• Journal of the Korean Society of Radiology
• /
• v.85 no.1
• /
• pp.171-183
• /
• 2024

Purpose This study aimed to investigate which indirect parameters on preoperative MRI were the principal predictors of subscapularis tendon tears (STTs) requiring surgical repair. Materials and Methods Preoperative MRI scans of 86 patients were retrospectively reviewed for visual assessment of the STT, pathology of the long head of the biceps tendon (LHBT), posterior decentering (PD) of the humeral head, humeral rotation, fatty degeneration, and subscapularis muscle atrophy. To evaluate atrophy, visual grading using the anatomical line connecting the coracoid tip to the glenoid base, designated as the base-to-tip line (BTL), and thickness measurements were performed in the en-face view. Results Arthroscopically, 31 patients (36%) exhibited Lafosse type III or IV STT and underwent surgical repair. LHBT pathology (p = 0.002), PD of the humeral head (p = 0.012), fatty degeneration (p < 0.001), and BTL grade (p = 0.003) significantly correlated with STT. In the multivariate analysis, PD of the humeral head (p = 0.011, odds ratio [OR] = 5.14) and fatty degeneration (p = 0.046, OR = 2.81) were independent predictors of STT. Conclusion PD of the humeral head and fatty degeneration of the subscapularis can help to diagnose clinically significant STT. Interpretation of these findings may contribute to the planning of an optimal surgical strategy.

• The Korean Journal of Applied Statistics
• /
• v.37 no.3
• /
• pp.339-353
• /
• 2024

In cases where the response variable in proportional data is confined to a limited interval, a regression model based on the assumption of normality can yield inaccurate results due to issues such as asymmetry and heteroscedasticity. In such cases, the beta regression model can be considered as an alternative. This model reparametrizes the beta distribution in terms of mean and precision parameters, assuming that the response variable follows a beta distribution. This allows for easy consideration of heteroscedasticity in the data. In this paper, we therefore aim to analyze proportional data using the beta regression model in two empirical analyses. Specifically, we investigate the relationship between smoking rates and coffee consumption using data from the 6th National Health Survey, and examine the association between regional characteristics in the U.S. and cumulative mortality rates based on COVID-19 data. In each analysis, we apply the ordinary least squares regression model, the beta regression model, and the extended beta regression model to analyze the data and interpret the results with the selected optimal model. The results demonstrate the appropriateness of applying the beta regression model and its extended version in proportional data.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.30 no.4
• /
• pp.365-372
• /
• 2024

The South Korean marine industry is emerging as a significant market, driven by the growing popularity of various water leisure activities, including sailing. This trend suggests a rising demand for sailing yachts. Consequently, since 2022, the design and development of a 28ft sailing yacht have been ongoing, supported by the government and the Ministry of Oceans and Fisheries, to promote yachting culture in South Korea. The Velocity Prediction Program (VPP) analysis was conducted using WinDesign during the preliminary design stage to evaluate performance and determine design parameters. The hydrodynamic model used for this vessel is based on regression methods developed from years of experience in naval architecture and yacht research at the Wolfson Unit, providing reliable estimates for most modern yachts. However, owing to the lack of specific hydrodynamic data from towing tank tests or CFD numerical analysis, verification of the hydrodynamic model has faced some challenges. Additionally, an incomplete weight estimate resulted in variable VCG values, potentially affecting stability and overall performance. The optimal boat speed for this vessel was determined at true wind speeds (TWS) of 4, 8, 12, 16, and 20 knots, using both the jib (up to 120° TWA) and the spinnaker (from 80° TWA). The optimized speed of the yacht was found to be comparable to that of international similar-class yachts.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.1-32
• /
• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.25 no.3
• /
• pp.147-153
• /
• 2013

There exist various types of the WEC (Wave Energy Converter), and among them, the point absorber is the most popularly investigated type. However, it is difficult to find examples of systematically measured data analysis for the design of the point absorber type of power buoy in the world. The study investigates the wave load acting on the point absorber type resonance power buoy wave energy extraction system proposed by Kweon et al. (2010). This study analyzes the time series spectra with respect to the three-year wave data (2002.05.01~2005.03.29) measured using the pressure type wave gage at the seaside of north breakwater of Hupo harbor located in the east coast of the Korean peninsula. From the analysis results, it could be deduced that monthly wave period and wave height variations were apparent and that monthly wave powers were unevenly distributed annually. The average wave steepness of the usual wave was 0.01, lower than that of the wind wave range of 0.02-0.04. The mode of the average wave period has the value of 5.31 sec, while mode of the wave height of the applicable period has the value of 0.29 m. The occurrence probability of the peak period is a bi-modal type, with a mode value between 4.47 sec and 6.78 sec. The design wave period can be selected from the above four values of 0.01, 5.31, 4.47, 6.78. About 95% of measured wave heights are below 1 m. Through this study, it was found that a resonance power buoy system is necessary in coastal areas with low wave energy and that the optimal design for overcoming the uneven monthly distribution of wave power is a major task in the development of a WEF (Wave Energy Farm). Finding it impossible to express the average spectrum of the usual wave in terms of the standard spectrum equation, this study proposes a new spectrum equation with three parameters, with which basic data for the prediction of the power production using wave power buoy and the fatigue analysis of the system can be given.

• Radiation Oncology Journal
• /
• v.19 no.2
• /
• pp.199-204
• /
• 2001

Purpoe : To find the optimal values of total arc degree to protect the normal brain tissue from high dose radiation in stereotactic radiotherapy planning. Methods and Materials : With Xknife-3 planning system & 4 MV linear accelerator, the authors planned under various values of parameters. One isocenter, 12, 20, 30, 40, 50, and 60 mm of collimator diameters, $100^{\circ},\;200^{\circ},\;300^{\circ},\;400^{\circ}C,\;500^{\circ},\;600^{\circ}$ or total arc degrees, and $30^{\circ}\;or\;45^{\circ}$ or arc intervals were used. After the completion of planning, the plans were compared each other using $V_{50}$ (the volume of normal brain that is delivered high dose radiation) and integral biologically effective dose. Results : At $30^{\circ}$ of arc interval, the values of $V_{50}$ had the decreased pattern with the increase of total arc degree in any collimator diameter. At 45 arc interval, up to $400^{\circ}$ of total arc degree, the values of $ V_{50}$ decreased with the increase of total arc degree, but at $500^{\circ}\;and\;600^{\circ}$ of total arc degrees, the values increased. At $30^{\circ}$ of arc interval, integral biologically effective dose showed the decreased pattern with the increase of total arc degree in any collimator diameter. At $45^{\circ}$ arc interval with less than 40 mm collimator diameter, the integral biologically effective dose decreased with the increase of total arc degree, but with n and n mm or collimator diameters, up to $400^{\circ}$ or total arc degree, integral biologically effective dose decreased with the increase of total arc degree, but at $500^{\circ}\;and\;600^{\circ}$ of total arc degrees, the values increased. Conclusion : In the stereotactic radiotherapy planning for brain lesions, planning with $400^{\circ}$ of total arc degree is optimal. Especially, when the larger collimator more than 50 mm diameter should be used, the uses of $500^{\circ}\;and\;600^{\circ}$ of total arc degrees make the increase of$V_{50}$ and integral biologically effective dose. Therefore stereotactic radiotherapy planning using $400^{\circ}$ of total arc degree can increase the therapeutic ratio and produce the effective outcome in the management of personal and mechanical sources in radiotherapy department.

• Radiation Oncology Journal
• /
• v.24 no.4
• /
• pp.285-293
• /
• 2006

$\underline{Purpose}$: This study was to search the optimal slice thickness of computed tomography (CT) in an intensity modulated radiation therapy plan through changing the slice thickness and comparing the change of the calculated absorbed dose with measured absorbed dose. $\underline{Materials\;and\;Methods}$: An intensity modulated radiation therapy plan for a head and neck cancer patient was done, first of all. Then CT with various ranges of slice thickness ($0.125{\sim}1.0\;cm$) for a head and neck anthropomorphic phantom was done and the images were reconstructed. The plan parameters obtained from the plan of the head and neck cancer patient was applied into the reconstructed images of the phantom and then absorbed doses were calculated. Films were inserted into the phantom, and irradiated with 6 MV X-ray with the same beam data obtained from the head and neck cancer patient. Films were then scanned and isodoses were measured with the use of film measurement software and were compared with the calculated isodeses. $\underline{Results}$: As the slice thickness of CT decreased, the volume of the phantom and the maximum absorbed dose increased. As the slice thickness of CT changed from 0.125 to 1.0 cm, the maximum absorbed dose changed ${\sim}5%$. The difference between the measured and calculated volume of the phantom was small ($3.7{\sim}3.8%$) when the slice thickness of CT was 0.25 cm or less. The difference between the measured and calculated dose was small ($0.35{\sim}1.40%$) when the slice thickness of CT was 0.25 cm or less. $\underline{Conclusion}$: Because the difference between the measured and calculated dose in a head and neck phantom was small and the difference between the measured and calculated volume was small when the slice thickness of CT was 0.25 cm or less, we suggest that the slice thickness of CT should be 0.25 cm or less for an optimal intensity modulated radiation therapy plan.

• Microbiology and Biotechnology Letters
• /
• v.26 no.5
• /
• pp.435-441
• /
• 1998

Optimal conditions for the production of natural color, betacyanin were investigated by varying light intensity, C/N ratio, concentrations of phosphate and kinds of elicitors. Batch cultivation was employed to characterize cell growth and betacyanin production of 32 days. The maximum specific growth rate, ${\mu}$$\sub$max/, was 0.3 (1/day) for batch cultivation. The maximum specific production rate, q$\^$max/$\sub$p/, was enhanced 0.11 (mg/g-cell/day) at 3 klux. A light intensity of 3 klux was shown to the best for both cell growth and betacyanin production. The maximum specific production rate was 0.125 (mg/g-cell/day) at 0.242 (1/day), the maximum specific growth rate. The dependence of specific growth rate on the light lintensity is fit to the photoinhibition model. The correlation between ${\mu}$ and q$\sub$p/ showed that the product formation parameters, ${\alpha}$ and ${\beta}$$\sub$p/ were 0.3756 (mg/cell) and 0.001 (mg/g-cell/day), respectively. The betacyanin production was partially cell growth related process, which is different from the production of a typical product in plant cell cultures. In C/N ratio experiment, high carbon concentration, 42.1 (w/w) improved cell growth rate while lower concentration, 31.6 (w/w) increased the betacyanin production rate. The ${\mu}$$\sub$max/ and q$\^$max/$\sub$p/ were 0.26 (1/day) and 0.075 (mg/g-cell/day), respectively. Beta vulgaris L. cells under 1.25 mM phosphate concentration produced 10.15 mg/L betacyanin with 13.46 (g-dry wt./L) of maximum cell density. The production of betacyanin was elongated by adding 0.1 ${\mu}$M of kinetin. This also increased the cell growth. Optimum culture conditions of light intensity, C/N, phosphate concentration were obtained as 5.5 klux, 27 (w/w), 1.25 mM, respectively by the response surface methodology. The maximum cell density, X$\sub$max/, and maximum production, P$\sub$max/, in optimized conditions were 16 (g-dry wt./L), 12.5 (mg/L) which were higher than 8 (g-dry wt./L), 4.48 (mg/L) in normal conditions. The ${\mu}$$\sub$max/ and q$\^$max/$\sub$p/ were 0.376 (1/day) and 0.134 (mg/g-cell/day) at the optimal condition. The overall results may be useful in scaling up hairy root cell culture system for commercial production of betacyanin.

• Journal of radiological science and technology
• /
• v.32 no.1
• /
• pp.101-106
• /
• 2009

Purpose of this study is to compare the signal intensity (SI) and CNR with T1 weighted image using FLASH at 3T abdominal MRI by varying flip angle (FA). Totally 20 patients (male : 12, female : 8, Age : $28{\sim}63$ years with mean : 51) were examined by 3 Tesla MR scanner (Magnetom Tim Trio, SIEMENS, Germany) with 8 channel body array coil between september and October 2008. Imaging parameters were as follows : FLASH sequence, TR : 120 ms, TE : minimum, FOV (field of view) : $360{\times}300\;mm$, Matrix : $256{\times}224$, slice : 6 mm, scan time : 15 sec and Breath-hold technique. Abdominal image, with a 50 ml syringe filled with water placed in the FOV measuring the water signal, were acquired with varying FA through $10^{\circ}$ to $90^{\circ}$ with $10^{\circ}$ interval. SI's were measured three times at liver parenchyme, water, spleen and background and averaged. The CNR's were measured between the ROIs (region of interest). Statistic analysis was performed with ANOVA test using SPSS software (version 17.0). Less than FA $30^{\circ}$, abdominal images were severely inhomogeneity. Especially, T1 effect of water signal was weak. As the flip angle increased, the signal intensity decreased at all the regions. Especially, flip angle of the highest signal intensity was observed with $40^{\circ}$ at the liver parenchyme, $20^{\circ}$ at water, $30^{\circ}$ at the spleen, respectively. The CNR between liver and water was -60.92 at FA $10^{\circ}$ and 15.16 at FA $80^{\circ}$. The CNR between liver and spleen was -3.18 at FA $10^{\circ}$ and 9.65 at $80^{\circ}$. In conclusion, FA $80^{\circ}$ is optimal for T1 weighted effect using FLASH pulse sequence at 3.0 T abdominal MRI.

• Journal of the Korean GEO-environmental Society
• /
• v.13 no.5
• /
• pp.5-12
• /
• 2012

Antibiotics have been considered emerging compounds due to their continuous input and persistence in environment. Due to the limited biodegradability and widespread use of these antibiotics, an incomplete removal is attained in conventional wastewater treatment plants and relative large quantities are released into the environment. In this study, it was determined the adsorption and photocatalysis kinetics of antibiotics (Sulfamethoxazole, SMX) with various catalyst (Titanium dioxide; $TiO_2$, Hydroxyapatite; HAP) conditions under UV/$TiO_2$/HAP system. In addition, the statistical analysis of response surface methods (RSM) was used to determine the effects of operating parameters on UV/$TiO_2$/HAP system. $TiO_2$/HAP adsorbent were found to follow the pseudo second order reaction in the adsorption. In the result of applied intrapaticle diffusion model, the constants of reaction rate were $TiO_2$=$0.064min^{-1}$, HAP=$0.2866min^{-1}$ and $TiO_2$/HAP=$0.3708min^{-1}$, respectively.The result of RSM, term of regression analysis in analysis of variance (ANOVA) showed significantly p-value (p<0.05) and high coefficients for determination values($R^2$=96.2%, $R^2_{Adj}$=89.3%) that allowed satisfactory prediction of second order regression model. And the estimated optimal conditions for Y(Sulfamethoxazole removal efficiency, %) were $x_1$(initial concentration of Sulfamethoxazole)=-0.7828, $x_2$(amount of catalyst)=0.9974 and $x_3$(reation time)=0.5738 by coded parameters, respectively. According to the result of intraparticle diffusion model and photocatalysis experiments, it was shown that the $TiO_2$/HAP was more effective system than conventional AOPs(advanced oxidation processes, UV/$TiO_2$ system).