• Journal of Wetlands Research
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• v.23 no.4
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• pp.317-326
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• 2021

The present study was carried out with a view to understand the distribution and ecology of Clihton retropictus (Martens, 1879), a class II endangered wildlife designated and protected by the Ministry of Environment, Republic of Korea, and to suggest the effective conservation and management measures for this species and its habit. First, the distribution of Clihton retropictus was investigated nationwide, and environmental factors such as salinity and substratum were analyzed in consideration of the ecological characteristics of this species. In addition, the individual size, density, and movement of Clihton retropictus per each district surveyed were analyzed. Due to its nature of inhabiting in the brackish water zone, the analysis showed that the salinity of this species was 0.7 ~ 16.6‰ at low tide and 1.0 ~ 17.3% at high tide. It was learned from the analysis of substratum that its composition in each river under investigation was slightly different, but most of substratum had a higher composition ratio than gravel (pebble, 16 ~ 64 mm). On the other hand, the size of each individual was checked by measuring the length of its diameter, and there was almost no change in the individual when the inhabited range of Clihton retropictus was short. However, there was tendency that the longer the habitat range, the bigger the individual size. From surveying the population density by season, it was made clear that, during the summer (July to August) and fall (September to October), the density was relatively higher while the number of individuals decreased significantly during winter (November to December) when the water temperature was lowered. In an effort to effectively establish conservation and management measures, the moving distance was measured, and it became known that, during the surveys in summer and fall when the individuals were active, the individuals moved in more distances than during the winter survey. The results of this study are expected to be utilized as basic data for establishing effective management plans such as creation of habitats for Clihton retropictus, its migration projects and selection of migration destinations which get unavoidable due to development projects.

• Journal of the Korean Society of Radiology
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• v.15 no.5
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• pp.591-602
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• 2021

Acute ischemic stroke(AIS) should be diagnosed within a few hours of onset of cerebral infarction symptoms using diagnostic radiology. In this study, we evaluated the clinical usefulness of SVD and the Bayesian algorithm to measure the volume of cerebral infarction using computed tomography perfusion(CTP) imaging and magnetic resonance diffusion-weighted imaging(MR DWI). We retrospectively included 50 patients (male : female = 33 : 17) who visited the emergency department with symptoms of AIS from September 2017 to September 2020. The cerebral infarct volume measured by SVD and the Bayesian algorithm was analyzed using the Wilcoxon signed rank test and expressed as a median value and an interquartile range of 25 - 75 %. The core volume measured by SVD and the Bayesian algorithm using was CTP imaging was 18.07 (7.76 - 33.98) cc and 47.3 (23.76 - 79.11) cc, respectively, while the penumbra volume was 140.24 (117.8 - 176.89) cc and 105.05 (72.52 - 141.98) cc, respectively. The mismatch ratio was 7.56 % (4.36 - 15.26 %) and 2.08 % (1.68 - 2.77 %) for SVD and the Bayesian algorithm, respectively, and all the measured values had statistically significant differences (p < 0.05). Spearman's correlation analysis showed that the correlation coefficient of the cerebral infarct volume measured by the Bayesian algorithm using CTP imaging and MR DWI was higher than that of the cerebral infarct volume measured by SVD using CTP imaging and MR DWI (r = 0.915 vs. r = 0.763 ; p < 0.01). Furthermore, the results of the Bland Altman plot analysis demonstrated that the slope of the scatter plot of the cerebral infarct volume measured by the Bayesian algorithm using CTP imaging and MR DWI was more steady than that of the cerebral infarct volume measured by SVD using CTP imaging and MR DWI (y = -0.065 vs. y = -0.749), indicating that the Bayesian algorithm was more reliable than SVD. In conclusion, the Bayesian algorithm is more accurate than SVD in measuring cerebral infarct volume. Therefore, it can be useful in clinical utility.

• Journal of Family Resource Management and Policy Review
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• v.25 no.1
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• pp.15-34
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• 2021

Purpose : This study aims to identify the influence of individual, parental, workplace, and policy variables on the intention of marriage of unmarried workers. The results of the study can be used as a basis to come up with policy and practical measures to increase these workers' intention of marriage. Methods : Data was collected from 480 participants through a questionnaire. The measuring tools in this study were tested for reliability and validity. In addition, technical statistics, ANOVA, correlation analysis, and hierarchical regression analysis were performed by SPSS 18.0. Results : First, unmarried workers' willingness to marry was higher above the average. Second, significant differences in the unmarried workers' intention of marriage were revealed based on gender, age, level of education, total assets, and debt status. Significant associations were also found with parents' economic levels and the possibility of parental support for housing and marriage expenses. The differences in response based on employment patterns, job satisfaction, and family-friendly organizational culture were also significant. The correlation between policy variables and marriage intentions also showed the necessity of a funded housing policy and a marriage preparation policy. Third, based on the hierarchical regression analysis using personal, parental, and workplace variables to identify the factors affecting unmarried workers' willingness to marry, it is clear that gender, age, and the likelihood of parental support for housing and marriage expenses have a significant impact. A family-friendly organizational culture and funded housing policy were also significant contributors. Conclusion : The study found that the funded housing policy was the most important factor affecting unmarried office workers' willingness to marry. Additionally, the possibility of parental support for housing and marriage expenses and a family-friendly organizational culture at work were found to have an important impact on the improvement of unmarried workers' willingness to marry.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• Knowledge Management Research
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• v.22 no.3
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• pp.151-172
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• 2021

The government's implementation of customer-friendly financial policies, such as lowering commission fees for credit card merchants and lowering the maximum interest rate, put the specialized credit finance companies in a crisis of lowering profitability. In this unfavorable situation, the efficiency study of specialized credit finance companies is meaningful. Accordingly, this study measured the efficiency of 34 specialized credit finance companies through Data Envelopment Analysis (DEA) and meta-frontier analysis. For meta-frontier analysis, specialized credit finance companies were divided into two groups (card companies and non-card companies) by industry or three groups (AA0 and above, AA-, and A+ or below) by credit rating. The results of the analysis will provide general insight into the efficiency of specialized credit finance companies. The results of this study are as follows. First, the average meta-efficiency of card companies was analyzed higher than that of non-card companies. Second, 80% of non-card's decision-making units (DMUs) were inefficient by pure technology rather than by scale. Third, decision-making units (DMUs), which account for 62.5% of the credit card company group and 80% of the 'AA-' credit rating group, are in non-economic areas of scale. Fourth, there was no statistically significant difference in meta-efficiency values (TE and PTE) by industry (card companies, non-card companies) and credit rating (AA0 or higher, AA-, A+ or lower). The contribution of this study will provide strategic initiatives for establishing management strategies to improve inefficiency by measuring the efficiency level of companies under an unfriendly business environment for specialized credit finance companies.

• Korean Journal of Food Science and Technology
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• v.53 no.2
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• pp.223-229
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• 2021

To evaluate the protective effect of Codium fragile on fine dust (PM2.5)-induced cytotoxicity, we investigated its antioxidant activity and cell protective effect on PM2.5-exposed cells. The 40% ethanolic extract of C. fragile showed the highest total phenolic content, whereas the water extract of C. fragile showed the highest total polysaccharide content. The protective effect of the extracts on PM2.5-induced oxidative damage in nasal cavity (RPMI2650), lung (A549), brain (MC-IXC), hippocampus (HT-22), and microglia (BV-2) cells was evaluated by measuring the intracellular reactive oxygen species (ROS) content and cell viability. The results showed that the 40% ethanolic extract more efficiently inhibited ROS production than the water extract. In contrast, PM2.5-exposed cells treated with the water extract showed higher viability than those treated with the 40% ethanolic extract.

• Journal of Bio-Environment Control
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• v.30 no.3
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• pp.196-205
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• 2021

This research was conducted in order to analyze the difference in yield through the changes in growth and measuring the photosynthesis efficiency in cherry tomatoes. Seedlings of cherry tomato 'Nonari' were used as scion and non-grafted control, while 4 different grafted tomatoes 'Powerguard', 'T1', 'L1', and 'B.blocking' were used as rootstocks. Plants grafted onto 'B.blocking' produced the highest fruit yield (417.5 g plant^-1), whereas non-grafted plant 'Nonari' had the lowest fruit yield, (354.2 g plant^-1) at the latter period of cherry tomatoes in May. The flowering position in May, plant grafted onto 'B.blocking', showed 14-17 cm, whereas non-grafted plant 'Nonari' showed 10-14 cm. The growth strength on May 15, non-grafted plant 'Nonari', showed 8.43 mm which was the lowest value among the treatments. Grafted plants kept the growth balance until the end of the harvest that led to an increase in fruit yield, while non-grafted plant weakened the vigor earlier that led to a decrease in fruit yield. Grafted plants showed higher values of chlorophyll fluorescence variables than the values of non-grafted plant. These results indicate that grafting influenced fruit yield which was observed as maintaining growth balance for longer and an increase in photosynthesis efficiency compared to non-grafting.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

• Journal of Korean Philosophical Society
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• v.116
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• pp.1-31
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• 2010

This Article studies a meaning of geometrical-mathematical spatial idea in the source of modern theories of space. Modern theories of space elucidated a relation of human and space through the geometrical terms; point, line, plane and extension etc. Descartes and Newton identified space as a natural realty, Leibniz and Kant elucidated space as a subjective idea or form. It is the result of modern spatial theories that space is lied nearly in human. In the meaning of natural space, space is empirically unfolded with a shape of measuring in front of human's eyes. In the meaning of cognitional space, space is a method or subjective cognitional form that human understands nature and constitutes world. Modern theories of space would be divided into four patterns. In Newton's theory space is absolutely prior to things. In Leibniz' theory space is a co-existence order of Monads. In Descartes's theory space is identified with extension. In Kant's theory space is cognitional form of subject. They all are confronted with each other in the source of space. In their confrontation they reflected on the relation of human and space in their own standpoint. We classify their particularly differential concepts of space into natural space and cognitional space. And then we analyze a difference of spatial meanings, and then investigate foundations of meaning of modern theories of space. On the one hand they are become to the source of alienation of human from space. But on the other they are contributed to get space familiar with human through a wakening for the correlation of human and space. The natural space indicates that with measurable shape space is extended really in front of human's experiential eyes. But the cognitional space elucidates that space is only a subjective idea or form with which human understands nature and constructs world. In the former it is embossed that space is independent to human, and is able to be measured and to be treated according to natural raws. In the latter it is evidenced that space is not separated to human, and that space is not without human, and a correlation existed between human and space. Humanist ideal is declared in them. It was a declaration of human sovereignty to nature. But this declaration is caused to alienate human beings from space.

• Journal of Ecology and Environment
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• v.42 no.4
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• pp.210-218
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• 2018

Background: Soil respiration (Rs) is a major factor of the absorption and accumulation of carbon through photosynthesis in the ecosystem carbon cycle. This directly affects the amount of net ecosystem productivity, which affects the stability and sustainability of the ecosystem. Understanding the characteristics of Rs is indispensable to scientifically understand the carbon cycle of ecosystems. It is very important to study Rs characteristics through analysis of environmental factors closely related to Rs. Rs is affected by various environmental factors, such as temperature, precipitation, soil moisture, litter supply, organic matter content, dominant plant species, and soil disturbance. This study was conducted to analyze the effects of micro-topographical differences on Rs in forest vegetation by measuring the Rs on the ridge and southern slope sites of the broadly established Quercus mongolica forest in the central Korean area. Method: Rs, Ts, and soil moisture data were collected at the southern slope and ridge of the Q. mongolica forest in the Mt. Jeombong area in order to investigate the effects of topographical differences on Rs. Rs was collected by the closed chamber method, and data collection was performed from May 2011 to October 2013, except Winter seasons from November to April or May. For collecting the raw data of Rs in the field, acrylic collars were placed at the ridge and southern slope of the forest. The accumulated surface litter and the soil organic matter content (SOMC) were measured to a 5 cm depth. Based on these data, the Rs characteristics of the slope and ridge were analyzed. Results: Rs showed a distinct seasonal variation pattern in both the ridge and southern slope sites. In addition, Rs showed a distinct seasonal variation with high and low Ts changes. The average Rs measurements for the two sites, except for the Winter periods that were not measured, were $550.1\;mg\;CO_2m^{-2}h^{-1}$ at the ridge site and $289.4\;mg\;CO_2m^{-2}h^{-1}$ at the southern slope, a difference of 52.6%. There was no significant difference in the Rs difference between slopes except for the first half of 2013, and both sites showed a tendency to increase exponentially as Ts increased. In addition, although the correlation is low, the difference in Rs between sites tended to increase as Ts increased. SMC showed a large fluctuation at the southern slope site relative to the ridge site, as while it was very low in 2013, it was high in 2011 and 2012. The accumulated litter of the soil surface and the SOMC at the depth range of 0~5 cm were $874g\;m^{-2}$ and 23.3% at the ridge site, and $396g\;m^{-2}$ and 19.9% at the southern slope site. Conclusions: In this study, Rs was measured for the ridge and southern slope sites, which have two different results where the surface litter layer is disturbed by strong winds. The southern slope site shows that the litter layer formed in autumn due to strong winds almost disappeared, and while in the ridge site, it became thick due to the transfer of litter from the southern slope site. The mean Rs was about two times higher in the ridge site compared to that in the southern slope site. The Rs difference seems to be due to the difference in the amount of litter accumulated on the soil surface. As a result, the litter layer supplied to the soil surface is disturbed due to the micro-topographical difference, as the slope and the change of the community structure due to the plant season cause heterogeneity of the litter layer development, which in turn affects SMC and Rs. Therefore, it is necessary to introduce and understand these micro-topographical features and mechanisms when quantifying and analyzing the Rs of an ecosystem.