This paper presents a methodology for automatic learning of ontologies from Thai text corpora, by extraction of terms and relations. A shallow parser is used to chunk texts on which we identify taxonomic relations with the help of cues: lexico-syntactic patterns and item lists. The main advantage of the approach is that it simplify the task of concept and relation labeling since cues help for identifying the ontological concept and hinting their relation. However, these techniques pose certain problems, i.e. cue word ambiguity, item list identification, and numerous candidate terms. We also propose the methodology to solve these problems by using lexicon and co-occurrence features and weighting them with information gain. The precision, recall and F-measure of the system are 0.74, 0.78 and 0.76, respectively.
A flight attendant has an irregular working schedule that requires to travel across different time zones, which affects their circadian rhythms and challenges the body to resynchronize with the local environment of the destination. Since human capabilities are considered critical factors that have an impact on safety in aviation, an accumulation of sleep debt over time can result in (1) impaired performance from fatigue and decreased alertness (2) increase the likelihood of forgetfulness, which can lead to the adverse in-flight operation safety. This study aimed to examine the sleep quality and to explore the sleep patterns of Thai Airways flight attendants. The PSQI (Pittsburgh Sleep Quality Index), a subjective measure of sleep, was adopted to recruit flight attendants with sleep difficulty. Two male and two female flight attendants who had the highest PSQI scores at 18, 18, 16, 15 of the total score 21 were selected, whereas lower scores under 5 denote a healthier sleep quality. Besides, Fitbit, an external sleep tracker device, was worn on individuals’ wrist for seven nights. Fitbit application on their smartphone created seven photos of each flight attendant, of which some show unusual sleep patterns that might associate with their working lifestyle and sleep habits.
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