Suchergebnisse

Abstract
This study estimates the effects of school start time on sleep time, time use, and educational achievement of high school students. Gyeonggi province, the largest province in South Korea, has implemented the 9 O'clock Attendance Policy, which has delayed school start times to 9:00 AM since September 2014. Changes in the above outcomes before and after the policy implementation are compared between Gyeonggi and other provinces which do not implement the policy. The difference-in-differences estimation results show that the policy increases sleep time, and this is mainly from delayed wake-up time. The policy also reduces adolescents' time use for computer games. The estimation results using administrative national exam data show that the 9 O'clock Attendance Policy does not significantly affect academic achievement.

The Building Supervision of South Korea has been developed under the government′s desire to prevent poor construction and improve the quality of buildings to promote a safer life for the people. Although the building environment of today has been achieved through several improvements, the introduction of such technology is insufficient. Especially since building supervision is primarily carried out almost by manpower, in an era where numerous convergence technologies from the 4th industry are being utilized. Therefore, this study aimed to solve this inefficiency in the building supervision system by using the object detection technology of deep learning in the BIM environment. As a basic study to develop a smart supervision checking system that checks whether the information on the construction site matches the design information, the column ties were selected as a supervision item, and research was conducted. For this, we constructed the tie detection network and suggested an algorithm for information checking between the construction site and BIM environment. Through this, it was possible to confirm the possibility of practical supervision work and improve the efficiency of the work, and furthermore, to see the possibility of using convergence technology.

AbstractBackgroundResearch outcomes on intellectual development and related disabilities in North Korea are not widely known. Therefore, the current scoping review aimed to provide preliminary insight on research topics concerning intellectual disabilities in North Korea.MethodA six‐stage framework for scoping review was adopted to examine research trends. Articles were categorised based on the era of supreme leader and research topic.ResultsThere is a greater amount of research regarding intellectual disabilities in the recent Kim Jong‐un era compared to the period of the previous leader where research outcomes on general intelligence were the focus. Significant qualitative progress was similarly found.ConclusionsThe current analysis on research outcomes provides meaningful insights to aid in understanding the atmosphere in North Korea surrounding intellectual disabilities. Follow‐up studies and open discussions are necessary for further progress.

Purpose Breathing sounds during sleep are altered and characterized by various acoustic specificities in patients with sleep disordered breathing (SDB). This study aimed to identify acoustic biomarkers indicative of the severity of SDB by analyzing the breathing sounds collected from a large number of subjects during entire overnight sleep. Methods The participants were patients who presented at a sleep center with snoring or cessation of breathing during sleep. They were subjected to full-night polysomnography (PSG) during which the breathing sound was recorded using a microphone. Then, audio features were extracted and a group of features differing significantly between different SDB severity groups was selected as a potential acoustic biomarker. To assess the validity of the acoustic biomarker, classification tasks were performed using several machine learning techniques. Based on the apnea–hypopnea index of the subjects, four-group classification and binary classification were performed. Results Using tenfold cross validation, we achieved an accuracy of 88.3% in the four-group classification and an accuracy of 92.5% in the binary classification. Experimental evaluation demonstrated that the models trained on the proposed acoustic biomarkers can be used to estimate the severity of SDB. Conclusions Acoustic biomarkers may be useful to accurately predict the severity of SDB based on the patient's breathing sounds during sleep, without conducting attended full-night PSG. This study implies that any device with a microphone, such as a smartphone, could be potentially utilized outside specialized facilities as a screening tool for detecting SDB. ; The work was partly supported by the SNUBH Grant #06-2014-157 and the Bio and Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government, Ministry of Science, ICT & Future Planning (MSIP) (NRF-2015M3A9D7066972, NRF-2015M3A9D7066980).