• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3672-3681
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• 2022

This study investigates the environmental footprint impacts of nuclear energy consumption in the presence of environmental technology and globalization of the ten largest ecological footprint countries from 1990 up to 2017. By considering a set of methods that can help solve the issue of cross-sectional dependence, we employ the Lagrange multiplier bootstrap cointegration method, Driscoll-Kraay standard errors for long-run estimation and feasible generalized least squares (FGLS) and panel-corrected standard errors (PCSE) for robustness. The finding revealed significant negative effects of nuclear energy consumption, environmental-related technology, population density and significant positive effects of globalization and economic growth on ecological footprint. These results are also robust by assessing the long-run impacts of predictors on carbon footprint and CO₂ emissions as alternate ecological measures. These conclusions provide the profound significance of nuclear energy consumption for environmentally sustainable development in the top ten ecological footprint countries and serve as an important reference for ecological security for other countries globally.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.407-419
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• 2006

In this paper, we analyze household overdue loans in Korea which has been causing serious social and economical problems. We consider customers of Bank A in Korea and focus on overdue cash services which have been snowballing in the past few years. From analysis of overdue loans, one can predict possible delays for current customers as well as build a credit evaluation and risk management system for future customers. As a statistical analytical tool, we propose a two-stage Generalized Linear regression Model (GLM) which assumes a logistic model for presence/non-presence of overdue and a gamma model for the amount of overdue in the case of overdue. We perform goodness of fit test for the two-stage model and select significant explanatory variables in each stage of the model. It turns out that age, the amount of credit loans from other financial companies, the amount of cash service from other companies, debit balance, the average amount of cash service, and net profit are important explanatory variables relevant to overdue credit card cash service in Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.43-46
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• 2015

Recently, full-duplex communications has been considered as one of the most promising techniques for net-generation mobile communication system. In this paper, we propose a compressed sensing based signal detection technique for full-duplex generalized spatial modulation (FD-GSM) systems. In FD-GSM systems, some antennas are used for signal transmission according to input data and the otehrs are used for detecting signals received over the same frequency band. The self-interference (SI) is assumed to be completely removed by help for the recently proposed SI cancellation techniques. The proposed signal detection technique significantly outperforms the conventional ones in terms of symbol error rate (SER). We will investigate the optimal number of used antennas in FD-GSM systems.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.131-142
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• 2017

The number of hospital admissions for pneumonia tends to increase annually and even more, pneumonia, the fifth leading causes of death among elder adults, is one of top diseases in terms of hospitalization rate. Although mainly bacteria and viruses cause pneumonia, the weather is also related to the occurrence of pneumonia. The candidate weather variables are humidity, amount of sunshine, diurnal temperature range, daily mean temperatures and density of particles. Due to the delayed occurrence of pneumonia, lagged weather variables are also considered. Additionally, year effects, holiday effects and seasonal effects are considered. We select the related variables that influence the occurrence of pneumonia using penalized generalized linear models.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.349-360
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• 2020

The study aims to empirically examine the determinants of bank margins from Pakistan, an emerging South Asian economy. To elucidate the importance of the Pakistani banking sector, secondary data has been used, which was extracted from the annual accounts of twenty-four Pakistani scheduled commercial banks (20 conventional, four full-fledged Islamic) over a sample period of 2006 to 2017. The factors identified in the dealership model and the subsequent empirical developments in the dealership model categorized as bank-specific, diversification, regulatory, and industry concentration are analyzed by applying the most-common linear dynamic panel-data estimator, the Generalized Method of Moments (GMM) estimator, developed by Arellano and Bond (1991). The findings reveal that, among the bank-specific variables, funding cost, credit risk, managerial efficiency, market share, and operating cost are significant predictors of bank margins. For diversification variables employed in the study, both variables including net non-interest income and asset diversity are as well significant predictors of bank margins. It is also found that the market concentration variable proxied by the Herfindahl-Hirschman Index (HHI) is significantly predicting bank margins. Subsequently, one of the regulatory variables, the opportunity cost of holding reserves, and one bank-specific variable, the degree of risk aversion, are insignificant in the model.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.592-602
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• 2021

Thorium compounds have attracted immense scientific and technological attention with regard to both fundamental and practical implications, owing to unique chemical and physical properties like high melting point, high density and thermal conductivity. Hereby, we investigate the mechanical and thermodynamic stability and report on the structural, electronic and magnetic properties of new silicon-doped cubic ternary thorium phosphides ThSi_xP_1-x (x = 0, 0.25, 0.5, 0.75 and 1). The first-principles density functional theory procedure was adopted within full-potential linearized augmented plane wave (FP-LAPW) method. The exchange and correlation potential terms were treated within Generalized-Gradient-Approximation functional modified by Perdew-Burke-Ernzerrhof parameterizations. The proposed compounds showed mechanical and thermodynamic stable structure and hence can be synthesized experimentally. The calculated lattice parameters, bulk modulus, total energy, density of states, electronic band structure and spin magnetic moments of the compounds revealed considerable correlation to the Si substitution for P and the relative Si/P doping concentration. The electronic and magnetic properties of the doped compounds rendered them non-magnetic but metallic in nature. The main orbital contribution to the Fermi level arises from the hybridization of Th(6d+5f) and (Si+P)3p states. Reported results may have potential implications with regard to both fundamental point of view and technological prospects such as fuel materials for clean nuclear energy.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.49 no.5
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• pp.635-641
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• 2016

The feeding habits of juvenile and young Seriola quinqueradiata, which were collected by a hand net and set net in coastal waters of the South Sea during the period from June to August 2014 and 2015, were analyzed. The size range of juveniles was 4.9-10.9 cm FL, and that of young S. quinqueradiata was 11.0-20.4 cm FL. Important prey items in the diets of juveniles were euphausiacea and copepoda, dominated by the Euphausia sp., Paracalanus sp. and Calanus sinicus while the diets of the young consisted mainly of pisces, dominated by Engraulis japonicus, Trachurus japonicus. Stomach content compositions differed significantly among body size levels in both the juveniles and young (ANOSIM, P<0.05). With increasing size, the mN/ST constantly decreased while the mW/ST constantly increased (one-way ANOVA). Graphical analysis of the diet composition showed that juvenile S. quinqueradiata are generalized feeders, young is a specialized feeders characterized by strong individual feeding specialization.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.217-230
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• 2014

The purpose of this study is to develop the Generalized Depreciation Function (GDF) and Winfrey Depreciation Function (WDF) by reviewing methods for the depreciation accountings. The Depreciation Accounting Models (DAM), including straight-line model, declining-balance model, sum-of-the-year-digit model and sinking fund model presented in this paper, are reclassified into the charging pattern of increasing type, decreasing type and constant type. This paper also discusses the development of the GDFs based on convex type, concave type and constant type according to the demand pattern of product, frequency of plant usage, deterioration of time, relative inadequacy, Capital Expenditure (CAPEX) and Operating Expenditure (OPEX) of the Total Productive Maintenance (TPM). The WDFs presented in this paper depict a sudden degradation of plant performance by measuring the change of TPM activity at the midpoint of useful life of asset. The WDFs are classified into left-modal type, symmetrical type and right-modal type by varying the value of skewness and kurtosis. Moreover, three increasing patterns, such as convex, concave and linear types, are used in this paper to present the distinct identification of WFDs by using Instantaneous Depreciation Rate (IDR) in terms of Performance Depreciation Function (PDF) and Depreciation Density Function (DDF). In order to have better understanding of depreciation models, the numerical examples are used for evaluating the Net Operating Less Adjusted Tax (NOPLAT) and Economic Value Added (EVA). It is concluded that the depreciation models showing a large dispersion of EVA require the adjustment of NOPLAT and Invested Capital (IC) based on the objective cash basis and net operating activity for reducing the variation of EVA.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.3
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• pp.193-198
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• 2022

In this study, for the purpose of reducing the catch of small giant octopus in a net pot, an escape experiment of octopus was performed on five types of escape rings of different sizes. As a result of the experiment, the smallest giant octopus with a weight of 406 g was found to escape from an escape ring with a diameter of 30 mm or larger, and 592 g octopus, a weight similar to the octopus of the current minimum landing weight (600 g), escaped from an escape ring with a diameter of larger than 40 mm. An individual weight with 406 g becomes 39 mm when converted from a diameter of 25 mm circular escape vent; that is, the circumference to the inner diameter of the mesh. It can be inferred that the converted mesh size of 39 mm cannot escape. Logistic regression analysis was performed using a generalized linear model (GLM) to investigate the correlation between the ratio of escape ring size/Mantle diameter (R/MD) and the escape rate. As a result, it was found that there was a significant correlation between the R/MD ratio and the escape rate and that the higher the R/MD ratio, the greater the escape rate. As a result of logistic regression analysis, the R/MD value was denoted 0.520 with the 50% escape rate. In addition, it can be estimated to be about 50 mm when converted to the mesh size. Therefore, in this study, the diameter of the escape ring and the size of the escape possible of the octopus were experimentally considered. It was found that there was a significant correlation.