• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.17-30
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• 2009

Recently, Interest in the riding of bicycles increased, but existing researches on the effect of bicycle facilities and the supply analysis and evaluation bike analysis of the importance of the item is most fulfilling. Those do not reflect characteristics of the region and the current satisfaction on the riding of bicycles. Therefore, this research will classify Gu Dong of Busan into good region, possible region and difficult region on the riding of bicycles to reflect characteristics of bicycles with the non-power and characteristics of riders with the main purpose of the exercise. Maintenance of bicycles classified according to the region will be decided to the Line-to-Line maintenance as to connect the main point of regions and to the Point-to-Point as to link the main point within region. Then, step-by-step bicycles activation of Busan differentiated by region offers. Also, Survey on Gangseo-Gu, Sasang-Gu, Gijang-Gun with good bicycle conditions and Busan-Jin-Gu with the best maintenance effect will be about the bicycle. The structure model of consciousness-based on the use of bicycles will be made by using Survey results and considering the region characteristics. This structure model will show a correlation of the current satisfaction, the bicycle-related facilities maintenance policy needs, region characteristics and the next intends to riding the bicycle.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.111-129
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• 2022

Insomnia is a chronic disease in modern society, with the number of new patients increasing by more than 20% in the last 5 years. Insomnia is a serious disease that requires diagnosis and treatment because the individual and social problems that occur when there is a lack of sleep are serious and the triggers of insomnia are complex. This study collected 5,699 data from 'insomnia', a community on 'Reddit', a social media that freely expresses opinions. Based on the International Classification of Sleep Disorders ICSD-3 standard and the guidelines with the help of experts, the insomnia corpus was constructed by tagging them as insomnia tendency documents and non-insomnia tendency documents. Five deep learning language models (BERT, RoBERTa, ALBERT, ELECTRA, XLNet) were trained using the constructed insomnia corpus as training data. As a result of performance evaluation, RoBERTa showed the highest performance with an accuracy of 81.33%. In order to in-depth analysis of insomnia social data, topic modeling was performed using the newly emerged BERTopic method by supplementing the weaknesses of LDA, which is widely used in the past. As a result of the analysis, 8 subject groups ('Negative emotions', 'Advice and help and gratitude', 'Insomnia-related diseases', 'Sleeping pills', 'Exercise and eating habits', 'Physical characteristics', 'Activity characteristics', 'Environmental characteristics') could be confirmed. Users expressed negative emotions and sought help and advice from the Reddit insomnia community. In addition, they mentioned diseases related to insomnia, shared discourse on the use of sleeping pills, and expressed interest in exercise and eating habits. As insomnia-related characteristics, we found physical characteristics such as breathing, pregnancy, and heart, active characteristics such as zombies, hypnic jerk, and groggy, and environmental characteristics such as sunlight, blankets, temperature, and naps.