• Journal of Preventive Medicine and Public Health
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• v.24 no.3 s.35
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• pp.428-440
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• 1991

This study was conducted to estimate the prevalence rate of cervical cancer and to investigate its risk factors. 5,417 asymptomatic married women were screened from March, 1984 to December, 1990 in Taegu city. Of 5,417 examinees, 3,817 (70.46%) were normal, 1,542 (28.7%) showed inflammatory change, 51 (0.94%) were dysplasia and 7 (0.13%) were carcinoma in situ or invasive carcinomas. The prevalence of abnormal finding (dysplasia, carcinoma in situ or invasive carcinoma) was 1,070 per 100,000 population. The prevalence of dysplasia was 940 per 100,000 and that of carcinoma in situ or invasive carcinoma was 130 per 100,000. Age-adjusted prevalence rate for abnormal finding adjusted with standard population of Taegu city was estimated to be 850 per 100,000. The prevalence of cervical cancer was significantly increased with age (P<0.05). The prevalence of cervical cancer was significantly decreased with age at marriage and educational level (P<0.05). The history of induced abortion and the number of pregnancies were significantly associated with the prevalence of cervical cancer (p<0.05), whereas, the number of parity was not. Age at marriage was significantly associated with the prevalence of cervical cancer after stratification by age (p<0.05). However, the level of education, parity, induced abortion, number of pregnancies were not significant. Inflammation and human papiloma virus infection were associated with cervical cancer with odds ratio of 13.48 (95% confidence interval $7.80{\sim}23.40$) and 474.29 (95% confidence interval $196.80{\sim}1143.10$), respectively. In conclusion, for early detection of cervical cancer it should be recommended to perform mass cytological screening. In particular, regular and periodic cytologic screening, starting at age 25, for cervical cancer should be recommended for those women who have frequent cervical inflammation and for those women married before age of 20.

• Tuberculosis and Respiratory Diseases
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• v.43 no.5
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• pp.763-773
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• 1996

Background : Behçet's syndrome is a chronic multisystemic disease affecting many organs such as skin, mucosa, eye, joint, central nervous system and blood vessels. Lung involvement occurs in 5% of Behçet's syndrome and is thought to be due to the pulmonary vasculitis leading to thromboembolism, aneurysm and arteriobronchial fistula. Pulmonary vasculitis in Behçet's syndrome is a unique clinical feature, differing from other vasculitis affecting the lung and is one of the major causes of death. Therefore, we examined the incidence, the clinical features, the radioloic findings and the clinical courses of the lung involvement in Behçet's syndrome. Methods: We retrospectively reviewed the medical records and radiologic studies of 10 cases of the lung involvement in Behçet's syndrome diagnosed at Yongdong Severance Hospital and Severance Hospital from 1986 to 1995. We analysed the clinical features, the radiological findings, the treatment modalities and the clinical courses. Results: 1) The incidence of the lung involvement in Behçet's syndrome was 2%(10/487). The male to female ratio was 8 : 2 and the mean age was 34 years. The presenting symptom was hemoptysis in 5 of 10 cases, and massive hemoptysis was noted in 2 cases. Other pulmonary symptoms were cough(6/10), dyspnea(4/10), and chest pain(2/10). Other manifestations were oral ulcers(10/10), genital ulcers(9/10), skin lesions(7/10), and eye lesions(6/10). 2) The laboratory findings were nonspecific. The posteroanterior views of chest radiographies showed multiple infiltrates(6/10), nodular or mass-like opacities(4/10), or normal findings(2/10). The chest CT scans showed multifocal consolidations(6/8), and aneurysms of the pulmonary aneries(4/8). The pulmonary angiographies were performed in 3 cases, and showed pulmonary artery aneurysms in 2 cases. The ventilation-perfusion scans in 2 cases of normal chest x-ray showed multiple mismatched findings. 3) The patients were treated with combination therapy consisting of corticosteroids, cyclophosphamide, and colchicine or anticoagulant agents. Surgical resection was performed in one case with a huge aneurysm. 4) We have followed up nine of ten cases. Three cases are well-being with medical therapy, two cases are severely disabled now and four cases died due to massive hemoptysis, massive pulmonary embolism, or sepsis. Conclusion : Pulmonary vasculitis is a main feature of the lung involvement of Behçet's syndrome, causing hemorrhage, aneurysmal formation, and/or thromboemboism. The lung involvement of Behçet's syndrome is uncommon but is one of the most serious prognostic factors of the disease. Therefore, an aggressive diagnostic work-up for early detection and proper treatment are recommended to improve the clinical course and the survival.

• Tuberculosis and Respiratory Diseases
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• v.43 no.3
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• pp.367-376
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• 1996

Background : The diagnosis of emphysema during life is based on a combination of clinical, functional, and radiographic findings, but this combination is relatively insensitive and nonspecific. The development of rapid, high-resolution third and fourth generation CT scanners has enabled us to resolve pulmonary parenchymal abnormalities with great precision. We compared the chest HRCT findings to the pulmonary function test and arterial blood gas analysis in pulmonary emphysema patients to test the ability of HRCT to quantify the degree of pulmonary emphysema. Methods : From october 1994 to october 1995, the study group consisted of 20 subjects in whom HRCT of the thorax and pulmonary function studies had been obtained at St. Mary's hospital. The analysis was from scans at preselected anatomic levels and incorporated both lungs. On each HRCT slice the lung parenchyma was assessed for two aspects of emphysema: severity and extent. The five levels were graded and scored separately for the left and right lung giving a total of 10 lung fields. A combination of severity and extent gave the degree of emphysema. We compared the HRCT quantitation of emphysema, pulmonary function tests, ABGA, CBC, and patients characteristics(age, sex, height, weight, smoking amounts etc.) in 20 patients. Results : 1) There was a significant inverse correlation between HRCT scores for emphysema and percentage predicted values of DLco(r = -0.68, p < 0.05), DLco/VA(r = -0.49, p < 0.05), FEV1(r = -0.53, p < 0.05), and FVC(r = -0.47, p < 0.05). 2) There was a significant correlation between the HRCT scores and percentage predicted values of TLC(r = 0.50, p < 0.05), RV(r = 0.64, p < 0.05). 3) There was a significant inverse correlation between the HRCT scores and PaO2(r = -0.48, p < 0.05) and significant correlation with D(A-a)O2(r = -0.48, p < 0.05) but no significant correlation between the HRCT scores and PaCO2. 4) There was no significant correlation between the HRCT scores and age, sex, height, weight, smoking amounts in patients, hemoglobin, hematocrit, and wbc counts. Conclusion : High-Resolution CT provides a useful method for early detection and quantitating emphysema in life and correlates significantly with pulmonary function tests and arterial blood gas analysis.

• Tuberculosis and Respiratory Diseases
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• v.42 no.6
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• pp.923-933
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• 1995

Background: Pleural abnormality is the the most common respiratory change caused by asbestos dust inhalation and also develop other asbestos related disease after cessation of asbestos exposure. So we conducted epidemiologic study to investigate if the pleural abnormality is associated with pulmonary function change and what factors are influenced on pulmonary function impairment. Methods: Two hundred and twenty two asbestos workers from 9 industries using asbestos in Korea were selected to measure the concentration of sectional asbestos fiber. Ouestionnaire, chest X-ray, PFT were also performed. All the data were analyzed by student t-test and chi-square test using SAS. Regressional analysis was performed to evaluate important factors, for example smoking, exposure concentration, period and the existence of pleural thickening, affecting to the change of pulmonary function. Results: 1) All nine industries except two, airborn asbestos fiber concentration was less than an average permissible concentration. PFT was performed on 222 workers and the percentage of male was 88.3%, their mean age was $41{\pm}9$ years old, and the duration of asbestos exposure was $10.6{\pm}7.8$ yrs. 2) The chest X-ray showed normal(89.19%), pulmonary Tb(inactive)(2.7%), pleral thickening (7.66%), suspected reticulonodular shadow(0.9%). 3) The mean values of height, smoking status, concentration of asbestos fiberwere not different between the subjects with pleural thickening and others, but age, cumulative pack-years, the duration of asbestos exposure were higher in subjects with pleural thickening. 4) All the PFT indices were lower in the subjects with pleural thickening than in the subjects without pleural thickening. 5) Simple regression analysis showed there was a significant correlation between $FEF_{75}$ which is sensitive in small airway obstruction and cumulative smoking pack-years, the duration of asbestos exposure and the concentration of asbestos fiber. 6) Multiple regression analysis showed all the pulmonary function indices were decreased as the increase of cumulative smoking pack-years and especially in the indices those are sensitive in small airway obstruction. Pleural thickening was associated with reduction in FVC, $FEV_1$, PEFR and $FEF_{25}$. Conclusion: The more concentration of asbestos fiber and the more duration of asbestos exposure, the greater reduction in $FEF_{50}$, $FEF_{75}$. Therefore PFT was important in the evaluation of early detection for small airway obstruction. Furthermore pleural thickening without asbesto-related parenchymal lung disease is associated with reduction in pulmonary function.

• Journal of Preventive Medicine and Public Health
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• v.30 no.3 s.58
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• pp.630-642
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• 1997

The purpose of this study was to examine the mortality risk associated with cognitive impairment among the rural elderly. The subjective of study was 558 of 'A Study on the Depression and Cognitive Impairment in the Rural Elderly' of Jung Ae Rhee and Hyang Gyun Jung's study(1993). Cognitive impairment and other social and health factors were assessed in 558 elderly rural community residents. For this study, a Korean version of the Mini-Mental State Examination(MMSEK) was used as a global indicator of cognitive functioning. And mortality risk factors for each cognitive impairment subgroup were identified by univariate and multivariate Cox regression analysis. At baseline 22.6% of the sample were mildly impaired and 14.2% were severely impaired. As the age increased, the cognitive function was more impaired. Sexual difference was existed in the cognitive function level. Also the variables such as smoking habits, physical disorders had the significant relationship with cognitive function impairment. Across a 3-year observation period the mortality rate was 8.5% for the cognitively unimpaired, 11.1% for the mildly impaired, and 16.5% for the severly impaired respendents. And the survival probability was .92 for the cognitively unimpaired, .90 for the mildly impaired, and .86 for the severly impaired respondents. Compared to survival curve for the cognitively unimpaired group, each survival curve for the mildly and the severely impaired group was not significantly different. When adjustments models were not made for the effects of other health and social covariates, each hazard ratio of death of mildly and severely impaired persons was not significantly different as compared with the cognitively unimpaired. But, as MMSEK score increased, significantly hazard ratio of death decreased. Employing Cox univariate proportional hazards model, statistically other significant variables were age, monthly income, smoking habits, physical disorders. Also when adjustments were made for the effects of other health and social covariates, there was no difference in hazard ratio of death between those with severe or mild impairment and unimpaired persons. And as MMSEK score increased, significantly hazard ratio of death did not decrease. Employing Cox multivariate proportional hazards model, statistically other significant variables were age, monthly income, physical disorders. Employing Cox multivariate proportional hazards model by sex, at men and women statistically significant variable was only age. For both men and women, also cognitive impairment was not a significant risk factor. Other investigators have found that cognitive impairment is a significant predictor of mortality. But we didn't find that it is a significant predictor of mortality. Even though the conclusions of our study were not related to cognitive impairment and mortality, early detection of impaired cognition and attention to associated health problems could improve the quality of life of these older adults and perhaps extend their survival.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.1
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• pp.50-59
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• 2019

Objectives : Many of the patients with type 2 diabetes are associated with sleep problems, and the rate of insomnia is known to be higher in the general population. The aims of this study were to know the frequency and clnical characteristics of insomnia, and related variables to insomnia in patients diagnosed with type 2 diabetes. Methods : For 99 patients from 18 to 80 years of age (65 males and 34 females) with type 2 diabetes, interviews were performed. Total sleep time and sleep latency was evaluated. Insomnia was evaluated using the Korean Version of the Insomnia Severity Index (ISI-K). Severity of depressive symptoms were evaluted using the Korean version of the Hamilton Depression Scale (K-HDRM). According to the cutoff score of 15.5 on the ISI-K, subjects were divided into the group of type 2 diabetics with insomnia (N=34) and those without insomnia (N=65) at first, and then statistically analyzed. Results : TInsomnia could be found in 34.34% of type 2 diabetics. Type 2 diabetics with insomnia had significantly more single or divorced (respectively 11.8%, p<0.05), higher total scores of the K-HDRS ($11.76{\pm}5.52$, p<0.001), shorter total sleep time ($5.35{\pm}2.00hours$, p<0.001), and longer sleep latency ($50.29{\pm}33.80minutes$, p<0.001). The all item scores of the ISI-K in type 2 diabetics with insomnia were significantly higher than those in type 2 diabetics without insomnia, that is, total ($18.38{\pm}2.69$), A1 (Initial insomnia) ($2.97{\pm}0.76$), A2 (Middle insomnia) ($3.06{\pm}0.69$), A3 (Terminal insomnia) ($2.76{\pm}0.61$), B (Satisfaction) ($3.18{\pm}0.72$), C (Interference) ($2.09{\pm}0.97$), D (Noticeability) ($2.12{\pm}1.09$) and E (Distress) ($2.21{\pm}0.81$) (respectively p<0.001). Variables associated with insomnia in type 2 diabetics were as following. Age had significant negative correlation with A3 items of the ISI-K (${\beta}=-0.241$, p<0.05). Total scores of the K-HDRS had significant positive correlation, while total sleep time had significant negative correlation with all items of the ISI-K (respectively p<0.05). Sleep latency had significant positive correlation with total,, A1, B and E item scores of the ISI-K (respectively p<0.05). Conclusions : Insomnia was found in about 1/3 of type 2 diabetics. According to the presence of insomnia, clinical characteristics including sleep quality as well as quantity seemed to be different. Because depression seemed to be correlated with insomnia, clinicians should pay attention to early detection and intervention of depression among type 2 diabetics.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.