• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.10
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• pp.763-774
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• 2019

A collaborative system supports collaboration among participants by providing functions such as group composition and management of data shared for collaboration. In recent years, research on collaborative services based on the blockchain technology has been done to guarantee the reliability of collaboration processes and outcomes. The diversity of the application domains in which collaborations are performed and the various characteristics of the participants in the collaboration group naturally leads to various forms of collaborative processes. In order for these processes to produce the desired outcome of the collaborative efforts, it is desirable to specify the appropriate collaborative process in advance, so that the participants can understand and agree on the process, carrying out the collaboration. In this paper, we propose a method to control flexible collaborative processes according to workflow specifications in the Ethereum-based collaborative service environment. The specification of the workflow for the designated task is stored in the Ethereum smart contract and the process of performing the task is controlled according to the stored workflow specification. For this, we introduce JSFlow which is a simple workflow specification method using JSON and an Ethereum library to utilize it.

• Management & Information Systems Review
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• v.38 no.1
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• pp.83-101
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• 2019

Blockchain is considered as an innovative technology along with Artificial Intelligence, Big Data, and Internet of Things. However, since the inception of the genesis of blockchain technology, the cryptocurrency Bitcoin, the technology is not utilized widely, not let alone disruptive applications. Most of the blockchain research deals with the cryptocurrency, general descriptions of the technology such as trend, outlook of the technology, explanation of component technology, and so on. There are no killer applications like Facebook or Google, of course. Reflecting on the slow adoption by businesses, we wanted know about the current status of the research on blockchain in Korea. The main purpose of this paper is to help business practitioners to identify the application of blockchain to enhance the competitiveness of their organization. To do that, we first use the framework by Iansiti et al (2017) and categorize the blockchain related articles published in Korea according to the framework. This is to provide a benchmark or cases of other organizations' adoption of blockchain technology. Second, based on the value proposition of blockchain applications, we suggest evolutionary paths for adopting them. Third, from the demand pull perspective of technology adoption for innovation, we propose applicable areas where blockchain applications can be introduced. Fourth, we use the value chain model to find out the appropriate domains of blockchain applications in the corporate value chains. And the five competitive forces models is adopted to find ways of lowering the power of forces by incorporating blockchain technology.

• Journal of The Korea Institute of Healthcare Architecture
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• v.27 no.2
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• pp.25-37
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• 2021

Purpose: The main purpose of this study is to develop an evaluation system using the weighted-values of various users and experts for the public space to apply Universal Design, and additionally to find out the commonalities and differences by comparing the importance of evaluation indicators between users and expert groups. Method: A one-sample t-test was conducted to verify that the components of the public space to universal design application are suitable as evaluation indicators, and AHP(analytic hierarchy process) was performed to derive weight-values for the evaluation system. Results: The importance-values for the total 23 facilities to be used as evaluation indicators were derived by multiplying the weighted-values of each sector, domain, and facility by the disabled, non-disabled, and experts. To summarize the results of overall importance-values derived from the AHP, The disabled showed high-rank weighted-values in facilities of building sector > park & recreation sector > cross domain and low-rank weighted-values for sidewalk and roadway domain. The non-disabled showed high-rank weighted-values in facilities of park & recreation sector > roadway domain > building sector > cross domain and low-rank weighted-values for sidewalk domain. Experts mainly showed high-rank weighted-values in the cross domain and in facilities related to entry and movement to the target space in all sectors and domains. However, it showed moderate importance-values in the sanitary space. The disabled who are restricted to movement have a high demand for universal design in buildings consisting of vertical moving line, and non-disabled people who are not limited to physical movement have a high demand for universal design in parks and recreation sector for increased leisure time. It means that experts are important to recognize the principles of making space because they value cross domain and the key spaces and facilities for suitable the purpose of use. In addition, it can be inferred that non-disabled people have a higher demand for safety than disabled people due to their high importance in roadway domain and facilities of safety and disaster prevention. Implications: The significance of this study is the establishment of a quantitative universal design evaluation system for public spaces considering the different perspectives of the disabled and the non-disabled.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.363-372
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• 2021

Aim of this study was to confirm the effect of teaching and learning methods on outcomes of learner according to learning style. For this, 22 of dental hygiene students(case group) was treated teaching & learning methods according to learning style while 24 of students(control group) was non treated. Pre-survey were performed before performance of program. Formative Evaluation(FE) was conducted in 2, 3 and 4 week of program respectively and summative evaluation(SE), survey of subject interest(SI) and learning motivation(LM) were conducted in 5 week. The result of study, FE, SI and LM after treatment were increased than before treatment in case group(p<0.05). SI and LM of case group were higher than control group(p<0.05). FE after treatment was increased than before treatment in he assimilator(p<0.05). SI and LM of case groups were higher than control group in assimilator and diverger(p<0.05). The result of correlation analysis, SI was related with SE, FE, LM(p<0.01, p<0.05). Thus, it is necessary to development, application and study of teaching & learning consider to learning style.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.315-325
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• 2021

The value and importance of Gamification has intensified as the way Gamification is applied to social networking applications has added to users' interest and involvement to the product. Gamification entails the adoption of gaming techniques and modes of thinking in non-gaming domains to elicit user engagement. To this end, the paper draws on Gamification's analytical model, Octalysis, with the aim of identifying user loyalty of the three major Chinese social networking applications and extracting their characteristics. In this regard, the first task in the advancement of the study is to establish an understanding of the components and characteristics of Gamification within the context of available examples. Next, a questionnaire survey covering China's three dominant social applications, WeChat, QQ, and Xiaohongshu, is administered and their user loyalty is examined through Octalysis's eight analytical frameworks. By virtue of analysis, the results demonstrate that the three elements of game mechanics, Point, Badge, and Leadboard, which are external to the game, fail to sustain the user loyalty, but are merely a means to an end. Only by including a combination of social application features, contents and user needs can Gamification considerations be maximized to ensure that users are subjectively engaged with the product.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.464-477
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• 2022

DFN (discrete fracture network) models that take account of spatial variability and correlation between rock fractures have been demanded for analysis of fractured rock mass behavior for wide areas with high reliability, such as that of underground nuclear waste repositories. In this regard, this report describes the spatial distribution characteristics of fracture networks, and the DFN modeling methodologies that aim to represent such characteristics. DFN modeling methods have been proposed to represent the spatial variability of rock fractures by defining fracture domains (Darcel et al., 2013) and the spatial correlation among fractures by genetic modeling techniques that imitate fracture growth processes (Davy et al., 2013, Libby et al., 2019, Lavoine et al., 2020).These methods, however, require further research for their application to field surveys and for modeling in-situ rock fracture networks.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.81-86
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• 2022

In this work, we propose a method for automatically determining the domain of columns of file data structured by csv format. New data can be generated through convergence between data and data, and the consistency of the joined columns must be maintained in order for these new data to become an important resource. One of the methods for measuring data quality is a domain-based quality diagnosis method. Domain is the broadest indicator that defines the nature of each column, so a method of automatically determining it is necessary. Although previous studies mainly studied domain automatic discrimination of relational databases, this study developed a model that can automate domains using the characteristics of file data. In order to specialize in the domain discrimination of file data, the data were simplified and patterned using a regular expression, and the contents of the data header corresponding to the column name were analyzed, and the suffix used was used as a derived variable. When derivatives of regular expressions and suffixes were added, the result of automatically determining the domain with an accuracy of 95% greater than the existing method of 87% was derived. This study is expected to reduce the quality measurement period and number of people by presenting an automation methodology to the quality diagnosis of public data.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.115-123
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• 2023

We introduce a new 'image-mapping' in-situ U-Pb dating method using LA-ICP-MS, proposed by Drost et al. (2018), and show the characteristics and usability of this method through several examples of absolute age results determined by first applying it to samples from the Joseon Supergroup of the Early Paleozoic Era in Korea. Unlike the previous in-situ spot analysis, this in-situ U-Pb dating method for carbonate minerals can determine the absolute age with high reliability by applying the 'image-mapping' method of micro-sized domains based on micro-textural observation, as well as determine the absolute age of multiple geological 'events' that occurred after deposition. This was confirmed in the case of determining the syn-depositional age and the multiple post-depositional ages from carbonate minerals of the Makgol and the Daegi Formations. Therefore, if the 'image-mapping' in-situ U-Pb dating method is applied to determine the absolute age of various types of carbonate minerals that exist in various geological environments throughout the geologic era, it will be possible to secure new geological age information.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.178-193
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• 2023

The aim of this study was to investigate differences in the achievement standards from the 2015 to the 2022 revised national science curriculum and to present the implications for science teaching under the revised curriculum. Achievement standards relevant to primary science education were therefore extracted from the national curriculum documents; conceptual domains in the two curricula were analyzed for differences; various kinds of centrality were computed; and the Louvain algorithm was used to identify clusters. These methods revealed that, in the revised compared with the preceding curriculum, the total number of nodes and links had increased, while the number of achievement standards had decreased by 10 percent. In the revised curriculum, keywords relevant to procedural skills and behavior received more emphasis and were connected to collaborative learning and digital literacy. Observation, survey, and explanation remained important, but varied in application across the fields of science. Clustering revealed that the number of categories in each field of science remained mostly unchanged in the revised compared with the previous curriculum, but that each category highlighted different skills or behaviors. Based on those findings, some implications for science instruction in the classroom are discussed.