• Journal of Korean Society for Atmospheric Environment
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• v.17 no.4
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• pp.331-345
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• 2001

The increase of carbon monoxide in the ambient air due to the emissions from point sources without control was estimated using three -dimensional numerical models. The target area was Ulsan where one of the largest industrial complexes was located. As a typical example using numerical models for air quality impact analysis of criteria pollutants that will determine whether the air quality standards would be exceeded or not, the following approaches were suggested. They include: (1) investigation of pre-existing atmospheric conditions, (2) identification of major factors causing high concentrations, (3) selection of episode days. (4) preparation of three-dimensional meteorological data, (5) confirmation of agreement between measured and predicted concentrations in the emission conditions of episode days, and (6) estimation of the impact due to changes of the emission conditions. In the present work, daily meteorological conditions for the specific period were classified into four clusters of distinctive features, and the episode days were selected individually from each cluster. Emphasis was placed on the selection of episodes representing meteorological conditions conducive to high concentrations especially for point sources that were sensitive to the wind direction variations.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.214-221
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• 2019

This study attempted to extend Korean Wave literature by investigating (a) the influence of protagonists' personality characteristics and the role of empathy under the affective disposition theory, and (b) the power of some external factors in the entertainment media selection. After watching an episode of the popular Korean drama, Secret Garden, participants completed a survey in the United States. Results demonstrated that (a) the effect of personality characteristics varied across gender and (b) external factors affects the entertainment media selection positively. Findings indicate that media enjoyment is dependent on the audience's external factors.

• Journal of IKEEE
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• v.23 no.4
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• pp.1150-1156
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• 2019

This paper explores a model-free value-based approach for solving survival gridworld problem. Survival gridworld problem opens up a challenge involving taking risks to gain better rewards. Classic value-based approach in model-free reinforcement learning assumes minimal risk decisions. The proposed method involves a hybrid on-policy and off-policy updates to experience roll-outs using a modified Q-based update equation that introduces a parametric linear rectifier and motivational discount. The significance of this approach is it allows model-free training of agents that take into account risk factors and motivated exploration to gain better path decisions. Experimentations suggest that the proposed method achieved better exploration and path selection resulting to higher episode scores than classic off-policy and on-policy Q-based updates.

• Journal of Preventive Medicine and Public Health
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• v.37 no.2
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• pp.150-156
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• 2004

Objectives : To investigate the utilization patterns of non-steroidal anti-inflammatory drugs (NSAIDs) among the elderly with osteoarthritis (OA) undergoing primary ambulatory care in Busan metropolitan city, Korea. Methods : OA patients, aged 65 years and over, were identified from the Korean National Health Insurance Review Agency drug prescription database. The subjects had at least one episode of claim for OA (ICD-10-CM: M15-M19) between August 1, 2000 and February 28, 2002. Trends in the determinations of NSAIDs utilization were identified using chi-squared tests for trend. Results : There were 47,711 osteoarthritic patients. The total number of visits by these patients was 177,443, with a total frequency for NSAID prescriptions of 214,952. Seventy-nine percent of the OA patients were female. NSAIDs were prescribed on 133,284 visits (75.1%) and the proportion of prescriptions was significantly increased with age. Only the proportion of visit when NSAIDs were prescribed decreased, from 65.1 to 43.5%, during the study period (p<0.001). However, the proportion of combined treatments with anti-ulcer drugs was increased. The use of NSAIDs injections was decreased. Of the individual NSAIDs, diclofenac (28.7% of total frequency of NSAID prescriptions), piroxicam (15.0%) and talniflumate (8.7%), were the most frequently prescribed. Among the NSAIDs prescribed OA visits, 45.7% used two or more NSAIDs. Conclusion : The total proportion of NSAIDs prescribed to the osteoarthritic patients was higher than in other studies. The decline in the use of NSAIDs during the study period, and the frequent selection of safer medications, such as combination therapy with anti-ulcer drug, may reflect the risk awareness of the use of NSAIDs.

• Kosin Medical Journal
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• v.33 no.2
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• pp.159-170
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• 2018

Objectives: The purpose of this study was to compare antibiotic resistance patterns between first urinary tract infection (UTI) and recurrent UTI groups and to obtain information regarding empirical antibiotic selection for treating recurrent UTI. Methods: We retrospectively reviewed 148 children treated for UTIs from January 2009 to June 2016. The patients were divided into two groups: first UTI (N = 148) and recurrent UTI (17 patients and 20 episodes). Results: In both groups, Escherichia coli was the most frequent causative organism, accounting for 89.9% and 75.0% in the first and recurrent UTI groups, respectively. When E. coli or Klebsiella pneumoniae was the causative organism, extended-spectrum ${\beta}-lactamase$ (ESBL)-producing organisms were more frequent in the recurrent UTI group (17.6%) than in the first UTI group (14.0%); however, this difference was not statistically significant (P = 0.684). Cefotaxime was the most frequently used first-line empirical antibiotic in both groups. In the first UTI and recurrent UTI groups, 7.4% and 15.0% of patients were treated with intravenous antibiotics as definitive therapy, respectively (P = 0.250). Fifteen out of 17 patients having a second UTI had different causative organisms or antibiotic susceptibility patterns compared to their previous episode. Conclusions: Escherichia coli was the most frequent causative organism in the recurrent UTI group. There were no differences in the proportion of ESBL-producing organisms between the first UTI and recurrent UTI groups. Therefore, when a UTI recurs in children, the antibiotics effective on the most common causative organism might be administered as empirical antibiotics.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.

• Clinical and Experimental Pediatrics
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• v.48 no.7
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• pp.716-722
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• 2005

Purpose : A full view of the spectrum of all bacterial diseases in healthy children is essential to the establishment of public health priorities. Accurate information on the relative importance of the various pathogens in terms of the age of the affected patients, the site of infection and the case fatality rate are valuable to the clinician in choosing antimicrobial treatments. Methods : Fifty-nine episodes of bacteremia were analysed. Data were collected at Ilsan Paik Hospital from January 2000 to December 2003. Analysis of each collected episode included isolating pathogen from blood culture, diagnosis, hospital course, isolating pathogens from other tissue sites, and studying results of antimicrobial sensitivity tests. Results : Fifty-nine cases of community-acquired bacteremia were reviewed. The most common pathogen was Staphylococcus aureus(11 cases, 18.6 percent), followed by Salmonella(10 cases, 16.9 percent), E. coli(7 cases, 11.9 percent), Streptococcus pneumoniae(five cases, 8.5 percent), Streptococcus viridans(5 cases 8.5 percent). The most common diagnosis was bacteremia without an indentified focus(61 percent), followed by meningitis(12 percent), bacteremia with enteritis(10.2 percent) and bacteremia with urinary tract infection(8.5 percent). Salmonella was still an important causative agent of bacteremia. The relative importance of Haemophilus influenza and Streptococcus pneumoniae was lower than in other studies. The most common organism responsible for bacteremia without an identified focus was Staphylococcus aureus. The case-fatality was 3.4 percent for all cases of bacteremia. Conclusion : We reviewed the etiology of community-acquired bacteremia. These data may be useful in the establishment of public health priorities and serve as a reference for selection of antibiotics in the empirical therapy of suspected invasive bacterial infection.