• The Korean Journal of Archival Studies
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• no.32
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• pp.3-44
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• 2012

The purpose of the study is to explore the strategies to build participatory digital archives for documenting localities. Following the introduction of the chapter one, the chapter two deals with categorizing participation types of persons and organizations for documenting localities, analysing characteristics and benefits of each type, and listing up the requirements of participatory archives based on literature reviews. The chapter three focuses on the analyses of digital archives especially based on the participation of organizations such as collecting institutions and community archives in USA, Canada and UK. The cases of participatory archives are divided into two types; i) digital archives based on archival collections of institutions such as libraries, archives, and museums, ii) digital archives mainly based on various community archives. Online Archives California(OAC) and Calisphere of University of California, MemoryBC of British Columbia of Canada, and People's Collection Wales of UK as the first type cases, and Connecting Histories of Birmingham, 'Community Archives Wales(CAW), Cambridgeshire Community Archive Network(CCAN), Norfolk Community Archives Network(NORCAN) as the second type cases are selected for comparative analyses. All these cases can be considered as archival portals since they cover collections from various organizations. This study then evaluates how these digital archives fulfill the requirements of participatory archives such as : i) integrated search of archives that are to be distributed, ii) participation of individuals and organizations, and iii) providing broader contextual information and representation of context as well as contents of archives. Lastly the final chapter suggests the implications for building participatory archives in Korean local areas based on following aspects : host organizations and implementation strategy, networks of collection institutions and community archives, preserving and reorganizing contextual information, selection and appraisal, and participation of records users and creators.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.1-13
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• 2019

As a way to find new and innovative technologies, many companies have invested in and acquired skilled startups. Because startups are usually small in size and have a small history of past business experience, there are many risks involved in acquiring them as they have limited technical skills and business feasibility verification methods. Thus, venture capital plays an important role in discovering and investing competitive startups. While Independent Venture Capital generally values financial returns, Corporate Venture Capital, which plays investment roles in the firm, values business synergies with the parent company from a strategic perspective. In an industry sector where development of technology is rapid and whether new technology is held determines a company's competitiveness, existing companies incorporate startups with innovative technologies into their investment portfolios, collaborate together, and take over for comprehensive cooperation. In addition, new investments and acquisitions are carried out through the management of portfolio companies to obtain and utilize industry information. In this paper, major U.S. companies listed in the U.S. verified their investment activities through corporate venture capital and their impact on parent companies and startups through regression, while the parent company's acquisition performance was analyzed through an event study based on a stock price analysis. The criteria for startup were defined as companies with less than 12 years of experience, and the analysis showed that the parent companies with corporate venture capital with a larger number of investments actively take over startups. In addition, increasing corporate venture capital's financial investment activities shows a negative impact on the parent companies' acquisition activities, and the acquisition performance increased when the parent companies took over startups in its portfolio.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.3
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• pp.11-28
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• 2021

Due to its size and complex characteristics, it is not often to newly create a large park within an existing urban area. Also, there has been a lack of research on the planting design methodologies for a large park. This study aims to elucidate how ecological ideas can be applied to planting practice from a designer's perspective, and eventually suggest a planting design framework in the actual case, the Central Park in the City of Gwangju. This framework consists of spatial structure of planting area in order to connect and unite the separated green patches, to adapt to the changes of existing vegetation patterns, to maintain the visual continuity of landscape, and to organize the whole open space system. The framework can be provided for the spatial planning and planting design phase in which the landscape designer flexibly uses it with the design intentions as well as with an understanding of the physical, social, and aesthetic characteristics of the site. The significance of this approach is, first that it can maintain ecological and visual consistency of the both existing and introduced landscapes as a whole in spite of its intrinsic complexity and largeness, and second that it can help efficiently respond to the unexpected changes in the landscape. In the case study, comprehensive site analysis is conducted before developing the framework. In particular, wetlands and grasslands have been identified as potential wildlife habitat which critically determines the vegetation patterns of the green area. Accordingly, the lists of plant communities are presented along with the planting scheme for their shape, layout, and relations. The model of the plant community is developed responding to the structure of surrounding natural landscape. However, it is not designed to evolve to a specific plant community, but is rather a conceptual model of ecological potentials. Therefore, the application of the model has great flexibility by using other plant communities as an alternative as long as the characteristics of the communities are appropriate to the physical conditions. Even though this research provides valuable implications for landscape planning and design in the similar circumstances, there are several limitations to be overcome in the further research. First, there needs to be more sufficient field surveys on the wildlife habitats, which would help generate a more concrete planting model. Second, a landscape management plan should be included considering the condition of existing forest, in particular the afforested landscapes. Last, there is a lack of quantitative data for the models of some plant communities.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.207-235
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• 2022

In a knowledge-based society where knowledge and information industries are the main pillars of the economy, knowledge sharing and diffusion and its systematic management are recognized as essential strategies for improving national competitiveness and sustainable social development. In the field of Information Systems (IS) research, where the convergence of information technology and management takes place in various ways, the evolution of knowledge occurs only when researchers cooperate in turning old knowledge into new knowledge from the perspective of the scientific knowledge network. In particular, it is possible to derive new insights by identifying topics of interest in the relevant research field, applied methodologies, and research trends through network-based interdisciplinary graftings such as citations, co-authorships, and keywords. In previous studies, various attempts have been made to understand the structure of the knowledge system and the research trends of the relevant community by revealing the relationship between research topics, methodologies, and co-authors. However, most studies have compared two or more journals and been limited to a certain period; hence, there is a lack of research that looked at research trends covering the entire history of IS research. Therefore, this study was conducted in the following order for all the papers (from its first issue in 1977 to the first quarter of 2022) published in the MIS Quarterly (MISQ) Journal, which plays a leading role in revealing knowledge in the IS research field: (1) After extracting keywords, (2) classifying the extracted keywords into research topics, methodologies, and theories, and (3) using topic modeling and keyword network analysis in order to identify the changes from the beginning to the present of the IS research in a chronological manner. Through this study, it is expected that by examining the changes in IS research published in MISQ, the developing patterns of IS research can be revealed, and a new research direction can be presented to IS researchers, nurturing the sustainability of future research.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.17-29
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• 2021

Recently, as social distancing have been raised due to the re-spread of COVID-19, the number of serial entrepreneurs who are closing their business is rapidly increasing. Learning from failure is a source of success, but business failure can result in psychological and economic losses and negative emotions of the serial entrepreneur. At this point, it is very important to find a way to recover the negative emotions caused by business failures of serial entrepreneurs. Recently, a strategic model has emerged to deal with the negative emotions of grief caused by business failures of serial entrepreneurs. This study identified the recovery factors from the grief of business failures of serial entrepreneurs and analyzed Shepherd's(2003) three areas: loss orientation, restoration orientation, and dual process. To this end, individual in-depth interviews were conducted with 12 small business serial entrepreneurs who challenged re-startup to identify the attributes of recovery factors that were not identified with quantitative data. As a result of the study, first, recovery factors were investigated in three areas: individual orientation, family orientation, and network orientation. It was found to help improve recovery in nine categories: self-esteem, persistence, personal competence, hobbies, self-confidence, family support, networks, religion, and social support. Second, recovery obstacle factors were investigated in three areas: psychological, economic, and environmental factors. Nine categories including family, health, social network, business partner, competitor, partner, fund, external environment, and government policy were found to persist negative emotions. Third, the emotional processing process for grief was investigated in three areas: loss orientation, restoration orientation, and dual process. Ten categories such as family, partner support, social member support, government support, hobbies, networks, change of business field, moving, third-party perspective, and meditation were confirmed to enhance rapid recovery in the emotional processing process for grief. The implications of this study are as follows. The process of recovering from the grief caused by business failures of serial entrepreneurs was attempted by a qualitative study. By extending the theory of Shepherd(2003), This study can be applied to help with recovery research. In addition, conceptual models and propositions for future empirical research were presented, which can be discussed in carious academic ways.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.3
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• pp.391-409
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• 2022

In this study, class demonstrations conducted integrating science education and 'Education for Sustainable Development (ESD)' by pre-service science teachers were analyzed, focusing on the concept of 'sustainable happiness' and the main elements of 'complexity theory'. In addition, changes before and after participating in such education implementation were analyzed from various angles. Through this, pre-service science teachers tried to derive implications for developing multidimensional teacher professionalism in ESD. The main findings are as follows. First, as a result of peer evaluation of class materials and class demonstrations designed by pre-service science teachers, the average of the integration for 'sustainable happiness' was relatively high. Next, it was analyzed that the elements of 'sustainable happiness' and 'complexity theory' generally had a positive correlation with ESD. In addition, after participating in the study, pre-service science teachers considered individual and social behavioral patterns as important in the sense of ESD. Regarding the need to integrate science education and ESD, pre-service science teachers thought it was necessary to deal with the concept of 'sustainable happiness' in science education to understand a sustainable way of life. It was analyzed that the elements of 'sustainable happiness' and 'complexity theory' generally had a positive correlation with ESD. It was found that pre-service science teachers' confidence in incorporating ESD in science classes was significantly higher after participation in the study. In addition, it was analyzed that pre-service science teachers have come to think more about the role of teachers who can communicate with students and think about happy lives together than before. Overall, it is thought that pre-service science teachers have come to think of multidimensional science teacher professionalism by applying the perspective of the teaching and learning strategy of the new ESD, which integrates the concept of 'sustainable happiness' and elements of 'complexity theory'.

• Journal of The Korean Association For Science Education
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• v.42 no.1
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• pp.77-96
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• 2022

This study investigated how collaborative reflection between novice secondary science teachers promoted the development of teaching professionalism. We intentionally selected research participants who shared sufficient rapport. Data were collected by videotaping the classes taught by participants, pre-talk, post-interviews and nine collaborative reflection processes. All data were transcribed and analyzed. Results indicated that all three teachers showed changes in teaching practice. Minyoung's practice involved a teacher-led lecture, but through collaborative reflection, she could create a learning environment to enhance students' power and ownership in her class. Emphasizing academic rigor, Soyoung used to teach content outside the scope of the curriculum, but through collaborative reflection, she became more considerate of students' understanding. Finally, in Jiyeon's classes inquiry activities and theoretical explanations were separated from each other. However, she repeated her efforts to improve her class after collaborative reflection, allowing students to construct explanations through activities. In this study, three factors that promoted the development of teachers' pedagogical content knowledge through collaborative reflection were identified. First, the different teaching orientations of the three teachers who participated in this study, promoted sharing of opinions through collaborative reflection. Second, reflection based on teaching practice enabled practical feedback on the class, which enhanced the development of teachers' pedagogical content knowledge. Third, the equal status and formation of rapport between the three teachers created an environment for productive reflection. These results suggest that future teacher education programs should target communities that can promote collaborative reflection based on teachers' teaching practice.

• Journal of Mushroom
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• v.21 no.3
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• pp.93-100
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• 2023

In this study, research trends in mushroom science were examined using North Korean journal articles published in 1978-2023. Researchers in each field reviewed 450 papers and finally selected 429 papers, excluding 21 papers classified in different fields. The number of researchers was 872, and the number of authors per paper was 2.03. Kim Cheol-Hak published the most academic papers in the field of mushroom science in North Korea, with 12 papers. The number of research articles increased annually, from 7 in 1985, 12 in 1998, 11 in 2008, and 27 in 2020, and has especially increased rapidly since the mid-2010s. The study by mushroom type was as follows: 42 pine mushrooms (17.8 %), 25 oyster mushrooms (10.6 %), 23 Ganoderma sp. (9.8 %), 19 shiitake mushrooms (8.1 %), 17 button mushrooms (7.2 %), and 16 manna lichens (6.8 %). This study is considered meaningful in reviewing the research status and technology level in North Korea through analyzing North Korean academic journals in the field of mushroom science for the first time.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.302-318
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• 2023

The purpose of this study was to study to the effect of presenting SBF questions on the level of conceptual achievement and eye movement of elementary students in seasonal constellation learning that requires systems thinking. In this study, the effectiveness of SBF questions was divided into experimental groups and comparison groups, and scientific texts with different question types were presented to analyze the level of conceptual achievement and differences in eye movement of sixth-grade elementary students. Data analysis quantitatively analyzed the pre- and post-test results of the developed concept test paper and the eye movement data when learning scientific texts related to seasonal constellations. As a result of the study, first, the SBF question was a valid learning strategy for learning seasonal constellations. The SBF question showed a statistically significant difference (p<0.05) in the pre- and post-test between groups, and a statistically significant difference (p<0.001) in the pre- and post-test within the group. Second, SBF questions had a positive effect on students' learning by inducing learners with low preconceptions to area of interest that help them achieve concepts. In other words, when presenting SBF questions with visual data from a space-based perspective, it was confirmed based on the results of eye movement analysis that there was a significant difference in total fixation count (p<0.01) of learners. On the other hand, for learners with high scientific preconceptions, the effect of exploration was not significant because the preconceptions of the learners themselves acted as a hard core rather than the effect of SBF questions. This study is different from existing seasonal constellation learning studies in that it provides quantitative data through pre- and post-test and eye movement analysis in the seasonal constellation learning process, and can help elementary students learn seasonal constellations.