• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.391-404
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• 2022

Actor-network theory (ANT) pays attention to the relational effect between human and non-human actors, and transforms numerous networks between these actors by treating non-humans as human-like actors. This paper investigated various non-human actors related to the context before and after the introduction of NCS-based curriculum through ANT. This approach is because as a new system is introduced, the impact on the existing network and conflict situations can be looked at more closely. To this end, the researcher reviewed data from October 2014, when S College discussed whether to introduce an NCS-based curriculum, to February 2017, when practical operation was carried out and graduates were produced. In order to understand ANT theory, we analyzed based on the four stages of translation as claimed by Callon in the ANT theory. As a result, some meanings were confirmed in the case of reforming the curriculum of S College where the NCS-based curriculum was introduced. First, it is an in-depth analysis of the situation surrounding the curriculum, which has been overlooked by research on the existing curriculum. Second, it contributed to interpreting the 'hidden meaning' beyond the 'superficial meaning' of the curriculum within the university. Third, it was possible to indirectly check the conflicts and conflicts with the existing system that appeared in the process of introducing the new system to the College.

• Journal of Science and Technology Studies
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• v.12 no.1
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• pp.145-183
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• 2012

Science reporting is easier to lead to failure than other news reporting because it needs higher professionalism. According to Actor-Network Theory(ANT), not only research results(artifacts) of scientists but also science articles are hybrid networks. Namely, they are connected by human actors(scientist, reporter, etc.) and nonhuman actors(press releases etc.). When the process of science reporting is examined on the view of ANT, it is the process that scientists' results translate the media via press releases as intermediaries and expand their network to the public. This study aims at making an ANT analysis of how research results of Electronics and Telecommunications Research Institute(ETRI) scientist Hyun-Tak Kim were reported by lots of media, focusing on the rhetoric of ETRI's press release. It can reveal the reason for the science reporting's failure and hint at the better science journalism.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.3
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• pp.334-349
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• 2008

In this study, the network formation process of personal actors in industries for the elderly was analyzed. This process is applied to the knowledge creation model of the SECI (Nonaka-Takeuchi learning cycle), that is socialization, externalization, combination, internalization. There are some kinds of opportunities to interact in these industries in the forms of field survey teams to overseas, some seminars and symposiums, many kinds of meetings, education and training programs, trade fairs and on-line forums. These palces(ba) - originating ba, interacting ba, cyber ba, exercising ba - played great roles in the formation of personal actor networks. Personal actors had opportunities to interconnect with distant actors through those places(ba). In the spatial perspective, personal actors could make face-to-face contact and build trust through temporary geographical proximity or temporary clusters with the help of personal mobility. Relations in the virtual spaces such as the Internet community did much toward building personal networks.

• Journal of Science and Technology Studies
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• v.19 no.2
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• pp.1-40
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• 2019

Built upon ethnographic method such as participant observation and in-depth interview, this study analyzes the material culture of electronic flower auctions at Yangjae Flower Market. From the viewpoint of Actor-Network Theory(ANT), this research examines how human actors like dealers and auctioneers interact with nonhuman actors such as market devices and these interactions form networks called "agencement." This research is focused on three main objectives: first, to study how the performance of auctions - i.e. the interactions between auctioneers and dealers - change in the wake of new market devices in the auctions; secondly, to look into what changes artifacts bring to the social relationships between auctioneers and dealers; lastly, to analyze the influence of new market devices on auction price in the market. The results of this research are as follows. First, the appearance of new market devices generates changes in the performance of auctions, which means the change of 'agencement' of flower auctions. Direct interactions between auctioneers and dealers turned into indirect interactions through new market devices. Moreover, the changes in the agencement brought changes to the identity of auctioneers and dealers. Secondly, the new agencement caused by the inflow of new market devices formed the trust between the devices and human actors, which gave rise to the trust in electronic auction and in counterpart actors as well. In addition, new market devices lowered direct interactions between auctioneers and dealers and thus made more equal relationships between the two than before. Lastly, market devices like trading screen reduced the leverage of auctioneers by providing dealers with bidding information previously possessed by auctioneers much openly and dealers were able to decide auction prices in more reasonable and dispassionate manner. Economic agency, power, trust, price, and information in the market is material and sensory.

• Information Systems Review
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• v.21 no.4
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• pp.125-141
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• 2019

With the advent of deep learning technology, which is represented by AlphaGo, artificial intelligence (A.I.) has quickly emerged as a key theme of digital transformation to secure competitive advantage for businesses. In order to understand the trends of A.I. based digital transformation, a clear comprehension of the A.I. business ecosystem should precede. Therefore, this study analyzed the A.I. business ecosystem from the multi-actor network perspective and identified the A.I. platform strategy type. Within internal three layers of A.I. business ecosystem (infrastructure & hardware, software & application, service & data layers), this study identified four types of A.I. platform strategy (Tech. vertical × Biz. horizontal, Tech. vertical × Biz. vertical, Tech. horizontal × Biz. horizontal, Tech. horizontal × Biz. vertical). Then, outside of A.I. platform, this study presented five actors (users, investors, policy makers, consortiums & innovators, CSOs/NGOs) and their roles to support sustainable A.I. business ecosystem in symbiosis with human. This study identified A.I. business ecosystem framework and platform strategy type. The roles of government and academia to create a sustainable A.I. business ecosystem were also suggested. These results will help to find proper strategy direction of A.I. business ecosystem and digital transformation.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.631-648
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• 2020

As an attempt to consider what to pay attention to in science learning, this study was conducted with the aim of discussing the meaning of science learning as a heterogeneous network. As a result of theoretical investigation, the characteristics of the heterogeneous network were described in three aspects: heterogeneous composition, existence by relations, and construction and change by translation. And it was discussed that science learning also has these characteristics of heterogeneous network. Relating to what to pay attention to in science learning, it was also discussed that science learning as a heterogeneous network requires us to pay attention to the elevation of things, the concept as a punctualized heterogeneous network, and the construction and expansion of heterogeneous network with neonadeuri of 'unripe' and 'ripe'. Finally, several suggestions for the science learning were given.

• 한국HCI학회:학술대회논문집
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• 2007.02b
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• pp.424-431
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• 2007

본 연구는 관계망 시각화에 이용되는 데이터의 특성을 분석하고 그에 맞는 시각화 요소를 추출하여 시각화하는 것에 관한 연구이다. 사회 관계망 시각화는 점과 선을 기초 요소로 하여 점은 사회적 요소(actor), 선은 관계(relation)를 의미한다, 점과 선은 시각화에 사용되는 데이터의 특성에 따라 다양한 형태를 갖게 된다. 이 논문에서는 관계망 시각화에 사용되는 데이터의 특성을 데이터의 형태, 관계, 상태에 따라 분류하고, 각각의 특성에 맞는 관계망 시각화의 형태를 추출하고, 그에 따른 시각화 요소를 추출하였다. 이를 바탕으로 모바일 커뮤니케이션을 통해 형성되는 인맥 네트워크를 시각화함으로써, 인맥 네트워크 구성원 간의 친밀도를 효과적으로 파악할 수 있는 방법에 대해 제시하였다. 또한, 시각화의 결과를 이용하여 휴대전화로 인맥 네트워크를 유지, 관리하기 위한 서비스를 제안하였다. 이러한 연구는 데이터의 특성에 맞는 시각화의 요소를 추출하고, 데이터의 형태, 관계, 상태를 직관적으로 제공함으로써 사용자로 하여금 자신의 인맥 네트워크 구성원들의 친밀도와 관계 형태, 상태를 파악하여 자신의 인맥을 유지, 관리하고 보수할 수 있도록 한다.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.51-60
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• 2016

This paper proposes a hierarchical routing algorithm for enhancing survivability of sensor nodes on WSAN. Proposed algorithm has two important parts. The first is a clustering algorithm that uses distance between sensor and actor, and remaining energy of sensor nodes for selecting cluster head. It will induce uniform energy consumption, and this has a beneficial effect on network lifetime. The second is an enhanced routing algorithm that uses the shortest path tree. The energy efficient routing is very important in WSAN which has energy limitation. As a result, proposed algorithm extends network and nodes lifetime through consuming energy efficiently. Simulation results show that the proposed clustering algorithm outperforms conventional routing algorithms such as VDSPT in terms of node and network life time, delay, fairness, and data transmission ratio to BS.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.138-141
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• 2003

Recently reinforcement learning has attracted attention of many researchers because of its simple and flexible learning ability for any environments. And so far many reinforcement learning methods have been proposed such as Q-learning, actor-critic, stochastic gradient ascent method and so on. The reinforcement learning system is able to adapt to changes of the environment because of the mutual action with it. However when the environment changes periodically, it is not able to adapt to its change well. In this paper we propose the reinforcement learning system that is able to adapt to periodical changes of the environment by introducing the time-varying parameters to be adjusted. It is shown that the proposed method works well through the simulation study of the maze problem with aisle that opens and closes periodically, although the conventional method with constant parameters to be adjusted does not works well in such environment.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.18-25
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• 2015

After the Korean Wave with the industrialization of acting arts, scientific actors management has been demanded for the purpose of investment stabilization in related areas. This study was undertaken to develop a new convergence actors evaluation model applying inter-disciplinary research. The assessment factors were selected through literature reviews and the consensus of experts has been derived through Delphi Method. In conclusion, the evaluation criteria for the actors were drawn by 10 different factors. They are composed of qualitative factors such as the ability of acting and communication, degree of understanding of works and production system, actor philosophy and stability of the actors' self-management, physical condition and image, passion and enthusiasm for acting and works, and performance factors such as the stardom, fandom, philmography, audience share and ticket power, and network size and quality.