÄÂη¿¥Ç¡¼¥¿¥»¥ó¥¿¡¼OS¤òÌܻؤ·¤¿¤µ¤¯¤é¥¤¥ó¥¿¡¼¥Í¥Ã¥È¸¦µæ½ê¤Î¼è¤êÁȤߤÈ̤Íè¤ò¸«¿ø¤¨¤¿¸¦µæÁÈ¿¥Àß·×
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¥Ú¡¼¥¸p. 1168
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6A-2 (»þ´Ö: 14:50 - 15:10)
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¥Ú¡¼¥¸pp. 1169 - 1174
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6A-3 (»þ´Ö: 15:10 - 15:30)
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¥Ú¡¼¥¸pp. 1175 - 1180
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 14:10 - 15:30
Éô²°: ²ÖÉñ¡¦°ì¤Î²Ö
ºÂĹ: ¿Àºê ±Ç¸÷ (Å纬Âç³Ø)

6B-1 (»þ´Ö: 14:10 - 14:30)
Âê̾ʣ¿ô¥¯¥é¥¦¥É¤òÍѤ¤¤¿ÂçÍÆÎ̥ꥢ¥ë¥¿¥¤¥àÊÂÎóʬ»¶½èÍý¥·¥¹¥Æ¥à¤È¤½¤ÎÀ­Ç½É¾²Á
Ãø¼Ô*·¯»³ ÇîÇ· (ÂçƱÂç³Ø), ´Ý»³ ½¼, ¾®Åç °ìÀ® (¿ÀÆàÀ²ÊÂç³Ø), Æ£°æ εÌé (£Î£Ô£Ô̤Íè¤Í¤Ã¤È¸¦µæ½ê)
¥Ú¡¼¥¸pp. 1181 - 1189
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6B-2 (»þ´Ö: 14:30 - 14:50)
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¥Ú¡¼¥¸pp. 1190 - 1195
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6B-3 (»þ´Ö: 14:50 - 15:10)
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¥Ú¡¼¥¸pp. 1196 - 1203
¥­¡¼¥ï¡¼¥ÉAI ¥ï¡¼¥¯¥í¡¼¥É, ÆÃħʬÀÏ, MLPerf, Zabbix, µ¡³£³Ø½¬
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6B-4 (»þ´Ö: 15:10 - 15:30)
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¥Ú¡¼¥¸pp. 1204 - 1211
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 14:10 - 15:30
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6C-1 (»þ´Ö: 14:10 - 14:30)
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¥Ú¡¼¥¸pp. 1212 - 1219
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6C-2 (»þ´Ö: 14:30 - 14:50)
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Ãø¼Ô*ËÌ°æ ͪ°ìϯ, ¿åËÜ °°ÍÎ, ĹëÀî οͤ, Æ⻳ ¾´ (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), ÀÐ´Ý Âçµ®, ËÙÅÄ ËÒ (ÂçºåÂç³ØÂç³Ø±¡°å³Ø·Ï¸¦µæ²Ê), ­Ω ¹À¾Í, ¹©Æ£ ¶¬ (ÂçºåÂç³Ø¥­¥ã¥ó¥Ñ¥¹¥é¥¤¥Õ·ò¹¯»Ù±ç¥»¥ó¥¿¡¼), ÃÓÅÄ ³Ø (ÂçºåÂç³ØÂç³Ø±¡°å³Ø·Ï¸¦µæ²Ê), ÅìÌî µ±É× (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1220 - 1230
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6C-3 (»þ´Ö: 14:50 - 15:10)
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Ãø¼Ô*°ËÆ£ ãÌÀ, ¼»³ ÂîÌï, Ãæ¼ ÂÙ¼£ (ÆüËÜÅÅ¿®ÅÅÏóô¼°²ñ¼Ò ¥µ¡¼¥Ó¥¹¥¨¥Ü¥ê¥å¡¼¥·¥ç¥ó¸¦µæ½ê), ÅçÅÄ Í­Íý»Ò, Ĺë¾ì δǷ (À¾ÆüËÜÅÅ¿®ÅÅÏóô¼°²ñ¼Ò), ¹Â¸ý ͺÅÍ, Ë̦ ¿¿Í³²Â, °ËÅì ¹ä»Ö, Æ£°æ ½¨É× (¶áµ¦ÆüËÜÅ´Æ»³ô¼°²ñ¼Ò)
¥Ú¡¼¥¸pp. 1231 - 1237
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¥»¥Ã¥·¥ç¥ó 6D  ITS¾õÂÖ¿äÄê
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 14:10 - 15:30
Éô²°: ²ÖÉñ¡¦¸Þ¤Î²Ö
ºÂĹ: ²°Âå ÃÒÇ· (ÀéÍÕ¹©¶ÈÂç³Ø)

6D-1 (»þ´Ö: 14:10 - 14:30)
Âê̾¥Ä¡¼¥ê¥ó¥°¤ÇÃç´Ö¤È¤Î¹çή¤ò»Ù±ç¤¹¤ë¿¨³Ð¥Õ¥£¡¼¥É¥Ð¥Ã¥¯¤òÍѤ¤¤¿¥Ê¥Ó¥²¡¼¥·¥ç¥ó
Ãø¼Ô*¾®Ìº ·ÃÂÀ (ÌÀÀ±Âç³ØÂç³Ø±¡ ¾ðÊó³Ø¸¦µæ²Ê), ´Ý»³ °ìµ® (ÌÀÀ±Âç³Ø ¾ðÊó³ØÉô)
¥Ú¡¼¥¸pp. 1238 - 1245
¥­¡¼¥ï¡¼¥É¥Ä¡¼¥ê¥ó¥°, ¿¨³Ð¥Õ¥£¡¼¥É¥Ð¥Ã¥¯, ¹çή»Ù±ç
¥¢¥Ö¥¹¥È¥é¥¯¥È¥Ä¡¼¥ê¥ó¥°¤Ï¼Ö¤ä¥ª¡¼¥È¥Ð¥¤¤Î±¿Å¾¤½¤Î¤â¤Î¤ò³Ú¤·¤à¼êÃʤǤ¢¤ê¡¤Ãç´Ö¤È¶¦¤Ë±¿Å¾¤¹¤ë³Ú¤·¤ß¤ò¶¦Í­¤¹¤ë¤³¤È¤â¤Ç¤­¤ë¡¥ ¥Ä¡¼¥ê¥ó¥°Ãæ¤ËÃç´Ö¤È¤Ï¤°¤ì¤¿¾ì¹ç¡¤ÀèƳ¼Ö¤ÏÄä¼Ö²Äǽ¤Ê¾ì½ê¤ÇÄä¼Ö¤·¤Æ¸å³¼Ö¤òÂÔ¤Á¡¤¸å³¼Ö¤Ë¤ÏÀèƳ¼Ö¤ÎÂÔµ¡¾ì½ê¤òÃΤ餻¤ëɬÍפ¬¤¢¤ë¡¥ ²»À¼ÄÌÏäòÍѤ¤¤ë¤³¤È¤¬¹Í¤¨¤é¤ì¤ë¤¬¡¤ÉÔ°ÆÆâ¤ÊÃÏ°è¤ÇÀµ³Î¤Ë¾ì½ê¤òÅÁ¤¨¤ë¤Î¤ÏÆñ¤·¤¯¡¤¥Ê¥Ó¥²¡¼¥·¥ç¥ó¤Ë¤è¤êͶƳ¤¹¤ë¤³¤È¤¬Ë¾¤Þ¤·¤¤¡¥ ¥Ä¡¼¥ê¥ó¥°Ãæ¤Ë»ÈÍѤ¹¤ë°ìÈÌŪ¤Ê¥Ê¥Ó¥²¡¼¥·¥ç¥ó¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤Ï¡¤Ä°³Ð¤È»ë³Ð¤Ë¥Õ¥£¡¼¥É¥Ð¥Ã¥¯¤¹¤ë¤â¤Î¤¬Â¿¤¤¡¥ ¤·¤«¤·¡¤¥Ä¡¼¥ê¥ó¥°Ãæ¤ÏÃç´Ö¤È²»À¼ÄÌÏäˤè¤ê²ñÏäò¤¹¤ë¤³¤È¤â¿¤¯¡¤¤Ï¤°¤ì¤¿¾ì¹ç¤ÎÄ°³Ð¤Ë¤è¤ë¥Ê¥Ó¥²¡¼¥·¥ç¥ó¤ÏŬÀڤǤϤʤ¤¡¥ ¤Þ¤¿¡¤¤Ï¤°¤ì¤¿¤³¤È¤Ç±¿Å¾¼Ô¤Ï¿´ÍýŪ¤Ë¾ÇÁç´¶¤ò»ý¤Ä¤¿¤á¡¤»ë³Ð¤Î¤ß¤Ë¤è¤ë¥ë¡¼¥ÈÊѹ¹¤Î¥Ê¥Ó¥²¡¼¥·¥ç¥ó¤Ï°ÂÁ´±¿Å¾¤Î´ÑÅÀ¤«¤é˾¤Þ¤·¤¯¤Ê¤¤¤È¹Í¤¨¤é¤ì¤ë¡¥ Ëܸ¦µæ¤Ï¼«Æ°¼Ö¤Ç¤Î¥Ä¡¼¥ê¥ó¥°¤òÂоݤȤ·¡¤Ãç´Ö¤È¤Î¹çή¤ò¹Íθ¤·¤¿¥Ä¡¼¥ê¥ó¥°»Ù±ç¥·¥¹¥Æ¥à¤ò¼ÂÁõ¤·¤¿¡¥ ËÜÏÀʸ¤Ç¤Ï¡¤¹çή¾ì½ê¤Î¼«Æ°ÀßÄê¤ÎÍ­¸úÀ­¤È¡¤»ë³Ð¤È¿¨³Ð¤òÁȤ߹ç¤ï¤»¤¿¥Õ¥£¡¼¥É¥Ð¥Ã¥¯¤Ë¤è¤ë¥Ê¥Ó¥²¡¼¥·¥ç¥ó¤Î²ÄǽÀ­¤ò¸¡¾Ú¤·¤¿¡¥

6D-2 (»þ´Ö: 14:30 - 14:50)
Âê̾¥í¡¼¥É¥ì¡¼¥¸¤ËÂФ¹¤ëÍ×·ïŪÄêµÁ¤ª¤è¤ÓȽÄê¥Á¥ã¡¼¥È¤ÎÄó°Æ
Ãø¼Ô*Àî°æ ÌÀ (¼¢²ìÂç³Ø¥Ç¡¼¥¿¥µ¥¤¥¨¥ó¥¹³ØÉô/ÆüËÜ¥»¡¼¥Õ¥Æ¥£¥½¥µ¥¤¥¨¥Æ¥£¸¦µæ¥»¥ó¥¿¡¼)
¥Ú¡¼¥¸pp. 1246 - 1253
¥­¡¼¥ï¡¼¥É¥í¡¼¥É¥ì¡¼¥¸, ¤¢¤ª¤ê±¿Å¾
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6D-3 (»þ´Ö: 14:50 - 15:10)
Âê̾±¿Å¾Éé²Ù¤Î¶¯¼å¤Ë¤è¤ëȯÏþõ¶·¤ÎÌÀ³Î²½
Ãø¼Ô*¾ë ½¨°ì (ÀÄ»³³Ø±¡Âç³Ø), ¿À¾Â ½¼¿­ (Æü»º¼«Æ°¼Ö³ô¼°²ñ¼Ò), ²£·¦ °ÂÆà, ¥í¥Ú¥º ¥®¥è¡¼¥à (ÀÄ»³³Ø±¡Âç³Ø)
¥Ú¡¼¥¸pp. 1254 - 1258
¥­¡¼¥ï¡¼¥É²»À¼ÂÐÏÃ, ¥«¡¼¥Ê¥Ó, ±¿Å¾Éé²Ù
¥¢¥Ö¥¹¥È¥é¥¯¥ÈËܸ¦µæ¤Ç¤Ï¡¤¥«¡¼¥Ê¥Ó¥²¡¼¥·¥ç¥óÍøÍÑ»þ¤Î²»À¼ÂÐÏäËÃåÌܤ·¡¢±¿Å¾Éé²Ù¤Î¹âÄã¤Ë¤è¤ëȯÏþõ¶·¤ÎÊѲ½¤Ë¤Ä¤¤¤ÆÄ´ºº¤·¤¿¡¥¿Í´Ö¤Î¼«Í³¤ÊȯÏäˤâÂбþ²Äǽ¤Êµ¿»÷¥«¡¼¥Ê¥Ó¤È±¿Å¾Éé²Ù¤Î°Û¤Ê¤ë¾õ¶·¤òÈ¿±Ç¤·¤¿¥É¥é¥¤¥Ó¥ó¥°¥·¥ß¥å¥ì¡¼¥¿¤òÍѤ¤¤Æ¡¤±¿Å¾¼Ô¤ËÂФ·¤Æ±¿Å¾¥¿¥¹¥¯¤¬²Ý¤»¤é¤ì¤¿´Ä¶­²¼¤Ç²»À¼ÂÐÏÃ¥·¥¹¥Æ¥à¤È¤ÎÂÐÏÃ¥¿¥¹¥¯¤ò¼Â»Ü¤·¡¤¥É¥é¥¤¥Ð¤ÎȯÏäÎÆÃħ¤òÄ´¤Ù¤ë¼Â¸³¤ò¹Ô¤Ã¤¿¡¥Ê¬ÀÏ·ë²Ì¤«¤é¡¤¸À¸ìŪÆÃħ¤Ï¤Û¤È¤ó¤ÉÊѲ½¤¬¤Ê¤«¤Ã¤¿¤¬¡¤ÂÐÏÃŪÆÃħ¤ÏUser Response Time(URT)µÚ¤ÓTime For Thinking(TFT)¤Ë¤Ä¤¤¤Æ±¿Å¾Éé²Ù¤¬¹â¤¤¤È¤­¤ËÍ­°Õ¤ËÁý²Ã¤·¤Æ¤¤¤¿¡¥°Ê¾å¤«¤é¡¤±¿Å¾Éé²Ù¤¬¹â¤¤¾ì¹ç¡¤¥«¡¼¥Ê¥Ó¤Ø¤Î±þÅú¤¬º¤Æñ¤Ë¤Ê¤ë²ÄǽÀ­¤¬¹â¤¤¤³¤È¤¬¼¨º¶¤µ¤ì¤¿¡¥

6D-4 (»þ´Ö: 15:10 - 15:30)
Âê̾ÈóÉéÃͥƥ󥽥ë°ø»Òʬ²ò¤òÍѤ¤¤¿´Ñ¸÷¹ÔÆ°¥Ç¡¼¥¿¤«¤é¤Î¾ðÊóÃê½Ð
Ãø¼Ô*µ×ÊÝ ´ð (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø Àèü²Ê³Øµ»½Ñ¸¦µæ²Ê ¾ðÊó²Ê³ØÎΰè/Íý²½³Ø¸¦µæ½ê ³×¿·ÃÎǽÅý¹ç¸¦µæ¥»¥ó¥¿¡¼ ´Ñ¸÷¾ðÊó²òÀÏ¥Á¡¼¥à), ÅÄÃæ ¹¨µ¨, Ãæ¼ ů (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø Àèü²Ê³Øµ»½Ñ¸¦µæ²Ê ¾ðÊó²Ê³ØÎΰè/Íý²½³Ø¸¦µæ½ê ³×¿·ÃÎǽÅý¹ç¸¦µæ¥»¥ó¥¿¡¼ ´Ñ¸÷¾ðÊó²òÀÏ¥Á¡¼¥à/ÆàÎÉÀèüÂç¥Ç¡¼¥¿¶îÆ°·¿¥µ¥¤¥¨¥ó¥¹ÁϤ¥»¥ó¥¿¡¼)
¥Ú¡¼¥¸pp. 1259 - 1263
¥­¡¼¥ï¡¼¥É¥¤¥ó¥Ð¥¦¥ó¥É, ¥Æ¥ó¥½¥ë, ÈóÉéÃͥƥ󥽥ë°ø»Òʬ²ò, ¥¯¥é¥¹¥¿¥ê¥ó¥°
¥¢¥Ö¥¹¥È¥é¥¯¥È¥¤¥ó¥Ð¥¦¥ó¥É´Ñ¸÷¤òÂ¥¿Ê¤¹¤ë¤¿¤á¤Ë¤Ï¡¤¤Þ¤º´Ñ¸÷µÒ¤Î¹ÔÆ°¤äÂÚºßÀè¤òʬÀϤ·¡¤¤½¤Î·¹¸þ¤ª¤è¤ÓÍ×°ø¤òÍý²ò¤¹¤ë¤³¤È¤¬¡¤É¬Í×ÉԲķç¤Ç¤¢¤ë¤È¸À¤¨¤ë¡¥ ´Ñ¸÷µÒ¤Î¹ÔÆ°¤Ë¤ÏÍÍ¡¹¤ÊÍ×°ø¡¦¾ðÊ󤬴ޤޤì¤Æ¤ª¤ê¡¤¤½¤ì¤é¤ò°ìµó¤ËʬÀϤ¹¤ë¤³¤È¤ÏÍưפǤϤʤ¤¡¥¤½¤³¤Ç¡¤º£²ó²æ¡¹¤Ï¥¹¥Þ¡¼¥È¥Õ¥©¥ó¥¢¥×¥ê¤«¤éÆÀ¤é¤ì¤¿Â¿¼¡¸µ¤Î´Ñ¸÷¹ÔÆ°¥í¥°¥Ç¡¼¥¿¤«¤é¡¤ÆüËÜÁ´¹ñ¤òÂоݤȤ·¤¿³°¹ñ¿Í´Ñ¸÷µÒ¤Î¹ÔÆ°¥Ñ¥¿¡¼¥ó¤ò¡¤Âں߻þ´ÖÂÓ/Âں߾ì½ê/¿äÄêµï½»¹ñ¡¤¤Î3³¬¥Æ¥ó¥½¥ë¤È¤·¤Æ¹½À®¤·¡¤ÈóÉéÃͥƥ󥽥ë°ø»Òʬ²ò(Nonnegative Tensor Factorization, NTF)¤òŬÍѤ¹¤ë¤³¤È¤ÇʬÀϤò¹Ô¤Ã¤¿¡¥·ë²Ì¤È¤·¤Æ¡¤3³¬¥Æ¥ó¥½¥ë¤ò5¤Ä¤Î¥¯¥é¥¹¥¿¤Ëʬ²ò¤¹¤ë¤³¤È¤Ç¡¤7·î¤È8·î¤Ç¤Ï¥¢¥á¥ê¥«¤òÃæ¿´¤È¤·¤¿Ë¬Æü³°¹ñ¿Í´Ñ¸÷µÒ¤Î¥¯¥é¥¹¥¿µÚ¤Ó¥¤¥¿¥ê¥¢¤òÃæ¿´¤È¤·¤¿Ë¬Æü³°¹ñ¿Í´Ñ¸÷µÒ¤Î¥¯¥é¥¹¥¿¤òÃê½Ð¤¹¤ë¤³¤È¤¬¤Ç¤­¤¿¡¥


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¥»¥Ã¥·¥ç¥ó 6E  ¹Ôưǧ¼±±þÍÑ
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 14:10 - 15:30
Éô²°: Í·Éñ¡¦¸Þ¤ÎÍ·
ºÂĹ: ÊÆß· ÂóϺ (̾¸Å²°Âç³Ø)

Í¥½¨ÏÀʸ¾Þ / Paper Awards
6E-1 (»þ´Ö: 14:10 - 14:30)
Âê̾Preliminary Investigation of Assembly Work Activity Recognition with Wearable Sensors via Unsupervised Learning
Ãø¼Ô*Qingxin Xia (Graduate School of Information Science and Technology, Osaka University), Atsushi Wada (Corporate Manufacturing Engineering Center, Toshiba Corporation), Joseph Korpela, Takuya Maekawa (Graduate School of Information Science and Technology, Osaka University), Yasuo Namioka (Corporate Manufacturing Engineering Center, Toshiba Corporation)
¥Ú¡¼¥¸pp. 1264 - 1272
¥­¡¼¥ï¡¼¥ÉActivity Recognition, Wearable sensor, Factory work
¥¢¥Ö¥¹¥È¥é¥¯¥ÈThis paper presents an unsupervised method for recognizing assembly work done by factory workers by using wearable sensor data. Such assembly work is a common part of line production systems and typically involves the factory workers performing a repetitive work process made up of a sequence of manual operations, such as setting a board on a workbench and screwing parts onto the board. This study aims to recognize the starting and ending times for individual operations in such work processes through analysis of sensor data collected from the workers along with analysis of the process instructions that detail and describe the flow of operations for each work process. We propose a particle-filter-based factory activity recognition method that leverages (i) trend changes in the sensor data detected by a nonparametric Bayesian hidden Markov model, (ii) sensor-data similarities between consecutive repetitions of individual operations, and (iii) frequent sensor-data patterns (motifs) discovered in the overall assembly work processes. We evaluated the proposed method from six workers collected in actual factories, achieving a recognition accuracy of 83.3% (macro-averaged F-measure).

Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
6E-2 (»þ´Ö: 14:30 - 14:50)
Âê̾¥Ù¥Ó¡¼¥«¡¼ÍøÍÑ»þ¤Ë¤ª¤±¤ë¼þ°Ï¤Ø¤ÎÆ°ºîͽ¹ð¥·¥¹¥Æ¥à¤Î¼ÂÁõ
Ãø¼Ô*Ω²Ö ¹ª¼ù (ÆüËÜÂç³ØʸÍý³ØÉô), ÉÙ±Ê »í²» (ÆüËÜÂç³ØÂç³Ø±¡Áí¹ç´ðÁòʳظ¦µæ²Ê), ÂçÀ¾ ½Óµ± (ÆüËÜÂç³ØʸÍý³ØÉô), ¸â ·òϯ (ÆüËÜÂç³ØÂç³Ø±¡Áí¹ç´ðÁòʳظ¦µæ²Ê), µÜÅÄ ¾Ï͵ (ÆüËÜÂç³ØʸÍý³ØÉô)
¥Ú¡¼¥¸pp. 1273 - 1279
¥­¡¼¥ï¡¼¥É¥Ù¥Ó¡¼¥«¡¼, ¹Ôưǧ¼±, »ö¸ÎËÉ»ß, µ¡³£³Ø½¬
¥¢¥Ö¥¹¥È¥é¥¯¥È³¹Ãæ¤Ç¥Ù¥Ó¡¼¥«¡¼ÍøÍѼԤÈÊâ¹Ô¼Ô¡¦¼«Å¾¼ÖÍøÍѼԤξ×ÆÍ»ö¸Î¤¬µ¯¤³¤ê¤½¤¦¤Ê¾ìÌ̤ò¤¿¤Ó¤¿¤Ó¸«¤«¤±¤ë¤³¤È¤¬¤¢¤ë¡¥¥Ù¥Ó¡¼¥«¡¼ÍøÍѼԤȡ¤Êâ¹Ô¼Ô¤ä¼«Å¾¼ÖÍøÍѼԤ¬¾×Æͤ·¤¿¾ì¹ç¡¤¥Ù¥Ó¡¼¥«¡¼¤¬²£Å¾¤¹¤ë¤Ê¤É¤·¤Æ¡¤ÀÖ¤Á¤ã¤ó¤ÎÌ¿¤Ë´Ø¤ï¤ë»öÂÖ¤¬À¸¤¸¤ë²ÄǽÀ­¤¬¤¢¤ë¡¥¤³¤ÎÌäÂê¤ò²ò·è¤¹¤ë¤¿¤á¤Ë²æ¡¹¤Ï¡¤¥Ù¥Ó¡¼¥«¡¼ÍøÍѼԤ¬ÆÃÊ̤ÊÁàºî¤ò¤¹¤ë¤³¤È¤Ê¤¯¡¤¥Ù¥Ó¡¼¥«¡¼¤Î¼¡¤ÎÆ°¤­¤òͽ¬¤·¤Æ¼þ°Ï¤ËÄÌÃΤ¹¤ë¥·¥¹¥Æ¥à¤òÄó°Æ¤·¤Æ¤­¤¿¡¥ËܹƤǤÏÄó°Æ¥·¥¹¥Æ¥à¤Î¼Â¸½¤Î¤¿¤á¡¤¥·¥¹¥Æ¥à¤Î¼ÂÁõ¤ò¹âÅÙ²½¤·¡¤¥Ù¥Ó¡¼¥«¡¼ÍøÍÑ»þ¤Î¥»¥ó¥µ¥Ç¡¼¥¿¤«¤éÆ°ºî¿äÄê¤Îɾ²Á¼Â¸³¤ò¹Ô¤Ã¤¿¡¥¼Â¸³·ë²Ì¤è¤ê¡¤Â¾¼Ô¤Î¥Ù¥Ó¡¼¥«¡¼¤ÎÆ°ºî¥Ç¡¼¥¿¤«¤é¹½ÃÛ¤·¤¿¿äÄê´ï¤òÍѤ¤¤Æ°ìÄêÀºÅ٤ǥ٥ӡ¼¥«¡¼¤ÎÆ°ºî¿äÄê¤ò¹Ô¤¨¤ë²ÄǽÀ­¤ò¼¨¤·¤¿¡¥

6E-3 (»þ´Ö: 14:50 - 15:10)
Âê̾¥â¡¼¥·¥ç¥ó¥­¥ã¥×¥Á¥ã¤òÍѤ¤¤¿¹Ôưǧ¼±¤Ë¤ª¤±¤ë¥Þ¡¼¥«¡¼¿ÈÂÎÂбþÉÕ¤±ºî¶È¤Îºï¸º
Ãø¼Ô*ÉðÅÄ ¿Â¸ã, Paula Lago, ÂçËÌ ¹ä, °æ¾å ÁϤ (¶å½£¹©¶ÈÂç³Ø), ½ÐÌî µÁ§ (³ô¼°²ñ¼Ò¥±¥¢¥³¥à)
¥Ú¡¼¥¸pp. 1280 - 1286
¥­¡¼¥ï¡¼¥É¹Ôưǧ¼±, µ¡³£³Ø½¬, ¥â¡¼¥·¥ç¥ó¥­¥ã¥×¥Á¥ã
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6E-4 (»þ´Ö: 15:10 - 15:30)
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Ãø¼Ô*¸åÆ£ ¹­¼ù, ÉðÅÄ ¿Â¸ã, Paula Lago, ÂçËÌ ¹ä, °æ¾å ÁϤ (¶å½£¹©¶ÈÂç³Ø)
¥Ú¡¼¥¸pp. 1287 - 1290
¥­¡¼¥ï¡¼¥É¹Ôưǧ¼±, ¥»¥ó¥µ, µ¡³£³Ø½¬, ²Ã®ÅÙ, ²ð¸î
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¥»¥Ã¥·¥ç¥ó 6F  ¥·¥¹¥Æ¥àÀ©ºî
Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 14:10 - 15:30
Éô²°: Í·Éñ¡¦»°¤ÎÍ·
ºÂĹ: °¤ÇÜÇî¿® (ÅìµþÅŵ¡Âç³Ø)

Í¥½¨ÏÀʸ¾Þ / Paper Awards
6F-1 (»þ´Ö: 14:10 - 14:30)
Âê̡̾²è¤Ë¤ª¤±¤ë¥»¥ê¥Õ°ÌÃ֤ȰÕÌ£¤Î»þ·ÏÎó¤ò¹Íθ¤·¤¿Ïüԥ­¥ã¥é¥¯¥¿¡¼¤Î¿äÄê
Ãø¼ÔÃæÀî ÎÊ (ÀéÍÕÂç³ØÂç³Ø±¡Í»¹çÍý¹©³ØÉÜ), *Çßß· ÌÔ, Âçß· ÈϹâ (ÀéÍÕÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ±¡)
¥Ú¡¼¥¸pp. 1291 - 1297
¥­¡¼¥ï¡¼¥ÉLSTM, µ¡³£³Ø½¬, Ì¡²è, ÏüԿäÄê
¥¢¥Ö¥¹¥È¥é¥¯¥ÈÌ¡²èºîÉʤϡ¢»ïÌ̹½À®¤ÎÆÃÀ­¡Ê¥³¥Þ³ä¤ê¡¢¿á¤­½Ð¤·¡Ë¤äÀþ²è¤Èʸ»ú¤¬º®ºß¤¹¤ëÍÍÂ֤Τ¿¤á¤Ë¡¢Ê¸»úǧ¼±µ»½Ñ¤ä¿Íʪ¸¡½Ðµ»½Ñ¤òñÆȤÇÍѤ¤¤¿¾ðÊóÃê½Ð¤¬Æñ¤·¤¤¡£¤½¤Î¤¿¤á¡¢Ì¡²è¥á¥¿¥Ç¡¼¥¿¤ÎºîÀ®¤Ë¤Ï¼êºî¶È¤¬É¬¿Ü¤ÇÉéô¤¬Â礭¤¤¡£ ¤È¤ê¤ï¤±¡¢Ç¤°Õ¤Î¥»¥ê¥Õ¤È¤½¤ì¤òȯ¤·¤¿¥­¥ã¥é¥¯¥¿¡¼¤ÎÂбþÉÕ¤±¤Ï¼«Æ°Ç§¼±¤¬º¤Æñ¤Ç¤¢¤ë¤È¤µ¤ì¤Æ¤¤¤ë¡£¤½¤³¤ÇËܸ¦µæ¤Ç¤Ï¡¢Ì¡²è¤Î¥»¥ê¥Õ¤ò°ÌÃ֤ȰÕÌ£¤Î´ÑÅÀ¤«¤é²òÀϤ¹¤ë¤È¤È¤â¤Ë¡¢»þ·ÏÎó¤ËÂФ¹¤ë³Ø½¬¥â¥Ç¥ë¤Ç¤¢¤ëºÆµ¢·¿¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯¡ÊRNN¡Ë¤òÍøÍѤ·¤Æ¡¢¥»¥ê¥Õ¤ÎÏüԤò¼«Æ°¿äÄꤹ¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡£Äó°Æ¼êË¡¤Ï¡¢°ÕÌ£¾ðÊó¤È»þ·ÏÎ󤫤éʸ̮¤òÇÄ°®¤¹¤ë¤³¤È¤Ç¡¢¤³¤ì¤Þ¤Çº¤Æñ¤Ç¤¢¤Ã¤¿¥­¥ã¥é¥¯¥¿¡¼¤È¥»¥ê¥Õ¤¬Æ±°ì¥³¥Þ¤Ë¸ºß¤·¤Ê¤¤¾ì¹ç¤Ç¤¢¤Ã¤Æ¤âÀºÅ٤褯ÂбþÉÕ¤±¤¬²Äǽ¤Ç¤¢¤ë¡£Âбþ¿äÄê¤Ë¤ÏÆÃħÎ̤Ȥ·¤Æ¡£¤³¤ì¤Þ¤Ç¤ËÍ­¸ú¤Ç¤¢¤ë¤³¤È¤¬¼¨¤µ¤ì¤Æ¤¤¤ë¿á¤­½Ð¤·¤ËÂФ¹¤ë³Æ¥­¥ã¥é¥¯¥¿¡¼´Ö¤Îµ÷Î¥¤ª¤è¤Ó¥»¥ê¥Õ¤Îʬ»¶°Ọ̃ɽ¸½¤òÍѤ¤¤ë¡£¤Þ¤¿¡¢Ì¡²è¤Ïʪ¸ì¤¬»þ·ÏÎó¤Ç·Ò¤¬¤Ã¤Æ¤¤¤ë¤³¤È¤«¤é¡¢RNN¤ò»È¤¦¤³¤È¤Çʸ̮¤«¤éÆÀ¤é¤ì¤ë¾ðÊó¤Ë¤è¤Ã¤Æ¥­¥ã¥é¥¯¥¿¡¼¤Î¿äÄêÀºÅÙ¤ò¹â¤á¤é¤ì¤ë¤È´üÂԤǤ­¤ë¡£¥»¥ê¥Õ¤ËÂФ¹¤ë³Æ¥­¥ã¥é¥¯¥¿¡¼¤Îµ÷Î¥¾ðÊó¤Ë¤è¤ë¿äÄê¡¢¤½¤³¤Ë¥»¥ê¥Õ¤Îʬ»¶°Ọ̃ɽ¸½¤ò²Ã¤¨¤¿ÆÃħ¥Ù¥¯¥È¥ë¤Ë¤è¤ë¿äÄê¡¢µ÷Î¥¾ðÊó¤Èʬ»¶°Ọ̃ɽ¸½¤ËRNN¤ò»È¤Ã¤¿Äó°Æ¼êË¡¤Ë¤è¤ë¿äÄê¤Î3¤Ä¤Î¿äÄêÀºÅÙ¤òÈæ³Ó¤·¡¢Äó°Æ¼êË¡¤ÎÍ­¸úÀ­¤ò¸¡¾Ú¤·¤¿¡£

6F-2 (»þ´Ö: 14:30 - 14:50)
Âê̾¼«Î§±ÇÁü½èÍý¤òȼ¤¦¥È¥é¥¹¥È»Ø¸þ¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®¥·¥¹¥Æ¥à¤Î¸¡Æ¤
Ãø¼Ô*¾¾ËÜ Å¯, µÁµ× ÃÒ¼ù (ÂçºåÂç³Ø), Àî¾å ÊþÌé (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø/ÂçºåÂç³Ø), »ûÀ¾ ͵°ì (¾ðÊóÄÌ¿®¸¦µæµ¡¹½/ÂçºåÂç³Ø)
¥Ú¡¼¥¸pp. 1298 - 1300
¥­¡¼¥ï¡¼¥É¥È¥é¥¹¥È»Ø¸þ, ¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®, ʬ»¶½èÍý
¥¢¥Ö¥¹¥È¥é¥¯¥È¶áǯ¤Î¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®¤ÎÉáµÚ¤Ëȼ¤¤YouTuber¤Ê¤É¤Î¥¤¥ó¥¿¡¼¥Í¥Ã¥ÈÇÛ¿®¼Ô¤¬ÃíÌܤòÍá¤Ó¤Æ¤¤¤ë.¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®¤Ç¤ÏÇÛ¿®¼Ô¤¬°ÜÆ°¤·¤Ê¤¬¤é¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Ç¼«¿È¤ò»£±Æ¤·¥¤¥ó¥¿¡¼¥Í¥Ã¥È¤ò²ð¤·¤Æ±ÇÁü¤òÇÛ¿®¤¹¤ë¤³¤È¤¬Â¿¤¤.ÇÛ¿®¼Ô¤È»ëÄ°¼Ô¤Î´Ö¤Ë¿®Íê´Ø·¸¡Ê¥È¥é¥¹¥È¤¬Ìµ¤¤¾ì¹ç»ëÄ°¼Ô¤¬ÇÛ¿®¼Ô¤ò¶¼Ç÷¤·¤¿¤ê½±¤¤³Ý¤«¤«¤ë¤È¤¤¤Ã¤¿¼Ò²ñÌäÂ꤬ȯÀ¸¤·¤Æ¤ª¤ê,¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®¤Ë¤ª¤¤¤Æ¥È¥é¥¹¥È¤ò³ÎÊݤ¹¤ë¤³¤È¤ÇÇÛ¿®¼Ô¤Ï°Â¿´¤·¤Æ¾ðÊóȯ¿®¤ò¹Ô¤¨¤ë.¤·¤«¤·¤³¤ì¤Þ¤Ç¤Ë¥È¥é¥¹¥È¤ò¹Íθ¤·¤¿¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®¥·¥¹¥Æ¥à¤Ï¤Ê¤¯,ÇÛ¿®¼Ô¤Ï´é¤ò±£¤·¤ÆÇÛ¿®¤·¤¿¤ê¼þ¤ê¤¬±Ç¤é¤Ê¤¤¤è¤¦¤ËÇÛ¿®¤·¤Æ¤¤¤¿.¤½¤³¤Ç,Ëܸ¦µæ¤Ç¤Ï¥È¥é¥¹¥È¤ò¹Íθ¤·¤¿¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®¥·¥¹¥Æ¥à¤Ç¤¢¤ë¥È¥é¥¹¥È»Ø¸þ¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®¥·¥¹¥Æ¥à¤òÄó°Æ¤¹¤ë.¥È¥é¥¹¥È»Ø¸þ¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®¥·¥¹¥Æ¥à¤Ç¤Ï,¥È¥é¥¹¥È¤Î̵ͭ¤Ë±þ¤¸¤Æ¼«Î§Åª¤Ë±ÇÁü½èÍý¤ò¹Ô¤¦.¥È¥é¥¹¥È¤Î̵¤¤¾õ¶·¤Ç¤ÏÇÛ¿®¼Ô¤Ë´Ø¤¹¤ë¾ðÊó¤ò±£Ê乤ëÊý¿Ë¤Ç±ÇÁü½èÍý¤ò¹Ô¤¤,Í­¤ë¾õ¶·¤Ç¤Ï¥È¥é¥¹¥È¤ò¤µ¤é¤Ë¿¼¤¯¹½ÃÛ¤¹¤ë¤¿¤á¤ËÇÛ¿®¼Ô¤Ë´Ø¤¹¤ë¾ðÊó¤ò˽Ϫ¤¹¤ëÊý¿Ë¤Ç±ÇÁü½èÍý¤ò¹Ô¤¦.Ëܸ¦µæ¤Ç¤Ï¼«Î§±ÇÁü½èÍý¤òȼ¤¦¥È¥é¥¹¥È»Ø¸þ¥¤¥ó¥¿¡¼¥Í¥Ã¥È¥é¥¤¥ÖÇÛ¿®¥·¥¹¥Æ¥à¤Î¸¡Æ¤¤ò¹Ô¤¤ÇÛ¿®¼Ô¾ðÊó¤È¥È¥é¥¹¥È´Ä¶­¤È±ÇÁüÆâÍƤδط¸¤Ë¤Ä¤¤¤ÆµÄÏÀ¤ò¹Ô¤Ã¤¿.

¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
6F-3 (»þ´Ö: 14:50 - 15:10)
Âê̾¥¹¥Þ¡¼¥È¥Õ¥©¥óVR¤òÍѤ¤¤¿»ùƸ¸ø±àÍ·¶ñ¤ÎÀ䶫²½¼êË¡¤ÎÄó°Æ
Ãø¼Ô*¿·ÃÏ Íΰì, ¿åÌî ¿µ»Î (°¦Ã驶ÈÂç³ØÂç³Ø±¡ ·Ð±Ä¾ðÊó²Ê³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1301 - 1307
¥­¡¼¥ï¡¼¥ÉVR, »ë³ÐŪ¸ØÄ¥, ¥»¥ó¥µ, ¥¤¥ó¥¿¥é¥¯¥·¥ç¥ó, ¥¹¥Þ¡¼¥È¥Õ¥©¥ó
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
6F-4 (»þ´Ö: 15:10 - 15:30)
Âê̾ΩÂ⻶Á¤òÍѤ¤¤ë¾®·¿¥µ¥é¥¦¥ó¥É¥¹¥Ô¡¼¥«¡¼´Ä¶­¤Î¸¦µæ
Ãø¼Ô*¾±»Ò ÂöϺ (·ÄØæµÁ½ÎÂç³ØÂç³Ø±¡¥á¥Ç¥£¥¢¥Ç¥¶¥¤¥ó¸¦µæ²Ê), ÄÍÅÄ ³Ø (ÅìµþÂç³ØÂç³Ø±¡¾ðÊóÍý¹©³Ø·Ï¸¦µæ²Ê), ²ÃÆ£ ϯ, º½¸¶ ½¨¼ù (·ÄØæµÁ½ÎÂç³ØÂç³Ø±¡¥á¥Ç¥£¥¢¥Ç¥¶¥¤¥ó¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1308 - 1315
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 14:10 - 15:30
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6G-1 (»þ´Ö: 14:10 - 14:30)
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Ãø¼Ô*¿Ûˬ Çîɧ, ÂçÄÚ ½ß, Ãæ¼ Í¥¸ã (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø), Ìî¸ý ¿¿»Ë (³ô¼°²ñ¼ÒLIFULL)
¥Ú¡¼¥¸pp. 1316 - 1321
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6G-2 (»þ´Ö: 14:30 - 14:50)
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Ãø¼Ô*±Û¸å ¹¨µª, ¾®ÎÓ Ì­ (ÌÀ¼£Âç³Ø)
¥Ú¡¼¥¸pp. 1322 - 1329
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6G-3 (»þ´Ö: 14:50 - 15:10)
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Ãø¼Ô*¿ûÌî ¿¿¸ù (ÌÀ¼£Âç³ØÀèü¿ôÍý²Ê³Ø¸¦µæ²ÊÀèü¥á¥Ç¥£¥¢¥µ¥¤¥¨¥ó¥¹À칶), ¾®ÎÓ Ì­ (ÌÀ¼£Âç³ØÁí¹ç¿ôÍý³ØÉôÀèü¥á¥Ç¥£¥¢¥µ¥¤¥¨¥ó¥¹³Ø²Ê)
¥Ú¡¼¥¸pp. 1330 - 1334
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 14:10 - 15:30
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6H-1 (»þ´Ö: 14:10 - 14:30)
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¥Ú¡¼¥¸pp. 1335 - 1341
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6H-2 (»þ´Ö: 14:30 - 14:50)
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Ãø¼Ô*¾å¼ ¹¦ÌÀ (¹­Åç»ÔΩÂç³Ø¾ðÊó²Ê³ØÉô), °æ¾å ÇîÇ· (¹­Åç»ÔΩÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), ÂçÊ¿ ½¤»ü (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³ØÀèü²Ê³Øµ»½Ñ¸¦µæ²Ê), ÀÐÅÄ ¸­¼£ (¹­Åç»ÔΩÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1342 - 1347
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6H-3 (»þ´Ö: 14:50 - 15:10)
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¥Ú¡¼¥¸pp. 1348 - 1352
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Æü»þ: 2019ǯ7·î5Æü(¶â) 8:30 - 10:10
Éô²°: É÷¤ÎÅÎ
ºÂĹ: ¾®Àî δ°ì (¾ðÊó½èÍý¿ä¿Êµ¡¹½)

¥·¥Ë¥¢¥ê¥µ¡¼¥Á¥ã¾Þ / Senior Researcher Awards
7A-1 (»þ´Ö: 8:30 - 8:50)
Âê̾IoT»þÂå¤Î¥»¥­¥å¥ê¥Æ¥£¤È¥Õ¥©¥ì¥ó¥¸¥Ã¥¯¤Îµ»½Ñ²ÝÂê¤ÈÂбþºö
Ãø¼Ô*º´¡¹ÌÚ ÎÉ°ì (ÅìµþÅŵ¡Âç³Ø)
¥Ú¡¼¥¸pp. 1353 - 1361
¥­¡¼¥ï¡¼¥ÉIoT, ¥ê¥¹¥¯, ¥»¥­¥å¥ê¥Æ¥£, ¥Õ¥©¥ì¥ó¥¸¥Ã¥¯, µ»½Ñ²ÝÂê
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7A-2 (»þ´Ö: 8:50 - 9:10)
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Ãø¼Ô*ËÌÂô ¶Æ¹¨, ¼ÄÅÄ ÍÛ°ì (ËÌΦÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø)
¥Ú¡¼¥¸pp. 1362 - 1367
¥­¡¼¥ï¡¼¥É¥µ¥¤¥Ð¡¼¥»¥­¥å¥ê¥Æ¥£, µ½âÖŪËɸæ, APT¹¶·â, Honeypot Detection, Fake Honeypot
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7A-3 (»þ´Ö: 9:10 - 9:30)
Âê̾·§ËÜÃϿ̸å¤ÎÇÀ¶È¥Ü¥é¥ó¥Æ¥£¥¢³èÆ°»Ù±ç¥·¥¹¥Æ¥à¤Î³èÍѾõ¶·¤«¤é¤Î¹Í»¡¤È¥·¥¹¥Æ¥à¹½À®¤Ë´Ø¤¹¤ë¸¡Æ¤
Ãø¼Ô*¹âÅÄ ·òÅÎ (ÆüËÜÂç³ØÂç³Ø±¡¡¿Íý¹©³Ø¸¦µæ²Ê), ²£°æ ²ÆÀ¸ (»°±Û°ËÀªÃ°¥·¥¹¥Æ¥à¡¦¥½¥ê¥å¡¼¥·¥ç¥ó¥º), ·ªÌî ½Ó°ì, µÈ³« ÈÏ¾Ï (ÆüËÜÂç³Ø¡¿Íý¹©³ØÉô)
¥Ú¡¼¥¸pp. 1368 - 1378
¥­¡¼¥ï¡¼¥É¥Ü¥é¥ó¥Æ¥£¥¢, Well-being, ¿®Íê
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7A-4 (»þ´Ö: 9:30 - 10:10)
Âê̾(¾·ÂÔ¹Ö±é) £Á£É¤Î¥»¥­¥å¥ê¥Æ¥£¤Î¸½¾õ¡§¸¦µæÆ°¸þ¤È¶âͻʬÌî¤Ç¤Î³èÍѤˤ«¤«¤ï¤ë¹Í»¡
Ãø¼Ô*±§º¬ Àµ»Ö (ÆüËܶä¹Ô¶âÍ»¸¦µæ½ê)
¥Ú¡¼¥¸p. 1379
¥­¡¼¥ï¡¼¥Éµ¡³£³Ø½¬, ¶âÍ», ¥»¥­¥å¥ê¥Æ¥£, ¥ê¥¹¥¯
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¥»¥Ã¥·¥ç¥ó 7B  ¥¢¥×¥ê¥±¡¼¥·¥ç¥ó
Æü»þ: 2019ǯ7·î5Æü(¶â) 8:30 - 10:10
Éô²°: ²ÖÉñ¡¦°ì¤Î²Ö
ºÂĹ: Àи¶ ¿Ê (ÀŲ¬Âç³Ø)

7B-1 (»þ´Ö: 8:30 - 8:50)
Âê̾Wordy¡§¥ï¡¼¥É¥¯¥é¥¦¥É¤Ë¤è¤ëÍ×Ìó¤È¸¡º÷¤ò»Ù±ç¤¹¤ë e ¥é¡¼¥Ë¥ó¥°¥·¥¹¥Æ¥à
Ãø¼Ô*¼ë °Î, Ä¥ ·³, ÈôÅÄ Çî¾Ï (»º¶Èµ»½ÑÂç³Ø±¡Âç³Ø)
¥Ú¡¼¥¸pp. 1380 - 1385
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7B-2 (»þ´Ö: 8:50 - 9:10)
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Ãø¼Ô*¸Í±© ½Ó²ð, ¶¶ËÜ ¹ÀÆó (´ä¼ê¸©Î©Âç³Ø¥½¥Õ¥È¥¦¥§¥¢¾ðÊó³ØÉô)
¥Ú¡¼¥¸pp. 1386 - 1391
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7B-3 (»þ´Ö: 9:10 - 9:30)
Âê̾±ó³Öºî¶È»Ù±ç¥Þ¥Ë¥Ô¥å¥ì¡¼¥¿¤Ë´Ø¤¹¤ë¸¦µæ - Ê£¿ô¥¤¥ó¥¿¥Õ¥§¡¼¥¹¤Ë¤ª¤±¤ëÁàºîÀ­¤ÎÈæ³Ó -
Ãø¼Ô*ÀÐÀî ÂçÊå (ÆüËÜÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), ÉðÆ£ ¿­ÍÎ (ÆüËÜÂç³Ø¹©³ØÉôµ¡³£¹©³Ø²Ê)
¥Ú¡¼¥¸pp. 1392 - 1395
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7B-4 (»þ´Ö: 9:30 - 9:50)
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¥Ú¡¼¥¸pp. 1396 - 1401
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7B-5 (»þ´Ö: 9:50 - 10:10)
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Ãø¼Ô*º£°æ Èþ´õ, ¹©Æ£ ÎÜÍþ»Ò (¤ªÃã¤Î¿å½÷»ÒÂç³Ø), ±Ý Èþµª (IBM Research Tokyo), ¾®¸ý Àµ¿Í (¤ªÃã¤Î¿å½÷»ÒÂç³Ø)
¥Ú¡¼¥¸pp. 1402 - 1408
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¥¢¥Ö¥¹¥È¥é¥¯¥È¶áǯÆüËܤòˬ¤ì¤ë³°¹ñ¿Í´Ñ¸÷µÒ¤ÏµÞ·ã¤ËÁý²Ã¤·¤Æ¤ª¤ê, 2020 ǯ¤Ë³«ºÅ¤µ¤ì¤ëÅìµþ¥ª¥ê¥ó¥Ô¥Ã¥¯¡¦¥Ñ¥é¥ê¥ó¥Ô¥Ã¥¯¤ò¹Íθ¤¹¤ë¤È¹¹¤Ê¤ëÁý²Ã¤¬¸«¹þ¤Þ¤ì¤ë. ´Ñ¸÷µÒ¤ÎÁý²Ã¤Ëȼ¤¤, ͭ̾¤Ê´Ñ¸÷¥¹¥Ý¥Ã¥È¤Ê¤É¤Î¾ðÊó¤òºÜ¤»¤¿¥¬¥¤¥É ¥Ö¥Ã¥¯¤ä Web ¥µ¥¤¥È¤Ï¸«¼õ¤±¤é¤ì¤ë¤è¤¦¤Ë¤Ê¤Ã¤Æ¤­¤¿. ¤·¤«¤·¤Ê¤¬¤é, ¤½¤ì¤é¤ÎÇÞÂΤ˺ܤäƤ¤¤Ê¤¤¤è¤¦¤Ê¥í¡¼¥«¥ë¤Ê¾ðÊó¤äº£¤Þ¤µ¤Ë³«ºÅ¤µ¤ì¤Æ¤¤¤ë¥¤¥Ù¥ó¥È¤òÃΤêÆÀ¤ë¤³¤È¤Ï, ¸½¾õÆñ¤·¤¤. ¤Þ¤¿¶½Ì£¤Î¤¢¤ë¥¤¥Ù¥ó¥È¾ðÊó¤ò¼«¿È¤Î¼ê¤Ë¤è¤Ã¤Æ¸«¤Ä¤±¤ë¤Î¤Ï¼ê´Ö¤¬¤«¤«¤ë. ¤½¤³¤Ç²æ¡¹¤Ï SNS ¤Ë¤¢¤ë¾ðÊó¤ËÃåÌܤ·¤¿. Ëܸ¦µæ¤Ç¤Ï, °ÌÃÖ¾ðÊó¤ò¹Íθ¤¹¤ë¤È¤È¤â¤Ë, ¥½¡¼¥·¥ã¥ë¥¹¥È¥ê¡¼¥à¤Ë´ð¤Å¤­Ë¬Æü³°¹ñ¿Í¤Î¼ñ¸þ¤ò¿äÄꤷ, ¥¤¥Ù¥ó¥È¾ðÊó¤Î½ç°ÌÉÕ¤±¤ò¹Ô¤¤ÇÛ¿®¤ò¹Ô¤¦.


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Æü»þ: 2019ǯ7·î5Æü(¶â) 8:30 - 10:10
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7C-1 (»þ´Ö: 8:30 - 8:50)
Âê̾¼«Î§·¿À¸ÂΥǡ¼¥¿¼ý½¸¤Ë¤ª¤±¤ëÏÓÁõÃå·¿¥»¥ó¥µ¤Î¿®ÍêÀ­¿äÄêË¡¤Î¸¡Æ¤
Ãø¼Ô*ÎÓ Àµ¹¬, µÈÀî ´²¼ù, Æ⻳ ¾´, ÅìÌî µ±É× (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1409 - 1414
¥­¡¼¥ï¡¼¥É¥¹¥Þ¡¼¥È¥¦¥©¥Ã¥Á, ¿´Çï¿ô, ´·À­¥»¥ó¥µ, À¸ÂΥǡ¼¥¿, ¥¦¥§¥¢¥é¥Ö¥ë¥»¥ó¥µ
¥¢¥Ö¥¹¥È¥é¥¯¥È¶áǯ¡¤¥¦¥§¥¢¥é¥Ö¥ë¥»¥ó¥µ¤ÎȯŸ¤Ë¤è¤ê¡¤ÍÍ¡¹¤ÊÀ¸ÂΥǡ¼¥¿¤ò¼ê·Ú¤Ë¼ý½¸¤¹¤ë¤³¤È¤¬²Äǽ¤È¤Ê¤Ã¤¿¡¥ ¿¼ï¿ÍͤʴĶ­¤Ë¤ª¤¤¤ÆÀ¸ÂΥǡ¼¥¿¼ý½¸¤ò¹Ô¤¦¾ì¹ç¤Ë¤Ï¡¤¥»¥ó¥µ¤ÎÁõÃåÀ­¤ä¥æ¡¼¥¶¤Î°Õ»×¤Ë¤è¤ê¡¤ÆÃÄê¤ÎüËö¤¬ÍøÍѤǤ­¤Ê¤¤¾ì¹ç¤â¤¢¤ê¡¤°Û¼ïüËö¤Îº®ºß¤¬Èò¤±¤é¤ì¤Ê¤¤¡¥Ã¼Ëö¤¬°Û¤Ê¤ë¾ì¹ç¤Ë¤Ï¬Ä긶Íý¤äÁõÃåÉô°Ì¤Î°ã¤¤¤Ë¤è¤Ã¤ÆÀºÅ٤κ¹¤¬¤¢¤ë¤¿¤á¡¤Â¬ÄêÃͤò¤½¤Î¤Þ¤ÞÈæ³Ó¤Ç¤­¤ë¤È¤Ï¸Â¤é¤Ê¤¤¡¥ ¤Þ¤¿¡¤¥Ç¥Ð¥¤¥¹¤ÎÁõÃ夬ŬÀڤ˹Ԥï¤ì¤Ê¤¤¤È¡¤Â¬ÄêÃͤΰÂÄêÀ­¤äÀºÅÙ¤ÎÄã²¼¤Ë¤Ä¤Ê¤¬¤ë¡¥ ¤³¤Î¤¿¤á¡¤À¸ÂΥǡ¼¥¿¼ý½¸¤Ë¤¢¤¿¤Ã¤Æ¤Ï¬ÄêÃͤÀ¤±¤Ç¤Ê¤¯¤½¤Î¿®ÍêÀ­¤â¤¢¤ï¤»¤Æ¼èÆÀ¤Ç¤­¤ë¤³¤È¤¬Ë¾¤Þ¤·¤¤¡¥ Ëܸ¦µæ¤Ç¤ÏÏÓÁõÃå·¿¥»¥ó¥µ¤Ë¾ÇÅÀ¤òÅö¤Æ¡¤¥Ð¥ó¥É¤ÎÄù¤á¶ñ¹ç¤¬À¸ÂΥǡ¼¥¿¤Î¬Äê¤Ë½ÅÍפǤ¢¤ë¤³¤È¤ËÃåÌܤ·¡¤ÏÓÁõÃå·¿¥»¥ó¥µ¤ËÅëºÜ¤·¤¿´·À­¥»¥ó¥µ¤òÍøÍѤ·¤¿¥Ð¥ó¥É¤ÎÄù¤á¶ñ¹ç¿äÄê¼êË¡¤òÀ߷פ·¤¿¡¥¥Ð¥ó¥É¤ÎÄù¤á¶ñ¹ç¤òÊѲ½¤µ¤»¤Æ¥¸¥ç¥®¥ó¥°¤Ë¤ª¤±¤ëÀ­Ç½É¾²Á¤ò¹Ô¤Ã¤¿¤È¤³¤í¡¤3Ãʳ¬¤Î¥Ð¥ó¥É¤ÎÄù¤á¶ñ¹ç¤òÊ¿¶ÑÀµ²òΨ51.1%¤Ç¿äÄê¤Ç¤­¤ë¤³¤È¤¬Ê¬¤«¤Ã¤¿¡¥

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7C-2 (»þ´Ö: 8:50 - 9:10)
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Ãø¼Ô¾å¸¶ Êþ»Ò, *Ìij¤ ÐÒ´õ, ²£·¦ °ÂÆà, ¥í¥Ú¥º ¥®¥è¡¼¥à (ÀÄ»³³Ø±¡Âç³Ø)
¥Ú¡¼¥¸pp. 1415 - 1418
¥­¡¼¥ï¡¼¥É²¹Åٻɷã, ³ÐÀÃ, ¥Ú¥ë¥Á¥§ÁÇ»Ò, ¥¦¥§¥¢¥é¥Ö¥ëüËö
¥¢¥Ö¥¹¥È¥é¥¯¥Èºòº£, µï̲¤ê±¿Å¾¤¬¸¶°ø¤È¤Ê¤ë»àË´¸òÄÌ»ö¸Î¤¬Á꼡¤¤¤ÇÌäÂê¤È¤Ê¤Ã¤Æ¤¤¤ë. ¤³¤Î¸½¾õ¤ÎËɻߺö¤È¤·¤Æ, ±¿Å¾Ãæ¤Î³ÐÀÃÅÙ¤ò¸þ¾å¤µ¤»¤ë¤¿¤á¤Ë¹á¤ê¡¦²»³Ú¡¦¿¶Æ°¤Ê¤É¤Î¥Õ¥£¡¼¥É¥Ð¥Ã¥¯¸¡Æ¤¤µ¤ì¤Æ¤¤¤ë¤¬, ¸ú²Ì¤Ï½½Ê¬¤È¤Ï¸À¤¤Æñ¤¤. ¤½¤³¤Ç, Ëܸ¦µæ¤Ç¤Ï, ³ÐÀÃÅÙ¤ò¸þ¾å¤¹¤ë¤¿¤á¤Î¿·¤¿¤Ê»É·ã¤È¤·¤Æ, ÈéÉæ¾å¤Î¶á˵¤Ë²¹¡¦Îä»É·ã¤òƱ»þ¤ËÄ󼨤·¤¿ºÝ¤ËÀ¸¤¸¤ë²¹ÅÙºø³Ð¸½¾Ý¡Ö¥µ¡¼¥Þ¥ë¥°¥ê¥ëºø³Ð¡Ê°Ê²¼TGI¡Ë¡×¤ËÃíÌܤ·¤¿. TGIÄ󼨤ò¹Ô¤¦¾®·¿¥Ç¥Ð¥¤¥¹¤ò³«È¯¤·, TGIȯÀ¸Í×·ï¤Î¸¡¾Ú¤ò¹Ô¤Ã¤¿·ë²Ì, ȯÀ¸Í×·ï¤òÌÀ³Î¤Ë¤·¤¿. º£¸å¤ÏTGI¤ò¥Õ¥£¡¼¥É¥Ð¥Ã¥¯¤È¤·¤¿³ÆÀºÅÙ¸þ¾å¤Î¸ú²Ì̵ͭ¤ò¸¡¾Ú¤·, TGI¤ÎÍ­¸úÀ­¤ò³Î¤«¤á¤Æ¤¤¤¯.

7C-3 (»þ´Ö: 9:10 - 9:30)
Âê̾Optimization Method of Thermal Comfort and Energy Saving Based on Individual Sensation Estimation
Ãø¼ÔTakuya Aoki, *Kizito Nkurikiyeyezu, Anna Yokokubo, Guillaume Lopez (Aoyama Gakuin University)
¥Ú¡¼¥¸pp. 1419 - 1422
¥­¡¼¥ï¡¼¥É²¹Îä²÷Ŭ´¶, ¶õÄ´, ¸ÄÊÌÎäÃÈ˼, ¶¨Ä´À©¸æ
¥¢¥Ö¥¹¥È¥é¥¯¥ÈIn office-occupied spaces, the ratio of energy consumption by air-conditioning and lighting that maintains the environment comfort accounts for about 70%. On the other hand, many people claim being dissatisfied with the temperature of the air conditioning. Therefore, there is concern about the work efficiency reduction caused by current air-conditioning control. In this research, we propose an automatic control system that both improves the energy saving and the thermal comfort of all indoor users by quantifying individual differences in thermal comfort from biological information, base on which optimal settings of both air-conditioning system and wearable system that can directly heat and cool individuals. Simulation results in various environments demonstrated the efficacy of the proposed system for both energy saving and comfort maximization.

7C-4 (»þ´Ö: 9:30 - 9:50)
Âê̾»ëÀþµ°ÀפηÁ¾õ¤ÈÉÁ²èÆÃħ¤òÍѤ¤¤¿¸Ä¿Íǧ¾Ú¼êË¡¤Î¸¡Æ¤
Ãø¼Ô*Æ£ËÜ ¹ª³¤ (¸øΩ¤Ï¤³¤À¤Æ̤ÍèÂç³ØÂç³Ø±¡ ¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ²Ê), ÇòÀÐ ÍÛ (¸øΩ¤Ï¤³¤À¤Æ̤ÍèÂç³Ø ¥·¥¹¥Æ¥à¾ðÊó²Ê³ØÉô)
¥Ú¡¼¥¸pp. 1423 - 1432
¥­¡¼¥ï¡¼¥É¸Ä¿Íǧ¾Ú, »ëÀþµ°À×, 2Í×ÁÇǧ¾Ú, ¥Ñ¥¹¥ï¡¼¥Éǧ¾Ú, ¥Ð¥¤¥ª¥á¥È¥ê¥¯¥¹Ç§¾Ú
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7C-5 (»þ´Ö: 9:50 - 10:10)
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Ãø¼Ô*ÃæÈ­ ¤«¤±¤ë (¸øΩ¤Ï¤³¤À¤Æ̤ÍèÂç³ØÂç³Ø±¡ ¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ²Ê), Ãæ¼ ²Åδ, °ð¼ ¹À (¸øΩ¤Ï¤³¤À¤Æ̤ÍèÂç³Ø ¥·¥¹¥Æ¥à¾ðÊó²Ê³ØÉô)
¥Ú¡¼¥¸pp. 1433 - 1440
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¥»¥Ã¥·¥ç¥ó 7D  ¸òÄÌή¡¦¿Íή
Æü»þ: 2019ǯ7·î5Æü(¶â) 8:30 - 10:10
Éô²°: ²ÖÉñ¡¦¸Þ¤Î²Ö
ºÂĹ: ÆÁ±Ê ͺ°ì (¶âÂô¹©¶ÈÂç³Ø)

¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
7D-1 (»þ´Ö: 8:30 - 8:50)
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Ãø¼Ô*Æü±º ͦµ®, »³ËÜ Âç²ð, ¹â¶¶ ľµ× (̾¸Å²°¹©¶ÈÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1441 - 1449
¥­¡¼¥ï¡¼¥É·Ðϩõº÷, ÃÏ¿Þ, Æ»¤Ê¤ê, ¥Ç¡¼¥¿¥Ù¡¼¥¹, ¥¹¥È¥í¡¼¥¯
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7D-2 (»þ´Ö: 8:50 - 9:10)
Âê̾¥Ç¥Þ¥ó¥É±þÅú·¿³°½Ð»Ù±ç¥µ¡¼¥Ó¥¹¤Ë¤ª¤±¤ë¹âÎð¼Ô¸þ¤±Á÷·ÞÍ×µá¼ý½¸¥·¥¹¥Æ¥à¤Î¹½ÃÛ
Ãø¼Ô*º´Ìî ͧºÈ, ¿ûÅÄ Í£¿Î (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø), ¿åËÜ °°ÍÎ (ÂçºåÂç³Ø), ¿Ûˬ Çîɧ (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø/Íý²½³Ø¸¦µæ½ê), °ÂËÜ ·Ä°ì (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø)
¥Ú¡¼¥¸pp. 1450 - 1456
¥­¡¼¥ï¡¼¥ÉÃÏ°è½õ¤±¹ç¤¤·¿°ÜÆ°¥µ¡¼¥Ó¥¹, ¹âÎð¼Ô»Ù±ç, ¸ø¶¦¸òÄÌÍøÍѺ¤ÆñÃÏ°è, LPWA, Í×µáÁ÷¿®¥Ç¥Ð¥¤¥¹
¥¢¥Ö¥¹¥È¥é¥¯¥È¶áǯ¡¤¹âÎ𲽤ä²áÁ²½¤Ë¤è¤ê¹âÎð¼Ô¤Î°ÜÆ°¼êÃʤ¬ÉÔ­¤·¤Æ¤ª¤ê¡¤°ÜÆ°¼êÃʤγÎÊݤΤ¿¤á¤Ë¡¤ ¥Ü¥é¥ó¥Æ¥£¥¢Í¢Á÷¤ä¥Ç¥Þ¥ó¥É¥Ð¥¹¤Ê¤É¥Ç¥Þ¥ó¥É±þÅú·¿¸òÄ̤ˤè¤ë°ÜÆ°»Ù±ç¤Ë´üÂÔ¤¬¹â¤Þ¤Ã¤Æ¤¤¤ë¡¥ ¥Ç¥Þ¥ó¥É±þÅú·¿¸òÄ̤Ǥϡ¤Á÷·ÞÍ×µá¤òÅÅÏä䥢¥×¥ê¥±¡¼¥·¥ç¥ó¤ò²ð¤·¤Æ¼õ¤±¼è¤ë¤¬¡¤ ÅÅÏäǤÎʹ¤­¼è¤ê¤Ë¤ÏÁ÷·Þ´ÉÍý¤ËÉéô¤¬Â礭¤¯¡¤¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤Ç¤Ï¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤ò½êÍ­¤·¤Æ¤¤¤Ê¤¤¡¤ ¤¢¤ë¤¤¤Ï¡¤Áàºî¤ËÉÔ´·¤ì¤Ê¹âÎð¼Ô¤Ë¤È¤Ã¤ÆÍøÍѤ¬Æñ¤·¤¤¤È¤¤¤¦ÌäÂ꤬¤¢¤ë¡¥ ¤½¤³¤Ç¡¤ËܹƤǤϡ¤¥Ç¥Þ¥ó¥É±þÅú·¿¤Î¥Ü¥é¥ó¥Æ¥£¥¢Í¢Á÷¤òÂоݤˡ¤ ¹âÎð¼Ô¤«¤éÍưפËÁ÷·ÞÍ×µá¤ò¼ý½¸¤·¡¤Á÷·Þ´ÉÍý¼Ô¤Ë²Ä»ë²½¤Ç¤­¤ë¹âÎð¼Ô¸þ¤±Á÷·ÞÍ×µá¼ý½¸¥·¥¹¥Æ¥à¤òÄó°Æ¤¹¤ë¡¥ Äó°Æ¥·¥¹¥Æ¥à¤Ç¤Ï¡¤¹âÎð¼Ô¸þ¤±¤Ë¿·¤¿¤Ë³«È¯¤·¤¿Í×µáÁ÷¿®¥Ç¥Ð¥¤¥¹¤ò¹âÎð¼ÔÂð¤ËÀßÃÖ¤·¡¤ LPWA¤Ë¤è¤ëÄÌ¿®¤ò²ð¤·¤ÆÃÏ°è¤ÎÁ÷·ÞÍ×µá¤ò¼ý½¸¡¤ÃÏ°è¤Î¥Ü¥é¥ó¥Æ¥£¥¢Í¢Á÷¤ò´ÉÍý¤¹¤ë¥¹¥¿¥Ã¥Õ¤Ë²Ä»ë²½¤ò¹Ô¤¦¡¥ ¥·¥¹¥Æ¥à¤Î¼Â±¿ÍѤòÁÛÄꤷ¡¤³«È¯¤·¤¿Í×µáÁ÷¿®¥Ç¥Ð¥¤¥¹¤ÎUIɾ²Á¤ÈLPWA ¤Ë¤è¤ëÄÌ¿®¼Â¸³¤òÆàÎɸ©¼¯¥ÎÂæÃ϶è¤Ë¤ª¤¤¤Æ¼Â»Ü¤·¤¿¡¥ ¹âÎð¼Ô¤ËÍ×µáÁ÷¿®¥Ç¥Ð¥¤¥¹¤òÁàºî¤·¤Æ¤â¤é¤Ã¤¿·ë²Ì¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Ë¤è¤ëÆþÎÏ¥¤¥ó¥¿¡¼¥Õ¥§¡¼¥¹¤ÈÈæ³Ó¤·¤Æ¡¤ ¹âÎð¼Ô¤Ë¤È¤Ã¤ÆÁàºîÀ­¤¬Í¥¤ì¤Æ¤¤¤ë¤³¤È¤¬Ê¬¤«¤Ã¤¿¡¥ ¤Þ¤¿¡¤¼Â±¿ÍѤò¹Íθ¤·¤Æ¡¤LPWA¤ÎÄÌ¿®²ÄǽÈϰϤòÄ´ºº¤·¤¿·ë²Ì¡¤ ½»Â𳹤伫Á³Êª¤Î±Æ¶Á¤Ë¤è¤êŵ÷Î¥ÄÌ¿®¤¬²Äǽ¤ÊLPWA¤òÍѤ¤¤Æ¤âÃ϶èÁ´°è¤ò¥«¥Ð¡¼¤Ç¤­¤Ê¤¤¤È¤¤¤¦²ÝÂ꤬ÌÀ¤é¤«¤Ë¤Ê¤Ã¤¿¡¥

7D-3 (»þ´Ö: 9:10 - 9:30)
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Ãø¼Ô*ËÌÌî ͤ, Þɸ¶ ¾´µ¬ ((³ô)ÆüΩÀ½ºî½ê)
¥Ú¡¼¥¸pp. 1457 - 1462
¥­¡¼¥ï¡¼¥ÉÆ°Àþ¥Ç¡¼¥¿, µ¡³£³Ø½¬, OD¥Í¥Ã¥È¥ï¡¼¥¯, µ÷Î¥ÆÃħÎÌ, ¥·¥ß¥å¥ì¡¼¥·¥ç¥ó
¥¢¥Ö¥¹¥È¥é¥¯¥È¸ø¶¦»ÜÀߤ侦¶È»ÜÀß¡¤¹©¾ì¡¦ÁҸˤˤª¤±¤ë¡¤¿Í¤äʪ¤ÎÆ°¤­¤Ë´Ø¤¹¤ë¥Ç¡¼¥¿(Æ°Àþ¥Ç¡¼¥¿) ¤ÎʬÀÏ¡¦Íø³èÍѤ¬¶áǯÃíÌܤµ¤ì¤Æ¤¤¤ë¡¥Ëܸ¦µæ¤Ç¤Ï¡¤¾åµ­¤Î¤è¤¦¤Ê»ÜÀߤα¿ÍѸúΨ²½¤Î¤¿¤á¤Î»Üºö¸¡Æ¤¤Ë¤ª¤¤¤Æ¡¤»Üºö¤Î»öÁ°É¾²Á¤ò¼Â¸½¤¹¤ë¤¿¤á¤Ë¡¤Æ°Àþ¥Ç¡¼¥¿¤ò³èÍѤ·¤¿µ¡³£³Ø½¬¤Ë¤â¤È¤Å¤¯¿Íή¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¼êË¡¤òÄó°Æ¤¹¤ë¡¥Æ°Àþ¥Ç¡¼¥¿¤ò¿Í¤ÎΩ¤Á´ó¤ê¾ì½ê¤´¤È¤Ëʬ³ä¤·¤¿¸å¡¤¿Í¡¤ÊÉ¡¤Î©¤Á´ó¤ê¾ì½ê¤Ë´Ø¤¹¤ëÁêÂÐŪ¤Êµ÷Î¥ÆÃħÎ̤òÆþÎÏ¡¤¼¡¥¹¥Æ¥Ã¥×¤Î®ÅÙ¤ò½ÐÎϤȤ¹¤ëͽ¬¥â¥Ç¥ë¤ò¸ûÇÛ¥Ö¡¼¥¹¥Æ¥£¥ó¥°²óµ¢Ìڤˤâ¤È¤Å¤­À¸À®¤·¡¤¤³¤Îͽ¬¥â¥Ç¥ë¤ËÍѤ¤¤¿¿Íή¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¼Â¸³¤ò¹Ô¤Ã¤¿¤È¤³¤í¡¤Ë¿¶õ¹Á¥Á¥§¥Ã¥¯¥¤¥ó¥í¥Ó¡¼¤Ë¤ª¤¤¤Æ·×¬¥Ç¡¼¥¿¤È¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¥Ç¡¼¥¿¤Î¿ÍÌ©ÅÙÃͤ˴ؤ·¤ÆÁê´Ø·¸¿ô¤¬0.929 ¤È¤Ê¤ë¤³¤È¤ò³Îǧ¤·¤¿¡¥

7D-4 (»þ´Ö: 9:30 - 9:50)
Âê̾ŴƻÀ©¸æ¥·¥¹¥Æ¥à¤ËÆò½¤·¤¿Î¥»¶À©¸æ´ï¹çÀ®¤Ë¤ª¤±¤ë¾õÂֺ︺¥â¥Ç¥ê¥ó¥°¼êË¡
Ãø¼Ô*·¬Ì¾ ¸­¸ã, Å¢ ¸²»Ö (Áá°ðÅÄÂç³Ø), ȾÅÄ Î´¿®, Ìø°æ Ë¡µ®, À¾ÌÌ ÆصÁ (»°É©½Å¹©¶È), ¿¼ß· Îɾ´, ËÜ°ÌÅÄ ¿¿°ì (Áá°ðÅÄÂç³Ø)
¥Ú¡¼¥¸pp. 1463 - 1464
¥­¡¼¥ï¡¼¥ÉITS, Å´Æ»¥·¥¹¥Æ¥à, Discrete Event System, Controller Synthesis, ¾õÂÖÇúȯ
¥¢¥Ö¥¹¥È¥é¥¯¥ÈÅ´Æ»¥·¥¹¥Æ¥à¤Ë¤ª¤¤¤Æ¡¤Ê£»¨¤ÊÏ©Àþ¤ÇÀ©¸æÍ×µá¤òËþ¤¿¤¹À©¸æ¥í¥¸¥Ã¥¯¤Î¿Í¼ê¤Ç¤Î¹½ÃۤˤÏËÄÂç¤Ê»þ´Ö¤¬É¬ÍפȤʤ롥¿Í¼ê¤Ë¤è¤ë¹½ÃÛ¤ÎÉéô·Ú¸º¤Î¤¿¤á¤Ë¡¤À©¸æ¥í¥¸¥Ã¥¯¤Î¼«Æ°¹çÀ®¼êË¡¤Ç¤¢¤ëÎ¥»¶À©¸æ´ï¹çÀ®µ»½Ñ¤ÎŬÍѤ¬»î¤ß¤Ï¤¸¤á¤é¤ì¤Æ¤¤¤ë¡¥¤·¤«¤·¡¤Î¥»¶À©¸æ´ï¹çÀ®¤Ç¤Ï¡¤³°Éô´Ä¶­¤ÎÍ×ÁÇ¿ô¤ËÂФ·¤Æ»Ø¿ô´Ø¿ôŪ¤Ë´Ä¶­¥â¥Ç¥ë¤Î¾õÂÖ¿ô¤¬ÁýÂ礷¡¤¤½¤ì¤Ëȼ¤¤·×»»»þ´Ö¤â»Ø¿ô´Ø¿ôŪ¤ËÁýÂ礹¤ë¡¥¤½¤Î¤¿¤á¡¤Å´Æ»¥·¥¹¥Æ¥à¤Ë¤ª¤¤¤Æ¼ÂÍÑŪ¤Ê»þ´ÖÆâ¤ËÆ°ºî»ÅÍͤòÀ¸À®¤¹¤ë¤³¤È¤¬¤Ç¤­¤Ê¤¤¡¥¤½¤³¤Ç¡¤Ëܸ¦µæ¤Ç¤Ï¤³¤ÎÌäÂê¤ò²ò·è¤¹¤ë¤¿¤á¤Ë¡¤½¾Íè¤ÎÎ¥»¶À©¸æ´ï¹çÀ®¤è¤ê100Çܰʾå¹â®¤ÊDirected Controller Synthesis(DCS)¥¢¥ë¥´¥ê¥º¥à¤òÅ´Æ»¥·¥¹¥Æ¥à¤ËŬÍѤ·¤¿¡¥¤·¤«¤·¡¤DCS¥¢¥ë¥´¥ê¥º¥à¤ÎŬÍѤˤè¤Ã¤Æ·×»»»þ´Ö¤Îû½Ì¤¬³Îǧ¤Ç¤­¤¿¤â¤Î¤Î¡¤¼ÂÍÑŪ¤Ê»þ´ÖÆâ¤Ë¤Ï¼ý¤Þ¤Ã¤Æ¤ª¤é¤º¡¤¤µ¤é¤Ê¤ë¹â®²½¼êË¡¤Î³«È¯¤¬É¬ÍפǤ¢¤ë¤³¤È¤¬¤ï¤«¤Ã¤¿¡¥¤½¤³¤Ç¡¤Ëܸ¦µæ¤Ç¤Ï´Ä¶­¥â¥Ç¥ëÃæ¤Ë´Þ¤Þ¤ì¤ë̵Â̤ÊÀ©¸æ¤Ë´Ø¤¹¤ë¾õÂÖ¤ò¾Ê¤¯À©Ìó¤ò²Ý¤¹¥É¥á¥¤¥ó¸ÇÍ­¤Ê¾õÂֺ︺¥â¥Ç¥ê¥ó¥°¼êË¡¤òÄó°Æ¤¹¤ë¡¥´Ä¶­¥â¥Ç¥ëÃæ¤Î¾õÂÖ¤òºï¸º¤¹¤ë¤³¤È¤Ç¡¤Î¥»¶À©¸æ´ï¹çÀ®»þ´Ö¤òºÇÂç1/10000ÄøÅ٤ޤǤÎû½Ì¤ò³Îǧ¤·¤¿¡¥

Í¥½¨ÏÀʸ¾Þ / Paper Awards
7D-5 (»þ´Ö: 9:50 - 10:10)
Âê̾IoT¥Ð¥¹¥í¥±¡¼¥·¥ç¥ó¥·¥¹¥Æ¥à¤Ë¤ª¤±¤ëÅŻҥڡ¼¥Ñ¡¼·¿¥¹¥Þ¡¼¥È¥Ð¥¹Ää¤Î»îºî
Ãø¼Ô*ÎëÌÚ ½¨ÏÂ, Êݲ¼ ÂóÌé, ¾¾ËÜ ¹¬Àµ (̾¾ëÂç³ØÂç³Ø±¡Íý¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1465 - 1471
¥­¡¼¥ï¡¼¥É¥Ð¥¹¥í¥±¡¼¥·¥ç¥ó¥·¥¹¥Æ¥à, ¥¹¥Þ¡¼¥È¥Ð¥¹Ää, ÅŻҥڡ¼¥Ñ¡¼, LPWA
¥¢¥Ö¥¹¥È¥é¥¯¥È¥Ð¥¹Ää¤Ë¤ª¤¤¤ÆưŪ¤Ë¾ðÊó¤òɽ¼¨¤ª¤è¤ÓÄ󶡤¹¤ë¤¿¤á¤Ë¤Ï¡¤ÄÌ¿®¥â¥¸¥å¡¼¥ë¤Èɽ¼¨¥Ç¥Ð¥¤¥¹¤¬É¬ÍפȤʤ롥½¾Íè¤Î¥Ð¥¹Ää¤ÏÅŸ÷·Ç¼¨ÈĤä±Õ¾½¥Ñ¥Í¥ë¡¤ÅŻҥڡ¼¥Ñ¡¼¤Ê¤É¤È·ÈÂÓÅÅÏÃÌÖ¤òÁȤ߹ç¤ï¤»¤ë¤³¤È¤Ë¤è¤ê¡¤¥Ð¥¹¤ÎÃÙ±ä¾ðÊó¤ä´Ñ¸÷¾ðÊó¤Ê¤É¤òÍøÍѼԤËÄ󶡤·¤Æ¤¤¤¿¡¥¤·¤«¤·¡¤¥Ð¥¹Ää¤Ëɽ¼¨¤¹¤ë¥³¥ó¥Æ¥ó¥Ä¤Î¾ðÊóÎ̤äºÎÍѤ¹¤ëɽ¼¨¥Ç¥Ð¥¤¥¹¤Î»ÅÍͤˤè¤ê¡¤¾ðÊó¤Î»ëǧÀ­¤¬ÂçÉý¤ËÄã²¼¤·¤Æ¤¤¤ë»öÎ㤬¾¯¤Ê¤¯¤Ê¤¤¡¥É®¼Ô¤é¤Ï¥ì¥¹¥Ý¥ó¥·¥Ö¥¦¥§¥Ö¥Ç¥¶¥¤¥ó¤Î¹Í¤¨Êý¤òºÎÍѤ·¡¤¥ï¥ó¥½¡¼¥¹¤Ç»ÅÍͤΰۤʤëÅŻҥڡ¼¥Ñ¡¼¤ËºÇŬ¤Ë¥³¥ó¥Æ¥ó¥Ä¤¬É½¼¨¤Ç¤­¤ë¥¹¥Þ¡¼¥È¥Ð¥¹Ää¤ò»îºî¤·¤¿¡¥ËܹƤǤϥ¹¥Þ¡¼¥È¥Ð¥¹Ä䤪¤è¤Óɽ¼¨¥³¥ó¥Æ¥ó¥Ä¤ÎÀ߷פˤĤ¤¤Æ½Ò¤Ù¡¤¥×¥í¥È¥¿¥¤¥×¼ÂÁõ¤·¤¿¥¹¥Þ¡¼¥È¥Ð¥¹Ää¤Îɾ²Á·ë²Ì¤Ë¤Ä¤¤¤Æ¼¨¤¹¡¥


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¥»¥Ã¥·¥ç¥ó 7E  Æ°²èÁü¿®¹æ½èÍý
Æü»þ: 2019ǯ7·î5Æü(¶â) 8:30 - 10:10
Éô²°: Í·Éñ¡¦¸Þ¤ÎÍ·
ºÂĹ: °æ¾å ÁϤ (¶å½£¹©¶ÈÂç³Ø)

Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
Í¥½¨ÏÀʸ¾Þ / Paper Awards
7E-1 (»þ´Ö: 8:30 - 8:50)
Âê̾ʪÂÎÆÃħÎ̤˴ð¤Å¤¯´í¸±±¿Å¾¾õ¶·¤Î¿äÄê
Ãø¼Ô*»³ËÜ ½¤Ê¿, ÁÒÅç ·ò, ¾¾ÎÓ Ã£»Ë, ¸ÍÅÄ ¹ÀÇ· (ÆüËÜÅÅ¿®ÅÅÏóô¼°²ñ¼Ò NTT¥µ¡¼¥Ó¥¹¥¨¥Ü¥ê¥å¡¼¥·¥ç¥ó¸¦µæ½ê)
¥Ú¡¼¥¸pp. 1472 - 1479
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7E-2 (»þ´Ö: 8:50 - 9:10)
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¥Ú¡¼¥¸pp. 1480 - 1485
¥­¡¼¥ï¡¼¥ÉObject Detection, 8K, TensorFlow
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7E-3 (»þ´Ö: 9:10 - 9:30)
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Ãø¼Ô*±ÊÅÄ ¾°»Ö (À¾ÆüËÜÅÅ¿®ÅÅÏóô¼°²ñ¼Ò)
¥Ú¡¼¥¸pp. 1486 - 1491
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7E-4 (»þ´Ö: 9:30 - 9:50)
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Ãø¼ÔÅļ Þ«¼ù, *Àõ°æ ¹¨ÅÍ, À¾Èø ¿®É§ (Ω̿´ÛÂç³Ø¾ðÊóÍý¹©³ØÉô)
¥Ú¡¼¥¸pp. 1492 - 1497
¥­¡¼¥ï¡¼¥É¥Ò¥¢¥é¥Ö¥ë, ¹Ôưǧ¼±, PDR, ²°Æ⬰Ì, ¥¦¥§¥¢¥é¥Ö¥ë
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7E-5 (»þ´Ö: 9:50 - 10:10)
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Ãø¼Ô¶áÆ£ ¾¢³¤, *³÷ÃÏ ÍÚ, ²£·¦ °ÂÆà, ¥í¥Ú¥º ¥®¥è¡¼¥à (ÀÄ»³³Ø±¡Âç³Ø)
¥Ú¡¼¥¸pp. 1498 - 1504
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Æü»þ: 2019ǯ7·î5Æü(¶â) 8:30 - 10:10
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ºÂĹ: ÈîÅÄ °ìÀ¸ (ÉÙ»ÎÄ̸¦µæ½ê)

ºÇÍ¥½¨ÏÀʸ¾Þ / Best Paper Awards
7F-1 (»þ´Ö: 8:30 - 8:50)
Âê̾Improving Face Recognition for Identity Verification by Managing Facial Directions and Eye Contact of Event Attendees
Ãø¼Ô*Akitoshi Okumura (IPA Information-technology Promotion Agency, Japan), Susumu Handa, Takamichi Hoshino, Naoki Tokunaga, Masami Kanda (NEC Solution Innovators, Ltd.)
¥Ú¡¼¥¸pp. 1505 - 1514
¥­¡¼¥ï¡¼¥ÉFace Recognition, Identity Verification,, Illegal Ticket Resale Prevention

7F-2 (»þ´Ö: 8:50 - 9:10)
Âê̾¥¹¥Þ¡¼¥È¥¦¥©¥Ã¥Á¤È¥ï¥¤¥ä¥ì¥¹¥Ø¥Ã¥É¥Õ¥©¥ó¤òÍѤ¤¤¿¸Ä¿Í¸þ¤±¾ðÊóÇÛ¿®¥·¥¹¥Æ¥à
Ãø¼Ô*¾®Àî ÂóÌé (°¦É²Âç³ØÂç³Ø±¡Íý¹©³Ø¸¦µæ²Ê), Æ£¶¶ ÂîÌé (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), ±óÆ£ ·Ä°ì, ¾®ÎÓ ¿¿Ìé (°¦É²Âç³ØÂç³Ø±¡Íý¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1515 - 1522
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
7F-3 (»þ´Ö: 9:10 - 9:30)
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¥Ú¡¼¥¸pp. 1523 - 1527
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7F-4 (»þ´Ö: 9:30 - 9:50)
Âê̾¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤òÍѤ¤¤¿SQRC¥ê¡¼¥À¥·¥¹¥Æ¥à¤Î³«È¯¡§nearly invisible¤ÊSQRC¤Î¥»¥é¥ß¥Ã¥¯¥¹¤Ø¤Î¾Æ¤­ÉÕ¤±¤È¿¦Ì³¸¢¸Â¤Ë±þ¤¸¤¿ÈëÌ©¾ðÊó¤Îɽ¼¨
Ãø¼Ô*Æ£Àî ¿¿¼ù, ¾åÌî Í£ (¹©³Ø±¡Âç³Ø), Âçß· ÂçÆó (³ô¼°²ñ¼Ò¹âº¬¥·¥ë¥¯), À¾Â¼ ±Ñ¸à (¥µ¥¤¥¨¥ó¥¹¥Ñ¡¼¥¯³ô¼°²ñ¼Ò), ¸ÞÌ£ ¹¨ÂÀϺ, ´äùõ ½¨¼ù (³ô¼°²ñ¼Ò»³²Ã¾¦Å¹), ¸¶ÅÄ ÉÒÌÀ, °Âã ľ¸Ê (´ôÉ츩¥»¥é¥ß¥Ã¥¯¥¹¸¦µæ½ê)
¥Ú¡¼¥¸pp. 1528 - 1536
¥­¡¼¥ï¡¼¥ÉSQRC, ¥¹¥Þ¡¼¥È¥Õ¥©¥ó, ÈëÌ©¾ðÊó, ¸ø³«¾ðÊó
¥¢¥Ö¥¹¥È¥é¥¯¥ÈËÜÏÀʸ¤Ç¤Ï¡¤¥»¥é¥ß¥Ã¥¯¥¹À½ÉʤÎɽÌ̤˷ÁÀ®¤¹¤ënearly invisible ¤Ê2 ¼¡¸µ¥³¡¼¥É¤Î·ÁÀ®ÊýË¡¤È¡¤Åö³º¥³¡¼¥É¤«¤éʸ»ú¾ðÊó¡Ê¸ø³«¾ðÊó¤È°Å¹æ²½¤µ¤ì¤¿ÈëÌ©¾ðÊó¡Ë¤òÃê½Ð¤¹¤ë¡¤¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤È»ç³°Àþ¸÷¸»¤òÍѤ¤¤¿2 ¼¡¸µ¥³¡¼¥É¥ê¡¼¥À¥·¥¹¥Æ¥à¤ò¾Ò²ð¤¹¤ë¡¥Nearly invisible ¤Ê2 ¼¡¸µ¥³¡¼¥É¤Ï¡¤¥»¥é¥ß¥Ã¥¯¥¹À½Éʤΰվ¢¤ò²Äǽ¤Ê¸Â¤ê»¤Ê¤ï¤º¤Ëʸ»ú ¾ðÊó¤òÀ½Éʤ˻ý¤¿¤»¤ë¤¿¤á¤ËÃø¼Ô¤é¤¬³«È¯¤·¤¿¤â¤Î¤Ç¤¢¤ê¡¤Åö³º¥³¡¼¥É¤Ï»ç³°Àþ¤¬¾È¼Í¤µ¤ì¤Æ¤¤¤ë´Ö¡¤ÀÄÇò¤¤¸÷¤òȯ¸÷¤¹¤ë¤¿¤áÆù´ã¤Ç¤Î»ëǧ¤¬ÍưפȤʤ롥¥ê¡¼¥À¥·¥¹¥Æ¥à¤Ï¡¤¥«¥á¥éµ¡Ç½¤È2 ¼¡¸µ¥³¡¼¥Éǧ¼±¥¢¥ë¥´¥ê¥º¥à¤òÍѤ¤¤Æʸ»ú¾ðÊó¤òÃê½Ð¤¹¤ë¤¬¡¤¥Ç¥¸¥¿¥ë¸°¤Ë¥¢¥¯¥»¥¹¤Ç¤­¤ë¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Î¤ß¤¬°Å¹æ²½¤µ¤ì¤¿ÈëÌ©¾ðÊó¤òÉü¹æ¤Ç¤­¤ë¡¥¼Â¸³¤Î·ë²Ì¡¤nearly invisible ¤Ê2 ¼¡¸µ¥³¡¼¥É¤¬·ÁÀ®¤Ç¤­¤ë¤³¤È¡¤¤ª¤è¤Ó¥ê¡¼¥À¥·¥¹¥Æ¥à¤¬Ê¸»ú¾ðÊó¤òºÆ¸½À­¤ò¤â¤Ã¤ÆÃê½Ð¤Ç¤­¤ë¤³¤È¤¬¤ï¤«¤Ã¤¿¡¥


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¥»¥Ã¥·¥ç¥ó 7G  ³Ø½¬»Ù±ç (2)
Æü»þ: 2019ǯ7·î5Æü(¶â) 8:30 - 10:10
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ºÂĹ: »Ô¼ ů (ÂçºÊ½÷»ÒÂç³Ø)

¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
7G-1 (»þ´Ö: 8:30 - 8:50)
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Ãø¼Ô*ÁêÀî Âç¸ã, Àõ°æ ¹¯µ®, ¹¾ÌÚ ·¼·± (Åŵ¤ÄÌ¿®Âç³ØÂç³Ø±¡¾ðÊóÍý¹©³Ø¸¦µæ²Ê¾ðÊó³ØÀ칶)
¥Ú¡¼¥¸pp. 1537 - 1542
¥­¡¼¥ï¡¼¥É³Ø½¬¼Ô¤ÎÈèÏ«, µÓÉôÆ°ºî, ¼ø¶ÈÃæ¤ÎµÙ·Æ
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7G-2 (»þ´Ö: 8:50 - 9:10)
Âê̾TA»Ù±ç¥·¥¹¥Æ¥à¤ÎƳÆþ¤Ë¤è¤ë³ØÀ¸¤Ø¤ÎÂбþ»þ´Öʬ»¶²½¤Î±Æ¶Á
Ãø¼Ô*º£Â¼ ÎÜ°ìϺ, ²£»³ ͵µª, ¹¾ÌÚ ·¼·± (Åŵ¤ÄÌ¿®Âç³ØÂç³Ø±¡¾ðÊóÍý¹©³Ø¸¦µæ²Ê¾ðÊó³ØÀ칶)
¥Ú¡¼¥¸pp. 1543 - 1548
¥­¡¼¥ï¡¼¥ÉTA, ¥×¥í¥°¥é¥ß¥ó¥°¶µ°é, ¹Ôưǧ¼±
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7G-3 (»þ´Ö: 9:10 - 9:30)
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Ãø¼Ô*»³ËÜ Èþ¹¬, Ê¡²¬ ¹¨°ì (ÁϲÁÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), À¶¸¶ ÎÉ»° (¿ÀÆàÀ²ÊÂç³Ø¾ðÊó³ØÉô¾ðÊ󹩳زÊ), »ûÅç Èþ¾¼ (ÁϲÁÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1549 - 1554
¥­¡¼¥ï¡¼¥ÉProject-based Learning, Teaching Assistant, ʬ»¶³«È¯, ¿ÊĽ´ÉÍý
¥¢¥Ö¥¹¥È¥é¥¯¥È¶áǯ¡¤Â絬ÌÏ¥½¥Õ¥È¥¦¥§¥¢³«È¯¤Îʬ»¶³«È¯¤ò³Ø¤Ö¡¢PBL¼ø¶È¤¬½ÅÍ׻뤵¤ì¤Æ¤¤¤ë¡¥¤½¤³¤Ç¡¤Ëܸ¦µæ¤Ïʬ»¶³«È¯¤òÁÛÄꤷ¤¿Project-based Learning(PBL)·¿¤Î¼ø¶È¤òÂоݤȤ·¡¤Ê¬»¶³«È¯¤ÎÆÈΩÀ­¤ò˸¤²¤Ê¤¤ÈóƱ´ü·¿¤Î¾ðÊó¶¦Í­¤òÍѤ¤¤Æ¡¤³«È¯¤ÎÃÙ±ä¤ò²ò·è¤¹¤ë¤¿¤á¤Î¿ÊĽ´ÉÍý¼êË¡¤òÄó°Æ¤¹¤ë¡¥PBL·¿¤Î¼ø¶È¤Ç¤Ï¡¤Teaching Assistant(TA)¤¬³ØÀ¸¤Î¥µ¥Ý¡¼¥È¤ò¹Ô¤¦¤¬¡¤Ê¬»¶³«È¯¤òÁÛÄꤹ¤ë¾ì¹ç¡¤TA¤È³ØÀ¸¤¬ÃÏÍýŪ¤ËÎ¥¤ì¤¿¾õ¶·¤Ë¤Ê¤ë¡¥¤½¤Î¤¿¤á¡¤Ê£¿ô¤Î¥×¥í¥¸¥§¥¯¥È¤ò´Æ»ë¤¹¤ë¤³¤È¤Ë»þ´Ö¤¬¤«¤«¤ê¡¤³ØÀ¸¤Ø¤ÎÂбþ¤¬ÃÙ¤ì¤ë²ÄǽÀ­¤¬¤¢¤ë¡¥Äó°Æ¼êË¡¤Ç¤ÏÈóƱ´ü·¿¤Î¾ðÊó¶¦Í­¤ò³«È¯¤Ë¼è¤êÆþ¤ì¡¤TA¤Î³«È¯¿ÊĽ´Æ»ë¤ÈʬÀÏ¡¤½õ¸À¤ÎÌò³ä¤ò¼«Æ°²½¤¹¤ë¤³¤È¤Ç³ØÀ¸¤ÎÃÙ±ä¤òÁá´ü¤Ë²ò·è¤¹¤ë¡¥TA¼«Æ°²½¤Î¤¿¤á¤Ë³«È¯¿ÊĽ¤ò¬¤ë»Øɸ¤È¤·¤Æ¡¤³ØÀ¸¤ÎÃٱ䤬¥×¥í¥¸¥§¥¯¥È¤ËÍ¿¤¨¤ë±Æ¶Á¤ò¿ôÃͲ½¤·¤¿¿¼¹ïÅÙ¤òÄêµÁ¤·¡¤¿¼¹ïÅÙ¤ËÂбþ¤·¤¿½õ¸ÀÆâÍƤòÄê¤á¤ë¡¥¼Â¸³¤Ç¤Ï¡¤¥×¥í¥¸¥§¥¯¥È¤Î³«È¯¿ÊĽ¤¬³ØÀ¸¤ÎǽÎϤäºî¶È¸úΨ¤Ëº¸±¦¤µ¤ì¤ë¤¿¤áºÆ¸½¤¹¤ë¤³¤È¤¬Æñ¤·¤¯¡¤¼Â¸³ÊýË¡¼«ÂΤò¹Íθ¤¹¤ëɬÍפ¬¤¢¤ë¤³¤È¤«¤é¡¤Äó°Æ¼êË¡¤Î¸ú²Ì¤ò³Îǧ¤¹¤ë¤³¤È¤Ë²Ã¤¨¡¤Í­¸úÀ­É¾²ÁÊýË¡¤Î¸¡Æ¤¤ò¹Ô¤Ã¤¿¡¥

7G-4 (»þ´Ö: 9:30 - 9:50)
Âê̾³Ø½¬¼Ô¤Îȯ¸Àµ¡²ñ¤ò¶ÑÅù¤Ë¤¹¤ëµÄÏÀ·±Îý¥·¥¹¥Æ¥à¤ÎÄó°Æ
Ãø¼Ô*¹¾ÌÚ ·¼·±, ²¬ß· Âç»Ö, ÀÐÀî À¿ÉË (Åŵ¤ÄÌ¿®Âç³ØÂç³Ø±¡¾ðÊóÍý¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1555 - 1560
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¥»¥Ã¥·¥ç¥ó 7H  ʬ»¶¥·¥¹¥Æ¥à
Æü»þ: 2019ǯ7·î5Æü(¶â) 8:30 - 10:10
Éô²°: ³ÚÉñ¡¦°ì¤Î³Ú
ºÂĹ: »ûÅÄ Ä¾Èþ (¾ðÊóÄÌ¿®¸¦µæµ¡¹½)

7H-1 (»þ´Ö: 8:30 - 8:50)
Âê̾Dynamic Updating Controller¼«Æ°À¸À®¤Î¤¿¤á¤Î´Ä¶­¥â¥Ç¥ë¹½Ãۤˤª¤±¤ë´Ø¿´»öʬΥ¼êË¡
Ãø¼Ô*»³Æâ Âó¿Í (Áá°ðÅÄÂç³Ø), Å¢ ¸²»Ö, ÏÉºê ¹°µ¹, ËÜ°ÌÅÄ ¿¿°ì (Áá°ðÅÄÂç³Ø/¹ñΩ¾ðÊó³Ø¸¦µæ½ê)
¥Ú¡¼¥¸pp. 1561 - 1562
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7H-2 (»þ´Ö: 8:50 - 9:10)
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Ãø¼Ô*Ê¿Ìî µ®µ¬, Áêß· ÏÂÌé (Áá°ðÅÄÂç³Ø), Å¢ ¸²»Ö (Áá°ðÅÄÂç³Ø/¹ñΩ¾ðÊó³Ø¸¦µæ½ê), ÏÉºê ¹°µ¹ (Áá°ðÅÄÂç³Ø), ËÜ°ÌÅÄ ¿¿°ì (Áá°ðÅÄÂç³Ø/¹ñΩ¾ðÊó³Ø¸¦µæ½ê)
¥Ú¡¼¥¸pp. 1563 - 1565
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7H-3 (»þ´Ö: 9:10 - 9:30)
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¥Ú¡¼¥¸pp. 1566 - 1570
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7H-4 (»þ´Ö: 9:30 - 9:50)
Âê̾ʬ»¶MQTT Broker¤ò³èÍѤ·¤¿Dataflow¥³¥ó¥Ý¡¼¥Í¥ó¥È´ÖÄÌ¿®¼êË¡¤ÎÄó°Æ
Ãø¼Ô*Àи¶ ¿¿ÂÀϺ, °ÂÅÄ ÏÂËá, ½©»³ Ë­Ï (µþÅÔ»º¶ÈÂç³Ø Àèü¾ðÊó³Ø¸¦µæ²Ê), °ÂÇÜ ¹­Â¿ (Âçºå»ÔΩÂç³ØÂç³Ø±¡ ¹©³Ø¸¦µæ²Ê), »ûÀ¾ ͵°ì (¾ðÊóÄÌ¿®¸¦µæµ¡¹½)
¥Ú¡¼¥¸pp. 1571 - 1580
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7H-5 (»þ´Ö: 9:50 - 10:10)
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¥Ú¡¼¥¸pp. 1581 - 1588
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Æü»þ: 2019ǯ7·î5Æü(¶â) 10:30 - 12:10
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8A-1 (»þ´Ö: 10:30 - 11:10)
Âê̾(¾·ÂÔ¹Ö±é) ºßÂð°åÎŤˤª¤±¤ëICT³èÍѤμè¤êÁȤ߾Ҳð
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¥Ú¡¼¥¸p. 1589
¥­¡¼¥ï¡¼¥ÉºßÂð°åÎÅ, ÅŻҥ«¥ë¥Æ, ¥»¥ó¥·¥ó¥°, CPS, ¥µ¡¼¥Ó¥¹À©¸æ
¥¢¥Ö¥¹¥È¥é¥¯¥È´µ¼Ô¤Î¥±¥¢¾ðÊó¤Î¼ý½¸¤äʬÀÏ¡¤ÊÝ´É¡¤¶¦Í­¤ò¼Â¸½¤¹¤ë¤¿¤á¤Ë¡¤ICT(Information and Cmmunication Technology)¤Î³èÍѤËÂФ¹¤ë´üÂԤϹ⤤¡¥ ËÜȯɽ¤Ç¤Ï¡¤ºßÂð°åÎŤθ½¾ì¤Ø¼ÂºÝ¤Ë ICT ¤òŬÍѤ·¤¿»ö Îã¤ò¾Ò²ð¤·¡¤¤½¤Î¥Ù¡¼¥¹¤È¤Ê¤ëµ»½Ñ¤Ë¤Ä¤¤¤ÆÀâÌÀ¤¹¤ë¤È¤È¤â¤Ë¡¤¥µ¡¼¥Ó¥¹¤ÎÄ󶡲ÁÃͤä²ÝÂê¤Ê¤É¤Ë¤Ä¤¤¤ÆµÄÏÀ¤¹¤ë¡¥°ì¤ÄÌܤλöÎã¤Ï¡¤ºßÂð°åÎŤΰåÎÅ´Ø·¸¼Ô¤¬´µ¼Ô¤Î¥±¥¢¾ðÊó¤Ø°ÂÁ´¤«¤Ä¸úΨŪ¤Ë¥¢¥¯¥»¥¹¡¦¶¦Í­¤¹¤ë¤³¤È¤ò²Äǽ¤È¤¹¤ë¼è¤êÁȤߤǤ¢¤ë¡¥¤³¤Î¼è¤êÁȤߤˤè¤ê¡¤¤³¤ì¤Þ¤Ç°Ê¾å¤Ë°åÎÅ´Ø·¸¼Ô´Ö¤ÇÉÑÈˤ˴µ¼Ô¤ÎºÇ¿·¤Î¥±¥¢¾ðÊó¤ò¶¦Í­¤¹¤ë µ¡²ñ¤¬¹â¤Þ¤ë¸ú²Ì¤ò³Îǧ¤·¤¿¡¥Æó¤ÄÌܤλöÎã¤Ï¡¤ºßÂð°åÎŤˤª¤±¤ë´µ¼Ô¤ÎÆü¾ïÀ¸³èÃæ¤Î¾õÂÖ¤òÍÍ¡¹¤Ê¥»¥ó¥µ¡¼¤Ç¥â¥Ë¥¿¥ê¥ó¥°¤·¤Æ¡¤É±¡¸¡ºº¤Ç¤Ï¸«¤Ä¤±Æñ¤¤Æü¾ïÀ¸³èÃæ¤Ë¸½¤ì¤ë¾É¾õ¤òª¤¨¤ë¼è¤êÁȤߤǤ¢¤ë¡¥¤³¤Î¼è¤êÁȤߤˤè¤ê¡¤¼«Âð¤ËÌá¤Ã¤¿´µ¼Ô¤¬°ÜÆ°¤Ë¶ìÏ«¤·¤Æ¤¤¤ëÍͻҤä°Û¾ïÊâ¹Ô¤Ê¤É¤òª¤¨¤é¤ì¡¤¤­¤áºÙ¤«¤Ê°åÎŤμ¸½¤ò»Ù±ç¤Ç¤­¤ë¸«¹þ¤ß¤òÆÀ¤¿¡¥ ¤³¤ì¤é¤Î¼è¤êÁȤߤòÄ̤·¤ÆÆÀ¤é¤ì¤¿¡¤ºßÂð°åÎŤǤΠICT³èÍѤβÄǽÀ­¤È¤È¤â¤Ë¡¢Ä¾Ì̤·¤¿Æñ¤·¤µ¤Ë¤Ä¤¤¤Æȯɽ¤·¡¢µÄÏÀ¤¹¤ë¡¥

8A-2 (»þ´Ö: 11:10 - 11:30)
Âê̾°åÎŵ¡´ïÁàºî¤Ë¤ª¤±¤ë½¬½ÏÅ٤ȱ¿Æ°¾ðÊó¤Î´ØÏ¢À­¤Ë´Ø¤¹¤ë¸¦µæ
Ãø¼Ô*¼¾å ÂóÌé (ÆüËÜÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), Àж¶ ͥʹ, ÉðÆ£ ¿­ÍÎ (ÆüËÜÂç³Ø¹©³ØÉô)
¥Ú¡¼¥¸pp. 1590 - 1593
¥­¡¼¥ï¡¼¥É±ó³Ö¶µ°é, °åÎŵ¡´ïÁàºî, ºî¶È½¬½ÏÅÙ, »ëÀþ¥»¥ó¥µ, ÎسÔÃê½Ð
¥¢¥Ö¥¹¥È¥é¥¯¥È¸½ºß¡¤Î×¾²¹©³Øµ»»Î¤Î¼ûÍפ¬Áý²Ã·¹¸þ¤Ë¤¢¤ê¤½¤Î°éÀ®¤Ë¤ª¤¤¤Æ¤Ï°åÎŵ¡´ï¤ÎÁàºîÊýË¡¤ò¸úΨŪ¤Ë½¬ÆÀ¤¹¤ë¤³¤È¤¬²ÝÂê¤Ç¤¢¤ê¡¤°åÎŵ¡´ïÁàºî¤Î½¬½ÏÅÙ¤òÄêÎÌŪ¤Ëɾ²Á¤¹¤ëɬÍפ¬¤¢¤ë¡¥¤·¤«¤·¸½ºß¤Ï½¬½ÏÅÙ¤òÁàºîÎò¤ä¶Ð³ǯ¿ô¤ÇȽÃǤ·¤Æ¤ª¤êÁàºî¤Î·×¬¤Ë¤è¤ëÄêÎÌŪ¤Ê»Øɸ¤Ï¤Ê¤¤¡¥¤½¤³¤ÇËܸ¦µæ¤Ç¤Ï°åÎŵ¡´ïÁàºî»þ¤Î±¿Æ°¾ðÊó¤ËÃåÌܤ·¤Æ½¬½ÏÅÙ¤ÎÄêÎÌɾ²Á»Øɸ¤ò¸¡Æ¤¤·¤¿¡¥¤½¤ÎÊýË¡¤È¤·¤Æ¡¤°åÎŵ¡´ïÁàºî¼Ô¤Îξ¼ê¼ó¤Ë9¼´¾ðÊ󥻥󥵡¤Æ¬Éô¤Ë»ëÀþ¥»¥ó¥µ¤òÁõÃ夷µ¡´ïÁàºî»þ¤Î²Ã®ÅÙ¡¤³Ñ®ÅÙ¤ä»ëÀþ°Üư®ÅÙ¡¤»ëÀþ°ÌÃ֥ǡ¼¥¿Åù¤ò¼èÆÀ¤·¡¤¤³¤ì¤é¤Î±¿Æ°¾ðÊó¤ÈÁàºî»þ´Ö¤È¤ÎÁê´Ø¤òƳ½Ð¤¹¤ë¡¥¤Þ¤¿¡¤ËÜÏÀʸ¤Ç¤Ï½¾Í踦µæ¤Ë¤Æ¼êºî¶È¤Ç¹Ô¤Ã¤Æ¤¤¤¿ºî¶ÈÂоݤòÃí»ë¤·¤¿»þ´Ö¤ÎÁàºî»þ´Ö¤Ë¤ª¤±¤ë³ä¹ç¤Î²òÀϤμ«Æ°²½¤Ë¤Ä¤¤¤Æ¸¡Æ¤¤·¤¿¡¥¶ñÂÎŪ¤Ë¤Ï»ëÀþ¥»¥ó¥µ¤Ç»£±Æ¤·¤¿±ÇÁü¤«¤éCannyË¡¤òÍѤ¤¤ÆÃí»ëÂоݤÎÎسԤò¸¡½Ð¤·¡¤ÌÌÀѤª¤è¤Ó·Á¾õ¤«¤éÃí»ëÂоݤòȽÄꤷ¤Æ¤½¤ÎÃæ¤ËÃí»ë°ÌÃÖ¤¬Æþ¤Ã¤Æ¤¤¤ë¤«¤ò²òÀϤ¹¤ë¡¥¼Â¸³¤Ïµ¡´ïÁàºî¤Î̤·Ð¸³¼Ô15¿Í¤òÂоݤ˼»ܤ·¤¿¡¥¤½¤Î·ë²Ì¡¤¼ê¼ó¤ª¤è¤ÓƬÉô¤Î±¿Æ°¾ðÊó¤Ë´Ø¤·¤Æ¤Ï¶¯¤¤Áê´Ø¤ÏÆÀ¤é¤ì¤Ê¤«¤Ã¤¿¡¥Ãí»ë°ÌÃ֤μ«Æ°¼èÆÀ¤Ë¤Ä¤¤¤Æ¡¤Ãí»ëÂоݤÎȽÄ꤬¤Ç¤­¤¿7¿Íʬ¤Î¥Ç¡¼¥¿¤Ë¤Ä¤¤¤Æ²òÀϤ·¤¿¤È¤³¤íÁàºî»þ´Ö¤ÈÃí»ë»þ´Ö³ä¹ç¤Ë¶¯¤¤Áê´Ø¤ò³Îǧ¤·¤¿¡¥

8A-3 (»þ´Ö: 11:30 - 11:50)
Âê̾¹âÎð¼Ô¸þ¤±³Ø½¬»Ù±ç¥·¥¹¥Æ¥à¤¿¤á¤ÎUI¥×¥í¥È¥¿¥¤¥×³«È¯¤È¼Â¸³
Ãø¼Ô*Φ ú¡, Åļ ¤«¤ª¤ê, ²¬ËÜ ¹ä (¶å½£Âç³Ø´ð´´¶µ°é±¡), Âç°æ µþ (¶å½£Âç³ØÉí°¿Þ½ñ´ÛÉÕÀ߶µºà³«È¯¥»¥ó¥¿¡¼), ÅçÅÄ ·É»Î (¶å½£Âç³ØÂç³Ø±¡¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ±¡), ȪǸ ¹¸Ê¿, »³ÅÄ À¯´², ÌÚÕé ¿·°ì (¶å½£Âç³Ø´ð´´¶µ°é±¡)
¥Ú¡¼¥¸pp. 1594 - 1598
¥­¡¼¥ï¡¼¥É³Ø½¬»Ù±ç¥·¥¹¥Æ¥à, ¹âÎð¼Ô, ¥æ¡¼¥¶¥¤¥ó¥¿¡¼¥Õ¥§¥¤¥¹, ¥æ¡¼¥¶¼Â¸³
¥¢¥Ö¥¹¥È¥é¥¯¥È¹âÎð¼Ô¸þ¤±³Ø½¬»Ù±ç¥·¥¹¥Æ¥à¤¿¤á¤ÎUI¤Ï¡¤ÍøÍѼԤÎÁàºîÉéô¤Î·Ú¸ºµÚ¤ÓÉ԰´¶¡¦Äñ¹³´¶¤Î²ò¾Ã¤ò¹Íθ¤·¤¿À߷פÎɬÍפ¬¤¢¤ë¡¥Ëܸ¦µæ¤Ï¥Ò¥¢¥ê¥ó¥°Ä´ºº¤Ç¤Î°Õ¸«Ä°¼è¤Ë´ð¤Å¤¤¤Æ¡¤¥¿¥Ö¥ì¥Ã¥È2Âæ¤ÎÍøÍѤˤè¤êµ¡Ç½¤òʬ»¶¤·¡¤¾ðÊóɽ¼¨¤Î³¬ÁØ¿ô¤ÈÁàºî¤ÎÊ£»¨ÅÙ¤òºï¸º¤·¤Æ¡¤¥¿¥Ã¥Á¥¹¥¯¥ê¡¼¥ó¤Çľ´¶ÅªÁàºî¤Ç¤­¤ë¤è¤¦¤ÊUI¤òÄó°Æ¤¹¤ë¡¥Äó°Æ¤·¤¿UI¤Î½éÊâŪ¼Â¸½¤È¸¡Æ¤¤Î¤¿¤á³«È¯¤µ¤ì¤¿¥×¥í¥È¥¿¥¤¥×¤Ï¡¤¥æ¡¼¥¶¼Â¸³¤Ç¹âÎð¼Ô¤Ë»îÍѤ·¤Æ¤â¤é¤¤¡¤·ÁÀ®ÅªÉ¾²ÁµÚ¤Ó²þÎɤ¿¤á¤Î°Õ¸«Ä°¼è¤ò¹Ô¤Ã¤¿¡¥¸å³¤Î²þÎɤȳ«È¯µÚ¤Óɾ²Á¼Â¸³¤Ë¤Ä¤¤¤Æ¹Í»¡¤ÈµÄÏÀ¤ò¹Ô¤Ã¤¿¡¥

8A-4 (»þ´Ö: 11:50 - 12:10)
Âê̾²ð¸îÆü»ï¼«Æ°À¸À®¤Î¤¿¤á¤Î²ð¸îʬÌ¥ó¥È¥í¥¸¡¼À¸À®µ»½Ñ¤Î¸¦µæ
Ãø¼Ô*ÌîËò Í¥ (Åŵ¤ÄÌ¿®Âç³ØÂç³Ø±¡¾ðÊóÍý¹©³Ø¸¦µæ²Ê¾ðÊ󡦥ͥåȥ¥¯¹©³ØÀ칶), ¾ÂÈø ²íÇ· (Åŵ¤ÄÌ¿®Âç³ØÂç³Ø±¡¾ðÊ󡦥ͥåȥ¥¯¹©³ØÀ칶)
¥Ú¡¼¥¸pp. 1599 - 1603
¥­¡¼¥ï¡¼¥É¼«Á³¸À¸ì½èÍý, ¥ª¥ó¥È¥í¥¸¡¼, ¹Ôưǧ¼±, ADL, LDA
¥¢¥Ö¥¹¥È¥é¥¯¥È¸½ºßÆüËܤǤϾ¯»Ò¹âÎ𲽤¬µÞ®¤Ë¿Ê¤ß¡¤¤½¤ì¤Ëȼ¤Ã¤Æ²ð¸î¶È³¦¤Ø¤Î´Ø¿´¤¬¹â¤Þ¤Ã¤Æ¤¤¤ë¡¥²ð¸î¶È³¦¤ÎÌäÂê¤Î°ì¤Ä¤Ë²ð¸îÆü»ï¤Ê¤É¤Î½ñÎàºîÀ®¤È¤¤¤Ã¤¿´ÖÀܶÈ̳¤Î¿¤µ¤¬µó¤²¤é¤ì¤ë¡¥¿¦°÷Ʊ»Î¤Î¿½¤·Á÷¤ê»ö¹à¤ÎÅÁã¤ä¡¤²ð¸î¥µ¡¼¥Ó¥¹ÍøÍѼԲȲ¤Ø¤ÎÏ¢Íí¼êÃʤȤ·¤Æ¤Î²ð¸îÆü»ï¤Ç¤¢¤ë¤¬¡¤¤³¤ÎÆþÎϤ¬¼«Æ°²½¤Ç¤­¤ì¤Ð¡¤²ð¸î»ÜÀß¿¦°÷¤Ï¤è¤êÎɤ¤¥µ¡¼¥Ó¥¹¤ÎÄ󶡤˽¸Ãæ¤Ç¤­¤ë¤è¤¦¤Ë¤Ê¤ë¤È¹Í¤¨¤é¤ì¤ë¡¥ËÜÏÀʸ¤Ç¤Ï¡¤²ð¸îÆü»ï¤Î¼«Æ°ÆþÎϤòÌÜɸ¤È¤·¤Æ¡¤²ð¸îʬÌî¤ËÆÃÍ­¤Î¥ª¥ó¥È¥í¥¸¡¼¤Î¼«Æ°¹½ÃۤˤĤ¤¤Æ¸¡Æ¤¤·¤¿¡¥


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Æü»þ: 2019ǯ7·î5Æü(¶â) 10:30 - 12:10
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8B-1 (»þ´Ö: 10:30 - 10:50)
Âê̾¼«Æ°¼Ö¤òÃæ¿´¤È¤·¤¿Î¦¾å¸òÄ̤Υꥢ¥ë¥¿¥¤¥à°ÌÃ֥ޥͥ¸¥á¥ó¥ÈÊý¼°¤Î¸¡Æ¤
Ãø¼Ô*º´Æ£ ±Ê¶Õ, ¾¾ÁÒ Î¶Ç·²ð, ¼ÅÄ ²ÅÍø, ÎëÌÚ ¾´¿¿ (´ä¼ê¸©Î©Âç³Ø)
¥Ú¡¼¥¸pp. 1604 - 1609
¥­¡¼¥ï¡¼¥É¸òÄÌ´ÉÍý¥·¥¹¥Æ¥à, ¼«Æ°¼Ö¤Î°ÌÃÖ´ÉÍý, MGRS
¥¢¥Ö¥¹¥È¥é¥¯¥È¤³¤ÎÏÀʸ¤Ç¤ÏΦ¾å¸òÄ̤μ¡À¤Âå¤Î´ÉÍýÊý¼°¤ò¼Â¸½¤¹¤ëÊýË¡¤ò¸¡Æ¤¤·¡¢¤½¤Î¤¦¤Á¤Î°ì¤Ä¤Ë¤Ä¤¤¤Æɾ²Á¤ò¹Ô¤¦¡£Î¦¾å¸òÄ̤˻²²Ã¤¹¤ë°ÜÆ°ÂΤοô¤¬ËÄÂç¤Ç¤¢¤ë¡¢¹Ò¶õ¸òÄ̤Τ褦¤Ë¾ÜºÙ¤Ë´ÉÍý¤·¤Ê¤¯¤Æ¤â½ÅÂç¤Ê»ö¸Î¤Ë¤ÏľÀܤĤʤ¬¤é¤Ê¤¤¡¢Âç·¿Á¥Çõ¤È°ã¤Ã¤ÆÈæ³ÓŪÁà½Ä¤¬ÍưפǤ¢¤êÌÜ»ë¸å¤ÎÂбþ¤Ç»ö¸Î¤òËɤ²¤ë¤Ê¤É¤ÎÍýͳ¤«¤é¡¢Î¦¾å¸òÄ̤ΰÜÆ°ÂΤϥޥ¹¤È¤·¤Æ¤ÏÇÄ°®¤µ¤ì¤Æ¤¤¤¿¤¬¸Ä¡¹¤Î°ÜÆ°ÂΤȤ·¤Æ¤ÏÇÄ°®¤µ¤ì¤Æ¤¤¤Ê¤«¤Ã¤¿¡£¤½¤³¤Ç¡¢Î¦¾å¸òÄ̤òÂоݤ˸ġ¹¤Î°ÜÆ°ÂΤΰÌÃ֤ʤɤòÇÄ°®¤·´ÉÍý¤¹¤ë¤¿¤á¤ÎÊý¼°¤òÄó°Æ¤¹¤ë¡£°ÜÆ°ÂΤΰÌÃÖ¾ðÊó¤ÎÍÑÅӤˤè¤ê¡¢¤É¤Î¤è¤¦¤Ê¥¢¡¼¥­¥Æ¥¯¥Á¥ã¤¬Ë¾¤Þ¤·¤¤¤Î¤«¤ò¸¡Æ¤¤·¡¢Åµ·¿Åª¤È»×¤ï¤ì¤ëÍÑÅÓ¤ËÆò½¤·¤¿¥·¥¹¥Æ¥à¤ÎÀ߷פò¹Ô¤¤¡¢¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤Ë¤è¤êɾ²Á¤·¤¿¡£

¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
8B-2 (»þ´Ö: 10:50 - 11:10)
Âê̾¥Ç¡¼¥¿Á÷¿®Î̲òÀϤòÍѤ¤¤¿¥¢¥É¥Û¥Ã¥¯¥Í¥Ã¥È¥ï¡¼¥¯¤ÎÆ°ºî¿äÄê¼êË¡¤ÎÄó°Æ
Ãø¼Ô*Ê¡²¬ ¹¨°ì, »³ËÜ Èþ¹¬ (ÁϲÁÂç³ØÂç³Ø±¡ ¹©³Ø¸¦µæ²Ê), ²£Ã« ůÌé (¶âÂô¹©¶ÈÂç³Ø ¹©³ØÉô), ã·Æ£ Àµ»Ë (¶âÂô¹©¶ÈÂç³Ø ¾ðÊó¥Õ¥í¥ó¥Æ¥£¥¢³ØÉô), »ûÅç Èþ¾¼ (ÁϲÁÂç³ØÂç³Ø±¡ ¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1610 - 1615
¥­¡¼¥ï¡¼¥É¥Í¥Ã¥È¥ï¡¼¥¯´Æ»ë, Æ°ºî¿äÄê, ¥¢¥É¥Û¥Ã¥¯¥Í¥Ã¥È¥ï¡¼¥¯
¥¢¥Ö¥¹¥È¥é¥¯¥ÈËܹƤǤϡ¤¼«Æ°¼Ö¤Î¼«Æ°À©¸æ±¿Å¾¡Ê¼«Æ°±¿Å¾¡Ë¤ÇÍѤ¤¤é¤ì¤ë̵Àþ¥¢¥É¥Û¥Ã¥¯¥Í¥Ã¥È¥ï¡¼¥¯¤òÂоݤˡ¤³°Éô¤«¤é´Ñ¬¤Ç¤­¤ëÄÌ¿®Ã¼Ëö¤ÎÁ÷¿®ÎÌÊѲ½¤òÈæ³Ó²òÀϤ¹¤ë¤³¤È¤Ë¤è¤Ã¤Æ¡¤ÄÌ¿®·ÐÏ©¤Ë»ÈÍѤµ¤ì¤Æ¤¤¤ëüËö·²¤È°ÜÆ°¤Ëȼ¤Ã¤ÆÊѲ½¤¹¤ëÄÌ¿®·ÐÏ©¤ÎÀÚÂØȯÀ¸»þ¹ï¤ò¿äÄꤹ¤ë¥¢¥ë¥´¥ê¥º¥à¤òÄó°Æ¤¹¤ë¡¥ÌµÀþ¥¢¥É¥Û¥Ã¥¯¥Í¥Ã¥È¥ï¡¼¥¯¤Ç¤Ï¡¤ÄÌ¿®¤Î°ÂÄêÅÙ¤ÎÄ㤵¤ä¶¯¸Ç¤Ê¥»¥­¥å¥ê¥Æ¥£¡¤ÂÓ°èÉý¤Î¶¹¤µ¤Ë¤è¤Ã¤Æ¡¤Í­Àþ¤Ç»ÈÍѤµ¤ì¤ë´ÉÍý¥×¥í¥È¥³¥ë¤ä¥Ñ¥±¥Ã¥È¥­¥ã¥×¥Á¥ã¤Ë¤è¤ë¥Í¥Ã¥È¥ï¡¼¥¯´Æ»ë¤¬Æñ¤·¤¤¡¥Äó°Æ¼êË¡¤Ç¤Ï¡¤¥Í¥Ã¥È¥ï¡¼¥¯¤ËÉé²Ù¤òÍ¿¤¨¤ë¤³¤È¤Ê¤¯³°Éô¤«¤é´Ñ¬¤Ç¤­¤ëÄÌ¿®Ã¼Ëö¤ÎÁ÷¿®ÎÌÊѲ½¤òÍѤ¤¤¿¡¤¥Ö¥é¥Ã¥¯¥Ü¥Ã¥¯¥¹¤ÊÆ°ºî´Æ»ë¤ò¼Â¸½¤Ç¤­¤ë¡¥¤Þ¤¿¡¤¥Í¥Ã¥È¥ï¡¼¥¯¥·¥ß¥å¥ì¡¼¥¿¤òÍѤ¤¤ÆÄó°Æ¼êË¡¤ÎÍýÏÀ¸¡¾Ú¤ÈÀºÅÙɾ²Á¤â¹Ô¤¦¡¥

8B-3 (»þ´Ö: 11:10 - 11:30)
Âê̾²ÐºÒÈòÆñ¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤òÍѤ¤¤¿ÄÌ¿®¼°²ÐºÒ·ÙÊó´ï¤ÎÍ­¸úÀ­¤Î¸¡¾Ú
Ãø¼Ô*ÀõÌî ½Ó¹¬ (¾ÅÆ²ÊÂç³Ø), ×¢Àî ͺ°ì, À¾Àî ·ûÌÀ (¹ñΩ¸¦µæ³«È¯Ë¡¿Í³¤Íθ¦µæ³«È¯µ¡¹½)
¥Ú¡¼¥¸pp. 1616 - 1619
¥­¡¼¥ï¡¼¥É¥Þ¥ë¥Á¥¨¡¼¥¸¥§¥ó¥È¥·¥ß¥å¥ì¡¼¥·¥ç¥ó, ÈòÆñ, °ÂÁ´, ÄÌÃÎ, ²ÐºÒ
¥¢¥Ö¥¹¥È¥é¥¯¥ÈËܸ¦µæ¤ÏÌÚ¤½»Âð¤¬Ì©½¸¤·¤Æ¤¤¤ëÃÏ°è¤Ë¤ª¤¤¤ÆÃϿ̸å¤Î±ä¾ÆÂкö¤È¤·¤ÆÍ­¸ú¤ÊÈòÆñÊýË¡¤òÄó°Æ¤¹¤ë¤³¤È¤òÌÜŪ¤È¤·¤Æ¤¤¤ë¡¥¤Þ¤º¡¤¥Þ¥ë¥Á¥¨¡¼¥¸¥§¥ó¥È¥â¥Ç¥ë¤ò²ÐºÒ³È»¶¤«¤é¤ÎÈòÆñ¤Î¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤ËŬÍѤ·¤¿¡¥²æ¡¹¤Ï¡¤¤½¤Î²Ä»ëÀ­¤Ë´ð¤Å¤¤¤Æ¡¤Ï¢Â³¶õ´Ö¤Ë¤ª¤±¤ëÊâ¹Ô¼Ô¤Î¹ÔÆ°¤ò¥·¥ß¥å¥ì¡¼¥È¤¹¤ë¤¿¤á¤ËÈù»ëŪÊâ¹Ô¼Ô¥â¥Ç¥ë¤ò¹½ÃÛ¤·¤¿¡¥²ÐºÒÈòÆñ¤Î¾ì¹ç¡¤·úʪ¤«¤é¤Î½Ð²Ð¸å¤ËÈòÆñ¤¬³«»Ï¤µ¤ì¤ë¡¥Ëܸ¦µæ¤Ç¤Ï¡¤¼¡¤Î2¤Ä¤ÎÈòÆñ³«»Ï¥·¥Ê¥ê¥ª¤òÁÛÄꤹ¤ë¡¥1¤ÄÌܤϡɶáÎÙ·úʪ¤Î½Ð²Ð¤Ë¤è¤êÈòÆñ³«»Ï¤¹¤ë¡É¡¤2¤ÄÌܤϡÉÊóÃδïƱ»Î¤Î¾ðÊóÅÁ㵡ǽ¤òÍ­¤¹¤ë²ÐºÒÊóÃε¡¤ÎºîÆ°¤Ë¤è¤êÈòÆñ³«»Ï¤¹¤ë¡É¤Ç¤¢¤ë¡¥ÌµÀþLAN¤òÍ­¤¹¤ë²ÐºÒÊóÃδï¤Ï²æ¡¹¤ÎÄó°Æ¤¹¤ëµ¡Ç½¤òÍ­¤·¤¿¤â¤Î¤Ç¤¢¤ê¡¤¤½¤ÎÍ­¸úÀ­¤òɾ²Á¤·¤¿¡¥¤³¤Î¤è¤¦¤Ë¼ÂÁ©Åª¤Ê¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤òÍѤ¤¤¿ÈòÆñ·×²è¤ÏÈó¾ï¤Ë½ÅÍפ«¤Ä¸ú²ÌŪ¤Ç¤¢¤ë¤È·ëÏÀ¤µ¤ì¤ë¡¥

8B-4 (»þ´Ö: 11:30 - 11:50)
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Ãø¼Ô*¸ÅÅÄ µ®Ìé (Áá°ðÅÄÂç³Ø´ð´´Íý¹©³Ø¸¦µæ²Ê¾ðÊóÍý¹©¡¦¾ðÊóÄÌ¿®À칶), ¹â¶¶ ε°ì (°ñ¾ëÂç³Ø¹©³ØÉô¾ðÊ󹩳زÊ), ¿¼ß· Îɾ´ (Áá°ðÅÄÂç³Ø´ð´´Íý¹©³Ø¸¦µæ²Ê¾ðÊóÍý¹©¡¦¾ðÊóÄÌ¿®À칶)
¥Ú¡¼¥¸pp. 1620 - 1630
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Æü»þ: 2019ǯ7·î5Æü(¶â) 10:30 - 12:10
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8C-1 (»þ´Ö: 10:30 - 10:50)
Âê̾NTMobile¤Ë¤è¤ëAndroid¥¹¥Þ¡¼¥È¥Õ¥©¥ó¤Î¤¿¤á¤ÎIP Flow Mobility¤ÎÄó°Æ
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¥Ú¡¼¥¸pp. 1631 - 1636
¥­¡¼¥ï¡¼¥ÉIP Flow Mobility, QoE, °ÜÆ°Æ©²áÀ­µ»½Ñ, Android, ¥ª¥Õ¥í¡¼¥É
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ºÇÍ¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Best Presentation Awards
Í¥½¨ÏÀʸ¾Þ / Paper Awards
8C-2 (»þ´Ö: 10:50 - 11:10)
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Ãø¼Ô*Å·Ìî äºÈ, »³¸ý ¹°½ã, ÅìÌî µ±É× (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), üâ°æ ÊöÀ¸ (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê/¥«¥ê¥Õ¥©¥ë¥Ë¥¢Âç³Ø¥í¥µ¥ó¥¼¥ë¥¹¹»)
¥Ú¡¼¥¸pp. 1637 - 1647
¥­¡¼¥ï¡¼¥ÉWi-Fi, ÅԻԴĶ­, AP°ÌÃÖ¿äÄê
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Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
ºÇÍ¥½¨ÏÀʸ¾Þ / Best Paper Awards
8C-3 (»þ´Ö: 11:10 - 11:30)
Âê̾Â絬ÌϤʼÂƯ̵ÀþLAN¥·¥¹¥Æ¥àɾ²Á¤Î¤¿¤á¤Î²¾ÁۥǥХ¤¥¹ÍøÍÑ·¿ÌµÀþLAN¥¨¥ß¥å¥ì¡¼¥¿
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¥Ú¡¼¥¸pp. 1648 - 1656
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8C-4 (»þ´Ö: 11:30 - 11:50)
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¥Ú¡¼¥¸pp. 1657 - 1662
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Æü»þ: 2019ǯ7·î5Æü(¶â) 10:30 - 12:10
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ºÂĹ: À¶¸¶ ÎÉ»° (¿ÀÆàÀ²ÊÂç³Ø)

8D-1 (»þ´Ö: 10:30 - 10:50)
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Ãø¼Ô*À¾Â¼ Å·À² (Áá°ðÅÄÂç³Ø), ¹â»³ ÉÒŵ (¥¼¥ó¥ê¥ó¥Ç¡¼¥¿¥³¥à), Ìøß· À¯À¸, ¸ÍÀî ˾ (Áá°ðÅÄÂç³Ø)
¥Ú¡¼¥¸pp. 1663 - 1669
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8D-2 (»þ´Ö: 10:50 - 11:10)
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Ãø¼Ô*±§º´¸« ͧÍý (Áá°ðÅÄÂç³Ø), ÀÐÀî ÏÂÌÀ, ¹â»³ ÉÒŵ (¥¼¥ó¥ê¥ó¥Ç¡¼¥¿¥³¥à), Ìøß· À¯À¸, ¸ÍÀî ˾ (Áá°ðÅÄÂç³Ø)
¥Ú¡¼¥¸pp. 1670 - 1675
¥­¡¼¥ï¡¼¥É¼«Å¾¼Ö, ¹Ôưǧ¼±, ¥¹¥Þ¡¼¥È¥Õ¥©¥ó, ITS, ºäÆ»
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8D-3 (»þ´Ö: 11:10 - 11:30)
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Ãø¼Ô*úËß· Íý¼Ó, ÃæÂô ¼Â (¶âÂô¹©¶ÈÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê¾ðÊ󹩳ØÀ칶), Ĺ¾Â Í× (¶âÂô¹©¶ÈÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Êµ¡³£¹©³ØÀ칶)
¥Ú¡¼¥¸pp. 1676 - 1681
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8D-4 (»þ´Ö: 11:30 - 11:50)
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Ãø¼Ô*ÀÐÅÄ ÈË̦, ÆâÌî ²í¿Í, ¾®ÃÓ ÂçÃÏ (¶å½£Âç³Ø), ÅÄƬ ÌÐÌÀ (´ØÀ¾Âç³Ø), Ê¡ÅÄ ¹¸ (¶å½£Âç³Ø)
¥Ú¡¼¥¸pp. 1682 - 1687
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8D-5 (»þ´Ö: 11:50 - 12:10)
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¥Ú¡¼¥¸pp. 1688 - 1696
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Æü»þ: 2019ǯ7·î5Æü(¶â) 10:30 - 12:10
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8E-2 (»þ´Ö: 10:30 - 10:50)
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¥Ú¡¼¥¸pp. 1697 - 1699
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¥¢¥Ö¥¹¥È¥é¥¯¥È¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¤Ïʹ¤­¼ê¤ÎÍý²ò¤äǼÆÀ¤òÆÀ¤ë¤¿¤á¤Î¾ðÊóÅÁã¼êÃʤǤ¢¤ê¡¤ÍÍ¡¹¤ÊÁÈ¿¥³èÆ°¤Ë¤ª¤¤¤Æ½ÅÍפÊǽÎϤȤäƤ¤¤ë¡¥¤·¤«¤·, Ʊ¤¸ÆâÍƤòȯɽ¤¹¤ë¤Ë¤·¤Æ¤â¡¤È¯É½¼Ô¤ÎÅÁ¤¨Êý¤äÀº¿À¾õÂ֤ˤè¤êʹ¤­¼ê¤«¤é¤Îɾ²Á¤ÏÂ礭¤¯ÊѤï¤Ã¤Æ¤·¤Þ¤¦. Ëܸ¦µæ¤Ç¤Ï, ÉáÃʤÎÃåÍѤÎ˸¤²¤Ë¤Ê¤é¤Ê¤¤¥¦¥§¥¢¥é¥Ö¥ë¥³¥ó¥Ô¥å¡¼¥Æ¥£¥ó¥°¤ÎÆÃħ¤ò³è¤«¤·¤Æ, ¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¤Î¼Â±é»þ¤Ë¤ª¤±¤ë¡ÖÀ¼ÎÌ¡¦ÌÜÀþ¡×¤Î¼Á¤ò¸þ¾å¤µ¤»¤ë¤³¤È¤ËÃåÌܤ·, ¶µ¼¨¥¢¥Ë¥á¡¼¥·¥ç¥ó¤òÍѤ¤¤¿¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¼Â±é»Ù±ç¥·¥¹¥Æ¥à¤òÄó°Æ¤·, ɾ²Á¼Â¸³¤ò¹Ô¤Ê¤Ã¤¿. ¤½¤Î·ë²Ì, ȯɽ¼Ô¤Î¼«¸Êɾ²Á¤ËÊѲ½¤Ï¸«¤é¤ì¤Ê¤«¤Ã¤¿¤¬, À¼ÎÌ¡¦ÌÜÀþ¤Ë¤ª¤¤¤Æ¤Ï¶¦¤ËÍ­°Õ¤ÊÊѲ½¤¬ÆÀ¤é¤ì¤¿.

ºÇÍ¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Best Presentation Awards
8E-3 (»þ´Ö: 10:50 - 11:10)
Âê̾Ê׺ߤ¹¤ë´é¥í¥Ü¥Ã¥È¤òÍѤ¤¤¿Ãí°ÕͶƳ¸ú²Ì¤Îɾ²Á
Ãø¼Ô*¹¾¸ý °½Î¼ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), °ë»³ ľÌé (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³ØÀèü²Ê³Øµ»½Ñ¸¦µæ²Ê), »ûÅÄ ÅØ, ÄÍËÜ ¾»É§ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1700 - 1707
¥­¡¼¥ï¡¼¥É¥í¥Ü¥Ã¥È, ¥¤¥ó¥¿¥é¥¯¥·¥ç¥ó, Ãí°ÕͶƳ, HRI
¥¢¥Ö¥¹¥È¥é¥¯¥È¿Í¤Î»ëÀþ¤Ï¡¤Ãí»ëÂоݤ伫¿È¤Î´¶¾ð¤òÅÁ¤¨¤ë¤À¤±¤Ç¤Ê¤¯¡¤¼þ°Ï¤Î¿Í¤ËÂФ·¤ÆÍÍ¡¹¤Ê±Æ¶Á¤ò¤â¤¿¤é¤¹¡¥Î㤨¤Ð¡¤¿Í¤Ï¾¼Ô¤Î»ëÀþÊý¸þ¤ËÃí°Õ¤¬Í¶Æ³¤µ¤ì¤ë¤³¤È¤ä¡¤Â¾¼Ô¤Ë¸«¤é¤ì¤Æ¤¤¤ë¤È¤¤¤¦°Õ¼±¤¬¿Í¤Î¹ÔÆ°¤Ë±Æ¶Á¤òÍ¿¤¨¤ë¤³¤È¤¬Àè¹Ô¸¦µæ¤Ë¤è¤Ã¤ÆÌÀ¤é¤«¤Ë¤µ¤ì¤Æ¤¤¤ë¡¥º£¸å¡¤¥¢¥ó¥É¥í¥¤¥É¥í¥Ü¥Ã¥È¤¬¼Ò²ñ¤Ç³èÌö¤¹¤ë¤è¤¦¤Ë¤Ê¤ê¡¤¤³¤Î¤è¤¦¤Ê»ëÀþ¤Ë¤è¤ë¥³¥ß¥å¥Ë¥±¡¼¥·¥ç¥ó¤ä¾ðÊóÅÁã¤Ï¿Í¤È¥í¥Ü¥Ã¥È¤Î´Ö¤Ç¤â²Äǽ¤Ë¤Ê¤ë¤È¹Í¤¨¤é¤ì¤ë¡¥¤·¤«¤·¡¤Æü¾ïÀ¸³è¤Ë¤ª¤¤¤ÆÊ׺ßŪ¤Ë¸ºß¤¹¤ë¥í¥Ü¥Ã¥È¤Î»ëÀþ¤¬¡¤¥æ¡¼¥¶¤ËÍ¿¤¨¤ë±Æ¶Á¤òÄ´ºº¤·¤¿¸¦µæ¤ÏÉ®¼Ô¤é¤ÎÃΤë¸Â¤ê¸ºß¤·¤Ê¤¤¡¥¤½¤³¤ÇËܸ¦µæ¤Ç¤Ï¡¤Æü¾ïÀ¸³è´Ä¶­¤ËÀßÃÖ¤µ¤ì¤¿´é¥í¥Ü¥Ã¥È¤Î»ëÀþ¤Ë¤è¤ëÃí°ÕͶƳ¸ú²Ì¤Îɾ²Á¤ò¹Ô¤¦¡¥ËܹƤǤϡ¤´é¥í¥Ü¥Ã¥È¤¬Æü¾ïÀ¸³è¤ËÊ׺ߤ¹¤ë´Ä¶­¤Ç¤Î¥µ¡¼¥Ó¥¹Îã¤òÊ£¿ô¼¨¤·¡¤¤½¤ÎÃ椫¤é¤Õ¤¿¤Ä¤ÎÁÛÄê´Ä¶­¤Ë¤ª¤¤¤ÆÃí°ÕͶƳ¸ú²Ì¤ò¸¡¾Ú¤¹¤ë¼Â¸³¤ò¹Ô¤Ã¤¿¡¥¼Â¸³¤Î·ë²Ì¡¤´é¥í¥Ü¥Ã¥È¤Î»ëÀþÊý¸þ¤ËÈ︳¼Ô¤¬Ãí°Õ¤ò¸þ¤±¤¿²ó¿ô¤Ï¾¯¤Ê¤«¤Ã¤¿¡¥¤·¤«¤·¡¤¼þ°Ï¤Î¾õ¶·¤ä¡¤´é¥í¥Ü¥Ã¥È¤Î¥µ¡¼¥Ó¥¹¤ËÂФ¹¤ë°Õ¼±¤Ê¤É¤ÎÍ×°ø¤Ë´Ø¤·¤Æ¤Î¹Í»¡¤òÄ̤·¤Æ¡¤Ãí°ÕͶƳ¤òÍѤ¤¤¿¥µ¡¼¥Ó¥¹¤Î¼Â¸½²ÄǽÀ­¤¬¼¨¤µ¤ì¤¿¡¥

8E-4 (»þ´Ö: 11:10 - 11:30)
Âê̾¹ÔÆ°ÊÑÍÆ¥¿¥¹¥¯¤ò¹Íθ¤·¤¿¥µ¡¼¥Ó¥¹´ÖÏ¢·È¥Õ¥ì¡¼¥à¥ï¡¼¥¯¤ÎÀ߷פȼÂÁõ
Ãø¼Ô*Ä¥ »Ö²Ú, ¾¾ÅÄ Íµµ®, Æ£ËÜ ¤Þ¤Ê¤È (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø¾ðÊó²Ê³Ø¸¦µæ²Ê¥æ¥Ó¥­¥¿¥¹¥³¥ó¥Ô¥å¡¼¥Æ¥£¥ó¥°¥·¥¹¥Æ¥à¸¦µæ¼¼), ¹ÓÀî Ë­ (¶å½£Âç³ØÂç³Ø±¡¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ±¡ ¥Ò¥å¡¼¥Þ¥Î¥Õ¥£¥ê¥Ã¥¯¥·¥¹¥Æ¥à¸¦µæ¼¼/JST¤µ¤­¤¬¤±), °ÂËÜ ·Ä°ì (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø¾ðÊó²Ê³Ø¸¦µæ²Ê¥æ¥Ó¥­¥¿¥¹¥³¥ó¥Ô¥å¡¼¥Æ¥£¥ó¥°¥·¥¹¥Æ¥à¸¦µæ¼¼)
¥Ú¡¼¥¸pp. 1708 - 1715
¥­¡¼¥ï¡¼¥É¹ÔÆ°ÊÑÍÆ, IFTTT
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Í¥½¨¥×¥ì¥¼¥ó¥Æ¡¼¥·¥ç¥ó¾Þ / Presentation Awards
8E-5 (»þ´Ö: 11:30 - 11:50)
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Ãø¼Ô*À¶¿å ͧ½ç (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), Áи« µþ²ð (Ω̿´ÛÂç³Ø¾ðÊóÍý¹©³ØÉô), »ûÅÄ ÅØ, ÄÍËÜ ¾»É§ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1716 - 1724
¥­¡¼¥ï¡¼¥ÉÁªÂò, ¿ÍÍÀ­, ¾ðÊóÄó¼¨, ¥Ò¥å¡¼¥Þ¥ó¥¤¥ó¥¿¥Õ¥§¡¼¥¹, ³ÈÄ¥-·ÁÀ®ÍýÏÀ
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Æü»þ: 2019ǯ7·î5Æü(¶â) 10:30 - 12:10
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8F-1 (»þ´Ö: 10:30 - 10:50)
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Ãø¼Ô¿¼Èø ¤¢¤«¤ê, *Áи« µþ²ð, ¼Èø ÏÂºÈ (Ω̿´ÛÂç³Ø¾ðÊóÍý¹©³ØÉô)
¥Ú¡¼¥¸pp. 1725 - 1730
¥­¡¼¥ï¡¼¥É¹Ôưǧ¼±, ÆþÂ༼ưºî, ¸Ä¿Íǧ¼±, ¥æ¥Ó¥­¥¿¥¹, ¥É¥¢
¥¢¥Ö¥¹¥È¥é¥¯¥ÈÊ£¿ô¿Í¤Ç¶¦Í­¤¹¤ëÉô²°¤ÏÆü¾ïÀ¸³è¤Ë¤ª¤¤¤Æ¿¤¯ÍøÍѤµ¤ì¤Æ¤¤¤ë¡¥¸Ä¿Íǧ¼±¤Î¤¿¤á¤Î¼êË¡¤Ï¿¤¯Äó°Æ¤µ¤ì¤Æ¤¤¤ë¤¬¡¤ÆþÂ༼¼Ô¤Îǧ¼±¤Ë¤¢¤¿¤Ã¤Æ¤Ï¡¤¥æ¡¼¥¶¤ËÉÔÍפʺî¶È¤äµ¡´ï·ÈÂÓ¤òÍפ¹¤ë¤Ê¤É¿´ÍýŪ¡¦¿ÈÂÎŪ¤ÊÉéô¤Î´ÑÅÀ¤Ç²ÝÂ꤬¤¢¤ë¡¥Ëܸ¦µæ¤Ç¤ÏÆþÂ༼¤Ëȼ¤¦Æ°ºî¤Ç¤¢¤ë¥É¥¢¤Î³«ÊÄÆ°ºî¤òÍøÍѤ¹¤ë¤³¤È¤Ç¡¤ÆþÂ༼¼Ô¤òǧ¼±¤¹¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡¥Äó°Æ¼êË¡¤Ï¡¤¥É¥¢¤Î³«ÊÄÆ°ºî¤Ë¤Ï¥æ¡¼¥¶¤´¤È¤Ë°Û¤Ê¤ëÆÃħ¤¬¤¢¤ë¤È¤¹¤ë²¾Àâ¤Ë¤â¤È¤Å¤¯¡¥¤½¤·¤Æ¡¤¥É¥¢¥Î¥Ö¤Ë³Ñ®ÅÙ¥»¥ó¥µ¤òÀßÃÖ¤·¡¤¥æ¡¼¥¶¤¬ÆþÂ༼¤·¤¿ºÝ¤Î¥É¥¢¤Î³«ÊÄÆ°ºî¤«¤é8¼ïÎà¤ÎÆÃħÎ̤òÃê½Ð¤·¡¤µ¡³£³Ø½¬¤òÍѤ¤¤ÆÆþÂ༼¼Ô¤òǧ¼±¤¹¤ë¡¥Äó°Æ¼êË¡¤Î¥×¥í¥È¥¿¥¤¥×¥·¥¹¥Æ¥à¤ò°ìÈÌŪ¤Ê¥ì¥Ð¡¼¥Ï¥ó¥É¥ë¼°¤Î¥É¥¢¤Ë¼ÂÁõ¤·¡¤°ìÈ̲ÈÄí¤òÁÛÄꤷ¤ÆÈ︳¼Ô4̾¤òÂоݤ˼¸³¤ò¹Ô¤¤¡¤Æþ¼¼Æ°ºî¤ÈÂ༼ưºî¤Îǧ¼±¤ò¤½¤ì¤¾¤ì¹Ô¤Ã¤¿¡¥¤½¤Î·ë²Ì¡¤Â༼ưºî¤ÎFÃͤϺÇÂç0.90¤Çǧ¼±¤Ç¤­¡¤¤Þ¤¿¡¤Æþ¼¼Æ°ºî¤ÎFÃͤϺÇÂç0.73¤Çǧ¼±¤Ç¤­¡¤Äó°Æ¼êË¡¤Î¼Â¸½²ÄǽÀ­¤ò³Îǧ¤·¤¿¡¥

¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
8F-2 (»þ´Ö: 10:50 - 11:10)
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Ãø¼Ô*À¾°æ ÍÚºÚ, Áи« µþ²ð, ¼Èø ÏÂºÈ (Ω̿´ÛÂç³Ø¾ðÊóÍý¹©³ØÉô)
¥Ú¡¼¥¸pp. 1731 - 1738
¥­¡¼¥ï¡¼¥ÉʪÂÎǧ¼±, ²»¶Á¥»¥ó¥·¥ó¥°, Ä´Íý
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
8F-3 (»þ´Ö: 11:10 - 11:30)
Âê̾finDrawers:¼ýǼʪ¤ò¸¡º÷²Äǽ¤Ê°ú¤­½Ð¤·¤Î¼ÂÁõ
Ãø¼Ô*ÎëÌÚ ñ¥ÇÏ, Ω²Ö ¹ª¼ù (ÆüËÜÂç³Ø), ÂçÏ ʹµ±, ¸â ·òϯ, ÉÙ±Ê »í²» (ÆüËÜÂç³ØÂç³Ø±¡), µÜÅÄ ¾Ï͵ (ÆüËÜÂç³Ø)
¥Ú¡¼¥¸pp. 1739 - 1745
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
8F-4 (»þ´Ö: 11:30 - 11:50)
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Ãø¼Ô*±üÅÄ ¿òÎé (Ë­¶¶µ»½Ñ²Ê³ØÂç³ØÂç³Ø±¡), µÜÏ© Í´°ì, Âç¼ Î÷ (Ë­¶¶µ»½Ñ²Ê³ØÂç³Ø)
¥Ú¡¼¥¸pp. 1746 - 1754
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¥»¥Ã¥·¥ç¥ó 8G  ʬÀÏ¡¦²Ä»ë²½
Æü»þ: 2019ǯ7·î5Æü(¶â) 10:30 - 12:10
Éô²°: Í·Éñ¡¦°ì¤ÎÍ·
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
8G-1 (»þ´Ö: 10:30 - 10:50)
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Ãø¼Ô*ĹÈø ¾­¹¨, ÊÒ²¬ ¾¼¿Í, ß·ÅÄ Ä¾¼ù, º£À¾ ¾»»Ò, Ëܶ¶ Íβð (NEC AI¡¦¥¢¥Ê¥ê¥Æ¥£¥¯¥¹»ö¶ÈÉô)
¥Ú¡¼¥¸pp. 1755 - 1759
¥­¡¼¥ï¡¼¥É¥Ê¥ì¥Ã¥¸¥Þ¥Í¥¸¥á¥ó¥È, ²Ä»ë²½, ¶È̳¥Î¥¦¥Ï¥¦, ¥¹¥­¥ë¥»¥Ã¥È, ¥Î¥¦¥Õ¡¼¾ðÊó
¥¢¥Ö¥¹¥È¥é¥¯¥ÈËܹƤǤϡ¢¶È̳¥í¥°¤ò¤â¤È¤Ë¤·¤¿¥Î¥¦¥Õ¡¼¾ðÊó²Ä»ë²½¥·¥¹¥Æ¥à¤òÄó°Æ¤¹¤ë¡£½¾Íè¤Î¥Ê¥ì¥Ã¥¸¥Þ¥Í¥¸¥á¥ó¥È¥·¥¹¥Æ¥à¤Ç¤Ï¡¢³Æ¿Í¤Î¥¹¥­¥ë¥»¥Ã¥È¤ä¥Î¥¦¥Õ¡¼¾ðÊó¤ò¼êÆþÎϤ¹¤ëɬÍפ¬¤¢¤ê¡¢¤Þ¤¿¡¢¶È̳ÆâÍƤÎÊѹ¹¤Ê¤É¤Ëȼ¤Ã¤ÆÄê´üŪ¤Ë¹¹¿·¤ò¤¹¤ëɬÍפ¬¤¢¤Ã¤¿¡£¤ï¤ì¤ï¤ì¤Ï¡¢¶È̳¥í¥°¤Î¼ý½¸¡¢¶È̳´ØϢñ¸ì¤ÎÃê½Ð¡¢³Æ¥ï¡¼¥«¡¼¤Èñ¸ì¤Î´Ø·¸À­¤ò»»½Ð¤¹¤ë¤³¤È¤Ç¡¢¼êÆþÎϤμê´Ö¤ò¤«¤±¤º¤Ë¥Î¥¦¥Õ¡¼¾ðÊó¤ò²Ä»ë²½¤¹¤ë¥·¥¹¥Æ¥à¤ò³«È¯¤·¤¿¡£¤Þ¤¿¡¢É¾²Á¼Â¸³¤È¤·¤Æ¥Î¥¦¥Õ¡¼¾ðÊó²Ä»ë²½¤ÎÂÅÅöÀ­¡¦Í­¸úÀ­¤Î¸¡¾Ú¤ò¹Ô¤Ã¤¿¡£

8G-2 (»þ´Ö: 10:50 - 11:10)
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Ãø¼Ô*°¤Áð ͵ (°¦É²Âç³ØÂç³Ø±¡Íý¹©³Ø¸¦µæ²Ê), Æ£¶¶ ÂîÌé (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), ±óÆ£ ·Ä°ì, ¹õÅÄ µ×ÂÙ, ¾®ÎÓ ¿¿Ìé (°¦É²Âç³ØÂç³Ø±¡Íý¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1760 - 1771
¥­¡¼¥ï¡¼¥É¾ðÊó¥·¥¹¥Æ¥à, IoT, ¥Ó¥Ã¥°¥Ç¡¼¥¿, ²Ä»ë²½, ÃÏ°è²ÝÂê²ò·è
¥¢¥Ö¥¹¥È¥é¥¯¥ÈÍÜ¿£µù¶È¤Ë¤ª¤¤¤Æ¤Ï¡¤¸½¾ì¼þ°Ï¤Î³¤°è¤Ë¤ª¤±¤ë³¤¿å²¹¾ðÊó¤¬Èó¾ï¤Ë½ÅÍפǤ¢¤ë¡¥¿å²¹¤òÃΤ뤳¤È¤Ç¡¤µûÉÂÂкö¤ä¡¤ÀÖĬ¤ÎȯÀ¸Í½Â¬¤ò¹Ô¤¦¤³¤È¤¬¤Ç¤­¤ë¤«¤é¤Ç¤¢¤ë¡¥¤·¤«¤·¡¤°¦É²¸©¤Ç¤Ï¡¤Ä´ººÁ¥¤Ë¤è¤ëÄêÅÀÄ´ºº¤ä¿å²¹´Ñ¬ÁõÃ֤ˤè¤ë¬Äê¤ÇÆÀ¤é¤ì¤¿¿å²¹¥Ç¡¼¥¿¤¬¡¤»þ´ÖŪ¡¦¶õ´ÖŪ¤ËϢ³¤·¤¿¥Ç¡¼¥¿¤È¤·¤ÆÉÔ½½Ê¬¤Ç¤¢¤ë¤È¤¤¤¦ÌäÂ꤬¤¢¤Ã¤¿¡¥¤Þ¤¿¡¤¼ý½¸¤·¤¿¿å²¹¾ðÊó¤òµù¶È½¾»ö¼Ô¤Ø¹ðÃÎÅÁ㤹¤ë¼êÃʤâ³ÎΩ¤Ç¤­¤Æ¤¤¤Ê¤«¤Ã¤¿¡¥¤½¤³¤ÇËܸ¦µæ¤Ç¤Ï¡¤Â¿¿¼Å٤Υ»¥ó¥µ¡¼¥Í¥Ã¥È¥ï¡¼¥¯¥·¥¹¥Æ¥à¤ÈËܥͥåȥ¥¯¥·¥¹¥Æ¥à¾å¤Ç¼ý½¸¤·¤¿¿å²¹¾ðÊó¤ò²Ä»ë²½¤¹¤ë¥·¥¹¥Æ¥à(³¤¿å²¹¾ðÊó¹ðÃÎÅÁ㥷¥¹¥Æ¥à)¤ò¹½ÃÛ¤·¤¿¡¥ËܹðÃÎÅÁ㥷¥¹¥Æ¥à¤Ç¤Ï¡¤Web¥Ö¥é¥¦¥¶¤«¤é¡¤ºÇ¿·¤Î¿å²¹¾ðÊó¤ä¿å²¹¤Î»þ´ÖÊѲ½¤òɽ¡¤¥°¥é¥Õ¡¤¤ª¤è¤Ó»°¼¡¸µ²¹ÅÙʬÉۿޤηÁ¤Ç¸«¤ë¤³¤È¤¬¤Ç¤­¤ë¡¥µù¶È½¾»ö¼Ô¤Ï¡¤ËÜ¥·¥¹¥Æ¥à¤òÍøÍѤ·¤Æ¿å²¹¾õ¶·¤òÇÄ°®¤¹¤ë¤³¤È¤Ç¸úΨŪ¤Êµù¶È¤ò¹Ô¤¦¤³¤È¤¬¤Ç¤­¤ë¤è¤¦¤Ë¤Ê¤Ã¤¿¡¥ËÜ¥·¥¹¥Æ¥à¤ËÂФ¹¤ë¥æ¥Ë¡¼¥¯¥¢¥¯¥»¥¹¿ô¤ÏËèÆü300¡Á700·ïÄøÅ٤ȤʤäƤª¤ê¡¤°¦É²¸©±§Ï³¤¤ÎÍÜ¿£µù¶È¼Ô¿ô¤òƧ¤Þ¤¨¤ë¤ÈËÜ¥·¥¹¥Æ¥à¼ÂÁõ¤¬ÍÜ¿£µù¶È¤ËÍ¿¤¨¤¿±Æ¶Á¤ÏÂ礭¤¤¤È¸À¤¨¤ë¡¥

8G-3 (»þ´Ö: 11:10 - 11:30)
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Ãø¼Ô*¾®ºå ¾°»Ò, à©Àî Ãι¨ (NTT¥»¥­¥å¥¢¥×¥é¥Ã¥È¥Õ¥©¡¼¥à¸¦µæ½ê), »³¸ý ·ò»Ë, ´¥ ·òÂÀϺ (ÅìËÌÂç³Ø)
¥Ú¡¼¥¸pp. 1772 - 1777
¥­¡¼¥ï¡¼¥É´íµ¡Âбþ¥Þ¥Í¥¸¥á¥ó¥È, ºÒ³²ÂкöËÜÉô, ¼«Á³¸À¸ì½èÍý, ³èÆ°ÌÜŪ
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¥ä¥ó¥°¥ê¥µ¡¼¥Á¥ã¾Þ / Young Researcher Awards
8G-4 (»þ´Ö: 11:30 - 11:50)
Âê̾1»þ´Ö¤´¤È¤Î¾¦Éʤθ«ÀÚ¤ê¤òÂоݤȤ·¤¿POS¥Ç¡¼¥¿¤ÎʬÀÏ
Ãø¼Ô*µÈÅÄ ·ë²Ö, µÈÌî ¹§ (ϲλ³Âç³Ø), ¾¾»³ ¹À»Î (³ô¼°²ñ¼Ò¥µ¥¤¥Ð¡¼¥ê¥ó¥¯¥¹), µ®»Ö ¾Í¹¾, ÂçÀ¾ ¹ä (³ô¼°²ñ¼Ò¥ª¡¼¥¯¥ï)
¥Ú¡¼¥¸pp. 1778 - 1783
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Æü»þ: 2019ǯ7·î5Æü(¶â) 10:30 - 12:10
Éô²°: ³ÚÉñ¡¦°ì¤Î³Ú
ºÂĹ: ¼¼ÅÄ Êþ¼ù (Åìµþ³¤ÍÎÂç³Ø)

8H-1 (»þ´Ö: 10:30 - 10:50)
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Ãø¼Ô*²ÃÆ£ ÂçÌï (·ÄØæµÁ½ÎÂç³ØÂç³Ø±¡ ¥á¥Ç¥£¥¢¥Ç¥¶¥¤¥ó¸¦µæ²Ê), Æ£Èø ÀµÏ (ÆüΩÀ½ºî½ê¸¦ µæ³«È¯¥°¥ë¡¼¥×), ÎÓ Ã£Ìé, º½¸¶ ½¨¼ù (·ÄØæµÁ½ÎÂç³ØÂç³Ø±¡ ¥á¥Ç¥£¥¢¥Ç¥¶¥¤¥ó¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1784 - 1789
¥­¡¼¥ï¡¼¥Éǧ¾Úǧ²Ä, FIDO, ¥Ñ¥¹¥ï¡¼¥É¥ì¥¹Ç§¾Ú, À¸ÂÎǧ¾Ú, ±¿ÍÑ
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8H-2 (»þ´Ö: 10:50 - 11:10)
Âê̾IPv6¥·¥ó¥°¥ë¥¹¥¿¥Ã¥¯¤Ë¤è¤ëeduroam¹½ÃÛ
Ãø¼Ô*³ÀÆâ ÀµÇ¯, ÄÔ°æ ¹â¹À, Æ£Àî ÏÂÍø (ÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø Áí¹ç¾ðÊó´ðÈ×¥»¥ó¥¿¡¼)
¥Ú¡¼¥¸pp. 1790 - 1794
¥­¡¼¥ï¡¼¥É¥Í¥Ã¥È¥ï¡¼¥¯´ÉÍý, ¥¤¥ó¥¿¡¼¥Í¥Ã¥È, ¥Í¥Ã¥È¥ï¡¼¥¯¥»¥­¥å¥ê¥Æ¥£
¥¢¥Ö¥¹¥È¥é¥¯¥ÈÆàÎÉÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø (°Ê²¼¡¢NAIST) ¤Ç¤Ï¡¢Âç³ØˬÌä¼Ô¸þ¤±¤Î¥Í¥Ã¥È¥ï¡¼¥¯¤È¤·¤ÆIPv6¥·¥ó¥°¥ë¥¹¥¿¥Ã¥¯¤Ë¤è¤ëeduroam¤ò¹½ÃÛ¤·¤¿¡£ ¥×¥é¥¤¥Ù¡¼¥ÈIP¥¢¥É¥ì¥¹¤Î³ä¤êÅö¤Æ¤ÏÄÌ¿®¥»¥Ã¥·¥ç¥ó¤Îµ­Ï¿¤¬²ÝÂê¤È¤Ê¤Ã¤¿¡£ ¤½¤Î¤¿¤á¡¢eduroam ÍøÍѼԤˤÏIPv6¥°¥í¡¼¥Ð¥ë¥¢¥É¥ì¥¹¤òÇÛÉÛ¤·¡¢IPv4¥µ¥¤¥È¤Ø¤ÎÀܳ¤Î¤¿¤á¤Ë DNS64 / NAT64 ¤òÄ󶡤¹¤ë¤³¤È¤È¤·¤¿¡£ ¤³¤ì¤Ë¤è¤ê¡¢ÄÌ¿®¥»¥Ã¥·¥ç¥ó¤Îµ­Ï¿¤¬É¬ÍפȤʤëNATÊÑ´¹¤òɬÍפȤ¹¤ë¥»¥Ã¥·¥ç¥ó¤ò3ʬ¤Î1°Ê²¼¤Ëºï¸º¤Ç¤­¤¿¡£ ¥¢¥É¥ì¥¹ÇÛÉÛÊýË¡¤È¤·¤ÆDHCPv6¤ÈSLAAC¤ò»î¤·¤¿·ë²Ì¡¢¥¢¥É¥ì¥¹¼èÆÀΨ¤Ï¤½¤ì¤¾¤ì81\%¡¢94\%¤Ç¤¢¤Ã¤¿¡£ ËÜȯɽ¤Ç¤Ï¡¢ÍøÍѼԤ˳ä¤êÅö¤Æ¤ëIP¥¢¥É¥ì¥¹¤Î¸¡Æ¤¡¢¹½ÃÛ¤·¤¿¥Í¥Ã¥È¥ï¡¼¥¯¤Î¹½À®¡¦ÀßÄê¥Ñ¥é¥á¡¼¥¿¡¢Æ³Æþ¸å¤ÎÍøÍѾõ¶·¤Ë¤Ä¤¤¤ÆÀâÌÀ¤¹¤ë¡£

8H-3 (»þ´Ö: 11:10 - 11:30)
Âê̾IMAP¥¨¡¼¥¸¥§¥ó¥È¤Ë¤è¤ë¥µ¡¼¥Ð¤ÎÀßÄêÊѹ¹¤òÍפ·¤Ê¤¤½ÀÆð¤Ê¥á¡¼¥ëžÁ÷¥·¥¹¥Æ¥à
Ãø¼Ô*ÅÄÂå ´²»°, »³°æ À®ÎÉ, ËÌÀî ľºÈ (ÅìµþÇÀ¹©Âç³Ø)
¥Ú¡¼¥¸pp. 1795 - 1800
¥­¡¼¥ï¡¼¥ÉÅŻҥ᡼¥ë, IMAP, ¥¨¡¼¥¸¥§¥ó¥È, ¥á¡¼¥ëžÁ÷
¥¢¥Ö¥¹¥È¥é¥¯¥ÈÅŻҥ᡼¥ë¤ÎžÁ÷½èÍý¤ÏMTA¡ÊMail Transfer Agent¡Ë¤ÎÀßÄê¤äMDA¡ÊMail Delivery Agent¡Ë¤Î ÀßÃ֤ˤè¤ë¼Â¸½¤¬°ìÈÌŪ¤Ç¤¢¤ë¡¥¤·¤«¤·¡¤¤½¤Î¤è¤¦¤ÊľÀÜŪ¤Ê¥á¡¼¥ë¥µ¡¼¥Ð¤ÎÀßÄêÊѹ¹¤¬Ç§¤á¤é¤ì¤Ê¤¤¥Õ ¥ê¡¼¥á¡¼¥ë¥µ¡¼¥Ó¥¹Åù¤Ë¤ª¤¤¤Æ¤Ï¡¤¥µ¡¼¥Ó¥¹±¿±Ä¼Ô¤¬Web ¥µ¡¼¥Ó¥¹Åù¤ò²ð¤·¤ÆÄ󶡤¹¤ëGUI ¤ÎÈϰϳ°¤Î ¹âÅ٤ʞÁ÷½èÍý¤ò¹Ô¤¦¤³¤È¤¬¤Ç¤­¤Ê¤¤¡¥¤³¤Î¤è¤¦¤Ë¸½¹Ô¤ÎžÁ÷¥·¥¹¥Æ¥à¤Ç¤Ï¡¤Å¾Á÷½èÍý¤Î½ÀÆðÀ­¤¬¥á¡¼¥ë ¥µ¡¼¥Ð¤ËÂФ¹¤ë¥æ¡¼¥¶¤Î¸¢¸Â¤Ëº¸±¦¤µ¤ì¤ë¡¥¤½¤³¤ÇËܹƤǤϡ¤¥á¡¼¥ë¥µ¡¼¥Ð¤ËÂФ¹¤ë¥æ¡¼¥¶¤Î¸¢¸Â¤Ë°Í¸ ¤»¤º¤Ë½ÀÆð¤ÊžÁ÷½èÍý¤ò¼Â¹Ô¤Ç¤­¡¤¤«¤Ä¥á¡¼¥ë¥µ¡¼¥Ð¤ÎÀßÄêÊѹ¹¤òɬÍפȤ·¤Ê¤¤¿·¤¿¤Ê¥á¡¼¥ëžÁ÷¥·¥¹¥Æ ¥à¤ò¡¤IMAP¡ÊInternet Message Access Protocol¡Ë¥¨¡¼¥¸¥§¥ó¥È¤Ë¤è¤Ã¤Æ¼Â¸½¤¹¤ë¡¥

8H-4 (»þ´Ö: 11:30 - 11:50)
Âê̾ID/LocatorʬΥ¤ÈLocatorʬ³ä¤Ë´ð¤Å¤¯¥Í¥Ã¥È¥ï¡¼¥¯¥¹¥é¥¤¥·¥ó¥°¤Ë¤ª¤±¤ëDiffserv¤Ë¤è¤ë»ñ¸»³ÖÎ¥
Ãø¼Ô*±Ê»³ ͵¿Í, ÅÏî´ Âçµ­ (·ÄØæµÁ½ÎÂç³ØÂç³Ø±¡Íý¹©³Ø¸¦µæ²Ê), »û²¬ ʸÃË (·ÄØæµÁ½ÎÂç³ØÍý¹©³ØÉô)
¥Ú¡¼¥¸pp. 1801 - 1810
¥­¡¼¥ï¡¼¥ÉIPv6, ID/LocatorʬΥ, Locatorʬ³ä, ¥Í¥Ã¥È¥ï¡¼¥¯¥¹¥é¥¤¥¹, Diffserv

8H-5 (»þ´Ö: 11:50 - 12:10)
Âê̾¥Í¥Ã¥È¥ï¡¼¥¯¥Ç¥Ð¥Ã¥¬¤ÎÄó°Æ
Ãø¼Ô*×¢Ãæ ñ¥, ¼ÄÅÄ ÍÛ°ì, ÃÎÇ° ¸­°ì, ±§Â¿ ¿Î (ËÌΦÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø)
¥Ú¡¼¥¸pp. 1811 - 1816
¥­¡¼¥ï¡¼¥É¥Í¥Ã¥È¥ï¡¼¥¯´ÉÍý, ¥È¥é¥Ö¥ë¥·¥å¡¼¥Æ¥£¥ó¥°, ²Ä»ë²½, ¾ðÊó¥·¥¹¥Æ¥à
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Æü»þ: 2019ǯ7·î4Æü(ÌÚ) 17:00 - 18:30
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DS-1
Âê̾IEEE 802.15.4 Backscatter ¤Î¼ÂÁõ¼Â¸³
Ãø¼Ô*ÌÚùõ °ì×¢, Àîºê »ü±Ñ, ±îÅÏ ½Ó²ð, ÅÏÊÕ ¾° (ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1817 - 1824
¥­¡¼¥ï¡¼¥ÉBacscatter, IEEE802.15.4, Zigbee
¥¢¥Ö¥¹¥È¥é¥¯¥ÈIoT (Internet of Things)¤ÎŸ³«¤Ë¤Ï¡¤Èù¾®¤Ê¾ÃÈñÅÅÎϤǡ¤ÌµÀþÅÅÎϵëÅŤ侮·¿¥Ü¥¿¥óÅÅÃӤθò´¹Ìµ¤·¤ÇÀ½Éʤμ÷Ì¿¤Þ¤ÇÆ°ºî¤¹¤ë¥Ç¥Ð¥¤¥¹¤¬É¬ÍפǤ¢¤ë¡¥½¾Íè¤ÎIEEE 802.15.4µ¬³Ê¤ò¼Â¸½¤¹¤ëÁ÷¿®²óÏ©¤Ï¡¤D/AÊÑ´¹´ï¡¤¶ÉÉôȯ¿®´ï¡¤Ä¾¸òÊÑ´¹´ï¡¤¥Ñ¥ï¡¼¥¢¥ó¥×¤Ç¹½À®¤µ¤ì¤Æ¤¤¤Æ¡¤¾ÃÈñÅÅÎϤϿô½½mW¤Ç¤¢¤Ã¤¿¡¥BackscatterÊý¼°¤ÎÁ÷¿®²óÏ©¤Ï¡¤SPDT¥¹¥¤¥Ã¥ÁÁÇ»Ò1¸Ä¤ÈÄñ¹³¡¤¥³¥ó¥Ç¥ó¥µ¤Ç¹½À®¤µ¤ì¤Æ¤¤¤Æ¡¤¿ô½½¦ÌW¤Î¾ÃÈñÅÅÎϤÇÆ°ºî¤¹¤ë¡¥ËܹƤǤϡ¤Ê¸¸¥[1]¤ò»²¹Í¤ËIEEE 802.15.4µ¬³Ê¤ÎBackscatterÊý¼°¤ÎÁ÷¿®²óÏ©¤òÀ߷ס¦À½ºî¤·¤Æ¼Â¸³¤ò¹Ô¤Ã¤¿·ë²Ì¡¤µ÷Î¥3.5m°Ê¾å¤Þ¤ÇÄÌ¿®²Äǽ¤Ê¤³¤È¤¬³Îǧ¤Ç¤­¤¿¡¥

DS-2
Âê̾¥¹¥Þ¡¼¥È¥Õ¥©¥ó¥¢¥×¥ê¤Ë¤ª¤±¤ëÍ׵Ḣ¸Â¤Î²Ä»ë²½¤ÎÄó°Æ
Ãø¼Ô*¶â¿ù ÍÎ (ÅìµþÂç³Ø¶õ´Ö¾ðÊó²Ê³Ø¸¦µæ¥»¥ó¥¿¡¼), ¾¾¸¶ ¹ä (ÅìµþÂç³ØÃϵå´Ñ¬¥Ç¡¼¥¿ÅýÍ»¹çÏ¢·È¸¦µæµ¡¹½), ¼Æºê μ²ð (ÅìµþÂç³Ø¶õ´Ö¾ðÊó²Ê³Ø¸¦µæ¥»¥ó¥¿¡¼)
¥Ú¡¼¥¸pp. 1825 - 1828
¥­¡¼¥ï¡¼¥É¥Ñ¡¼¥½¥Ê¥ë¥Ç¡¼¥¿, ¥¹¥Þ¥Û¥¢¥×¥ê, Ʊ°Õ¼èÆÀ

Ìî¸ý¾Þ(Í¥½¨¥Ç¥â¥ó¥¹¥È¥ì¡¼¥·¥ç¥ó¾Þ)/ Noguchi Awards
DS-3
Âê̾²£Ê⤭¤ä¸åÂà¤ËÂбþ¤Ç¤­¤ëPDR¥¹¥Þ¥Û¥¢¥×¥ê
Ãø¼Ô¶â»Ò ²íμ (°¦Ã驶ÈÂç³Ø¾ðÊó²Ê³ØÉô¾ðÊó²Ê³Ø²Ê), °ËÆ£ ¿®¹Ô (»°É©Åŵ¡¥¨¥ó¥¸¥Ë¥¢¥ê¥ó¥°³ô¼°²ñ¼Ò), ÆâÆ£ ¹î¹À, ÃæÛê ľÌé, ¿åÌî Ãé§, *³á ¹îɧ (°¦Ã驶ÈÂç³Ø¾ðÊó²Ê³ØÉô¾ðÊó²Ê³Ø²Ê)
¥Ú¡¼¥¸pp. 1829 - 1836
¥­¡¼¥ï¡¼¥ÉPDR, °ÌÃÖ¿äÄê, ¥¹¥Þ¡¼¥È¥Õ¥©¥ó¥¢¥×¥ê
¥¢¥Ö¥¹¥È¥é¥¯¥È²°Æâ°ÌÃÖ¿äÄê¼êË¡¤ÏÍÍ¡¹¤Ê¸¦µæ¤¬¹Ô¤ï¤ì¤Æ¤¤¤ë¤¬¡¤¤½¤ÎÃæ¤Ç¤âÍ­ÎϤʲ°Æâ°ÌÃÖ¿äÄê¼êË¡¤È¤·¤ÆPDR ¤¬µó¤²¤é¤ì¤ë¡¥¤·¤«¤·¡¤°ìÈÌŪ¤ÊPDR ¤Ç¤Ï¿Ê¹ÔÊý¸þ¤ò³Ñ®ÅÙ¥»¥ó¥µ¤ÎÃͤ«¤éµá¤á¤Æ¤¤¤ë¤¿¤á²£Ê⤭¤ä¸å Âà¤Ê¤É¤Î³Ñ®ÅÙ¤ÎÃͤ¬ÊѲ½¤·¤Ê¤¤¹ÔÆ°¤Î¿äÄ꤬º¤Æñ¤Ç¤¢¤ë¡¥²æ¡¹¤Ï¤³¤ÎÌäÂê¤ò²ò·è¤¹¤ë¤¿¤á¡¤²Ã®ÅÙÊ¿ÌÌ À®Ê¬¤òÍѤ¤¤Æ1 Ê⤴¤È¤Î¿Ê¹ÔÊý¸þ¤ò¿äÄꤹ¤ë¼êË¡¤òÄó°Æ¤·¤¿¡¥¤³¤Î¸¦µæ¤Ë¤è¤Ã¤Æ³Ñ®ÅÙ¤ÎÃͤÎÊѲ½¤·¤Ê¤¤ ¹ÔÆ°¤â¿äÄê¤Ç¤­¤ë¤è¤¦¤Ë¤Ê¤Ã¤¿¤¬¡¤Ä¾¿Ê»þ¤Ë¿äÄêµ°Àפ¬¥¸¥°¥¶¥°¤Ë¤Ê¤Ã¤Æ¤·¤Þ¤¦ÌäÂ꤬¤¢¤Ã¤¿¡¥µ°Àפ¬¥¸ ¥°¥¶¥°¤Ë¤Ê¤ë¼ç¤ÊÍýͳ¤Ï¹ø¤Î²óž¤¬¹Í褵¤ì¤Æ¤¤¤Ê¤¤ÅÀ¤Ë¤è¤ë¤â¤Î¤Ç¤¢¤ë¡¥¤½¤³¤ÇËܸ¦µæ¤Ç¤Ï¡¤²Ã®ÅÙÊ¿ ÌÌÀ®Ê¬¤Ë²Ã¤¨¤Æ³Ñ®ÅÙÊ¿ÌÌÀ®Ê¬¤òÊ»ÍѤ·¡¤¹ø²óž¤Î¥­¥ã¥ó¥»¥ë¤Ë¤è¤Ã¤Æ1 Ê⤴¤È¤Î¿Ê¹ÔÊý¸þ¿äÄê¤ò¹âÀºÅÙ ²½¤¹¤ë¡¥Àè¹Ô¸¦µæ¤Î¼êË¡¤Ç¿äÄꤷ¤¿¿Ê¹ÔÊý¸þ¤ÈÈæ³Ó¤·³ÑÅÙ¤Î¸íº¹¤òµá¤á¡¤ÀºÅÙɾ²Á¤ò¹Ô¤Ã¤¿¡¥¤½¤Î·ë²Ì¡¤ Àè¹Ô¸¦µæ¤Î¼êË¡¤ÏÊ¿¶ÑÌó14.2¡ë¡¤Ëܸ¦µæ¤Î¼êË¡¤ÏÊ¿¶ÑÌó9.1¡ë ¤Î¸íº¹¤È¤Ê¤ê¡¤Ê¿¶ÑÌó5.1¡ë ¤ÎÀºÅÙ¸þ¾å¤ò ³Îǧ¤·¤¿¡¥¤Þ¤¿¡¤Äó°Æ¼êË¡¤ò¥ê¥¢¥ë¥¿¥¤¥à½èÍý¤ËÂбþ¤µ¤»¡¤Android ¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤È¤·¤Æ¼ÂÁõ¤·¤¿¡¥

Ìî¸ý¾Þ(Í¥½¨¥Ç¥â¥ó¥¹¥È¥ì¡¼¥·¥ç¥ó¾Þ)/ Noguchi Awards
DS-4
Âê̾ARIA: ¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¡¦¥¨¥ß¥å¥ì¡¼¥·¥ç¥óÏ¢·È´ðÈפòÍøÍѤ·¤¿¥¤¥ó¥¿¥é¥¯¥Æ¥£¥Ö¤ÊÅÔ»Ô·¿¿å³²¤ÎÈﳲͽ¬¥·¥¹¥Æ¥à
Ãø¼Ô*×¢°æ ·Å (̾¸Å²°Âç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), °æ¾å ÊþºÈ, ÌÀÀÐ Ë®É×, Åò¼ Íã (¾ðÊóÄÌ¿®¸¦µæµ¡¹½ËÌΦStarBEDµ»½Ñ¥»¥ó¥¿¡¼), ×¢Ãæ ñ¥, ¿ûÌî Íο® (ËÌΦÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø), µÜÃÏ Íø¹¬ (¾ðÊóÄÌ¿®¸¦µæµ¡¹½ËÌΦStarBEDµ»½Ñ¥»¥ó¥¿¡¼), ¼ÄÅÄ ÍÛ°ì (ËÌΦÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø)
¥Ú¡¼¥¸pp. 1837 - 1845
¥­¡¼¥ï¡¼¥É¥·¥ß¥å¥ì¡¼¥·¥ç¥óÏ¢·È, ¿å³², ¥Þ¥ë¥Á¥¨¡¼¥¸¥§¥ó¥È¥·¥ß¥å¥ì¡¼¥·¥ç¥ó
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Ìî¸ý¾Þ(Í¥½¨¥Ç¥â¥ó¥¹¥È¥ì¡¼¥·¥ç¥ó¾Þ)/ Noguchi Awards
DS-5
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Ãø¼Ô*±ö¸« Í´ºÈ (ÀŲ¬Âç³Ø ¾ðÊó³ØÉô¾ðÊó²Ê³Ø²Ê), ¿ùËÜ ¸µµ±, ¿ùËÜ ºÌ²Î, ¾å¸¶ ¹ÒÂÁ, Æ£ÅÄ ¿¿¹À, âÃÌî ͦ¿Í (ÀŲ¬Âç³ØÂç³Ø±¡ Áí¹ç²Ê³Øµ»½Ñ¸¦µæ²Ê), ÂçÌÚ Å¯»Ë, À¾³À Àµ¾¡ (ÀŲ¬Âç³Ø)
¥Ú¡¼¥¸pp. 1846 - 1851
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DS-6
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Ãø¼Ô*°ËÆ£ ΤºÚ, ¿åÌî ¿µ»Î (°¦Ã驶ÈÂç³Ø)
¥Ú¡¼¥¸pp. 1852 - 1856
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DS-7
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Ãø¼Ô*µÈÀî ¹Ò´ø, ¿åÌî ¿µ»Î (°¦Ã驶ÈÂç³ØÂç³Ø±¡·Ð±Ä¾ðÊó²Ê³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1857 - 1862
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DS-8
Âê̾¥Ò¥È¥ê¥¹¡§·ò¹¯Â¥¿Ê¤òÌÜŪ¤È¤·¤ÆÂΤÈƬ¤òÊ£¹çŪ¤Ë»È¤ï¤»¤ë¥¤¥ó¥¿¥é¥¯¥Æ¥£¥Ö¥²¡¼¥à
Ãø¼Ô*ÂçÀ¾ °¾Èþ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê), ÌøÀ¸ ÍÚ, ÀçÇÈ Âó (¿À¸ÍÂç³Ø¹©³ØÉô), »ûÅÄ ÅØ, ÄÍËÜ ¾»É§ (¿À¸ÍÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê)
¥Ú¡¼¥¸pp. 1863 - 1870
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KS-1
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¥Ú¡¼¥¸p. 1871
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SP-1 (»þ´Ö: 15:50 - 16:50)
Âê̾(ÆÃÊֱ̹é) µðÂç²½¤¹¤ë¼«Á³ºÒ³²¤È·Ú¸º¤Ø¤ÎÀïά ¡¼ÅìÆüËÜÂç¿ÌºÒ¤äÆ¥È¥é¥ÕÃϿ̤ʤɤò»öÎã¤Ë
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¥Ú¡¼¥¸pp. 1872 - 1873
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