• The Korean Journal of Nuclear Medicine
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• v.35 no.2
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• pp.89-99
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• 2001

Purpose: In this study, we developed a new software tool for the analysis of renal scintigraphy which can be modified more easily by a user who needs to study new clinical applications, and the appropriateness of the results from our program was studied. Materials and Methods: The analysis tool was programmed with IDL5.2 and designed for use on a personal computer running Windows. For testing the developed tool and studying the appropriateness of the calculated glomerular filtration rate (GFR), $^{99m}Tc$-DTPA was administered to 10 adults in normal condition. In order to study the appropriateness of the calculated mean transit time (MTT), $^{99m}Tc-DTPA\;and\;^{99m}Tc-MAG3$ were administered to 11 adults in normal condition and 22 kidneys were analyzed. All the images were acquired with ORBITOR. the Siemens gamma camera. Results: With the developed tool, we could show dynamic renal images and time activity curve (TAC) in each ROI and calculate clinical parameters of renal function. The results calculated by the developed tool were not different statistically from the results obtained by the Siemens application program (Tmax: p=0.68, Relative Renal Function: p:1.0, GFR: p=0.25) and the developed program proved reasonable. The MTT calculation tool proved to be reasonable by the evaluation of the influence of hydration status on MTT. Conclusion: We have obtained reasonable clinical parameters for the evaluation of renal function with the software tool developed in this study. The developed tool could prove more practical than conventional, commercial programs.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.1
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• pp.18-29
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• 2010

Offshore subsurface storage of $CO_2$ is regarded as one of the most promising options to response severe 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 offshore subsurface geological structure such as the depleted gas reservoir and deep sea saline aquifer. Since 2005, we have developed relevant technologies for marine geological storage of $CO_2$. Those technologies include possible storage site surveys and basic designs for $CO_2$ transport and storage processes. To design a reliable $CO_2$ marine geological storage system, we devised a hypothetical scenario and used a numerical simulation tool to study its detailed processes. The process of transport $CO_2$ from the onshore capture sites to the offshore storage sites can be simulated with a thermodynamic equation of state. Before going to main calculation of process design, we compared and analyzed the relevant equation of states. To evaluate the predictive accuracies of the examined equation of states, we compare the results of numerical calculations with experimental reference data. 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, $H_{2}O$, $SO_{\chi}$, $H_{2}S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification and transport processes. This paper analyzes the major design parameters that are useful for constructing onshore and offshore $CO_2$ transport systems. On the basis of a parametric study of the hypothetical scenario, we suggest relevant variation ranges for the design parameters, particularly the flow rate, diameter, temperature, and pressure.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.83-100
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• 2020

This study evaluated the accuracy of soil moisture and evapotranspiration by calculating the hydrological parameters in Korean peninsula using Land Information System(LIS) developed by US NASA. We used Noah-MP surface model to calculate hydrological parameters, and used MERRA2(Modern-Era Retrospective analysis for Research and Applications, Version 2) for hydrological forcing data. And, International Geosphere-Biosphere Program(IGBP) and University of Maryland(UMD) land cover maps were applied to compare the output accuracy, and Automated Synoptic Observing System(ASOS) of KMA was used as ground observation data. In order to evaluate the accuracy of the output data, the correlation coefficient(CC), BIAS, and efficiency factor (NSE, Nash-Sutcliffe Efficiency) were analyzed with soil moisture and evapotranspiration by ASOS ground observation data. As a result, the correlation coefficient of soil moisture using IGBP was 0.56 on average, and evapotranspiration was about 0.71. On the other hand, soil moisture using UMD was 0.68 on average and evapotranspiration was about 0.72, and the correlation coefficient by UMD was evaluated as high accuracy compared to the results by using IGBP. The correlation coefficient of soil moisture was an average of 0.68 and evapotranspiration was an average of 0.72 when MERRA2 was used as hydrological forcing data. On the other hand, the soil moisture applied with ASOS was an average of 0.66, and evapotranspiration was an average of 0.72. It is judged that the ASOS point data was reanalyzed as 0.65°× 0.5°grids, which is the same spatial resolution with MERRA2, resulting in differences in accuracy depending on the region.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.363-371
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• 2023

To construct a ship, blocks of various sizes must be moved and erected . In this process, lugs are used such that they match the block fastening method and various functions suitable for the characteristics of each shipyard facility. The sizes and shapes of the lugs vary depending on the weight and shape of the block structures. The structure is reinforced by welding the doubling pads to compensate for insufficient rigidity around the holes where the shackle is fastened. As for the method of designing lugs according to lifting loading conditions, a simple calculation based on the beam theory and structural analysis using numerical modeling are performed. In the case of the analytical method, a standardized evaluation method must be established because results may differ depending on the type of element and modeling method. The application of this ambiguous methodology may cause serious safety problems during the process of moving and turning-over blocks. In this study , the effects of various parameters are compared and analyzed through numerical structural analysis to determine the modeling conditions and evaluation method that can evaluate the actual structural response of the lug. The modeling technique that represents the plate part and weld bead around the lug hole provides the most realistic behavior results. The modeling results with the same conditions as those of the actual lug where only the weld bead is connected to the main body of the lug, showed a lower ulimated strength compared with the results obtained by applying the MPC load. The two-dimensional shell element is applied to reduce the modeling and analysis time, and a safety working load was verified to be predicted by reducing the thickness of the doubling pad by 85%. The results of the effects of various parameters reviewed in the study are expected to be used as good reference data for the lug design and safe working load prediction.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.8 no.2
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• pp.47-60
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• 1975

For the calculation of population parameter and estimation of recruitment of a fish population, an application of multiple regression method was used with some statistical inferences. Then, the differences between the calculated values and the true parameters were discussed. In addition, this method criticized by applying it to the statistical data of a population of bigeye tuna, Thunnus obesus of the Indian Ocean. The method was also applied to the available data of a population of Pacific saury, Cololabis saira, to estimate its recuitments. A stock at t year and t+1 year is, $N_{0,\;t+1}=N_{0,\;t}(1-m_t)-C_t+R_{t+1}$ where $N_0$ is the initial number of fish in a given year; C, number o: fish caught; R, number of recruitment; and M, rate of natural mortality. The foregoing equation is $$\phi_{t+1}=\frac{(1-\varrho^{-z}{t+1})Z_t}{(1-\varrho^{-z}t)Z_{t+1}}-\frac{1-\varrho^{-z}t+1}{Z_{t+1}}\phi_t-a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}C_t+a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}R_{t+1}......(1)$$ where $\phi$ is CPUE; a', CPUE $(\phi)$ to average stock $(\bar{N})$ in number; Z, total mortality coefficient; and M, natural mortality coefficient. In the equation (1) , the term $(1-\varrho^{-z}t+1)/Z_{t+1}$s almost constant to the variation of effort (X) there fore coefficients $\phi$ and $C_t$, can be calculated, when R is a constant, by applying the method of multiple regression, where $\phi_{t+1}$ is a dependent variable; $\phi_t$ and $C_t$ are independent variables. The values of Mand a' are calculated from the coefficients of $\phi_t$ and $C_t$; and total mortality coefficient (Z), where Z is a'X+M. By substituting M, a', $Z_t$, and $Z_{t+1}$ to the equation (1) recruitment $(R_{t+1})$ can be calculated. In this precess $\phi$ can be substituted by index of stock in number (N'). This operational procedures of the method of multiple regression can be applicable to the data which satisfy the above assumptions, even though the data were collected from any chosen year with similar recruitments, though it were not collected from the consecutive years. Under the condition of varying effort the data with such variation can be treated effectively by this method. The calculated values of M and a' include some deviation from the population parameters. Therefore, the estimated recruitment (R) is a relative value instead of all absolute one. This method of multiple regression is also applicable to the stock density and yield in weight instead of in number. For the data of the bigeye tuna of the Indian Ocean, the values of estimated recruitment (R) calculated from the parameter which is obtained by the present multiple regression method is proportional with an identical fluctuation pattern to the values of those derived from the parameters M and a', which were calculated by Suda (1970) for the same data. Estimated recruitments of Pacific saury of the eastern coast of Korea were calculated by the present multiple regression method. Not only spring recruitment $(1965\~1974)$ but also fall recruitment $(1964\~1973)$ was found to fluctuate in accordance with the fluctuations of stock densities (CPUE) of the same spring and fall, respectively.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.301-308
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• 2018

This study explores an analytical mathematical model designed to estimate the optimal debt ratio of the Korean automobile industry, which has a more significant effect on the national economy than that of other industries, and attempts to estimate the optimal debt ratio based on objective data. The analytical model is based on ROA and ROE which uses the debt ratio as an independent variable and employs ROS, TAT, and NFCL as the related parameters. Regarding the NFCL, the optimal debt ratio is usually defined as the debt ratio that maximizes the ROA and ROE and is calculated using analytical procedures, such as by adding an equation that considers the debt ratio and the linearity relationship to the analytical model. This is because the optimal debt ratio can be calculated reliably by making use of an estimated value within a certain range, which is derived from more than two calculations rather than a single estimation starting from one calculation formula. In this study, for the estimation of the optimal debt ratio, the ROA and ROE are expressed as a quadratic equation with the debt ratio as the independent variable. Using this analysis procedure, the optimal debt ratio obtained using the data from the Korean automobile industry over a sixteen year period, which would optimize the profitability of the Korean automobile industry, was found to be 188% of the debt ratio in the ROA and 213% of the debt ratio in the ROE. This result was obtained by overcoming the problem of the reliability of the estimation value in spite of the limitations of the logical theory of this study, and can be interpreted as meaning that maintaining a debt ratio of 188% to 213% can enhance the profitability and reduce the risks in the Korean automobile industry. Furthermore, this indicates that the existing debt ratio of the Korean automobile industry is lower than the optimal value within the estimated range. Consequently, it is necessary for corporations to change their future debt ratio policies, given that the purpose of debt ratio management is to maintain safety and increase profitability, and to take into account the characteristics of the specific industry.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.1-6
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• 2013

This study was aimed to solve the problems of current national genetic evaluation systems in Korea and its development to pass the verification processes as required by International Bull Evaluation Service (Interbull). This will enable Korea to participate in international genetic evaluation program. A total of 1,416,589 test-day milk records with calving dates used in this study were collected by National Agricultural Cooperative Federation from 2001 to 2009. Parity was limited up to fifth calving and milk production records were adjusted to cumulative 305 day lactation. The pedigree consisted of 2,279,741 animals where 2,467 bulls had 535,409 parents. A newly developed multiple trait model was used in calculation of breeding values for milk yield, milk fat, and protein yield. Data were edited with SAS (version 9.2) and R programs, and genetic parameters were estimated using VCE 6.0. Results showed a continuous increase in genetic potentials, in general, and no remarkable differences were found between performances by parity. Except fat yield, potentials in milk yield and protein yield were well calculated. We found an increased number of daughters per each top ranked 1,000 bulls in recent years of calf births compared to the cases of previous evaluations. Of the bulls ranked top 100 by our new models (multiple-trait models) we found that increased numbers of bulls were included. Of twenty eight bulls born in 2006, twenty bulls born in 2007 and eight bulls born in 2008 that were listed by new models, only 23, 12, and 2 bulls born in respective years were represented on top 100 by old single-trait models. Re-ranking of the daughters or sires by multiple-trait models suggest that this new multiple trait approach should be used for dairy cattle genetic evaluation and seed-stock selection in the future to increase the accuracy of multiple trait selection. Breeding values for these traits should also be calculated by new method for international genetic evaluation.

• Journal of the Korean Society for Marine Environment & Energy
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• v.19 no.4
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• pp.322-331
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• 2016

Oil budget calculator identifies the removal pathways of spilled oil by both natural and response methods, and estimates the remaining oil required response activities. A oil budget calculator was newly developed as a response tool for Deepwater Horizon oil spill incident in Gulf of Mexico in 2010 to inform clean up decisions for Incident Comment System, which was also successfully utilized to media and general public promotion of oil spill response activities. This study analyzed the theoretical background of the oil budget calculator and explored its future application to Korea. The oil budge calculation of four catastrophic marine pollution incidents indicates that 3~8% of spilled oil was removed mechanically by skimmers, 1~5% by in-situ burning, 4.8~16% by chemical dispersion due to dispersant operation, and 37~56% by weathering processes such as evaporation, dissolution, and natural dispersion. The results show that in-situ burning and chemical dispersion effectively remove spilled oil more than the mechanical removal by skimming, and natural weathering processes are also very effective to remove spilled oil. To apply the oil budget calculator in Korea, its parameters need to be optimized in response to the seasonal characteristics of marine environment, the characteristics of spilled oil and response technologies. A new algorithm also needs to be developed to estimate the oil budget due to shoreline cleanup activities. An oil budget calculator optimized in Korea can play a critical role in informing decisions for oil spill response activities and communicating spill prevention and response activities with the media and general public.

• Progress in Medical Physics
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• v.12 no.1
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• pp.41-50
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• 2001

The quantification analysis of renal scintigraphy is strongly affected by the location, shape and size of region of interest(ROI). When ROIs are drawn manually, these ROIs are not reproducible due to the operators' subjective point of view, and may lead to inconsistent results even if the same data were analyzed. In this study, the effect of the ROI variation on the analysis of renal scintigraphy when the ROIs are drawn manually was investigated, and in order to obtain more consistent results, methods for automated ROI definition were developed and the results from the application of the developed methods were analyzed. Relative renal function, glomerular filtration rate and mean transit time were selected as clinical parameters for the analysis of the effect of ROI and the analysis tools were designed with the programming language of IDL5.2. To obtain renal scintigraphy, $^{99m}$Tc-DTPA was injected to the 11 adults of normal condition and to study the inter-operator variability, 9 researchers executed the analyses. The calculation of threshold using the gradient value of pixels and border tracing technique were used to define renal ROI and then the background ROI and aorta ROI were defined automatically considering anatomical information and pixel value. The automatic methods to define renal ROI were classified to 4 groups according to the exclusion of operator's subjectiveness. These automatic methods reduced the inter-operator variability remarkably in comparison with manual method and proved the effective tool to obtain reasonable and consistent results in analyzing the renal scintigraphy quantitatively.