• 한국산학기술학회논문지
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• 제20권1호
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• pp.41-51
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• 2019

본 연구는 동적역량과 혁신성과 간의 관계를 탐험과 활용의 관점에서 구분된 운영역량과 IT역량이 조절하고 매개하는지를 조사하였다. 178개 기업의 설문지를 분석한 결과, 포착역량과 재구성역량이 점진적 혁신성과와 급진적 혁신성과에 정(+), 탐험적 운영역량과 활용적 운영역량이 점진적 혁신성과에 정(+), 탐험적 운영역량이 급진적 혁신성과에 정(+)의 영향을 미치고 있다. 또한 유의적인 상호작용항은 점진적 혁신성과에 대하여 '탐험적 운영역량*탐험적 IT역량', '탐험적 운영역량*활용적 IT역량', '활용적 운영역량*활용적 IT역량' 등이며, 급진적 혁신성과에 대하여 '탐험적 운영역량*탐험적 IT역량'이다. 유의한 매개효과가 검증된 경우는 7가지였다. 본 연구의 의미는 동적역량이 혁신성과에 미치는 영향을 직접 효과와 간접효과로 나누어 실증적인 연구를 최초로 시도하였으며 운영역량과 IT역량을 탐험과 활용 역량으로 구분하여 정밀한 분석을 하였다는 점이다. 본 연구 결과를 통하여 기업이 적응하고 진화하는데 동적역량과 운영역량이 상호보완적인 역할을 한다는 시사점을 얻을 수 있다.

• Asia pacific journal of information systems
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• 제28권4호
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• pp.240-257
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• 2018

In today's turbulent business landscape, a firm's ability to explore new IT capabilities and exploit current ones is essential for enabling organizational agility and achieving high organizational performance. We propose IT exploration and exploitation as two critical organizational learning processes that are essential for gaining and sustaining competitive advantages. However, it remains unclear how the emerging cloud-based IT architecture affects an organization's ability to explore and exploit its IT capabilities. We conceptualize modularity and virtuality as two critical dimensions of emerging cloud-based IT architecture and investigate how they affect IT exploration and exploitation. We test our hypotheses using data obtained from our field survey of IT managers. We find that modularity is positively associated with both exploration and exploitation whereas virtuality is positively associated with exploration, but not with exploitation. We also find that the effect of modularity on exploitation is stronger than its effect on exploration.

• 한국조리학회지
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• 제20권5호
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• pp.1-10
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• 2014

The employment rate has become the standard for university values. This raises the need to investigate the antecedents of university students' career exploration. Focused on the hospitality majored students, this study aims to investigate both individual and relational factors that influence their career exploration behaviors. Differentiation of self has been chosen as the individual and the relational antecedents based on Bowen's theory. It was investigated whether each dimension(I-position, emotional reactivity, fusion with others, and emotional cutoff) explains the amount of self-exploration and the amount of environmental exploration. The university students majoring in hospitality were surveyed and a total of 269 cases out of 300 cases were analyzed employing descriptive statistics and multi-variate analysis of variance, and structural equation modeling(SEM). The study found that I-position positively influenced self-exploration and environmental exploration. Emotional reactivity made an influence on environmental exploration, while it failed to explain self-exploration. Fusion with others and emotional cutoff also significantly influenced environmental exploration, however, it didn't make any significant influence on self-exploration. This study implies that the college of hospitality majors needs to understand that differentiation of self forms through family relationship and needs to provide the students the programs of how to understand themselves and what to do for their career exploration.

• 대한지구과학교육학회지
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• 제9권1호
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• pp.54-64
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• 2016

The purpose of this study was to see the influences of science class applying learning cycle emphasized exploration on science learning motivation and scientific attitude of elementary students. The results drawn from this analysis were as below. Firstly, positive relationship was found between science learning motivation and science class applying learning cycle emphasized exploration among the research group. This shows that science learning motivation was improved by science class applying learning cycle emphasized exploration. It indicates that science class applying learning cycle emphasized exploration is effective in improving science learning motivations. Secondly, positive relationship was found between scientific attitude and science class applying learning cycle emphasized exploration among the research group and this means that science class applying learning cycle that emphasizes exploration stimulates intellectual curiosity of elementary school students and improves their scientific attitude. Thirdly, students thought that science class applying learning cycle emphasized exploration was very effective to improve their satisfaction, interest, participation in their science classes. Above results show that science class applying learning cycle emphasized exploration is highly effective for elementary students. Thus, it is needed to utilize science class applying learning cycle emphasized exploration to current science class as it can promote wider scientific activities among elementary school students.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.250-255
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• 2005

For navigation of a service robot, mapping and localization are very important. To estimate the robot pose, the map of the environment is required and it can be built by exploration or SLAM. Exploration is the fundamental task of guiding a robot autonomously during mapping such that it covers the entire environment with its sensors. In this paper, an efficient exploration scheme based on the position probability of the end nodes of a topological map is proposed. In this scheme, a topological map is constructed in real time using the thinning-based approach. The robot then updates the position probability of each end node maintaining its position at the current location based on the Bayesian update rule using the range data. From this probability, the robot can determine whether or not it needs to visit the specific end node to examine the environment around this node. Various experiments show that the proposed exploration scheme can perform exploration more efficiently than other schemes in that, in most cases, exploration for the entire environment can be completed without directly visiting everywhere in the environment.

• 제어로봇시스템학회논문지
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• 제15권12호
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• pp.1232-1239
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• 2009

This paper proposes an exploration strategy to efficiently find a specific place in large unknown environments with wall-following based path planning. Many exploration methods proposed so far showed good performance but they focused only on efficient planning for modeling unknown environments. Therefore, to successfully accomplish the room finding task, two additional requirements should be considered. First, suitable path-planning is needed to recognize the room number. Most conventional exploration schemes used the gradient method to extract the optimal path. In these schemes, the paths are extracted in the middle of the free space which is usually far from the wall. If the robot follows such a path, it is not likely to recognize the room number written on the wall because room numbers are usually too small to be recognized by camera image from a distance. Second, the behavior which re-explores the explored area is needed. Even though the robot completes exploration, it is possible that some rooms are not registered in the constructed map for some reasons such as poor recognition performance, occlusion by a human and so on. With this scheme, the robot does not have to visit and model the whole environment. This proposed method is very simple but it guarantees that the robot can find a specific room in most cases. The proposed exploration strategy was verified by various experiments.

• 산업기술연구
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• 제41권1호
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• pp.21-24
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• 2021

In this study, the development and production of electric vehicles and hydrogen vehicles are presented as a method for realizing carbon-neutral. Accordingly, the demand and need for development of underground metal mineral resources such as copper and nickel has increased. The research was carried out using MT survey, which is very useful for deep exploration such as mineral resources and oil exploration because of it's low cost and explorable depth. In Korea, there are very few cases of MT exploration in terms of mineral development, so the study was conducted based on the MT exploration conducted previously in AusLAMP, Australia. Through comparative analysis of the MT exploration data conducted to identify the ore body in the deep area of the Olympic Dam in Australia, with the data directly calculated in 2D inversion, it was confirmed that it can have a positive effect on the possibility of resource development and carbon neutrality using MT exploration in Korea.

• 지구물리와물리탐사
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• 제23권3호
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• pp.178-191
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• 2020

무인항공기는 최근 10년간 빠르게 성장하고 있는 한편, 복잡하고 어려운 환경에서 적용가능하며, 높은 분해능을 가진 효율적인 탐사 기법의 필요성이 대두되고 있다. 이에 따라 기존의 탐사기술을 보완하고 대체할 수 있는 효율적인 탐사 방법으로 무인항공 탐사기술이 주목받고 있다. 특히나, 자력탐사기술은 무인항공기와 접목되어 빠르게 탐사 시장에서 자리를 잡아가고 있으며, 향후 활발하게 탐사분야에서 사용될 것이라고 기대된다. 국내 탐사시장에서 적절하게 활용되기 위해서는 최신 연구 동향에 대한 검토가 필요하며, 이를 위해 이 해설논문에서는 현재까지의 무인항공기반 자력탐사시스템 개발에 대한 연구동향들을 정리한 후, 향후과제들에 대해 검토하였다.

• 품질경영학회지
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• 제43권4호
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• pp.559-572
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• 2015

Purpose: Many firms have implemented Six Sigma in order to improve employee's creativity and performance. However, few researchers have studied the effect of Six Sigma on performance through creativity process. This study aims to investigate the impact of Six Sigma, exploitation, and exploration on performance. Methods: Based on literature review, this paper develops hypotheses and tests them by employing a structural equations model. Using survey data of 209 Six Sigma experts who have conducted Six Sigma projects from different companies, this study empirically shows that the activities for Six Sigma enhance exploitation, exploration, and performance. Results: Six Sigma affects exploration and exploitation, each of which in turn enhances performance. It is noted that Six Sigma has an indirect influence on performance through exploitation and exploration. Conclusion: Apart from Parast(2011) who insists that Six Sigma is effective in improving exploitation rather than exploration, this study suggest that Six Sigma can affect both in order to enhance corporate performance.

• 한국정보기술학회 영문논문지
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• 제9권1호
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• pp.127-134
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• 2019

In terms of deep Reinforcement Learning (RL), exploration can be worked stochastically in the action of a state space. On the other hands, exploitation can be done the proportion of well generalization behaviors. The balance of exploration and exploitation is extremely important for better results. The randomly selected action with ε-greedy for exploration has been regarded as a de facto method. There is an alternative method to add noise parameters into a neural network for richer exploration. However, it is not easy to predict or detect over-fitting with the stochastically exploration in the perturbed neural network. Moreover, the well-trained agents in RL do not necessarily prevent or detect over-fitting in the neural network. Therefore, we suggest a novel design of a deep RL by the balance of the exploration with drop-out to reduce over-fitting in the perturbed neural networks.