{"created":"2020-09-01T09:58:36.855800+00:00","id":3341,"links":{},"metadata":{"_buckets":{"deposit":"ddeee91b-bdb0-4676-bcfe-06e762e8158a"},"_deposit":{"id":"3341","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3341"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3341","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Classification of Acute Upper Gastrointestinal Bleeding based on Rough Neural Network","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"The main emphasize of paper is theclassification of Acute upper GastrointestinalBleeding based on Rough neural network.Classification is used to extract model describingimportant and data classes or future data trends. Aconventional neural network consists of severallayers of neurons. Each neuron receives input fromother neurons and external environment andproduces output. A rough neural network consists ofconventional neurons and rough neurons connectedto each other. A rough neuron can be viewed as apair of neurons, one for the upper bound and theother for the lower bound. Rough neural networkconsists of one input layer, one output layer and onehidden layer. The system can classify 7 types ofclasses for acute upper gastrointestinal bleeding.This system is implemented by using Javaprogramming language."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Neural network"},{"interim":"neurons"},{"interim":"rough neural network"},{"interim":"Acute upper gastrointestinal bleeding"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-22"}],"displaytype":"preview","filename":"psc2010paper (165).pdf","filesize":[{"value":"201 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3341/files/psc2010paper (165).pdf"},"version_id":"0b939862-f44b-432c-8e56-9b75d3c5a437"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fifth Local Conference on Parallel and Soft Computing","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Aung, Su Mon"},{"subitem_authors_fullname":"Pa, Win Pa"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2010-12-16"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1101"},"item_title":"Classification of Acute Upper Gastrointestinal Bleeding based on Rough Neural Network","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-22","publish_status":"0","recid":"3341","relation_version_is_last":true,"title":["Classification of Acute Upper Gastrointestinal Bleeding based on Rough Neural Network"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T00:32:59.893667+00:00"}