• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.66-73
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• 2016

Objectives : The purpose of this study was to investigate the characteristics of psychosocial factors related to functional dyspepsia(FD) and their effects on quality of life(QOL) in firefighters. Methods : This study examined data collected from 1,217 firefighters. We measured psychological symptoms by Patient Health Questionnaire-9(PHQ-9), Generalized Anxiety Disorder questionnaire(GAD-7), Korean Occupational Stress Scale(KOSS), Ways of Coping checklist(WCCL), Rosenberg's Self-Esteem Scale(RSES) and World Health Organization Quality of Life Scale abbreviated version(WHOQOL-BREF). Chi-square test, independent t-test, Pearson's correlation test, logistic regression analysis, and hierarchical regression analysis were used as statistical analysis methods. Results : For the group with FD, the male participants showed significantly higher frequency(p=0.006) compared to the female participants. The group with FD had higher scores for depressive symptoms(p<.001), anxiety (p<.001), and occupational stress(p<.001), and did lower scores for self-esteem(p=.008), quality of life(p<.001) than those without FD. The FD risk was higher in the following KOSS subcategories: job demand(OR 1.94, 95% CI : 1.29-2.93), lack of reward(OR 2.47, 95% CI : 1.61-3.81), and occupational climate(OR 1.51, 95% CI : 1.01-2.24). In the hierarchical regression analysis, QOL was best predicted by depressive symptoms, self-esteem, and occupational stress. Three predictive variables above accounts for 42.0% variance explained of total variance. Conclusions : The psychosocial factors showed significant effects on FD, and predictive variables for QOL were identified based on regression analysis. The results suggest that the psychiatric approach should be accompanied with medical approach in future FD assessment.

• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.83-93
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• 2016

Objectives : The Center for Epidemiologic Studies Depression scale-Revised is a recently revised scale which has been reported as a valid tool for the assessment of depressive symptoms. It encompasses cardinal symptoms of depression described in the Diagnostic and Statistical Manual of Mental disorders, fourth edition. In this study, we assessed the reliability, validity and psychometric properties of the Korean version of the CESD-R(K-CESD-R). Methods : Forty-eight patients diagnosed as major depressive disorder, dysthymia, depressive disorder NOS according to the DSM-IV criteria using Mini International Neuropsychiatric Interview and 48 healthy controls were enrolled in this study. They were assessed with K-CESD-R, K-MADRS, PHQ-9, KQIDS-SR, STAI to check cross-validation. Statistical analyses were performed using calculation of Cronbach's alpha, Pearson correlation coefficient, Principal Component Analysis, ROC curve and optimal cut-off value. Results : The Cronbach's alpha of K-CESD-R was 0.98. The total score of K-CESD-R revealed significantly high correlations with those of K-MADRS, PHQ-9, KQIDS-SR(r=0.910, 0.966 and 0.920, p<0.001, respectively). Factor analysis showed two factors account for 76.29% of total variance. We suggested the optimal cut-off value of K-CESD-R as 13 according to analysis of the ROC curve which value sensitivity and specificity both equally. Conclusions : These Results showed that the K-CESD-R could be a reliable and valid scale to assess depressive symptoms. The K-CESD-R is expected as a useful and effective tool for screening and measuring depressive symptoms not only in outpatient clinic but also epidemiologic studies.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.3
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• pp.255-263
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• 2021

Soybean extract is known to play an important role in preventing and treating diseases associated with aging, cancer, obesity, and cardiovascular disease. A recent has revealed that soybean extract has a potent effect on hair growth in in vitro, in vivo, and clinical studies. Recently, it has been reported that their fermented extracts exhibit numerous and high efficacy, as compared to general extracts. However, the underlying mechanisms that induce hair growth after using fermented soybean extract are not well understood. The present study aimed to determine the effects of fermented Jeju soybean (FJS) extract on hair growth, with a focus on the underlying mechanisms similar to those of minoxidil. We conducted in vitro and ex vivo investigations and clinical studies. FJS extract enhanced dermal papilla cell proliferation, VEGF levels, and potassium channel opening. Moreover, it promoted human hair follicle elongation. These effects were comprehensively demonstrated in the clinical results, in which FJS extract-containing shampoo improved hair density after 24 weeks of utilization. Collectively, the results of this study demonstrate that FJS extract promotes hair growth and inhibits hair loss through a mechanism similar to that of minoxidil in hair follicles.

• Journal of agricultural medicine and community health
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• v.46 no.4
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• pp.280-294
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• 2021

Objectives: The purpose of this study is to investigate the effects of social capital characteristics, socio-demographic characteristics, physical condition, and health behavior characteristics on health-related quality of life of the elderly in Korea. Methods: T-test, one-way ANOVA, and regression analysis were performed by applying a complex sample design to 57.787 people aged 65 and over using the 2019 Community Health Survey. Results: First, as a result of complex-sample T-test and ANOVA analysis, it was found that there were differences in health-related quality of life according to social capital characteristics, physical condition & health behavior characteristics, and socio-demographic characteristics. Complex Sample Regression Analysis Results, the explanatory power of the model was 28%. When living in the metropolitan area, living in an apartment building, having a spouse, having a higher household income, economic activity, higher educational attainment, increase sleeping time, walking time, frequent binge drinking, health checkup, networking, trust, and social participation showed higher health-related quality of life. When people were older, their gender was female, higher BMI, number of chronic diseases, and severe stress that showed lower health-related quality of life. Conclusions: It was proved that the factors affecting the health-related quality of life of the elderly are not only physical condition and health behavior factors, but also social capital and socio-demographic characteristics. It was found that the role as a member was important.

• 한국노년학
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• v.38 no.3
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• pp.569-592
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• 2018

This study purported to investigate the current state of human rights of older adults residing in rural areas of Korea. The study utilized, as an analytic framework, 4 priority directions (1. "older persons and development", 2. "rural area development", 3. "advancing health and well-being into old age", and 4. "ensuring enabling and supportive environments") with 13 task actions recommended by Madrid International Plan of Action on Ageing (MIPAA). Furthermore, the study examined gender differences in all items included in the analytic framework. Data was collected by the face-to-face survey on 800 subjects aged 65 and over. Statistical analyses were conducted using STATA 13.0 program. The main results were summarized in order of 4 priority directions as follows. First, average working hours per day were 6.2, and men reportedly participated in economic activities and needed job training more than women, while women participated in lifelong education programs more than men. Awareness of fire and disaster prevention facilities was low in both genders. Second, accessibility to the support center for the elderly living alone as well as protective services for the vulnerable elderly was found to be low. IT-based services and networking were used more by men than women, and specifically, IT-based financial transactions and welfare services were least used. Third, medical check-ups and vaccinations were well received, while consistent treatments for chronic illnesses and long-term care services were relatively less given. In addition, accessibility to mental health service centers was considerably low. Fourth, although old house structures and the lack of convenience facilities were found to be circumstantial risk factors for these elders, experiences of receiving housing support services were scarce. The elderly were found to rely more on informal care, and concerns for their care were higher in women than men. Plus, accessibility to elderly abuse services was markedly low. Based on these results, discussed were implications for implementing policies and practical interventions to raise the levels of the human rights for this population.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.193-200
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• 2019

The study was conducted surveying ultrasound room workers on hospital infection awareness in Daejeon and Choong-chunng region. The contamination of ultrasonic probes used in clinical trials was measured using ATP, and the results were verified after using 70% alcohol sterilization. It was measured on the group's general characteristics and the specific categories such as academic background, job type, having professional certificate and infection education. After the examination, the gel removal and method, disinfection status of the probe and variable correlation analysis were performed to analyze the recognition of the ultrasonic probe disinfection. After examination in ultrasound room, it was found that towels were used the most for cleaning, and the gel container was not replaced for more than three months. After 70% alcohol disinfection, ATP contamination was reduced from $1055.4{\pm}944.2$ to $133.5{\pm}93.2$ and the result was analyzed to be statistically significant.(${\rho}<0.01$) The found bacteria were CNS, Gram positive bacillus, and Micrococcus specs. In order to solve this problem, 70% alcohol sterilization was applied and the bacteria were not detected after the treatment. The research shows that regular training on infection control and efforts to prevent infection are necessary, and that 70% alcohol is effective in disinfect the bacteria. Therefore, the medical institution should provide active hospital infection control education to improve the awareness of hospital infection among workers and contribute to the prevention of patient infection. It is also understood that proper use of the results of this study will help prevent infection by means of ultrasonic probes.

• Sleep Medicine and Psychophysiology
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• v.25 no.2
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• pp.51-57
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• 2018

Objectives: Previous studies have shown that periodic limb movements in sleep (PLMS) could be one of risk factors for cardiovascular morbidity. The purpose of this study was to investigate the association between PLMS and blood pressure changes during sleep. Methods: We analyzed data from 358 adults (176 men and 182 women) aged 18 years and older who were free from sleep apnea syndrome (Respiratory Disturbance Index < 5) and sleep disorders such as REM sleep behavior disorder or narcolepsy. Demographic characteristics, polysomnography records, and clinical variable data including blood pressure, body mass index, alcohol, smoking, and current medications were collected. In addition, self-report questionnaires including the Beck Depression Index, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index were completed. Blood pressure change from bedtime to awakening was compared between the two periodic limb movement index (PLMI) groups [low PLMI ($PLMI{\leq}15$) and high PLMI (PLMI > 15)]. Blood pressure change patterns were compared using repeated measures analysis of variance. Results: Systolic blood pressure in the high PLMI group was lower than that in the low PLMI group (p = 0.036). These results were also significant when adjusted for gender and age, but were not statistically significant when adjusted for BMI, alcohol, smoking, anti-hypertension medication use and sleep efficiency (p = 0.098). Systolic blood pressure dropped by 9.7 mm Hg in the low PLMI group, and systolic blood pressure in the high PLMI group dropped by 2.9 mm Hg. There was a significant difference in delta systolic blood pressure after sleep between the two groups in women when adjusted for age, BMI, alcohol, smoking, antihypertensive medication use and sleep efficiency (p = 0.023). Conclusion: PLMS was significantly associated with a decreasing pattern in nocturnal BP during sleep, and this association remained significant in women when adjusted for age, BMI, alcohol, smoking, antihypertension medication use and sleep efficiency related to blood pressure. We suggest that PLMS may be associated with cardiovascular morbidity.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.2
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• pp.97-100
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• 2018

Purpose The glomerular filtration rate (GFR) test is an important indicator of glomerular filtration and has been used to test renal function and the extent of its function. The GFR test is performed by intravenous injection of radioactive medicines made of $^{51}Cr$-EDTA, and blood concentration is measured by taking blood according to the elapsed time. also, PET-CT, bone scan, transfusion and so on will affect the outcome. Therefore, we will improve the quality of the test by providing guidelines for the GFR test for more accurate testing. Materials and Methods 5 mL of physiological saline solution and 2 mL of $^{51}Cr$-EDTA solution are used to make 5 mL of the radiopharmaceutical solution to be injected into the patient. First, the syringe weight is measured before the injection, and then the radioactive medicine is injected into the patient's vein and the syringe weight is measured after the injection. Blood sampling is performed twice in total. In adults, blood is collected 3 hours / 5 hours after injection and in children 2 hours / 5 hours after injection. The blood sample is centrifuged at 3300 rpm for 5 minutes. Standard solution is prepared by filling diluent water up to the scale indicated in the 200-mL volumetric flask, discarding $500{\mu}L$, injecting $500{\mu}L$ of GFR reagent and mixing well. $500{\mu}L$ each of the standard solution is dispensed into two test tubes, and $500{\mu}L$ of each of the plasma samples collected in time is dispensed into two test tubes and measured with a Cobra Counter. Results At present, the reference range applied in this study is $119.5{\pm}30.3ml/min/1.73m2$ for males and $125.2{\pm}28.2ml/min/1.73m^2$ for females. Conclusion The GFR test is conducted using radioactive medical products. GFR testing is performed as a scheduled test, but PET-CT, dialysis and transfusion, which may affect GFR testing, may be scheduled during GFR testing. Therefore, we could get accurate GFR test results by notifying the ward and department beforehand when booking.