• International Commerce and Information Review
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• v.14 no.2
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• pp.249-269
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• 2012

The focus of our work is to identify and understand the drivers of alliance performance so that businesses can maximize their chances of a successful alliance-an area that has received little attention in empirical modeling. Although both conceptual and applied research on alliances has increased, an empirically tested comprehensive theoretical model that explains alliance performance has yet to be developed. Using five salient perspective, namely market power theory, transaction cost theory, the resource-based view, institutional theory, real option theory, this paper attempts to provide a theoretical rationale linking motives of global alliance networks on firm's capabilities, partner's capabilities, operating structures, and performances of Korean companies. The key contribution of this study is that it paints a picture of what matters in driving alliance performance. Our work shows the complex nature of driving performance and the interplay of firm's capabilities, partner's capabilities, and operating structures for understanding alliance performances. This study has given us a small but significant step forward towards understanding the intricacies of alliance performance. We are now better able to understand the respective roles played by various alliance factors and derive insights that lead to improved alliance performance.

• The Journal of Bigdata
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• v.5 no.1
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• pp.11-27
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• 2020

In this paper, we developed a big data platform to store, process, and analyze effectively on such education longitudinal study data. And it was applied to the Seoul Education Longitudinal Study(SELS) to confirm its usefulness. The developed platform consists of data preprocessing unit and data analysis unit. The data preprocessing unit 1) masking, 2) converts each item into a factor 3) normalizes / creates dummy variables 4) data derivation, and 5) data warehousing. The data analysis unit consists of OLAP and data mining(DM). In the multidimensional analysis, OLAP is performed after selecting a measure and designing a schema. The DM process involves variable selection, research model selection, data modification, parameter tuning, model training, model evaluation, and interpretation of the results. The data warehouse created through the preprocessing process on this platform can be shared by various researchers, and the continuous accumulation of data sets makes further analysis easier for subsequent researchers. In addition, policy-makers can access the SELS data warehouse directly and analyze it online through multi-dimensional analysis, enabling scientific decision making. To prove the usefulness of the developed platform, SELS data was built on the platform and OLAP and DM were performed by selecting the mathematics academic achievement as a measure, and various factors affecting the measurements were analyzed using DM techniques. This enabled us to quickly and effectively derive implications for data-based education policies.

• School Mathematics
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• v.10 no.4
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• pp.489-514
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• 2008

Since 2005 KICE - TLC has focused on the development of supporting programs for teaching consultation and pedagogical content knowledge(PCK). The purpose of this year's research was to explore types of pedagogical content knowledge(PCK, hereafter) for effective teaching mathematics topics drawn from the amended national mathematics curriculum announced in February, 2007. Based on this year's PCK research, we will develop mathematics teaching consulting program from 2009 research by field testing of developed mathematics PCK. The major source of data for this study was transcripts of audiotapes of the group discussions that took place during the regular weekly meetings where we compared and analyzed three teachers' classes. We also conducted open-ended interviews with the three teachers and collected reflective notes written by participants. This research provided teachers with an opportunity to think about what is important in the teaching of a topic and why, and to consider possibilities for future development. This research highlights the importance of teacher meetings where teachers share their expertises and insights through reflection and dialogue. By introducing the concept of PCK, examining, analyzing and modelling it in pre-service and in-service teacher education practice, we can contribute to extend teachers' professional learning. Finally, just like quality student learning, quality teaching and teacher education practices require critical reflection and careful scaffolding.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.87-104
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• 2015

Currently the IoT (Internet of Things) environments and related technologies are being developed rapidly through the networks for connecting many intelligent objects. The IoT is providing artificial intelligent services combined with context recognition based knowledge and communication methods between human and objects and objects to objects. With the help of IoT technology, many research works are being developed using the C-ITS (Cooperative Intelligent Transport System) which uses road infrastructure and traveling vehicles as traffic control infrastructures and resources for improving and increasing driver's convenience and safety through two way communication such as bus-only lane and license plate recognition and road accidents, works ahead reports, which are eventually for advancing traffic effectiveness. In this paper, a system for deciding whether the traveling vehicle is possible or not to drive on bus-only lane in highway is researched using the lane and number plate recognition on the road in C-ITS traffic infrastructure environments. The number plates of vehicles on the straight ahead and sides are identified after the location of bus-only lane is discovered through the lane recognition method. Research results and experimental outcomes are presented which are supposed to be used by traffic management infrastructure and controlling system in future.

• Journal of dental hygiene science
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• v.16 no.2
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• pp.134-141
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• 2016

The purpose of this study was to develop a dental communication course in dental hygiene schools that included theory, practice, and skill for effective dental communication. Thirty-six senior dental hygiene students in a dental hygiene school took a dental communication course and responded to a questionnaire. The instrument used in the study was a modified form of Kim's communication skill self-assessment sheet. The self-assessment questionnaire about communication competencies was administered before and after the class, and the difference between scores at each time point was analyzed using the Wilcoxon signed rank sum test. Among seven elements of dental communication competencies, the competency of "information gathering" was significantly improved (p=0.008). Students' scores on perception of the importance (p=0.019) and necessity (0.016) of a communication course significantly increased after the course. Competencies in communication are essential requirement for dental hygienists. This study showed the possibility of communication skill training. An objective evaluation tool regarding students' communication competencies should be developed. Further studies with larger samples size are needed to develop a standardized comprehensive communication course in dental hygiene schools.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.469-469
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• 2017

기후 변화 및 환경오염으로 인하여 물부족 국가가 세계적으로 증가하고 있는 추세이며, 특히 집중형 강우의 형태가 많아짐에 따라 홍수피해 및 상수공급의 문제가 사회적으로 큰 이슈가 되고 있다. 최근 20여 년간의 급속한 경제성장과 도시화 과정에서 인도네시아는 인구와 산업의 과도한 도시집중으로 지난 1960-80년대 한국이 산업화 과정에서 겪었던 것보다 훨씬 심각한 환경문제에 직면하고 있으며, 자카르타와 반둥을 포함하는 광역 수도권 지역의 물 부족과 수질 오염, 환경문제가 이미 매우 위험한 수준에 도달하고 있는 실정이다. 특히, 찌따룸강 중상류에 위치한 인도네시아 3대 도시인 반둥시는 고질적인 용수부족 문제를 겪고 있다. 2010년 현재 약 일평균 15 CMS의 용수가 부족한 상황이며, 2030년에는 지속적인 인구증가로 약 23 CMS의 용수가 추가로 더 필요한 것으로 전망된다. 이러한 용수공급 문제 해결을 위해 반둥시 및 찌따룸강 유역관리청은 댐 및 지하수 개발, 유역 간 물이동 등의 구조적인 대책뿐만 아니라 비구조적인 대책으로써 기존 및 신규 저수지 연계운영을 통한 용수이용의 효율성을 높이는 방안을 모색하고 있다. 이에 따라 본 연구에서는 해당유역의 용수공급 부족 문제를 해소할 수 있는 비구조적인 대책의 일환으로써 다양한 댐 및 보, 소수력 발전, 취수장 등 유역 내 수리 시설물의 운영 최적화를 위한 지능형 물관리 시스템 적용 방안을 제시하고자 한다. 본 연구의 지능형 물관리 시스템은 센서 및 사물 인터넷(Internet of Things, IoT), 네트워크 기술을 바탕으로 시설물 및 운영자, 유관기관 간의 양방향 통신을 통해 유기적인 상호연계 체계를 제공 할 수 있다. 또한 유역의 수문상황과 시설물의 운영현황, 용수공급 및 수요 현황을 실시간으로 확인함으로써 수요에 따른 즉각적인 용수공급량의 조절이 가능하다. 또한, 빅데이터 분석 및 기계학습(Machine Learning)을 통해 개별 물관리 시설물에 대한 최적 운영룰을 업데이트할 수 있으며, 유역의 수문상황과 용수 수요 현황을 고려하여 최적의 용수공급 우선순위를 선정할 수 있다. 지능형 물관리 시스템 개발의 목적은 찌상쿠이 유역의 수문현황을 실시간으로 모니터링하고, 하천시설물의 운영을 분석하여 최적의 용수공급 및 배분을 통해 유역의 수자원 활용 효율성을 향상시키는 데 있다. 이를 위해 수문자료의 수집체계를 구축하고 기관간 정보공유체계를 수립함으로써 분석을 위한 기반 인프라를 구성하며, 이를 기반으로 유역 유출을 비롯한 저수지 운영, 물수지 분석을 수행하고, 분석 및 예측결과, 과거 운영 자료를 토대로 새로운 물관리 시설 운영룰 및 시설물 간 연계운영 방안, 용수공급 우선순위 의사결정 등을 지원하고자 한다. 본 연구의 지능형 물관리 시스템은 통합 DB를 기반으로 수리수문 현상의 모의 분석을 통해 하천 시설물 운영의 합리적 기준을 제시함으로써 다양한 관리주체들의 시설물운영에 대한 이견 및 분쟁을 해소하고, 한정된 수자원과 다양한 수요 간의 효율적이고 합리적인 분배 및 시설물 운영문제를 해결하기 위한 의사결정도구로써 활용할 수 있을 것으로 기대된다.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.368-376
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• 2021

Artificial intelligence clouds help to efficiently develop the autonomous things integrating artificial intelligence technologies and control technologies by sharing the learned models and providing the execution environments. The existing autonomous things development technologies only take into account for the accuracy of artificial intelligence models at the cost of the increment of the complexity of the models including the raise up of the number of the hidden layers and the kernels, and they consequently require a large amount of computation. Since resource-constrained computing environments, could not provide sufficient computing resources for the complex models, they make the autonomous things violate time criticality. In this paper, we propose a digital twin software development framework that selects artificial intelligence models optimized for the computing environments. The proposed framework uses a load estimation DNN model to select the optimal model for the specific computing environments by predicting the load of the artificial intelligence models with digital twin data so that the proposed framework develops the control software. The proposed load estimation DNN model shows up to 20% of error rate compared to the formula-based load estimation scheme by means of the representative CNN models based experiments.

• Journal of Korean Library and Information Science Society
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• v.50 no.1
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• pp.357-380
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• 2019

The purpose of this study is to analyze the Elementary and Secondary Education Act(ESEA) of the U.S. reauthorized by the Every Student Succeeds Act in 2015 from the viewpoint of the library and information services, and to derive implications for improving the library and information services. For the first time, ESEA includes effective school library programs and school librarians, and links school library programs and school librarians with literacy, digital literacy, books, resources, up-to-date materials, technology, library services and educational services. It provides a financial and institutional base for library and information services in elementary and secondary schools of the US to be more conducted. In addition, school librarians are required to participate in personalized learning experiences, evidence-based assessments, and professional development in the law, so school librarians must provide library and information services to students, staff, and parents in order to improve student achievement and digital literacy. Based on these analyses, this study discussed strengthening access to the school library, specifying the work of the teacher-librarian's library and information services, strengthening collaboration with school members, educational activities based on evidence base, sharing educational effects and developing of library and information curriculum.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.23-30
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• 2021

The shift to the digital media era is increasing the importance of the ability to accept, produce and share news through digital media(news literacy), but there is a lack of diagnosis of the level of news literacy among Korean adults and discussions on how to improve news literacy. This study analyzed the news literacy level of Korean adults according to background variables (urbanization degree, gender, age, academic background) and examined the relationship between the amount of news literacy-related practices and the level of news literacy. The results showed that the overall level of news literacy among adults in Korea was not high and that differences between groups were also statistically significant. The significant relevance between the amount of news literacy-related practices and the level of news literacy has also been identified. Based on the findings, it was suggested that the need for policy support to improve news literacy among Korean adults, the need to prioritize the resources of news literacy education according to background variables of adult learners, and the need to continuously monitor news literacy levels of Korean adults.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.313-332
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• 2020

The purpose of this study is to compare motivations for self-archiving across disciplines on an academic social networking site. We carried out an online survey with ResearchGate(RG) users, testing 18 motivational factors that we developed from a previous study (enjoyment, personal/professional gain, reputation, learning, self-efficacy, altruism, reciprocity, trust, community interest, social engagement, publicity, accessibility, self-archiving culture, influence of external actors, credibility, system stability, copyright concerns, additional time, and effort). We adapted Biglan's classification system of academic disciplines and compared motivations across different categories of discipline. First, we compared motivations across the four combined categories by the two dimensions - hard-pure, hard-applied, soft-pure, and soft-applied. We also performed a motivation comparison across each dimension between soft and hard disciplines and between pure and applied disciplines. We examined investigated statistical differences in motivations by demographic characteristics and RG usage of participants across categories as well. Findings showed that there were differences of motivations, such as enjoyment, accessibility, influence of external actors and additional time and effort, and personal/professional gains, for self-archiving across disciplines. For example, RG users in the hard-applied were more highly motivated by enjoyment than others; RG users in the soft-pure were more highly motivated by personal/professional gains than others. It is expected that findings could be used to develop strategies encouraging researchers in various disciplines contributing to share their data and publications in ASNSs.