• Journal of Yeungnam Medical Science
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• v.24 no.2
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• pp.197-205
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• 2007

Background : The occurrence of atrial fibrillation after ablation of atrial flutter is clinically important. We investigated variables predicting this evolution in ablated patients without a previous atrial fibrillation history. Materials and Methods : Thirty-six patients (Male=28) who were diagnosed as atrial flutter without previous atrial fibrillation history were enrolled in this study. Group 1 (n=11) was defined as those who developed atrial fibrillation after atrial flutter ablation during 1 year follow-up. Group 2 (n=25) was defined as those who has not occurred atrial fibrillation during same follow-up term. Echocardiogram was performed to all patients. We measured left atrial size, left ventricle end diastolic and systolic dimension, ejection fraction and left atrial volume index before and after ablation of atrial flutter. The differences of each variables were compared and analyzed between two groups. Results : The preablation left ventricular ejection fraction (preLVEF) and postablation left ventricular ejection fraction (postLVEF) are $54{\pm}14%$, $56{\pm}13%$ in group 1 and $47{\pm}16%$, $52{\pm}13%$ in group 2. The differences between each two groups are statistically insignificant ($2.2{\pm}1.5$ in group 1 vs $5.4{\pm}9.8$ in group 2, p=0.53). The preablation left atrial size (preLA) and postablation left atrial size (postLA) are $40{\pm}4mm$, $41{\pm}4mm$ in group1 and $44{\pm}8mm$, $41{\pm}4mm$ in group 2. The atrial sizes of both groups were increased but, the differences of left atrial size between two groups before and after flutter ablation were statistically insignificant ($0.6{\pm}0.9mm$ in group 1 vs $-3.8{\pm}7.4mm$ in group 2, p=0.149). The left atrial volume index before flutter ablation was significantly reduced in group 1 than group 2 ($32{\pm}10mm^3/m^2$, $35{\pm}10mm^3/m^2$ in group 1 and $32{\pm}10mm^3/m^2$, $29{\pm}8mm^3/m^2$ in group 2, p<0.05). Conclusion : The difference between left atrial volume index before and after atrial flutter ablation is the robust predictor of occurrence of atrial fibrillation after atrial flutter ablation without previous atrial fibrillation.

• Journal of the Korean Institute of Gas
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• v.24 no.6
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• pp.34-46
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• 2020

In order to supply stable natural gas in the future, it is necessary to forecast the demand in advance and secure the quantity of supply. In this paper, we propose a method of estimating the demand function of industrial natural gas, which is the core of the increase of domestic natural gas demand in the future. The cross-sectional data of 304 domestic industries were used to estimate the demand function of the industrial natural gas, and the effect of industry specific characteristics such as capital investment, manufacturing cost. Finally, the least absolute deviation estimation method which is robust to outliers and does not assume the homogeneity of the error term and the normality, And the results were derived. In addition, the economic value of industrial city gas was estimated using the price elasticity of industrial city gas. Therefore, it can be seen that the continuous expansion and supply of city gas to the industrial sector is beneficial at the national level, and the government needs to promote expansion through the industrial city gas support policy.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.26-37
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• 2021

This study conducted a big data analysis on news to identify the agenda of media literacy, which has been socially discussed, and on which relevant policy directions will be proposed. To this end 1,336 articles from January 1, 2019 to September 30, 2020 were collected and a topic modeling analysis was conducted according to four periods. Five topics for each period were derived through the analysis, and implications based on the results are as follows. First, the government should implement a nation-level systematic approach to media literacy education according to life cycle stages to generate economic and cultural value. Second, local communities and schools should provide systematic support and education guidance activities to ensure a sustainable ecosystem for media literacy and prevent an educational gap and loss in learning. Third, efforts should be made in various aspects to minimize the side effects resulting from constantly providing media literacy education; furthermore a culture of desirable media application should be established. Finally, a research environment for scientific research on media literacy, active exchange of experience and value obtained in the field, and long-term accumulation of research results should be encouraged to develop a robust knowledge exchange culture.

• Korean small business review
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• v.42 no.4
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• pp.285-308
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• 2020

This paper analyzes the factors which affect University professors and students on their startup activities, such as (a) University factors: their industrial cooperation organization and systems, their resources for startup support, their knowledge assets, and (b) socioeconomic characteristics in which Universities are located. We used the data and information from the University Information System and the National Statistical Office Publication to analyze 157 4-year Universities in Korea who uploaded their startup-related information on the system. Our analysis shows that Universities' systems, such as the term for Professors' leave of absence for startup activities, and their amount of knowledge assets affect the number of Professor startups significantly positively, while there is no significant effect on their performance, in terms of sales, from those factors, except for the amount of patents that the University has. In the meantime, the number of practical startup courses, the number of startup clubs, and the number of professor startups in the University affect the number of student startups, while the size of industrial cooperation body, the amount of knowledge asset, the area's socioeconomic characteristics didn't affect their performance. The result implies that we need to take different approaches to boost University professor startups and their student startups: better system and more knowledge for the former, more practical courses and programs for the latter. Further study is needed to get a more robust result because this analysis used only one year data, and personal trait data was not included in the analysis. A panel data analysis for several years is recommended for further research.

• Journal of Animal Science and Technology
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• v.64 no.6
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• pp.1105-1116
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• 2022

Recently, we reported the robust in vitro three-dimensional (3D) expansion of intestinal organoids derived from adult bovine (> 24 months) samples. The present study aimed to establish an in vitro 3D system for the cultivation of intestinal organoids derived from growing cattle (12 months old) for practical use as a potential alternative to in vivo systems for various purposes. However, very few studies on the functional characterization and 3D expansion of adult stem cells from livestock species compared to those from other species are available. In this study, intestinal crypts, including intestinal stem cells, from the small intestines (ileum and jejunum) of growing cattle were isolated and long-term 3D cultures were successfully established using a scaffold-based method. Furthermore, we generated an apical-out intestinal organoid derived from growing cattle. Interestingly, intestinal organoids derived from the ileum, but not the jejunum, could be expanded without losing the ability to recapitulate crypts, and these organoids specifically expressed several specific markers of intestinal stem cells and the intestinal epithelium. Furthermore, these organoids exhibited key functionality with regard to high permeability for compounds up to 4 kDa in size (e.g., fluorescein isothiocyanate [FITC]-dextran), indicating that apical-out intestinal organoids are better than other models. Collectively, these results indicate the establishment of growing cattle-derived intestinal organoids and subsequent generation of apical-out intestinal organoids. These organoids may be valuable tools and potential alternatives to in vivo systems for examining host-pathogen interactions involving epithelial cells, such as enteric virus infection and nutrient absorption, and may be used for various purposes.

• Advances in nano research
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• v.16 no.6
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• pp.565-577
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• 2024

Vibration investigation of fluid-filled functionally graded cylindrical shells with ring supports is studied here. Shell motion equations are framed first order shell theory due to Sander. These equations are partial differential equations which are usually solved by approximate technique. Robust and efficient techniques are favored to get precise results. Employment of the Rayleigh-Ritz procedure gives birth to the shell frequency equation. Use of acoustic wave equation is done to incorporate the sound pressure produced in a fluid. Hankel's functions of second kind designate the fluid influence. Mathematically the integral form of the Langrange energy functional is converted into a set of three partial differential equations. A cylindrical shell is immersed in a fluid which is a non-viscous one. These shells are stiffened by rings in the tangential direction. For isotropic materials, the physical properties are same everywhere where the laminated and functionally graded materials, they vary from point to point. Here the shell material has been taken as functionally graded material. After these, ring supports are located at various positions along the axial direction round the shell circumferential direction. The influence of the ring supports is investigated at various positions. Effect of ring supports with empty and fluid-filled shell is presented using the Rayleigh - Ritz method with simply supported condition. The frequency behavior is investigated with empty and fluid-filled cylindrical shell with ring supports versus circumferential wave number and axial wave number. Also the variations have been plotted against the locations of ring supports for length-to-radius and height-to-radius ratio. Moreover, frequency pattern is found for the various position of ring supports for empty and fluid-filled cylindrical shell. The frequency first increases and gain maximum value in the midway of the shell length and then lowers down. It is found that due to inducting the fluid term frequency result down than that of empty cylinder. It is also exhibited that the effect of frequencies is investigated by varying the surfaces with stainless steel and nickel as a constituent material. To generate the fundamental natural frequencies and for better accuracy and effectiveness, the computer software MATLAB is used.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Distribution Science
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• v.8 no.3
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• pp.27-35
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• 2010

As the population, buying power, and intensity of self-expression of the elderly generation increase, its importance as a market segment is also growing. Therefore, the mass marketing strategy for the elderly generation must be changed to a micro-marketing strategy based on the results of sub-segmentation that suitably captures the characteristics of this generation. Furthermore, as a customer access strategy is decided by sub-segmentation, proper segmentation is one of the key success factors for micro-marketing. Segments or sub-segments are different from sectors, because segmentation or sub-segmentation for micro-marketing is based on the homogeneity of customer needs. Theoretically, complete segmentation would reveal a single voice. However, it is impossible to achieve complete segmentation because of economic factors, factors that affect effectiveness, etc. To obtain a single voice from a segment, we sometimes need to divide it into many individual cases. In such a case, there would be a many segments to deal with. On the other hand, to maximize market access performance, fewer segments are preferred. In this paper, we use the term "sub-segmentation" instead of "segmentation," because we divide a specific segment into more detailed segments. To sub-segment the elderly generation, this paper takes their lifestyles and life stages into consideration. In order to reflect these aspects, various surveys and several rounds of expert interviews and focused group interviews (FGIs) were performed. Using the results of these qualitative surveys, we can define six sub-segments of the elderly generation. This paper uses five rules to divide the elderly generation. The five rules are (1) mutually exclusive and collectively exhaustive (MECE) sub-segmentation, (2) important life stages, (3) notable lifestyles, (4) minimum number of and easy classifiable sub-segments, and (5) significant difference in voices among the sub-segments. The most critical point for dividing the elderly market is whether children are married. The other points are source of income, gender, and occupation. In this paper, the elderly market is divided into six sub-segments. As mentioned, the number of sub-segments is a very key point for a successful marketing approach. Too many sub-segments would lead to narrow substantiality or lack of actionability. On the other hand, too few sub-segments would have no effects. Therefore, the creation of the optimum number of sub-segments is a critical problem faced by marketers. This paper presents a method of evaluating the fitness of sub-segments that was deduced from the preceding surveys. The presented method uses the degree of homogeneity (DoH) to measure the adequacy of sub-segments. This measure uses quantitative survey questions to calculate adequacy. The ratio of significantly homogeneous questions to the total numbers of survey questions indicates the DoH. A significantly homogeneous question is defined as a question in which one case is selected significantly more often than others. To show whether a case is selected significantly more often than others, we use a hypothesis test. In this case, the null hypothesis (H0) would be that there is no significant difference between the selection of one case and that of the others. Thus, the total number of significantly homogeneous questions is the total number of cases in which the null hypothesis is rejected. To calculate the DoH, we conducted a quantitative survey (total sample size was 400, 60 questions, 4~5 cases for each question). The sample size of the first sub-segment-has no unmarried offspring and earns a living independently-is 113. The sample size of the second sub-segment-has no unmarried offspring and is economically supported by its offspring-is 57. The sample size of the third sub-segment-has unmarried offspring and is employed and male-is 70. The sample size of the fourth sub-segment-has unmarried offspring and is not employed and male-is 45. The sample size of the fifth sub-segment-has unmarried offspring and is female and employed (either the female herself or her husband)-is 63. The sample size of the last sub-segment-has unmarried offspring and is female and not employed (not even the husband)-is 52. Statistically, the sample size of each sub-segment is sufficiently large. Therefore, we use the z-test for testing hypotheses. When the significance level is 0.05, the DoHs of the six sub-segments are 1.00, 0.95, 0.95, 0.87, 0.93, and 1.00, respectively. When the significance level is 0.01, the DoHs of the six sub-segments are 0.95, 0.87, 0.85, 0.80, 0.88, and 0.87, respectively. These results show that the first sub-segment is the most homogeneous category, while the fourth has more variety in terms of its needs. If the sample size is sufficiently large, more segmentation would be better in a given sub-segment. However, as the fourth sub-segment is smaller than the others, more detailed segmentation is not proceeded. A very critical point for a successful micro-marketing strategy is measuring the fit of a sub-segment. However, until now, there have been no robust rules for measuring fit. This paper presents a method of evaluating the fit of sub-segments. This method will be very helpful for deciding the adequacy of sub-segmentation. However, it has some limitations that prevent it from being robust. These limitations include the following: (1) the method is restricted to only quantitative questions; (2) the type of questions that must be involved in calculation pose difficulties; (3) DoH values depend on content formation. Despite these limitations, this paper has presented a useful method for conducting adequate sub-segmentation. We believe that the present method can be applied widely in many areas. Furthermore, the results of the sub-segmentation of the elderly generation can serve as a reference for mature marketing.

• Journal of Plant Biotechnology
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• v.45 no.3
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• pp.171-182
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• 2018

Papaya (Carica papaya L.) is one of the crops widely planted in tropical and subtropical areas. The papaya fruit has low calories and are plentiful in vitamins A and C and in minerals. A major problem in papaya production is a plant disease caused by the papaya ringspot virus (PRSV). The first PRSV-resistant GM papaya expressing a PRSV coat protein gene was developed by USA scientists in 1992. The first commercial GM papaya cultivars derived from the event was approved by the US government in 1997. Development of transgenic papayas has been focused on vaccine production and limited agricultural traits, including insect and pathogen resistance, long shelf life, and aluminum and herbicide tolerance. Approximately 17 countries, including the USA and China, produced transgenic papayas and/or commercialized them, which provoked studies on biosafety assessment and development of GM-detection technologies. For the biosafety assessment of potential effects on human health, effects of long-term feeding to model animals have been studied in terms of toxicity and allergenicity. Studies on environmental safety assessment include influence on soil-microbial biodiversity and transfer to soil bacteria of GM selection markers. Many countries, such as Korea, the European Union, and Japan, that have strict regulations for GM crops have serious concerns about unintended introduction of GM cultivars and food commodities using unauthorized GM crops. Transgene- and/or GM event-specific molecular markers and technologies for genomics-based detection of unauthorized GM papaya have been developed and have resulted in the robust detection of GM papayas.

• Korean Journal of Ecology and Environment
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• v.33 no.3 s.91
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• pp.187-196
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• 2000

This paper describes a simple method that uses differences among Carlson's (1977) trophic state index (TSI) values based on total phosphorus (TP), chlorophyll a (CHL) and Secchi depth (SD) to draw inferences regarding the factors that are limiting to phytoplankton growth and the composition of lake seston. Examples are provided regarding seasonal and spatial patterns in a large subtropical lake (Lake Okeechobee, Florida, USA) and inter- and intra-lake variations from a multilake data set developed from published studies. Once an investigator has collected routine water quality data and established TSI values based on TP, CHL, and SD, a number of inferences can be made. Additional information can be provided where it also is possible to calculate a TSI based on total nitrogen (TN). Where TSI (CHL)<>TSI (SD), light attenuating particles are large (large filaments or colonies of algae), and the phytoplankton may be limited by zooplankton grazing. Other limiting conditions are inferred by different relationships between the TSI values. Results of this study indicate that the analysis is quite robust, and that it generally gives good agreement with conclusions based on more direct methods (e.g., nutrientaddition bioassays, zooplankton size data, zooplankton removal experiments). The TSI approach, when validated periodically with these more costly and time-intensive methods, provides an effective, low cost method for tracking long-term changes in pelagic structure and function with potential value in monitoring lake ecology and responses to management.