• Economic and Environmental Geology
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• v.54 no.1
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• pp.49-60
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• 2021

The Geumhwa Au-Ag deposit is located within the Cretaceous Gyeongsang basin. Mineral paragenesis can be divided into two stages (stage I and II) by major tectonic fracturing. Stage II is economically barren. Stage I, at which the precipitation of major ore minerals occurred, is further divided into three substages(early, middle and late) with paragenetic time based on minor fractures and discernible mineral assemblages: early substage, marked by deposition of pyrite with minor wolframite; middle substage, characterized by introduction of electrum and base-metal sulfides with Cu-As and/or Cu-Sb sulfosalts; late substage, marked by hematite and Bi-sulfosalts with secondary minerals. Changes in vein mineralogy reflect decreases in temperature and sulfur fugacity with a concomitant increase in oxygen fugacity. Fluid inclusion data indicate progressive decreases in temperature and salinity within each substage with increasing paragenetic time. During the early portion of stage I, high-temperature (≥410℃), high-salinity fluids (up to ≈44 equiv. wt. % NaCl) formed by condensation during decompression of a magmatic vapor phase. During waning of early substage, high-temperature, high-salinity fluids gave way to progressively cooler, more dilute fluids associated with main Au-Ag mineralization (middle) and finally to ≈180℃ and ≥0.7 equiv. wt. % NaCl fluids associated with hematite and sulfosalts (± secondary) mineralization (late substage). These trends are interpreted to indicate progressive mixing of high- and medium to low-salinity hydrothermal fluids with cooler, more dilute, oxidizing meteoric waters. The Geumhwa Au-Ag deposit may represent a vein-type system transitional between porphyry-type and epithermal-type.

• Korean Journal of Optics and Photonics
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• v.33 no.4
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• pp.167-176
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• 2022

Adaptive optics (AO) systems compensate for atmospheric disturbance, especially phase distortion, by introducing counter-wavefront deformation calculated from real-time wavefront sensing or prediction. Because AO system implementations are time-consuming and costly, it is highly desirable to estimate the system's performance during the development of the AO system or its parts. Among several techniques, we mostly apply statistical analysis, computational simulation, and optical-bench tests. Statistical analysis estimates performance based on the sum of performance variances due to all design parameters, but ignores any correlation between them. Computational simulation models every part of an adaptive optics system, including atmospheric disturbance and a closed loop between wavefront sensor and deformable mirror, as close as possible to reality, but there are still some differences between simulation models and reality. The optical-bench test implements an almost identical AO system on an optical bench, to confirm the predictions of the previous methods. We are currently developing an AO system for a 1.6-m ground telescope using a deformable mirror that was recently developed in South Korea. This paper reports the results of the statistical analysis and computer simulation for the system's design and confirmation. For the analysis, we apply the Strehl ratio as the performance criterion, and the median seeing conditions at the Bohyun observatory in Korea. The statistical analysis predicts a Strehl ratio of 0.31. The simulation method similarly reports a slightly larger value of 0.32. During the study, the simulation method exhibits run-to-run variation due to the random nature of atmospheric disturbance, which converges when the simulation time is longer than 0.9 seconds, i.e., approximately 240 times the critical time constant of the applied atmospheric disturbance.

• Proceedings of the Mineralogical Society of Korea Conference
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• 2001.06a
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• pp.38-39
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• 2001

The seasonal changes in pH, Fe, Al and SO$_4$$\^$2-/ contents of acid drainage released from coal mine dumps play a major role in precipitation of metal hydroxides in the Taebaek coal field area, southeastern Korea. Precipitates in the creeks underwent a cycle of the color change showing white, reddish brown and brownish yellow, which depends on geochemical factors of the creek waters. White precipitates consist of Al-sulfate (basaluminite and hydrobasaluminite) and reddish brown ones are composed of ferrihydrite and brownish yellow ones are of schwertmannite. Goethite coprecipitates with ferrihydrite and schwertmannite. Ferrihydrite formed at higher values than pH 5.3 and schwertmannite precipitated below pH 4.3, and goethite formed at the intermediate pH range between the two minerals. With the pH being increased from acid to intermediate regions, Fe is present both as schwertmannite and goethite. From the present observation, the most favorable pH that basauluminte can precipitate is in the range of pH 4.45-5.95. SEM examination of precipitates at stream bottom shows that they basically consist of agglomerates of spheroid and rod-shape bacteria. Bacteria species are remarkably different among bottom precipitates and, to a less extent, there are slightly different chemical compositions even within the same bacteria. The speciation and calculation of the mineral saturation index were made using MINTEQA2. In waters associated with yellowish brown precipitates mainly composed of schwertmannite, So$_4$ species is mostly free So$_4$$\^$2-/ ion with less AlSo$_4$$\^$+/, CaSo$\sub$(aq)/, and MgSo$\sub$4(aq)/. Ferrous iron is present mostly as free Fe$\^$2+/, and FeSo$\sub$4(aq)/ and ferric iron exists predominantly as Fe(OH)$_2$$\^$+/, with less FeSo$\sub$4(aq)/, Fe(OH)$_2$$\^$-/, FeSo$_4$$\^$-/ and Fe$\^$3+/, respectively Al exists as free Al$\^$3+/, AlOH$_2$$\^$-/, (AlSo$_4$)$\^$+/, and Al(So$_4$)$\^$2-/. Fe is generally saturated with respect to hematite, magnetite, and goethite, with nearly saturation with lepidocrocite. Aluminum and sulfate are supersaturated with respect to predominant alunite and less jubanite, and they approach a saturation state with respect to diaspore, gibbsite, boehmite and gypsum. In the case of waters associated with whitish precipitates mainly composed of basaluminite, Al is present as predominant Al$\^$3+/ and Al(SO$_4$)$\^$+/, with less Al(OH)$\^$2+/, Al(OH)$_2$$\^$+/ and Al(SO$_4$)$\^$2-/. According to calculation for the mineral saturation, aluminum and sulfate are greatly supersaturated with respect to basaluminite and alunite. Diaspore is flirty well supersaturated while jubanite, gibbsite, and boehmite are already supersaturated, and gypsum approaches its saturation state. The observation that the only mineral phase we can easily detect in the whitish precipitate is basaluminite suggests that growth rate of alunite is much slower than that of basaluminite. Neutralization of acid mine drainage due to the dilution caused by the dilution effect due to mixing of unpolluted waters prevails over the buffering effect by the dissolution of carbonate or aluminosilicates. The main factors to affect color change are variations in aqueous geochemistry, which are controlled by dilution effect due to rainfall, water mixng from adjacent creeks, and the extent to which water-rock interaction takes place with seasons. pH, Fe, Al and SO$_4$ contents of the creek water are the most important factors leading to color changes in the precipitates. A geochemical cycle showing color variations in the precipitates provides the potential control on acid mine drainage and can be applied as a reclamation tool in a temperate region with four seasons.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.2
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• pp.1-10
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• 2023

This study aims to explore the significance of historic changes and cultural characteristics of landscape architecture in Korean Seowon. Seowon refers to educational private institutes that also served as Confucian shrines and were prevalent during the mid-to-late Joseon dynasty. Seowon comprised three distinct functional spaces: a shrine, a school, and a garden. The concept of Seowon's garden extended beyond designed landscapes to include the surrounding natural environment. The importance of landscape architecture in Seowon is rooted in its connection to the educational philosophy of these institutes. During the Joseon dynasty, scholars revered nature as a manifestation of Confucian ideals, and they believed that close engagement with nature was integral to self-discipline and learning. This research investigated fifteen relatively well-preserved garden in South Korea and conducted a comprehensive analysis of their gardens. The analysis revealed two key findings. Firstly, gardens in Seowon were actively designed and constructed during the early phase of Seowon culture but gradually diminished after the 17th century. This can be attributed to the shift in Seowon's purpose, with a greater emphasis on its religious function over education. Consequently, the significance and presence of landscape architecture in Seowon, which was closely related with its Confucianist education, declined. Secondly, the study explored the historical backgrounds of each Seowon's landscape architecture and found that many of them were designed or influenced by individuals who were later memorialized and deified in the Seowon's shrines. The landscape architecture created by these predecessors was carefully preserved by the faculties and students as a form of respect. Therefore, landscape architecture in Korean Seowon not only conveys the institutional purpose as an educational hub for the local society but also reflects the institute's strong relationship with the figures they worship as shrines.

• Journal of Gastric Cancer
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• v.23 no.2
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• pp.315-327
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• 2023

Purpose: Oxaliplatin, a component of the capecitabine plus oxaliplatin (XELOX) regimen, has a more favorable toxicity profile than cisplatin in patients with advanced gastric cancer (GC). However, oxaliplatin can induce sensory neuropathy and cumulative, dose-related toxicities. Thus, the capecitabine maintenance regimen may achieve the maximum treatment effect while reducing the cumulative neurotoxicity of oxaliplatin. This study aimed to compare the survival of patients with advanced GC between capecitabine maintenance and observation after 1st line XELOX chemotherapy. Materials and Methods: Sixty-three patients treated with six cycles of XELOX for advanced GC in six hospitals of the Catholic University of Korea were randomized 1:1 to receive capecitabine maintenance or observation. The primary endpoint was progression-free survival (PFS), analyzed using a two-sided log-rank test stratified at a 5% significance level. Results: Between 2015 and 2020, 32 and 31 patients were randomized into the maintenance and observation groups, respectively. After randomization, the median number of capecitabine maintenance cycles was 6. The PFS was significantly higher in the maintenance group than the observation group (6.3 vs. 4.1 months, P=0.010). Overall survival was not significantly different between the 2 groups (18.2 vs. 16.5 months, P=0.624). Toxicities, such as hand-foot syndrome, were reported in some maintenance group patients. Maintenance treatment was a significant factor associated with PFS in multivariate analysis (hazard ratio, 0.472; 95% confidence interval, 0.250-0.890; P=0.020). Conclusions: After 6 cycles of XELOX chemotherapy, capecitabine maintenance significantly prolonged PFS compared with observation, and toxicity was manageable. Maintenance treatment was a significant prognostic factor associated with PFS.

• Resources Recycling
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• v.32 no.1
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• pp.42-49
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• 2023

The glass ceramic secondary resource containing Li-Al-Si is used in inductor, fireproof glass, and transparent cookware and accounts for 14% of the total consumption of Li, which is the second most widely used after Li-ion batteries. Therefore, new Li resources should be explored when the demand for Li is exploding, and extensive research on Li recovery is needed. Herein, we recovered Li from fireproof Li-Al-Si glass ceramic, which is a new secondary resource containing Li. The fireproof glass among all Li-Al-Si glass ceramics was used as raw material that contained 1.5% Li, 9.4% Al, and 28.9% Si. The process for recovering Li from the fireproof glass was divided into two parts: (1) calcium salt roasting and (2) water leaching. In calcium salt roasting, a sample of fireproof glass was crushed and ground below 325 mesh. The leaching efficiency was compared based on the presence or absence of heat treatment of the fireproof glass. Moreover, the leaching rates based on the input ratios of calcium salt, Li-Al-Si glass, and ceramics and the leaching process based on calcium salt roasting temperatures were compared. In water leaching, the leaching and recovery rates of Li based on different temperatures, times, solid-liquid ratios, and number of continuous leaching stages were compared. The results revealed that fireproof glass ceramics containing Li-Al-Si should be heat treated to change phase to beta-type spodumene. CaCO₃ salt should be added at a ratio of 6:1 with glass ceramics containing Li-Al-Si, and then leached 4 times or more to achieve a recovery efficiency of Li over 98% from a solution containing 200 mg/L of Li.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.35-44
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• 2024

Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.

• Sim-seong Yeon-gu
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• v.38 no.2
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• pp.269-304
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• 2023

The purpose of this paper is to present the psychological meaning of the creation myths by utilizing related myths, analysand's dreams, active imagination, and artwork to reveal the creative function of the unconscious. The creation myth is the phenomenon of projection when a new order is demanded in the chaotic phase of personal and human history. Depending on the attitude of the ego, it can be a sign of a reconstruction/alteration of consciousness or an invasion. Related literature such as Jung, von Franz, Neumann, Harding, and Edinger, domestic papers, and case reports are introduced to identify the background for this research. The psychological meaning of 'darkness' in creation myths is regarded as unconscious that is too dark to see. The Eskimo creation myth and an analysand's dreams of being blind and wandering in darkness are discussed in relation to nigredo in Alchemy. The psychological meaning of 'massa confusa' regards Uroboros, pleroma, early childhood experience, and a psychological womb in which everything is contained in one. With related myths and unconscious materials, a discussion is followed on how this realm can be a precursor of creation but also be trapped in an abyss. The psychological meaning of 'separation of world parent' is related to splitting one into two when unconscious contexts were touched before it became consciousness. Related myths, 'the world created between heaven and earth,' 'celestial being descending to the earth,' and 'the legend of relocation of a mountain,' as well as clinical material, are examined. Then this paper discusses the clinical implications of the separation of heaven and earth occurring on its own, that the creator's emotional aspects, such as loneliness and anxiety, are involved, and that delayed separation leads to the death of creatura and sudden separation leads to the death of the chaos. Then, the meaning of 'separation of world parent' is discussed in relation with separatio, the alchemical process of acquiring light/consciousness from darkness/unconsciousness. The psychological meaning of the creation of 'land/island' refers to the emergence of consciousness, the contents of the unconscious material into the realm of the ego. Related myths, such as the 'body of the monster/dragon becoming land' and analysand's dreams, are introduced, referring to the embodiment of Mercurius. This is followed by discussing related myths in creating the land to coagulatio in alchemy and utilizing creative work such as active imagination, art, music, and dance that can coagulate or concretize unconscious material in clinical approaches. Finally, myths of resurfaced land after the Flood or the complete destruction of the world in relation to the reconstruction of ego are discussed with related clinical material to show the importance of the analyst/therapist/supervisor's mental stability and capacity.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

• Applied Biological Chemistry
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• v.16 no.2
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• pp.99-111
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• 1973

Percentage recovery or fertilizer nitrogen, phosphorus and potassium by rice plant(Oriza sativa L.) were investigated at 8, 10, 12, 14 kg/10a of N, 6 kg of $P_2O_5$ and 8 kg of $K_2O$ application level in 1967 (51 places) and 1968 (32 places). Two types of nutrient contribution for the yield, that is, P type in which phosphorus firstly increases silicate uptake and secondly silicate increases nitrogen uptake, and K type in which potassium firstly increases P uptake and secondly P increases nitrogen uptake were postulated according to the following results from the correlation analyses (linear) between percentage recovery of fertilizer nutrient and grain or dry matter yields and nutrient uptake. 1. Percentage frequency of minus or zero recovery occurrence was 4% in nitrogen, 48% in phosphorus and 38% in potassium. The frequency distribution of percentage recovery appeared as a normal distribution curve with maximum at 30 to 40 recovery class in nitrogen, but appeared as a show distribution with maximum at below zero class in phosphorus and potassium. 2. Percentage recovery (including only above zero) was 33 in N (above 10kg/10a), 27 in P, 40 in K in 1967 and 40 in N, 20 in P, 46 in Kin 1968. Mean percentage recovery of two years including zero for zero or below zero was 33 in N, 13 in P and 27 in K. 3. Standard deviation of percentage recovery was greater than percentage recovery in P and K and annual variation of CV (coefficient of variation) was greatest in P. 4. The frequency of significant correlation between percentage recovery and grain or dry matter yield was highest in N and lowest in P. Percentage recovery of nitrogen at 10 kg level has significant correlation only with percentage recovery of P in 1967 and only with that of potassium in 1968. 5. The correlation between percentage recovery and dry matter yield of all treatments showed only significant in P in 1967, and only significant in K in 1968, Negative correlation coefficients between percentage recovery and grain or dry matter yield of no or minus fertilizer plots were shown only in K in 1967 and only in P in 1968 indicating that phosphorus fertilizer gave a distinct positive role in 1967 but somewhat' negative role in 1968 while potassium fertilizer worked positively in 1968 but somewhat negatively in 1967. 6. The correlation between percentage recovery of nutrient and grain yield showed similar tendency as with dry matter yield but lower coefficients. Thus the role of nutrients was more precisely expressed through dry matter yield. 7. Percentage recovery of N very frequently had significant correlation with nitrogen uptake of nitrogen applied plot, and significant negative correlation with nitrogen uptake of minus nitrogen plot, and less frequently had significant correlation with P, K and Si uptake of nitrogen applied plot. 8. Percentage recovery of P had significant correlation with Si uptake of all treatments and with N uptake of all treatments except minus phosphorus plot in 1967 indicating that phosphorus application firstly increases Si uptake and secondly silicate increases nitrogen uptake. Percentage recovery of P also frequently had significant correlation with P or K uptake of nitrogen applied plot. 9. Percentage recovery of K had significant correlation with P uptake of all treatments, N uptake of all treatments except minus phosphorus plot, and significant negative correlation with K uptake of minus K plot and with Si uptake of no fertilizer plot or the highest N applied plot in 1968, and negative correlation coefficient with P uptake of no fertilizer or minus nutrient plot in 1967. Percentage recovery of K had higher correlation coefficients with dry matter yield or grain yield than with K uptake. The above facts suggest that K application firstly increases P uptake and secondly phosphorus increases nitrogen uptake for dry matter yied. 10. Percentage recovery of N had significant higher correlation coefficient with grain yield or dry matter yield of minus K plot than with those of minus phosphorus plot, and had higher with those of fertilizer plot than with those of minus K plot. Similar tendency was observed between N uptake and percentage recovery of N among the above treatments. Percentage recovery of K had negative correlation coefficient with grain or-dry matter yield of no fertilizer plot or minus nutrient plot. These facts reveal that phosphorus increases nitrogen uptake and when phosphorus or nitrogen is insufficient potassium competatively inhibits nitrogen uptake. 11. Percentage recovery of N, Pand K had significant negative correlation with relative dry matter yield of minus phosphorus plot (yield of minus plot x 100/yield of complete plot; in 1967 and with relative grain yield of minus K plot in 1968. These results suggest that phosphorus affects tillering or vegetative phase more while potassium affects grain formation or Reproductive phase more, and that clearly show the annual difference of P and K fertilizer effect according to the weather. 12. The correlation between percentage recovery of fertilizer and the relative yield of minus nutrient plat or that of no fertilizer plot to that of minus nutrient plot indicated that nitrogen is the most effective factor for the production even in the minus P or K plot. 13. From the above facts it could be concluded that about 40 to 50 percen of paddy fields do rot require P or K fertilizer and even in the case of need the application amount should be greatly different according to field and weather of the year, especially in phosphorus.