• The Korean Journal of Mycology
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• v.47 no.2
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• pp.125-130
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• 2019

A fungal isolate, designated KNU-JJ-1824, was isolated from a soil sample collected from a field on Jeju, Korea. Colonies of the isolates cultured on PDA, MEA and CMAD for 14 days grew to diameters of 49~51 mm, 60~63 mm, and 47~50 mm, respectively. The colonies of this fungal isolate were dark green in color on both sides, and had irregular margins on the PDA media. Mycelia submerged and exhibited clear lines from the center to the edge on MEA media. On CMAD media, they were dark brown to greenish-brown, with narrow white margins. The shape of the conidia was guttulate, fusiform or clavate, and $1.9{\sim}3.4{\times}6.5{\sim}10.2{\mu}m$ in size. A molecular phylogenetic tree was constructed using dataset from small subunit (SSU) rDNA and the internal transcribed spacer (ITS) regions, and the isolate was found to cluster with Scleroconidioma sphagnicola UAMH 9731. Based on the results of the phylogenetic tree analysis and the cultural and morphological characteristics, the isolate was identified as Scleroconidioma sphagnicola. We report S. sphagnicola for the first time in Korea.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.427-439
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• 2019

This study investigated the semantic network based on the focus of the fashion image and SNS text utilized by global SPA brands on the last seven years in terms of the quantity and quality of data generated by the fast-changing fashion trends and fashion content-based media environment. The research method relocated frequency, density and repetitive key words as well as visualized algorithms using the UCINET 6.347 program and the overall classification of the text related to fashion images on social networks used by global SPA brands. The conclusions of the study are as follows. A common aspect of global SPA brands is that by looking at the basis of text extraction on SNS, exposure through image of products is considered important for sales. The following is a discriminatory aspect of global SPA brands. First, ZARA consistently exposes marketing using a variety of professions and nationalities to SNS. Second, UNIQLO's correlation exposes its collaboration promotion to SNS while steadily exposing basic items. Third, in the case of H&M, some discriminatory results were found with other brands in connectivity with each cluster category that showed remarkably independent results.

• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.603-615
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• 2021

The aim of this study was to analyze the semantic network structure of keywords and the visual composition of images extracted from Instagram in relation to the multi-persona phenomenon with in fashion imagery, which has recently been attracting attention. To this end, the concept of a 'secondary character', which forms a separate identity from a 'main character' on various social media platforms as well as on the airwaves, was considered as the spread of multi-persona and #SecondaryCharacter on Instagram was investigated. 3,801 keywords were collected after crawling the data using Python and morphological analysis was undertaken using KoNLP. The semantic network structure was then examined by conducting a CONCOR analysis using UCINET and Netdraw to determine the top 50 keywords. The results were then classified into a total of 6 clusters. In accordance with the meaning and context of the keywords included in each cluster, group names were assigned : virtual characters, relationship with the main character, hobbies, daily record, N-job person, media and marketing. Image analysis considered the technical, compositional, and social styles of the media based on Gillian Rose's visual analysis method. The results determined that Instagram uses fashion images that virtualize one's face to produce multi-persona representation s that show various occupations, describe different types of hobbies, and depict situations pertaining to various social roles.

• The Research Journal of the Costume Culture
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• v.20 no.4
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• pp.500-514
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• 2012

The purpose of this study was to classify the lifestyles of 20's unmarried women, identify the differences among the lifestyle groups, and analyze sportswear purchase behaviors and brand loyalty according to the lifestyle types. The subjects were 312 single women who had purchased sportswear. The questionnaire consisted of measurement items for lifestyle, purchase behaviors, brand loyalty and demographic attributions. The data were analyzed by Cronbach's ${\alpha}$, factor analysis, cluster analysis, ANOVA, ${\chi}^2$-test and Duncan's multiple range test, using SPSS 18.0 program. The results of the study were as follows. First, as a result of cluster analysis to classify the lifestyles of 20's single women, 4 groups were identified as practical and advanced-media-usage type, adventurous and self-actualizing type, enthusiastic-fashion seeking type, active and leisure-oriented type. Second, 3 factors of brand loyalty were classified as continuous brand loyalty, habitual brand loyalty and no brand loyalty. Third, upon analyzing the differences of brand loyalty based on lifestyles, practical and advanced-media-usage type and enthusiastic-trend seeking type showed no brand loyalty. Forth, 4 groups showed different sportswear purchase behaviors, such as purchase motivation, information sources, purchase frequency, purchase cost of one time, purchase place, the number of possession and purchase items.

• Journal of KIISE:Information Networking
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• v.32 no.6
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• pp.659-667
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• 2005

A Mobile Ad Hoc Network(MANET) is a multi hop wireless network with no prepared base stations or centralized administrations, where flocks of peer systems gather and compose a network. Each node operates as a normal end system in public networks. In addition to it, a MANET node is required to work as a router to forward traffic from a source or intermediate node to others. Each node operates as a normal end system in public networks, and further a MANET node work as a router to forward traffic from a source or intermediate node to the next node via routing path. Applications of MANET are extensively wide, such as battle field or any unwired place; however, these are exposed to critical problems related to network management, node's capability, and security because of frequent and dynamic changes in network topology, absence of centralized controls, restricted usage on network resources, and vulnerability oi mobile nodes which results from the special MANET's character, shared wireless media. These problems induce MANET to be weak from security attacks from eavesdropping to DoS. To guarantee secure authentication is the main part of security service In MANET because networks without secure authentication are exposed to exterior attacks. In this paper, a multistage authentication strategy based on CGSR is proposed to guarantee that only genuine and veritable nodes participate in communications. The proposed authentication model is composed of key manager, cluster head and common nodes. The cluster head is elected from secure nodes, and key manager is elected from cluster heads. The cluster head will verify other common nodes within its cluster range in MANET. Especially, ID of each node is used on communication, which allows digital signature and blocks non repudiation. For performance evaluation, attacks against node authentication are analyzed. Based on security parameters, strategies to resolve these attacks are drawn up.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2827-2848
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• 2012

Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.

• The KIPS Transactions:PartA
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• v.8A no.3
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• pp.217-226
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• 2001

In this paper, for continuous media access operations performed by Clustered Continuous Media Storage Server (CCMSS) system, we present the analytical model based on the open queueing network, which considers simultaneously two critical delay factors, the disk I/O and the internal network, in the CCMSS system. And we derive by using the analytical model the stochastic model for the total service delay time in the system. Next, we propose the integrated stochastic admission control model for the CCMSS system, which estimate the maximum number of admittable service requests at the allowable service failure rate by using the derived stochastic model and apply the derived number of requests in the admission control operation. For the performance evaluation of the proposed model, we evaluated the deadline miss rates by means of the previous stochastic model considering only the disk I/O and the propose stochastic model considering the disk I/O and the internal network, and compared the values with the results obtained from the simulation under the real cluster-based distributed media server environment. The evaluation showed that the proposed admission control policy reflects more precisely the delay factors in the CCMSS system.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.444-454
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• 2015

The purpose of this study is to investigate factors related to use-diffusion of Nscreen service as well as consumers' lifestyle and media usage of Nscreen service, which is fundamentally changing both the competitive landscape for business and the daily lives of consumers. The data of 1,524 consumers used in this study were drawn from the first Korea Media Panel Study in 2012 of Korea Information Society Development Institute. This study categorized adopters depending on the usage rate of contents and the variety of media platforms they used. Consumers using various media platforms enjoyed more categories of contents provided by Nscreen services. The variety of media platforms was useful in grouping users to explain the difference between the groups in terms of lifestyle activities. Based on the factor analysis and cluster analysis based on the consumers' lifestyle to find out different characteristics of each clusters, the result elicited some implications.

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.806-816
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• 2017

Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.123-131
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• 2019

In this study, we modified CT images of femoral head in consideration of anatomically meaningful structure, proposing the method to augment the training data of convolution Neural network for segmentation of femur mesh model. First, the femur mesh model is obtained from the CT image. Then divide the mesh model into meaningful parts by using cluster analysis on geometric characteristic of mesh surface. Finally, transform the segments by using an appropriate mesh deformation algorithm, then create new CT images by warping CT images accordingly. Deep learning models using the data enhancement methods of this study show better image division performance compared to data augmentation methods which have been commonly used, such as geometric conversion or color conversion.