• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.6 no.2
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• pp.120-128
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• 2003

Purpose: Recently, while the authors were experiencing that the epidemic period of rotaviral infection happened more in the early spring, we tried to find out how the outbreaks of rotaviral infection are changing in detail depending on the weather condition since it has something to do with the climate factors and PM10. Methods: Fourteen hundreds seventy nine patients who were proved to be positive to rotavirus were chosen among children less than 5 years old from January 1995 to June 2003. Among various climate factors, monthly average temperature, humidity, rainfall and PM10 were selected. Results: Rotaviral infection was most active in 2002 as 309 (20.9%) patients. It has been the spring that is the most active period of rotaviral infection since 2000. The temperature (RR=0.9423, CI=0.933424~0.951163), rainfall (RR=1.0024, CI=1.001523~1.003228) and PM10 (RR=1.0123, CI=1.009385~1.015248) were significantly associated with the monthly distribution of rotaviral infection. Conclusion: Through this study we determined that the epidemic period of rotaviral infection is changed to spring, which is different from the usual seasonal periods such as late fall or winter as reported in previous articles. As increased PM10 which could give serious influence to the human body, and changing pattern of climate factors such as monthly average temperature and rainfall have something to do with the rotaviral infection, we suppose that further study concerning this result is required in the aspects of epidemiology, biology and atmospheric science.

• Tuberculosis and Respiratory Diseases
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• v.52 no.5
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• pp.529-538
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• 2002

Background : Many clinicians are reluctant to prescribe systemic corticosteroids to manage an asthmatic attack because of many complications such as osteoporosis, cushing's syndrome, diabetes, hypertension and bleeding tendency. The use of nebulized budesonide may be of value in some infants, old men, and in particular adult asthmatic patients who complain of severe dyspnea. A clinical validation and steroid-sparing effect of nebulized budesonide in asthmatic adults and COPD were evaluated, and the short-term effects of budesonide use on the HPA axis were assessed. Materials and Methods : Study A was prospectively done with 41 patients diagnosed with pure asthma and 30 patients diagnosed with COPD (including asthmatic component) in Soonchunhyang Hospital, Chunan from June. 2000 to Sep. 2001. They were treated with nebulized budesonide including systemic steroids (Group 1), a budesonide tubuhaler including a systemic steroid (Group 2), or only the systemic steroid(Group 3). The peak flow rate, arterial blood gas in room air, pulmonary function test, symptom scoring, steroid amount and hospital stay were analyzed. Study B was conducted with 19 patients to evaluate the short-term effects on the HPA axis of treatment with nebulized budesonide 1mg twice daily and a budesonide turbuhaler 5 puffs twice daily. The adrenal function was assessed prior to budesonide inhalation and after 7 days of budesonide inhalation. Results : In the pure asthmatic patients, the mean value of the symptoms (dyspnea, wheezing, cough, night asthma) or the arterial BGAs, total amounts of steroid or hospital stay and the difference in the results of the pulmonary function tests or peak expiratory flow rate were similar in the three groups. In COPD with an asthmatic component, there were no significant differences among the three groups. Although nebulized budesonide suppressed HPA function,(p=0.006) the HPA responses from the nebulized budesonide and turbuhaler budesonide were similar (p=0.288) Conclusion : This result suggests that systemic steroid should only be made available for acute asthmatic patients irrespective of the inhaled budesonides. Nebulized budesonide at the therapeutic dose has similar effects on the HPA axis compared to that of turbuhaler budesonide.

• Sleep Medicine and Psychophysiology
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• v.12 no.2
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• pp.122-132
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• 2005

Objectives: The objective of this study is to assess cognitive functions and their relationship with sleep symptoms in young narcoleptic patients. Methods: Eighteen young narcolepsy patients and 18 normal controls (age: 17-35 years old) were recruited. All narcolepsy patients had HLA $DQB_1$ *0602 allele and cataplexy. Several important areas of cognition were assessed by a battery of neuropsychological tests consisting of 13 tests: executive functions (e.g. cognitive set shifting, inhibition, and selective attention) through Wisconsin card sorting test, Trail Making A/B, Stroop test, Ruff test, Digit Symbol, Controlled Oral Word Association and Boston Naming Test; alertness and sustained attention through paced auditory serial addition test; verbal/nonverbal short-term memory and working memory through Digit Span and Spatial Span; visuospatial memory through Rey-Osterrieth complex figure test; verbal learning and memory through California verbal learning test; and fine motor activity through grooved pegboard test. Sleep symptoms in narcolepsy patients were assessed with Epworth sleepiness scale, Ullanlinna narcolepsy scale, multiple sleep latency test, and nocturnal polysomnography. Relationship between cognitive functions and sleep symptoms in narcolepsy patients was also explored. Results: Compared with normal controls, narcolepsy patients showed poor performance in paced auditory serial addition (2.0 s and 2.4 s), digit symbol tests, and spatial span (forward)(t=3.86, p<0.01; t=-2.47, p=0.02; t=-3.95, p<0.01; t=-2.22, p=0.03, respectively). There were no significant between-group differences in other neuropsychological tests. In addition, results of neuropsychological test in narcolepsy patients were not correlated with Epworth sleepiness scale score, Ullanlinna narcolepsy scale score and sleep variables in multiple sleep latency test or nocturnal polysomnography. Conclusion: The current findings suggest that young narcolepsy patients have impaired attention. In addition, impairment of attention in narcolepsy might not be solely due to sleep symptoms such as excessive daytime sleepiness.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.3
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• pp.142-154
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• 2011

This study predicted the probability of corrosion initiation of reinforced concrete tunnel boxes structures using the Monte Carlo Simulation. For the inner wall and outer wall in the tunnel boxes, exposed to airborne chloride ion and seawater directly respectively, statistical values of parameters like diffusion coefficient D, surface chloride content $C_s$, cover depth c, and the chloride threshold level $C_{lim}$ were examined from experiment or literature review. Their average values accounted for $3.77{\times}10^{-12}m^2/s$, 3.0% by weight of cement, 94.7mm and 45.5mm for outer wall and inner wall, respectively, and 0.69% by weight of cement for D, $C_s$, c, and $C_{lim}$, respectively. With these parametric values, the distribution of chloride contents at rebar with time and the probability of corrosion initiation of the tunnel boxes, inner wall and outer wall, was examined by considering time dependency of chloride transport. From the examination, the histogram of chloride contents at rebar is closer to a gamma distribution, and the mean value increases with time, while the coefficient of variance decreases with time. It was found that the probability of corrosion initiation and the time to corrosion were dependent on the time dependency of chloride transport. Time independent model predicted time to corrosion initiation of inner wall and outer wall as 8 and 12 years, respectively, while 178 and 283 years of time to corrosion was calculated by time dependent model for inner wall and outer wall, respectively. For time independent model, the probability of corrosion at 100 years of exposure for inner wall and outer wall was ranged 59.5 and 95.5%, respectively, while time dependent model indicated 2.9 and 0.2% of the probability corrosion, respectively. Finally, impact of $C_{lim}$, including values specified in current codes, on the probability of corrosion initiation and corrosion free life is discussed.

• Analytical Science and Technology
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• v.17 no.6
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• pp.496-513
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• 2004

This study was carried out to evaluate the performance of sampling and analytical methodology used for the measurement of toxic volatile organic compounds (VOCs) in the ambient air. VOCs were determined by the adsorbent tube sampling and automatic thermal desorption coupled with GC/MSD analysis. Target analytes were 33 compounds including major aromatic compounds such as BTEX, and halogenated compounds. The methodology was investigated with a wide range of different adsorbents which are commercially available and have been frequently adopted for the VOC measurement. A total of 10 adsorbents were tested in this study: 6 carbon-based adsorbents such as Carbotrap, Carbopack B, Carbosieve S-III, Carboxen 1000, Carbotrap C, Activated Charcoal; and 4 polymer-based adsorbents including Tenax, Porapak Q, Chromosorb 102, and Chromosorb 106. The sampling performance was evaluated with respect to the sampling capacity of VOCs with single-adsorbent and multiple-adsorbents methods for standard samples and field samples. As a result, the best adsorbents for single-adsorbent method in the sampling of toxic organic compounds (including benzene, toluene, xylenes etc.) appeared to be Carbotrap, Carbopack B and Tenax TA. On the other hand, Chromosorb 102, Chromosorb 106 and Porapak Q were found to be unsuitable adsorbents for VOC measurement based on thermal desorption method. Multi-adsorbent packings were evaluated with 4 carbon-based adsorbents, which classified by 3 combination sets of double adsorbents and 2 combination sets of triple adsorbents. The results indicated that the most suitable combination for toixc VOC measurements is Carbotrap C with Carbotrap. Multi-sorbents tubes packed with a strong adsorbent such as Carbosieve S-III or Carboxen 1000 were found to be relatively unsuitable for several compounds, not only owing to the effect of migration of adsorbed compounds from weaker adsorbent to stronger adsorbent, but to hydrophobic nature of the adsorbents. Therefore, it should be addressed that selection of a proper adsorbent (or combination of multi sorbents) is extremely important to obtain reliable data for the concentrations of toxic VOCs in indoor and outdoor environments.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.379-394
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• 2021

Air pollution data in South Korea is provided on a real-time basis by Air Korea stations since 2005. Previous studies have shown the feasibility of gridding air pollution data, but they were confined to a few cities. This paper examines the creation of nationwide gridded maps for PM10 concentration using 333 Air Korea stations with variogram optimization and ordinary kriging. The accuracy of the spatial interpolation was evaluated by various sampling schemes to avoid a too dense or too sparse distribution of the validation points. Using the 114,745 matchups, a four-round blind test was conducted by extracting random validation points for every 365 days in 2019. The overall accuracy was stably high with the MAE of 5.697 ㎍/m³ and the CC of 0.947. Approximately 1,500 cases for high PM10 concentration also showed a result with the MAE of about 12 ㎍/m³ and the CC over 0.87, which means that the proposed method was effective and applicable to various situations. The gridded maps for daily PM10 concentration at the resolution of 0.05° also showed a reasonable spatial distribution, which can be used as an input variable for a gridded prediction of tomorrow's PM10 concentration.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.71-82
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• 2023

Forest biomass is used as a representative indicator of forest size, maturity, and productivity. Therefore, quantitative evaluation is important for management and harvest as well as the evaluation of ecosystem functions and services including CO₂ absorption. The allometric equation is a widely used method for estimating the value of each component through the relative growth rate of plants. Recently, studies indicated that the relative growth of trees is changing because of the increased CO₂ concentration in the atmosphere and the resulting climate change, raising the need to review the previously developed relative growth models and coefficients. In this study, the height-diameter at breast height (DBH) relationships of four major tree species in Korea [(Pinus densiflora (PD), Larix kaempferi (LK), Quercus variabilis (QV), and Quercus mongolica (QM)] were analyzed using the 5th-7th National Forest Inventory (NFI) data. Furthermore, these results were compared with the present yield table from the National Institute for Forest Science. This analysis revealed that the expected height for the same DBH increased as the NFI progressed. For example, in model analysis, the expected heights for PD, LK, QV, and QM for DBH of 25 cm were 12.48, 19.17, 14.47, and 13.19 m, respectively, in the 5th NFI data. In the 7th NFI data, these values were estimated as 13.61 (+9.1%), 21.58 (+12.7%), 15.76 (+8.9%), and 13.93 m (+5.6%), respectively. These results indicate that the major tree species in South Korean forests currently are more vigorous in height growth than in diameter growth when compared to the height-DBH development trends by tree species identified through past survey data.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.