{"id":5212,"date":"2022-11-02T20:04:09","date_gmt":"2022-11-02T11:04:09","guid":{"rendered":"https:\/\/orsj.org\/?page_id=5212"},"modified":"2022-11-03T10:53:02","modified_gmt":"2022-11-03T01:53:02","slug":"2022%e5%b9%b4%e7%a7%8b%e5%ad%a3%e7%a0%94%e7%a9%b6%e7%99%ba%e8%a1%a8%e4%bc%9a%e3%82%a2%e3%83%96%e3%82%b9%e3%83%88%e3%83%a9%e3%82%af%e3%83%88","status":"publish","type":"page","link":"https:\/\/orsj.org\/nc2022f-abstract","title":{"rendered":"2022\u5e74\u79cb\u5b63\u7814\u7a76\u767a\u8868\u4f1a\u30a2\u30d6\u30b9\u30c8\u30e9\u30af\u30c8"},"content":{"rendered":"

\u516c\u958b\u306b\u540c\u610f\u3044\u305f\u3060\u3044\u305f\u65b9\u306e\u30a2\u30d6\u30b9\u30c8\u30e9\u30af\u30c8\u3092\u63b2\u8f09\u3057\u3066\u304a\u308a\u307e\u3059\u3002<\/p>\n

\uff11\u65e5\u76ee (2022\/9\/13)<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n <\/tbody>\n<\/table>\n<\/figure>\n

\u3000<\/p>\n

\uff12\u65e5\u76ee (2022\/9\/14)<\/p>\n

\n
1-A-1<\/td>\n\u30d1\u30b9\u306em\u6700\u9069\u307a\u30d6\u30ea\u30f3\u30b0\u6570<\/a>
\n\u753a\u7530 \u8ad2\uff08\u4e5d\u5dde\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-A-2<\/td>\n\u30e2\u30b8\u30e5\u30e9\u30ea\u30c6\u30a3\u5bc6\u5ea6\u6700\u5927\u5316\u306b\u5bfe\u3059\u308b\u9ad8\u901f\u306a\u5217\u751f\u6210\u6cd5\u306e\u8a2d\u8a08\u3068\u8a08\u7b97\u56f0\u96e3\u6027\u306e\u89e3\u6790<\/a>
\n\u52a9\u7530 \u4e00\u665f\uff08\u6771\u4eac\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-A-3<\/td>\n\u8fba\u306e\u9577\u3055\u304c\u64ec\u9806\u5e8f\u96c6\u5408\u306e\u8981\u7d20\u3067\u4e0e\u3048\u3089\u308c\u305f\u6700\u77ed\u7d4c\u8def\u554f\u984c<\/a>
\n\u91d1 \u6b63\u9053\uff08\u5f18\u524d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-A-4<\/td>\n\u518d\u751f\u53ef\u80fd\u30a8\u30cd\u30eb\u30ae\u30fc\u306e\u6d3b\u7528\u306b\u5411\u3051\u305f\u5b85\u914d\u96fb\u6c17\u30c8\u30e9\u30c3\u30af\u306e\u5145\u96fb\u30b9\u30c6\u30fc\u30b7\u30e7\u30f3\u306e\u6700\u9069\u914d\u7f6e<\/a>
\n\u690d\u7530 \u548c\u6a39\uff08\u5927\u962a\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-A-5<\/td>\n\u96fb\u67f1\u6cbf\u9053\u5bc6\u5ea6\u306e\u5730\u57df\u5225\u9053\u8def\u7a2e\u5225\u6bd4\u8f03<\/a>
\n\u6b27\u967d \u541b\u9854\uff08\u7b51\u6ce2\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-A-6<\/td>\n\u591a\u5909\u91cf\u89e3\u6790\u306e\u9069\u7528\u306b\u3088\u308b\u8ecc\u9053\u5909\u4f4d\u7570\u5e38\u7b87\u6240\u691c\u77e5\u306e\u52b9\u7387\u5316\u3068\u691c\u8a3c<\/a>
\n\u677e\u672c \u9ebb\u7f8e\uff08\uff08\u516c\u8ca1\uff09\u9244\u9053\u7dcf\u5408\u6280\u8853\u7814\u7a76\u6240\uff09<\/p>\n<\/tr>\n
1-A-7<\/td>\nDX\u306b\u5f79\u7acb\u3064LocalSolver11.0<\/a>
\n\u5bae\u5d0e \u77e5\u660e\uff08MSI\u682a\u5f0f\u4f1a\u793e\uff09<\/p>\n<\/tr>\n
1-A-8<\/td>\nQ&A\u30b5\u30a4\u30c8\u3067\u306e\u95b2\u89a7\u8005\u306e\u56de\u7b54\u78ba\u7387\u4e88\u6e2c\u3068\u30aa\u30f3\u30e9\u30a4\u30f3\u8cea\u554f\u63a8\u85a6<\/a>
\n\u661f\u91ce \u96c4\u6bc5\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
1-B-1<\/td>\n\u4e0d\u53ef\u5206\u8ca1\u306b\u5bfe\u3059\u308b\u8fd1\u4f3c\u7684\u306a\u6bd4\u4f8b\u914d\u5206\u306e\u5b58\u5728\u6027<\/a>
\n\u99ac\u539f \u51cc\u6cb3\uff08\u4eac\u90fd\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-B-2<\/td>\n\u968e\u5c64\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u6700\u9069\u5316\u554f\u984c\u306b\u5bfe\u3059\u308b\u5c40\u6240\u63a2\u7d22\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/a>
\n\u8fbb\u5ddd \u4f91\u99ac\uff08\u9759\u5ca1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-B-3<\/td>\n\u30a2\u30c9\u30ef\u30fc\u30ba\u554f\u984c\u306b\u5bfe\u3059\u308b\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/a>
\n\u68ee\u5c71 \u4f0a\u7e54\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-B-4<\/td>\n\u8d85\u5b89\u5b9a\u30c6\u30f3\u30bb\u30b0\u30ea\u30c6\u30a3\u306e\u30b0\u30e9\u30d5\u306e\u7279\u5fb4\u3065\u3051
\n \u8c37\u5ddd \u771e\u4e00\uff08\u6771\u4eac\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-B-5<\/td>\n\u79fb\u52d5\u6642\u9593\u3068\u5bb9\u91cf\u304c\u4e00\u5b9a\u3067\u3042\u308b\u8fba\u3092\u6301\u3064\u53cc\u65b9\u5411\u30b0\u30ea\u30c3\u30c9\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u304a\u3051\u308b\u6700\u901f\u907f\u96e3\u554f\u984c<\/a>
\n\u6238\u570b \u53cb\u8cb4\uff08\u5175\u5eab\u770c\u7acb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-B-6<\/td>\n\u5229\u5f97\u884c\u5217\u304c\u5236\u9650\u3055\u308c\u305f2\u4eba\u30b2\u30fc\u30e0\u4e0a\u306e\u4e00\u69d8Nash\u5747\u8861\u306e\u8a08\u7b97\u56f0\u96e3\u6027
\n \u77f3\u585a \u5929\uff08\u4e5d\u5dde\u5927\u5b66\u5927\u5b66\u9662 \u6570\u7406\u5b66\u5e9c\uff09<\/p>\n<\/tr>\n
1-B-7<\/td>\n\u30aa\u30f3\u30e9\u30a4\u30f3\u30ca\u30c3\u30d7\u30b5\u30c3\u30af\u554f\u984c\u306b\u5bfe\u3059\u308b\u6700\u5c0f\u63a1\u629e\u78ba\u7387\u6700\u5927\u5316<\/a>
\n\u5584\u6c38 \u5fb9\uff08\u6771\u4eac\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-B-8<\/td>\n\u30b8\u30e3\u30f3\u30d7\u30b7\u30b9\u30c6\u30e0\u304a\u3088\u3073\u30c7\u30eb\u30bf\u30de\u30c8\u30ed\u30a4\u30c9\u4e0a\u306e\u6700\u9069\u5316\u554f\u984c\u306b\u5bfe\u3059\u308b\u6e2c\u5730\u7dda\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u69cb\u7bc9<\/a>
\n\u5357\u5ddd \u667a\u90fd\uff08\u6771\u4eac\u90fd\u7acb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-B-9<\/td>\nL2\u51f8\u96c6\u5408\u306e\u591a\u9762\u4f53\u8868\u73fe<\/a>
\n\u68ee\u53e3 \u8061\u5b50\uff08\u6771\u4eac\u90fd\u7acb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
1-C-1<\/td>\nDEA-BSC\u7d71\u5408\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f \u300c\u8907\u6570\u4e8b\u696d\u4f53\u3092\u6301\u3064\u4f01\u696d\u306e\u7d4c\u55b6\u8ab2\u984c\u89e3\u6c7a\u300d\u3078\u306e\u5fdc\u7528<\/a>
\n\u5e73\u7530 \u4e00\u90ce\uff08\u5175\u5eab\u770c\u7acb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-C-2<\/td>\nAn approximate method for large-scale DEA problem<\/a>
\nZhuang Qianwei\uff08Osaka University\uff09<\/p>\n<\/tr>\n
1-C-3<\/td>\nData envelopment analysis\u306b\u3088\u308b\u30aa\u30d5\u30a3\u30b9\u30d3\u30eb\u7a7a\u8abf\u904b\u7528\u6539\u5584<\/a>
\n\u68ee\u9cf0 \u6b66\u53f2\uff08\u5927\u962a\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-C-4<\/td>\n\u30d7\u30ed\u30b7\u30e5\u30fc\u30de\u30fc\u306e\u6295\u8cc7\u610f\u601d\u6c7a\u5b9a-\u30ea\u30a2\u30eb\u30aa\u30d7\u30b7\u30e7\u30f3\u30fb\u30a2\u30d7\u30ed\u30fc\u30c1-<\/a>
\n\u6851\u539f \u5927\u6a39\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\u5927\u5b66\u9662\uff09<\/p>\n<\/tr>\n
1-C-5<\/td>\nA well-defined extended production possibility set and strongly monotonic efficiency measures<\/a>
\n\u95a2\u8c37 \u548c\u4e4b\uff08\u6210\u8e4a\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-C-6<\/td>\n\u7570\u306a\u308b\u65bd\u7b56\u4e0b\u306b\u3042\u308b\u4e8b\u696d\u3092\u76f8\u5bfe\u8a55\u4fa1\u3059\u308b\u305f\u3081\u306e\u968e\u5c64\u5206\u6790\u6cd5\u306e\u67a0\u7d44\u307f<\/a>
\n\u98ef\u7530 \u6d0b\u5e02\uff08\u516c\u7acb\u8acf\u8a2a\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-C-7<\/td>\n\u640d\u5931\u304c\u8ca1\u914d\u5206\u306b\u4e0e\u3048\u308b\u5f71\u97ff \u2014 \u7d4c\u6e08\u5b9f\u9a13\u306b\u3088\u308b\u691c\u8a3c<\/a>
\n\u798f\u7530 \u6075\u7f8e\u5b50\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-C-8<\/td>\nSystemic Risk and Short-Term Financial Networks<\/a>
\nFu Jing\uff08Fukuoka Institute of Technology\uff09<\/p>\n<\/tr>\n
1-C-9<\/td>\nEx Ante User Equilibrium of Capacitated Networks<\/a>
\n\u5897\u7530 \u9756\uff08\u6176\u61c9\u7fa9\u587e\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
1-D-1<\/td>\n\u6559\u80b2\u30ed\u30fc\u30f3\u5411\u3051\u5be9\u67fb\u30e2\u30c7\u30eb\u306e\u9ad8\u5ea6\u5316<\/a>
\n\u6238\u57ce \u6b63\u6d69\uff08\uff08\u682a\uff09\u65e5\u672c\u653f\u7b56\u91d1\u878d\u516c\u5eab\uff09<\/p>\n<\/tr>\n
1-D-2<\/td>\nIntegrated Gradients\u306b\u3088\u308b\u683c\u4ed8AR\u5024\u5909\u5316\u306e\u5bc4\u4e0e\u5ea6\u5206\u89e3<\/a>
\n\u6728\u6751 \u548c\u592e\uff08\u682a\u5f0f\u4f1a\u793e\u65e5\u7d4c\u91d1\u878d\u5de5\u5b66\u7814\u7a76\u6240\uff09<\/p>\n<\/tr>\n
1-D-3<\/td>\n\u30a8\u30f3\u30c8\u30ed\u30d4\u30fc\u3068\u5909\u52d5\u4fc2\u6570\u6bd4\u6700\u5927\u5316\u306b\u3088\u308b \u30dd\u30fc\u30c8\u30d5\u30a9\u30ea\u30aa\u554f\u984c\u306e\u4e00\u89e3\u6cd5
\n \u91d1\u5ddd \u660e\u5f18\uff08\u5ca1\u5c71\u770c\u7acb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-D-4<\/td>\n\u4e00\u822c\u72b6\u614b\u7a7a\u9593\u30e2\u30c7\u30eb\u3092\u6d3b\u7528\u3057\u305fMean-Variance\u30dd\u30fc\u30c8\u30d5\u30a9\u30ea\u30aa<\/a>
\n\u7530\u4e2d \u84ee\uff08\u660e\u6cbb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-D-5<\/td>\nCVaR\u30ec\u30b7\u30aa\u6700\u5927\u5316\u306b\u57fa\u3065\u304f\u5206\u5e03\u7684\u30ed\u30d0\u30b9\u30c8\u30dd\u30fc\u30c8\u30d5\u30a9\u30ea\u30aa\u9078\u629e\u554f\u984c\u306b\u3064\u3044\u3066<\/a>
\n\u8d64\u6cbc \u967d\u592a\u90ce\uff08\u6176\u61c9\u7fa9\u587e\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-D-6<\/td>\n\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u9593\u306e\u985e\u4f3c\u5c3a\u5ea6\u3092\u7528\u3044\u305f\u696d\u7a2e\u533a\u5206\u306e\u518d\u7de8\u3068\u30ea\u30b9\u30af\u30b3\u30f3\u30c8\u30ed\u30fc\u30eb<\/a>
\n\u9577\u5cf6 \u6689\uff08\u660e\u6cbb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-D-7<\/td>\n\u30da\u30a2\u30c8\u30ec\u30fc\u30c7\u30a3\u30f3\u30b0\u306b\u3088\u308b\u53ce\u76ca\u7372\u5f97\u53ef\u80fd\u6027\u306e\u8a55\u4fa1<\/a>
\n\u6797 \u826f\u8f14\uff08\u660e\u6cbb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-D-8<\/td>\nOptimal default decision with an upper reflecting barrier<\/a>
\n\u829d\u7530 \u9686\u5fd7\uff08\u6771\u4eac\u90fd\u7acb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
1-E-1<\/td>\nBCMP \u5f85\u3061\u884c\u5217\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u305f\u6700\u9069\u62e0\u70b9\u914d\u7f6e\u306b\u304a\u3051\u308b\u8a08\u7b97\u52b9\u7387\u5316<\/a>
\n\u91ce\u5d5c \u771f\u7531\u5b50\uff08\u9759\u5ca1\u7406\u5de5\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-E-2<\/td>\n\u5272\u308a\u8fbc\u307f\u3092\u8003\u616e\u3057\u305fErlang B\u30e2\u30c7\u30eb\u306e\u6f38\u8fd1\u89e3\u6790<\/a>
\n\u5b89\u90e8 \u548c\u771f\uff08\u7b51\u6ce2\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-E-3<\/td>\n\u5fcd\u8010\u6642\u9593\u4ed8\u304d\u78ba\u7387\u7684\u30de\u30c3\u30c1\u30f3\u30b0\u30e2\u30c7\u30eb\u306e\u89e3\u6790<\/a>
\n\u963f\u90e8 \u5bdb\u4eba\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-E-4<\/td>\nA Fast DC Algorithm for a Unified Class of Convexity-Preserving Sparse Regularizers<\/a>
\n\u5f35 \u6bc5\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-E-5<\/td>\n\u8907\u6570\u306e\u60c5\u5831\u30bd\u30fc\u30b9\u3092\u3082\u3064\u30d6\u30ed\u30c3\u30ad\u30f3\u30b0\u30b5\u30fc\u30d0\u306b\u304a\u3051\u308bAge of Information\u306e\u540c\u6642\u5206\u5e03\u89e3\u6790<\/a>
\n\u5c0f\u91ce\u5bfa \u5927\u6bc5\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-E-6<\/td>\n\u8cb4\u91d1\u5c5e\u6bd4\u306e\u985e\u4f3c\u6bd4\u306b\u3088\u308b\u30c6\u30aa\u30c9\u30ed\u30b9\u306e\u87ba\u65cb\u3084\u7b49\u89d2\u87ba\u65cb\u306e\u82b8\u8853\u7684\uff06\u5e7e\u4f55\u5b66\u7684\u518d\u8003<\/a>
\n\u4e2d\u897f \u771f\u609f\uff08\u5927\u962a\u5de5\u696d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-E-7<\/td>\n\u707d\u5bb3\u6642\u306e\u914d\u9001\u8a08\u753b\u306b\u95a2\u3059\u308b\u7591\u4f3c\u91cf\u5b50\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u306e\u6709\u52b9\u6027<\/a>
\n\u9ad8\u6a4b \u4f73\u6b69\uff08\u682a\u5f0f\u4f1a\u793e\u65e5\u7acb\u88fd\u4f5c\u6240\uff09<\/p>\n<\/tr>\n
1-E-8<\/td>\n\u6d25\u6ce2\u6d78\u6c34\u60c5\u5831\u3092\u7528\u3044\u305f\u907f\u96e3\u7d4c\u8def\u751f\u6210\u74b0\u5883\u306e\u69cb\u7bc9<\/a>
\n\u77f3\u4e95 \u660e\u65e5\u9999\uff08\u9752\u5c71\u5b66\u9662\u5927\u5b66\uff09<\/p>\n<\/tr>\n
1-E-9<\/td>\nIoT\u30bb\u30f3\u30b5\u88c5\u7f6e\u3092\u7528\u3044\u305f\u9053\u8def\u6cbf\u7dda\u659c\u9762\u7b49\u306e\u9632\u707d\u7ba1\u7406\u624b\u6cd5\u306e\u63d0\u6848<\/a>
\n\u524d\u5ddd \u6d69\u57fa\uff08\u5175\u5eab\u770c\u7acb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
1-F-1<\/td>\n\u6771\u65e5\u672c\u5927\u9707\u707d\u306b\u304a\u3051\u308b\u907f\u96e3\u884c\u52d5\u3068\u8a8d\u77e5\u6a5f\u80fd\u306e\u5f71\u97ff<\/a>
\n\u9db4\u5cf6 \u5f70\uff08\u30bb\u30b3\u30e0\u682a\u5f0f\u4f1a\u793e\uff09<\/p>\n<\/tr>\n
1-F-2<\/td>\n\u640d\u5bb3\u4fdd\u967a\u4f1a\u793e\u306b\u304a\u3051\u308b\u5efa\u8a2d\u73fe\u5834\u306eDX\u306b\u5411\u3051\u305f\u4e8b\u4f8b<\/a>
\n\u6728\u6751 \u82f1\u667a\uff08\u6771\u4eac\u6d77\u4e0a\u65e5\u52d5\u30b7\u30b9\u30c6\u30e0\u30ba\u682a\u5f0f\u4f1a\u793e\uff09<\/p>\n<\/tr>\n
1-F-3<\/td>\n\u30ed\u30d0\u30b9\u30c8\u6700\u9069\u5316\u306b\u3088\u308b\u518d\u30a8\u30cd\u6291\u5236\u3068\u516c\u5e73\u6027\u3092\u8003\u616e\u3057\u305f\u767a\u96fb\u8a08\u753b<\/a>
\n\u8c4a\u5d8b \u4f0a\u77e5\u90ce\uff08\u6771\u829d\u30a8\u30cd\u30eb\u30ae\u30fc\u30b7\u30b9\u30c6\u30e0\u30ba\uff09<\/p>\n<\/tr>\n
1-F-4<\/td>\n\u5bfe\u6d41\u570f\u30a6\u30a3\u30f3\u30c9\u30d7\u30ed\u30d5\u30a1\u30a4\u30e9\u306e\u958b\u767a\u3068\u6c17\u8c61\u89b3\u6e2c\u3067\u306e\u5b9f\u7528\u5316<\/a>
\n\u677e\u7530 \u77e5\u4e5f\uff08\u4e09\u83f1\u96fb\u6a5f\u682a\u5f0f\u4f1a\u793e\uff09<\/p>\n<\/tr>\n
1-F-5<\/td>\n\u9700\u7d66\u8a08\u753b\u30b7\u30b9\u30c6\u30e0\u5c0e\u5165\u306b\u3088\u308b\u8ab2\u984c\u89e3\u6c7a\u4e8b\u4f8b \u98df\u54c1\u696d\u754c\u3092\u4e2d\u5fc3\u306b<\/a>
\n\u591a\u30f6\u8c37 \u6709\uff08\u30ad\u30e4\u30ce\u30f3IT\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30ba\u682a\u5f0f\u4f1a\u793e\uff09<\/p>\n<\/tr>\n
1-F-6<\/td>\n\u88fd\u9020\u6d41\u901a\u696d\u306b\u304a\u3051\u308b\u9069\u6b63\u5728\u5eab\u81ea\u52d5\u8abf\u6574\u65b9\u5f0f\u306e\u958b\u767a\u3068\u305d\u306e\u9069\u7528<\/a>
\n\u5c0f\u6797 \u88d5\u5f81\uff08\u682a\u5f0f\u4f1a\u793e\u65e5\u7acb\u88fd\u4f5c\u6240\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
2-A-1<\/td>\n\u5168\u52fe\u914d\u3092\u7528\u3044\u306a\u3044\u52fe\u914d\u63a8\u5b9a\u91cf: 1\u6b21\u53ca\u30732\u6b21\u306e\u6700\u9069\u6027\u3068\u9023\u5408\u5b66\u7fd2<\/a>
\n\u5927\u53e4 \u4e00\u8061\uff08\u6771\u4eac\u5927\u5b66 \/ \u7406\u7814 AIP\uff09<\/p>\n<\/tr>\n
2-A-2<\/td>\nRandomized subspace regularized Newton method for unconstrained non-convex optimization<\/a>
\nPoirion Pierre-Louis\uff08RIKEN-AIP\uff09<\/p>\n<\/tr>\n
2-A-3<\/td>\n2\u6bb5\u968e\u5206\u5e03\u7684\u30ed\u30d0\u30b9\u30c8\u78ba\u7387\u975e\u5354\u529b\u30b2\u30fc\u30e0\u306b\u304a\u3051\u308b\u5747\u8861\u89e3\u306e\u5b58\u5728\u6027\u3068\u30af\u30fc\u30eb\u30ce\u30fc\u7af6\u4e89\u3078\u306e\u5fdc\u7528<\/a>
\n\u5800 \u7be4\u53f2\uff08\u4eac\u90fd\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-A-4<\/td>\n\u4e00\u822c\u5316Cayley\u5909\u63db\u306b\u3088\u308b\u52d5\u7684\u30d1\u30e9\u30e1\u30fc\u30bf\u8868\u73fe\u6cd5\u306b\u57fa\u3065\u304f\u76f4\u4ea4\u5236\u7d04\u4ed8\u304d\u6700\u9069\u5316\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u305f\u3081\u306e\u7d71\u4e00\u7684\u53ce\u675f\u89e3\u6790<\/a>
\n\u4e45\u7c73 \u5553\u592a\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-A-5<\/td>\n\u6700\u9069\u6c7a\u5b9a\u6728\u3092\u7528\u3044\u305f\u51e6\u65b9\u7684\u4fa1\u683c\u6700\u9069\u5316<\/a>
\n\u6c60\u7530 \u6625\u4e4b\u4ecb\uff08\u682a\u5f0f\u4f1a\u793e\u30ea\u30af\u30eb\u30fc\u30c8\uff09<\/p>\n<\/tr>\n
2-A-6<\/td>\nOn the Global Convergence of Riemannian Interior Point Method<\/a>
\n\u983c \u5fd7\u5805\uff08\u7b51\u6ce2\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-A-7<\/td>\n\u53cc\u66f2\u9310\u3078\u306e\u5c04\u5f71\u8a08\u7b97<\/a>
\n\u6c38\u91ce \u9686\u4e4b\uff08\u6771\u4eac\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-A-8<\/td>\nLevenberg\u2013Marquardt\u6cd5\u306e\u30ea\u30fc\u30de\u30f3\u591a\u69d8\u4f53\u3078\u306e\u62e1\u5f35\u3068\u5927\u57df\u53ca\u3073\u5c40\u6240\u7684\u53ce\u675f\u6027\u89e3\u6790<\/a>
\n\u8db3\u7acb \u52dd\uff08\u6771\u4eac\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-A-9<\/td>\nRevisiting Superlinear Convergence of Proximal Semismooth Newton Methods to Degenerate Solutions<\/a>
\nLee Ching-pei\uff08Academia Sinica\uff09<\/p>\n<\/tr>\n
2-A-10<\/td>\n\u91cd\u307f\u4ed8\u304d\u96c6\u5408\u95a2\u4fc2\u306e\u9806\u5e8f\u69cb\u9020\u306b\u3064\u3044\u3066<\/a>
\n\u8352\u8c37 \u6d0b\u8f14\uff08\u79cb\u7530\u770c\u7acb\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-A-11<\/td>\n\u6a19\u6e96DC 2 \u6b21\u8a08\u753b\u554f\u984c\u306b\u5bfe\u3059\u308bKKT\u5217\u6319\u6cd5\u3092\u5c0e\u5165\u3057\u305f\u5206\u679d\u9650\u5b9a\u6cd5<\/a>
\n\u5c71\u7530 \u4fee\u53f8\uff08\u65b0\u6f5f\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
2-B-1<\/td>\n\u7d44\u5408\u305b\u9077\u79fb\u3078\u306e\u62db\u5f85<\/a>
\n\u4f0a\u85e4 \u5065\u6d0b\uff08\u6771\u5317\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-2<\/td>\nZDD\u3092\u7528\u3044\u305f\u7d44\u5408\u305b\u9077\u79fb\u30bd\u30eb\u30d0\u30fc<\/a>
\n\u5ddd\u539f \u7d14\uff08\u4eac\u90fd\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-3<\/td>\n\u6b63\u5247\u8a98\u5c0e\u90e8\u5206\u30b0\u30e9\u30d5\u9077\u79fb\u554f\u984c\u306e\u8a08\u7b97\u8907\u96d1\u3055<\/a>
\n\u6c5f\u85e4 \u5b8f\uff08\u6771\u5317\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-4<\/td>\n\u7403\u9762\u306e\u4e09\u89d2\u5f62\u5206\u5272\u306e\u5f69\u8272\u9077\u79fb<\/a>
\n\u5ca9\u653f \u52c7\u4ec1\uff08\u4eac\u90fd\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-5<\/td>\n\u7121\u7fa8\u671b\u30de\u30c3\u30c1\u30f3\u30b0\u306e\u9077\u79fb<\/a>
\n\u795e\u5c71 \u76f4\u4e4b\uff08\u4e5d\u5dde\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-6<\/td>\n\u914d\u96fb\u640d\u5931\u6700\u5c0f\u5316\u554f\u984c\u306b\u5bfe\u3059\u308b\u7d44\u5408\u305b\u9077\u79fb\u7684\u30a2\u30d7\u30ed\u30fc\u30c1<\/a>
\n\u9234\u6728 \u9855\uff08\u6771\u5317\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-7<\/td>\n\u5165\u9662\u60a3\u8005\u306e\u75c5\u5e8a\u30b9\u30b1\u30b8\u30e5\u30fc\u30ea\u30f3\u30b0\u2015\u5165\u9662\u6570\u3068\u5728\u9662\u65e5\u6570\u4e88\u6e2c-<\/a>
\n\u677e\u6797 \ufa4f\u52a0\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-8<\/td>\n\u624b\u8853\u6642\u9593\u306e\u4e0d\u78ba\u5b9f\u6027\u3068\u9045\u5ef6\u30ea\u30b9\u30af\u3092\u8003\u616e\u3057\u305f\u624b\u8853\u5ba4\u306e\u30b9\u30b1\u30b8\u30e5\u30fc\u30ea\u30f3\u30b0<\/a>
\n\u96e3\u6ce2 \u798e\u4eba\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-9<\/td>\n\u6570\u7406\u6700\u9069\u5316\u3092\u7528\u3044\u305f\u5927\u5b66\u6642\u9593\u5272\u4f5c\u6210\u304a\u3088\u3073\u6559\u5ba4\u5272\u5f53<\/a>
\n\u5c0f\u5f62 \u512a\u4eba\uff08\u91d1\u6ca2\u5b66\u9662\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-10<\/td>\n\u96c6\u5408\u6bd4\u8f03\u3092\u7528\u3044\u305f\u6700\u9069\u5316\u554f\u984c\u306e\u5b9f\u884c\u53ef\u80fd\u6027\u5224\u5b9a\u306b\u3064\u3044\u3066<\/a>
\n\u5c0f\u5f62 \u512a\u4eba\uff08\u91d1\u6ca2\u5b66\u9662\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-11<\/td>\n\u96c6\u5408\u5024\u5199\u50cf\u306e\u9310\u9023\u7d9a\u6027\u306e\u4e00\u822c\u5316\u306b\u3064\u3044\u3066<\/a>
\n\u7530\u4e2d \u74b0\uff08\u65b0\u6f5f\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-B-12<\/td>\nSome properties of convex-cone-based intuitionistic fuzzy set relations<\/a>
\n\u30d7\u30e9\u30c6\u30a3\u30eb \u30ed\u30f3\u30b0\u30ea\u30aa\uff08\u65b0\u6f5f\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
2-C-1<\/td>\n\u5be1\u5360\u7684\u96fb\u529b\u5c0f\u58f2\u5e02\u5834\u306b\u304a\u3051\u308bprice-based DR\u306e\u5206\u6790
\n \u95a2\u5d0e \u771f\u4e5f\uff08\u5e83\u5cf6\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-C-2<\/td>\n\u4e3b\u6210\u5206\u8a98\u5c0e\u578b\u30b9\u30d1\u30fc\u30b9\u56de\u5e30\u3092\u7528\u3044\u305f\u96fb\u529b\u30b9\u30dd\u30c3\u30c8\u4fa1\u683c\u4e88\u6e2c<\/a>
\n\u677e\u672c \u62d3\u53f2\uff08\u91d1\u6ca2\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-C-3<\/td>\nFeed-in Premium\u5236\u5ea6\u306e\u7d4c\u6e08\u6027\u8a55\u4fa1 ~\u4e0d\u78ba\u5b9f\u6027\u306e\u5f71\u97ff~<\/a>
\n\u9ad8\u6a4b \u8ad2\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-C-4<\/td>\n\u4e8b\u696d\u6240\u6570Google\u691c\u7d22\u306b\u3064\u3044\u3066Deep learning\u306b\u3088\u308b\u691c\u8a3c<\/a>
\n\u5742\u672c \u61b2\u662d\uff08\u6cd5\u653f\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-C-5<\/td>\n\u65b0\u7a7a\u6e2f\u7dda(\u6771\u6025\u591a\u6469\u5ddd\u7dda\u3068\u4eac\u6025\u7a7a\u6e2f\u7dda\u84b2\u7530\u99c5\u63a5\u7d9a)\u306e\u9244\u9053\u5229\u4fbf\u6027\u306b\u5bfe\u3059\u308b\u52b9\u679c\u306e\u691c\u8a3c<\/a>
\n\u7530\u53e3 \u6771\uff08(\u682a)\u30d9\u30af\u30c8\u30eb\u7dcf\u7814\uff09<\/p>\n<\/tr>\n
2-C-6<\/td>\n\u653e\u5c04\u74b0\u72b6\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u901a\u904e\u91cf\u5206\u5e03<\/a>
\n\u8170\u585a \u6b66\u5fd7\uff08\u7b51\u6ce2\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-C-7<\/td>\n\u751f\u8d77\u78ba\u7387\u6700\u5927\u5316\u30a8\u30f3\u30c8\u30ed\u30d4\u30fc\u30e2\u30c7\u30eb\u306b\u3088\u308b\u30cf\u30d5\u30e2\u30c7\u30eb\u306e\u8a98\u5c0e<\/a>
\n\u6817\u7530 \u6cbb\uff08\u6176\u61c9\u7fa9\u587e\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-C-8<\/td>\n\u5e83\u57df\u9023\u643a\u65bd\u8a2d\u3078\u306e\u516c\u5171\u4ea4\u901a\u306b\u3088\u308b\u30a2\u30af\u30bb\u30b9\u6027<\/a>
\n\u77f3\u4e95 \u5100\u5149\uff08\u56fd\u571f\u6280\u8853\u653f\u7b56\u7dcf\u5408\u7814\u7a76\u6240\uff09<\/p>\n<\/tr>\n
2-C-9<\/td>\n\u6c34\u9762\u501f\u666f\u306e\u5909\u5316\u3092\u7acb\u4f53\u89d2\u3067\u6570\u5024\u5316\u3059\u308b<\/a>
\n\u4efb \u4f0a\u30ab\u30f3\uff08\u7b51\u6ce2\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-C-10<\/td>\nExact Solution Methods for the Multi-Weber Problem with Manhattan Distance<\/a>
\nByrne Thomas\uff08University of Strathclyde\uff09<\/p>\n<\/tr>\n
2-C-11<\/td>\n\u76f8\u7d9a\u306f\u5730\u65b9\u3092\u3044\u304b\u306b\u8870\u9000\u3055\u305b\u3066\u3044\u308b\u306e\u304b~\u53ef\u52d5\u7523\u306b\u7740\u773c\u3057\u3066~<\/a>
\n\u963f\u90e8 \u304f\u3089\u3093\uff08\u7b51\u6ce2\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-C-12<\/td>\n\u6df7\u5408\u6574\u6570\u6700\u9069\u5316\u306b\u3088\u308b\u76f8\u7d9a\u5de5\u7a0b\u306e\u9577\u671f\u5316\u30ea\u30b9\u30af\u63a1\u70b9\u30b7\u30b9\u30c6\u30e0<\/a>
\n\u690e\u540d \u840c\uff08\u7b51\u6ce2\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
2-D-1<\/td>\n\u30de\u30af\u30ed\u7d4c\u6e08\u30a2\u30ca\u30a6\u30f3\u30b9\u30e1\u30f3\u30c8\u304c\u30ea\u30b9\u30af\u30d7\u30ec\u30df\u30a2\u30e0\u30fb\u30ea\u30b9\u30af\u30fb\u9078\u597d\u306b\u4e0e\u3048\u308b\u5f71\u97ff<\/a>
\n\u9727\u751f \u62d3\u4e5f\uff08\u5927\u962a\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-2<\/td>\nStrategic Liquidity Provision in High Frequency Trading<\/a>
\n\u897f\u51fa \u52dd\u6b63\uff08\u4e00\u6a4b\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-3<\/td>\nCorporate sustainability, investment, and capital structure<\/a>
\n\u897f\u539f \u7406\uff08\u5927\u962a\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-4<\/td>\nJ1 \u30ea\u30fc\u30b0\u306b\u304a\u3051\u308b\u9078\u624b\u306e\u5e74\u4ff8\u306e\u6c7a\u5b9a\u8981\u56e0<\/a>
\n\u4e09\u8c37 \u99ff\u8f14\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-5<\/td>\n\u9023\u7d9a\u6642\u9593\u30e2\u30c7\u30eb\u306b\u57fa\u3065\u304f\u696d\u7e3e \u9023\u52d5 \u30b9\u30c8\u30c3\u30af\u30fb\u30aa\u30d7\u30b7\u30e7\u30f3\u306e\u4fa1\u5024\u8a55\u4fa1<\/a>
\n\u5927\u897f \u5321\u5149\uff08\u5927\u548c\u5927\u5b66\uff0f\u5927\u962a\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-6<\/td>\n\u30a8\u30b9\u30c6\u30b5\u30ed\u30f3\u5229\u7528\u9867\u5ba2\u306e\u4ed6\u8005\u3078\u306e\u63a8\u5968\u610f\u56f3\u3092\u9ad8\u3081\u308b\u8981\u56e0\u5206\u6790<\/a>
\n\u8d8a \u9678\u6597\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-7<\/td>\n\u5e83\u544a\u3068\u5951\u7d04\u306e\u8981\u56e0\u304c\u30cd\u30fc\u30df\u30f3\u30b0\u30e9\u30a4\u30c4\u306e\u4fa1\u683c\u306b\u53ca\u307c\u3059\u5f71\u97ff<\/a>
\n\u85e4\u6cbc \u4eae\u592a\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-8<\/td>\nInstagram\u306e\u6295\u7a3f\u304c\u8cfc\u5165\u610f\u5411\u306b\u3082\u305f\u3089\u3059\u52b9\u679c\u306b\u3064\u3044\u3066\u306e\u5206\u6790<\/a>
\n\u4e09\u5cf6 \u601c\u5948\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-9<\/td>\n\u5c0f\u5150\u80a5\u6e80\u304c\u4e0e\u3048\u308b\u6210\u4eba\u7cd6\u5c3f\u75c5\u3078\u306e\u5f71\u97ff\u306e\u30d0\u30af\u30c6\u30ed\u30a4\u30c7\u30b9\u5bfe\u30af\u30ed\u30b9\u30c8\u30ea\u30b8\u30a6\u30e0\u91cf\u6bd4(Rbc)\u306b\u304a\u3044\u3066\u306e\u90fd\u9053\u5e9c\u770c\u3054\u3068\u306e\u691c\u8a0e<\/a>
\n\u7c9f\u570b \u6674\u697d\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-10<\/td>\n\u5b66\u7fd2\u587e\u306b\u304a\u3051\u308b\u5bfe\u9762\u30fb\u30aa\u30f3\u30c7\u30de\u30f3\u30c9\u578b\u6388\u696d\u306e\u6e80\u8db3\u5ea6\u5206\u6790
\n \u4f50\u91ce \u5c0b\u4e16\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-D-11<\/td>\n\u643a\u5e2f\u30ad\u30e3\u30ea\u30a2\u30d7\u30e9\u30f3\u5229\u7528\u8005\u7279\u5fb4\u5206\u6790<\/a>
\n\u6c38\u4e95 \u3042\u3084\u306e\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
2-E-1<\/td>\nA Markov Game Model for Determining Tactical Changes in Soccer<\/a>
\n\u5ee3\u6d25 \u4fe1\u7fa9\uff08\u9806\u5929\u5802\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-E-2<\/td>\n\u57fa\u5730\u5c40\u306e\u30af\u30e9\u30b9\u30bf\u914d\u7f6e\u3092\u8003\u3048\u305f2\u5c64\u30bb\u30eb\u30e9\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u304a\u3051\u308bTime-based\u306a\u30cf\u30f3\u30c9\u30aa\u30fc\u30d0\u5236\u5fa1\u624b\u6cd5\u306e\u8a55\u4fa1<\/a>
\n\u5fb3\u5c71 \u559c\u4e00\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-E-3<\/td>\n\u635c\u7d22\u6d3b\u52d5\u306b\u304a\u3051\u308b\u52b9\u679c\u7684\u306a\u7d4c\u8def\u3068\u6295\u5165\u6642\u9593\u306e\u5c0e\u51fa<\/a>
\n\u4e2d\u6751 \u7950\u8f1d\uff08\u9632\u885b\u5927\u5b66\u6821\uff09<\/p>\n<\/tr>\n
2-E-4<\/td>\n\u5927\u76f8\u64b2\u529b\u58eb\u306b\u5bfe\u3059\u308b\u4f11\u5834\u4e88\u6e2c\u30e2\u30c7\u30eb\u306e\u6027\u80fd\u8a55\u4fa1<\/a>
\n\u592a\u7530 \u4fee\u5e73\uff08\u795e\u5948\u5ddd\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-E-5<\/td>\n\u78ba\u7387\u7684\u5408\u610f\u5f62\u6210\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306b\u3088\u308a\u5f97\u3089\u308c\u308b\u5408\u610f\u7d50\u679c\u306e\u78ba\u7387\u7684\u6027\u8cea<\/a>
\n\u7af9\u539f \u5065\u592a\uff08\u5343\u8449\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-E-6<\/td>\n\u5371\u5bb3\u30ea\u30b9\u30af\u3068\u4fdd\u5168\u30b3\u30b9\u30c8\u3092\u8003\u616e\u3057\u305fE\/E\/PE\u5b89\u5168\u95a2\u9023\u7cfb\u306e\u4fdd\u5168\u65b9\u7b56
\n \u4e95\u4e0a \u771f\u4e8c\uff08\u95a2\u897f\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-E-7<\/td>\n\u30b8\u30cb\u4fc2\u6570\u3092\u6700\u5c0f\u5316\u3059\u308b\u8b70\u5e2d\u914d\u5206\u3092\u6c42\u3081\u308b2\u3064\u306e\u5272\u5f53\u6cd5\u306e\u6bd4\u8f03<\/a>
\n\u8af8\u661f \u7a42\u7a4d\uff08\u653f\u7b56\u7814\u7a76\u5927\u5b66\u9662\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-E-8<\/td>\n\u6700\u9069\u5316\u3068\u89e3\u5217\u6319\u306b\u3088\u308b2022 \u9078\u6319\u533a\u52e7\u544a\u6848\u306e\u691c\u8a3c\u8a55\u4fa1<\/a>
\n\u5800\u7530 \u656c\u4ecb\uff08\u6587\u6559\u5927\u5b66\uff09<\/p>\n<\/tr>\n
<\/td>\n<\/td>\n
2-F-1<\/td>\n\u9589\u9396\u3092\u4f34\u3046\u968e\u5c64\u578b\u65bd\u8a2d\u306e\u6700\u9069\u306a\u6570<\/a>
\n\u5bae\u5ddd \u96c5\u81f3\uff08\u5c71\u68a8\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-F-2<\/td>\n\u5efa\u7bc9\u30fb\u90fd\u5e02\u7a7a\u9593\u306e\u6570\u7406\u7684\u8a55\u4fa1\u306b\u5411\u3051\u305f\u6975\u5927\u51f8\u7a7a\u9593\u306e\u5217\u6319\u30b7\u30b9\u30c6\u30e0<\/a>
\n\u672c\u9593 \u88d5\u5927\uff08\u6771\u4eac\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-F-3<\/td>\n\u9577\u671f\u7684\u306a\u4eba\u53e3\u5909\u52d5\u3092\u8003\u616e\u3057\u305f\u62e0\u70b9\u8a08\u753b\u624b\u6cd5<\/a>
\n\u56b4 \u5148\u93de\uff08\u7b51\u6ce2\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-F-4<\/td>\n\u4e2d\u4eac\u90fd\u5e02\u570f\u306e\u9244\u9053\u5229\u7528\u8005\u3092\u5bfe\u8c61\u3068\u3057\u305f\u99c5\u3078\u306e\u7acb\u5bc4\u308a\u6613\u3055<\/a>
\n\u7530\u4e2d \u5065\u4e00\uff08\u6176\u61c9\u7fa9\u587e\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-F-5<\/td>\n\u5bfe\u8c61\u5730\u57df\u306e\u30b0\u30eb\u30fc\u30d7\u6027\u3092\u8003\u616e\u3057\u305f\u65bd\u8a2d\u518d\u914d\u7f6e\u554f\u984c<\/a>
\n\u6a4b\u672c \u71ce\uff08\u9752\u5c71\u5b66\u9662\u5927\u5b66\uff09<\/p>\n<\/tr>\n
2-F-6<\/td>\n\u5730\u7406\u60c5\u5831\u3092\u7528\u3044\u305f\u7af6\u54082\u793e\u306b\u3088\u308b\u30d5\u30e9\u30f3\u30c1\u30e3\u30a4\u30ba\u5e97\u8217\u914d\u7f6e\u554f\u984c<\/a>
\n\u9152\u4e95 \u5b97\u4e00\u90ce\uff08\u9752\u5c71\u5b66\u9662\u5927\u5b66\uff09<\/p>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

\u516c\u958b\u306b\u540c\u610f\u3044\u305f\u3060\u3044\u305f\u65b9\u306e\u30a2\u30d6\u30b9\u30c8\u30e9\u30af\u30c8\u3092\u63b2\u8f09\u3057\u3066\u304a\u308a\u307e\u3059\u3002 \uff11\u65e5\u76ee (2022\/9\/13) 1-A-1 \u30d1\u30b9\u306em\u6700\u9069\u307a\u30d6\u30ea\u30f3\u30b0\u6570 \u753a\u7530 \u8ad2\uff08\u4e5d\u5dde\u5927\u5b66\uff09 1-A-2 \u30e2\u30b8\u30e5\u30e9\u30ea\u30c6\u30a3\u5bc6\u5ea6\u6700\u5927\u5316\u306b\u5bfe\u3059\u308b\u9ad8\u901f\u306a\u5217\u751f\u6210\u6cd5\u306e\u8a2d\u8a08\u3068\u8a08 … <\/p>\n

Continue reading “2022\u5e74\u79cb\u5b63\u7814\u7a76\u767a\u8868\u4f1a\u30a2\u30d6\u30b9\u30c8\u30e9\u30af\u30c8”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":5207,"menu_order":222,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_mc_calendar":[]},"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false,"education-pro-homepage-thumb":false},"uagb_author_info":{"display_name":"\u7ba1\u7406\u8005","author_link":"https:\/\/orsj.org\/?author=1"},"uagb_comment_info":0,"uagb_excerpt":"\u516c\u958b\u306b\u540c\u610f\u3044\u305f\u3060\u3044\u305f\u65b9\u306e\u30a2\u30d6\u30b9\u30c8\u30e9\u30af\u30c8\u3092\u63b2\u8f09\u3057\u3066\u304a\u308a\u307e\u3059\u3002 \uff11\u65e5\u76ee (2022\/9\/13) 1-A-1 \u30d1\u30b9\u306e…","_links":{"self":[{"href":"https:\/\/orsj.org\/index.php?rest_route=\/wp\/v2\/pages\/5212"}],"collection":[{"href":"https:\/\/orsj.org\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/orsj.org\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/orsj.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/orsj.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5212"}],"version-history":[{"count":4,"href":"https:\/\/orsj.org\/index.php?rest_route=\/wp\/v2\/pages\/5212\/revisions"}],"predecessor-version":[{"id":5586,"href":"https:\/\/orsj.org\/index.php?rest_route=\/wp\/v2\/pages\/5212\/revisions\/5586"}],"up":[{"embeddable":true,"href":"https:\/\/orsj.org\/index.php?rest_route=\/wp\/v2\/pages\/5207"}],"wp:attachment":[{"href":"https:\/\/orsj.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5212"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}