• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.463-477
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• 2009

Parameter estimation methods such as maximum likelihood estimation method, probability weighted moments method, regression method have been popularly applied to various extreme value models in numerous literature. Among three methods above, the performance of regression method has not been rigorously investigated yet. In this paper the regression method is compared with the other methods via Monte Carlo simulation studies for estimation of parameters of the Generalized Extreme Value(GEV) distribution and the Generalized Pareto(GP) distribution. Our simulation results indicate that the regression method tends to outperform other methods under small samples by providing smaller biases and root mean square errors for estimation of location parameter of the GEV model. For the scale parameter estimation of the GP model under small samples, the regression method tends to report smaller biases than the other methods. The regression method tends to be superior to other methods for the shape parameter estimation of the GEV model and GP model when the shape parameter is -0.4 under small and moderately large samples.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.443-450
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• 2020

The purpose of this study was to examine the inter-rater and intra-rater reliability of the oral mucosa pressure ulcer classification system based on the photographs. The study consisted of two stages; development and evaluation. In the developmental stage, 9 photographs of 82 were selected. In the evaluation stage, a total of 49 participants were invited web-based survey by e-mail. Cohen's weighted kappa and Krippendorff's alpha were used to define the inter-rater reliability. Nine photographs consisted of two, three, three, and one in normal, stage 1, stage 2, and stomatitis, respectively. The inter-rater reliabilities of wound care nurse specialist, intensive care nurse specialist, and dentist groups were 0.75, 0.70, and 0.78, respectively. The intra-rater reliability was 0.73. The inter-rater and intra-rater reliabilities of the oral mucosa pressure ulcer classification system showed substantially good agreement.

• The Journal of Internal Korean Medicine
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• v.38 no.5
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• pp.769-777
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• 2017

Objective: Facial nerve palsy is caused by damage to the 7th cranial nerve. It is the main symptom of facial muscle paralysis on the affected side. Usually, recovery from this disease begins 2-3 weeks after onset and most patients recover in 4-8 weeks. If the patients cannot receive proper treatment, severe permanent impairments, both physical and mental, may remain, so this disease should be treated appropriately. In this study, a patient with facial nerve palsy was admitted to the Korean medicine hospital for treatment. We report on the patient's progress and the effects of treatment. Methods: We cured the patient with herbal medicines, acupuncture, herbal acupuncture therapy, and physical therapy. We used a numerical rating scale, the House Brackmann grading system, and a weighted regional grading system to assess symptom changes. Result: The patient with facial nerve palsy was hospitalized for 23 days and recovered from symptoms without significant problems on the face or in motor function.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.625-632
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• 2001

The electronic stores have realized that they need to understand their customers and to quickly response their wants and needs. To be successful in increasingly competitive Internet marketplace, recommender systems are adapting data mining techniques. One of most successful recommender technologies is collaborative filtering (CF) algorithm which recommends products to a target customer based on the information of other customers and employ statistical techniques to find a set of customers known as neighbors. However, the application of the systems, however, is not very suitable for seasonal products which are sensitive to time or season such as refrigerator or seasonal clothes. In this paper, we propose a new adjusted item-based recommendation generation algorithms called the exponentially weighted collaborative filtering recommendation (EWCFR) one that computes item-item similarities regarding seasonal products. Finally, we suggest the recommendation system with relatively high quality computing time on main memory database (MMDB) in XML since the collaborative filtering systems are needed that can quickly produce high quality recommendations with very large-scale problems.

• The Korean Journal of Pain
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• v.24 no.1
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• pp.7-12
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• 2011

Background: Adenosine has been shown to have a wide spectrum of unique pain-relieving effects in various clinical situations. The aim of this study was to investigate the effects of intraoperative adenosine infusion on acute opioid tolerance and opioid induced hyperalgesia induced by remifentanil in adult patients undergoing tonsillectomy. Methods: For this study, ninety patients were randomly allocated into groups that receive either adenosine (adenosine group) or saline (remifentnail group) intravenously under remifentanil based anesthesia and saline (sevoflurane group) under sevoflurane anesthesia. The patients in adenosine group received adenosine at dose of $80\;{\mu}g$/kg/min, and those in remifentnail group and sevoflurane group received an equal volume of saline 10 minutes after the induction of anesthesia until the end of surgery. Intraoperative evaluation included time weighted mean remifentanil dose, and postoperative evaluations included degree of pain severity at 1, 6, 12, and 24 hours, time to first postoperative requirement, and analgesic dose required during 24 hours after operation. Results: Time weighted mean remifentanil dose during intraoperative period in adenosine group was significantly lower than that of remifentnail group (P = 0.00). The first postoperative analgesic were required earlier in remifentanil group than sevoflurane group or adenosine group (P = 0.00). Pethidine requirement during 24 hours in sevoflurane group and adenosine group was significantly lower than that of remifentnail group (P = 0.00). The visual analog scale scores for pain in sevoflurane group and adenosine group were significantly lower than those of remifentnail group for 12 hours after operation (P = 0.00). Incidence of hypotension (P = 0.024) and number of ephedrine administered (P = 0.011) in adenosine group were significantly higher than those of sevoflurane group. Conclusions: The above results suggest that intraoperative adenosine infusion prevent acute opioid tolerance and opioid induced hyperalgesia induced by remifentanil.

• Journal of Environmental Impact Assessment
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• v.23 no.1
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• pp.39-50
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• 2014

In recent years, the frequency and scale of the natural disasters are growing rapidly due to the global climate change. In case of the urban flooding, high-density of population and infrastructure has caused the more intensive damages. In this study, we analyzed the spatial characteristics of urban flooding damage factors using GWR(Geographically Weighted Regression) for effective disaster prevention and then, classified the causes of the flood damage by spatial characteristics. The damage factors applied consists of natural variables such as the poor drainage area, the distance from the river, elevation and slope, and anthropogenic variables such as the impervious surface area, urbanized area, and infrastructure area, which are selected by literature review. This study carried out the comparative analysis between OLS(Ordinary Least Square) and GWR model for identifying spatial non-stationarity and spatial autocorrelation, and in the results, GWR model has higher explanation power than OLS model. As a result, it appears that there are some differences between each of the flood damage areas depending on the variables. We conclude that the establishment of disaster prevention plan for urban flooding area should reflect the spatial characteristics of the damaged areas. This study provides an improved understandings of the causes of urban flood damages, which can be diverse according to their own spatial characteristics.

• Journal of Korean Society of Rural Planning
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• v.20 no.4
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• pp.13-24
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• 2014

The pond wetlands in agricultural landscape are important natural resources that carry out the function of bio-diversity conservation. However, recently, those have been gradually embedded as their utility value were disappeared. And, the assessment methods used for pond wetlands are insufficient. Therefore, this study was conducted to examine the conservation value of pond wetlands by using the modified RAM, and present the improvement of assesment methods. The study sites, a total of 32 pond of 4 types by land use, were selected on the basis of Ramsar Convention. Through the analysis of precedent studies, the weighted 8 functions were adjusted. According to the assessment results, pond wetlands made the largest contribution to Fishery and Herpetile Habitat function. In addition, it also made large contribution to Floral Diversity, Wildlife Habitat, and Water Quality Protection function. On the other hand, it made a small contribution to Aesthetics and Recreation, Runoff Attenuation, Shoreline /Stream Bank Protection, and Flood/Storm Water Storage function due to the characteristics of small-scale pond wetlands. In the assessment of 8 functions, house type showed the worst assessment result, and mountain type showed the best assessment result. It is thought that those are due to land use type in terms of vicinity. 10 items among 52 of the modified RAM showed the same assessment results in all land use types. Accordingly, it is required to be deleted and modified the assessment method. On the other hand, it is required to add age, interference, and water use to the assessment method. It is thought that these results can be utilized for the development and modification of assessment methods focused on pond wetlands in rural area.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.323-341
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• 2021

Various research are being published in the areas of humanities, history, aviation/ports, and regional development, centering on the Incheon area which has issues such as large-scale ports and airports, archipelago, and urban regeneration. This study explored the scope of the subject and the distribution of researchers using a informetric analysis focusing on the studies of Incheon. Specifically, this study extracted authors from about 500 Incheon-related research papers listed in the Korean journal's citation index and analyzed the co-author relationship network to understand the cooperative behavior between authors' institutions. In addition, by extracting keywords from the articles and performing a weighted network (PFNET) analysis on the relationship between keywords, the intellectual structure was analyzed. As a result, it was found that Inha University and Incheon National University showed a high TBC, and Incheon Development Institute showed the high NNC. Meanwhile, the intellectual structure of Incheon-related research was found to be composed of 11 thematic clusters, and the social issues of Incheon, ports, and aviation were analyzed as representative clusters.

• Journal of Korean Neurosurgical Society
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• v.65 no.1
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• pp.13-21
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• 2022

Objective : Nontraumatic subdural hematoma (SDH) is a common disease, and spinal cerebrospinal fluid (CSF) leakage is a possible etiology of unknown significance, which is commonly investigated by several invasive studies. This study demonstrates that heavily T2-weighted magnetic resonance myelography (HT2W-MRM) is a safe and clinically effective imaging modality for detecting CSF leakage in patients with nontraumatic SDH. Methods : All patients who underwent HT2W-MRM for nontraumatic SDH workup at our institution were searched and enrolled in this study. Several parameters were measured and analyzed, including patient demographic data, initial modified Rankin Scale (mRS) score upon presentation, SDH bilaterality, hematoma thickness upon presentation, CSF leakage sites, treatment modalities, follow-up hematoma thickness, and follow-up mRS score. Results : Forty patients were identified, of which 22 (55.0%) had CSF leakage at various spinal locations. Five patients (12.5%) showed no change in mRS score, whereas the remaining (87.5%) showed decreases in follow-up mRS scores. In terms of the overall hematoma thickness, four patients (10.0%) showed increased thickness, two (5.0%) showed no change, 32 (80.0%) showed decreased thickness, and two (5.0%) did not undergo follow-up imaging for hematoma thickness measurement. Conclusion : HT2W-MRM is not only safe but also clinically effective as a primary diagnostic imaging modality to investigate CSF leakage in patients with nontraumatic SDH. Moreover, this study suggests that CSF leakage is a common etiology for nontraumatic SDH, which warrants changes in the diagnosis and treatment strategies.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1273-1283
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• 2019

This paper proposes an advanced crop classification model that combines a procedure for weighted combination of spatial features extracted from multi-scale input images with a conventional convolutional neural network (CNN) structure. The proposed model first extracts spatial features from patches with different sizes in convolution layers, and then assigns different weights to the extracted spatial features by considering feature-specific importance using squeeze-and-excitation block sets. The novelty of the model lies in its ability to extract spatial features useful for classification and account for their relative importance. A case study of crop classification with multi-temporal Landsat-8 OLI images in Illinois, USA was carried out to evaluate the classification performance of the proposed model. The impact of patch sizes on crop classification was first assessed in a single-patch model to find useful patch sizes. The classification performance of the proposed model was then compared with those of conventional two CNN models including the single-patch model and a multi-patch model without considering feature-specific weights. From the results of comparison experiments, the proposed model could alleviate misclassification patterns by considering the spatial characteristics of different crops in the study area, achieving the best classification accuracy compared to the other models. Based on the case study results, the proposed model, which can account for the relative importance of spatial features, would be effectively applied to classification of objects with different spatial characteristics, as well as crops.