• 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.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.7
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• pp.297-306
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• 2019

This is a longitudinal study which aims to examine the effects of the use frequency of SNS on adolescents' stress and the relationship between the former and the latter, based on big five personality factors. To this end, the valid data of 994 adolescents were collected by administering questionnaires to the cohort groups of those using Facebook twice for one year(T1-T2). An analysis of the data showed that the use frequency of Facebook(T1) had no direct effects on stress(T2), and that there was an interaction between users' personality and the use frequency. In particular, users' stress(T2) was varied depending on neuroticism among personality factors, as the use frequency of Facebook(T1) increased. The higher the use frequency of Facebook, the more the stress in the group with weak neuroticism, while the higher the use frequency of Facebook, the less the stress in other group with strong neuroticism, probably because each group has different motivation for meeting their needs for social support: the former's stress may increase, since they has relatively lower needs for social support and face more conflicts as they more frequently use Facebook, while the latter's stress may decrease, because they have relatively stronger needs for social support and are likely to acquire psychological support, as they more frequently use it.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1965-1974
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• 2021

Satellite remote sensing approach can be actively used for forest monitoring. Especially, it is much meaningful to utilize Korea multi-purpose satellites, an independently operated satellite in Korea, for forest monitoring of Korea, Recently, several studies have been performed to exploit meaningful information from satellite remote sensed data via machine learning approaches. The forest information produced through machine learning approaches can be used to support the efficiency of traditional forest monitoring methods, such as in-situ survey or qualitative analysis of aerial image. The performance of machine learning approaches is greatly depending on the characteristics of study area and data. Thus, it is very important to survey the best model among the various machine learning models. In this study, the performance of deep neural network to classify artificial or natural forests was analyzed in Samcheok, Korea. As a result, the pixel accuracy was about 0.857. F1 scores for natural and artificial forests were about 0.917 and 0.433 respectively. The F1 score of artificial forest was low. However, we can find that the artificial and natural forest classification performance improvement of about 0.06 and 0.10 in F1 scores, compared to the results from single layered sigmoid artificial neural network. Based on these results, it is necessary to find a more appropriate model for the forest type classification by applying additional models based on a convolutional neural network.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.219-227
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• 2019

This study aims to examine Blockchain research trend using bibliometrics-based network analysis. The data were collected from WoS, Scopus, Korea Citation Index and National science & Technology Information Service, from 2009 to 2018. As results, the number of publications has started increasing rapidly from 2017 and it showed the initial stage of formation of coauthor network. Words often used in the title of the publications were related to application development, controversy and technology development. In addition, the majority of domestic papers are in the subject of social science, while international papers tend to focus on engineering issues. The results of the temporal analysis show that Korean researchers' block chain 3.0 started in 2017 and are rapidly increasing in 2018. The number of citations was associated with publication year in a statistically signifiant way. By examining these research trends, we hope that this paper can be a useful basis for the development of blockchain. Future research is expected to reveal more clearly the knowledge structure and characteristics of blockchain around the world.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.13-24
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• 2012

CCGIS (Climate Change Adaptation Toolkit based on GIS) was developed to use as a tool for the climate change assessment and any relevant tasks involving climate change adaptation policy over Korean peninsula. The main objective of CCGIS is to facilitate an efficient and relevant information for the estimation of climate change vulnerability index by providing key information in the climate change adaptation process. In particular, the atmospheric modeling system implemented in CCGIS, which is composed of climate and meteorological numerical model and the atmospheric environmental models, were used as a tool to generate the climate and environmental IPCC SRES (A2, B1, A1B, A1T, A1FI, and A1 scenarios) climate data for the year of 2000, 2020, 2050, and 2100. This article introduces the components of CCGIS and describes its application to the Korean peninsula. Some examples of the CCGIS and its use for both climate change adaptation and estimation of vulnerability index applied to Korean provinces are presented and discussed here.

• Science of Emotion and Sensibility
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• v.22 no.2
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• pp.49-58
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• 2019

In the era of the 4th Industrial Revolution, artificial intelligence (AI) has become one of the core technologies in terms of the business strategy among information technology companies. Both international and domestic major portal companies are launching AI search services. These AI search services utilize voice, images, and other unstructured data to provide different experiences from existing text-based search services. An unfamiliar experience is a factor that can hinder the usability of the service. Therefore, the usability testing of the AI search services is necessary. This study examines the usability of the AI search service on the Naver App 8.9.3 beta version by comparing it with the search services of the current Naver App and targets 30 people in their 20s and 30s, who have experience using Naver apps. The usability of Smart Lens, Smart Voice, Smart Around, and AiRS, which are the Naver App beta versions of their artificial intelligence search service, is evaluated and statistically significant usability changes are revealed. Smart Lens, Smart Voice, and Smart Around exhibited positive changes, whereas AiRS exhibited negative changes in terms of usability. This study evaluates the change in usability according to the application of the artificial intelligence search services and investigates the correlation between the evaluation factors. The obtained data are expected to be useful for the usability evaluation of services that use AI.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.173-185
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• 2019

Causal questions are prevalent in scientific research, for example, how effective a treatment was for preventing an infectious disease, how much a policy increased utility, or which advertisement would give the highest click rate for a given customer. Causal inference theory in statistics interprets those questions as inferring the effect of a given intervention (treatment or policy) in the data generating process. Causal inference has been used in medicine, public health, and economics; in addition, it has received recent attention as a tool for data-driven decision making processes. Many recent datasets are observational, rather than experimental, which makes the causal inference theory more complex. This review introduces key concepts and recent trends of statistical causal inference in observational studies. We first introduce the Neyman-Rubin's potential outcome framework to formularize from causal questions to average treatment effects as well as discuss popular methods to estimate treatment effects such as propensity score approaches and regression approaches. For recent trends, we briefly discuss (1) conditional (heterogeneous) treatment effects and machine learning-based approaches, (2) curse of dimensionality on the estimation of treatment effect and its remedies, and (3) Pearl's structural causal model to deal with more complex causal relationships and its connection to the Neyman-Rubin's potential outcome model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.3
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• pp.13-26
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• 2019

There is a growing interest in the entrepreneurial activity that has long been considered essential for sustainable economic development and value creating. Although it is strongly encouraged by focusing on the positive aspects of venturing, less has been paid attention to entrepreneurial failure, which is the biggest cause of hesitation in starting a business. The uncertain and risky nature of entrepreneurship implies a considerable possibility of failure. Even if it fails, the experience and knowledge of entrepreneurs acquired through entrepreneurship indeed offers valuable lessons for the re-venturing, which can serve as an important social asset that should not be lost. It has been argued that re-entering the same industry for the subsequent venture maximizes the learning effect through utilizing potential benefits from industry-specific knowledge. Although the re-startup after entrepreneurial failure is a very important topic in the studies on serial entrepreneurs, there is a paucity of systematic empirical investigation. This study responds to calls for more research on the re-startup after entrepreneurial failure, and specifically complements existing studies on serial entrepreneurs. Focusing on the entrepreneurs' attribution for the failure, we conducted an empirical analysis of how this affects the re-startup process. Moreover, we also examined the moderating effects of entrepreneurial self-efficacy and resilience. For the analyses, we surveyed the entrepreneurs who tried to re-start the subsequent business after the entrepreneurial failure through the "Revitalization Center for Strained Entrepreneur". The results found that failed entrepreneurs who blamed internal factors for their previous venture failures were likely to keep the same industry for their subsequent business. In addition, the positive effect of internal attribution on maintaining the same industry for the re-startup was found to be stronger when entrepreneurial self-efficacy and resilience were high.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.57-66
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• 2019

This study investigates the factors influencing to users' intention to retain monthly movie subscription VOD service in the Pay-TV. A dual model of a dedication-based mechanism and constraint-based mechanism used as the analytical framework for the service subscription retention. This study surveyed the total of 366 respondents who aged 15 years or older among the subscribers who use monthly movie subscription VOD service in Pay-TV from May 8 to May 14, 2018 through online surveys. And the study used SPSS 25 and AMOS 21 for data analysis. The results of the analysis are as follows. First, the price, the contents diversity and the ease of use were found to affect the user satisfaction. From three components, the price is the most effective and the ease of use is the next. Second, user satisfaction were found to affect the intention to retain a subscription in the dedication-based mechanism. Third, procedural switching cost were found to affect the intention to retain a subscription in the constraint-base mechanism.

• Journal of the Korean Society for information Management
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• v.37 no.4
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• pp.131-150
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• 2020

This study was conducted to ascertain a better understanding of researchers' perception of open peer review (OPR), which is being attempted to improve the problems of traditional peer review methods in recent journal publications. A survey was conducted on the Korean authors of a mega open access (OA) journals and the results were analyzed. The subjects of the survey were selected as Korean corresponding authors published on PLOS, an international OA journal and mega journal. The survey was conducted as an online questionnaire and a total of 238 responses were collected; the analysis was based on 202 valid responses. Data were analyzed by performing frequency analysis and average comparison between groups for the collected questionnaire results. As a result of analyzing whether there is a difference in perception of OPR depending on the age, research experience, and OPR experience of the researcher, researchers under the age of 44, researchers with research experience of 9 years or less, and researchers with OPR participation experience had differences in some OPR perceptions. Results show that researchers under the age of 44 want to change the current peer review approach, but they are not yet actively accepting OPR. As a result of analyzing the reasons why the researcher disagrees with OPR, they raised questions about lack of objectivity, increased burden of reviewers, emotions and relationships, and responded that the right to be forgotten was also necessary.