• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.126-134
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• 2019

Nowadays, since there are so many big data available everywhere, those big data can be used to find useful information to improve design and operation by using various analysis methods such as data mining. Especially if we have event log data that has execution history data of an organization such as case_id, event_time, event (activity), performer, etc., then we can apply process mining to discover the main process model in the organization. Once we can find the main process from process mining, we can utilize it to improve current working environment. In this paper we developed a new method to find a final diagnosis of a patient, who needs several procedures (medical test and examination) to diagnose disease of the patient by using process mining approach. Some patients can be diagnosed by only one procedure, but there are certainly some patients who are very difficult to diagnose and need to take several procedures to find exact disease name. We used 2 million procedure log data and there are 397 thousands patients who took 2 and more procedures to find a final disease. These multi-procedure patients are not frequent case, but it is very critical to prevent wrong diagnosis. From those multi-procedure taken patients, 4 procedures were discovered to be a main process model in the hospital. Using this main process model, we can understand the sequence of procedures in the hospital and furthermore the relationship between diagnosis and corresponding procedures.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.17 no.1
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• pp.45-54
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• 2010

Purpose: The purpose of this study was to develop and test an explanatory model of dyspnea in patients with chronic lung disease (CLD). Methods: Participants were 181 patients with CLD, recruited from the outpatient pulmonary clinic of one university hospital in Korea. Data were collected using questionnaires, as well as measurement of 6-minute walking distance (6MWD), oxygen saturation ($SpO_2$), FEV1% predicted, and Body Mass Index (BMI). Results: The results indicated a good fit between the proposed dyspnea model and the collected data [$x^2$=91.27, p= .13, $x^2$/d.f.=1.17, Normal Fit Index= .934]. Oxygenation ($SpO_2$, = -.530), self-efficacy (= -.429), anxiety (= .253), depression (= .224), exercise endurance (6MWD, = -.211), and pulmonary function (FEV1% predicted, = -.178) had a direct effect on dyspnea (all p< .05) and these variables explained 74% of variance in dyspnea. BMI, smoking history, and social support had an indirect effect on dyspnea. Conclusion: The findings of this study suggest that comprehensive nursing interventions should focus on recovery of respiratory health and improvement of emotions, exercise ability, and nutritional status. From this perspective, pulmonary rehabilitation would be an effective strategy for managing dyspnea in patients with CLD.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.529-546
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• 2011

A deterministic tuberculosis model for theoretically assessing the potential impact of the combined effects of case detection in the presence of treatment is formulated. The qualitative features of its equilibria are analyzed and it is found that the disease-free equilibrium may not be globally asymptotically stable when the reproduction number is less than unity. This disease threshold number is further used to assess the impact of active TB case finding alone and in conjunction with treatment. A critical threshold parameter ${\Theta}$ say for which case detection will have a positive impact is derived. Using the Centre Manifold theory, the model may exhibit the phenomenon of backward bifurcation (coexistence of a locally stable endemic equilibrium with a stable disease-free equilibrium) when the reproduction number is less than unity. It is shown that the possibility of backward bifurcation occurring decreases with increase case detection. Graphical representations suggest that increase in case finding accompanied by treatment of detected TB cases, result in a marked decrease of TB cases (both latent and active TB).

• Korean Journal of Veterinary Research
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• v.60 no.1
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• pp.15-18
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• 2020

Canine heartworm disease is a vector-borne disease that is transmitted from dog to dog by mosquitoes. It causes epidemics that disrupt the health environments of dogs and are burdensome for many dog owners. Recent trends of changing temperatures and weather conditions in South Korea may have an impact on the population of mosquitoes, and it affects the population of dogs at risk of heartworm infection. Mathematical modeling has become an important measure for analyzing the epidemiological characteristics of infectious diseases. However, canine heartworm infection transmission has not been reported yet through mathematical modeling. We develop a mathematical model of canine heartworm infection to predict the population of infected dogs depending on the vector (mosquito) population using a susceptible, exposed, infected, and recovered model. Simulation results show that after 1 year, 3,289 dogs out of 73,602 (about 4.5%) are exposed and 134 (about 0.2%) are infected. Only 0.2% of susceptible dogs become infected after 1 year. However, if all exposed dogs are maintained in the same circumstances without any treatment, then the number of infected subjects will increase over time. This may increase the possibility of other dogs, especially dogs that live outside, being infected.

• The Journal of Korean Medicine
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• v.39 no.4
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• pp.126-135
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• 2018

Objectives: Chronic obstructive pulmonary disease (COPD) is characterized by chronic inflammation and irreversible airflow. This study aimed to evaluate the effects of GHX02 in a COPD-induced mouse model. Methods: The COPD mouse model was established by exposure to cigarette smoke extract and lipopolysaccharide which were administered by intratracheal injection three times with a 7 day interval. GHX02 (100, 200, 400 mg/kg) and all other drugs were orally administrated for 14 days from Day 7 to Day 21. Results: GHX02 significantly decreased the neutrophil counts in bronchoalveolar lavage fluid (BALF) and the number of $CD4^+$, $CD8^+$, $CD69^+$, and $CD11b^+/GR1^+$ cells in BALF and lung cells. GHX02 also suppressed the secretion of tumor necrosis factor-alpha ($TNF-{\alpha}$), interleukin-17A, macrophage inflammatory protein 2 (MIP2), and chemokine (C-X-C motif) ligand 1 (CXCL-1) in BALF and ameliorated the lung pathological changes. Conclusions: Thus, GHX02 effectively inhibited airway inflammation by inhibiting migration of inflammatory cells and expression of pro-inflammatory cytokines. Therefore, GHX02 may be a promising therapeutic agent for COPD.

• Korean Journal of Organic Agriculture
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• v.29 no.4
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• pp.507-521
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• 2021

The livestock farmers are producing under uncertainties such as Foot-and-Mouth Disease (FMD) and Free Trade Agreement (FTA). The purpose of this study is to strengthen the management capabilities of Hanwoo farmers to prepare them for the uncertainties just mentioned. To this end, this study was conducted to find the optimal rearing period in order to reduce the feed cost, which accounts for the largest portion of the operation cost of Hanwoo. Using the universal lattice model, 41,139 of 289,000 Hanwoo slaughter data from 2010 to 2019 were used for the FMD period and 246,605 heads for the general period. The results show that the maximum cutoff price of Hanwoo steer is 6,394,457 won at the 4th week of 27 months of age in general period, where as 6,242,752 won at the 2nd week of 26 months of age in the FMD period. Therefore, it is judged that it will be helpful for Hanwoo farms to maximize their business profits by slaughtering one month and two weeks earlier in the FMD period than in the general period. In addition, Hanwoo farmers need to break away from the conventional rearing method and improve their management efficiency through a more flexible rearing method.

• The Journal of Bigdata
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• v.6 no.2
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• pp.161-168
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• 2021

In this study, we propose a cardiovascular disease prediction model using machine learning. First, a multidimensional analysis of various differences between the two groups is performed and the results are visualized. In particular, we propose a predictive model using cost-sensitive learning that can improve the sensitivity for cases where there is a high class imbalance between the normal and patient groups, such as diseases. In this study, a predictive model is developed using CART and XGBoost, which are representative machine learning technologies, and prediction and performance are compared for cardiovascular disease patient data. According to the study results, CART showed higher accuracy and specificity than XGBoost, and the accuracy was about 70% to 74%.

• Journal of Environmental Science International
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• v.32 no.10
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• pp.723-729
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• 2023

Parkinson's disease (PD) is the second most common neurodegenerative disorder, characterized by dopaminergic neuronal loss in the substantia nigra, resulting in reduced dopamine levels and consequent motor dysfunction. Genetic and environmental factors contribute to oxidative stress in PD. Cicadidae Periostracum (CP), a traditional Korean medicine, has shown neuroprotective effects against MPTP-induced neurotoxicity in PD. However, its effects on the 6-hydroxydopamine (6-OHDA) model have not been established. This study examined CP's effects on a 6-OHDA-induced PD model. CP protected against 6-OHDA damage in both in vitro and in vivo studies. Furthermore, CP reduced the production of reactive oxygen species, inhibited apoptosis, preserved dopamine levels, protected tyrosine hydroxylase in the substantia nigra, and improved motor function. These findings suggest that CP may delay PD progression by maintaining the redox balance.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4327-4330
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• 2012

The mouse double minute 2 (MDM2) gene plays a key role in the p53 pathway, and the SNP 309T/G single-nucleotide polymorphism in the promoter region of MDM2 has been shown to be associated with increased risk of cancer. However, no consistent results were found concerning the relationships between the polymorphism and prostate cancer risk. This meta-analysis, covering 4 independent case-control studies, was conducted to better understand the association between MDM2-SNP T309G and prostate cancer risk focusing on overall and subgroup aspects. The analysis revealed, no matter what kind of genetic model was used, no significant association between MDM2-SNP T309G and prostate cancer risk in overall analysis (GT/TT: OR = 0.84, 95%CI = 0.60-1.19; GG/TT: OR = 0.69, 95%CI = 0.43-1.11; dominant model: OR = 0.81, 95%CI= 0.58-1.13; recessive model: OR = 1.23, 95%CI = 0.95-1.59). In subgroup analysis, the polymorphism seemed more likely to be a protective factor in Europeans (GG/TT: OR = 0.52, 95%CI = 0.31-0.87; recessive model: OR = 0.58, 95%CI = 0.36-0.95) than in Asian populations, and a protective effect of the polymorphism was also seen in hospital-based studies in all models (GT/TT: OR = 0.74, 95%CI = 0.57-0.97; GG/TT: OR = 0.55, 95%CI = 0.38-0.79; dominant model: OR = 0.69, 95%CI = 0.54-0.89; recessive model: OR = 0.70, 95%CI = 0.51-0.97). However, more primary studies with a larger number of samples are required to confirm our findings.

• The Plant Pathology Journal
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• v.35 no.6
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• pp.585-597
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• 2019

A disease forecast model for Marssonina blotch of apple was developed based on field observations on airborne spore catches, weather conditions, and disease incidence in 2013 and 2015. The model consisted of the airborne spore model (ASM) and the daily infection rate model (IRM). It was found that more than 80% of airborne spore catches for the experiment period was made during the spore liberation period (SLP), which is the period of days of a rain event plus the following 2 days. Of 13 rain-related weather variables, number of rainy days with rainfall ≥ 0.5 mm per day (L_day), maximum hourly rainfall (P_max) and average daily maximum wind speed (W_avg) during a rain event were most appropriate in describing variations in airborne spore catches during SLP (S_i) in 2013. The ASM, Ŝ_i = 30.280+5.860×L_day×P_max-2.123×L_day×P_max×W_avg was statistically significant and capable of predicting the amount of airborne spore catches during SLP in 2015. Assuming that airborne conidia liberated during SLP cause leaf infections resulting in symptom appearance after 21 days of incubation period, there was highly significant correlation between the estimated amount of airborne spore catches (Ŝ_i) and the daily infection rate (R_i). The IRM, ${\hat{R}}_i$ = 0.039+0.041×Ŝ_i, was statistically significant but was not able to predict the daily infection rate in 2015. No weather variables showed statistical significance in explaining variations of the daily infection rate in 2013.