• Animal Bioscience
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• v.37 no.3
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• pp.500-508
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• 2024

Objective: Due to current selection practices for increased egg production and peak persistency, the production profile, age at maturity, and body weight criteria for commercial layers are constantly changing. Body weight and age at the time of photostimulation will thus always be the factors that need to be adequately addressed among various production systems. The current study was carried out to determine the effects of pullets' body weight (low, medium, and heavy) on their performance, welfare, physiological response, and hormonal profile. Methods: With regard to live weight, 150 16-week-old pullets were divided into three groups using a completely randomized design (CRD) and held until the 50th week. One-way analysis of variance was used to evaluate the data under the CRD, and the least significant difference test was used to distinguish between treatment means. Results: In comparison to the medium and light birds, the heavy birds had higher body weight at maturity, an earlier age at maturity, and higher egg weight, eggshell weight, eggshell thickness, egg yolk index, breaking strength, egg surface area, egg shape index, egg volume, and hormonal profile except corticosterone. However, the medium and light birds had lower feed consumption rates per dozen eggs and per kilogram of egg mass than the heavy birds. Light birds showed greater body weight gain, egg production, and egg specific gravity than the other categories. At 20 weeks of age, physiological response, welfare aspects, and catalase were non-significant; however, at 50 weeks of age, all these factors-aside from catalase-were extremely significant. Conclusion: The findings of this study indicate that layers can function at lower body weights during photostimulation; hence, dietary regimens that result in lighter pullets may be preferable. Additionally, the welfare of the birds was not compromised by the lighter weight group.

• Korean Journal of Radiology
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• v.22 no.9
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• pp.1514-1524
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• 2021

Objective: To develop a radiomics risk score based on dynamic contrast-enhanced (DCE) MRI for prognosis prediction in patients with glioblastoma. Materials and Methods: One hundred and fifty patients (92 male [61.3%]; mean age ± standard deviation, 60.5 ± 13.5 years) with glioblastoma who underwent preoperative MRI were enrolled in the study. Six hundred and forty-two radiomic features were extracted from volume transfer constant (K^trans), fractional volume of vascular plasma space (V_p), and fractional volume of extravascular extracellular space (V_e) maps of DCE MRI, wherein the regions of interest were based on both T1-weighted contrast-enhancing areas and non-enhancing T2 hyperintense areas. Using feature selection algorithms, salient radiomic features were selected from the 642 features. Next, a radiomics risk score was developed using a weighted combination of the selected features in the discovery set (n = 105); the risk score was validated in the validation set (n = 45) by investigating the difference in prognosis between the "radiomics risk score" groups. Finally, multivariable Cox regression analysis for progression-free survival was performed using the radiomics risk score and clinical variables as covariates. Results: 16 radiomic features obtained from non-enhancing T2 hyperintense areas were selected among the 642 features identified. The radiomics risk score was used to stratify high- and low-risk groups in both the discovery and validation sets (both p < 0.001 by the log-rank test). The radiomics risk score and presence of isocitrate dehydrogenase (IDH) mutation showed independent associations with progression-free survival in opposite directions (hazard ratio, 3.56; p = 0.004 and hazard ratio, 0.34; p = 0.022, respectively). Conclusion: We developed and validated the "radiomics risk score" from the features of DCE MRI based on non-enhancing T2 hyperintense areas for risk stratification of patients with glioblastoma. It was associated with progression-free survival independently of IDH mutation status.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.213-224
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• 2021

Objective: Clinical outcomes of patients who undergo transarterial chemoembolization (TACE) for single small hepatocellular carcinoma (HCC) are not consistent, and may differ based on certain imaging findings. This retrospective study was aimed at determining the efficacy of pre-TACE CT or MR imaging findings in predicting survival outcomes in patients with small HCC upon being treated with TACE. Besides, the study proposed to build a risk prediction model for these patients. Materials and Methods: Altogether, 750 patients with functionally good hepatic reserve who received TACE as the first-line treatment for single small HCC between 2004 and 2014 were included in the study. These patients were randomly assigned into training (n = 525) and validation (n = 225) sets. Results: According to the results of a multivariable Cox analysis, three pre-TACE imaging findings (tumor margin, tumor location, enhancement pattern) and two clinical factors (age, serum albumin level) were selected and scored to create predictive models for overall, local tumor progression (LTP)-free, and progression-free survival in the training set. The median overall survival time in the validation set were 137.5 months, 76.1 months, and 44.0 months for low-, intermediate-, and high-risk groups, respectively (p < 0.001). Time-dependent receiver operating characteristic curves of the predictive models for overall, LTP-free, and progression-free survival applied to the validation cohort showed acceptable areas under the curve values (0.734, 0.802, and 0.775 for overall survival; 0.738, 0.789, and 0.791 for LTP-free survival; and 0.671, 0.733, and 0.694 for progression-free survival at 3, 5, and 10 years, respectively). Conclusion: Pre-TACE CT or MR imaging findings could predict survival outcomes in patients with small HCC upon treatment with TACE. Our predictive models including three imaging predictors could be helpful in prognostication, identification, and selection of suitable candidates for TACE in patients with single small HCC.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• The Korean Journal of Pesticide Science
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• v.17 no.4
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• pp.350-358
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• 2013

Both 13-week and 1-year studies in dog were required for pesticide registration in domestic pesticide control authority. It is raising issue up whether to request 1-year dog study of pesticides using non-food crop. So at this investigation, relevant toxicity test to establish acceptable daily intake (ADI), target organs, difference of no-observed adverse-effect levels (NOAELs) in 13-week and 1-year of 166 active ingredients are analyzed. The data were evaluated to determine if the 13-week dog study and the long term studies in two rodent species (mice and rats) without 1-year dog study were sufficient for the identification of NOAELs and lowest observed adverse effect levels (LOAELs) for the derivation of ADI. Toxicity end points and dose response data from 13 week and 1-year studies were compared. The analysis showed that 68 ADIs of the 166 pesticides were established from dog studies. Major target organs of dog studies were liver in 49 cases, body weight change in 21 cases, cholinesterase inhibition in 16 cases, and alteration in hematology in 14 cases. Similarity of target organ in 13-week and 1-year was 73%. 22 of 40 pesticides had similar critical effects regardless of duration and had NOAELs within a difference of 1.5-fold of each other. For the remaining 18 pesticides, 14 items had lower NOAELs in the 1-year study than 13-week study primarily due to dose selection and spacing. In only 10% of the cases were additional toxic effects identified in the 1-year study that were not observed in the 13-week study.

• Korean Journal of Environment and Ecology
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• v.30 no.3
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• pp.406-414
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• 2016

This study examined the factors by which people choose auto-camping as their primary leisure activity after conducting a questionnaire survey of the visitors to the Chiaksan national park Guryong auto-campground. The majority of the visitors were employed (60%) in their 30s and 40s (85%) with relatively high education (88% of which had bachelor's degree or higher) and income levels (87% of which had family income greater than KRW30 million). Most visitors were family group visitors (82%), and for many visitors, auto-camping appeared to be their primary leisure activity as 24% of the respondents said that they visited auto-campground more than 10 times a year. Only 18% of the visitors had auto-camped for longer than 5 years, indicating that auto-camping is a relatively new leisure activity that has become popular in recent times. Factor analysis with 19 items that measured the degree of agreement on the relative advantages of auto-camping extracted four latent factors that affected the selection of auto-camping as a leisure activity: factor 1 (refreshment through contact with nature), factor 2 (novelty and a sense of accomplishment), factor 3 (convenience), and factor 4 (entertainment). Results of regression analysis that examined the effects of the four extracted factors on the visitors' level of satisfaction on auto-camping (measured by the number of visits to auto-campgrounds per year) indicated that 'refreshment through contact with nature' was the most critical factor when deciding to select auto-camping as their leisure activity. 'Novelty and a sense of accomplishment' and 'convenience' were also statistically significant -but to a lesser degree, whereas 'entertainment' did not statistically significantly affect the visitors' decision. These results suggest that, for designing and managing auto-campgrounds, it is more important to preserve the surrounding nature than to provide more facilities for campers' convenience and entertainment.

• The Journal of Engineering Geology
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• v.26 no.1
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• pp.33-49
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• 2016

The study area, located in Sinam-ri, Ulsan, in the southeastern part of the Korean Peninsula, is mainly composed of hornblende granite (ca. 65 Ma). Fracturing and reactivation of a fault striking ENE-WSW was strongly controlled by the intrusion of a mafic dyke (ca. 44 Ma), which behaves as a discontinuity in the mechanically homogeneous pluton, increasing the instability of the basement in this area. A geometric and kinematic study undertaken to interpret the faults and fractures was performed in a trench excavated almost perpendicular to the orientation of the dyke. The analysis of structural elements, such as dykes, veins, and faults, is used to infer the deformation history and to determine the paleostress orientations at the time of formation of the structures. The deformation history established based on this analysis is as follows: (1) NNE-SSW, E-W, ENE-WSW, and NE-SW trending fractures had already developed in the pluton before dyke intrusion; (2) felsic dykes intruded under conditions of σ_Hmax oriented N-S and σ_Hmin oriented E-W; (3) mafic dykes intruded under conditions of σ_Hmax oriented E-W and σ_Hmin oriented N-S; (4) dextral reactivation of the main fault associated with the development of hydrothermal quartz veins under conditions of σ_Hmax oriented E-W and σ_Hmin oriented N-S; (5) sinistral reactivation of the main fault and high-angle normal faults under conditions of σ_Hmax oriented NE-SW and σ_Hmin oriented NW-SE; and (6) dextral reactivation of the main fault and NE-SW low-angle reverse faults under conditions of σ_Hmax oriented NW-SE and σ_Hmin oriented NE-SW. These results are consistent with the tectonic history of the Pohang-Ulsan block in the southeastern part of the Korean Peninsula, and indicates the tectonic deformation of the southern area of the Ulsan fault bounded by Yangsan fault was analogous to that of the Pohang-Ulsan area from the Cenozoic. This work greatly aids the selection of sites for critical facilities to prevent potential earthquake hazards in this area.

• Journal of Preventive Medicine and Public Health
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• v.31 no.4 s.63
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• pp.692-707
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• 1998

Aim. A neurobehavioral test for workers exposed to organic solvents in the workplace can be affected by many factors : age, education, motivation, ethnicity, etc. To apply more suitable neurobehavioral test for Korean workers, we evaluated the validity of several items of computerized and traditional neurobehavioral tests. Methods. We have applied eleven tests : four items of computerized neurobehavioral test(Swedish Performance Evaluation System) including Addition, Symbol-Digit, Dig-it Span, and Finger tapping speed, and seven items of traditional neurobehavioral test consisting of Addition, Digit-Symbol, Digit Span, Benton visual retention test, Pursuit aiming, Pegboard, and Tapping. These tests were performed on 96 workers exposed to solvents, and 100 reference workers. The concurrent and construct validities were evaluated by group difference, correlation with age, educational level, hippuric acid level, neurotoxic symptom, current exposure level, multitrait-multimethod matrix, fator analysis, and discriminant analysis. Results. Statistically significant differences were observed between the workers exposed to solvents and referents in computerized Symbol-Digit, Finger tapping speed, traditional Digit-Symbol and Pegboard. The computerized Symbol-Digit, traditional Digit-Symbol, Addition, Benton visual retention test, and Pegboard were found to be related to the age. The performance of computerized Symbol-Digit, Addition, and traditional Digit-Symbol were found to be related to the educational level significantly. The computerized Symbol-Digit, Finger tapping speed, and traditional Digit-Symbol were found to be related to hippuric acid, and neurotoxic symptom. The discriminability of Finger tapping speed, and Pegboard was better than the other tests. In discriminant analysis, the model with two variables, the computerized Symbol-Digit and Pegboard, classified almost 70 percent of the workers correctly. Conclusions. These results suggest that the computerized Symbol-Digit, Finger tapping speed, and Pegboard are more satisfactory for our purpose, and the Addition, Tapping, Benton visual retention test, and Pursuit aiming are less valid than other items. These may allow the reasonable selection of core neurobehavioral tests for workers exposed to solvents in Korea.

• Economic and Environmental Geology
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• v.51 no.2
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• pp.185-201
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• 2018

Nuclear power plants(NPP) are constructed and operated to ensure safety against natural disasters and man-made disasters in all processes including site selection, site survey, design, construction, and operation. This paper will introduce a series of efforts conducted in Korea Hydro and Nuclear Power Co. Ltd., to assure the safety of nuclear power plant against earthquakes and other natural hazards. In particular, the present status of the earthquake, fault, and slope safety monitoring system for nuclear power plants is introduced. A earthquake observatory network for the NPP sites has been built up for nuclear safety and providing adequate seismic design standards for NPP sites by monitoring seismicity in and around NPPs since 1999. The Eupcheon Fault Monitoring System, composed of a strainmeter, seismometer, creepmeter, Global Positioning System, and groundwater meter, was installed to assess the safety of the Wolsung Nuclear Power Plant against earthquakes by monitoring the short- and long-term behavioral characteristics of the Eupcheon fault. Through the analysis of measured data, it was verified that the Eupcheon fault is a relatively stable fault that is not affected by earthquakes occurring around the southeastern part of the Korean peninsula. In addition, it was confirmed that the fault monitoring system could be very useful for seismic safety analysis and earthquake prediction study on the fault. K-SLOPE System for systematic slope monitoring was successfully developed for monitoring of the slope at nuclear power plants. Several kinds of monitoring devices including an inclinometer, tiltmeter, tension-wire, and precipitation gauge were installed on the NPP slope. A macro deformation analysis using terrestrial LiDAR (Light Detection And Ranging) was performed for overall slope deformation evaluation.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.8
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• pp.449-455
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• 2017

Process input data including material and energy, process output data including product, co-product and its environmental emissions of the reference and target processes were collected and analyzed to evaluate the process performance. Environmentally problematic input/environmental emissions of the manufacturing processes were identified using these data. Significant process inputs contributing to each of the environmental emissions were identified using multiple regression analysis between the process inputs and environmental emissions. Optimum combination of the end-of-pipe technologies for treating the environmental emissions considering economic aspects was made using the linear programming technique. The cement manufacturing processes in Korea and the EU producing same type of cement were chosen for the case study. Environmentally problematic input/environmental emissions of the domestic cement manufacturing processes include coal, dust, and $SO_x$. Multiple regression analysis among the process inputs and environmental emissions revealed that $CO_2$ emission was influenced most by coal, followed by the input raw materials and gypsum. $SO_x$ emission was influenced by coal, and dust emission by gypsum followed by raw material. Optimization of the end-of-pipe technologies treating dust showed that a combination of 100% of the electro precipitator and 2.4% of the fiber filter gives the lowest cost. The $SO_x$ case showed that a combination of 100% of the dry addition process and 25.88% of the wet scrubber gives the lowest cost. Salient feature of this research is that it proposed a method for identifying environmentally problematic input/environmental emissions of the manufacturing processes, in particular, cement manufacturing process. Another feature is that it showed a method for selecting the optimum combination of the end-of-pipe treatment technologies.