• 한국의상디자인학회지
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• 제21권3호
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• pp.161-172
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• 2019

This study examines the characteristics and recent changes of the Hanbok industrial cluster in Gwangju Metropolitan City, in order to understand the problems in the activation of the Hanbok industry and to seek future policies. A total 32 companies comprise the 'Small Manufacturer Specialized Support Center of Hanbok' and were surveyed with a 41 questions with questions in four categories. The Gwangju Hanbok area has been in existence for more than 40 years and was composed of small groups of one or two manufacturers. They are experiencing the same difficulties as other Hanbok clusters, such as the aging of workers, the downturn of dress culture, and changing consumption paradigms. However, since 2015, various efforts have been made in order to seek countermeasures to cope with such difficulties, particularly with the foundation of the 'Small Manufacturer Specialized Support Center of Hanbok' with the support of the Ministry of Small Venture Business. This study focuses on the alterations in the current Hanbok industry due to the IT industrialization as well as the changes in the locations of the Hanbok clusters due to the revitalization of old towns by local governments., The results providing an opportunity to appreciate the problems therein and seek the solutions. Small manufacturers of the Hanbok cluster are trying to improve their entrepreneurship, digital technology application, and knowledge in accordance with the socio-economic trends, but they have limitations to practically apply it to business, barely keeping the minimum production base. The central government and the Gwangju should reinforce and expand the support for marketing and public relations for the Hanbok to foster the designer population, to establish mutual brands, to raise brand awareness, and to promote the technological perfection of the individual businesses, to allow them to cope with the current market trends, in order for the technological development and firm settlement of the local Hanbok industrial cluster.

• 디지털산업정보학회논문지
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• 제20권1호
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• pp.17-29
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• 2024

The Gyeongin Ara Waterway is a regional development project designed to transport cargo by sea and to utilize the surrounding waterfront area to enjoy tourism and leisure. It is being used as a space for demonstration projects for urban air transportation (UAM), which has recently been attracting attention, and various efforts are being made at the local level to strengthen cultural and tourism functions and revitalize local food. This study examined the perception and trends of tourism consumers on the Gyeongin Ara Waterway before and after the outbreak of COVID-19. The research method utilized semantic network analysis based on social network analysis. As a result of the study, first, before the outbreak of COVID-19, key words such as bicycle, Han River, riding, Gimpo, Seoul, hotel, cruise ship, Korea Water Resources Corporation, emotion, West Sea, weekend, and travel showed a high frequency of appearance. After the outbreak of COVID-19, keywords such as cafe, discovery, women, Gimpo, restaurant, bakery, observatory, La Mer, and cruise ship showed a high frequency of appearance. Second, the results of the degree centrality analysis showed that before the outbreak of COVID-19, there was increased interest in accommodations for tourism, such as Marina Bay and hotels. After the outbreak of COVID-19, interest in food such as specific bakeries and cafes such as La Mer was found to be high. Third, due to the CONCOR analysis, five keyword clusters were formed before the outbreak of COVID-19, and the number of keyword clusters increased to eight after the outbreak of COVID-19.

• 디지털산업정보학회논문지
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• 제5권3호
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• pp.69-75
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• 2009

In this paper, we proposed CPLD low power algorithm using reduce glitch power consumption. Proposed algorithm generated a feasible cluster by circuit partition considering the CLB condition within CPLD. Glitch removal process using delay buffer insertion method for feasible cluster. Also, glitch removal process using same method between feasible clusters. The proposed method is examined by using benchmarks in SIS, it compared power consumption to a CLB-based CPLD low power technology mapping algorithm for trade-off and a low power circuit design using selective glitch removal method. The experiments results show reduction in the power consumption by 15% comparing with that of and 6% comparing with that of.

• 대한산업공학회지
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• 제39권5호
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• pp.412-421
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• 2013

Motion picture industry is one of the most representative fields in the cultural industry and has experienced constant growth both worldwide and within domestic markets. However, little research has been undertaken for diffusion patterns of motion pictures, whereas various issues such as demand forecasting and success factor analysis have been widely explored. To analyze diffusion patterns, we adopted extended Bass model to reflect the potential demand of movies. Four clusters of selected movies were derived by k-means clustering method with criteria of opening strength and profitability and then compared by their diffusion patterns. Results indicated that movies with high profitability and medium opening strength are most significantly influenced by word of mouth effect, while low profitability movies display nearly monotonic decreasing diffusion patterns with noticeable initial adoption rates and relatively early peak points in their runs.

• 한국의류산업학회지
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• 제11권5호
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• pp.779-787
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• 2009

The purpose of this study was to classify the head shape for the apparel industry and to suggest standard head model for korean women. The 23 measurement items of 891 females, aged more than 18 years were used to analysis by statistical methods. Factor analysis, cluster analysis and duncan test were performed using these data. Through factor analysis, 5 factors were extracted upon factor scores and those factors comprised 68.76% for the total variances. 5 clusters as their head and face shape were categorized. We decided for the type 3 to standard head shape. 24 participants were measured using computed tomography(CT). The measured data of skin and skeleton and the standard head shapes were illustrated.

• 디지털산업정보학회논문지
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• 제9권2호
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• pp.17-22
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• 2013

In this paper, we propose a concrete crack detection method using shape properties. It is based on morphology algorithm and crack features. We assume that an input image is contaminated by various noises. Thus, we use a morphology operator and extract patterns of crack. It segments cracks and background using opening and closing operations. Morphology based segmentation is better than existing integration methods using subtraction in detecting a crack it has small width. Also, it is robust to noisy environment. The proposed algorithm classifies the segmented image into crack and background using shape properties of crack. This method calculates values of properties such as the number of pixels and the maximum length of the segmented region. Also, pixel counts of clusters are considered. We decide whether the segmented region belongs to cracks according to those data. Experimental results show that our proposed crack detection method has better results than those by existing detection methods.

• 디지털산업정보학회논문지
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• 제6권4호
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• pp.11-20
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• 2010

Ontology is important role in semantic web to construct and query semantic data. Because of dynamic characteristic of ontology, P2P environment is considered for ontology processing in web environment. For efficient processing of ontology in P2P environment, clustering of peers should be considered. When new peer is added to the network, cluster allocation problem of the new peer is important for system efficiency. For clustering of peers with similar chateristics, similarlity measure method of ontology in added peer with ontologies in other clusters is needed. In this paper, we propose similarity measure techniques of ontologies for clustering of peers. Similarity measure method in this paper considered ontology's strucural characteristics like schema, class, property. Results of experiments show that ontologies of similar topics, class, property can be allocated to the same cluster.

• Asian Journal of Innovation and Policy
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• 제5권2호
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• pp.116-128
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• 2016

Value chain analysis has been applied in various fields, from the time the concept of “value chain” was introduced by Porter in 1985. Several frameworks have emerged and have been used to study individual firms, entire industries, industry clusters, as well as global production networks. The purpose of this paper is to provide a brief review of these frameworks, identify factors that influence the performance of value chains, and suggest areas for future research. Since there is a wide range of value chain literature, this paper focuses on a selective set of earlier works within the value chain model as conceptualized by Porter. The study takes note of the many dimensions and applications of value chain analysis, and shows that value chain analysis is an effective way to examine the interaction among different players in a given industry. The study further points out the shortcomings of the traditional or Porter view of value chain analysis.

• 디지털산업정보학회논문지
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• 제7권3호
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• pp.11-23
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• 2011

Recently, Open APIs are getting attention with the advent of Web 2.0. Open APIs are used to combine services and generate new services by Mashup. However, the growing number of available Open APIs raises a challenging issue how to locate the desired APIs. We automatically build ontologies from WSDL, WADL, HTML, and their underlying semantics. The key ingredient of our method is a technique that clusters input/output parameters in the collection of API methods into semantically meaningful concepts, and captures the hierarchical relationships between the terms contained in a parameter. These semantic ontologies allow search engines to support a similarity search for Open APIs based on various protocols such as SOAP, REST, JavaScript, and XML-RPC, and significantly improve the quality of APIs matching by the clustering and hierarchical relationships mechanism.

• 디지털산업정보학회논문지
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• 제13권2호
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• pp.77-85
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• 2017

Due to the expansion of accommodation space caused by increase of population along with lifestyle changes, most of people spend their time indoor except for the travel time. Because of this, environmental change of indoor is very important, and it affects people's health and economy in resources. But, most of people don't acknowledge the importance of indoor environment. Thus, monitoring system for sustaining and managing indoor environment systematically is needed, and big data clusters should be used in order to save and manage numerous sensor data collected from many spaces. In this paper, we design a big data cluster for the indoor environment monitoring in order to store the sensor data and monitor unit of the huge building Implementation design big data cluster-based system for the analysis, and a distributed file system and building a Hadoop, HBase for big data processing. Also, various sensor data is saved for collection, and effective indoor environment management and health enhancement through monitoring is expected.