• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.153-160
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• 2009

This study investigated what factors influence the knowledge contribution in online communities. Based on the theoretical framework like self-presentation theory and organizational citizenship behavior theory, we developed the research model and proposed four hypotheses. In order to test our hypotheses with an empirical study, we have conducted a survey which resulted in 192 valid responses in the final sample. The PLS analysis results indicate that knowledge contribution is influenced by self-presentation, innovation, organizational citizenship behavior, and affection similarity of online community users. Practical implications of these findings and future research implications are also discussed.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.3
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• pp.492-510
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• 2023

The metaverse, an expansion of the real world, refers to a three-dimensional virtual world where daily life and economic activities can be conducted through avatars. This study examines the effect of avatar identification on metaverse immersion, vicarious pleasure, and fashion brand item sharing intention by subdividing avatar identification into similarity identification, wishful identification, and embodied presence. In addition, it investigates the difference in the influence relationship between avatar identification, immersion, and vicarious pleasure according to the degree of fashion involvement. The total of 319 participants were analyzed using SPSS 26.0 and AMOS 24.0. The results showed that similarity identification, wishful identification, and embodied presence had significant impacts on immersion and vicarious pleasure, influencing sharing intention. There was also a difference in the effect of avatar identification on consumer responses depending on fashion involvement. This study provides theoretical implications for experiential marketing and presents practical suggestions for developing metaverse marketing strategies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2103-2118
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• 2024

Chinese herbal slices (CHS) automated recognition based on computer vision plays a critical role in the practical application of intelligent Chinese medicine. Due to the complexity and similarity of herbal images, identifying Chinese herbal slices is still a challenging task. Especially, easily-confused CHS have higher inter-class and intra-class complexity and similarity issues, the existing deep learning models are less adaptable to identify them efficiently. To comprehensively address these problems, a novel tiny easily-confused CHS dataset has been built firstly, which includes six pairs of twelve categories with about 2395 samples. Furthermore, we propose a ResNeSt-CHS model that combines multilevel perception fusion (MPF) and perceptive sparse fusion (PSF) blocks for efficiently recognizing easilyconfused CHS images. To verify the superiority of the ResNeSt-CHS and the effectiveness of our dataset, experiments have been employed, validating that the ResNeSt-CHS is optimal for easily-confused CHS recognition, with 2.1% improvement of the original ResNeSt model. Additionally, the results indicate that ResNeSt-CHS is applied on a relatively small-scale dataset yet high accuracy. This model has obtained state-of-the-art easily-confused CHS classification performance, with accuracy of 90.8%, far beyond other models (EfficientNet, Transformer, and ResNeSt, etc) in terms of evaluation criteria.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5A
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• pp.441-450
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• 2006

Recently, with the exponential growth of the number of Internet users, IP traffic which occupies more than 90 percent of the entire Internet traffic affects significantly to the performance of networks. Therefore, the design of the self-similar traffic generator reflected the feature of IP traffic is very important to design the networks efficiently and evaluate the performance of it correctly. In this paper, we design the self-similar traffic generator using OPNET. In order to implement the self-similar characteristics, ON-OFF sources with Pateto distribution are employed and aggregated. The designed self-similarity traffic generator is evaluated and verified with R/S plot, variance time(VT) plot under the various offered loads and the number of sources. It is expected that the designed self-similar traffic generator can be put to practical use when wire or wireless networks is designed and verified as well as it can be useful to decide the specific parameter value for Internet traffic modeling.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.279-285
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• 2012

This study classified the categorization process of convergence products as a rule-based and a similarity-based categorization process. And we examined that how the categorization process was determined according to information types(visual vs. visual + verbal) about the components of two prototypes before convergence and thinking styles(holistic vs. analytic). The result of this study showed: (1) The rule-based categorization process appeared more in case of visual information with verbal information than only visual information. (2) Analytic thinkers chose a rule-based categorization process more than holistic thinkers. These findings provide the theoretical and practical implications to comprehend the categorization process of convergence products and the judgement for consideration set from various convergence products.

• Reproductive and Developmental Biology
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• v.28 no.1
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• pp.45-52
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• 2004

To search a new porcine pheromonal odorants, this research for biostimulation and role of pheromone was augmented by means of "control system technologies" to offer a potentially useful and practical way to improve reproductive efficiency in livestock species. Therefore the 13 physicochemical parameters such as similarity indice (S), hydrophobicity (logP) and van der Waals molecule volume (MV) etc. of 54 steroid analogues, which are analogous of substrate molecules, 5$\alpha$-androst-16-en-3-one (P1) and 5$\alpha$-androst-16-en-3-ol (P2) of lipocalin as receptor of pig pheromones were calculated and discussed. The physicochemical properties of these steroid analogues were mainly followed by steric dissimilar of A and D ring in steroid nucleus. And we found that from correlation with S values and MV constants of molecules, the more MV constants are small, the more S values tend to approach 1. Based on this results, the S-values of 4-androsten-3,17-dione (P1-1) and 5 $\alpha$ -androstan-3-one (P2-1) were 1.0, respectively. The two compounds of them were chosen because they showed the same value each other at a side of hydrophobicity, molar refractivity and molecular volume. It is expected that the new two compounds will be able to substitute for P1 and P2, porcine pheromonal odorants.

• The Journal of Industrial Distribution & Business
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• v.12 no.4
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• pp.35-51
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• 2021

Purpose: As the digital environment has expanded opportunity for consumers to acquire information from social media and social network services(SNS), With this environment, influencer has not only promoted products, but also participated in distribution and influencing on their followers. Despite the increasing interest in influencers, there has not been enough research on the structure of fashion influencer, relationship of immersion and purchase intention. This study examined the effects of fashion influencers' characteristics to the immersion of relationship with followers and purchase intention. Research design, data and methodology: For data collection, a pilot survey and the final survey were conducted. The pilot survey data was conducted to 50 female SNS users following fashion influencers. Based on the pilot tests, questionnaire was revised and the final survey was conducted online from august 22 to September 1, 2019 to female SNS users who have followed fashion influencer. A total of 408 data were collected, and exploratory factor analysis, correlation analysis, and structural equational modeling techniques were employed for the data analyses using AMOS 26.0 and SPSS 26.0. Results: First, five factors were extracted for the fashion influencers' characteristics: interactivity, similarity, reliability, expertise and attractiveness. Second, fashion influences' reliability, expertise, similarity, interactivity have a positive (+) effects on relationship immersion; however, attractiveness has no effect on relationship immersion with followers and fashion influencer. It was also determined that relationship immersion had positive (+) influences on purchase intention. The relationship immersion has been found to have a partially mediated effect and similarity has complete mediated effects between interactivity, reliability, and expertise of fashion influencers and purchasing intentions. In terms of fashion opinion leadership, it was found to have a significant influence on purchase intention only for low fashion leadership groups. Conclusions: The present study found the structural relationships among the influencer characteristics, relationship immersion and purchase intentions to provide framework for succeeding research. This research revealed academic association of intention of purchasing through use of fashion social media and fashion influencer marketing. The results also showed the practical implications that fashion influencers' expertise and reliability perceived by their followers are key determinants to success in influencer marketing.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.3
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• pp.29-45
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• 2022

For biodiversity conservation, the importance of beta-diversity which is changes in the composition of species according to environmental changes has become emphasized. However, given the systematic investigation of species distribution and the accumulation of large amounts of data in the Republic of Korea(ROK), research on the spatialization of beta-diversity using them is insufficient. Accordingly, this research investigated the applicability of the Generalized Dissimilarity Modeling(GDM) to ROK, which can predict and map the similarity of compositional turnover (beta-diversity) based on environmental variables. A brief overview of the statistical description on using GDM was presented, and a model was fitted using the flora distribution data(410,621points) from the National Ecosystem Survey and various environmental spatial data including climate, soil, topography, and land cover. Procedures and appropriated spatial units required to improve the explanatory power of the model were presented. As a result, it was found that geographical distance, temperature annual range, summer temperature, winter precipitation, and soil factors affect the dissimilarity of the vegetation community composition. In addition, as a result of predicting the similarity of vegetation composition across the nation, and classifying them into 20 and 100 zones, the similarity was high mainly in the central inland area, and tends to decrease toward the mountainous areas, southern coastal regions, and island including Jeju island, which means the composition of the vegetation community is unique and beta diversity is high. In addition, it was identified that the number of common species between zones decreased as the geographic distance between zones increased. It classified the spatial distribution of plant community composition in a quantitative and objective way, but additional research and verification are needed for practical application. It is expected that research on community-level biodiversity modeling in the ROK will be conducted more actively based on this study.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1217-1224
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• 2014

This paper provides a practical scaling method to solve an old problem for scaling and developing the speed and resistance of a model to full-scale submarine in fully submerged underwater test. In every experimental test in towing tank, water tunnel and wind tunnel, in the first step, the speed of a model should be scaled to the full-scale vessel (ship or submarine). In the second step, the obtained resistance of the model should be developed. For submarine, there are two modes of movement: surface and submerged mode. There is no matter in surface mode because, according to Froude's law, the ratio of speed of the model to the full-scale vessel is proportional to the square root of lengths (length of the model on the length of the vessel). This leads to a reasonable speed and is not so much for the model that is applicable in the laboratory. The main problem is in submerged mode (fully submerged) that there isn't surface wave effect and therefore, Froude's law couldn't be used. Reynold's similarity is actually impossible to implement because it leads to very high speeds of the model that is impossible in a laboratory and inside the water. According to Reynold's similarity, the ratio of speed of the model to the full-scale vessel is proportional to the ratio of the full-scale length to the model length that leads to a too high speed. This paper proves that there is no need for exact Reynold's similarity because after a special Reynolds, resistance coefficient remains constant. Therefore, there is not compulsion for high speeds of the model. For proving this finding, three groups of results are presented: two cases are based on CFD method, and one case is based on the model test in towing tank. All these three results are presented for three different shapes that can show; this finding is independent of the shapes and geometries. For CFD method, Flow Vision software has been used.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.406-415
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• 2005

Prosperity of Internet led to the web containing huge number of documents. Thus increasing importance is given to the web information retrieval technology that can provide users with documents that contain the right information they want. This paper proposes several techniques that are effective for the improvement of web information retrieval. Similarity between a document and the query is a major source of information exploited by conventional systems. However, we suggest a technique to make use of similarity between a sentence and the query. We introduce a technique to compute the approximate score of the sentence-query similarity even without a mature technology of natural language processing. It was shown that the amount of computation for this task is linear to the number of documents in the total collection, which implies that practical systems can make use of this technique. The next important technique proposed in this paper is to use stratification of documents in re-ranking the documents to output. It was shown that it can lead to significant improvement in performance. We furthermore showed that using hyper links, anchor texts, and titles can result in enhancement of performance. To justify the proposed techniques we developed a large scale web information retrieval system and used it for experiments.