• Pediatric Infection and Vaccine
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• v.16 no.1
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• pp.40-46
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• 2009

Purpose : The purpose of this study was to identify useful predictors for diagnosing bacterial meningitis and performing CSF studies in febrile infants three months or younger. Methods : Six hundred and fifty two febrile infants with a rectal temperature ${\geq}38.0^{\circ}C$ presented from January 2003 to April 2008 and were retrospectively studied. The total white blood cell count (WBC), band count, absolute neutrophil count (ANC), quantitative C-reactive protein (CRP) and blood cultures were performed on admission. The clinical variables associated with bacterial meningitis were analyzed. Results : In patients with bacterial meningitis, the clinical variables including CRP (P=0.036), band count (P=0.037), ANC (P=0.036) and age (P=0.001) were significantly different. The area under the receiver-operating characteristic curve was 0.969 for CRP, 0.946 for the band count, 0.765 for the ANC and 0.235 for age. A CRP cutoff point of 8 mg/dL was determined to maximize both the sensitivity and specificity (sensitivity 83%, specificity 95%, likelihood ratio 16.6). A CRP concentration of <7 mg/dL "ruled-out" bacterial meningitis, with a likelihood ratio of 0.17, a posttest probability of <0.1% and negative predictive value 91%. A CRP concentration greater than 9 mg/dL had a much higher likelihood ratio (20.1) than the band count (16.6) and ANC (2.2). Conclusion : The CRP concentration was a useful laboratory test for the differential diagnosis of bacterial meningitis among febrile infants three months of age or younger. A CRP concentration of <7 mg/dL effectively ruled out bacterial meningitis; a value ${\geq}9mg/dL$ increased the clinical suspicion of bacterial meningitis and the need for CSF evaluation.

• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.74-82
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• 2016

Objectives : Suicide attempters have impaired decision making and are at high risk of reattempt. Therefore it is important to refer them to psychiatric treatment. Especially, People with medical comorbidity are at higher risk of suicidal attempt and mortality. The aim of this study was to investigate the characteristics of suicidal attempters and to analyze the influence of the medical comorbidity on decision to receive psychiatric treatment after visit to an emergency department. Methods : One hundred and thirty two patients, who visited the emergency room of a general hospital in Gyeonggi-do between January, 2012 and December, 2012 were enrolled as the subjects of this study. After reviewing each subject's medical records retrospectively, demographic and clinical factors were analyzed. Results : Regardless of the engagement type, either via admission or outpatient clinic, the determinant factors of psychiatric treatment engagement were psychiatric diagnosis, employment status, previous psychiatric treatment history, and previous attempt history. Comparison of severity of medical comorbidity(Charlson Comorbidity Index) showed that suicide attempters who received psychiatric treatment via admission or refused the treatment tended to have higher level of medical comorbidity than who received psychiatric treatment via outpatient department. Conclusions : Our findings showed that medical comorbidity of suicide attempters affected the decision to accept psychiatric treatment. All psychiatrists should evaluate the presence and the severity of medical comorbidity of the suicide attempters and consider implementing more intervention for the medically ill attempters who are willing to discharge against advice.

• Publications of The Korean Astronomical Society
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• v.36 no.3
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• pp.47-63
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• 2021

Variability is one of the major characteristics of Active Galactic Nuclei (AGN), and it is used for understanding the energy generation mechanism in the center of AGN and/or related physical phenomena. It it known that there exists a time lag between AGN light curves simultaneously observed at different wavelengths, which can be used as a tool to estimate the size of the area that produce the radiation. In this paper, We present long term near-infrared variability of optically bright type 1 AGN using the Wide-field Infrared Survey Explorer data. From the Milliquas catalogue v6.4, 73 type 1 QSOs/AGN and 140 quasar candidates are selected that are brighter than 18 mag in optical and located within 5 degree around the ecliptic poles. Light curves in the W1 band (3.4 ㎛) and W2 band (4.6 ㎛) during the period of 2010-2019 were constructed for these objects by extracting multi-epoch photometry data from WISE and NEOWISE all sky survey database. Variability was analyzed based on the excess variance and the probability P_var. Applying both criteria, the numbers of variable objects are 19 (i.e., 26%) for confirmed AGN and 12 (i.e., 9%) for AGN candidates. The characteristic time scale of the variability (τ) and the variability amplitude (σ) were derived by fitting the DRW model to W1 and W2 light curves. No significant correlation is found between the W1/W2 magnitude and the derived variability parameters. Based on the subsample that are identified in the X-ray source catalog, there exists little correlation between the X-ray luminosity and the variability parameters. We also found four AGN with changing W1-W2 color.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.293-300
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• 2012

This study was to investigate the unsuitable rate of the storage facilities, the changes in corrosion process over time after installation according to the status, the time to install the facilities, years elapsed after facilities installation, inspection of methods and motivation, and so on, based on the results of the inspection at the petroleum storage facilities conducted by domestic soil-relate specialized agency to derive optimal management plans which meet the status of soil contamination facilities. The results showed that the facilities more than 5 years after the initial leak test at the time of the installation need to be inspected periodically by considering costs of leak test and remediation of polluted soil. The inspection period can be decided by cost and leak test methods showing discrepancies for the results obtained from individual test whether it was direct or indirect. To compensate these matters, we suggested that the direct inspection method on regular schedule is recommended. On the other hand, the inspection can be voluntarily completed to ease burden of the results by inspection or equivalent level to this inspection method. Also, it may need improved construction supervision and performance test system to minimize the occurrence of the nature defects in installing the facilities as well as the upgrade program for the facilities during intervals of inspection period.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Radiation Oncology Journal
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• v.16 no.3
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• pp.265-274
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• 1998

Purpose : This prospective study has been conducted to assess the value of three dimensional conformal radiation therapy (3DCRT) for lung cancer and to determine its potential advantage over current treatment approaches. Specific aims of this study were to 1) find the most ideal 3DCRT technique 2) establish the maximum tolerance dose that can be delivered with 3DCRT and 3) identify patients at risk for development of radiation pneumonitis. Materials and Methods : Beginning in Nov. 1994, 95 patients with inoperable non-small cell lung cancer (stage I; 4, stage II; 1, stage IIIa; 14, stage IIIb; 76) were entered onto this 3D conformal trial Areas of known disease and elective nodal areas were initially treated to 45 Gy and then using 3DCRT technique 65 to 70 Gy of total dose were delivered to the gross disease. Sixty nine patients received 65 Gy of total dose and 26 received 70 Gy Seventy eight patients (82.1$\%$) also received concurrent MVP chemotherapy. 3DCRT plans were compared with 2D plans to assess the adequacy of dose delivery to target volume, dose volume histograms for normal tissue, and normal tissue complication Probabilities (NTCP). Results : Most of plans (78/95) were composed of non-coplanar multiple (4-8) fields. Coplanar segmented conformal therapy was used in 17 pateints, choosing the proper gantry angle which minimize normal lung exposure in each segment. 3DCRT gave the full dose to nearly 100$\%$ of the gross disease target volume in all patients. The mean NTCP for ipsilateral lung with 3DCRT (range; 0.17-0.43) was 68$\%$ of the mean NTCP with 2D treatment planning (range; 0.27-0.66). DVH analysis for heart showed that irradiated volume of heart could be significantly reduced by non-coplanar 3D approach especially in the case of left lower lobe lesion. Of 95 patients evaluable for response, 75 (79$\%$), showed major response including 25 (26$\%$) with complete responses and 50 (53$\%$) with partial responses. One and two rear overall survivals of stage III patients were 62.6$\%$ and 35.2$\%$ respectively. Twenty percent (19/95) of patients had pneumonitis; Eight patients had grade 1 pneumonitis and 11 other patients had grade 2. Comparison of the average of NTCP for lung showed a significant difference between patients with and without radiation pneumonitis. Average NTCP for Patients without complication was 62$\%$ of those with complications. Conclusions : This study showed that non-coplanar multiple fields (4-8) may be one of the ideal plans for 3DCRT for lung cancer. It also suggested that 3DCRT may provide superior delivery of high dose radiation with reduced risk to normal tissue and that NTCP can be used as a guideline for the dose escalation.

• Proceedings of the Safety Management and Science Conference
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• 2004.11a
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• pp.355-380
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• 2004

I test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. Using thirty-six industry portfolios and the broad market index as our test assets, I establish several key results. First, a number of industries such as semiconductor, electronics, metal, and petroleum lead the stock market by up to one month. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets. Traditional theories of asset pricing assume that investors have unlimited information-processing capacity. However, this assumption does not hold for many traders, even the most sophisticated ones. Many economists recognize that investors are better characterized as being only boundedly rational(see Shiller(2000), Sims(2201)). Even from casual observation, few traders can pay attention to all sources of information much less understand their impact on the prices of assets that they trade. Indeed, a large literature in psychology documents the extent to which even attention is a precious cognitive resource(see, eg., Kahneman(1973), Nisbett and Ross(1980), Fiske and Taylor(1991)). A number of papers have explored the implications of limited information- processing capacity for asset prices. I will review this literature in Section II. For instance, Merton(1987) develops a static model of multiple stocks in which investors only have information about a limited number of stocks and only trade those that they have information about. Related models of limited market participation include brennan(1975) and Allen and Gale(1994). As a result, stocks that are less recognized by investors have a smaller investor base(neglected stocks) and trade at a greater discount because of limited risk sharing. More recently, Hong and Stein(1999) develop a dynamic model of a single asset in which information gradually diffuses across the investment public and investors are unable to perform the rational expectations trick of extracting information from prices. Hong and Stein(1999). My hypothesis is that the gradual diffusion of information across asset markets leads to cross-asset return predictability. This hypothesis relies on two key assumptions. The first is that valuable information that originates in one asset reaches investors in other markets only with a lag, i.e. news travels slowly across markets. The second assumption is that because of limited information-processing capacity, many (though not necessarily all) investors may not pay attention or be able to extract the information from the asset prices of markets that they do not participate in. These two assumptions taken together leads to cross-asset return predictability. My hypothesis would appear to be a very plausible one for a few reasons. To begin with, as pointed out by Merton(1987) and the subsequent literature on segmented markets and limited market participation, few investors trade all assets. Put another way, limited participation is a pervasive feature of financial markets. Indeed, even among equity money managers, there is specialization along industries such as sector or market timing funds. Some reasons for this limited market participation include tax, regulatory or liquidity constraints. More plausibly, investors have to specialize because they have their hands full trying to understand the markets that they do participate in

• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1296-1307
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• 1997

Background : Erdosteine is a thiol derivative developed for the treatement of chronic obstructive bronchitis, including acute infective exacerbation of chronic bronchitis. Erdosteine has mucomodulating and antioxidant properties and especially exhibits excellent gastrointestinal tolerability. Methods : The study was conducted as a prospective evaluation, with 2 comparative groups orally treated with erdosteine 300mg (bid.) or ambroxol 30mg (b.i.d.) for 7 days and the design of trial was double-blind. The treatments have been assigned randomly to patients (n=80) with acute or chronic bronchitis. The primary end-point used to determine efficacy in this study was subjective symptoms including expectorating frequence, expectoration volume, expectorating difficulty, expectoration viscosity, cough intensity and dyspnea. The secondary end-points of efficacy was the result of arterial blood gas analysis and pulmonary function test. Safety was evaluated with adverse drug reactions and laboratory tests monitoring. 61 patients was included in the efficacy analysis, due to the fact that 19 patients drop-out for different reasons. The obtained values have been analyzed with paired Hest., ANOVA test., multivariate $t^2$-test, repeated measures analysis of covariance, two sample t-test, loglinear-logit model analysis, Fisher's exact test. Results : 1) There was no significant difference on demographic data and vital signs between erdosteine and ambroxol treated groups. 2) The comparison between erdosteine and ambroxol treated groups showed no significant difference in improvement of each symptom in spite of the more favorable efficacy obtained with erdosteine. No difference on the contrary was observed for arterial blood gas analysis and pulmonary function test. 3) As safety is concerned, no clinical significant changes in laboratory test and symptom were induced in erdosteine and ambroxol treated group and two patients in ambroxol treated group drop-out for adverse reactions in symptom. 4) In the evaluation of final clinical efficacy, erdosteine improved more effectively patient's overall symptoms {very good effect (11/31), good effect (12/31), moderate effect (6/31), no effect (2/31), aggravation (0/31)} than ambroxol {very good effect (6/30), good effect (14/30), moderate effect (5/30), no effect (4/30), aggravation (2/30)}. And the probability of symptomatic improvement by erdosteine compared to ambroxol was 2.5 times. (p<0.05). Conclusion : This study showed that erdosteine was clinically effective and safe drug for treatment of acute and chronic bronchitis.