• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.46-46
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• 2011

Severe sediment erosion during floods occur disaster and economic losses, but general sediment erosion is basic mechanism to move sediment from upstream to downstream river. In addition, it is important process to change river form. Check dam, which is constructed in mountain stream, play a vital role such as control of sudden debris flow, but it has negative aspects to river ecosystem. Now a day, check dam of open type is an alternative plan to recover river biological diversity and ecosystem through sediment transport while maintaining the function of disaster control. The purpose of this paper is to verify sediment erosion progress of river bottom and bank as first step for river restoration after dam slit by cross-sectional shear stress and critical shear stress. Study area is upstream reach of slit check dam in mountain stream, named Wasada, in Japan. The check dam was slit with two passages in August, 2010. The transects were surveyed for four upstream cross-sections, 7.4 m, 34 m, 86 m, and 150 m distance from dam in October 2010. Sediment size was surveyed at river bottom and bank. Sediment of cobble size was found at the wetted bottom, and small size particles of sand to medium gravel composed river bank. Discharge was $2.5\;m^3/s$ and bottom slope was 0.027 m/m. Excess shear stress (${\tau}_{ex}$) was calculated for hydraulic erosion by subtracting the values of critical shear stress (${\tau}_{c}$) from the value of shear stress (${\tau}$) at river bottom and bank (${\tau}_{ex}=\tau-{\tau}_c$). Shear stress of river bottom (${\tau}_{bottom}$) was calculated using the cross-sectional shear stress, and bank shear stress (${\tau}_{bank}$) was calculated from the method of Flintham and Carling (1988). $${\tau}_{bank}={\tau}^*SF_{bank}((B+P_{bed})/(2^*P_{bank}))$$ where $SF_{bank}=1.77(P_{bed}/p_{bank}+1.5)^{-1.4}$, B is the water surface width, $P_{bed}$ and $P_{bank}$ are wetted parameter of the bed and bank. Estimated values for ${\tau}_{bottom}$ for a flow of $2.5\;m^3/s$ were lower as 25.0 (7.5 m cross-section), 25.7 (34 m), 21.3 (86 m) and 19.8 (150 m), in N/$m^2$, than critical shear stress (${\tau}_c=62.1\;N/m^2$) with cobble of 64 mm. The values were insufficient to erode cobble sediment. In contrast, even if the values of ${\tau}_{bank}$ were lower than the values for ${\tau}_{bottom}$ as 18.7 (7.5 m), 19.3 (34 m), 16.1 (86 m) and 14.7 (150 m), in N/$m^2$, excess shear stresses were calculated at the three cross-sections of 7.5 m, 34 m, and 86 m distances compare with ${\tau}_c$ is 15.5 N/$m^2$ of 16mm gravel. Bank shear stresses were sufficient for erosion of the medium gravel to sand. Therefore there is potential to erode lateral bank than downward erosion in a flow of $2.5\;m^3/s$. Undercutting of the wetted bank can causes bank scour or collapse, therefore this channel has potential to become wider at the same time. This research is about a potential of sediment erosion, and the result could not verify with real data. Therefore it need next step for verification. In addition an erosion mechanism for river restoration is not simple because discharge distribution is variable by snow-melting or rainy season, and a function for disaster control will recover by big precipitation event. Therefore it needs to consider the relationship between continuous discharge change and sediment erosion.

• Journal of the Korean Society of Radiology
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• v.14 no.1
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• pp.53-60
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• 2020

The purpose of this study is to identify factors affecting picture quality in Roadmap images, which were studied by varying the dilution rate, collimation field and flow rate of contrast medium. For a quantitative evaluation of the quality of the picture, a 3mm vessel model Water Phantom was self-produced using acrylic, a roadmap image was acquired with a self-produced vascular model Water Phantom, and the SNR(Signal to Noise Ratio) and CNR (Contrast to Noise Ratio) were analyzed. CM:N/S In the study on the change of dilution rate, CM:N/S dilution rate changed to (100%~10%:100%), and the measurement of the roadmap image taken using the vascular model Water Phantom showed that the measurement value of SNR gradually decreased as the N/S dilution rate was increased, and the measurement of CNR was gradually reduced. It was confirmed that the higher the dilution rate of CM:N/S, the lower the SNR and CNR, and also significant image can be obtained at the dilution rate of CM:N/S (100%~70:30%). The study showed the value of SNR and CNR in Roadmap image was increased as the Collimation Field was narrowed to the center of the vascular phantom; the Collimation Field was narrowed to the center of the vessel model by 2cm intervals to 0cm through 12cm. To verify the relationship with Roadmap image and Flow Rate, volume of the autoinjector was kept constant at 15 and the flow rate was gradually increased 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. The value of SNR and CNR of images taken by using water Phantom gradually decreased as the Flow Rate increased, but at Flow Rate 9 and 10, the SNR and CNR value was increase. It was not possible to confirm the relationship with SNR and CNR by ROI mean value and Background mean value. It is considered that further study is needed to evaluate the correlation about Roadmap image and Flow Rate. In conclusion, as the dilution rate of N/S in contrast medium was increased, the value of SNR and CNR was decreased. The narrower the Collimation Field, the higher image quality by increasing value of SNR and CNR. However, it is not confirmed the relationship Roadmap image and Flow Rate. It is considered that appropriate contrast medium concentration to minimize the effects of kidney and proper Collimation Field to improve contrast of image and reduce exposure X-ray during procedure is needed.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.17-24
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• 2011

Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.

• Journal of Animal Science and Technology
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• v.50 no.4
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• pp.561-572
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• 2008

Responses of real-time control parameters, such as ORP, DO and pH, to the conditions of biological animal wastewater treatment process were examined to evaluate the stability of real-time control using each parameter. Also an optimum index for supplemental carbon source addition based on NOx-N level was determined under a consideration of denitrification rate by endogenous respiration of microorganism and residual organic matter in liquor. Experiment was performed with lab-scale sequencing batch reactor(SBR) and working volume of the process was 45L. The distinctive nitrogen break point(NBP) on ORP-and DO-time profiles, which mean the termination of nitrification, started disappearing with the maintenance of low NH4-N loading rate. Also the NBP on ORP-and DO-time profiles was no longer observed when high NOx-N was loaded into the reactor, and the sensitivity of ORP became dull with the increase of NOx-N level. However, the distinctive NBP was constantly occurred on pH(mV)-time profile, maintaining unique profile patterns. This stable occurrence of NBP on pH(mV)-time profile was lasted even at very high NOx-N:NH4-N ratio(over 80:1) in reactor, and the specific point could be easily detected by tracking moving slope change(MSC) of the curve. Revelation of NBP on pH(mV)-time profile and recognition of the realtime control point using MSC were stable at a condition of over 300mg/L NOx-N level in reactor. The occurrence of distinctive NBP was persistent on pH(mV)-time profile even at a level of 10,000mg/L STOC(soluble total organic carbon) and the recognition of NBP was feasible by tracing MSC, but that point on ORP and DO-time profiles began to disappear with the increase of STOC level in reactor. The denitrfication rate by endogenous respiration and residual organic matter was about 0.4mg/L.hr., and it was found that 0.83 would be accepted as an index for supplemental carbon source addition when 0.1 of safety factor was applied.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.22 no.2
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• pp.78-83
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• 2012

The structural change and the electrical conductivity with Sr content in $La_{1-x}Sr_xMn_{0.8}Cu_{0.2}O_3$ (LSMCu) were studied. $La_{0.8}Sr_{0.2}MnO_3$ (LSM) and $La_{1-x}Sr_xMn_{0.8}Cu_{0.2}O_3$ ($0.1{\leq}x{\leq}0.4$) were synthesized by EDTA citric complexing process (ECCP). A decrease in the lattice parameters and lattice volumes was observed with increase of Sr content, and these results were attributed to the increasing $Mn^{4+}$ ions and $Cu^{3+}$ ions in B-site. The electrical conductivity measured from $500^{\circ}C$ to $1000^{\circ}C$ was increased with increase of Sr content in the $0.1{\leq}x{\leq}0.3$ composition range, and it was 172.6 S/cm (at $750^{\circ}C$) and 177.7 S/cm (at $950^{\circ}C$, the maximum value) in x = 0.3. The electrical conductivity was decreased in x = 0.4 because of the presence of the second phase in the grain boundaries. The lattice volume was contracted by increase of $Mn^{4+}$ ions and $Cu^{3+}$ ions in B-site according to increase of Sr content and the electrical conductivity was increased with increase of charge carriers which were involved in the hopping mechanism.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.171-181
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• 2021

The purposes of this study were to determine how changes in temperature affect germination rates and growth of hulled and dehulled barley, malting barley, and naked oat plants, and to measure chlorophyll content, photosynthetic efficiency, and secondary compounds (total phenol, total flavonoid, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity) in plants grown at 13℃ or 25℃). Various types of barley seeds were collected from areas with ideal conditions for barley cultivation, hereinafter referred to as IA, and also from areas where barley cultivation is more difficult due to lower temperatures, hereinafter referred to as LTA. Seeds were tested for seed vigor. While there were significant differences in the electrical conductivity values between seeds collected from certain specific areas, no significant differences were evident between IA and LTA seeds, regardless of the type of barley seed. When plants were grown at 25℃, there were no significant differences in germination rates, plant height, root length and shoot fresh weight between plants originating from IA and LTA. However, there were differences in the measured parameters of some specific seeds. Similarly, under the low temperature condition of 13℃, no differences in the emergence rate, plant height, and shoot fresh weight were evident between plants originating from IA or LTA, regardless of the type of barley. However, there were differences between some specific seeds. One parameter that did vary significantly was the emergence date. Hulled barley and malting barley emerged 5 days after sowing, whereas naked oats emerged 7 days after sowing. There were no differences in the chlorophyll content and photosynthetic efficacy, regardless of the type of barley. There were no significant differences in total phenol, total flavonoid content, and DPPH radical scavenging activity between plants originating from IA and LTA, regardless of the type of barley. However, there were differences between some specific seeds. In particular, for malting barley the total flavonoid content differed in the order of Gangjin > Changwon > Haenam = Jeonju > Naju. The results indicate that crop growth, yield and content of secondary compounds in various types of barley may be affected by climate change.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Korean Journal of Poultry Science
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• v.33 no.3
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• pp.171-179
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• 2006

Changes in the chicken testis from hatching to adulthood were studied in Korean native chickens of 1, 2, 4, 6, 8, 10, 12, 14, 16, 18, 21, 24, 28, 32, 44, 52 and 64 weeks (n=13 chickens per group) of age. The present study was to investigate in more detail the post-hatching development of testis in Korean native chickens. Testes of chickens were fixed by whole body perfusion using a fixative containing 2.5% glutaraldehyde in cacodylate buffer, processed and embedded in Epon-araldite. Using $1{\mu}m$ sections stained with methylene blue-azure II, qualitative and quantitative(stereological) morphological studies were performed. Sperm production was measured by routine technique. The average volume of a testis of 1 week old Korean native chickens was determined as 0.015 g and the parameter increased linearly from 1 week to 21 weeks days (28.9 g), and did not change from 21 weeks to 64 weeks. The volume density of the seminiferous tubules increased with age from 32.6% at week 1 to 92.89% at week 64. The volume density of the interstitium represents 67.4% of the testicular parenchyma at week 1. This proportion progressively diminished during development to reach a value of 7.11% at week 64. Total sperm production per testis increased significantly from 18 weeks to 28 weeks and remained unchanged. Sperm production per 1 g testis increased significantly from 18 weeks to 28 weeks, did not change significantly from 28 weeks to 52 weeks, and declined significantly at 64 weeks of age. The average diameter of the seminiferous tubules gradually increased with age from 1 week $(42.4{\mu}m)$ to 21 weeks $(412.8{\mu}m)$. The length of the seminiferous tubules was 0.34 m at 1 week, increased significantly in subsequent age groups and reached 72.2 m by weeks 64. The stage of germ cell development in seminiferous tubules was classified as 1) spermatogonia $(1\sim8\;weeks)$, 2) spermatogonia and spermatocytes $(10\sim12\;weeks)$, 3) spermatogonia, spermatocytes and round spermatids $(14\sim16\;weeks)$, and 4) speramatogonia, spermatocytes, spermatids and spermatozoa $(18\sim64\;weeks)$. These results clarified the pattern of changes in the testicular development in Korean native chickens from hatching to adulthood as 1) neonatal-prepubertal $(1\sim12\;weeks)$, 2) puberty$(14\sim18\;weeks)$, and adult$(21\sim64\;weeks)$.

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