• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.3
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• pp.217-226
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• 2009

Marine geological storage of $CO_2$ is regarded as one of the most promising options to response climate change. Marine geological storage of $CO_2$ is to capture $CO_2$ from major point sources, to transport to the storage sites and to store $CO_2$ into the marine geological structure such as deep sea saline aquifer. Up to now, process design for this $CO_2$ marine geological storage has been carried out mainly on pure $CO_2$. Unfortunately the captured $CO_2$ mixture contains many impurities such as $N_2$, $O_2$, Ar, $H_2O$, $SO_x$, $H_2S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification and transport processes. In order to design a reliable $CO_2$ marine geological storage system, it is necessary to perform numerical process simulation using thermodynamic equation of state. The purpose of the present paper is to compare and analyse the relevant equations of state including PR, PRBM, RKS and SRK equation of state for $CO_2-N_2$ mixture. To evaluate the predictive accuracy of the equation of the state, we compared numerical calculation results with reference experimental data. In addition, optimum binary parameter to consider the interaction of $CO_2$ and $N_2$ molecules was suggested based on the mean absolute percent error. In conclusion, we suggest the most reliable equation of state and relevant binary parameter in designing the $CO_2-N_2$ mixture marine geological storage process.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.381-396
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• 2003

Subsequence matching is an operation that finds subsequences whose changing patterns are similar to a given query sequence from time-series databases. This paper points out the performance bottleneck in subsequence matching, and then proposes an effective method that improves the performance of entire subsequence matching significantly by resolving the performance bottleneck. First, we analyze the disk access and CPU processing times required during the index searching and post processing steps through preliminary experiments. Based on their results, we show that the post processing step is the main performance bottleneck in subsequence matching, and them claim that its optimization is a crucial issue overlooked in previous approaches. In order to resolve the performance bottleneck, we propose a simple but quite effective method that processes the post processing step in the optimal way. By rearranging the order of candidate subsequences to be compared with a query sequence, our method completely eliminates the redundancy of disk accesses and CPU processing occurred in the post processing step. We formally prove that our method is optimal and also does not incur any false dismissal. We show the effectiveness of our method by extensive experiments. The results show that our method achieves significant speed-up in the post processing step 3.91 to 9.42 times when using a data set of real-world stock sequences and 4.97 to 5.61 times when using data sets of a large volume of synthetic sequences. Also, the results show that our method reduces the weight of the post processing step in entire subsequence matching from about 90% to less than 70%. This implies that our method successfully resolves th performance bottleneck in subsequence matching. As a result, our method provides excellent performance in entire subsequence matching. The experimental results reveal that it is 3.05 to 5.60 times faster when using a data set of real-world stock sequences and 3.68 to 4.21 times faster when using data sets of a large volume of synthetic sequences compared with the previous one.

• Resources Recycling
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• v.30 no.6
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• pp.43-52
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• 2021

In this study, the optimal nitration process for selective lithium leaching from powder of a spent battery cell (LiNi_xCo_yMn_zO₂, LiCoO₂) was studied using Taguchi method. The nitration process is a method of selective lithium leaching that involves converting non-lithium nitric compounds into oxides via nitric acid leaching and roasting. The influence of pretreatment temperature, nitric acid concentration, amount of nitric acid, and roasting temperature were evaluated. The signal-to-noise ratio and analysis of variance of the results were determined using L₁₆(4⁴) orthogonal arrays. The findings indicated that the roasting temperature followed by the nitric acid concentration, pretreatment temperature, and amount of nitric acid used had the greatest impact on the lithium leaching ratio. Following detailed experiments, the optimal conditions were found to be 10 h of pretreatment at 700℃ with 2 ml/g of 10 M nitric acid leaching followed by 10 h of roasting at 275℃. Under these conditions, the overall recovery of lithium exceeded 80%. X-ray diffraction (XRD) analysis of the leaching residue in deionized water after roasting of lithium nitrate and other nitrate compounds was performed. This was done to determine the cause of rapid decrease in lithium leaching rate above a roasting temperature of 400℃. The results confirmed that lithium manganese oxide was formed from lithium nitrate and manganese nitrate at these temperatures, and that it did not leach in deionized water. XRD analysis was also used to confirm the recovery of pure LiNO₃ from the solution that was leached during the nitration process. This was carried out by evaporating and concentrating the leached solution through solid-liquid separation.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.1
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• pp.75-79
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• 2019

Purpose Cadmium-zinc-telluride (CZT) camera with semiconductor detector is capable of dynamic myocardial perfusion SPECT for coronary flow reserve (CFR). Image acquisition with the heart positioned within 2 cm in the center of the quality field of view (QFOV) is recommended because the CZT detector based on focused multi-pinhole collimators and is stationary gantry without rotation. The aim of this study was to investigate the optimal method for measuring position of the heart within the center of the QFOV when performing dynamic myocardial perfusion SPECT with the Discovery NM 530c camera. Materials and Methods From June to September 2018, 45 patients were subject to dynamic myocardial perfusion SPECT with D530c. For accurate heart positioning, the patient's heart was scanned with a mobile ultrasound and marked at the top of the probe where the mitral valve (MV) was visible in the parasternal long-axis view (PLAX). And, the marked point on the patient's body matched with the reference point indicated CZT detector in dynamic stress. The heart was positioned to be in the center of the QFOV in rest. The coordinates of dynamic stress and rest were compared statistically. Results The coordinates of the dynamic stress using mobile ultrasound and those taken of the rest were recorded for comparative analysis with regard to the position of the couch and analyzed. There were no statistically significant differences in the coordinates of Table in & out, Table up & down, and Detector in & out (P > 0.05). The difference in distance between the 2 groups was measured at $0.25{\pm}1.00$, $0.24{\pm}0.96$ and $0.25{\pm}0.82cm$ respectively, with no difference greater than 2 cm in all categories. Conclusion The position of the heart taken using mobile ultrasound did not differ significantly from that of the center of the QFOV. Therefore, The use of mobile ultrasound in dynamic stress will help to select the correct position of the heart, which will be effective in clinical diagnosis by minimizing the image quality improvement and the patient's exposure to radiation.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1465-1483
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• 2020

Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.

• Clean Technology
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• v.28 no.4
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• pp.309-315
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• 2022

Research was conducted to derive the optimal operation conditions and the optimal cathode for using a DSA electrode as an anode to minimize electrode consumption during the removal of nitrogen from wastewater by the electro-chemical method. Of the various electrodes tested as cathodes, brass was determined to be the optimal electrode. It had the highest NO₃-N removal rate and the lowest concentration of residual NH₃-N, a by-product when Cl is present in the solution. Investigating the effect of current density found that when the initial concentration of NO₃-N was 50 mg L^-1, the optimal current density was 15 mA cm^-2. In addition, current densities above 15 mA cm^-2 did not significantly affect the NO₃-N removal rate. The effect of electrolytes on removing NO₃-N and minimizing NH₃-N was investigated by using Na₂SO₄ and NaCl as electrolytes and varying the reaction times. When Na₂SO₄ and NaCl are mixed at a ratio of 1.0 g L^-1 to 0.5 g L^-1 and reacted for 90 min at a current density of 15 mA cm^-2 and an initial NO₃-N concentration of 50 mg L^-1, the removal rate of NO₃-N was about 48% and there was no residual NH₃-N. On the other hand, when using only 1.5 g L^-1 of NaCl as an electrolyte, the removal rate of NO₃-N was the highest at about 55% and there was no residual NH₃-N.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.993-1003
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• 2023

Due to the increasing greenhouse gas emissions, the global mean temperature has risen by 1.1℃ compared to pre-industrial levels, and significant changes are expected in functioning of water supply systems. In this study, we assessed impacts of climate change and instreamflow management on water supply reliability in the Geum River basin, Korea. We proposed univariate climate response functions, where mean precipitation and potential evaporation were coupled as an explanatory variable, to assess impacts of climate stress on multiple water supply reliabilities. To this end, natural streamflows were generated in the 19 sub-basins with the conceptual GR6J model. Then, the simulated streamflows were input into the Water Evaluation And Planning (WEAP) model. The dynamic optimization by WEAP allowed us to assess water supply reliability against the 2020 water demand projections. Results showed that when minimizing the water shortage of the entire river basin under the 1991-2020 climate, water supply reliability was lowest in the Bocheongcheon among the sub-basins. In a scenario where the priority of instreamflow maintenance is adjusted to be the same as municipal and industrial water use, water supply reliability in the Bocheongcheon, Chogang, and Nonsancheon sub-basins significantly decreased. The stress tests with 325 sets of climate perturbations showed that water supply reliability in the three sub-basins considerably decreased under all the climate stresses, while the sub-basins connected to large infrastructures did not change significantly. When using the 2021-2050 climate projections with the stress test results, water supply reliability in the Geum River basin was expected to generally improve, but if the priority of instreamflow maintenance is increased, water shortage is expected to worsen in geographically isolated sub-basins. Here, we suggest that the climate response function can be established by a single explanatory variable to assess climate change impacts of many sub-basin's performance simultaneously.

• Journal of radiological science and technology
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• v.31 no.4
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• pp.401-406
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• 2008

The aim of this study is to evaluate contra-lateral breast (CLB) surface dose in Field-in-Field (FIF) technique for breast conserving surgery patients. For evaluation of surface dose in FIF technique, we have compared with other techniques, which were open fields (Open), metal wedge (MW), and enhanced dynamic wedge (EDW) techniques under same geometrical condition and prescribed dose. The three dimensional treatment planning system was used for dose optimization. For the verification of dose calculation, measurements using MOSFET detectors with Anderson Rando phantom were performed. The measured points for four different techniques were at the depth of 0cm (epidermis) and 0.5cm bolus (dermis), and spacing toward 2cm, 4cm, 6cm, 8cm, 10cm apart from the edge of tangential medial beam. The dose calculations were done in 0.25cm grid resolution by modified Batho method for inhomogeneity correction. In the planning results, the surface doses were differentiated in the range of $19.6{\sim}36.9%$, $33.2{\sim}138.2%$ for MW, $1.0{\sim}7.9%$, $1.6{\sim}37.4%$ for EDW, and for FIF at the depth of epidermis and dermis as compared to Open respectively. In the measurements, the surface doses were differentiated in the range of $11.1{\sim}71%$, $22.9{\sim}161%$ for MW, $4.1{\sim}15.5%$, $8.2{\sim}37.9%$ for EDW, and 4.9% for FIF at the depth of epidermis and dermis as compared to Open respectively. The surface doses were considered as underestimating in the planning calculation as compared to the measurement with MOSFET detectors. Was concluded as the lowest one among the techniques, even if it was compared with Open method. Our conclusion could be stated that the FIF technique could make the optimum dose distribution in Breast target, while effectively reduce the probability of secondary carcinogenesis due to undesirable scattered radiation to contra-lateral breast.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.379-385
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• 2017

This study identifies the optimal tube voltages depending on the changes in the patient's body type for limb tests using a digital radiography (DR) system. For the upper-limp test, the dose area product (DAP) was fixed at $5.06dGy{\ast} cm^2$, and for the lower-limb test, the DAP was fixed at $5.04dGy{\ast} cm^2$. Afterwards, the tube voltage was changed to four different stages and the images were taken three times at each stage. The thickness of the limbs was increased by 10 mm to 30 mm to change in the patient's body type. For a quantitative evaluation, Image J was used to calculate the contrast to noise ratio (CNR) and signal to noise ratio (SNR) among the four groups, according to the tube voltage. For statistical testing, the statistically significant differences were analyzed through the Kruskal-Wallis test at a 95% confidence level. For the qualitative analysis of the images, the pre-determined items were evaluated based on a 5-point Likert scale. In both upper-limb and lower-limb tests, the more the tube voltage increased, the more the CNR and SNR of the images decreased. The test on the changes depending on the patient's body shape showed that the more the thickness increased, the more the CNR and SNR decreased. In the qualitative evaluation on the upper limbs, the more the tube voltage increased, the more score increased to 4.6 at the maximum of 55kV and 3.6 at 40kV, respectively. The mean score for the lower limbs was 4.4, regardless of the tube voltage. The more either the upper or lower limbs got thicker, the more the score generally decreased. The score of the upper limps sharply dropped at 40kV, whereas that of the lower limps sharply dropped at 50kV. For patients with a standard thickness, the optimized images can be obtained when taken at 45kV for the upper limbs, and at 50kV for the lower limbs. However, when the thickness of the patient's limbs increases, it is best to set the tube voltage at 50 kV for the upper limbs and at 55 kV for the lower limbs.