• KOREAN JOURNAL OF CROP SCIENCE
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• v.13
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• pp.1-40
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• 1973

These studies were aimed at clarification of genetic and ecological variation in culm length, panicle length and plant height of the $\textrm{F}_2$ plants in some selected crosses made between semi-dwarf rice varieties and tall Japonica ones. One Indica semi-dwarf, Taichung Native 1, one Indica $\times$ Japonica hybrid, IE51 and one Japonica semi-dwarf, Tankanbaekmang were used as short-gene donors while two of medium maturity varieties, Jinheung and Kwanok and one late veriety, Palkweng were used as the corresponding counterpart of respective dwarf varieties in a series of crosses. Five different crosses, Kwanok $\times$ Tankanbaekmang, Palkweng $\times$ Tankanbaekmang, Jinheung $\times$ T(N)1, Kwanok $\times$ T(N)1 and Kwanok $\times$ IE51, were made among the above six varieties. The $\textrm{F}_2$ plants of these crosses together with the concerned parental varieties were grown under several different conditions including three levels of each nitrogen and planting space, three planting seasons and three locations in 1968, to investigate variation in length of culm and panicle, and plant height. On the other hand, the F$_3$ progenies which were derived from the shortest 10 percent of the plants of three $\textrm{F}_2$ populations, Kwanok $\times$ T(N)1, Jinheung $\times$ T(N) 1 and Kwanok $\times$ IE51 grown in the previous year, were compared each other on the basis of selection efficiency in culm length. The experimental results could be summarized as follows; 1. Genetic behavior A. It was revealed that Tankanbaekmang, one of Japonica dwarf has a simple recessive gene responsible for short culm expression, showing a typical segregation ratio of three tall to one short culm plants in $\textrm{F}_2$ generation of the crosses either with Kwanok or Palkweng. B. In the both combinations, segregation pattern of the panicle length was exactly same as that of culm length. It seems that the same gene controls both culm length and panicle length. C. No difference between segregation of culm length and plant height in the above crosses was observed. D. T(N)1, one of Indica semi-dwarf did not show such a simple genetic behavior as detected from the crosses with Tankanbaekmang in segregation of culm length but formed a continuous and normal distribution curve. Therefore, some nonallelic genic actions might be involved in expression of culm length of the counterpart varieties of T(N)1. In particular, a transgressive segregation appeared toward the direction of longer culm length in case of Jinheung $\times$ T(N)1. The genetic behavior of panicle length and plant height generally coincided with that of culm length in all the cases. E. IE51 demonstrated exactly the same genetic behavior as that of T(N)1 when this variety was crossed with Kwanok. It was clearly clarified that the simple recessive gene controlling dwarfism from T(N)1 was well incorporated into this variety. 2. Ecological variation A. In general, there was a decreasing tendency in culm length and plant height of rice plant as seeding delayed while it was not so noticeable in panicle length. The decreasing magnitude varied from variety to variety and from cross to cross. Genetic behavior of the culm length and related characters of these materials was not disturbed by the variation of seeding season, nitrogen level, planting space and experimental location. E. The elongation mode of the upper three internodes was very similar to the segregation mode of culm length, panicle length and plant height in $\textrm{F}_2$ populations of . all the crosses investigated in this study. Accordingly, this result confirmed that the roles of the upper three internodes are very important in manifesting plant stature in rice. C. The effect of nitrogen on culm length and the related other two characters seemed to be meager. However, it was true to show an increasing tendency of those characters as nitrogen level got increased from 4 kg to 12kg per l0a, with different magnitude depending upon variety or cross. D. Also, the effect of planting space on culm length, panicle length and plant height was relatively small in all the cases. Those characters varied again depending upon variety or cross. However, a general increasing tendency was detected in manifestation of those traits under denser planting space condition. E. All the parental varieties produced shorter culm, panicle and plant height when they were grown at the lower latitude locations. It might be attributed to the fact that their reproductive growth accelerated with increased temperature prevailing at the lower latitude locations such as Iri and Mi1yang. On the countrary, $\textrm{F}_2$ population reacted differently to the different locations from the parental varieties. All the $\textrm{F}_2$ plants produced the longest culm, panicle and plant at Milyang. 3. Selection efficiency A. The heritability of culm length in Kwanok $\times$ T(N)1, Kwanok $\times$ IE51 and Jinheung$\times$T(N)1 was 92 percent, 74 percent and 55 percent, respectively. B. The actual genetic advance for culm length obtained from the progeny lines of the selected plants(10 precent) from the $\textrm{F}_2$ generation, was comparable to the expected advance calculated from the original $\textrm{F}_2$ populations. As compared with the $\textrm{F}_2$ population, the $\textrm{F}_3$ plants of Kwanok $\times$ T(N)l shortened on the average by 20.8cm, those of Kwanok $\times$ IE51 did 8.7cm and those of Jinheung$\times$T(N)1 20.0cm, respectively. C. Panicle length of the populations was differently affected from one cross to another by the selection based upon culm length in $\textrm{F}_2$ Kwanok $\times$ T(N)1 did not show any noticeable shortening of its culm length due to the selection pressure. On the other hand, both Kwanok $\times$ IE51 and Jinheung $\times$ T(N)1 showed a considerable shortening of their panicles in case of selection for culm length. Based upon the above results, it could be concluded that the ecological variation in culm length, panicle length and plant height was relatively small and fallen within the range of genetic variation. Considering from the fact that the simple recessive gene governing short height of Tankanbaekmang always accompanied with some undesirable characters such as short panicle and extremely small grain, the short gene of T(N)1 seemed to be more useful as dwarf gene source since it did not carry short gene together with such undesirable traits.

• Journal of Chest Surgery
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• v.37 no.3
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• pp.201-209
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• 2004

Extracorporeal life support (ECLS) system is a device for respiratory and/or heart failure treatment, and there have been many trials for development and clinical application in the world. Currently, a non-pulsatile blood pump is a standard for ECLS system. Although a pulsatile blood pump is advantageous in physiologic aspects, high pressure generated in the circuits and resultant blood cell trauma remain major concerns which make one reluctant to use a pulsatile blood pump in artificial lung circuits containing a membrane oxygenator. The study was designed to evaluate the hypothesis that placement of a pressure-relieving compliance chamber between a pulsatile pump and a membrane oxygenator might reduce the above mentioned side effects while providing physiologic pulsatile blood flow. The study was performed in a canine model of oleic acid induced acute lung injury (N=16). The animals were divided into three groups according to the type of pump used and the presence of the compliance chamber, In group 1, a non-pulsatile centrifugal pump was used as a control (n=6). In group 2 (n=4), a single-pulsatile pump was used. In group 3 (n=6), a single-pulsatile pump equipped with a compliance chamber was used. The experimental model was a partial bypass between the right atrium and the aorta at a pump flow of 1.8∼2 L/min for 2 hours. The observed parameters were focused on hemodynamic changes, intra-circuit pressure, laboratory studies for blood profile, and the effect on blood cell trauma. In hemodynamics, the pulsatile group II & III generated higher arterial pulse pressure (47$\pm$ 10 and 41 $\pm$ 9 mmHg) than the nonpulsatile group 1 (17 $\pm$ 7 mmHg, p<0.001). The intra-circuit pressure at membrane oxygenator were 222 $\pm$ 8 mmHg in group 1, 739 $\pm$ 35 mmHg in group 2, and 470 $\pm$ 17 mmHg in group 3 (p<0.001). At 2 hour bypass, arterial oxygen partial pressures were significantly higher in the pulsatile group 2 & 3 than in the non-pulsatile group 1 (77 $\pm$ 41 mmHg in group 1, 96 $\pm$ 48 mmHg in group 2, and 97 $\pm$ 25 mmHg in group 3: p<0.05). The levels of plasma free hemoglobin which was an indicator of blood cell trauma were lowest in group 1, highest in group 2, and significantly decreased in group 3 (55.7 $\pm$ 43.3, 162.8 $\pm$ 113.6, 82.5 $\pm$ 25.1 mg%, respectively; p<0.05). Other laboratory findings for blood profile were not different. The above results imply that the pulsatile blood pump is beneficial in oxygenation while deleterious in the aspects to high pressure generation in the circuits and blood cell trauma. However, when a pressure-relieving compliance chamber is applied between the pulsatile pump and a membrane oxygenator, it can significantly reduce the high circuit pressure and result in low blood cell trauma.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.1-10
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• 2009

The purpose of this study was to categorize the gap between coffee shop 'importance' (as perceived by customers before patronizing the coffee shop) and 'satisfaction' (perception of customers after patronizing the coffee shop) as positive or negative and to analyze the effect of these gaps on purchasing behavior. To do this, I used the gap between importance and satisfaction regarding the choice of a coffee shop as the explanatory variable and performed an empirical analysis of the direction and size of the effect of the gap on purchasing behavior (overall satisfaction, willingness-to-revisit) by applying the Ordered Probit Model (OPM). A previous study that used IPA to evaluate the effects of gaps estimated the direction and size of a quadrant but failed to analyze the effect of gaps on customers. In this study, I evaluated the effects of positive and negative gaps on customer satisfaction and willingness-to-revisit. Using OPM, I quantified the effect of positive and negative gaps on overall customer satisfaction and willingness-to-revisit. Per-head expenditure, frequency of visits, and coffee-purchasing place had the most positive effects on overall customer satisfaction. Frequency of visits, followed by per-head expenditure and then coffee-purchasing place, had the most positive impact on willingness-to-visit. Thus per-head expenditure and frequency of visits had the greatest positive effects on overall satisfaction and willingness-to-revisit. This finding implies that the higher the actual satisfaction (gap) of customers who spend KRW5,000 or more once or more per week at coffee shops is, the higher their overall satisfaction and willingness-to-revisit are. Despite the fact that economical efficiency had a significant effect on overall satisfaction and willingness-to-revisit, college and university students still use coffee shops and are willing to spend KRW5,000 because they do not only purchase coffee as a product itself, but use the coffee shop for other activities, such as working, meeting friends, or relaxing. College and university students also access the Internet in coffee shops via personal laptops, watch movies, and study; thus, coffee shops should provide their customers with the appropriate facilities and services. The fact that a positive gap for coffee shop brand had a positive effect on willingness-to-revisit implies that the higher the level of customer satisfaction, the greater the willingness-to-revisit. A negative gap for this factor, on the other hand, implies that the lower the level of customer satisfaction, the lower the willingness-to-revisit. Thus, the brand factor has a comparatively greater effect on satisfaction than the other factors evaluated in this study. Given that the domestic coffee culture is becoming more upscale and college/university students are sensitive to this trend, students are attentive to brands. In most upscale coffee shops in Korea, the outer wall is built out of glass that can be opened, the interiors are exotic with an open kitchen. These upscale coffee shops function as landmarks and match the taste of college/university students. Coffee shops in Korea have become a cultural brand. To make customers feel that coffee shops are upscale, good quality establishments and measures to provide better services in terms of brand factor should be instituted. The intensified competition among coffee shop brands in Korea as a result of the booming industry indicates that provision of additional services is needed to differentiate competitors. These customers can also use a scanner free of charge. Another strategy that can be used to boost brands could be to provide and operate a seminar room for seminars and group study. If coffee shops adopt these types of strategies, college/university students would be more likely to consider the expenses they incur worthwhile and, subsequently, they would be more likely to be satisfied with the brands of these coffee shops, with an associated increase in their willingness-to-revisit. Gender and study year had the most negative effects on overall satisfaction and willingness-to-revisit. Female students were more likely to be satisfied and be willing to return than male students, and third and fourth-year students were more likely to be satisfied and willing-to-return than first or second-year students. Students who drink coffee, read books, and use laptops alone at coffee shops are easily noticeable. High-grade students tend to visit coffee shops alone in order to use their time efficiently for self-development and to find jobs. The economical efficiency factor had the greatest effect on overall satisfaction and willingness-to-revisit in terms of a positive gap. The higher the actual satisfaction (gap) of students with the price of the coffee, the greater their overall satisfaction and willingness-to-revisit. Economical efficiency with a negative gap had a negative effect on willingness-to-revisit, which implies that a less negative gap will result in a greater willingness-to-revisit. Amid worsening market conditions, coffee shops located around colleges/universities are using strategies, such as a point or membership card, strategic alliances with credit-card companies, development of a set menu or seasonal menu, and free coffee-shot services to increase their competitive edge. Product power also had a negative effect in terms of a negative gap, which indicates that a higher negative gap will result in a lower willingness-to-revisit. Because there are many more customers that enjoy coffee in this decade, as compared to previous decades, the new generation of customers, namely college/university students, want various menu items in addition to coffee, and coffee shops should, therefore, add side menu items, such as waffles, rice cakes, cakes, sandwiches, and salads. For example, Starbucks Korea is making efforts to enhance product power by selling rice cakes flavored in strawberry, wormwood, and pumpkin, and providing coffee or cream free of charge. In summary, coffee shops should focus on increasing their economical efficiency, brand, and product power to enhance the satisfaction of college/university students. Because shops adjacent to colleges or universities enjoy a locational advantage, providing differentiated services in terms of economical efficiency, brand, and product power, is likely to increase customer satisfaction and return visits. Coffee shop brands should, therefore, be innovative and embrace change to meet their customers' desires. Because this study only targeted college/university students in Seoul, comparative studies targeting diverse regions and age groups are required to generalize the findings and recommendations of this study.

• Journal of the korean academy of Pediatric Dentistry
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• v.26 no.2
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• pp.377-398
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• 1999

Calcium fluoride, created by topical fluoride application, is the reservoir for fluoride ion regulated by pH in the oral environment. Therefore, the amount and the maintenance of calcium fluoride have an important role in preventing dental caries. The aim of this study is to evaluate the effect of Nd:YAG laser irradiation on the generation of calcium fluoride and the acid resistance of tooth enamel. The bovine anterior permanent teeth were prepared (n=276), and divided into following groups : no treatment (control) fluoride application alone, laser irradiation alone, laser irradiation after fluoride application, and fluoride application after laser irradiation. And each group was subdivided based on the application time of 1.23% acidulated phosphate fluoride (APF) (5 min and 30 min) and the irradiation energy of Nd:YAG laser ($20J/cm^2\;and\;40J/cm^2$). In case of fluoride application, each group was divided according to KOH treatment. Twenty three treatment conditions were made for this experiment and twelve specimens were assigned to each treatment condition. In each treatment condition, ten specimens were used for chemical analysis and two specimens were observed under SEM. In groups without treating KOH, fluoride content and the depth of enamel dissolved were measured using enamel biopsy technique. In groups with treating KOH, the amount of calcium fluoride was measured by the treatment with 1 M KOH for 24 hours and enamel biopsy was performed after KOH treatment. The results were analyzed by the fluoride content and the depth of enamel dissolved by enamel biopsy, amount and thickness of calcium fluoride, and the surface structures of enamel. The results are as follows: 1. In groups without treating KOH, the fluoride content of removed enamel showed a positive relationship with the energy density of laser when the laser irradiated before fluoride application 2. In groups without treating KOH, the depth of enamel dissolved decreased more with the combined laser and fluoride treatment than with laser or fluoride treatment, except for the case of $20J/cm^2$ laser irradiation after 5 minute fluoride application (p<0.05). 3. The amount of calcium fluoride did not increased by laser treatment with no statistical significance(p>0.05). 4. The particle size of calcium fluoride increased in case of fluoride treatment after laser irradiation, compared with fluoride application alone. In case of laser treatment after fluoride application, the particle size of calcium fluoride increased and some of the particles fused as well. 5. There were no significant differences in the fluoride content of dissolved enamel between groups without treating KOH and control group, except for the case of laser irradiation after treatment of APF for 30 minutes (p>0.05). 6. In groups with treating KOH, depth of removed enamel in the groups of combined treatment with laser and fluoride was shallower than that in fluoride application groups (p<0.05). 7. In groups without treating KOH, the relationship between fluoride content and the depth of enamel dissolved showed more negative (Spearman correlation coefficient: -0.6281) than in groups with treating KOH (Spearman correlation coefficient: -0.3792). The greater amount of calcium fluoride could be found in case where there was a significant differences of the depth of enamel dissolved between groups with and without treating KOH. From these results, it can be concluded that laser seems to be a little effects on the amount of calcium fluoride formation, but has some effect on the lowering the solubility of calcium fluoride. As the combined treatment of laser and fluoride application showed more effective acid-resistant property, more extended recall period for fluoride application can be achieved with this combined treatment in the clinic.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.5
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• pp.853-860
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• 2012

To estimate potential use of fly ash in reducing $CH_4$ and $CO_2$ emission from soil, $CH_4$ and $CO_2$ fluxes from a paddy soil mixed with fly ash at different rate (w/w; 0, 5, and 10%) in the presence and absence of fertilizer N ($(NH_4)_2SO_4$) addition were investigated in a laboratory incubation for 60 days under changing water regime from wetting to drying via transition. The mean $CH_4$ flux during the entire incubation period ranged from 0.59 to $1.68mg\;CH_4\;m^{-2}day^{-1}$ with a lower rate in the soil treated with N fertilizer due to suppression of $CH_4$ production by $SO_4^{2-}$ that acts as an electron acceptor, leading to decreases in electron availability for methanogen. Fly ash application reduced $CH_4$ flux by 37.5 and 33.0% in soils without and with N addition, respectively, probably due to retardation of $CH_4$ diffusion through soil pores by addition of fine-textured fly ash. In addition, as fly ash has a potential for $CO_2$ removal via carbonation (formation of carbonate precipitates) that decreases $CO_2$ availability that is a substrate for $CO_2$ reduction reaction (one of $CH_4$ generation pathways) is likely to be another mechanisms of $CH_4$ flux reduction by fly ash. Meanwhile, the mean $CO_2$ flux during the entire incubation period was between 0.64 and $0.90g\;CO_2\;m^{-2}day^{-1}$, and that of N treated soil was lower than that without N addition. Because N addition is likely to increase soil respiration, it is not straightforward to explain the results. However, it may be possible that our experiment did not account for the substantial amount of $CO_2$ produced by heterotrophs that were activated by N addition in earlier period than the measurement was initiated. Fly ash application also lowered $CO_2$ flux by up to 20% in the soil mixed with fly ash at 10% through $CO_2$ removal by the carbonation. At the whole picture, fly ash application at 10% decreased global warming potential of emitted $CH_4$ and $CO_2$ by about 20%. Therefore, our results suggest that fly ash application can be a soil management practice to reduce green house gas emission from paddy soils. Further studies under field conditions with rice cultivation are necessary to verify our findings.

• Tuberculosis and Respiratory Diseases
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• v.65 no.3
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• pp.177-182
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• 2008

Background: Isoniazid (INH, H) is a key drug of the standard first-line regimen for the treatment of tuberculosis (TB), yet some reports have suggested that treatment efficacy was maintained even though INH was omitted from the treatment regimen. Methods: One hundred forty C57BL/6 mice were infected with the H37Rv strain of M. tuberculosis with using a Glas-Col aerosol generation device, and this resulted in depositing about 100 bacilli in the lung. Four weeks after infection, anti-TB treatment was initiated with varying regimens for 4-8 weeks; Group 1: no treatment (control), Group 2 (4HREZ): 4 weeks of INH, rifampicin (R), pyrazinamide (Z) and ethambutol (E), Group 3: 1HREZ/3REZ, Group 4: 4REZ, Group 5: 4HREZ/4HRE, Group 6: 1HREZ/3REZ/4RE, and Group 7: 4REZ/4RE. The lungs and spleens were harvested at several time points until 28 weeks after infection, and the colony-forming unit (CFU) counts were determined. Results: The CFU counts increased steadily after infection in the control group. In the 4-week treatment groups (Group 2-4), even though the culture was negative at treatment completion, the bacilli grew again at the 12-week and 20-week time points after completion of treatment. In the 8-week treatment groups (Groups 5-7), the bacilli did not grow in the lung at 4 weeks after treatment initiation and thereafter. In the spleens of Group 7 in which INH was omitted from the treatment regimen, the culture was negative at 4-weeks after treatment initiation and thereafter. However, in Groups 5 and 6 in which INH was taken continuously or intermittently, the bacilli grew in the spleen at some time points after completion of treatment. Conclusion: TThe exclusion of INH from the standard first-line regimen did not affect the treatment outcome in a murine model of TB in the early stage of disease. Further studies using a murine model of chronic TB are necessary to clarify the role of INH in the standard first-line regimen for treating TB.

• Pediatric Infection and Vaccine
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• v.10 no.2
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• pp.167-177
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• 2003

Purpose : To know the trends of antimicrobial susceptibility is critical for antimicrobial treatment. We studied the organisms isolated from blood, urine, stool, and cerebrospinal fluid from 1997 to 2001 to reveal the trends of their antimicrobial susceptibility. Methods : We conducted a retrospective study with isolates obtained from 0~18 year old outpatients and inpatients from 1997 to 2001 at Department of Pediatrics, Hanil general hospital. We gathered the data through the laboratory test files and the origin of microorganisms cultured from blood, urine, stool and cerebrospinal fluid and their antimicrobial susceptibility. Results : Microorganisms were isolated from 226(3.3%) out of 6,974 blood cultures, 365 (8.0%) out of 4,549 urine cultures, 50(1.9%) out of 2,593 stool cultures and 9(1.4%) in 655 cerebrospinal fluid cultures. The most frequently isolated organisms from blood cultures was Staphylococcus epidermidis(33.5%) which was followed by Staphylococcus aureus(19.7%), Escherichia coli(13.8%), and Burkholderia cepacia(9.0%). Among the urine cultures, E. coli was the most common(74.7%) which was followed by Group D Enterococcus(11.3%), Klebsiella pneumoniae(7.1%) and Proteus mirabilis(2.5%). The positive stool cultures all yield Salmonella species. Group D Salmonella was obtained most frequently. Among the positive cerebrospinal fluid cultures, Group B Streptococcus was isolated most frequently. Among the 40 cases of S. aureus in blood cultures, 27 cases were methicillin-resistant. The rates of susceptibility for amikacin, ceftizoxime and ceftriaxone of E. coli isolated from blood cultures were 80%, 100% and 60% in 1997 and 60%, 80% and 60% in 2001. The rates of susceptibility for amikacin, ceftizoxime and ceftriaxone of K. pnumoniae isolated from urine cultures. were 80%, 100% and 80% in 1997 and 50%, 83% and 50% in 2001 Enterococcus was isolated from 6.7% to 15.8% and vancomycin-resistant Enterococcus was observed in 17% of Group D Enterococcus isolated from urine cultures. The rates of susceptibility for amikacin, ceftizoxime and ceftriaxone of Group D Salmonella were 96%, 96% and 92% during the study period. Conclusion : Among the blood cultures S. epidermidis, S. aureus, E. coli and B. cepacia were isolated in order of frequency and among the urine cultures E. coli, Group D Enterococcus, K. pneumoniae and P. mirabilis were isolated in order of frequency. During the study period there was no big difference in major organisms isolated from blood and urine. The methicillin-resistant S. aureus was observed in 67% of S. aureus isolated from blood cultures but vancomycin-reistant S. aureus or vancomycin intermediate resistant S. aureus was not observed. The rates of susceptibility to amikacin and the third generation cephalosporin of E. coli isolated from blood cultures and K. pneumoniae from urine cultures have decreased. The isolation rates of Group D Enterococcus and vancomycin resistant Enterococcus have increased.