This study is about a life history. Through investigating the life of retired teachers in preschool, elementary, and middle schools, authors wanted to explore the meaning of retirement and the process of adaptation to find out their personal and social needs in post-retirement life. Studies have shown that their experiences at childhood have greatly influenced the performance of one's profession, such as contributing to setting limits on behaviors of their students. In the period of interdependence, they have contributed to serving society and the nation beyond as a professional, and in the second half of his teaching career, they have learned that their painful experience was a resource and have realized that changing mind can make the world changed. Since teachers' behavior affects on many subjects unlike other jobs, rewards or satisfaction from the job was bigger than any other jobs. However, after retirement, they felt a sense of emptiness in life without any sense of belonging or accomplishment, while feeling happiness and infinite freedom in other hand. Thy still go forward for life challenging to new study.
Journal of the Computational Structural Engineering Institute of Korea
/
v.36
no.1
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pp.39-48
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2023
Because a railway bridge is designed over a long period of time and covers a large site, it involves various environmental factors and uncertainties. For this reason, design changes often occur, even if the design was thoroughly reviewed in the initial design stage. In particular, design changes of large-scale facilities, such as railway bridges, consume significant time and cost, and it is extremely inefficient to repeat all the procedures each time. In this study, a technique that can improve the efficiency of learning after design change was developed by utilizing the learning result before design change through transfer learning among deep-learning algorithms. For analysis, scenarios were created, and a database was built using a previously developed railway bridge deep-learning-based prediction system. The proposed method results in similar accuracy when learning only 1000 data points in the new domain compared with the 8000 data points used for learning in the old domain before the design change. Moreover, it was confirmed that it has a faster convergence speed.
Objectives: Sleep disturbance is a very rapidly growing disease with aging. The purpose of this study was to investigate the prevalence of sleep disturbances and its predictive factors in a three-year cohort study of people aged 60 years and over in Korea. Methods: In 2012 and 2014, we obtained data from a survey of the Korean Social Life, Health, and Aging Project. We asked participants if they had been diagnosed with stroke, myocardial infarction, angina pectoris, arthritis, pulmonary tuberculosis, asthma, cataract, glaucoma, hepatitis B, urinary incontinence, prostate hypertrophy, cancer, osteoporosis, hypertension, diabetes, hyperlipidemia, or metabolic syndrome. Cognitive function was assessed using the Mini-Mental State Examination for dementia screening in 2012, and depression was assessed using the Center for Epidemiologic Studies Depression Scale in 2012 and 2014. In 2015, a structured clinical interview for Axis I psychiatric disorders was administered to 235 people, and sleep disturbance was assessed using the Pittsburgh Sleep Quality Index. The perceived stress scale and the State-trait Anger Expression Inventory were also administered. Logistic regression analysis was used to predict sleep disturbance by gender, age, education, depression score, number of coexisting diseases in 2012 and 2014, current anger score, and perceived stress score. Results: Twenty-seven percent of the participants had sleep disturbances. Logistic regression analysis showed that the number of medical diseases three years ago, the depression score one year ago, and the current perceived stress significantly predicted sleep disturbances. Conclusion: Comorbid medical disease three years previous and depressive symptoms evaluated one year previous were predictive of current sleep disturbances. Further studies are needed to determine whether treatment of medical disease and depressive symptoms can improve sleep disturbances.
To evaluate the impacts of the health education programs including smoking cessation, pap smear and breast self-examination(BSE), a community trial was conducted during one year from December 1996 to December 1997 in Kyongju City. Before health education, a base-line survey was implemented and the target population was allocated randomly to case and control groups. The case and control groups were divided into three categories which were smoking cessation, pap smear and BSE. The series of health education leaflets about anti-smoking, pap smear and BSE were mailed to case group and the evaluation survey was conducted at the end of this trial to compare the change of health related behaviours of case and control groups. Smoking prevalence of case group did not decline significantly after anti-smoking education but the cessation rates of the elderly and low educated were higher than others. The knowledge level of case group on the health risk associated with smoking was higher than that of control group and the willingness of case group to quit smoking was higher than the control group. The case group's compliance with pap smear for cervical cancer was more increased compared to control group after health education. Of the case group, the younger and lower educated women were screened at a higher rate than others. The knowledge level of case group on the risk factors of cervical cancer and how to prevent it was higher than that of control group. Nearly 60 percent of case group reported that the health education leaflet influenced them to have the pap smear. The unscreened cases were highly motivated to get the pap smear test in the future.
Kim, Do-Yeon;Choi, Yun-Jin;Lee, Seung-Joo;Ko, Min-Seok;Choi, Chong-Hyuk
Journal of Korean Orthopaedic Sports Medicine
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v.9
no.2
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pp.79-84
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2010
Purpose: In patients with meniscal tear with degenerative arthritis, controversy remains as to whether arthroscopic menisectomy is worthwhile or not. The purpose of this study was to evaluate the effect of arthroscopic medial meniscectomy in degenerative arthritis of the knee with meniscal tear. We also intended to identify pertinent indications and risk factors. Materials and Methods: 287 patients underwent arthroscopic medial meniscectomy from 2006 to 2008; 103 patients who had Kellgren-Lawrence grade II, III arthritis of the knee, were over 50 years old, and had minimum 1 year follow-up, were analyzed in this study. Clinical assessment was performed retrospectively using the arthroscopic surgery database, medical records, questionnires and interviews. Assessment included visual analogue scale (VAS) scores and Lysholm scores. Results: The mean Lysholm score increased from 69 to 85 after surgery. The mean VAS score improved from 7 to 3.1 after surgery. Kellgren-Lawrence grade II group and group with trauma history showed significant improvement of pain and function compared with grade III and group without trauma history. Outerbridge grade I showed significantly more improvement of pain than grade III and IV. Multiple regression analysis showed that trauma history and Outerbridge grade affect the improvement of Lysholm score. Conclusion: In one year follow-up, arthroscopic medial menisectomy can improve pain and function of patients in Kellgren-Lawrence grade II, III degenerative arthritis of the knee. We could expect good results especially in group with low Kellgren-Lawrence grade, trauma history, and mild articular cartilage lesion.
Background: It is well known that rifampin decreases the hypoprothrombinemic effect of warfarin by induction of cytochrome P-450 enzyme in healthy volunteer. However, in patients the dosage schedule of warfarin during rifampin therapy is not established. Therefore, patients taking both rifampin and warfarin were reviewed to find out the adequate dosage schedule of warfarin in addition to side effects by interaction of two drugs. Method: Patients taking both rifampin and warfarin were retrieved from patients who were admitted due to heart disease and tuberculosis at Boochun Sejong Hospital from January of 1995 to August of 1999. To decide the adequate dosage of warfarin, the dosage of warfarin before, during, and after rifampin was evaluated in patients who kept adequate hypoprothrombinemic effect of warfarin during rifampin. To decide the adequate dosage schedule of warfarin, the time interval from the beginning of rifampin to normalization of prothrombin time(INR$\geq$1.1) was evaluated. And, the side effects by interaction of two drugs were reviewed. Results: All 12 patients taking both rifampin and warfarin were retrieved. Among them only 6 kept adequate hypoprothrombinemic effect of warfarin during rifampin. The dosage of warfarin during rifampin was $2.4{\pm}0.6$(mean$\pm$standard deviation) times as much as that before rifampin but the dosage after rifampin was the same as that before rifampin. The time interval from the beginning of rifampin to normalization of prothrombin time was $5.8{\pm}2.9$(mean${\pm}$standard deviation) days. 2 out of 12 had complication related to the interaction of rifampin and warfarin, one cerebral embolism just after the beginning of rifampin and the other cerebral hemorrhage just after the discontinuation of rifampin. Conclusion: When both rifampin and warfarin are prescribed, it would be a possible method to be confirmed by prospective study that warfarin be gradually increased about 2 times more than that without rifampin over 1 week or so after the beginning of rifampin and be tapered to the same dosage as that before rifampin when rifampin is discontinued. And, it would be prudent that prothrombin time be monitored frequently during rifampin and warfarin therapy, especially the beginning or discontinuation of rifampin.
As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.
Kim, Young-Du;Park, Kuhn;Kang, Chul-Ung;Yoon, Jeong-Seob;Moon, Seok-Whan;Wang, Young-Pil;Jo, Kuhn-Hyun
Journal of Chest Surgery
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v.40
no.1
s.270
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pp.32-36
/
2007
Background: Although acute renal failure (ARF) after coronary artery bypass graft (CABG) is relatively rare, but devastating complication with high mortality. Our study aims to evaluate the effectiveness of early application of CRRT in patients with ARF which developed after on-pump CABG. Material and Method: Two hundred and eighty seven patients underwent isolated on-pump CABG between May 2002 and Feb. 2006 at our institution, of whom 15 (5.2%) needed CRRT (11 patients for postoperatively developed ARF and the remaining 4 patients with preexisting dialysis-dependent chronic renal failure (CRF) for postoperative hemodynamic and metabolic control). Criteria for early application of CRRT were as follows; decreased urine output less than 0.5cc/h/kg for 2 consecutive hours and elevated serum creatinine level greater than 2.0 mg/dL. Result: The incidence of ARF requiring CRRT after on-pump CABG was 3.9% (11/283) and the overall hospital mortality of patient with CRRT was 33.3% (5/15). Of 5 deaths, 4 were patients with postoperatively developed ARF, and 1 was a patient with pre-existing dialysis-dependent CRF patient. The mean time between the operation and the initiation of CRRT was $25.8{\pm}5.8$ hours and the mean duration of CRRT was $62.1{\pm}41.2$ hours. Of the 7 survivors who were not on dialysis-dependent preoperatively, 6 patients fully recovered renal function during hospital stay and 1 patient required permanent renal supportive treatment after discharge from hospital. Conclusion: Early application of CRRT could maintain stable postoperative hemodynamic status and make outcomes better than those of previous reports in patients with ARF which developed after on-pump CABG.
In this study our main focus is to verify the relationship between social value of transportation system and its perceived features. To achieve this objective, we investigated the value of public bike system (PBS) through willingness to pay (WTP) analysis using contingent valuation method (CVM) and the survey was conducted for 1726 respondents who live in Suwon, Korea. Moreover the determinants related to features related to bicycle use were also gathered. The estimated binary logistic regression and censored regression reveal that the value of PBS is influenced by perceived features towards bicycle use incorporating non-congestion, transportation mode like auto and bus, and high mobility system as well as other variables such as income, bicycle ownership etc. Furthermore the results show that the perceiving of positive features to bicycle use leads to higher social value of PBS. Based on the findings, we discuss the importance of pre-review for transport policy implementation, and also explore the possibilities for application to PBS.
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