• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.173-186
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• 2013

Web-based map services provide various geographic information that users want to get by continuous updating of data. Those map services provide different information for a geographic object respectively. It causes several problems, and most of all various information cannot be integrated and provided. To resolve the problem, this paper proposes a system which can integrate diverse geographic information and provide users rich geographic information. In this paper, a hybrid schema matching (HSM) algorithm is proposed and the algorithm is a mixture of the adapter-based semantic processing method, static semantic management-based approach, and dynamic semantic management-based approach. A comparative evaluation is described to show effectiveness of the proposed algorithm. The proposed algorithm in this paper improves the accuracy of schema matching because of registration and management of schemas of new semantic information. The proposal enables vocabulary-based schema matching using various schemas, and it thus also supports high usability. Finally, the proposed algorithm is cost-effective by providing the progressive extension of relationships between schema meanings.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.51-64
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• 2017

After Bitcoin was proposed by Satoshi Nakamoto in 2009, studies have been carried out to apply the Block Chain technology in various environment, which was applied as a distributed transaction of Bitcoin. Smart contracts, voting and proof of ownership of digital contents are typical applications of Block Chain. They used the feature that it is impossible to modify or delete once recorded facts. They also applied to prove relevant facts and to provide data integrity. The applied cases are mainly made in an environment where the data should or could be open to the public, and they have been proposed as solutions to solve the problems occurred in relations. This fact has led to the attention that Block Chain can be applied as a good alternative in similar circumstances. In this study, real estate market service was selected to expand the application range of Block Chain. Although there are about 250 applications and web services in total, the satisfaction is not high due to false offerings. Thus we propose a countermeasure against the problem by applying the Block Chain to the real estate market service, and investigate the research direction of the Block Chain in the future market.

• Journal of KIISE:Databases
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• v.33 no.6
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• pp.600-619
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• 2006

According to recent technical advances on sensors and mobile devices, processing of data streams generated by the devices is becoming an important research issue. The data stream of real values obtained at continuous time points is called streaming time-series. Due to the unique features of streaming time-series that are different from those of traditional time-series, similarity matching problem on the streaming time-series should be solved in a new way. In this paper, we propose an efficient algorithm for streaming time- series matching problem that supports normalization transform. While the existing algorithms compare streaming time-series without any transform, the algorithm proposed in the paper compares them after they are normalization-transformed. The normalization transform is useful for finding time-series that have similar fluctuation trends even though they consist of distant element values. The major contributions of this paper are as follows. (1) By using a theorem presented in the context of subsequence matching that supports normalization transform[4], we propose a simple algorithm for solving the problem. (2) For improving search performance, we extend the simple algorithm to use $k\;({\geq}\;1)$ indexes. (3) For a given k, for achieving optimal search performance of the extended algorithm, we present an approximation method for choosing k window sizes to construct k indexes. (4) Based on the notion of continuity[8] on streaming time-series, we further extend our algorithm so that it can simultaneously obtain the search results for $m\;({\geq}\;1)$ time points from present $t_0$ to a time point $(t_0+m-1)$ in the near future by retrieving the index only once. (5) Through a series of experiments, we compare search performances of the algorithms proposed in this paper, and show their performance trends according to k and m values. To the best of our knowledge, since there has been no algorithm that solves the same problem presented in this paper, we compare search performances of our algorithms with the sequential scan algorithm. The experiment result showed that our algorithms outperformed the sequential scan algorithm by up to 13.2 times. The performances of our algorithms should be more improved, as k is increased.

• Journal of the Korea Computer Graphics Society
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• v.26 no.1
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• pp.17-25
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• 2020

We present a novel multi-core CPU based parallel algorithm for the cell-connectivity information extraction algorithm, which is one of the preprocessing steps for volume rendering of unstructured grid data. We first check the synchronization issues when parallelizing the prior serial algorithm naively. Then, we propose a 3-step parallel algorithm that achieves high parallelization efficiency by removing synchronization in each step. Also, our 3-step algorithm improves the cache utilization efficiency by increasing the spatial locality for the duplicated triangle test process, which is the core operation of building cell-connectivity information. We further improve the efficiency of our parallel algorithm by employing a memory pool for each thread. To check the benefit of our approach, we implemented our method on a system consisting of two octa-core CPUs and measured the performance. As a result, our method shows continuous performance improvement as we add threads. Also, it achieves up to 82.9 times higher performance compared with the prior serial algorithm when we use thirty-two threads (sixteen physical cores). These results demonstrate the high parallelization efficiency and high cache utilization efficiency of our method. Also, it validates the suitability of our algorithm for large-scale unstructured data.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.2
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• pp.267-277
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• 2017

One of fundamental problems in developing robust distributed services is how to achieve distributed consensus agreeing some data values that should be shared among participants in a distributed service. As one of algorithms for distributed consensus, Raft is known as a simple and understandable algorithm by decomposing the distributed consensus problem into three subproblems(leader election, log replication and safety). But, the algorithm dose not mention any types of dynamic configuration of participant peers such as adding new peers to a consensus group or deleting peers from the group. In this paper, we present a new consensus algorithm named Raft-D, which supports the dynamic configuration of participant peers by extending the Raft algorithm. For this, Raft-D manages the additional information maintained by participant nodes, and provides a technique to check the connection status of the nodes belonging to the consensus group. Based on the technique, Raft-D defines conditions and states to deal with adding new peers to the consensus group or deleting peers from the group. Based on those conditions and states, Raft-D performs the dynamic configuration process for a consensus group through the log update mechanism of the Raft algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.414-426
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• 2018

The purpose of this study is to conceptualize reading capital in the career context and to provide basic data for further study by exploring the components of reading capital. For this purpose, previous studies and literature were reviewed. In addition, we conducted big data analysis regarding 209 papers concerning various activities related to reading, and explored the components of reading capital. Through this study, reading capital can express personal, intangible ability such as literacy, experience, and attitude embodied through reading, and enable understanding persons, looking at the world positively, and creating personal, social and economic values. The components of reading capital are reading competency and humanistic knowledge; the former was conceptualized to be reading literacy, reading activity, reading attitude, reading ability, and the latter was conceptualized to be emotional intelligence, relationship, self-identity, creativity, adaptability, self-directedness and values. The definitions and components researched of the reading capital derived through this study are thought to be highly useful as basic data for the expansion of research between related studies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.49-63
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• 2008

RDF is the base ontology model which is used in Semantic Web defined by W3C. OWL expands the RDF base model by providing various vocabularies for defining much more ontology relationships. Recently Jain and Farkas have suggested an RDF access control model based on RDF triple. Their research point is to introduce an authorization conflict problem by RDF inference which must be considered in RDF ontology data. Due to the problem, we cannot adopt XML access control model for RDF, although RDF is represented by XML. However, Jain and Farkas did not define the authorization propagation over the RDF upper/lower ontology concepts when an RDF authorization is specified. The reason why the authorization specification should be defined clearly is that finally, the authorizatin conflict is the problem between the authorization propagation in specifying an authorization and the authorization propagation in inferencing authorizations. In this article, first we define an RDF access authorization specification based on RDF triple in detail. Next, based on the definition, we analyze the authoriztion conflict problem by RDF inference in detail. Next, we briefly introduce a method which can quickly find an authorization conflict by using graph labeling techniques. This method is especially related with the subsumption relationship based inference. Finally, we present a comparison analysis with Jain and Farkas' study, and some experimental results showing the efficiency of the suggested conflict detection method.

• Design Convergence Study
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• v.16 no.6
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• pp.169-184
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• 2017

There is a lot of needs that are not expressed as much as the expressed needs in familiar products and services that are used in daily life such as a smartphone. Finding the 'Inconveniences in familiar use' make it possible to create opportunities for value expanding in the existing products and service area. There are a lot of related works, which have studied the definition of hidden needs and the methods to find it. But, they are making it difficult to address the hidden needs in the cases of familiar use due to focus on the new product or service developing typically. In this study, we try to redefine the hidden needs in the daily familiarity and approach it in the new way to find out. Because of the users' unability to express what they want and the complexity of needs which can not be explained clearly, we can not approach it as the quantitative issue. For this reason, the basic data type selected as the user behavior data excluding all description is the screen-shot of the smartphone. We try to apply the integrated rules and patterns to the individual data using the qualitative coding techniques to overcome the limitations of qualitative analysis based on unstructured data. From this process, We can not only extract meaningful clues which can make to understand the hidden needs but also identify the possibility as a way to discover hidden needs through the review of relevance to actual market trends. The process of finding hidden needs is not easy to systemize in itself, but we expect the possibility to be conducted a reference frame for finding hidden needs of other further studies.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.462-477
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• 2021

The purpose of this study was to understand changes in domestic forest policy and social perception of forests from a macro perspective using big data analysis of news articles and editorials. A total of 13,570 'forest' related data were collected from metropolitan and economic journals from 1946-2017 using keyword and CONCOR (Convergence of iterated Correlations) analysis. First, we found the percentage of articles and editorials using the keyword 'forest'increased overall. Second, news data on 'forest' in the field of reporting was concentrated in the "social" sector during the first period (1946-1966), followed by forest-related issues expanding to various fields from the second (1967-1972) to fifth (1988-1997) periods, then toward the "culture" sector in the sixth (1998-2007) and "politics" after the seventh (2008-2017) period. Third, we found changes in the policy paradigm over time significantly changed social awareness. In the first and second periods, people experienced livelihood issues rather than forest greening or forest protection policy and expanded their awareness of planned and scientific afforestation (third) to environmental protection (fourth) and ecological perspectives (sixth to seventh). The key outcome of our analysis was leveraging news big data that reflected polices on forests and public social perception To further derive future social issues,more in-depth analysis of public discourse and perception will be possible using textual big data and GDP of various social network services (SNS), such as combining blogs and YouTube.

• Korea Journal of Hospital Management
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• v.26 no.4
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• pp.12-28
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• 2021

Purposes: The convenience of smartphones have lead to people's overdependence on devices, which may cause obstacles in daily life. It is useful to manage smartphone overdependence by using mobile health applications. We aimed to investigate the acceptance of mobile health applications designed to help in the management of smartphone overdependence. Methodology/Approach: We developed the extended model based on the Unified Theory of Acceptance and Use of Technology 2. The modified model had six hypotheses with six variables: result demonstrability, performance expectancy, effort expectancy, social influence, perceived risk, and behavioral intention to use. We randomly included 425 smartphone users in an online survey in 2020. A structural equation model was used to estimate the significance of the path coefficients. Findings: Performance expectancy and social influence had a very strong direct positive association with behavioral intention to use. Result demonstrability had a direct positive association with performance expectancy. Perceived risk had a strong direct negative association with performance expectancy. Performance expectancy and social influence were the main factors directly influencing the acceptance of mobile health applications for the management of smartphone overdependence. Practical Implications: We demonstrated smartphone users' acceptance of mobile health applications for smartphone overdependence management. Based on these results, we could develop mobile health applications more effectively.