• Journal of Korean Neurosurgical Society
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• v.30 no.8
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• pp.985-991
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• 2001

Objectives : The craniopharyngioma is a benign tumor located at least in part in the suprasellar cistern. However, the symptoms and signs from this tumor may be determined not only by the location of the tumor but also by its size and the age of the patient. The objective of our study is to analyze retrospectively the clinical manifestations of craniopharyngiomas with regards to tumor characteristics in children and adults. Material and Methods: Twenty-three patients(16 adults, 7 children) treated for craniopharyngioma between 1990 and 1999 were studied to demonstrate the relationship of tumor size, growth pattern, and its invasiveness with clinical symptoms. As part of the assessment, 16 adults(M : F=8 : 8, mean age : 43.7 years) and 7 children(M : F=5 : 2, mean age : 10.1 years) underwent magnetic resonance(MR) imaging and computerized tomography(CT) scanning with a three-dimensional volume acquisition sequence. Results : The three major cardinal signs were defined to increased intracranial pressure, endocrine dysfunction, and visual problems. The tumor size in child group was larger than that in adult group. Also, visual problems, symptoms of increased intracranial pressure and hydrocephalus were more frequently observed in child group. However, endocrine dysfunction and neuropsychological symptoms related with hypothalamic connections to the thalamus, pituitary, frontal lobe, and other cortical areas were more frequent in adult group. Conclusions: In our series, the tumor size and invasiveness of craniopharyngioma revealed to be relevent with initial symptoms of increased intracranial pressure and visual symptoms which were more frequent in child group. As for the growth pattern, we did not find major difference between adults and children.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.583-597
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• 2020

This study analyzed how elderly people's perception of social welfare affects social welfare service and social welfare policy satisfaction by paying attention to the use of social welfare services and satisfaction with social welfare policies. In order to achieve this research goal, 465 people aged 60 or older who completed responses to the additional survey were collected and analyzed as research targets based on data from the Korea Welfare Panel, which is accumulated by the Korea Institute for Health and Social Affairs and Seoul National University's Social Welfare Research Institute. The results of this study are as follows. First, "Awareness of welfare for the elderly (recognition of welfare expenditure, recognition of welfare targets, recognition of welfare tax increases)" was found to have a negative impact on "use of social services." Second, "Awareness of welfare for the elderly (recognition of welfare expenditure, recognition of welfare targets, recognition of welfare tax increases)" was found to have a negative impact on "satisfaction with social welfare policies." Third, the impact of the recognition of welfare for the elderly on the use of social services was found to be different according to the demographic characteristics (education level, income level, educational background, gender). Fourth, according to the "population statistical characteristics (education level, income level, educational background, gender)" the impact of the recognition of welfare for the elderly on the satisfaction of social welfare policy was shown to be different. The implications of this study are that we looked at multi-dimensional welfare awareness and social service use experience together as factors affecting social welfare policy satisfaction. In other words, it is meaningful that the government focused on welfare awareness based on individual values and subjective perceptions as an influence on social welfare policy satisfaction, and sought practical alternatives to welfare policies and welfare sites by examining whether the experience of using social services in relation to welfare awareness and social welfare policy satisfaction among the elderly.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1219-1230
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• 2008

Stream inflows induced by flood runoffs have a higher density than the ambient reservoir water because of a lower water temperature and elevated suspended sediment(SS) concentration. As the propagation of density currents that formed by density difference between inflow and ambient water affects reservoir water quality and ecosystem, an understanding of reservoir density current is essential for an optimization of filed monitoring, analysis and forecast of SS and nutrient transport, and their proper management and control. This study was aimed to quantify the characteristics of inflow density current including plunge depth($d_p$) and distance($X_p$), separation depth($d_s$), interflow thickness($h_i$), arrival time to dam($t_a$), reduction ratio(${\beta}$) of SS contained stream inflow for different flood magnitude in Daecheong Reservoir with a validated two-dimensional(2D) numerical model. 10 different flood scenarios corresponding to inflow densimetric Froude number($Fr_i$) range from 0.920 to 9.205 were set up based on the hydrograph obtained from June 13 to July 3, 2004. A fully developed stratification condition was assumed as an initial water temperature profile. Higher $Fr_i$(inertia-to-buoyancy ratio) resulted in a greater $d_p,\;X_p,\;d_s,\;h_i$, and faster propagation of interflow, while the effect of reservoir geometry on these characteristics was significant. The Hebbert equation that estimates $d_p$ assuming steady-state flow condition with triangular cross section substantially over-estimated the $d_p$ because it does not consider the spatial variation of reservoir geometry and water surface changes during flood events. The ${\beta}$ values between inflow and dam sites were decreased as $Fr_i$ increased, but reversed after $Fr_i$>9.0 because of turbulent mixing effect. The results provides a practical and effective prediction measures for reservoir operators to first capture the behavior of turbidity inflow.

• Journal of dental hygiene science
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• v.17 no.2
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• pp.134-141
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• 2017

This study examined 191 pregnant women before delivery in an obstetrics and gynecology clinic in North Gyeongsang Province from May to September 2016 by using a questionnaire after obtaining informed consent for voluntary participation in the study. The study was performed to investigate the association of depression with sociodemographic characteristics, pregnancy-related characteristics, social support, sleep quality and Oral Health Impact Profile (OHIP) in pregnant women. The prevalence of depression among the pregnant women was 25.1% in the healthy group and 74.9% in the depression group. The depression level was significantly higher in women in the depression group who were unsatisfied with their marriage life, had no occupation, had lower social support, had poor sleep quality and had higher OHIP scores. The results of the logistic regression analysis indicated that, the risk ratio for more severe depression was significantly higher in the group with no experience of miscarriage and induced childbirth than in the group with childbirth experience. Conversely, the risk ratio for more severe depression was significantly lower in the group with high social support than in the group with low social support. Depression in the respondents significantly positively correlated with sleep quality and OHIP score but significantly negatively correlated with social support. The multiple regression analysis revealed that the depression level was significantly higher by 22.3% among pregnant women with lower marital satisfaction, no childbirth experience, lower social support and higher OHIP scores. In summary, depression was related to marital satisfaction, childbirth experience, social support, and OHIP score, among others, in pregnant women in this study. Therefore, further investigation is warranted to construct programs and measures that will help build positive thinking by designing and verifying a three-dimensional study model by taking into consideration various variables to reduce the incidence of depression in pregnant women.

• Fashion & Textile Research Journal
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• v.2 no.3
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• pp.253-264
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• 2000

The purpose of this study was to examine the thermal comfort characteristics of the garments for school, textile and bank worker's uniform. The garments selected for this study were frequently used in Taegu area in terms of design and material used for making garments by the survey for the study The human subject tests were performed to determine the thermal comfort characteristics of garments including thermal, humidity, and wearing sensation and the data were analysed statistically. The results of the study were as follows: 1. According to the result of the survey jacket was mostly used as a school uniform for both male and female high school students. The survey showed that 93% of male students wore 'neck T-shirts' and dimensional fitness for the school uniform got suitable at 2~3 grade high school students. In terms of human subject tests, most students rated 'uncomfortable' in wearing sensation of their school uniform. One of this reason was due to the humidity sensation and air velocity sensation. Level of significance of the thermal sensation for gender difference was higher in hands and feet of the subjects than in chest and thigh of them. 2. According to the result of the survey jacket with zipper was mostly used as a textile worker's uniform. The result of the survey indicated that some textile workers are wearing their inner wear (38.7% for upper and 46.6% for lower). In the human subject tests, about 50% of subjects rated 'comfortable to slightly comfortable' for wearing sensation of the textile worker's uniform. It showed that the female subjects of the humidity sensation was rated higher than the male subjects of the humidity sensation, while the male subjects of the thermal sensation was rated higher than the female subjects of the thermal sensation. There was a closer correlation with the subjective thermal sensation for textile worker's uniform in center parts of the subjects such as back and waist than exposed parts. 3. The result of the survey showed that 70% and 23% of the female banker uniform were blouse and jacket, respectively and 75% and 25% of the male banker uniform were jacket and T-shirt, respectively. All interviewee rated trousers and skirts that were used for their lower. 4. The result indicated that 50% male and 67.7% female subjects for the banker uniform rated 'slightly comfortable for the comfort' sensation. 50% male subjects rated 'neutral' and about 50% female subjects rated 'slightly warm to neutral' for the thermal sensation. In addition, The result showed that 75% male subjects for both upper and lower rated 'neutral' for the humidity sensation and also 75% female subjects rated 'neutral to slightly dry'. Thus, there was no significant different between gender. 5. In the thermal sensation of the subjects for the banker's uniform by parts, 50% subjects rated 'neutral' for their body parts, including head, neck, back, waist, hip, lower arm, and thigh. The extremely cold parts were hands and feet for both male and female subjects.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.1
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• pp.39-50
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• 2014

This paper reviews the results of recent observations in the Yeonsuri valley of Mt. Youngmun during springtime (March to May) in 2012. Automated weather stations were installed at twelve sites in the valley to measure temperature and 2, 3 dimensional wind. We examined temporal and spatial characteristics of temperatures and wind data. The Yeonsuri valley springtime average temperature lapse rate between the top and bottom of the entire period is $-0.44^{\circ}C/100$ m. It can be changed by the synoptic weather conditions, the lapse rates is greatest in order of clear days ($-0.48^{\circ}C/100$ m), rainy ($-0.41^{\circ}C/100$ m) and cloudy days ($-0.40^{\circ}C/100$ m). In the night, the temperature inversion layer (thermal belt) and the cold pool are formed within the valley. In addition, we measured temperature and wind distribution from the bottom to 3.5 m, the cold layers existed up to 1.5 m, which were affected by ground mixed layer. The results will provide useful guidance on agricultural practices as well as model simulations.

• Korean Journal of Heritage: History & Science
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• v.54 no.4
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• pp.232-245
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• 2021

The present study is about a brand development strategy that utilizes Korean traditional patterns. The global culturenomics phenomenon confirms the value of the cultural aspects of design when a national brand is established. People succeed with their unique aesthetic sense and reinterpret it in a modern view, and this design acts as today's national brands. In this way, people used traditional patterns and original designs, along with regional characteristics and formative style, in developing their designs. However, due to recent changes in the global environment, modern people live in an "untact" world, and consumption culture shifted toward online marketing. In this environment, where one is isolated from social activities, there needs to be a strong image that can dramatically change the mood of one's home. I would like to re-examine the Dan-Chung pattern, whose painting depends on the aesthetic characteristics of architecture to protect the wooden members of the framework in traditional architecture. The pattern and color of Dan-Chung, coated in traditional architecture, differs by the type of construction used, which includes a palace, a Buddhist temple, and a Confucianism Dan Chung. The Geummoon pattern contains aesthetic factors to add solemnity to the Main Buddhist Halls, which contain Buddha. This is a new medium that continues the current traditions instead of remaining in the past. Among different Dan Chung patterns, Geummoon has magnificent decoration consisting of the highest grade materials and unique composition; therefore, it is suitable to be reinterpreted in modern terms. The same pattern can be interpreted in different ways with different colors, so there is a great aesthetic impression in the Geummoon pattern. The value of preservation for exploration and theoretical study of the traditional pattern is important, but recreating the pattern into modern formative art can present a new angle of view and national brand, bearing pride in our cultural assets. The study used multidimensional molding methods for realistic presentation after going through the two-dimensional design process. The significant value of Korean molding beauty which hangs onto the past will play a crucial role in establishing our national brand.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.3
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• pp.133-149
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• 2021

This study aims to report the behavioral mechanism of steel pipe reinforcement grouting, which is being actively used to ensure the stability of the excavation surface during tunnel excavation, based on measurements taken at the actual site. After using a 12 m steel pipe attached with a shape displacement meter and a strain gauge to reinforce the actual tunnel surface, behavioral characteristics were identified by analyzing the measured deformation and stress of the steel pipe. Taking into account that the steel pipes were overlapped every 6 m, the measured data up to 7 m of excavation were used. In addition, the behavioral characteristics of the steel pipe reinforcement according to the difference in strength were also examined by applying steel pipes with different allowable stresses (SGT275 and SGT550). As a result of analyzing the behavior of steel pipes for 7 hours after the first excavation for 1 m and before proceeding with the next excavation, the stress redistribution due to the arching effect caused by the excavation relaxation load was observed. As excavation proceeded by 1 m, the excavated section exhibited the greatest deformation during excavation of 4 to 6 m due to the stress distribution of the three-dimensional relaxation load, and deformation and stress were generated in the steel pipe installed in the ground ahead of the tunnel face. As a result of comparing the behavior of SGT275 steel pipe (yield strength 275 MPa) and SGT550 steel pipe (yield strength 550 MPa), the difference in the amount of deformation was up to 18 times and the stress was up to 12 times; the stronger the steel pipe, the better it was at responding to the relaxation load. In this study, the behavior mechanism of steel pipe reinforcement grouting in response to the arching effect due to the relaxation load was identified based on the measured data during the actual tunnel excavation, and the results were reported.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1041-1052
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• 2022

This study is to estimate the optimal ecological flow and analysis the spatial distribution of fish habitat for Andong dam downstream reach (4,565.7 km²) using PHABSIM (Physical Habiat Simulation System) and River2D. To establish habitat models, the cross-section informations and hydraulic input data were collected uisng the Nakdong river basic plan report. The establishment range of PHABSIM was set up about 410.0 m from Gudam streamflow gauging station (GD) and about 6.0 km including GD for River2D. To select representative fish species and construct HSI (Habitat Suitability Index), the fish survey was performed at Pungji bridge where showed well the physical characteristics of target stream located downstream of GD. As a result of the fish survey, Zacco platypus was showed highly relative abundance resulting in selecting as the representative fish species, and HSI was constructed using physical habitat characteristics of the Zacco platypus. The optimal range of HSI was 0.3~0.5 m/s at the velocity suitability index, 0.4~0.6 m at the depth suitability index, and the substrate was sand to fine gravel. As a result of estimating the optimal ecological flow by applying HSI to PHABSIM, the optimal ecological flow for target stream was 20.0 m³/sec. As a result of analysis two-dimensional spatial analysis of fish habitat using River2D, WUA (Weighted Usable Area) was estimated 107,392.0 m²/1000 m under the ecological flow condition and it showed the fish habitat was secured throughout the target stream compared with Q₃₅₅ condition.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.