• The KIPS Transactions:PartC
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• v.10C no.5
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• pp.625-634
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• 2003

More than a decade after its initial proposal, deployment of IP Multicast has been limited due to the problem of traffic control in multicast routing, multicast address allocation in global internet, reliable multicast transport techniques etc. Lately, according to increase of multicast application service such as internet broadcast, real time security information service etc., overlay multicast is developed as a new internet multicast technology. In this paper, we describe an overlay multicast protocol and propose fast join mechanism that considers switching of the tree. To find a potential parent, an existing search algorithm descends the tree from the root by one level at a time, and it causes long joining latency. Also, it is try to select the nearest node as a potential parent. However, it can't select the nearest node by the degree limit of the node. As a result, the generated tree has low efficiency. To reduce long joining latency and improve the efficiency of the tree, we propose searching two levels of the tree at a time. This method forwards joining request message to own children node. So, at ordinary times, there is no overhead to keep the tree. But the joining request came, the increasing number of searching messages will reduce a long joining latency. Also searching more nodes will be helpful to construct more efficient trees. In order to evaluate the performance of our fast join mechanism, we measure the metrics such as the search latency and the number of searched node and the number of switching by the number of members and degree limit. The simulation results show that the performance of our mechanism is superior to that of the existing mechanism.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Journal of Korean Academy of Nursing
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• v.26 no.1
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• pp.223-247
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• 1996

This study was done to provide information which would lead to nursing care of the elderly being more holistically through an understanding of the phenomena of powerlessness based on the lived experience of powerlessness by the elderly, the meaning the elderly give to such phenomena, and what essence of powerlessness is. The methodology used in this study was Max Van Manen's phenomenological method based on the philosophy of Merleu-Ponty and a concerted approach was realized through the 11 steps suggested in the Van Manen's method. Data collection was done from March 2, 1995 to December 30, 1995. The subjects for this study were four elderly persons who lived with their families and who were over 60 years of age. Data were collected about the lived experience of the elderly, this researcher's experience of powerlessness, the linguistic meaning of powerlessness, idioms of the word or a feeling of powerlessness, and descriptions of powerlessness in the elderly as they appeared in the literature, are works, and phenomenological literature. All data were used to provide insights into the phenomena of powerlessness. Data about the experience of powerlessness by the elderly were collected through open interviews, participation, and observation. In the analysis of the theme of this study, the aspects of the theme, powerlessness in the elderly were clarified, thereby abstracting and finding meaningful statements by the elderly about their feeling of powerlessness, and then those significant statements were expressed as linguistic transformations. The summarized findings from the study are as follows : 1. Five meanings of powerlessness in the elderly were defined. 〈weakness〉, 〈dependence〉, 〈frustration〉, 〈worthlessness〉 and 〈giving up〉. 2. 〈Weakness〉 means that the elderly experience, not only their aging but also, their becoming weak and the loss of physical function frequently caused by diseases. 〈Dependence〉 means that the elderly experience dependence without any influence from the surroundings and that elderly patients who are hospitalized lose their autonomy, follow entirely their doctor's prescriptions, use aid equipment and directions, and depend only on those things. 〈Frustration〉 means that the elderly experience the loss of their roles from the past, there by feeling that there is no work for them to do anymore and therefore feel unable to do anything. 〈Worthlessness〉 means that the elderly experience the feeling of losing their social roles from the past, having no financial ability, thereby being a burden to their children or the people around them, and therefore regarding themselves useless. 〈Giving up〉 means that the elderly experience the feeling of closeness to death in the final stage of their lifetime, lose hope to be healed from their disease, and recognize the incontrollability of their own body. 3. From a general view of the meaning of the theme the powerlessness in the elderly-the most essential meaning of the theme is the 〈sense of loss〉. For the elderly are experiencing a sense of loss in the situation of being elderly and therefore being often hospitalized. Brief definitions of the five phenomena could be 〈weakness〉 meaning the loss of physical strength, 〈dependence〉 the loss of mentality caused by disease and hospitalization, 〈frustration〉 and 〈worthlessness〉 the loss of social performance caused by the loss of social functions from the past, and lastly 〈giving up〉 the loss of the controllability of such situations of aging and suffering disease. In light of the discussion above, it is understandable that the hospitalized elderly experience powerlessness not only as it related to their diseases but also to their normal aging, and this related to other characteristics of being elderly means that the 〈sense of loss〉 is the very essence of their powerlessness. 4. While most cases are of the normal elderly experiencing powerlessness in relation to their social network, cases of elderly who are hospitalized are of those experiencing powerlessness in relation to the loss of their physical desire. 5. The findings discussed above can serve as guidelines for nurses who take care of the ill elderly who are hospitalized and that can provide cues to appropriate nursing service, recognizing that the subjective experience of the objective age of the elderly is so important. Nurses can provide highly qualitative nursing service, based on their deep understanding of the suffering of the elderly due to feelings of powerlessness.

• Spatial Information Research
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• v.23 no.3
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• pp.11-21
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• 2015

While the number of total population in Seoul has been on the constant decline for the last few years, the number of household has increased due to the rising tendency of the smaller households. In 2010, the small households in the metropolitan areas accounted for 44% of the entire households, and Statistics Korea has reported that one person household, which will take up more than 30% of the whole household, will have been the most common type of household by 2020. This reason of rise will be differently shown according to age like the preferred housing type or surrounding environments, this research is suggest to research hypothesis that distinction of age leads to the spatial distribution of one person household. Therefore, this research is to exercise a multiple regression analysis targeting on the facilities, which become the spatial distribution factor of one person household, with the independent variable gained from the concluded area calculated with the area ratio of the spatial unit followed by the service area analysis based on network. The spatial unit is the census output of Seoul, and based on this the interaction between the number of one person household according to age and the factors of its distribution. Also, the spatial regions - downtown, northeast, southeast, northwest, southwest - are designed as dummy variables and the results of each region are found out. As a result, the spatial regions occupied according to age are found to be varied - people in their 20s prefer housings near the college, 30s lease or the monthly rental housings, 40s the monthly rental housings, and over 60s the housing with the floor area of less than $40m^2$. Likewise, one person household has different types of housing environments preferred according to age, and thus a housing policy concerning this will have to be suggested.

• Korea journal of population studies
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• v.23 no.2
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• pp.79-112
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• 2000

This study was focused on the contrasting pattern of part-time employment between Japan and Taiwan where the environments are similar in terms of expanding service industries and increasing flexibility of labor. In Japan, the expansion of part-time employment and its feminization have occurred, whereas they have not at all in Taiwan. The purpose of this study was to examine the reasons behind this phenomena, and to explore what relations they might have with the supply of women\`s labor in each country. Data analysis showed the following results. First, when the phenomena of part-time employment in Japan and Taiwan are summarized as \`active\` and \`inactive\` models, the difference could be explained by a structure-oriented approach rather than an individual-oriented approach. In other words, the difference between the two countries is mainly because of the structural characteristics of the labor market. a combination of capitalism and patriarchy, and an effect of state welfare and family policies rather than a \`voluntaristic choice\` due tn household work and child rearing. In light of this. the labor market segmentation and flexibility of labor theory in particular provided a useful frame for explanation. Second, with regard to the supply of women\`s labor, the difference between Japan and Taiwan could be found in the structure of the labor market and in family response strategies. The large corporation-oriented and strictly divided labor market structure in Japan activated part-time employment and its feminization, whereas, the small family-oriented businesses and less divided labor market in Taiwan supported the continuity of full-time employment of married women. There was also a room for informal employment in Taiwan which made part-time employment unnecessary. This study showed that even within similar environments of expanding service industry and pursuing flexibility of labor different measures and adaptations were possible. The case of Taiwan in particular, showed the significance of an informal labor market which was a part of industrialization process and a strategy of producing various products through a subcontracting network.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.325-338
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• 2003

Video adaptation in response to dynamic resource conditions and user preferences is required as a key technology to enable universal multimedia access (UMA) through heterogeneous networks by a multitude of devices In a seamless way. Although many adaptation techniques exist, selections of appropriate adaptations among multiple choices that would satisfy given constraints are often ad hoc. To provide a systematic solution, we present a general conceptual framework to model video entity, adaptation, resource, utility, and relations among them. It allows for formulation of various adaptation problems as resource-constrained utility maximization. We apply the framework to a practical case of dynamic bit rate adaptation of MPEG-4 video streams by employing combination of frame dropping and DCT coefficient dropping. Furthermore, we present a descriptor, which has been accepted as a part of MPEG-21 Digital Item Adaptation (DIA), for supporting terminal and network quality of service (QoS) in an interoperable manner. Experiments are presented to demonstrate the feasibility of the presented framework using the descriptor.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.109-135
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• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

• Journal of Nutrition and Health
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• v.56 no.5
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• pp.573-588
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• 2023

Purpose: This study aimed to examine social networking service (SNS) use and recommended information utilization (SURU) according to the food-related lifestyles (FRLs) of consumers and analyze how the interaction between the FRL and SURU affects the practice of eating alone and visiting restaurants. Methods: Data on 4,624 adults in their 20s to 50s were collected from the 2021 Consumer Behavior Survey for Food. Statistical methods included factor analysis, K-means cluster analysis, the complex samples general linear model, the complex samples Rao-Scott χ² test, and the general linear model. Results: The following three factors were extracted from the FRL data: Convenience pursuit, rational consumption pursuit, and gastronomy pursuit, and the subjects were classified into three groups, namely the rational consumption, convenient gastronomy, and smart gourmet groups. An examination of the difference in SURU according to the FRL showed that the smart gourmet group had the highest score. The result of analyzing the effects of the FRL and SURU on eating alone revealed that both the main effect and the interaction effect were significant (p < 0.01, p < 0.001). The higher the SURU, the higher the frequency of eating alone in the convenience pursuit, and gastronomy pursuit groups. The main and interaction effects of the FRL and SURU on the frequency of eating out were also significant (p < 0.01, p < 0.001). In all the FRL groups, the higher the SURU level, the higher the frequency of visiting restaurants. Specifically, the two groups with convenience and gastronomic tendencies showed a steeper increase. Conclusion: This study provides important basic data for research on consumer behavior related to food SNS, market segmentation of restaurant consumers, and development of marketing strategies using SNS in the future.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.