• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.60-75
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• 2022

The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Journal of the Korean Orthopaedic Association
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• v.54 no.2
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• pp.133-140
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• 2019

Purpose: This study examined the radiological and clinical outcomes of tibiotalocacalcaneal arthrodesis using retrograde intramedullary nailing in a severe hindfoot deformity and ankle/subtalar arthritis. Materials and Methods: A total of 22 patients (22 cases) with a severe hindfoot deformity and arthritis underwent tibiotalocalcaneal arthrodesis with retrograde intramedullary nails. The average age was 57.4 years (22-82 years) and the mean follow-up was 29.6 months (12-74 months). The radiological outcomes included an assessment of the preoperative and postoperative coronal ankle alignment, hindfoot alignment, sagittal alignment, and postoperative union time. The clinical outcomes were evaluated using the visual analogue scale (VAS), American Orthopaedic Foot and Ankle Society (AOFAS) score, and postoperative complications. The results were analyzed statistically by dividing the patients into two groups based on a 10° angle of deformity. Results: Regarding the preoperative coronal ankle alignment, 14 patients had a mean varus deformity of 17.8°±14.5° and six had a mean valgus deformity of 8.1°±6.6°. Postoperatively, a satisfactory postoperative coronal ankle alignment of less than 5° was obtained in all patients. Regarding the preoperative hindfoot alignment, 12 patients showed a mean varus deformity of 15.2°±10.5° and six had a mean valgus deformity of 8.1°±4.2°. In total, 94.4% (17 patients) had satisfactory postoperative hindfoot alignment of less than 5°. Radiological union was achieved in 90.9% at an average of 19.2 weeks (12-32 weeks) and there were 2 cases of nonunion. The clinical outcomes showed improvement in the mean VAS and AOFAS scores (p<0.001, p<0.001, respectively). Even a preoperative severe deformity more than 10° showed a significant deformity correction of coronal ankle alignment and hindfoot alignment, postoperatively (p<0.001, p<0.001, respectively). No significant differences were found between the patients with a preoperative coronal ankle deformity more than 10° and those less than 10° regarding the mean postoperative coronal ankle alignment (p=0.162). Conclusion: Tibiotalocalcaneal arthrodesis using retrograde intramedullary nailing is an acceptable technique for achieving satisfactory deformity correction, high union rate with minimal complications, and improvement of the clinical outcomes. In addition, tibiotalocalcaneal arthrodesis using retrograde intramedullary nailing is considered an effective treatment option, particularly in severe ankle and hindfoot deformities.

• Journal of the Korean Orthopaedic Association
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• v.54 no.5
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• pp.427-434
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• 2019

Purpose: This study evaluated the long term clinical and radiographic results and the survival rates of unicompartmental knee arthroplasty (UKA). In addition, the factors affecting the survival of the procedure were analyzed and the survival curve was compared according to the affecting factors. Materials and Methods: Ninety-nine cases of UKA performed between December 1982 and January 1996 were involved: 10 cases with Modular II, 44 cases with Microloc, and 45 cases with Allegretto prostheses. The mean follow-up period was 16.5 years. Clinically, the hospital for special surgery (HSS) scoring system and the range of motion (ROM) were evaluated. Radiographically, the femorotibial angle (FTA) was measured. The survival rate was analyzed using the Kaplan-Meier method. Cox regression analysis was used to identify the factors affecting the survival according to age, sex, body mass index, preoperative diagnosis, and type of implant. The Kaplan-Meier survival curves were compared according to the factors affecting the survival of UKA. Results: The overall average HSS score and ROM was 57.7 and 134.3° preoperatively, 92.7 and 138.4° at 1 year postoperatively, and 79.1 and 138.4° at the last follow-up (p<0.001, respectively). The overall average FTA was varus 0.8° preoperatively, valgus 4.1° at postoperative 2 weeks, and valgus 3.0° at the last follow-up. The overall 5-, 10-, 15- and 20-year survival rates were 91.8%, 82.9%, 71.0%, and 67.0%, respectively. The factors affecting the survival were the age and type of implant. The risk of the failure decreased with age (hazard ratio=0.933). The Microloc group was more hazardous than the other prostheses (hazard ratio=0.202, 0.430, respectively). The survival curve in the patients below 60 years of age was significantly lower than those of the patients over 60 years of age (p=0.003); the survival curve of the Microloc group was lower compared to the Modular II and Allegretto groups (p=0.025). Conclusion: The long-term clinical and radiographic results and survival of UKA using old fixed bearing prostheses were satisfactory. The selection of appropriate patient and prosthesis will be important for the long term survival of the UKA procedure.

• The Journal of the Society of Stroke on Korean Medicine
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• v.12 no.1
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• pp.24-31
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• 2011

Objective : Fire and heat related symptoms and signs are considered common in acute stage of diseases. The purpose of this study is to evaluate the occurrences and changes of fire and heat related symptoms and signs in acute cerebral infarction patients. Method & subjects : 40 acute cerebral infarction patients hospitalized in Oriental medicine hospital, Kyung-Hee University, who had examined and diagnosed 2 or 3 times based on oriental medical diagnosis were selected. We chose 23 as fire and heat related symptoms and signs from 94 diagnostic articles, and we added all those scores together of each patient. We analysed the scores of fire and heat related symptoms and signs as the time passed, and depending on oriental medical diagnosis. Result : In acute cerebral infarction patients of this study, 4 of fire and heat related symptoms and signs were took 1st, 2nd, 4th and 8th places in most changeable 10 articles of total 94 articles. The mean score of fire and heat related symptoms and signs of all patients were decreased significantly over the 3 times of measurements. The 8 patients diagnosed as fire and heat diagnosis at visit1 were samely diagnosed as fire and heat diagnosis at visit2, and at visit3 5 patients of them except for 3 patients excluded between visit2 and visit3, were still diagnosed as fire and heat diagnosis. At all of 3 measuring times, the scores of fire and heat related symptoms and signs of fire and heat diagnosis group were higher than non-fire and heat diagnosis group. Conclusion : This study indicated that fire and heat related symptoms and signs were very changeable phenomenon in acute cerebral infarction patients. And they decreased as time goes on.

• Korean Journal of Cognitive Science
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• v.34 no.2
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• pp.111-151
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• 2023

It is reported that binge drinkers show cognitive impairment similar to alcohol use disorder patients. A previous studies using neuropsychological tests and brain imaging techniques to investigate the visual perception of alcohol use disorder patients reported that they had global-local visual perception defects. Although the neurological basis for the global-local visual perception deficit in the heavy drinking group has been presented, there are no studies to date that have investigated the global-local visual perception in the heavy drinking group. This study investigated local-biased visual perception in female college students with binge drinking (BD) using event-related potentials (ERPs). Based on the scores of the Korean version of Alcohol Use Disorder Identification Test and the Alcohol Use Questionnaire, participants were assigned into BD (n=25) and non-BD (n=25) groups. Local-global visual processing was assessed using a local-global paradigm, in which large stimuli (global level) composed of small stimuli (local level) were presented. The stimuli presented at global and local levels were either congruent or incongruent. The behavioral results exhibited that the BD and non-BD groups did not differ in terms of accuracy and response time. In terms of ERPs, the BD and non-BD groups did not show difference in N100, P150 and N200 amplitude. However, the BD group showed significantly smaller P300 amplitude than non-BD group especially in the local condition. In addition, a negative correlation between P300 amplitude and binge drinking score was observed, i.e., severer binge drinking smaller P300 amplitude. The P300 is known to reflect cognitive inhibition and attentional allocation. In the global-local paradigm, the local condition required to attend to local target while ignoring global non-target. Therefore, the present results indicate that female college students with BD do not have local-biased visual processing, instead they seem to have difficulties in inhibition of irrelevant stimuli.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Sleep Medicine and Psychophysiology
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• v.29 no.1
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• pp.21-28
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• 2022

Objectives: Our study aimed to investigate the relationship between the anxiety at first year and chronotype and sleep quality at third year in medical students. We also investigated the association between sleep quality, chronotype, depression and resilience at third year. Methods: Fifty two medical students (36 males, 69%, aged 21 ± 0.93) in first year, and forty four medical students (31 males, 70.5%, aged 23.05 ± 0.99) at third year answered Beck Depression Inventory 2, Beck anxiety inventory, Insomnia severity index-K, Composite scale of morningness and Conner-Davidson Resilience scale-10. Multiple linear regression analysises were performed to identify predictors of chronotype, sleep quality and resilience. Results: Higher anxiety (β = -0.434, p = 0.006) at first year was significant predictor of eveningness at third year, while lower anxiety score (β = 0.606, p < 0.001) at first year was significant predictor of sleep quality at third year. Lower sleep quality (β = -0.314, p = 0.042) and eveningness (β = 0.315, p = 0.041) were associated with low resilience at third year. Also, Lesser depression (β = -0.717, p < 0.001) was associated with higher resilience at third year. Conclusion: Our study showed that higher anxiety in first year had significantly related with eveningness and poor sleep quality at third year. In addition, higher sleep quality, morningness and less depression had significantly associated with better resilience at third year.

• Journal of the Korean Society of Food Culture
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• v.21 no.6
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• pp.653-660
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• 2006

Some quality characteristics of tofu prepared with cuttlefish ink were investigated to study the effects of various of coagulants. Each concentration of coagulant was determined as 0.2% of GDL, 0.3# of $MgCl_2$, 1%^ of $CaCl_2$, 1.5% of $CaSO_4$ and 0.6% D-gluconic acid calcium by pre-experiment. Also, the optimum concentration of added cuttlefish ink was chosen as 3%(diluted in twenty times). The yield of inky tofu prepared with GDL as coagulant was the highest. According to prepared with $MgCl_2$ was the highest. The result of microstructure was examined by SEM, the particles of inky tofu coagulated with GDL and D-gluconic acid calcium were small and uniformity. In overall acceptability of sensory properties, inky tofu coagulated with GDL was the highest in score. In the color of inky tofu, L value and a value were the highest coagulated with GDL, but that coagulated with $CaCl_2$ had the highest b value. In the texture properties of inky tofu, hardness, gumminess and brittleness were the highest coagulated with D-gluconic acid calcium. A positive correlation was observed between the pH of tofu whey and acidity. Sensory properties of roasted nutty flavor, hardness, cohesiveness and springiness were positively correlated with the acceptability.