• Journal of Korean Society on Water Environment
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• v.37 no.3
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• pp.217-228
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• 2021

This paper discusses a methodology where an integrated modelling framework is used to quantify the risk derived from anthropic activities on habitats and species. To achieve this purpose, a tool comprising the Delft3D and HABITAT model, was applied in the Yeongsan river. Delft3D effectively simulated the operational condition and flow of weirs in river. In accuracy evaluation of the Delft3D-FLOW, the Bias, Pbias, Mean Absolute Error (MAE), Nash-Sutcliffe Efficiency (NSE), and Index of Agreement (IOA) were used, and the result was evaluated as grade above 'Satisfactory'. The HABITAT calculated Habitat Suitability Value (HSV) for the following eight species: mammal, fish, aquatic plant, and benthic macroinvertebrate. An Area was defined as a suitable habitat if the HSV was larger than 0.5. HABITAT was judged accurately by measuring the Correct Classification rate (CCR) and the area under the ROC curve (AUC). For benthic macroinvertebrate, the CCR and AUC were 77% and 0.834, respectively, at thresholds of 0.017 and 4 inds/m² for HSV and individuals per unit area. This meant that the HABITAT model accurately predicted the appearance of the benthic macroinvertebrates by approximately 77% and that the probability of false alarms was also very low. As a result of evaluating the suitability of habitats, in the Yeongsan river, if the annual "lowest level" (Seungchon weir: 2.5 EL.m/ Juksan weir: -1.35 EL.m) was maintained, the average habitat improvement effect of 6.5%P compared to the 'reference' scenario was predicted. Consequently, it was demonstrated that the integrated modelling framework for habitat suitability assessment is able to support the remedy aquatic ecological management.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.19-26
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• 2023

The increase in the dropout rate of college students nationwide has a serious negative impact on universities and society as well as individual students. In order to proactive identify students at risk of dropout, this study built a decision tree, random forest, logistic regression, and deep learning-based dropout prediction model using academic data that can be easily obtained from each university's academic management system. Their performances were subsequently analyzed and compared. The analysis revealed that while the logistic regression-based prediction model exhibited the highest recall rate, its f-1 value and ROC-AUC (Receiver Operating Characteristic - Area Under the Curve) value were comparatively lower. On the other hand, the random forest-based prediction model demonstrated superior performance across all other metrics except recall value. In addition, in order to assess model performance over distinct prediction periods, we divided these periods into short-term (within one semester), medium-term (within two semesters), and long-term (within three semesters). The results underscored that the long-term prediction yielded the highest predictive efficacy. Through this study, each university is expected to be able to identify students who are expected to be dropped out early, reduce the dropout rate through intensive management, and further contribute to the stabilization of university finances.

• Sleep Medicine and Psychophysiology
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• v.30 no.1
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• pp.22-27
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• 2023

Objectives: The purpose of this study was to develop a screening tool that is simple and easy to use for assessing sleep problems, including hypersomnolence, restless legs syndrome, and insomnia. We also examined the reliability and validity of this tool. Methods: We developed the Sleep Problem Screening Questionnaire (SPSQ), which consists of three sub-sections: insomnia (SPSQi), hypersomnolence (SPSQh), and restless legs syndrome (SPSQr). Subsequently, the participants, consisting of 222 patients with insomnia disorder and 78 healthy individuals, completed both the SPSQ and the comparative scale (Korean version of the Insomnia Severity Index). The analysis was then conducted using this data. Results: The SPSQ demonstrated good convergent and discriminant validity, as well as satisfactory internal consistency. A cutoff score of 6 on the SPSQi was found to be optimal for distinguishing individuals with insomnia. Conclusion: The results of this study suggest that the SPSQ is a reliable and valid tool for screening sleep problems among general adult population. However, there is a limitation as a comparison and validation with scales related to restless legs syndrome and hypersomnolence were not conducted.

• Tuberculosis and Respiratory Diseases
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• v.56 no.6
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• pp.600-610
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• 2004

Background : The plasma B-type natriuretic peptide(BNP) concentration increases with the degree of pulmonary hypertension in patients with chronic respiratory disease. The aim of this study was to examine the prognostic role of BNP in the acute exacerbation of chronic obstructive lung disease (COPD). Method : We selected 67 patients who were admitted our hospital because of an acute exacerbation of COPD. Their BNP levels were checked on admission at the Emergency Department. Their medical records were analyzed retrospectively. The patients were divided into two groups according to their in-hospital mortality. The patients' medical history, comobidity, exacerbation type, blood gas analysis, pulmonary function, APACHE II severity score and plasma BNP level were compared. Results : Multiple logistic regression analysis identified three independent predictors of mortality: $FEV_1$, APACHE II score and plasma BNP level. The decedents group showed a lower $FEV_1$($28{\pm}7$ vs. $37{\pm}15%$, p=0.005), a higher APACHE II score($22.4{\pm}6.1$ vs. $15.8{\pm}4.7$, p=0.000) and a higher BNP level ($201{\pm}116$ vs. $77{\pm}80pg/mL$, p=0.000) than the sSurvivors group. When the BNP cut-off level was set to 88pg/mL using the receiver operating characteristic curve, the sensitivity was 90% and the specificity was 75% in differentiating between the survivors and decedents. On Fisher's exact test, the odds ratio for mortality was 21.2 (95% CI 2.49 to 180.4) in the patients with a BNP level > 88pg/mL. Conclusion : The plasma BNP level might be a predictor of mortality in an acute exacerbation of COPD as well as the $FEV_1$ and APACHE II score.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.4
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• pp.285-291
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• 2008

Purpose: Although automatic quantification software of myocardial perfusion SPECT provides highly objective and reproducible quantitative measurements, there is still some limitation in the direct use of quantitative measurements. In this study we derived parameters using normal variation of perfusion measurements, and tried to test the usefulness of these parameters. Materials and Methods: In order to calculate normal variation of perfusion measurements on myocardial perfusion SPECT, 55 patients (M:F = 28:27) of low-likelihood for coronary artery disease were enrolled and $^{201}TI$ rest/$^{99m}Tc$-MIBI stress SPECT studies were performed. Using 20-segment model, mean (m) and standard deviation (SD) of perfusion were calculated in each segment. As a myocardial viability assessment group, another 48 patients with known coronary artery disease, who underwent coronary artery bypass graft surgery (CABG) were enrolled. $^{201}TI$ rest/$^{99m}Tc$-MIBI stress / $^{201}TI$ 24-hr delayed SPECT was performed before CABG and SPECT was followed up 3 months after CABG. From the preoperative 24-hr delayed SPECT, $Q_{delay}$ (perfusion measurement), ${\Delta}_{delay}$ ($Q_{delay}$ - m) and $Z_{delay}$ (($Q_{delay}$ - m)/SD) were defined and diagnostic performances of them for myocardial viability were evaluated using area under curve (AUC) on receiver operating characteristic (ROC) curve analysis. Results: Segmental perfusion measurements showed considerable normal variations among segments. In men, the lowest segmental perfusion measurement was $51.8{\pm}6.5$ and the highest segmental perfusion was $87.0{\pm}5.9$, and they are $58.7{\pm}8.1$ and $87.3{\pm}6.0$, respectively in women. In the viability assessment $Q_{delay}$ showed AUC of 0.633, while those for ${\Delta}_{delay}$ and $Z_{delay}$ were 0.735 and 0.716, respectively. The AUCs of ${\Delta}_{delay}$ and $Z_{delay}$ were significantly higher than that of $Q_{delay}$ (p = 0.001 and 0.018, respectively). The diagnostic performance of ${\Delta}_{delay}$, which showed highest AUC, was 85% of sensitivity and 53% of specificity at the optimal cutoff of -24.7. Conclusion: On automatic quantification of myocardial perfusion SPECT, the normal variation of perfusion measurements were considerable among segments. In the viability assessment, the parameters considering normal variation showed better diagnostic performance than the direct perfusion measurement. This study suggests that consideration of normal variation is important in the analysis of measurements on quantitative myocardial perfusion SPECT.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Tuberculosis and Respiratory Diseases
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• v.44 no.4
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• pp.785-795
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• 1997

Background : Tumor markers have been used in diagnosis, predicting the extent of disease, monitoring recurrence after therapy and prediction of prognosis. But the utility of markers in lung cancer has been limited by low sensitivity and specificity. TPA-M is recently developed marker using combined monoclonal antibody of Cytokeratin 8, 18, and 19. This study was conducted to evaluate the efficacy of new tumor marker, TPA-M by comparing the estabilished markers SCC, CEA, Cyfra21-1 in lung cancer. Method : An immunoradiometric assay of serum CEA, sec, Cyfra21-1, and TPA-M was performed in 49 pathologically confirmed lung cancer patients who visited Keimyung University Hospital from April 1996 to August 1996, and 29 benign lung diseases. Commercially available kits, Ab bead CEA (Eiken) to CEA, SCC RIA BEAD (DAINABOT) to SCC, CA2H (TFB) to Cyfra2H. and TPA-M (DAIICHI) to TPA-M were used for this study. Results : The mean serum values of lung cancer group and control group were $10.05{\pm}38.39{\mu}/L$, $1.59{\pm}0.94{\mu}/L$ in CEA, $3.04{\pm}5.79{\mu}/L$, $1.58{\pm}2.85{\mu}/L$ in SCC, $8.27{\pm}11.96{\mu}/L$, $1.77{\pm}2.72{\mu}/L$ in Cyfra21-1, and $132.02{\pm}209.35\;U/L$, $45.86{\pm}75.86\;U/L$ in TPA-M respectively. Serum values of Cyfra21-1 and TPA-M in lung cancer group were higher than control group (p<0.05). Using cutoff value recommended by the manufactures, that is $2.5{\mu}/L$ in CEA, $3.0{\mu}/L$ in Cyfra21-1, 70.0 U/L in TPA-M, and $2.0{\mu}/L$ in SCC, sensitivity and specificity of lung cancer were 33.3%, 78.6% in CEA, 50.0%, 89.7% in Cyfra21-1, 52.3%, 89.7% in TPA-M, 23.8%, 89.3% in SCC. Sensitivity and specificity of nonsmall cell lung cancer were 36.1%, 78.1% in CEA, 50.1%, 89.7% in Cyfra21-1, 53.1%, 89.7% in TPA-M, 33.8%, 89.3% in SCC. Sensitivity and specificity of small cell lung cancer were 25.0%, 78.5% in CEA, 50.0%, 89.6% in Cyfra21-1, 50.0%, 89.6% in TPA-M, 0%, 89.2% in SCC. Cutoff value according to ROC(Receiver operating characteristics) curve was $1.25{\mu}/L$ in CEA, $1.5{\mu}/L$ in Cyfra2-1, 35 U/L in TPA-M, $0.6{\mu}/L$ in SCC. With this cutoff value, sensitivity, specificity, accuracy and kappa index of Cyfra21-1 and TPA-M were better than CEA and SCC. SCC only was related with statistic significance to TNM stages, dividing to operable stages(TNM stage I to IIIA) and inoperable stages (IIIB and IV) (p<0.05). But no tumor markers showed any correlation with significance with tumor size(p>0.05). Conclusion : Serum TPA-M and Cyfra21-1 shows higher sensitivity and specificity than CEA and SCC in overall lung cancer and nonsmall cell lung cancer those were confirmed pathologically. SCC has higher specificity in nonsmall cell lung cancer. And the level of serum sec are signiticantly related with TNM staging.

• Tuberculosis and Respiratory Diseases
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• v.60 no.5
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• pp.540-547
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• 2006

Background : Vital stability and right side heart failure are major prognostic factors of acute pulmonary thromboembolism. While it is important to recognize right side heart failure, it is often difficult in real practice. Recently, several studies have described early diagnostic tools for detecting right side heart failure including echocardiography and biochemical markers. This study, we evaluated the prognostic role of the B-type natriuretic peptide (BNP) in an acute pulmonary thromboembolism. Methods : Thirty-four patients with a diagnosis of acute pulmonary thromboembolism were enrolled in the study. The BNP levels were measured and echocardiography was performed at the Emergency Department. Data on the prognostic factors including ventilatory support, vital stability, pulmonary artery pressure, degree of tricuspid valve regurgitation, complications and death was collected from the patients' medical records. The patients with an acute pulmonary thromboembolism were divided into two groups based on the vital stability and the BNP level and the cutoff values and prognostic factors of the two groups were compared. Results : The predictors of the vital stability that influence the prognosis of patients with acute pulmonary thromboembolism were the BNP level, ventilatory support and death. The plasma BNP levels showed a strong correlation with the vital stability, ventilatory support, thrombolytic therapy and death. When the BNP cutoff level was set to 377.5 pg/dl in a ROC curve, the sensitivity and the specificity for differentiating between the groups with stable or unstable vital signs was 100% and 90%, respectively. Conclusion : This study indicates that a measurement of the plasma BNP levels may be a useful prognostic marker in patients with an acute pulmonary thrombo-embolism.

• Tuberculosis and Respiratory Diseases
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• v.42 no.3
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• pp.322-331
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• 1995

Introduction: This study was performed to evaluate the diagnostic usefulness of simultaneous determination of 3 tumor markers {serum carcinoembryonic antigen(CEA), squamous cell carcinoma antigen (SCC Ag) and neuron specific enolase(NSE)} in lung cancer patients. Method: In 113 patients with primary lung cancer(70 with squamous cell carcinoma, 30 with adenocarcinoma, 13 with small cell carcinoma) and 103 patients with benign lung diseases, serum CEA and NSE were measured by enzyme immunoassay, and SCC Ag was measured by microparticle enzyme immunoassay. Results: 1) The mean serum levels of 3 tumor markers were significantly higher in lung cancer groups than benign lung disease groups respectively(p=0.001). 2) In squamous cell carcinoma, the SCC Ag was elevated in 67%, in adenocarcinoma CEA was elevated in 77% and in small cell carcinoma NSE was elevated in 77%, but there were no significant differences according to the stage of each cancer cell types. 3) CEA was the most sensitive marker, but nonspecific to cancer types. SCC Ag was less sensitive than other markers, but more specific toward squamous cell carcinoma, and NSE was more specific to primary lung cancer. 4) As the number of positive tumor markers was increased, the relative possibility of lung cancer was also increased. If two markers were positive, it increased to 77%, and if three markers were positive it increased to 90%. Conclusion: The simultaneous measurement of serum CEA, SCC Ag and NSE would provide additional information for the diagnosis of lung cancer.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.6
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• pp.456-463
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• 2008

Purpose: We evaluated the incidence and malignant risk of focal breast lesions incidentally detected by $^{18}F-FDG$ PET/CT. Various PET/CT findings of the breast lesions were also analyzed to improve the differentiation between benign from malignant focal breast lesions. Materials & Methods: The subjects were 3,768 consecutive $^{18}F-FDG$ PET/CT exams performed in adult females without a history of breast cancer. A focal breast lesion was defined as a focal $^{18}F-FDG$ uptake or a focal nodular lesion on CT image irrespective of $^{18}F-FDG$ uptake in the breasts. The maximum SUV and CT pattern of focal breast lesions were evaluated, and were compared with final diagnosis. Results: The incidence of focal breast lesions on PET/CT in adult female subjects was 1.4% (58 lesions in 53 subjects). In finally confirmed 53 lesions of 48 subjects, 11 lesions of 8 subjects (20.8%) were proven to be malignant. When the PET/CT patterns suggesting benignancy (maximum attenuation value>75 HU or <30HU; standard deviation of mean attenuation > 20) were added as diagnostic criteria of PET/CT to differentiate benign from malignant breast lesions along with maximum SUV, the area under ROC curve of PET/CT was significantly increased compared with maximum SUV alone ($0.680{\pm}0.093$ vs. $0.786{\pm}0.076$, p<0.05). Conclusion: The malignant risk of focal breast lesions incidentally found on $^{18}F-FDG$ PET/CT is not low, deserving further diagnostic confirmation. Image interpretation considering both $^{18}F-FDG$ uptake and PET/CT pattern may be helpful to improve the differentiation from malignant and benign focal breast lesion.