• Journal of radiological science and technology
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• v.46 no.4
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• pp.277-285
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• 2023

In this study, pneumonia identification networks with the small number of layers were constructed by using chest X-ray images. The networks had similar trainable-parameters, and the performance of the trained models was quantitatively evaluated with the modification of the network architectures. A total of 6 networks were constructed: convolutional neural network (CNN), VGGNet, GoogleNet, residual network with identity blocks, ResNet with bottleneck blocks and ResNet with identity and bottleneck blocks. Trainable parameters for the 6 networks were set in a range of 273,921-294,817 by adjusting the output channels of convolution layers. The network training was implemented with binary cross entropy (BCE) loss function, sigmoid activation function, adaptive moment estimation (Adam) optimizer and 100 epochs. The performance of the trained models was evaluated in terms of training time, accuracy, precision, recall, specificity and F1-score. The results showed that the trained models with the small number of layers precisely detect pneumonia from chest X-ray images. In particular, the overall quantitative performance of the trained models based on the ResNets was above 0.9, and the performance levels were similar or superior to those based on the CNN, VGGNet and GoogleNet. Also, the residual blocks affected the performance of the trained models based on the ResNets. Therefore, in this study, we demonstrated that the object detection networks with the small number of layers are suitable for detecting pneumonia using chest X-ray images. And, the trained models based on the ResNets can be optimized by applying appropriate residual-blocks.

• Korean Journal of Environmental Biology
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• v.40 no.2
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• pp.206-213
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• 2022

Ecological characteristics of a brown alga, Scytosiphon lomentaria, were investigated from January 2021 to December 2021 in its natural habitat off Sodol, Jumunjin, eastern coast of Korea. The S. lomentaria population at the site formed widespread patches on mid shore. During the investigation, environmental conditions including seawater temperature, salinity, and dissolved oxygen were monitored at the site. Growth and maturation of the S. lomentaria population were identified through qualitative and quantitative investigations. An estimation of the effective cumulative temperature for maturation of the alga was obtained based on growth data and a biological zero temperature of 8℃. Sporangia were observed from February to May when seawater temperatures ranged from 7.7℃ to 16.4℃. A maturation peak was detected in April when seawater temperature was 12.1℃. After zoospore release, the alga became bleached and only the crust remained after June. Developmental initiation of the thallus occurred at temperatures above 8℃. Its maturation required approximately 162 degree-days.

• Korean Journal of Construction Engineering and Management
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• v.24 no.1
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• pp.21-30
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• 2023

Excessive complaints and traffic jams occurred as customers who visited the Drive-thru waited in a long line. Company S recommends DT Pass to reduce the queues. Therefore, this study confirmed the improvement in performance of the queue increasing the number of stores operated by two servers insteaol of one using a queue model. And then confirmed performance improvement by dividing them into DT and DT Pass. After that, the L value derived through the queue model and the number of queues in each store were compared to calculate the number of queues to be additionally provided. Through this, the validity of selecting the minimum number of queues in the future is verified based on the results derived in this study.

• Journal of The Geomorphological Association of Korea
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• v.18 no.4
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• pp.35-57
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• 2011

Minor erosional forms in the bedrock river, like potholes, are not just research subject for the professional geomorphologis. In addition, these features attract general public and make them understand the social contribution and importance of geomorphologic research activities. In this paper, the studies on bedrock minor forms in Korea was reviewed. For further researches, some of major erosional processes and minor forms in bedrock rivers were discussed in detail. Cavitation, plucking, hydro-wedging, and abrasion by passing sediment particles are the major processes to create the longitudinal or transverse minor forms like pothole, furrows, flutes, and runnels. Especially the definition of furrows and runnels are explained to prevent the confusion with pothole, weathering pits and grooves. To make a progress in research on bedrock minor forms the quantitative relationship between the variables should be studied. New techniques for scientific estimation of erosion rates and exposure ages of bedrock surfaces should be used in this field.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4367-4381
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• 2023

Nuclear power plants are increasingly being equipped with digital I&C systems. Although some probabilistic safety assessment (PSA) models for the digital I&C of nuclear power plants have been constructed, there is currently no specific internationally agreed guidance for their modeling. This paper presents an initiative by the OECD Nuclear Energy Agency called "Digital I&C PSA - Comparative application of DIGital I&C Modelling Approaches for PSA (DIGMAP)", which aimed to advance the field towards practical and defendable modeling principles. The task, carried out in 2017-2021, used a simplified description of a plant focusing on the digital I&C systems important to safety, for which the participating organizations independently developed their own PSA models. Through comparison of the PSA models, sensitivity analyses as well as observations throughout the whole activity, both qualitative and quantitative lessons were learned. These include insights on failure behavior of digital I&C systems, experience from models with different levels of abstraction, benefits from benchmarking as well as major contributors to the core damage frequency and those with minor effect. The study also highlighted the challenges with modeling of large common cause component groups and the difficulties associated with estimation of key software and common cause failure parameters.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.1
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• pp.141-152
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• 2007

Considering uncertainties of random input data, it is more reasonable to use probabilistic method than the conventional deterministic method for the design of structures or for the assessment of the responses of structures, which are designed as safe even under extreme loads. Therefore, to assess the quantitative effects of the constructed cable stayed bridge by the input random variables, a sensitivity analysis is studied. Using perturbation method, an analysis program is developed for the iterative probabilistic finite element analyses and sensitivity analyses of the cable stayed bridge, except the initial shape analysis. Monte-Carlo Simulations were used for the verification of the developed program. The results of sensitivity analysis shows the governing effects of external loads. Because the results also provide the sensitive effects of the stiffness of members and the magnitudes of prestressing force of cables, the developed

• Journal of the Korean Institute of Rural Architecture
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• v.26 no.3
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• pp.1-9
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• 2024

This study aims to estimate the cover classification and carbon respiration of halophytes based on the issues of utilising blue carbon in recent context of climate change. To address the aims, the study classified halophytes(Triglochin maritimum L and Phragmites australis), Intertidal(non-vegetated tidal flats) and Supratidal(sandy tidal flats) to measure carbon respiration and classify cover. The results are revealed that first, the carbon respiration in vegetated areas was less than that in non-vegetated areas. Second, the cover classification could be divided into halophyte communities(Triglochin maritimum L, Phragmites australis), Intertidal and Supratidal by NDWI(Moisture Index, Normalized Difference Water Index) Third, the total carbon respiration of blue carbon was calculated to be -0.0121 Ton km² hr^-1 with halophyte communities at -0.0011 Ton km² hr^-1, Intertidal respiration at -0.0113 Ton km² hr^-1 and Supratidal respiration at 0.0003 Ton km² hr^-1. As this challenge is a fundamental study that calculates the quantitative net carbon storage based on the blue carbon-based marine ecosystem, contributing to firstly, measuring the carbon respiration of cordgrass communities, reed communities, and non-vegetated tidal flats, which are potential blue carbon candidates in the study area, to establish representative values for carbon respiration, secondly, verifying the reliability of cover classification of native halophytes extracted through image classification technology, and thirdly, challenging to create a thematic map of carbon respiration, calculating the area and carbon respiration for each classification category.

• Asia-Pacific Journal of Business
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• v.15 no.3
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• pp.139-172
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• 2024

Purpose - This study investigates the relationship between corporate ownership structure and technological innovation for Chinese listed firms. Specifically, we analyze four ownership characteristics: concentration, constraints, alignment, and foreign/domestic institutional investor ownership, and use patent applications to measure innovation. Design/methodology/approach - Employing a quantitative research design, this study uses panel data of Chinese listed companies during the period from 2015 to 2021. The empirical analysis relies on multiple regression models, including Tobit models and two-stage least squares estimation, to assess the relationship between corporate ownership structure characteristics and innovation. Robustness checks are conducted using lagged dependent variables and subgroup analyses based on firm age, ownership type, and stock exchange listing. Findings - First, it provides empirical evidence on the non-linear relationship between ownership concentration and innovation, suggesting that there is an optimal level of ownership concentration for promoting innovation. Second, it highlights the importance of equity constraints in influencing innovation, showing that both excessive and insufficient equity constraints can hinder innovation. Third, the study demonstrates the negative impact of aligned ownership and control on innovation, suggesting that separation of ownership and control may be beneficial for fostering innovation. Fourth, it sheds light on the differential impact of domestic and foreign institutional investors on innovation, suggesting that foreign institutional investors may play a more positive role in promoting innovation. Research implications or Originality - The significance of this study's results lies in the fact that we empirically analyze the relationship between corporate ownership characteristics and technological innovation, thereby suggesting the direction of a desirable corporate governance structure that listed companies should pursue depending on their circumstances. This research contributes to a deeper understanding of the ownership characteristics that influence technological innovation and provides valuable insights for policymakers and corporate managers.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of Plant Biotechnology
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• v.42 no.1
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• pp.60-70
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• 2015

The aim of this study was to investigate whether fourier transform infrared (FT-IR) spectroscopy can be applied to simultaneous determination of fatty acids contents in different soybean cultivars. Total 153 lines of soybean (Glycine max Merrill) were examined by FT-IR spectroscopy. Quantification of fatty acids from the soybean lines was confirmed by quantitative gas chromatography (GC) analysis. The quantitative spectral variation among different soybean lines was observed in the amide bond region ($1,700{\sim}1,500cm^{-1}$), phosphodiester groups ($1,500{\sim}1,300cm^{-1}$) and sugar region ($1,200{\sim}1,000cm^{-1}$) of FT-IR spectra. The quantitative prediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid) from soybean lines were established using partial least square regression algorithm from FT-IR spectra. In cross validation, there were high correlations ($R^2{\geq}0.97$) between predicted content of 5 individual fatty acids by PLS regression modeling from FT-IR spectra and measured content by GC. In external validation, palmitic acid ($R^2=0.8002$), oleic acid ($R^2=0.8909$) and linoleic acid ($R^2=0.815$) were predicted with good accuracy, while prediction for stearic acid ($R^2=0.4598$), linolenic acid ($R^2=0.6868$) had relatively lower accuracy. These results clearly show that FT-IR spectra combined with multivariate analysis can be used to accurately predict fatty acids contents in soybean lines. Therefore, we suggest that the PLS prediction system for fatty acid contents using FT-IR analysis could be applied as a rapid and high throughput screening tool for the breeding for modified Fatty acid composition in soybean and contribute to accelerating the conventional breeding.