{"id":12715,"date":"2021-07-09T19:04:55","date_gmt":"2021-07-09T10:04:55","guid":{"rendered":"https:\/\/adc-japan.com\/uk\/?p=12715"},"modified":"2026-10-20T16:20:19","modified_gmt":"2026-10-20T07:20:19","slug":"ang-uchida-kraepelin-test-at-digital-transformation-dx","status":"publish","type":"post","link":"https:\/\/adc-japan.com\/uk\/tl\/tips-tl\/12715.html","title":{"rendered":"Ang Uchida-Kraepelin Test at Digital na Pagbabago (DX)"},"content":{"rendered":"<aside class=\"uk-ai-translation-notice\" lang=\"tl\" style=\"box-sizing:border-box;clear:both;margin:0 0 1.5em;padding:1em;border:1px solid #ccd5de;border-left:4px solid #486581;background:#f4f7fa;color:#243746;font-size:14px;line-height:1.8;overflow-wrap:anywhere;\">\n<p style=\"margin:0;\">Awtomatikong isinalin ang pahinang ito mula sa orihinal na wikang Hapon gamit ang generative AI. Maaaring may mga pagkakamali sa salin. Mangyaring makipag-ugnayan sa amin upang kumpirmahin ang mahahalagang impormasyon.<\/p>\n<\/aside>\n<h3>Paggamit ng DX para sa mga katangian ng tao<\/h3>\n<p>Ang Uchida-Kraepelin Test ay angkop na angkop sa paghawak ng mga katangian ng kakayahan at personalidad\/pag-uugali ng tao sa digital transformation (DX).<\/p>\n<h3>Ano ang DX?<\/h3>\n<p>Ang digital transformation ay ang ideyang <strong><span style=\"color: #ff6600;\">binabago ng paglaganap ng IT ang buhay ng tao tungo sa ikabubuti sa lahat ng aspeto<\/span><\/strong>. Karaniwang iniuugnay ang konsepto kay Propesor Erik Stolterman ng Ume\u00e5 University sa Sweden noong 2004, at pinaikli bilang DX.<\/p>\n<p>Ganito inilalarawan ng Ministry of Economy, Trade and Industry ng Japan ang DX sa mga gabay nito (paglalahad sa ibang pananalita):<\/p>\n<p><span style=\"color: #ff6600;\"><strong>Tumutugon ang mga negosyo sa mabilis na pagbabago ng kapaligiran sa pamamagitan ng datos at digital na teknolohiya upang baguhin ang mga produkto, serbisyo at modelo ng negosyo ayon sa pangangailangan ng mamimili at lipunan. Kasabay nitong binabago ang gawain, organisasyon, proseso at kultura ng kompanya para magkaroon ng kalamangan sa kompetisyon.<\/strong><\/span><\/p>\n<h3>Ang Uchida-Kraepelin Test at DX<\/h3>\n<p>Dahil papel at lapis ang gamit, tila walang kaugnayan sa digital na teknolohiya ang Uchida-Kraepelin Test.<br \/>\nNgunit ang natatanging paraang binubuo lamang ng pagdaragdag ng mga numero at paghawak ng datos sa dami ng trabaho at mali bawat minuto ay likas na digital.<br \/>\nAng mga graph at teksto sa ulat ng pagtatasa ay biswal na anyo lamang ng digital na datos upang madaling mabasa ng tao.<\/p>\n<figure class=\"uk-dx-image\" style=\"margin:0 0 24px;\"><a href=\"https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-tl.png\"><img decoding=\"async\" width=\"1680\" height=\"830\" class=\"wp-image-12042 alignnone\" src=\"https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-tl.png\" alt=\"Uchida-Kraepelin Test: pagdigitisa ng kakayahan at katangian ng pag-uugali; Big data\" style=\"max-width:100%;height:auto;width:600px;\" srcset=\"https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-tl.png 1680w, https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-tl-300x148.png 300w, https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-tl-1024x506.png 1024w, https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-tl-768x379.png 768w, https:\/\/adc-japan.com\/uk\/wp-content\/uploads\/2026\/10\/uk-applications-tl-1536x759.png 1536w\" sizes=\"(max-width: 1680px) 100vw, 1680px\" \/><\/a><figcaption>\n<details>\n<summary>Uchida-Kraepelin Test: pagdigitisa ng kakayahan at katangian ng pag-uugali<\/summary>\n<div class=\"uk-dx-diagram\" style=\"max-width:600px;border:1px solid #ccc;padding:16px;box-sizing:border-box;line-height:1.7;overflow-wrap:anywhere;\">\n<p style=\"background:#20478f;color:#fff;padding:12px;text-align:center;\"><strong>Uchida-Kraepelin Test: pagdigitisa ng kakayahan at katangian ng pag-uugali<\/strong><br \/>\u2193<br \/>Raw data ng resulta ng pagsusulit<\/p>\n<p style=\"background:#e7f0f5;padding:12px;text-align:center;\"><strong>Big data<\/strong><br \/>&#x2194; Ihambing sa klinikal na datos<br \/>\u2193 Bumuo at mag-update ng mga modelo ng pagtatasa<br \/>Mga resulta mula sa iba&#x27;t ibang modelo<\/p>\n<ul style=\"margin-bottom:0;\">\n<li>Tamang tao sa tamang gawain: pagtatasa sa pagkuha, pagtatalaga at paglilipat<\/li>\n<li>Pamamahala sa kaligtasan: pag-iwas sa aksidente at sistema ng lisensiya<\/li>\n<li>Edukasyon at pagsasanay: pagpaplano, gabay sa karagdagang pag-aaral, edukasyong panlipunan at suporta sa karera<\/li>\n<li>Kalusugang pangkaisipan: emosyonal na suporta, pagtatasa sa kalusugan at tulong sa pagbabalik-trabaho<\/li>\n<\/ul>\n<\/div>\n<\/details>\n<\/figcaption><\/figure>\n<p>Pangunahing nagbibigay ang test ng dalawang uri ng datos:<\/p>\n<ol>\n<li>Raw data gaya ng dami ng trabaho at bilang ng mali bawat minuto, at edad<\/li>\n<li>Datos ng resulta kapag ipinadaan ang raw data sa modelo ng pagtatasa<\/li>\n<\/ol>\n<p>Ang modelo ng pagtatasa ay isang function na nabubuo sa paghahambing ng raw data at klinikal na datos, tulad ng karaniwang asal sa trabaho, estilo ng pag-aaral, kaangkupan sa partikular na gawain, aksidente at kalusugan. Patuloy itong ina-update upang umangkop sa mga layuning nagbabago sa panahon.<\/p>\n<p>Nagbibigay ang cloud assessment service ng Uchida-Kraepelin ng CSV file na naglalaman ng mga resulta ng isang partikular na modelong inilapat sa raw data.<\/p>\n<p>Kung may angkop nang modelo, maaaring gamitin ang resulta nito. Kung wala, maaaring suriin ng AI ang ugnayan ng klinikal na datos at raw data o dati nang mga resulta para makabuo ng bagong modelo.<\/p>\n<p>Isaalang-alang ang test para sa inyong mga inisyatibang DX.<\/p>\n<h3>Panukalang DX: paggamit ng test upang makatulong sa pagbabawas ng aksidente sa kalsada<\/h3>\n<p>Kasama sa SDG 3 para sa kalusugan at kagalingan ng lahat ang target 3.6 na bawasan nang kalahati ang pagkamatay at pinsala sa aksidente sa kalsada. Ang orihinal na takdang taon nito ay 2020. Sa maraming hakbang sa kaligtasan, tingnan natin ang maaaring gamit ng Uchida-Kraepelin Test.<\/p>\n<p>Kailangang siyasatin kung may korelasyon ang kakayahan, personalidad at pag-uugali sa aksidente. Iniulat ng orihinal na artikulo ang magkaibang distribusyon ng mga katangian sa resulta ng mga dating nakapagdulot ng malubhang aksidente at ng mga hindi kailanman nakapagdulot nito.<\/p>\n<p>Sa pansamantalang pamantayan ng pagtatasa para ihiwalay ang mas mababa at mas mataas na tendensiya ng panganib, ginamit ang aktuwal na datos para hatiin ang bawat populasyon sa A at B gaya ng talahanayan.<\/p>\n<div class=\"uk-dx-data-table\" tabindex=\"0\" role=\"region\" aria-label=\"Halimbawa sa kaligtasan sa kalsada: paghahambing ng mga grupo\" style=\"max-width:100%;overflow-x:auto;\">\n<table style=\"min-width:420px;width:100%;\" border=\"0\" cellspacing=\"0\" cellpadding=\"0\">\n<tbody>\n<tr style=\"height: 18.0pt;\">\n<td class=\"xl65\" style=\"height: 18pt; width: 52pt; text-align: center;\" width=\"69\" height=\"24\"><\/td>\n<td class=\"xl65\" style=\"border-left: none; width: 52pt; text-align: center;\" align=\"left\" width=\"69\">Grupong may aksidente<\/td>\n<td class=\"xl65\" style=\"border-left: none; width: 52pt; text-align: center;\" align=\"left\" width=\"69\">Grupong walang aksidente<\/td>\n<\/tr>\n<tr style=\"height: 18.0pt;\">\n<td class=\"xl65\" style=\"height: 18pt; border-top: none; text-align: center;\" align=\"left\" height=\"24\">Grupo A<\/td>\n<td class=\"xl66\" style=\"border-top: none; border-left: none; text-align: center;\" align=\"right\">38%<\/td>\n<td class=\"xl66\" style=\"border-top: none; border-left: none; text-align: center;\" align=\"right\">76%<\/td>\n<\/tr>\n<tr style=\"height: 18.0pt;\">\n<td class=\"xl65\" style=\"height: 18pt; border-top: none; text-align: center;\" align=\"left\" height=\"24\">Grupo B<\/td>\n<td class=\"xl66\" style=\"border-top: none; border-left: none; text-align: center;\" align=\"right\">62%<\/td>\n<td class=\"xl66\" style=\"border-top: none; border-left: none; text-align: center;\" align=\"right\">24%<\/td>\n<\/tr>\n<tr>\n<td style=\"border-top: none; text-align: center;\">Kabuuan<\/td>\n<td style=\"border-top: none; border-left: none; text-align: center;\">100%<\/td>\n<td style=\"border-top: none; border-left: none; text-align: center;\">100%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>Hindi lubos na maihihiwalay ng mga grupo ang lahat ng may aksidente sa mga walang aksidente. Ngunit sa paghahambing na ito, mas mababa ang tendensiyang kaugnay ng aksidente sa A kaysa B.<\/p>\n<p>Ano ang mangyayari sa halimbawang rate kung hindi magmaneho ang B? Gumagamit ang artikulong Hapones noong 2021 ng palagay na humigit-kumulang 1% ang taunang posibilidad ng aksidente. Kapag inilapat sa 10,000 tao, lalabas ang sumusunod.<\/p>\n<div class=\"uk-dx-data-table\" tabindex=\"0\" role=\"region\" aria-label=\"Halimbawa sa kaligtasan sa kalsada: paghahambing ng mga grupo\" style=\"max-width:100%;overflow-x:auto;\">\n<table style=\"min-width:420px;width:100%;\">\n<tbody>\n<tr>\n<td style=\"text-align: center;\" width=\"69\"><\/td>\n<td style=\"text-align: center;\" width=\"68\">Grupong may aksidente<\/td>\n<td style=\"text-align: center;\" width=\"69\">Grupong walang aksidente<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Grupo A<\/td>\n<td style=\"text-align: center;\">38<\/td>\n<td style=\"text-align: center;\">7524<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Grupo B<\/td>\n<td style=\"text-align: center;\">62<\/td>\n<td style=\"text-align: center;\">2376<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">Kabuuan<\/td>\n<td style=\"text-align: center;\">100 (1%)<\/td>\n<td style=\"text-align: center;\">9900 (99%)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>Ito ang orihinal na pagkukuwenta:<br \/>\nGrupo A: 38 \u00f7 7524 \u2248 0.5%<br \/>\nGrupo B: 62 \u00f7 2376 \u2248 2.6%<br \/>\nSa halimbawa, ang rate ng aksidente ng grupo B ayon sa orihinal na pagkukuwenta ay higit limang ulit kaysa sa grupo A. Kung hindi magmaneho ang B, magiging mga 0.5% ang rate sa natitirang mga drayber sa halip na ipinagpalagay na 1%\u2014humigit-kumulang kalahati. Tingnan ang tala sa ibaba tungkol sa denominator na buong grupo.<br \/>\nNgunit kung hindi bigyan ng lisensiya ang B, hindi rin makakapagmaneho ang 2,376 taong walang aksidente, kaya hindi makatotohanan ang ganitong paraan.<br \/>\nDito maaaring makatulong ang IT. Iminumungkahi ng artikulo na unahing hikayatin ang B na lumipat sa ASV (Advanced Safety Vehicles) o mga awtomatikong sasakyan upang hangaring makamit ang katulad na pakinabang sa kaligtasan.<\/p>\n<p>Inilalarawan ng orihinal ang Japan bilang may kakaunting aksidente kumpara sa ibang bansa at nagmumungkahi ng mas malaking potensiyal sa mga bansang hindi pa ganap ang sistema ng lisensiya o tuntunin sa trapiko. Mga panukala ito ng artikulo, hindi napatunayang epekto sa lahat ng bansa.<br \/>\nKalusugan at kagalingan para sa lahat.<\/p>\n<div class=\"uk-editorial-note\" style=\"border-left:4px solid #777;padding:12px;background:#f5f5f5;\"><strong>Mga tala sa orihinal na halimbawa at pagkukuwenta<\/strong><\/p>\n<p>Pinananatili ng saling ito ang mga talahanayan at halimbawa ng artikulong Hapones noong 9 Hulyo 2021. Ang taunang 1% ay palagay ng halimbawa, hindi kasalukuyang pambansang estadistika. Ang orihinal na takdang taon ng SDG 3.6 ay 2020. Hinahati ng orihinal na pormula ang may aksidente sa walang aksidente; kung buong grupo ang denominator, ang proporsiyon ay 38\/(38+7524) \u2248 0.50% at 62\/(62+2376) \u2248 2.54%. Hindi ito patunay ng sanhi at bunga, balidong prediksiyon ng indibidwal na panganib, o garantiya ng pagbaba ng aksidente dahil sa test, ASV o awtomatikong pagmamaneho. Kailangan ng pagpapatunay bago gamitin sa ibang populasyon. Huwag magpasya sa pagkuha sa trabaho, lisensiya o iba pang pagiging kuwalipikado batay lamang sa test na ito.<\/p>\n<p><a href=\"https:\/\/sdgs.un.org\/goals\/goal3\">SDG 3.6 \u2014 United Nations<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Awtomatikong isinalin ang pahinang ito mula sa orihinal na wikang Hapon gamit ang generative AI. Maaaring may  &hellip; <a href=\"https:\/\/adc-japan.com\/uk\/tl\/tips-tl\/12715.html\" class=\"more-link\">\u7d9a\u304d\u3092\u8aad\u3080 <span class=\"screen-reader-text\">Ang Uchida-Kraepelin Test at Digital na Pagbabago (DX)<\/span> <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":12021,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[144],"tags":[],"class_list":["post-12715","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tips-tl"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - aioseo.com -->\n\t<meta name=\"description\" content=\"Paggamit ng raw data at mga modelo ng pagtatasa ng Uchida-Kraepelin Test sa DX, kasama ang halimbawang pangkaligtasan sa kalsada at mga limitasyon nito.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" 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