• Geophysics and Geophysical Exploration
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• v.10 no.3
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• pp.173-182
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• 2007

It is well known that manganese nodules enriched with valuable metals are abundantly distributed in the abyssal plain area in the Clarion-Clipperton (C-C) fracture zone of the northeast Pacific. Previous studies using deep-sea camera (DSC) system reported different observations about the relation of seafloor topographic change and nodule abundance, and they were sometimes contradictory. Moreover, proper foundation on the estimation of DSC underwater position, was not introduced clearly. The variability of the mining condition of manganese nodule according to seafloor topography was examined in the Korea Deep Ocean Study (KODOS) area, located in the C-C zone. In this paper, it is suggested that the utilization of deep towing system such as DSC is very useful approach to whom are interested in analysing the distributional characteristics of manganese nodule filed and in selecting promising minable area. To this purpose, nodule abundance and detailed bathymetry were acquired using deep-sea camera system and multi-beam echo sounder, respectively on the seamount free abyssal hill area of southern part ($132^{\circ}10'W$, $9^{\circ}45'N$) in KODOS regime. Some reasonable assumptions were introduced to enhance the accuracy of estimated DSC sampling position. The accuracy in the result of estimated underwater position was verified indirectly through the comparison of measured abundances on the crossing point of neighboring DSC tracks. From the recorded seafloor images, not only nodules and sediments but cracks and cliffs could be also found frequently. The positions of these probable unminable area were calculated by use of the recorded time being encountered with them from the seafloor images of DSC. The results suggest that the unminable areas are mostly distributed on the slope sides and hill tops, where nodule collector can not travel over.

• KSBB Journal
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• v.21 no.2
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• pp.110-117
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• 2006

During routine maintenance, animal cell lines are commonly cryopreserved in growth medium containing serum with 10% DMSO. But, in case of bioprocess under the serum-free conditions, including cultivation of cell lines and producing of pharmaceuticals, the cryopreservation should be executed without serum to prevent a cross-contamination. This experiments were performed to investigate the effects of the serum-free cryopreservation on the CHO cells. To improve the survival rates of the cryopreserved CHO cells in serum-free condition, first, the effects of permeable and non-permeable additives for substitute serum on cell viability were investigated. The combination of 10% DMSO and 0.03 M raffinose in MEM-${\alpha}$ without serum indicated 76% of cell viability. However, it did not reach the survival rates(more than 95%) of the conventional cryopreservation. In the second, to evaluate the cryopreservative ability of the serum-free medium(SFM) we compared viability of the CHO cells cryopreserved in the SFMs(Sigma C5467, C4726, and C1707, JBI SF486 and PF486), the cryoprotectant(Genenmed CAN-1000) and the MEM-${\alpha}$ with serum. All solution contained 10% DMSO. As a result of the comparison, cryopreserved cells in the SFMs showed over 95% of viability and appeared predominant viability better than cryoprotectant CAN-1000. Finally, we assessed the stability of the CHO cells in the long-term cryopreservation(LTC) using SFM. Every three months, the cryopreserved CHO cells were thawed to estimate the cell viability and the recovery rates. Then, real-time RT-PCR analyzed the inserted CHO DHFR gene. All results for the LTC appeared the same stability as the serum containing cryopreservation. In the conclusion, it could be seen that the LTC in the SFM can substitute for serum using methods in the bioprocess proceeded by CHO cells for more than 18 months.

• Journal of Chest Surgery
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• v.37 no.5
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• pp.416-422
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• 2004

Acute renal failure (ARF) is a common postoperative complication after the cardiac surgery. Postoperative ARF have various causes, and are combined with other complications rather than being the only a complication. It deteriorates the general condition of the patient, and makes it difficult to manage the combined complications by disturbing the adequate medication and fluid therapy. We have planned this study to evaluate the effects of postoperative ARF after the on-pump coronary artery bypass surgery (CABG) on the recovery of patients and identify the risk factors. Method and Material: We reviewed the medical records of patients who underwent CABG with cardiopulmonary bypass by a single surgeon from Jan. 2000 to Dec. 2002, We checked the preoperative factors; sex, age, history of previous serum creationism over 2.0 mg/㎗, preoperatively last checked serum creatinine, diabetes, hypertension, left ventricular ejection fraction, intraoperative factors; whether the operation is an emergent case or not, cardiopulmonary bypass time, aortic cross clamp time, the number of distal anastomosis, postoperative factors: IABP. Then we have studied the relations of these factors and the cases of postoperative peak serum creatinine over 2.0 mg/㎗. Result: There were 19 cases with postoperative peak serum creatinine over 2.0 mg/㎗ in a total 97 cases. Dialysis were done in 3 cases for ARF with pulmonary edema and severely reduced urine output. There were 8 cases (42.1%) with combined complications among the 19 patients. This finding showed a significant difference from the 5 cases (6,4%) in the patients whose creatinine level have not increased over 2.0 mg/㎗. The mortalities are different as 1.3% to 10.5%. The risk factors that are related with postoperative serum creatinine increment over 2.0 mg/㎗ are diabetes, the history of previous serum creatinine over 2.0 mg/㎗ and left ventricular ejection fraction. Conclusion: Postoperative ARF after the on-pump CABG is related with preoperative diabetes, the history of previous serum creatinine over 2,0 mg/㎗ and left ventricular ejection fraction. Postoperative ARF could De the reason for increased rate of complications and mortality after on-pump CABG. Therefore, in the patients with these risk factors, the efforts to prevent postoperative ARF like off-pump CABG should be considered.

• Journal of Food Hygiene and Safety
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• v.27 no.4
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• pp.432-441
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• 2012

In this study, the transfer rate of wild type Listeria mon, ytogenes (LM) was investigated to establish the standard of safety management during pork meat pr, essing for meat to meat and meat to food contact surfaces contamination at 5 and $10^{\circ}C$. The transfer rate of LM from meat to meat during the pr, essing increased from 0.02% after 30 min to 0.42% after 120 min at $5^{\circ}C$, while for conveyor belt and stainless steel, it decreased from 0.015% and 0.013% after 30 min to 0.002% and 0.0003% after 120 min at $5^{\circ}C$, respectively (p < 0.05). When temperature increased to $10^{\circ}C$, the transfer rates of LM from meat to meat, conveyor belt and stainless steel were the highest at 60 min exposure, and all decreased after 120 min. In reverse, the transfer rate from food contact surface to pork meat was significantly higher than that from pork meat to food contact surface (p < 0.01). Also, the transfer rate to conveyor belt was significantly higher than stainless steel (p < 0.05) and it was highest at 30 min exposure time in both 5 and $10^{\circ}C$. This study indicates that the transfer and adherence rates of LM are influenced by the contact time and temperature. Consequently, these results were utilized to develop a predictive model with a high level of confidence which can lead to prevent cross-contamination during pork meat processing.

• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.83-93
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• 2016

Objectives : The Center for Epidemiologic Studies Depression scale-Revised is a recently revised scale which has been reported as a valid tool for the assessment of depressive symptoms. It encompasses cardinal symptoms of depression described in the Diagnostic and Statistical Manual of Mental disorders, fourth edition. In this study, we assessed the reliability, validity and psychometric properties of the Korean version of the CESD-R(K-CESD-R). Methods : Forty-eight patients diagnosed as major depressive disorder, dysthymia, depressive disorder NOS according to the DSM-IV criteria using Mini International Neuropsychiatric Interview and 48 healthy controls were enrolled in this study. They were assessed with K-CESD-R, K-MADRS, PHQ-9, KQIDS-SR, STAI to check cross-validation. Statistical analyses were performed using calculation of Cronbach's alpha, Pearson correlation coefficient, Principal Component Analysis, ROC curve and optimal cut-off value. Results : The Cronbach's alpha of K-CESD-R was 0.98. The total score of K-CESD-R revealed significantly high correlations with those of K-MADRS, PHQ-9, KQIDS-SR(r=0.910, 0.966 and 0.920, p<0.001, respectively). Factor analysis showed two factors account for 76.29% of total variance. We suggested the optimal cut-off value of K-CESD-R as 13 according to analysis of the ROC curve which value sensitivity and specificity both equally. Conclusions : These Results showed that the K-CESD-R could be a reliable and valid scale to assess depressive symptoms. The K-CESD-R is expected as a useful and effective tool for screening and measuring depressive symptoms not only in outpatient clinic but also epidemiologic studies.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1739-1756
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• 2021

Atmospheric nitrogen dioxide (NO₂) is mainly caused by anthropogenic emissions. It contributes to the formation of secondary pollutants and ozone through chemical reactions, and adversely affects human health. Although ground stations to monitor NO₂ concentrations in real time are operated in Korea, they have a limitation that it is difficult to analyze the spatial distribution of NO₂ concentrations, especially over the areas with no stations. Therefore, this study conducted a comparative experiment of spatial interpolation of NO₂ concentrations based on two linear-regression methods(i.e., multi linear regression (MLR), and regression kriging (RK)), and two machine learning approaches (i.e., random forest (RF), and support vector regression (SVR)) for the year of 2020. Four approaches were compared using leave-one-out-cross validation (LOOCV). The daily LOOCV results showed that MLR, RK, and SVR produced the average daily index of agreement (IOA) of 0.57, which was higher than that of RF (0.50). The average daily normalized root mean square error of RK was 0.9483%, which was slightly lower than those of the other models. MLR, RK and SVR showed similar seasonal distribution patterns, and the dynamic range of the resultant NO₂ concentrations from these three models was similar while that from RF was relatively small. The multivariate linear regression approaches are expected to be a promising method for spatial interpolation of ground-level NO₂ concentrations and other parameters in urban areas.

• Journal of the Korean Applied Science and Technology
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• v.36 no.3
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• pp.1028-1040
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• 2019

The current study was performed to investigate the magnitude of exercise-induced muscle damage (EIMD) after downhill running (DR) of different intensities and to examine the availability of muscle echo intensity as biomarkers to detect regional damage within quadriceps muscle group (QG) following DR. Healthy college-age men (n=11) were experienced twice DR sessions [$50%HR_{max}$ DR, LDR; $70%HR_{max}$ DR, HDR] separated by a 2-week wash-out period with the random order. After DR, severity of EIMD according to exercise intensity were determined by serum creatine kinase (CK) activity, muscle tenderness, and neuromuscular function indicators such as a maximal voluntary isometric contraction (MVIC) and range of motion (ROM). Transvaginal B-mode imaging had been employed to evaluate regional muscle echo intensity within QG [rectus femoris, RF; vastus lateralis, VL; vastus medialis, VM; vastus intermedius, VI]. After both DR sessions, changes in serum CK activity and muscle tenderness have tended to more increase in HDR compared to those of LDR. There was a significant interaction effect between exercise intensity during DR and the time course of serum CK activity(p<.05). However, there were no statistical differences between sessions in muscle tenderness. The time course of changes in the neuromuscular functions after DR were similar to those of regional muscle echo intensity regardless exercise intensity. Although neuromuscular function showed to decline in HDR more than those of LDR after DR, no statistical differences between sessions. In contrast, there were significant interaction effects between sessions and time course of changes in RF and VL muscle echo intensity(p<.01), but not shown in those of VI and VM. These results indicated that each muscles within the QG show different response profiles for EIMD during DR, exercise intensity influences on these responses as well. In particular, current findings suggested that muscle echo intensity derived from ultrasound imaging is capable of detecting regional muscle damage in QG following DR.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• Journal of Life Science
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• v.32 no.12
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• pp.947-955
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• 2022

Silkworms, which have recently shown promise as functional health foods, show functional differences between varieties; therefore, the need for variety identification is emerging. In this study, we analyzed the whole silkworm genome to identify 10 unique silkworm varieties (Baekhwang, Baekok, Daebaek, Daebak, Daehwang, Goldensilk, Hansaeng, Joohwang, Kumkang, and Kumok) using single nucleotide polymorphisms (SNP) present in the genome as biomarkers. In addition, nine SNPs were selected to discriminate between varieties by selecting SNPs specific to each variety. We subsequently created a decision tree capable of cross-verifying each variety and classifying the varieties through sequential analysis. Restriction fragment length polymorphism (RFLP) was used for SNP867 and SNP9183 to differentiate between the varieties of Daehwang and Goldensilk and between Kumkang and Daebak, respectively. A tetra-primer amplification refractory (T-ARMS) mutation was used to analyze the remaining SNPs. As a result, we could isolate the same group or select an individual variety using the nine unique SNPs from SNP780 to SNP9183. Furthermore, nucleotide sequence analysis for the region confirmed that the alleles were identical. In conclusion, our results show that combining SNP analysis of the whole silkworm genome with the decision tree is of high value as a discriminative marker for classifying silkworm varieties.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.