• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1272-1278
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• 2011

This study was conducted to reclassify Cheongweon series based on the second edition of Soil Taxonomy and to discuss the formation of Cheongweon series distributed on broad continental alluvial plains. Morphological properties of typifying pedon of Cheongweon series were investigated and physico-chemical properties were analyzed according to Soil survey laboratory methods manual. The typifying pedon of Cheongweon series has dark grayish brown (2.5Y 4/2) silt loam Ap horizon (0~18 cm), dark grayish brown (2.5Y 4/2) silt loam BA horizon (18~30 cm), dark yellowish brown (10YR 4/6) silty clay loam Bt1 horizon (30~60 cm), strong brown (7.5YR 4/6) silty clay loam Bt2 horizon (60~91 cm), brown (10YR 4/4) silt loam BC horizon (91~104 cm), and mottled (7.5YR 4/6, and 7.5YR 5/2) silt loam C horizon (104~160 cm). The typifying pedon has an argillic horizon from a depth of 30 to 91 cm and a base saturation (sum of cations) of 35% or more at 125 cm below the upper boundary of the argillic horizon. It can be classified as Alfisol, not as Incceptisol. It has udic soil moisture regime, and can be classified as Udalf. Also that meets the requirements of Hapluadalf. It has anthraquic condition, and keys out as Anthraquic Hapludalf. That has fine silty textural family, and has mesic soil temperature regime. Therefore Cheongweon series can be classified as fine silty, mixed, mesic family of Anthraquic Hapludalfs, not as fine silty, mixed, mesic family of Fluvaquentic Epiaquepts.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.968-974
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• 2010

We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.1
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• pp.25-30
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• 2007

Objective of this experiment was to investigate the growth effects of Chinese cabbage and soil salinity to alternative irrigation waters for drought periods. The treatments were consisted of the discharge water from industrial wastewater treatment plant (DIWT), the discharge water from municipal wastewater treatment plant (DMWT) and ground water as the control. For the chemical compositions of alternative water, it appeared that concentrations of the $Ni^+$ and SAR values in DIWT were over the reuse criteria of other countries for irrigation, but CODcr concentration in DMWT was higher than the reuse criteria for agricultural irrigation. According to classification of water by $EC_i$ value, DIWT and DMWT are ranged from 0.7 to $2.0dS\;m^{-1}$, slight salinity. Average harvest indexes were 0.64 for DIWT and 0.63 for DMWT as compared to 0.61 of the control regardless of irrigation periods. SAR value in soil was increased with prolonging the irrigation periods at head forming stage, but not much difference except for 30 days of irrigation period at harvesting time for DIWT. However, it was not much difference along with irrigation periods through the growth stages for DMWT as compared with the groundwater. At harvesting time, average $EC_e$ for the soil irrigated with alternative agricultural waters was $0.017dS\;m^{-1}$ for its DIMT and $0.036dS\;m^{-1}$ for its DMWT as compared to $0.013dS\;m^{-1}$ of its groundwater as the control. For $NH_4-N$ concentrations, it observed that there were no differences among the treatments with different irrigation periods at head forming stage in soil after irrigation. Also, $NO_3-N$ concentration in soil was increased up to 20 days after irrigation, and then decreased at 30 days after irrigation with DMWT at head forming stage. The $Ni^+$ concentration in upper layer soil (0-15 cm) irrigated with DIWT was increased with prolonging the irrigation period at head forming stage, but it was dramatically decreased and almost constant in all the treatments at harvesting time. Therefore, it might be concluded that there was potentially safe to irrigate the discharge water from municipal wastewater treatment plant for 20 days after transplanting to drought periods with cultivating the Chinese cabbage.

• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.28-42
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• 2016

Objectives : The author tried to find out reasons why and how hysteria(and conversion disorder) patient numbers, which were so prevalent even a few decades ago, have decreased and the phenotype of symptoms have changed. Methods : The number of visiting patients diagnosed with conversion disorder and their phenotype of symptoms were investigated through chart reviews in a psychiatric department of a University hospital for the last 12 years. Additionally, the characteristics of conversion disorder patients visiting the emergency room for last 2 years were also reviewed. Those results were compared with previous research results even if it seemed to be an indirect comparisons. The research relied on Briquet P. and Charcot JM's established factors of the vicissitudes of hysteria(and conversion disorder) which has been the framework for more than one hundred and fifty years since hysteria has been investigated. Results : The author found decreased numbers and changes of the phenotype of the hysteria patients(and conversion disorder) over the last several decades. The decreased numbers and changes of the symptoms of those seemed to be partly due to several issues. These issues include the development of the diagnostic techniques to identify organic causes of hysteria, repeated changes to the symptom descriptions and diagnostic classification, changes of the brain nervous functions in response to negative emotions, and the influence of human evolution. Conclusions : The author proposed that the evolutionary brain discord reaction theory explains the causes of disappearance of and changes to symptoms of hysteria(conversion disorder). Most patients with hysteria(conversion disorder) have been diagnosed in the neurological department. For providing more appropriate treatment and minimizing physical disabilities to those patients, psychiatrists should have a major role in cooperating not only with primary care physicians but with neurologists. The term 'hysteria' which had been used long ago should be revived and used as a term to describe diseases such as somatic symptom disorder, functional neurological symptoms, somatization, and somatoform disorders, all of which represent almost the same vague concept as hysteria.

• Korean Journal of Psychosomatic Medicine
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• v.23 no.1
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• pp.26-35
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• 2015

Objectives:The purpose of this study was to evaluate reliability and validity of the Korean version of the Postconcussional Syndrome Questionnaire(KPCSQ) which was originally developed in 1992 by Lees-Haley. Methods:Patients with traumatic brain injury were recruited from April 2009 to December 2011 from the Korean University Ansan Hospital. We selected patients that met the ICD-10 diagnostic criteria of postconcussional syndrome and organic mental disorder including organic mood disorder, organic emotionally labile disorder, organic anxiety disorder and organic personality disorder. The KPCSQ, Trait and State Anxiety Inventory(STAI-I, II), and Center for Epidemiologic Studies Depression Scale(CESD) were administered to all subjects. Factor analysis of the items were performed and test-retest correlation were evaluated. Internal consistency of the KPCSQ and its subscales was assessed with Cronbach's alpha. External validity of the KPCSQ were examined by correlation coefficient with the STAI-I, II, and CESD. Results:The Cronbach's alpha coefficient of the total PCSQ was 0.956. The test-retest reliability coefficient was 0.845. The PCSQ showed significant correlation with STAI-I, II and CESD. The factor analysis of the PCSQ yielded 4 factors model. Factor 1 represented 'affective and cognitive symptoms', factor 2 represented 'somatic symptoms', factor 3 represented 'infrequent symptoms' and factor 4 represented 'exaggeration or inattentive response'. There was no significant difference between the PCS group and the organic mental disorder group in the score on each measure. The scores on KPCSQ and its subscales in the subjects that had scored 5 or more in 'exaggeration or inattentive response' are significantly higher than those in the subjects had scored 4 in 'exaggeration or inattentive response'. Conclusions:This study suggests that the Korean version of PCSQ is a valid and reliable tool for assessing psychiatric symptomatology of patients with traumatic brain injury. Further investigations with greater numbers of subjects are necessary to assess the clinical usefulness of the KPCSQ.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1475-1490
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• 2021

Detecting oil spill area using statistical characteristics of SAR images has limitations in that classification algorithm is complicated and is greatly affected by outliers. To overcome these limitations, studies using neural networks to classify oil spills are recently investigated. However, the studies to evaluate whether the performance of model shows a consistent detection performance for various oil spill cases were insufficient. Therefore, in this study, two CNNs (Convolutional Neural Networks) with basic structures(Simple CNN and U-net) were used to discover whether there is a difference in detection performance according to the structure of CNN and distribution characteristics of oil spill. As a result, through the method proposed in this study, the Simple CNN with contracting path only detected oil spill with an F1 score of 86.24% and U-net, which has both contracting and expansive path showed an F1 score of 91.44%. Both models successfully detected oil spills, but detection performance of the U-net was higher than Simple CNN. Additionally, in order to compare the accuracy of models according to various oil spill cases, the cases were classified into four different categories according to the spatial distribution characteristics of the oil spill (presence of land near the oil spill area) and the clarity of border between oil and seawater. The Simple CNN had F1 score values of 85.71%, 87.43%, 86.50%, and 85.86% for each category, showing the maximum difference of 1.71%. In the case of U-net, the values for each category were 89.77%, 92.27%, 92.59%, and 92.66%, with the maximum difference of 2.90%. Such results indicate that neither model showed significant differences in detection performance by the characteristics of oil spill distribution. However, the difference in detection tendency was caused by the difference in the model structure and the oil spill distribution characteristics. In all four oil spill categories, the Simple CNN showed a tendency to overestimate the oil spill area and the U-net showed a tendency to underestimate it. These tendencies were emphasized when the border between oil and seawater was unclear.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.113-137
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• 2021

According to the clear potential of mobile banking growth, many studies related to this are being conducted, but in Korea, it is concentrated on the analysis of technical factors or consumers' intentions, behaviors, and satisfaction. In addition, even though it has a strong customer base of 20s, there are few studies that have been conducted specifically for this customer group. In order for mobile banking to take a leap forward, a strategy to secure various perspectives is needed not only through research on itself but also through research on external factors affecting mobile banking. Therefore, this study analyzes impulsiveness, credit card use, and SNS addiction among various external factors that can significantly affect mobile banking in their 20s. This study examines whether the relationship between impulsiveness and mobile banking usage depends on whether or not a credit card is used, and checks whether a customer's impulsiveness is possible by examining whether a credit card is used. Based on this, it is possible to establish new standards for classification of marketing target groups of mobile banking. After finding out the static or unsuitable relationship between whether to use a credit card and impulsiveness, we want to indirectly predict the customer's impulsiveness through whether to use a credit card or not to use a credit card. It also verifies the mediating effect of SNS addiction in the relationship between impulsiveness and mobile banking usage. For this analysis, the collected data were conducted according to research problems using the SPSS Statistics 25 program. The findings are as follows. First, positive urgency has been shown to have a significant static effect on mobile banking usage. Second, whether to use credit cards has shown moderating effects in the relationship between fraudulent urgency and mobile banking usage. Third, it has been shown that all subfactors of impulsiveness have significant static relationships with subfactors of SNS addiction. Fourth, it has been confirmed that the relationship between positive urgency, SNS addiction, and mobile banking usage has total effect and direct effect. The first result means that mobile banking usage may be high if positive urgency is measured relatively high, even if the multi-dimensional impulsiveness scale is low. The second result indicates that mobile banking usage rates were not affected by the independent variable, negative urgency, but were found to have a significant static relationship with negative urgency when using credit cards. The third result means that SNS is likely to become addictive if lack of premeditation or lack of perseverance is high because it provides instant enjoyment and satisfaction as a mobile-based service. This also means that SNS can be used as an avoidance space for those with negative urgency, and as an emotional expression space for those with high positive urgency.

• Journal of Science Education
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• v.45 no.2
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• pp.187-200
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• 2021

This study was conducted to identify students' meaningful scientific experiences and to ascertain the path through which the experience led to learning. The subjects of 'Understanding of the History of Science' were asked to write an essay on the subject of 'Effects of science on my life' to 81 students in the department of literature and 125 students in the science department. After that Classification criteria were established through scientific experts' seminars, and the scientific experiences that affected students and their effects were examined. The results from analyses were summarized as follows: First, As a result of study about Science Education experience that has impacted students' lives, the students were influenced by images, most of which were influenced by scientific videos. They were also influenced by science classes and science books. As a result of classifying science experience, most of the experience is composed of Informal Science Learning. Second, as a result of examining how students were influenced by their scientific experience, they found that they were affected by their daily life or influenced by science. As a result of the research, it can be confirmed that Informal Science Learning experience is an important learning form that has a great influence on students. Therefore, appropriate Informal Science Learning experience should be introduced into the class, and research and development on the Informal Science Learning experience preferred by the students should be done.

• 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.

• Journal of Life Science
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• v.31 no.9
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• pp.840-848
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• 2021

This study was conducted to estimate annual trends and the environmental effects in the racing records of Jeju horses. The Korean Racing Authority (KRA) collected 48,645 observations for 2,167 Jeju horses from 2002 to 2019. Racing records were preprocessed to eliminate errors that occur during the data collection. Racing times were adjusted for comparison between race distances. A stepwise Akaike information criterion (AIC) variable selection method was applied to select appropriate environment variables affecting racing records. The annual improvement of the race time was -0.242 seconds. The model with the lowest AIC value was established when variables were selected in the following order: year, budam classification, jockey ranking, trainer ranking, track condition, weather, age, and gender. The most suitable model was constructed when the jockey ranking and age variables were considered as random effects. Our findings have potential for application as basic data when building models for evaluating genetic abilities of Jeju horses.