{"id":320,"date":"2024-11-20T01:21:26","date_gmt":"2024-11-20T01:21:26","guid":{"rendered":"https:\/\/sasaki-lab.ws.hosei.ac.jp\/wp\/?p=320"},"modified":"2026-04-27T03:45:15","modified_gmt":"2026-04-27T03:45:15","slug":"achievement","status":"publish","type":"post","link":"https:\/\/sasaki-lab.ws.hosei.ac.jp\/wp\/2024\/11\/20\/320\/","title":{"rendered":"Achievements"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">2020\u5e74\u5ea6\u4ee5\u524d\u304a\u3088\u3073\u4ed6\u6a5f\u95a2\u95a2\u9023\u306e\u696d\u7e3e\u306f<a href=\"https:\/\/kenkyu-web.hosei.ac.jp\/Profiles\/112\/0011115\/profile.html\">\u3053\u3061\u3089<\/a>\u3092\u53c2\u7167\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\u53d7\u8cde<\/h2>\n\n\n\n<h5 class=\"wp-block-heading\">\u5b66\u5916<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u9577\u5c71 \u6cf0\u8f14\uff0c\u4ee4\u548c7\u5e74\u5ea6\u96fb\u6c17\u5b66\u4f1a\u7523\u696d\u5fdc\u7528\u90e8\u9580\u512a\u79c0\u8ad6\u6587\u767a\u8868\u8cde\uff0c2026\u5e743\u670831\u65e5\uff0e<\/li>\n\n\n\n<li>\u5c0f\u64ad\u512a\u8cb4\uff0c\u4ee4\u548c7\u5e74\u5ea6\u96fb\u6c17\u5b66\u4f1a\u7523\u696d\u5fdc\u7528\u90e8\u9580\u512a\u79c0\u8ad6\u6587\u767a\u8868\u8cde\uff0c2026\u5e743\u670831\u65e5\uff0e<\/li>\n\n\n\n<li>\u7247\u5ca1\u512a\u6597\uff0c\u4ee4\u548c7\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\u512a\u79c0\u8ad6\u6587\u767a\u8868\u8cde\uff0c2026\u5e743\u670831\u65e5\uff0e<\/li>\n\n\n\n<li>\u5ca9\u7530\u548c\u4e45\uff0c\u4ee4\u548c6\u5e74\u5ea6\u96fb\u6c17\u5b66\u4f1a\u7523\u696d\u5fdc\u7528\u90e8\u9580\u512a\u79c0\u8ad6\u6587\u767a\u8868\u8cde\uff0c2025\u5e743\u670831\u65e5\uff0e<\/li>\n\n\n\n<li>\u4e2d\u91ce \u7693\u5e73\uff0c\u4ee4\u548c6\u5e74\u5ea6\u96fb\u6c17\u5b66\u4f1a\u6771\u4eac\u652f\u90e8\u96fb\u6c17\u5b66\u8853\u5968\u52b1\u8cde\uff0c2025\u5e743\u670831\u65e5\uff0e<\/li>\n\n\n\n<li>\u4e94\u5341\u5d50\u4e00\u8f1d\uff0cIEEE CEFC2024 Best student presentation awards(Poster)\uff0c2024\u5e746\u67085\u65e5.<\/li>\n\n\n\n<li>\u5ca9\u7530\u548c\u4e45\uff0cIEEE CEFC2024 Best student presentation awards(Oral)\uff0c2024\u5e746\u67085\u65e5.<\/li>\n\n\n\n<li>\u5c0f\u6797\u7531\u4f73\uff0c\u4ee4\u548c5\u5e74\u5ea6\u96fb\u6c17\u5b66\u4f1a\u6771\u4eac\u652f\u90e8\u96fb\u6c17\u5b66\u8853\u5973\u6027\u6d3b\u52d5\u5968\u52b1\u8cde\uff0c2024\u5e743\u670831\u65e5.<\/li>\n\n\n\n<li>\u5ca9\u7530\u548c\u4e45\uff0c\u4ee4\u548c4\u5e74\u5ea6\u96fb\u6c17\u5b66\u4f1a\u6771\u4eac\u652f\u90e8\u96fb\u6c17\u5b66\u8853\u5968\u52b1\u8cde\uff0c2023\u5e743\u670831\u65e5.<\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\uff0cMAGDA2021\u512a\u79c0\u8ad6\u6587\u767a\u8868\u8cde\uff0c2021\u5e7412\u6708.<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">\u5b66\u5185<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u4e2d\u91ce \u7693\u5e73\uff0cCHANCE \u7814\u7a76\u6240 \u7b2c \uff14\u56de\u7814\u7a76\u6210\u679c\u5831\u544a\u4f1a\u3000\u512a\u79c0\u767a\u8868\u8cde\uff0c2025\u5e7410\u670831\u65e5\uff0e<\/li>\n\n\n\n<li>\u5c0f\u64ad\u512a\u8cb4\uff0c\u540c\u7a93\u4f1a\u8912\u7ae0\uff0c2025\u5e743\u670831\u65e5\uff0e<\/li>\n\n\n\n<li>\u9577\u5c71 \u6cf0\u8f14\uff0c\u6cd5\u653f\u5927\u5b66\u79d1\u5b66\u6280\u8853\u30d5\u30a9\u30fc\u30e9\u30e0\u3000\u512a\u79c0\u767a\u8868\u8cde\uff0c2025\u5e743\u670810\u65e5\uff0e<\/li>\n\n\n\n<li>\u9577\u5c71 \u6cf0\u8f14\uff0cCHANCE \u7814\u7a76\u6240 \u7b2c 3 \u56de\u7814\u7a76\u6210\u679c\u5831\u544a\u4f1a\u3000\u767a\u8868\u8cde\uff0c2024\u5e7410\u670830\u65e5.<\/li>\n\n\n\n<li>\u7530\u4e2d \u99ff\u4e5f\uff0cCHANCE \u7814\u7a76\u6240 \u7b2c 3 \u56de\u7814\u7a76\u6210\u679c\u5831\u544a\u4f1a\u3000\u767a\u8868\u8cde\uff0c2024\u5e7410\u670830\u65e5.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"2022\">\u89e3\u8aac<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\u3001\u300c<a href=\"https:\/\/www.jstage.jst.go.jp\/article\/ieejjournal\/143\/10\/143_628\/_article\/-char\/ja\/\" data-type=\"link\" data-id=\"https:\/\/www.jstage.jst.go.jp\/article\/ieejjournal\/143\/10\/143_628\/_article\/-char\/ja\/\">\u6df1\u5c64\u5b66\u7fd2\u3068\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u6280\u8853\u306e\u878d\u5408\u306b\u3088\u308b\u30e2\u30fc\u30bf\u958b\u767a\u306e\u52b9\u7387\u5316<\/a>\u300d\u3001\u96fb\u6c17\u5b66\u4f1a\u8a8c\u3001Vol. 143\u3001No. 10\u3001\u96fb\u6c17\u5b66\u4f1a\u30012023\u5e7410\u6708.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\u3001\u300c<a href=\"https:\/\/www.jstage.jst.go.jp\/article\/jsaem\/30\/4\/30_373\/_article\/-char\/ja\/\" data-type=\"URL\" data-id=\"https:\/\/www.jstage.jst.go.jp\/article\/jsaem\/30\/4\/30_373\/_article\/-char\/ja\/\">\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u30e2\u30fc\u30bf\u306e\u7279\u6027\u63a8\u5b9a\u624b\u6cd5\u306e\u958b\u767a\u3068\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306e\u9ad8\u901f\u5316<\/a>\u300d\u3001\u65e5\u672cAEM\u5b66\u4f1a\u8a8c\u3001Vol. 30\u3001No. 4\u3001\u65e5\u672cAEM\u5b66\u4f1a\u30012022\u5e7412\u6708.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\u3001\u300cAI\u3092\u7528\u3044\u305f\u30e2\u30fc\u30bf\u30e2\u30c7\u30eb\u306e\u751f\u6210\u3068\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306e\u9ad8\u901f\u5316\u300d\u3001\u6a5f\u68b0\u8a2d\u8a08\u3001vol.66\u3001No.11\u3001\u65e5\u520a\u5de5\u696d\u65b0\u805e\u793e\u30012022\u5e7410\u6708\uff0e<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4e94\u5341\u5d50\u4e00\u3001\u4f50\u3005\u6728\u79c0\u5fb3\u3001\u300c<a rel=\"noreferrer noopener\" href=\"https:\/\/sasaki-lab.ws.hosei.ac.jp\/wp\/wp-content\/uploads\/2022\/06\/150-155_%E9%9B%BB%E9%80%9A%E4%BC%9A%E8%AA%8C2%E6%9C%88_01.pdf\" target=\"_blank\">\u4eba\u5de5\u77e5\u80fd(AI)\u6280\u8853\u3068\u96fb\u78c1\u6c17\u5b66\u3092\u7528\u3044\u305f\u6700\u9069\u8a2d\u8a08(2\u30fb\u5b8c)\u6df1\u5c64\u5b66\u7fd2\u30fb\u30e2\u30f3\u30c6\u30ab\u30eb\u30ed\u6728\u63a2\u7d22\u306e\u5fdc\u7528<\/a>\u300d\u3001\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u8a8c\u3001105(2) 150-155 2022\u5e742\u6708.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"2022\">\u62db\u5f85\u8b1b\u6f14<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u4f50\u3005\u6728\u79c0\u5fb3, \u300cAI\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u56de\u8ee2\u6a5f\u30fb\u9759\u6b62\u5668\u8a2d\u8a08\u6280\u8853\u306e\u6700\u65b0\u52d5\u5411, \u300d\u4ee4\u548c8\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a,\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\u8b1b\u6f14\uff0c2026\u5e743\u670813\u65e5\uff0e<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3, \u300c\u30e2\u30fc\u30bf\u6700\u9069\u5316\uff081\uff09AI\u30fb\u6a5f\u68b0\u5b66\u7fd2\u306e\u9069\u7528,\u300d \u96fb\u6c17\u5b66\u4f1a\u7523\u696d\u5fdc\u7528\u30d5\u30a9\u30fc\u30e9\u30e0\u300c\u96fb\u78c1\u754c\u89e3\u6790\u306b\u3088\u308b\u56de\u8ee2\u6a5f\u306e\u9ad8\u7cbe\u5ea6\u30e2\u30c7\u30ea\u30f3\u30b0\u3068\u5148\u9032\u6700\u9069\u5316\u6280\u8853\u300d, 2025\u5e7412\u670810\u65e5\uff0e<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300c\u30e2\u30fc\u30bf\u8a2d\u8a08\u306b\u304a\u3051\u308bAI\u6d3b\u7528\u306e\u57fa\u790e\u3068\u5c55\u671b\u300d\uff0c\u96fb\u6c17\u5b66\u4f1a\uff0c\u7b2c28\u56de\u96fb\u78c1\u754c\u6570\u5024\u89e3\u6790\u306b\u95a2\u3059\u308b\u30bb\u30df\u30ca\u30fc\u3000\uff5e\u56de\u8ee2\u6a5f\u96fb\u78c1\u754c\u89e3\u6790\u306e\u57fa\u790e\u304b\u3089\u6700\u9069\u8a2d\u8a08\uff0cAI\u6d3b\u7528\u307e\u3067\uff5e\uff0c2025\u5e7410\u670831\u65e5.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>Hidenori Sasaki, \"Development of an Automatic Design Algorithm via Deep Generative Models and Topology Optimization, \"The 49th Annual Conference on MAGNETICS in Japan, 2025\u5e749\u670818\u65e5. <strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>Hidenori Sasaki, \"Accelerating topology optimization of interior permanent magnet synchronous motor using deep generative models,\" NuMoDiTEE2025, 2025\u5e743\u670826\u65e5.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300c\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u3068\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u30d9\u30fc\u30b9\u30e2\u30fc\u30bf\u8a2d\u8a08\u652f\u63f4\u300d\uff0c\u7b2c2\u56de \u300c\u96fb\u6a5f\u30b7\u30b9\u30c6\u30e0\u00d7AI\u300d\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\uff0c2024\u5e7410\u67084\u65e5.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300c\u30e2\u30fc\u30bf\u6700\u9069\u5316\uff081\uff09AI\u30fb\u6a5f\u68b0\u5b66\u7fd2\u306e\u9069\u7528\u300d\uff0c\u96fb\u6c17\u5b66\u4f1a\u7523\u696d\u5fdc\u7528\u30d5\u30a9\u30fc\u30e9\u30e0 \u300c\u96fb\u78c1\u754c\u89e3\u6790\u306b\u3088\u308b\u56de\u8ee2\u6a5f\u306e\u9ad8\u7cbe\u5ea6\u6027\u80fd\u8a55\u4fa1\u6280\u8853\u300d\uff0c2023\u5e7411\u670810\u65e5.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300cAI\u3084\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306e\u57fa\u790e\u3068\u30e2\u30fc\u30bf\u8a2d\u8a08\u3078\u306e\u9069\u7528\u306b\u95a2\u3059\u308b\u6280\u8853\u52d5\u5411\u300d\uff0cTECHNO-FRONTIER 2023 \u7b2c44 \u56de \u30e2\u30fc\u30bf\u6280\u8853\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c2023\u5e747\u670828\u65e5.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u4e94\u5341\u5d50\u4e00\uff0c\u300c\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u30e2\u30fc\u30bf\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306e\u9ad8\u901f\u5316\u300d\uff0c\u4ee4\u548c5\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\u8b1b\u6f14S16-4\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c2023\u5e743\u670815\u65e5.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>Hajime Igarashi, Hidenori Sasaki, Hayaho Sato, \"Optimal design of electric devices based on machine learning,\" ISEM2022, Online,2022\u5e746\u67085\u65e5.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3,\uff0c\u4e94\u5341\u5d50\u4e00\uff0c \u300c\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u56de\u8ee2\u6a5f\u78c1\u6c17\u69cb\u9020\u306e\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u6280\u8853\u300d\uff0c\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u7dcf\u5408\u5927\u4f1a\uff0cOnline\uff0c2022\u5e743\u670816\u65e5.<strong><span data-color=\"#ff6900\" style=\"background: linear-gradient(transparent 60%,rgba(255, 105, 0, 0.7) 0);\" class=\"vk_highlighter\">(\u62db\u5f85\u6709)<\/span><\/strong><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"2022\">\u67fb\u8aad\u4ed8\u8ad6\u6587<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Nakano K,\u00a0Sasaki H,\u00a0Matsuura T,\u00a0Sasaki K,\u00a0Morimoto T,\u00a0Kato T (2026;), \"Design exploration of variable leakage flux interior permanent magnet synchronous motors through parameter and topology optimization using covariance matrix adaptation evolution strategy\".\u00a0<em>COMPEL<\/em>, <a href=\"https:\/\/doi.org\/10.1108\/COMPEL-10-2025-0512\">https:\/\/doi.org\/10.1108\/COMPEL-10-2025-0512<\/a><\/li>\n\n\n\n<li>Daisuke Nakagawa, Tomoya Ueda, Hidenori Sasaki, Kazuhisa Iwata, Hajime Igarashi, \"Machine Learning Accelerated Shape Optimization with Robust Shape-Collapse Prevention for Interior Permanent Magnet Synchronous Motors,\" <strong><em>IEEE Transactions on Magnetics<\/em><\/strong>, 2025.<a href=\"https:\/\/doi.org\/10.1109\/tmag.2025.3644307\">https:\/\/doi.org\/10.1109\/tmag.2025.3644307<\/a><\/li>\n\n\n\n<li>Kohei Nakano, Hidenori Sasaki, \"Latent Space Bayesian Parameter Topology Optimization of Permanent Magnet Synchronous Motors via a Variational Autoencoder,\" <strong><em>IEEE Transactions on Magnetics<\/em><\/strong>, 2025. <a href=\"https:\/\/doi.org\/10.1109\/TMAG.2025.3612042\">https:\/\/doi.org\/10.1109\/TMAG.2025.3612042<\/a><\/li>\n\n\n\n<li>Taisuke Nagayama, Hidenori Sasaki, \"Predicting torque characteristics of synchronous reluctance motors using swin transformer,\" <strong><em>COMPEL-The international journal for computation and mathematics in electrical and electronic engineering<\/em><\/strong>, 2025. <a href=\"https:\/\/doi.org\/10.1108\/COMPEL-01-2025-0022\">https:\/\/doi.org\/10.1108\/COMPEL-01-2025-0022<\/a><\/li>\n\n\n\n<li>Kazuki Igarashi, Hidenori Sasaki, \"Nondestructive Magnetisation Estimation for Permanent Magnets Using Autoencoder\u2010Based Dimensionality Reduction,\" <em><strong>IET Science, Measurement &amp; Technology<\/strong><\/em>, 2025.  <a href=\"https:\/\/doi.org\/10.1049\/smt2.70024\">https:\/\/doi.org\/10.1049\/smt2.70024<\/a><\/li>\n\n\n\n<li>Kazuhisa Iwata, Hidenori Sasaki, \"Design-LIME: An Interpretable Visualization Method for Electric Motor Design Based on Deep Learning,\"&nbsp;<strong><em>IEEE&nbsp;Access<\/em><\/strong>, 2025. <a href=\"https:\/\/doi.org\/10.1109\/ACCESS.2025.3563351\">https:\/\/doi.org\/10.1109\/ACCESS.2025.3563351<\/a>&nbsp;(IF: 3.4)<\/li>\n\n\n\n<li>Kosuke Tomotani, Hidenori Sasaki, Ran Dong, Soichiro Ikuno, \"Pre-Processing of Deep Neural Network for Motor Torque Characteristics Using Empirical Mode Decomposition,\"&nbsp;<strong><em>Studies in Applied Electromagnetics and Mechanics<\/em><\/strong>, 2025.&nbsp;<a href=\"https:\/\/doi.org\/10.3233\/saem250017\">https:\/\/doi.org\/10.3233\/saem250017<\/a><\/li>\n\n\n\n<li>Hidenori Sasaki, Kazuhisa Iwata, Takahiro Sato, Yuki Sato, \"Prediction of Motor Characteristic Maps via Deep Operator Networks for Topology Optimization,\" <strong><em>IEEE Transactions on Magnetics<\/em><\/strong>, 2024.<a href=\"https:\/\/doi.org\/10.1109\/tmag.2024.3477448\">https:\/\/doi.org\/10.1109\/tmag.2024.3477448<\/a><\/li>\n\n\n\n<li>Hidenori Sasaki, Koichi Yamamura, \"Topology Optimization with Shapley Additive Explanations for Permanent Magnet Synchronous Motors,\" <strong><em>IEEE Transactions on Magnetics<\/em><\/strong>, 2023.<a href=\"https:\/\/doi.org\/10.1109\/TMAG.2023.3325460\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/doi.org\/10.1109\/TMAG.2023.3325460<\/a><\/li>\n\n\n\n<li>Kazuhisa Iwata, Hidenori Sasaki, Hajime Igarashi, Daisuke Nakagawa, Tomoya Ueda, \"Generalization Performance in Predicting Torque Characteristics Using Convolutional Neural Network and Stator Magnetic Flux,\" <strong><em>IEEE Transactions on Magnetics<\/em><\/strong>, 2023. <a href=\"https:\/\/doi.org\/10.1109\/tmag.2023.3303458\">https:\/\/doi.org\/10.1109\/tmag.2023.3303458<\/a><\/li>\n\n\n\n<li>Hidenori Sasaki, \"Topology Optimization for Motor Using Multitask Convolutional Neural Network under Multiple Current Conditions,\"<strong><em>&nbsp;IEEE Transactions on Magnetics<\/em><\/strong>, 2022.&nbsp;<a rel=\"noreferrer noopener\" href=\"https:\/\/doi.org\/10.1109\/TMAG.2022.3179426\" target=\"_blank\">https:\/\/doi.org\/10.1109\/TMAG.2022.3179426<\/a><\/li>\n\n\n\n<li>Hidenori Sasaki, Yuki Hidaka, Hajime Igarashi, \"Prediction of IPM Machine Torque Characteristics Using Deep Learning Based on Magnetic Field Distribution,\"&nbsp;<strong><em>IEEE&nbsp;<\/em><\/strong><em><strong>Access<\/strong><\/em>, 2022.&nbsp;<a href=\"https:\/\/doi.org\/10.1109\/ACCESS.2022.3179835\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/doi.org\/10.1109\/ACCESS.2022.3179835<\/a>&nbsp;(IF: 3.367)<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"2021\">\u56fd\u969b\u4f1a\u8b70<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Yuka Kobayashi, Kazuhisa Iwata, Hidenori Sasaki, \"Optimized Design of a High-Torque-Density Permanent Magnet Synchronous Motor with Asymmetric Consequent Poles,\"2025 IEEE ENERGY CONVERSION CONGRESS &amp; EXPOSITION, philadelphia, USA,  2025\u5e7410\u670821\u65e5<\/li>\n\n\n\n<li>Yudai Suzuki, Hidenori Sasaki, \"Study on High-Precision Prediction of Static Magnetic Fields and Acceleration of Topology Optimization via Graph Neural Networks,\"18th International Workshop on Optimization and Inverse Problems in Electromagnetism, Lodz, Poland, 2025\u5e749\u670810\u65e5.<\/li>\n\n\n\n<li>Kohei NAKANO, Hidenori SASAKI, Toru MATSUURA, Kensuke SASAKI, Takashi KATO, \"Parameter and Topology Optimization of Variable Leakage Flux IPMSM Using Covariance Matrix Adaptation Evolution Strategy,\"18th International Workshop on Optimization and Inverse Problems in Electromagnetism, Lodz, Poland, 2025\u5e749\u670810\u65e5.<\/li>\n\n\n\n<li>Kohei Nakano, Hidenori Sasaki, \"Topology Optimization of Synchronous Motors using Bayesian Optimization and Variational Auto Encoder,\" 25th International Conference on the Computation of Electromagnetic Fields (Compumag 2025), Naples, Italy, 2024\u5e746\u670825\u65e5\uff0e<\/li>\n\n\n\n<li>Hiroki Kohari, Hidenori Sasaki, Masahiro Kitano, Masanori Watahiki, Tomoya Ueda, \"Parameter and Topology Optimization for Permanent Magnet Synchronous Motors Using Reinforcement Learning,\" 25th International Conference on the Computation of Electromagnetic Fields (Compumag 2025), Naples, Italy, 2024\u5e746\u670825\u65e5\uff0e<\/li>\n\n\n\n<li>Daisuke Nakagawa, Tomoya Ueda, Hidenori Sasaki, Kazuhisa Iwata, Hajime Igarashi, \"Fast Shape Optimization with Effective Shape Collapse Prevention for IPM Motors using Machine Learning,\" 25th International Conference on the Computation of Electromagnetic Fields (Compumag 2025), Naples, Italy, 2024\u5e746\u670825\u65e5\uff0e<\/li>\n\n\n\n<li>Hidenori Sasaki, Kataoka Hiroki, Yuki Sato, \"Generation Method of Equivalent Circuit for Electric Devices Considering Circuit Topology,\" 25th International Conference on the Computation of Electromagnetic Fields (Compumag 2025), Naples, Italy, 2024\u5e746\u670824\u65e5\uff0e<\/li>\n\n\n\n<li>Kazuhisa Iwata, Hidenori Sasaki,\"Motor-LIME: Interpretation Method for Motor Design Based on Deep Learning,\"21st International IGTE Symposium 2024\uff0cGraz\uff0cAustria\uff0c2024\u5e749\u670816\u65e5.<\/li>\n\n\n\n<li>Taisuke Nagayama, Hidenori Sasaki,\"Predicting Torque Characteristics of Synchronous Reluctance Motos Using Swin Transformer\"21st International IGTE Symposium 2024\uff0cGraz\uff0cAustria\uff0c2024\u5e749\u670816\u65e5.<\/li>\n\n\n\n<li>Hidenori Sasaki, Kazuhisa Iwata, Takahiro Sato, Yuki Sato,\"Motor Characteristics Map Prediction Using Deep Operator Neural Networks,\"The 21st Biennial IEEE Conference on Electromagnetic Field Computation (IEEE CEFC 2024)\uff0cJeju\uff0cKorea\uff0c2024\u5e746\u67085\u65e5.<\/li>\n\n\n\n<li>Yuki Sato, Hirokazu Matsumoto, Akito Maruo, Takahiro Sato, Hidenori Sasaki\uff0c\"Fast Analysis and Design for 3D-Structured Magnetic Components Using Surrogate Model from Transfer Learning,\"The 21st Biennial IEEE Conference on Electromagnetic Field Computation (IEEE CEFC 2024)\uff0cJeju\uff0cKorea\uff0c2024\u5e746\u67085\u65e5.<\/li>\n\n\n\n<li>Kazuki Igarashi, Hidenori Sasaki, Masahide Shioyama, Yoshifumi Okamoto\uff0c\"Magnetization Estimation for Permanent Magnet Using Convolutional Neural Network,\"The 21st Biennial IEEE Conference on Electromagnetic Field Computation (IEEE CEFC 2024)\uff0cJeju\uff0cKorea\uff0c2024\u5e746\u67084\u65e5.<\/li>\n\n\n\n<li>Kazuhisa Iwata, Hidenori Sasaki, Hajime Igarashi, Daisuke Nakagawa, Tomoya Ueda\uff0c\"Parameter and Topology Optimization Method for IPM Motors Using Multimodal Neural Network,\"The 21st Biennial IEEE Conference on Electromagnetic Field Computation (IEEE CEFC 2024)\uff0cJeju\uff0cKorea\uff0c2024\u5e746\u67083\u65e5.<\/li>\n\n\n\n<li>Tatsuya Yamaguchi, Yuki Kuroda, Yoshifumi Okamoto, Hidenori Sasaki, Koji Fujiwara,\"Acceleration of Waveform Cotrol for Measurement of Magnetic Hysteresis Based on Single Sheet Tester Using Neural Network,\"The 21st Biennial IEEE Conference on Electromagnetic Field Computation (IEEE CEFC 2024)\uff0cJeju\uff0cKorea\uff0c2024\u5e746\u67083\u65e5.<\/li>\n\n\n\n<li>Kosuke TOMOTANI, Hidenori SASAKI, Ran DONG, Soichiro IKUNO, \"Pre-Processing for Deep Learning of Motor Characteristics Using Empirical Mode Decomposition,\"PB-1a: 7, ISEM2023,Hatchioji,Japan,2023\u5e7411\u670814\u65e5.<\/li>\n\n\n\n<li>Hidenori Sasaki, Koichi Yamamura, \"Topology Optimization of Permanent Magnet Synchronous Motor with Shapley Additive Explanations, \"449, Compumag2023, Kyoto, Japan, 2023\u5e745\u670825\u65e5.<\/li>\n\n\n\n<li>Takahiro Sato, Hidenori Sasaki, Yuki Sato,\" A Fast Physics-informed Neural Network Based on Extreme Learning Machine for Solving Magnetostatic Problems,\" 381, Compumag2023, Kyoto, Japan, 2023\u5e745\u670824\u65e5.<\/li>\n\n\n\n<li>Kazuhisa Iwata, Hidenori Sasaki, Hajime Igarashi, Daisuke Nakagawa, Tomoya Ueda, \"Prediction of Interior Permanent Magnet Motor Characteristics Using CNN with Vector Input of Magnetic Flux Density Distribution,\" 438, Compumag2023, Kyoto, Japan, 2023\u5e745\u670824\u65e5.<\/li>\n\n\n\n<li>Hidenori Sasaki, Daichi Takasu, Narichika Nakamura, Yoshifumi Okamoto, \"Estimation Method for Magnetization Distribution in Permanent Magnet Using Deep Neural Network,\" CEFC2022, 353, Online, 2022\u5e7410\u670826\u65e5\uff0e<\/li>\n\n\n\n<li>Kazuki Sumi, Yoshifumi Okamoto, Koji Fujiwara, Hidenori Sasaki, \"Speedup of Flux Waveforms Control Using Deep Neural Network for Single Sheet Tester,\" CEFC2022, 345, Online, 2022\u5e7410\u670825\u65e5\uff0e<\/li>\n\n\n\n<li>Hidenori Sasaki, \"Visualization of Contributing region to Motor Characteristics Using Explainable Deep Learning,\" IGTE2022, Graz, Austria, 2022\u5e749\u670819\u65e5.<\/li>\n\n\n\n<li>Hidenori Sasaki, \"Topology Optimization for IPM Motor Using Multitask CNN Considering Current Conditions,\" Compumag2021, Online, 2022\u5e741\u670819\u65e5.<\/li>\n\n\n\n<li>Daichi Takasu, Hidenori Sasaki, Narichika Nakamura, Yoshifumi Okamoto, \"Deep Learning-based Estimation Method of Magnetization Distribution in Permanent Magnet,\" 2022 Joint MMM-Intermag Conference,&nbsp;Online, 2022\u5e741\u670810\u65e5.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"2021\">\u56fd\u5185\u4f1a\u8b70<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u5c71\u53e3\u98af\u58eb, \u5c0f\u6797\u7531\u4f73, \u5ca9\u7530\u548c\u4e45, \u4f50\u3005\u6728\u79c0\u5fb3, \u300c\u975e\u5bfe\u79f0\u30b3\u30f3\u30b7\u30af\u30a8\u30f3\u30c8\u78c1\u6975\u578b\u57cb\u8fbc\u578b\u6c38\u4e45\u78c1\u77f3\u540c\u671f\u30e2\u30fc\u30bf\u306e\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u304a\u3088\u3073\u5b9f\u6a5f\u691c\u8a3c,\u300d \u4ee4\u548c8\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a,  \u4ed9\u53f0\uff0c2026\u5e743\u670813\u65e5\uff0e<\/li>\n\n\n\n<li>\u4e0a\u91ce\u7950\u57fa, \u4f50\u3005\u6728\u79c0\u5fb3, \u4e94\u5341\u5d50\u4e00, \u4e2d\u5ddd\u5927\u8f14, \u4e0a\u7530\u667a\u54c9, \u300c\u30a2\u30ad\u30b7\u30e3\u30eb\u30d5\u30e9\u30c3\u30af\u30b9\u30e2\u30fc\u30bf\u306e\u4e09\u6b21\u5143\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e,\u300d \u96fb\u6c17\u5b66\u4f1a \u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a, \u5ddd\u8d8a\uff0c 2026\u5e743\u67086\u65e5\uff0e<\/li>\n\n\n\n<li>\u95a2\u5c71 \u822a, \u4f50\u3005\u6728 \u79c0\u5fb3, \u5742\u672c \u5b8f\u7d00, \u9ad8\u6a4b \u614e\u77e2\uff0c\u300c\u2f24\u898f\u6a21\u2f94\u8a9e\u30e2\u30c7\u30eb\u3092\u2f64\u3044\u305f\u57cb\u8fbc\u578b\u6c38\u4e45\u78c1\u2f6f\u540c\u671f\u30e2\u30fc\u30bf\u306e \u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d\uff0cMAGDA2025\uff0c\u677e\u672c\uff0c\u9577\u91ce\uff0c 2025\u5e7411\u670810\u65e5\uff0e<\/li>\n\n\n\n<li>\u77e2\u91ce \u884c\u7950, \u4f50\u3005\u6728 \u79c0\u5fb3, \u4e2d\u897f\u5d07\u6587, \u751f\u91ce \u58ee\u4e00\u90ce\uff0c\u300cApproximate Inverse Model Explanations\u3092\u2f64\u3044\u305f\u57cb\u8fbc\u578b \u6c38\u4e45\u78c1\u2f6f\u540c\u671f\u30e2\u30fc\u30bf\u30c8\u30eb\u30af\u63a8\u5b9a\u30e2\u30c7\u30eb\u306e\u89e3\u91c8\u300d\uff0cMAGDA2025\uff0c\u677e\u672c\uff0c\u9577\u91ce\uff0c 2025\u5e7411\u670810\u65e5\uff0e<\/li>\n\n\n\n<li>\u7530\u4e2d \u62d3\u6d77, \u4f0a\u85e4 \u6167\u609f, \u4f50\u85e4 \u4f51\u6a39, \u677e\u672c \u6d0b\u548c, \u4f50\u85e4 \u5b5d\u6d0b, \u4f50\u3005\u6728 \u79c0\u5fb3\uff0c\u300c\u2fae\u63a5\u89e6\u754c\u78c1\u7d66\u96fb\u7cfb\u3092\u6709\u3057\u305f\u6ce2\u2f12\u767a\u96fb\u6a5f\u306e\u57fa\u790e\u691c\u8a0e\u300d\uff0cMAGDA2025\uff0c\u677e\u672c\uff0c\u9577\u91ce\uff0c 2025\u5e7411\u670810\u65e5\uff0e<\/li>\n\n\n\n<li>\u9577\u5c71\u6cf0\u8f14, \u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300cNeural Field\u3092\u7528\u3044\u305f\u30b7\u30f3\u30af\u30ed\u30ca\u30b9\u30ea\u30e9\u30af\u30bf\u30f3\u30b9\u30e2\u30fc\u30bf\u306e\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d\uff0c\u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a\uff0cSA-25-114\uff0cRM-25-126, \u79cb\u7530\uff0c 2025\u5e748\u670827\u65e5.<\/li>\n\n\n\n<li>\u4e2d\u91ce\u7693\u5e73, \u4f50\u3005\u6728\u79c0\u5fb3, \u677e\u6d66 \u900f, \u4f50\u3005\u6728\u5065\u4ecb, \u52a0\u85e4 \u5d07\uff0c\u300c\u53ef\u5909\u6f0f\u308c\u78c1\u675f\u578b\u6c38\u4e45\u78c1\u77f3\u540c\u671f\u30e2\u30fc\u30bf\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fb\u30c8\u30dd\u30ed\u30b8\u30fc\u540c\u6642\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u691c\u8a0e\u300d\uff0c2025\u5e74\u96fb\u6c17\u5b66\u4f1a\u7523\u696d\u5fdc\u7528\u90e8\u9580\u5927\u4f1a\uff0c3-3\uff0c\u5fb3\u5cf6\uff0c 2025\u5e748\u670819\u65e5\uff0e<\/li>\n\n\n\n<li>\u7247\u5ca1 \u512a\u6597, \u4f50\u3005\u6728 \u79c0\u5fb3\uff0c\u300c\u5b9f\u6570\u5024\u907a\u4f1d\u7684\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u7528\u3044\u305f \u56de\u8def\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d\uff0c\u4ee4\u548c7\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c\u6771\u4eac\uff0c2025\u5e743\u670819\u65e5\uff0e<\/li>\n\n\n\n<li>\u95a2\u53e3\u6c50\u97f3\uff0c\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300cCNN-LSTM\u3092\u6d3b\u7528\u3057\u305f\u6bb5\u30b9\u30ad\u30e5\u30fcIPMSM\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306e\u9ad8\u901f\u5316\u306b\u95a2\u3059\u308b\u691c\u8a0e\u300d\uff0c\u4ee4\u548c7\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c\u6771\u4eac\uff0c2025\u5e743\u670819\u65e5\uff0e<\/li>\n\n\n\n<li>\u95a2\u5c71 \u822a, \u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300c42\u697536\u30b9\u30ed\u30c3\u30c8\u30a2\u30a6\u30bf\u30fc\u30ed\u30fc\u30bf\u578b\u6c38\u4e45\u78c1\u77f3\u540c\u671f\u30e2\u30fc\u30bf\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30c8\u30dd\u30ed\u30b8\u30fc\u540c\u6642\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u691c\u8a0e\u300d\uff0c\u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a\uff0cSA-25-042, RM-25-042, \u9577\u5d0e\uff0c 2025\u5e743\u67087\u65e5.<\/li>\n\n\n\n<li>\u4e2d\u91ce\u7693\u5e73, \u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300c\u5909\u5206\u30aa\u30fc\u30c8\u30a8\u30f3\u30b3\u30fc\u30c0\u3068\u30d9\u30a4\u30ba\u6700\u9069\u5316\u3092\u7528\u3044\u305f\u30d1\u30e9\u30e1\u30fc\u30bf\u30c8\u30dd\u30ed\u30b8\u30fc\u540c\u6642\u6700\u9069\u5316\u306e\u9ad8\u901f\u5316\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d\uff0c\u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a\uff0cSA-25-041, RM-25-041, \u9577\u5d0e\uff0c 2025\u5e743\u67087\u65e5.<\/li>\n\n\n\n<li>\u5c0f\u64ad\u512a\u8cb4, \u4f50\u3005\u6728\u79c0\u5fb3, \u5317\u91ce\u771f\u5f18, \u7dbf\u5f15\u6b63\u502b, \u4e0a\u7530\u667a\u54c9\uff0c\u300c\u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u3092\u7528\u3044\u305f\u6c38\u4e45\u78c1\u77f3\u540c\u671f\u30e2\u30fc\u30bf\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fb\u30c8\u30dd\u30ed\u30b8\u30fc\u540c\u6642\u6700\u9069\u5316\u300d\uff0c\u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a\uff0cSA-25-032, RM-25-032, \u9577\u5d0e\uff0c 2025\u5e743\u67087\u65e5.<\/li>\n\n\n\n<li>\u4e2d\u5ddd\u5927\u8f14, \u4e0a\u7530\u667a\u54c9, \u4f50\u3005\u6728\u79c0\u5fb3, \u5ca9\u7530\u548c\u4e45, \u4e94\u5341\u5d50\u4e00\uff0c\u300c\u6a5f\u68b0\u5b66\u7fd2\u3092\u7528\u3044\u305fIPM\u30e2\u30fc\u30bf\u306e\u52b9\u7387\u7684\u306a\u5f62\u72b6\u5d29\u58ca\u9632\u6b62\u306b\u3088\u308b\u9ad8\u901f\u5f62\u72b6\u6700\u9069\u5316\u300d\uff0c\u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a\uff0cSA-25-031, RM-25-031, \u9577\u5d0e\uff0c 2025\u5e743\u67087\u65e5.<\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3, \u7247\u5ca1\u512a\u6597, \u4f50\u85e4\u4f51\u6a39\uff0c\u300c\u56de\u8def\u30c8\u30dd\u30ed\u30b8\u30fc\u3092\u8003\u616e\u3057\u305f\u7b49\u4fa1\u56de\u8def\u751f\u6210\u624b\u6cd5\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d\uff0c\u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a\uff0cSA-25-009, RM-25-009, \u9577\u5d0e\uff0c 2025\u5e743\u67086\u65e5.<\/li>\n\n\n\n<li>\u9234\u6728\u52c7\u5927, \u9577\u5c71\u6cf0\u8f14, \u4f50\u3005\u6728\u79c0\u5fb3,\u300c\u30b0\u30e9\u30d5\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u2f64\u3044\u305f\u57cb\u8fbc\u78c1\u2f6f\u578b\u540c\u671f\u30e2\u30fc\u30bf\u306e\u7279\u6027\u2fbc\u7cbe\u5ea6\u4e88\u6e2c\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d,MAGDA2024,OS-4-7,\u6771\u4eac, 2024\u5e7411\u670818\u65e5.<\/li>\n\n\n\n<li>\u4e2d\u91ce \u7693\u5e73, \u4f50\u3005\u6728\u79c0\u5fb3,\u300c\u30d9\u30a4\u30ba\u6700\u9069\u5316\u3092\u2f64\u3044\u305f\u540c\u671f\u30e2\u30fc\u30bf\u306e\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e \u300d&nbsp;,MAGDA2024,OS-4-4,\u6771\u4eac, 2024\u5e7411\u670818\u65e5.<\/li>\n\n\n\n<li>\u5c0f\u6797\u7531\u4f73, \u5ca9\u7530\u548c\u4e45, \u4f50\u3005\u6728\u79c0\u5fb3, \u300cCMA-ES\u306b\u3088\u308b\u975e\u5bfe\u79f0\u30b3\u30f3\u30b7\u30af\u30a8\u30f3\u30c8\u78c1\u6975\u3092\u8003\u616e\u3057\u305f\u57cb\u8fbc\u578b\u6c38\u4e45\u78c1\u77f3\u540c\u671f\u30e2\u30fc\u30bf\u306e\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d, \u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a, SA-24-069, RM-24-107, \u672d\u5e4c\uff0c2024\u5e749\u670811\u65e5.<\/li>\n\n\n\n<li>\u5c71\u6751\u5b5d\u5e02, \u4f50\u3005\u6728\u79c0\u5fb3, \u300cSHAP\u306b\u3088\u308b\u96fb\u6d41\u6761\u4ef6\u3092\u8003\u616e\u3057\u305f\u57cb\u8fbc\u578b\u6c38\u4e45\u78c1\u77f3\u540c\u671f\u30e2\u30fc\u30bf\u306e\u30c8\u30eb\u30af\u5bc4\u4e0e\u9818\u57df\u53ef\u8996\u5316\u624b\u6cd5\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d, \u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a, SA-24-064, RM-24-102, \u672d\u5e4c\uff0c2024\u5e749\u670811\u65e5.<\/li>\n\n\n\n<li>\u5ca9\u7530\u548c\u4e45, \u4f50\u3005\u6728\u79c0\u5fb3, \u300c\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u8a2d\u8a08\u306b\u7279\u5316\u3057\u305f\u7279\u6027\u5bc4\u4e0e\u9818\u57df\u53ef\u8996\u5316\u624b\u6cd5\u306b\u95a2\u3059\u308b\u691c\u8a0e\uff1aDesign-LIME\u300d, \u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a, SA-24-063, RM-24-101, \u672d\u5e4c\uff0c2024\u5e749\u670811\u65e5.<\/li>\n\n\n\n<li>\u5c71\u53e3\u9054\u4e5f, \u9ed2\u7530\u512a\u8f1d, \u5ca1\u672c\u5409\u53f2, \u4f50\u3005\u6728\u79c0\u5fb3, \u85e4\u539f\u8015\u4e8c\uff0c\u300cNeural Network\u3092\u7528\u3044\u305f\u5358\u677f\u78c1\u6c17\u8a66\u9a13\u5668\u306b\u304a\u3051\u308b\u6ce2\u5f62\u5236\u5fa1\u306e\u9ad8\u901f\u5316\u306b\u95a2\u3059\u308b\u691c\u8a0e \u300d\uff0c\u4ee4\u548c6\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c\u5fb3\u5cf6\u5927\u5b66\uff0c 2024\u5e743\u670816\u65e5\uff0e<\/li>\n\n\n\n<li>\u7530\u4e2d\u99ff\u4e5f, \u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300c\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u62e1\u5f35\u73fe\u5b9f\u6280\u8853\u3092\u7528\u3044\u305f\u4e8c\u6b21\u5143\u975e\u7dda\u5f62\u78c1\u754c\u53ef\u8996\u5316\u306e\u9ad8\u901f\u5316\u306b\u95a2\u3059\u308b\u691c\u8a0e \u300d\uff0c\u4ee4\u548c6\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c3-084\uff0c\u5fb3\u5cf6\u5927\u5b66\uff0c 2024\u5e743\u670816\u65e5\uff0e<\/li>\n\n\n\n<li>\u9234\u6728\u52c7\u5927, \u4f50\u3005\u6728\u79c0\u5fb3, \u4f50\u85e4\u5b5d\u6d0b, \u4f50\u85e4\u4f51\u6a39\uff0c\u300cPhysics Informed Neural Networks\u3092\u7528\u3044\u305f\u4e8c\u6b21\u5143\u9759\u78c1\u754c\u63a8\u5b9a\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e \u300d\uff0c\u4ee4\u548c6\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c3-085\uff0c\u5fb3\u5cf6\u5927\u5b66\uff0c 2024\u5e743\u670816\u65e5\uff0e<\/li>\n\n\n\n<li>\u95a2\u53e3\u6c50\u97f3, \u4f50\u3005\u6728\u79c0\u5fb3, \u65e5\u9ad8\u52c7\u6c17\uff0c\u300c\u4e3b\u6210\u5206\u5206\u6790\u3092\u6d3b\u7528\u3057\u305fCNN\u306b\u3088\u308bSynRM\u306e\u7279\u6027\u4e88\u6e2c\u624b\u6cd5\u306b\u95a2\u3059\u308b\u691c\u8a0e \u300d\uff0c\u4ee4\u548c6\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c5-038\uff0c\u5fb3\u5cf6\u5927\u5b66\uff0c 2024\u5e743\u670814\u65e5\uff0e<\/li>\n\n\n\n<li>\u5c0f\u6797\u7531\u4f73, \u5ca9\u7530\u548c\u4e45, \u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300c\u975e\u5bfe\u79f0\u30b3\u30f3\u30b7\u30af\u30a8\u30f3\u30c8\u78c1\u6975\u3092\u6709\u3059\u308b\u57cb\u8fbc\u578b\u6c38\u4e45\u78c1\u77f3\u540c\u671f\u30e2\u30fc\u30bf\u306e\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316 \u300d\uff0c\u4ee4\u548c6\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c5-026\uff0c\u5fb3\u5cf6\u5927\u5b66\uff0c 2024\u5e743\u670814\u65e5\uff0e<\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3, \u9234\u6728\u52c7\u5927, \u4f50\u85e4\u5b5d\u6d0b, \u4f50\u85e4\u4f51\u6a39\uff0c\u300cPhysics Informed Neural Networks\u3068\u6709\u9650\u8981\u7d20\u3092\u7528\u3044\u305f\u9759\u78c1\u754c\u89e3\u6790\u624b\u6cd5\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e \u300d\uff0c\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a\uff0cSA-24-009\uff0fRM-24-009\uff0c\u9752\u5c71\u5b66\u9662\u5927\u5b66\uff0c2024\u5e743\u67084\u65e5\uff0e<\/li>\n\n\n\n<li>\u91ce\u53e3\u6176\u559c, \u5ca9\u7530\u548c\u4e45, \u4f50\u3005\u6728\u79c0\u5fb3,\u300c\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u56de\u8ee2\u6a5f\u306e\u30c8\u30eb\u30af\u6ce2\u5f62\u9ad8\u901f\u4e88\u6e2c\u30e2\u30c7\u30eb\u306b\u95a2\u3059\u308b\u691c\u8a0e \u300d,MAGDA2023,OS-4-10,\u91d1\u6ca2, 2023\u5e7411\u670827\u65e5.<\/li>\n\n\n\n<li>\u9577\u5c71\u6cf0\u8f14, \u4f50\u3005\u6728\u79c0\u5fb3,\u300c\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u5fdc\u529b\u3068\u78c1\u754c\u3092\u8003\u616e\u3057\u305f\u30b7\u30f3\u30af\u30ed\u30ca\u30b9\u30ea\u30e9\u30af\u30bf\u30f3\u30b9\u30e2\u30fc\u30bf\u306e\u8a2d\u8a08\u9818\u57df\u53ef\u5909\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u691c\u8a0e \u300d&nbsp;,MAGDA2023,OS-4-9,\u91d1\u6ca2, 2023\u5e7411\u670827\u65e5.<\/li>\n\n\n\n<li>\u9786\u8c37\u5b5d\u7950, \u4f50\u3005\u6728\u79c0\u5fb3, \u300c\u30ae\u30e3\u30c3\u30d7\u78c1\u675f\u5bc6\u5ea6\u5206\u5e03\u3092\u6d3b\u7528\u3057\u305f\u56de\u8ee2\u6a5f\u7279\u6027\u3092\u63a8\u5b9a\u3059\u308b\u6df1\u5c64\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u7cbe\u5ea6\u5411\u4e0a\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d,2023\u5e74 \u96fb\u6c17\u5b66\u4f1a \u96fb\u5b50\u30fb\u60c5\u5831\u30fb\u30b7\u30b9\u30c6\u30e0\u90e8\u9580\u5927\u4f1a, MC2-5, \u672d\u5e4c, 2023\u5e749\u67081\u65e5.<\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3, \u5ca9\u7530\u548c\u4e45, \u4f50\u85e4\u5b5d\u6d0b, \u4f50\u85e4\u4f51\u6a39, \u300c\u7573\u8fbc\u307f\u51e6\u7406\u3092\u6d3b\u7528\u3057\u305fDeep Operator Network\u306b\u3088\u308b\u30e2\u30fc\u30bf\u30c8\u30eb\u30af\u30de\u30c3\u30d7\u63a8\u5b9a\u306b\u95a2\u3059\u308b\u691c\u8a0e\u300d, \u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a, SA-23-079, RM-23-078, \u9577\u5ca1\uff0c2023\u5e748\u670829\u65e5.<\/li>\n\n\n\n<li>\u5ca9\u7530\u548c\u4e45, \u4f50\u3005\u6728\u79c0\u5fb3, \u4e94\u5341\u5d50\u4e00, \u4e2d\u5ddd\u5927\u8f14, \u4e0a\u7530\u667a\u54c9, \u300c\u6df1\u5c64\u5b66\u7fd2\u3068\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u3092\u4f75\u7528\u3057\u305f\u96fb\u6c17\u6a5f\u5668\u69cb\u9020\u306e\u9ad8\u901f\u9006\u89e3\u6790\u624b\u6cd5\u306b\u95a2\u3059\u308b\u691c\u8a0e\u300d, \u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a, SA-23-074, RM-23-073, \u9577\u5ca1\uff0c2023\u5e748\u670829\u65e5.<\/li>\n\n\n\n<li>\u4f50\u85e4\u5b5d\u6d0b, \u4f50\u85e4\u4f51\u6a39, \u4f50\u3005\u6728\u79c0\u5fb3, \u300cDeep Operator Network\u3092\u7528\u3044\u305f\u5fdc\u7b54\u5c40\u9762\u4f5c\u6210\u306b\u95a2\u3059\u308b\u691c\u8a0e\u300d, \u96fb\u6c17\u5b66\u4f1a\u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a, SA-23-067, RM-23-066, \u9577\u5ca1\uff0c2023\u5e748\u670828\u65e5.<\/li>\n\n\n\n<li>\u4e94\u5341\u5d50\u4e00\u8f1d, \u4f50\u3005\u6728\u79c0\u5fb3, \u5869\u5c71\u5c06\u82f1, \u5ca1\u672c\u5409\u53f2,\u300c\u7573\u307f\u8fbc\u307f\u51e6\u7406\u3092\u6d3b\u7528\u3057\u305f\u6df1\u5c64\u5b66\u7fd2\u30e2\u30c7\u30eb\u306b\u3088\u308b\u6c38\u4e45\u78c1\u77f3\u5185\u90e8\u78c1\u5316\u5206\u5e03\u306e\u9006\u63a8\u5b9a\u300d,2023\u5e74\u96fb\u6c17\u5b66\u4f1a\u7523\u696d\u5fdc\u7528\u90e8\u9580\u5927\u4f1a, Y-112, \u540d\u53e4\u5c4b\u5de5\u696d\u5927\u5b66\uff0c2023\u5e748\u670822\u65e5.<\/li>\n\n\n\n<li>\u4e94\u5341\u5d50\u4e00\u8f1d\uff0c\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u5869\u5c71\u5c06\u82f1\uff0c\u4e2d\u6751\u52e2\u5230\uff0c\u5ca1\u672c\u5409\u53f2\uff0c\u300c\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u975e\u7834\u58ca\u306b\u3088\u308b\u6c38\u4e45\u78c1\u77f3\u306e\u78c1\u5316\u9006\u63a8\u5b9a\u300d\uff0c\u4ee4\u548c5\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c2\u208b086\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c2023\u5e743\u670817\u65e5.<\/li>\n\n\n\n<li>\u9786\u8c37\u5b5d\u7950\uff0c\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u751f\u91ce\u58ee\u4e00\u90ce\uff0c\u8463\u3000\u7136\uff0c\u300c\u7d4c\u9a13\u7684\u30e2\u30fc\u30c9\u5206\u89e3\u3092\u7528\u3044\u305f\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u30e2\u30fc\u30bf\u7279\u6027\u63a8\u5b9a\u7cbe\u5ea6\u5411\u4e0a\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d\uff0c\u4ee4\u548c5\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c5\u208b058\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c2023\u5e743\u670817\u65e5.<\/li>\n\n\n\n<li>\u5c71\u6751\u5b5d\u5e02\uff0c\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300cSHAP\u306b\u3088\u308bIPMSM\u306e\u30c8\u30eb\u30af\u30ea\u30d7\u30eb\u5bc4\u4e0e\u9818\u57df\u306e\u53ef\u8996\u5316\u300d\uff0c\u4ee4\u548c5\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff0c5-045\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c2023\u5e743\u670815\u65e5.<\/li>\n\n\n\n<li>\u5ca9\u7530\u548c\u4e45\uff0c\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u300c\u30b3\u30f3\u30b7\u30af\u30a8\u30f3\u30c8\u30dd\u30fc\u30eb\u578b\u6c38\u4e45\u78c1\u77f3\u540c\u671f\u30e2\u30fc\u30bf\u306e\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d,\u96fb\u6c17\u5b66\u4f1a \u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a,SA-23-025\/RM-23-025,\u6771\u6d77\u5927\u5b66,2023\u5e743\u67083\u65e5.<\/li>\n\n\n\n<li>\u4f50\u85e4\u5b5d\u6d0b\uff0c\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u4f50\u85e4\u4f51\u6a39\uff0c\u300cExtreme Learning Machine\u3092\u7528\u3044\u305f\u78c1\u754c\u7cfbPhysics-informed\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u691c\u8a0e\u300d\uff0c\u96fb\u6c17\u5b66\u4f1a \u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a,SA-23-023\/RM-23-023,\u6771\u6d77\u5927\u5b66,2023\u5e743\u67083\u65e5.<\/li>\n\n\n\n<li>\u5ca9\u2f65 \u548c\u4e45\uff0c\u4f50\u3005\u2f4a \u79c0\u5fb3 \uff0c\u4e94\u2f17\u5d50 \u2f00\uff0c\u4e2d\u5ddd \u2f24\u8f14\uff0c\u4e0a\u2f65 \u667a\u54c9\uff0c\u300c\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u78c1\u2f6f\u4f4d\u7f6e\u3068\u78c1\u6027\u4f53\u5f62\u72b6\u306e\u5909\u5316\u3092\u540c\u6642\u8003\u616e\u3057\u305fIPMSM\u306e\u7279\u6027\u63a8\u5b9a\u306b\u95a2\u3059\u308b\u691c\u8a0e\u300d\uff0cMAGDA2022\uff0cOS-4-15\uff0c\u9e7f\u5150\u5cf6\uff0c2022\u5e7411\u67081\u65e5\uff0e<\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3, \u300cSHAP\u306b\u3088\u308b\u6df1\u5c64\u5b66\u7fd2\u8aac\u660e\u6027\u3092\u4f75\u7528\u3057\u305fIPMSM\u306e\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u300d, \u96fb\u6c17\u5b66\u4f1a \u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a,&nbsp;\u8fd1\u757f\u5927\u5b66,&nbsp;2022\u5e749\u670830\u65e5.<\/li>\n\n\n\n<li>\u4e2d\u5ddd\u5927\u8f14, \u4e0a\u7530\u667a\u54c9,\u3000\u4f50\u3005\u6728\u79c0\u5fb3, \u4e94\u5341\u5d50\u4e00,  \u81ea\u52d5\u8eca\u99c6\u52d5\u7528\u30e2\u30fc\u30bf\u306b\u304a\u3051\u308b\u78c1\u6c17\u56de\u8def\u8a2d\u8a08\u306e\u81ea\u52d5\u5316\u3068\u9ad8\u901f\u5316\u306b\u5411\u3051\u305f\u30e2\u30fc\u30bf\u306e\u78c1\u6c17\u7279\u6027\u4e88\u6e2c\u306e\u691c\u8a0e \u7b2c2\u5831\u300d, \u96fb\u6c17\u5b66\u4f1a \u9759\u6b62\u5668\/\u56de\u8ee2\u6a5f\u5408\u540c\u7814\u7a76\u4f1a,&nbsp;\u8fd1\u757f\u5927\u5b66,&nbsp;2022\u5e749\u670830\u65e5.<\/li>\n\n\n\n<li>\u4f50\u3005\u6728\u79c0\u5fb3\uff0c\u4e94\u5341\u5d50\u4e00\uff0c\u4e2d\u5ddd\u5927\u8f14\uff0c\u4e0a\u7530\u667a\u54c9\uff0c\u300c\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u30e2\u30fc\u30bf\u69cb\u9020\u306e\u591a\u6bb5\u968e\u30c8\u30dd\u30ed\u30b8\u30fc\u6700\u9069\u5316\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u300d\uff0c\u4ee4\u548c4\u5e74\u5ea6\u96fb\u6c17\u5b66\u4f1a\u7523\u696d\u5fdc\u7528\u90e8\u9580\u5927\u4f1a\uff0c\u4e0a\u667a\u5927\u5b66\uff0c3-70\uff0c2022\u5e749\u67081\u65e5.<\/li>\n\n\n\n<li>\u89d2 \u548c\u6a39, \u5ca1\u672c\u5409\u53f2, \u85e4\u539f\u8015\u4e8c, \u4f50\u3005\u6728\u79c0\u5fb3, \u300cDeep Neural Network\u3092\u7528\u3044\u305f\u521d\u671f\u6ce2\u5f62\u63a8\u5b9a\u306b\u3088\u308b\u5358\u677f\u78c1\u6c17\u8a66\u9a13\u5668\u306b\u304a\u3051\u308b\u78c1\u675f\u6ce2\u5f62\u5236\u5fa1\u306e\u9ad8\u901f\u5316\u306b\u95a2\u3059\u308b\u691c\u8a0e\u300d,\u4ee4\u548c4\u5e74\u96fb\u6c17\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a,&nbsp;Online,&nbsp;2022\u5e743\u670821\u65e5.<\/li>\n\n\n\n<li>\u4e2d\u5ddd\u5927\u8f14, \u4e0a\u7530\u667a\u54c9, \u4f50\u3005\u6728\u79c0\u5fb3, \u4e94\u5341\u5d50\u4e00,\u300c\u81ea\u52d5\u8eca\u99c6\u52d5\u7528\u30e2\u30fc\u30bf\u306b\u304a\u3051\u308b\u78c1\u6c17\u56de\u8def\u8a2d\u8a08\u306e\u81ea\u52d5\u5316\u3068\u9ad8\u901f\u5316\u306b\u5411\u3051\u305f\u30e2\u30fc\u30bf\u306e\u78c1\u6c17\u7279\u6027\u4e88\u6e2c\u306e\u691c\u8a0e\u300d,\u96fb\u6c17\u5b66\u4f1a 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