• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.643-650
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• 2009

As one of typical techniques for acquiring bio-information, microarray has contributed greatly to development of bioinformatics. Although it is established as a core technology in bioinformatics, it has difficulty in sharing and storing data because data from experiments has huge and complex type. In this paper, we propose a new method which uses the feature that microarray data format in MAGE-ML, a standard format for exchanging data, has frequent structurally similar patterns. This method constructs compact database by simplifying MAGE-ML schema. In this method, Inlining techniques and newly proposed classification techniques using structural similarity of elements are used. The structure of database becomes simpler and number of table-joins is reduced, performance is enhanced using this method.

• 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 Information Science Theory and Practice
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• v.12 no.3
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• pp.49-62
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• 2024

Strategy monitoring is essential for business management and for administrators, including managers and executives, to build a data-driven organization. Having a tool that is able to visualize strategic data is significant for business intelligence. Unfortunately, there are gaps between business users and information technology departments or business intelligence experts that need to be filled to meet user requirements. For example, business users want to be self-reliant when using business intelligence systems, but they are too inexperienced to deal with the technical difficulties of the business intelligence systems. This research aims to create an automatic matching framework between the key performance indicators (KPI) formula and the data in database systems, based on ontology concepts, in the case study of Prince of Songkla University. The mapping data schema with ontology (MapDSOnto) framework is created through knowledge adaptation from the literature review and is evaluated using sample data from the case study. String similarity methods are compared to find the best fit for this framework. The research results reveal that the "fuzz.token_set_ratio" method is suitable for this study, with a 91.50 similarity score. The two main algorithms, database schema mapping and domain schema mapping, present the process of the MapDS-Onto framework using the "fuzz.token_set_ratio" method and database structure ontology to match the correct data of each factor in the KPI formula. The MapDS-Onto framework contributes to increasing self-reliance by reducing the amount of database knowledge that business users need to use semantic business intelligence.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.6
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• pp.363-368
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• 2017

The tsunami flood the coastal cities and damage the land structures. The study on wave pressure and force on land structures is one of the important factors in designing the stability of inland structures. In this study, two - dimensional wave flume tests on the horizontal wave force and pressure of tsunamis on a simplified box-type structure was conducted. Vertical distribution and wave power of horizontal wave pressure over time were measured by pressure sensors and force transducer. Also, those were measured from the different wave breaking types. The vertical distribution of horizontal wave pressure was uniform at the moment when the horizontal wave force to the structure was maximum under the breaking wave condition. A surf similarity parameter was employed in order to figure out the relationship between the maximum horizontal wave force on the structure as a function of various incident wave conditions. As a result, the non - dimensionalized horizontal wave force tends to decrease exponentially as the surf similarity parameter increases.

• Ocean and Polar Research
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• v.33 no.2
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• pp.159-169
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• 2011

Antifreeze proteins (AFPs) have ice binding affinity, depress freezing temperature and inhibit ice recystallization which protect cellular membranes in polar organisms. Recent structural studies of antifreeze proteins have significantly expanded our understanding of the structure-function relationship and ice crystal growth inhibition. Although AFPs (Type I-IV AFP from fish, insect AFP and Plant AFP) have completely different fold and no sequence homology, they share a common feature of their surface area for ice binding property. The conserved ice-binding sites are relatively flat and hydrophobic. For example, Type I AFP has an amphipathic, single ${\alpha}$-helix and has regularly spaced Thr-Ala residues which make direct interaction with oxygen atoms of ice crystals. Unlike Type I AFP, Type II and III AFP are compact globular proteins that contain a flat ice-binding patch on the surface. Type II and Type III AFP show a remarkable structural similarity with the sugar binding lectin protein and C-terminal domain of sialic acid synthase, respectively. Type IV is assumed to form a four-helix bundle which has sequence similarity with apolipoprotein. The results of our modeling suggest an ice-binding induced structural change of Type IV AFP. Insect AFP has ${\beta}$-helical structure with a regular array of Thr-X-Thr motif. Threonine residues of each Thr-X-Thr motif fit well into the ice crystal lattice and provide a good surface-surface complementarity. This review focuses on the structural characteristics and details of the ice-binding mechanism of antifreeze proteins.

• Korean Journal of Cognitive Science
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• v.10 no.4
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• pp.71-83
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• 1999

Conventional symbolic inference systems lack flexibility because they do not well reflect flexible semantic structure of knowledge and use symbolic logic for their basic inference mechanism. For solving this problem. we have recently proposed the 'Connectionist Semantic Network(CSN)' as a model for flexible knowledge representation and inference based on neural networks. The CSN is capable of carrying out both approximate reasoning and commonsense reasoning based on similarity and association. However. we have difficulties in representing general and structured high-level knowledge and variable binding using the connectionist framework of the CSN. In this paper. we propose a hybrid system called SymCSN(Symbolic CSN) that combines a symbolic module for representing general and structured high-level knowledge and a connectionist module for representing and learning low-level semantic structure Simulation results show that the SymCSN is a plausible model for human-like flexible knowledge representation and inference.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.137-147
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• 2010

A blog is a website, usually maintained by an individual, with regular entries of commentary, descriptions of events, or other material such as graphics or video. Entries are commonly displayed in reverse chronological order. Blog search engines, like web search engines, seek information for searchers on blogs. Blog search engines sometimes output unsatisfactory results, mainly due to spam blogs or splogs. Splogs are blogs hosting spam posts, plagiarized or auto-generated contents for the sole purpose of hosting advertizements or raising the search rankings of target sites. This thesis focuses on splog detection. This thesis proposes a new splog detection method, which is based on blog post structure similarity and posting count per day. Experiments based on methods proposed a day show excellent result on splog detection tasks with over 90% accuracy.

• Wind and Structures
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• v.25 no.1
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• pp.1-24
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• 2017

This paper presents a 1:25 multi-freedom aero-elastic model for a high lighting pole at the Zhoushan stadium. To validate the similarity characteristics of the model, a free vibration test was performed before the formal test. Beat phenomenon was found and eliminated by synthesis of vibration in the X and Y directions, and the damping ratio of the model was identified by the free decay method. The dynamic characteristics of the model were examined and compared with the real structure; the similarity results were favorable. From the test results, the major along-wind dynamic response was the first vibration component. The along-wind wind vibration coefficient was calculated by the China code and Eurocode. When the peak factor equaled 3.5, the coefficient calculated by the China code was close to the experimental result while Eurocode had a slight overestimation of the coefficient. The wind vibration coefficient during typhoon flow was analyzed, and a magnification factor was suggested in typhoon-prone areas. By analyzing the power spectrum of the dynamic cross-wind base shear force, it was found that a second-order vortex-excited resonance existed. The cross-wind response in the test was smaller than Eurocode estimation. The aerodynamic damping ratio was calculated by random decrement technique and the results showed that aerodynamic damping ratios were mostly positive at the design wind speed, which means that the wind-induced galloping phenomenon is predicted not to occur at design wind speeds.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.610-617
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• 2003

Similarity matching in video database is of growing importance in many new applications such as video clustering and digital video libraries. In order to provide efficient access to relevant data in large databases, there have been many research efforts in video indexing with diverse spatial and temporal features. however, most of the previous works relied on sequential matching methods or memory-based inverted file techniques, thus making them unsuitable for a large volume of video databases. In order to resolve this problem, this paper proposes an effective and scalable indexing technique using a trie, originally proposed for string matching, as an index structure. For building an index, we convert each frame into a symbol sequence using a window order heuristic and build a disk-resident trie from a set of symbol sequences. For query processing, we perform a depth-first search on the trie and execute a temporal segmentation. To verify the superiority of our approach, we perform several experiments with real and synthetic data sets. The results reveal that our approach consistently outperforms the sequential scan method, and the performance gain is maintained even with a large volume of video databases.

• Journal of Forest and Environmental Science
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• v.30 no.1
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• pp.167-178
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• 2014

The populations of Pinus densiflora in South Korea were grouped into 4 types; Community of Pinus densiflora-Quercus serrata, Community of Pinus densiflora-Quercus mongolica, Community of Pinus densiflora-Fraxinus sieboldiana & Rhus javanica & Quercus mongolica and Community of Pinus densiflora-Prunus sargentii & Rhododendron mucronulatum. The Shannon diversity index was varied between 0.9171 and 1.5016, while the Similarity index was varied between 43.18 and 72.16. The species of Pinus densiflora are correlated positively significant with Carex humilis var. nana, Quercus serrata and Atractylodes ovata and negatively significant with Aster scaber and Sorbus alnifolia in order. According to the Correlation analysis, the relationship between the distribution of Pinus densiflora populations and the environment factors are closely related with the character of forest soil. Thus types for Pinus densiflora are differed. pH, Ex. K and Ex. Ca of Pinus densiflora populations effect No. of species and H'(shannon index). Canopy open effects No. of Individuals of Pinus densiflora community.