• 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.

• Sleep Medicine and Psychophysiology
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• v.3 no.2
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• pp.32-42
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• 1996

Objectives : Upper airway resistance syndrome(UARS) is a sleep-related breathing disorder characterized by abnormal negative intrathoracic pressure during sleep. Abnormally increased negative intrathoracic pressure results in microarousal and sleep fragmentation which underlay UARS-associated complaints of daytime fatigue and sleepiness. Although daytime dysfunction in patients with UARS is comparable to that of sleep apnea syndrome, UARS has been relatively unnoticed in clinical setting. That is why UARS is apt to be excluded in diagnosing of sleep-related breathing disorders since its respiratory disturbance index and arterial oxygen saturation are within normal limits. The current study presents a summary of clinical and polysomnographic characteristics found in patients with UARS. The present study aims (1) to explore characteristics of patients diagnosed with UARS, (2) to characterize the polysomnographic findings of UARS patients, and (3) to enhance the understanding of UARS through those clinical and laboratory characteristics. Methods : This was a retrospective study of 20 UARS patients (male 15, female 5) and 30 obstructive sleep apnea (OSA) patients (male 21, female 9) at the Stanford Sleep Disorders Clinic. We diagnosed patients as having UARS when they met critenia, RDI < 5 characteristic findings of an elevated esophageal pressure($<-10\;cmH_2O$), frequent arousals secondary to an elevated esophageal pressure, and symptoms of daytime fatigue and sleepiness. We used polysomnographic value, which is standardized by Williams et al(1974), as normal control. Statiotical test were done with student t-tests. Results : (1) Mean age of UARS was $41.0\;{\pm}\;14.8$ years and OSA was $50.9\;{\pm}\;12.0$ years. UARS subject was significantly younger than OSA subject (p<0.05). (2) The total score of Epworth Sleepiness Scale (ESS) was UARS $9.7\;{\pm}\;6.3$ and OSAS $11.2\;{\pm}\;6.3$. There was no significant difference between two groups. (3) The mean body mass index was UARS $28.1\;{\pm}\;5.7\;kg/m^2$ and OSAS $32.9\;{\pm}\;7.0\;kg/m^2$. UARS had significantly lower meen body man index than OSAS subjects (p<0.05). (4) The polysomnographic parameters of UARS were not significantly different from those of OSA except RDI(p<0.001), $SaO_2$ (p<0.001) and slow wave sleep latency (p<0.05). (5) Compared with normal control, Total sleep time in UARS subjects was significantly shorter (p<0.001), sleep efficiency index was significantly lower (p<0.001), total awakening percentage was significantly higher (p<0.001), and sleep stage 1 (p<0.001) were significantly higher. (6) OSA patients showed poor sleep quality and distinct abnormal sleep architectures compared with normal control. Conclusions : Conclusions from the above results are as follows : (1) UARS patients were younger and had lower body mass index when umpared with OSA patients. (2) The quality of sleep and sleep architectures of the UARS and OSA patients are significantly different from those of normal control. (3) ESS scores and awakening frequencies of UARS are similar with those of OSA, suggesting that daytime dysfunction of UARS patients may be comparable to those of OSA patients. (4) The RDI and the $SaO_2$ which are important indicators in diagnosing sleep-related breathing disorders, of UARS subjects are close to normal value. (5) According to the the above results, we unclude that despite the absence of $SaO_2$ drops and the absence of an elevated number of apnea and hypopnea, subjects developed clinical complaints which were associated with laborious breathing, elevated Pes nadir, and frequently snoring. (6) Accordingly, we suggest including LIARS in the differential diagnosis list when sleep related breathing disorder is suspected clinically and overnight polysomnographic findings except snoring and frequent microarousal are within normal limits.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.141-156
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• 2013

Researchers in welfare services of local government in Korea have rather been on isolated issues as disables, childcare, aging phenomenon, etc. (Kang, 2004; Jung et al., 2009). Lately, local officials, yet, realize that they need more comprehensive welfare services for all residents, not just for above-mentioned focused groups. Still cases dealt with focused group approach have been a main research stream due to various reason(Jung et al., 2009; Lee, 2009; Jang, 2011). Social Security Information System is an information system that comprehensively manages 292 welfare benefits provided by 17 ministries and 40 thousand welfare services provided by 230 local authorities in Korea. The purpose of the system is to improve efficiency of social welfare delivery process. The study of local government expenditure has been on the rise over the last few decades after the restarting the local autonomy, but these studies have limitations on data collection. Measurement of a local government's welfare efforts(spending) has been primarily on expenditures or budget for an individual, set aside for welfare. This practice of using monetary value for an individual as a "proxy value" for welfare effort(spending) is based on the assumption that expenditure is directly linked to welfare efforts(Lee et al., 2007). This expenditure/budget approach commonly uses total welfare amount or percentage figure as dependent variables (Wildavsky, 1985; Lee et al., 2007; Kang, 2000). However, current practice of using actual amount being used or percentage figure as a dependent variable may have some limitation; since budget or expenditure is greatly influenced by the total budget of a local government, relying on such monetary value may create inflate or deflate the true "welfare effort" (Jang, 2012). In addition, government budget usually contain a large amount of administrative cost, i.e., salary, for local officials, which is highly unrelated to the actual welfare expenditure (Jang, 2011). This paper used local government welfare service data from the detailed data sets linked to the Social Security Information System. The purpose of this paper is to analyze the factors that affect social welfare spending of 230 local authorities in 2012. The paper applied multiple regression based model to analyze the pooled financial data from the system. Based on the regression analysis, the following factors affecting self-funded welfare spending were identified. In our research model, we use the welfare budget/total budget(%) of a local government as a true measurement for a local government's welfare effort(spending). Doing so, we exclude central government subsidies or support being used for local welfare service. It is because central government welfare support does not truly reflect the welfare efforts(spending) of a local. The dependent variable of this paper is the volume of the welfare spending and the independent variables of the model are comprised of three categories, in terms of socio-demographic perspectives, the local economy and the financial capacity of local government. This paper categorized local authorities into 3 groups, districts, and cities and suburb areas. The model used a dummy variable as the control variable (local political factor). This paper demonstrated that the volume of the welfare spending for the welfare services is commonly influenced by the ratio of welfare budget to total local budget, the population of infants, self-reliance ratio and the level of unemployment factor. Interestingly, the influential factors are different by the size of local government. Analysis of determinants of local government self-welfare spending, we found a significant effect of local Gov. Finance characteristic in degree of the local government's financial independence, financial independence rate, rate of social welfare budget, and regional economic in opening-to-application ratio, and sociology of population in rate of infants. The result means that local authorities should have differentiated welfare strategies according to their conditions and circumstances. There is a meaning that this paper has successfully proven the significant factors influencing welfare spending of local government in Korea.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.175-196
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• 2022

Information and communication and home appliance industries, which were one of South Korea's main industries, are gradually losing their export share as their export competitiveness is weakening. This study objectively analyzed export competitiveness and suggested export-promising countries in order to help South Korea's information communication and home appliance industries improve exports. In this study, network properties, centrality, and structural hole analysis were performed during network analysis to evaluate export competitiveness. In order to select promising export countries, we proposed a new variable that can take into account the characteristics of an already established International Trade Network (ITN), that is, the Global Value Chain (GVC), in addition to the existing economic factors. The conditional log-odds for individual links derived from the Exponential Random Graph Model (ERGM) in the analysis of the cross-border trade network were assumed as a proxy variable that can indicate the export potential. In consideration of the possibility of ERGM linkage, a parametric approach and a non-parametric approach were used to recommend export-promising countries, respectively. In the parametric method, a regression analysis model was developed to predict the export value of the information and communication and home appliance industries in South Korea by additionally considering the link-specific characteristics of the network derived from the ERGM to the existing economic factors. Also, in the non-parametric approach, an abnormality detection algorithm based on the clustering method was used, and a promising export country was proposed as a method of finding outliers that deviate from two peers. According to the research results, the structural characteristic of the export network of the industry was a network with high transferability. Also, according to the centrality analysis result, South Korea's influence on exports was weak compared to its size, and the structural hole analysis result showed that export efficiency was weak. According to the model for recommending promising exporting countries proposed by this study, in parametric analysis, Iran, Ireland, North Macedonia, Angola, and Pakistan were promising exporting countries, and in nonparametric analysis, Qatar, Luxembourg, Ireland, North Macedonia and Pakistan were analyzed as promising exporting countries. There were differences in some countries in the two models. The results of this study revealed that the export competitiveness of South Korea's information and communication and home appliance industries in GVC was not high compared to the size of exports, and thus showed that exports could be further reduced. In addition, this study is meaningful in that it proposed a method to find promising export countries by considering GVC networks with other countries as a way to increase export competitiveness. This study showed that, from a policy point of view, the international trade network of the information communication and home appliance industries has an important mutual relationship, and although transferability is high, it may not be easily expanded to a three-party relationship. In addition, it was confirmed that South Korea's export competitiveness or status was lower than the export size ranking. This paper suggested that in order to improve the low out-degree centrality, it is necessary to increase exports to Italy or Poland, which had significantly higher in-degrees. In addition, we argued that in order to improve the centrality of out-closeness, it is necessary to increase exports to countries with particularly high in-closeness. In particular, it was analyzed that Morocco, UAE, Argentina, Russia, and Canada should pay attention as export countries. This study also provided practical implications for companies expecting to expand exports. The results of this study argue that companies expecting export expansion need to pay attention to countries with a relatively high potential for export expansion compared to the existing export volume by country. In particular, for companies that export daily necessities, countries that should pay attention to the population are presented, and for companies that export high-end or durable products, countries with high GDP, or purchasing power, relatively low exports are presented. Since the process and results of this study can be easily extended and applied to other industries, it is also expected to develop services that utilize the results of this study in the public sector.

• Asia Marketing Journal
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• v.12 no.4
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• pp.27-54
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• 2011

This research attempted to present the efficiency of culture marketing to the organizations producing culture-art products and to the companies utilizing art and suggest the practical viewpoints to the culture and art policy agencies. The methodology used was to take an in-depth look at the consumer value cognition and benefits of culture-art products in contemporary consumption culture from a social context by conducting a total of 12 Focus Group Interviews, consisting of 58 males and females in their 10s~50s who can represent culture-art product consumers. The culture-art products refer to the artist's spiritual, actual act of creating or to the end products with economic exchange value. They are also sense goods and merit goods that affect the mental state of consumers. By looking at culture-art products as consumer merit goods, this research examined consumer value cognition of culture-art products based on the characteristics culture-art products. As a result, this research determined that consumers view culture-art products largely as 'aesthetic and sensuous merit goods', 'actual and individual merit goods', and 'social public property'. As 'aesthetic and sensuous merit goods', culture-art products are considered as the products of an artist's creative activities; as 'social public property', culture-art products have a public value in terms of ownership; and as 'actual and individual merit goods', culture-art products act on the spirit and reality of a consumer in terms of consumption. As a result of analyzing the benefits of culture-art products based on the above-mentioned consumer value cognition, it was observed that the benefits of culture-art-product consumption are chiefly divided into 'aesthetic character-oriented', 'social relationships-oriented', and 'individual benefits-oriented' depending on how consumers see culture-art products. A 3-conceptional structures model was constructed according to the relationship between consumer value cognition of culture-art products and the benefits. This research revealed that consumers who pursue the aesthetic value or sense of beauty as the central reason experience culture-art products themselves, enjoy intellectual quests, and pursue their satisfaction by expressing affection for and interests in culture-art products. On the other hand, consumers who pursue social value as the central reason as a means of communication by perceiving culture-art products as a public property of society, pursue sympathy with people close to them through the symbolic power of culture-art product consumption or the joy of self-display. Consumers who perceive art products as spiritual and actual merit goods and pursue consumer value as a central reason want to express their own personality, develop themselves, and differentiate themselves or identify themselves with others in the context of social relations for the ultimate goal of living a happy and satisfied life while pursuing to satisfy imminent and actual necessities as emotional stability and rest. The fact that culture-art product benefits could vary according to how a consumer perceives them implies that consumer value cognition of culture-art products and their benefits significant affect consumers' decision in choosing and consuming various culture-art products. It turned out that such benefits from the consumption of culture-art products reflect the complex contemporary consumption culture of rational consumption, symbolic consumption, experiential consumption, and social reflective consumption. This research identified conceptional structures of consumer value cognition on culture-art products and benefits that can be used for studying and understanding culture-art products consumers who pursue a variety of consumption values. They can also be used by private companies in utilizing art, as well as by national agencies in enhancing the population's quality of life. However, since this research could only conceptually grasp consumer perception of culture-art products and reveal the dimension of classification due to its own limitations arising from characteristic investigation, quantitative data on the benefits of culture-art product consumers should be measured in future studies through a quantitative investigation, while using the value cognition of culture-art products and the individual characteristics of consumers as variables based on this research.