{"created":"2023-10-27T05:41:10.359778+00:00","id":9064,"links":{},"metadata":{"_buckets":{"deposit":"e8f4414c-51c7-4380-b7df-008ed8606d6d"},"_deposit":{"created_by":20,"id":"9064","owner":"20","owners":[20],"owners_ext":{"displayname":"","email":"minmoe37aung@gmail.com","username":""},"pid":{"revision_id":0,"type":"depid","value":"9064"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/00009064","sets":["1582963436320","1582963436320:1582965742757"]},"author_link":[],"control_number":"9064","item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Statistical Modelling of Road Traffic Accidents In Yangon (Khin Thet Tun, 2023)","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Road traffic accidents constitute one of the most pressing concerns for\ngovernments worldwide. Thousands of people are fatal and injured on the roads due\nto accidents. This study aims to analyze and predict road traffic accidents and\ncasualties in Yangon using data from the No. (2) Office of Traffic Police for the\nperiod from January 2013 to December 2022. Descriptive statistics show that the\nnumber of accidents increased from 2013 to 2014, but it has significantly decreased\nstarting from 2015. The analysis of the binary logistic regression model reveals that\nthe risk factors for traffic casualties mainly include gender, place of accident, type of\nvehicle, time of accident, and immediate causes of accidents. Furthermore, the bestfitting\nmodel for predicting traffic accidents was found to be ARIMAX-TFM (0, 1, 1).\nSimilarly, ARIMAX-TFM (1, 0, 1) and ARIMAX-TFM (1, 0, 1) were the best-fitting\nmodels for traffic injury and fatality data. The forecasted number of traffic accidents\nand injuries is steadily decreasing, while the number of fatalities is steadily increasing\nfor January 2023 to March 2023. Additionally, the analysis of ARIMAX-TFM\nconfirms a significant impact of road safety measures on the reduction of the number\nof accidents and casualties in Yangon. To reduce road traffic accidents, traffic\nauthorities should focus on upgrading safer driving behaviors, improving the safety\nfeatures of vehicles, enforcing laws related to key risks, conducting public awareness\ncampaigns to better understand the risks, and establishing a comprehensive strategy."}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-10-27"}],"displaytype":"preview","filename":"Khin Thet Tun, 4 Paragu Ah-3.pdf","filesize":[{"value":"2.9 MB"}],"format":"application/pdf","licensetype":"license_0","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/9064/files/Khin Thet Tun, 4 Paragu Ah-3.pdf"},"version_id":"5f43c263-d0be-4c05-96f3-a747a3c37026"}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"Yangon University of Economics","subitem_supervisor(s)":[{"subitem_supervisor":"Pro-Rector.Dr.Mya Thandar"}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Khin Thet Tun"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Other"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Dissertation"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2023-09-01"},"item_title":"Statistical Modelling of Road Traffic Accidents In Yangon (Khin Thet Tun, 2023)","item_type_id":"21","owner":"20","path":["1582963436320","1582965742757"],"publish_date":"2023-10-27","publish_status":"0","recid":"9064","relation_version_is_last":true,"title":["Statistical Modelling of Road Traffic Accidents In Yangon (Khin Thet Tun, 2023)"],"weko_creator_id":"20","weko_shared_id":-1},"updated":"2024-05-27T03:54:56.796756+00:00"}