Collaborative research has been actively done on the basis of academic relationships among various study area. The importance of collaboration has also been increased. Collaborative researchers can reduce time, cost, and research risk to maximize research productivity. This study aims to develop a framework for understanding the behavior of professional groups through network characteristics. To achieve the goal, we collected data of the co-authored network and that of the reviewer network from from 2006 to 2012. Total 230 submitted papers were analyzed on the views of research performance and productivity. Various analytical methods such as centrality analysis, sub-group analysis, correlation, and regression were conducted for assuring the reliability and validity of our research. The results shows that the productivity of the co-authored network was increased and the efficiency of the reviewer network was also identified through several network indexes.
This study recognized the importance of joint research in the field of artificial intelligence and analyzed the characteristics of the industry-academic-research technological cooperation ecosystem focusing on patents from the perspective of the Techno-Economic Segment (TES). To this end, economic entities such as companies, universities, and research institutes within the ecosystem were identified for 7,062 joint research projects out of 113,289 artificial intelligence patents over the past 10 years filed in IP5 countries since 2012. Next, this study identified the topics of technological cooperation and the characteristics of cooperation. As a result of the analysis, technological cooperation is increasing, and the frequency of all types of cooperation was high in industry-to-industry (40%) and industry-to-university (25.2%) relationships. Here, this study confirmed that the role of universities is being strengthened, with an increase in the ratio of companies with strengths in funding and analytical data, industry and universities with excellent research personnel (9.8%), and cooperation between universities (1.9%). In addition, as a result of identifying collaborative patent research areas of interest and collaborative relationships through topic modeling and network analysis, overall similar research interests were derived regardless of the type of cooperation, and applications such as autonomous driving, edge computing, cloud, marketing, and consumer behavior analysis were derived. It was confirmed that the scope of research was expanding, collaborating entities were becoming more diverse, and a large-scale network including Chinese-centered universities was emerging.
Objectives: This article reviewed researches on intersectoral partnership of school health programs to suggest importance, current status and development plan of those. Methods: Domestic research papers were screened though Research Information Sharing Service (RISS), Koreanstudies Information Service System (KISS), Medical Library Information System (MEDLIS), Korean Medical Database (KMbase), and digital national assembly library. International papers were searched mainly via Pubmed. Results: Since intersectoral partnership is effective, comprehensive and universal approach for school health programs, many collaborative programs are universally progressing in various domain including smoking, alcohol, mental health and sexual behavior. On the other hand, intersectoral partnership of school health programs in Korea is still in the beginning stage, and there are few intersectoral partnerships. Moreover, there are several limitations including top-down approach, passive participation and lack of studies on the effect of intersectoral partnership. However, intersectoral partnerships in school health program including tuberculosis control system in school or WEE project are in progress, so it is worth looking forward in the future. Conclusions: To achieve successful intersectoral partnership in school health programs, appropriate partnership guideline for Korean society, policy support, active participation and improvement of consciousness in community stakeholders are needed.
Journal of the Korean Society for Library and Information Science
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v.53
no.2
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pp.5-27
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2019
The purpose of this study is to analyze the media of middle school social studies 1 textbooks with the information processing model and to suggest educational information services of teacher librarians under a collaborative Instruction. For this purpose, 1,089 inquiry tasks embedded in 8 types of textbooks for middle school social studies developed under the 2015 revised curriculum were analyzed. The media as an input element was analyzed by the type and the characteristic as a processing element was analyzed by the cognitive behavior types. And the aspect of the output factor of the media utilized the multiple intelligences. As a result of the analysis, the media in the inquiry task solving process mainly consisted of visual media based on photographs and illustrations and general reading materials. The processing method of media is understanding through analysis and inference through structuring. And the output utilized speaking and writing of the language intelligence. Based on the results, it is shown that educational information services that teacher librarians could provide for inquiry activities are composed of developing curriculum map, teaching inquiry processing and skills, and designing work sheets with graphic organizer and multiple intelligences under the information processing steps.
Nicholes, Martin O;Chuah, Chen-Nee;Wu, Shyhtsun Felix;Mukherjee, Biswanath
Journal of Communications and Networks
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v.13
no.5
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pp.499-510
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2011
Any server offering a routing service in the Internet would naturally be in competition for clients, and clients may need to utilize service from a specific server in order to achieve a desired result. We study the various properties of this competition, such as the fraction of route requests handled by a routing service provider and the fraction of total revenue obtained. As the routing service providers (i.e., servers or routers in this context) compete, they may alter behavior in order to optimize one of the above properties. For example, a service provider may lower the price charged for its service, in order to increase the number of clients served. Our models are based on servers offering a routing service to clients within representative network topologies based on actual Internet sub-graphs. These models provide, a framework for evaluating competition in the Internet. We monitor key aspects of the service, as several variables are introduced into the models. The first variable is the fraction of client requests that will pay more for a better quality route. The remaining requests are normal client requests that are satisfied by the most economical route. The second variable is the fraction of servers who choose to lower service prices in order to maximize the number of client requests served. As this fraction increases, it is more likely that a server will lower the price. Finally, there are some resource constraints applied to the model, to increase the difficulty in providing a routing solution, i.e., to simulate a realistic scenario. We seek to understand the effect on the overall network, as service providers compete. In simple cases, we show that this competition could have a negative impact on the overall efficiency of a service. We show that the routing variety present in the larger models is unable to mask this tendency and the routing service performance is decreased due to competition.
Journal of the Korea Society of Computer and Information
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v.26
no.1
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pp.265-274
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2021
In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers' purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.
Learning in medical school is usually regarded as a very specialized type of learning compared to that of other academic disciplines. Medical students might have general beliefs about their own learning. Beliefs about learning have a critical effect on learning behavior. There are several factors that affect medical students' learning behavior: epistemological beliefs, learning styles, learning strategies, and learning beliefs. Several studies have addressed epistemological beliefs, learning styles, and learning strategies in medical education. There are, however, few studies that have reported on medical students' beliefs about learning. The purpose of this study was to determine what learning beliefs medical students have, what the causes of these beliefs are, and how medical educators teach students who have such beliefs. In this study, the five learning beliefs are assumed and we considered how these beliefs can affect students' learning behaviors. They include: 1) medical students are expected to learn a large amount of information in a short time. 2) memorization is more important than understanding to survive in medical schools. 3) learning is a competition and work is independent, rather than collaborative. 4) reading textbooks is a heavy burden in medical education. 5) the most effective teaching and learning method is the lecture. These learning beliefs might be the results of various hidden curricula, shared experiences of the former and the present students as a group, and personal experience. Some learning beliefs may negatively affect students' learning. In conclusion, the implications of medical students' learning beliefs are significant and indicate that students and educators can benefit from opportunities that make students' beliefs about learning more conscious.
Journal of Korea Society of Industrial Information Systems
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v.28
no.4
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pp.45-58
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2023
In a world of uncertainty and complexity, leadership is essential to lead collaborative and positive interactions among employees. In other words, if members share opinions and work through voluntary leadership, they will respond more effectively to uncertain challenges and get closer to the targeted management performance. Therefore, in this study, we would like to elucidate the importance of shared leadership, which has recently become an issue. We will examine the impact of shared leadership on team efficacy, team organizational citizenship behavior, and turnover intention. A survey was conducted among members working in a team organization in Busan, and the results were as follows. First, the effects of shared leadership on team efficacy were found to have significant positive(+) effects, such as the hypotheses set at planning and organizing 0.202(C.R.=2.853), problem solving 0.463(C.R.=5.620), support and caring 0.237(C.R.=3.326), and development and mentoring 0.366(C.R.=5.132), respectively. Second, the effects of team efficacy on team organizational citizenship behavior and turnover intention were 0.545(C.R.=5.895) and -0.143(C.R.=-0.817), respectively, and team efficacy was found to have a positive(+)positive(+) effect on team organizational citizenship behavior, but team efficacy did not have a significant effect on turnover intention.
Open Source Software Development (OSSD) differentiates itself from traditional closed software development in that it reveals its source codes online and allows anyone to participate in projects. Even though its success was in doubt, many of the open collaborative working models produced successful results. Academia started to get interested in how developers are willing to participate even when there are no extrinsic rewards for their efforts. Many studies tried to explain developers' motivations, and the pursuit of ideology, reputation, and altruism are found to be the answers. Those studies, however, focused mostly on how the first contribution is made out of a certain motivation. Nowadays, OSSD reaches at its maturity and 70% of professional developers have used or utilized open source software or code in their works. As the proportion of people experiencing OSS, the accounts from previous studies are expected to be weakened. Also, extant literature fails to explain how the motivation of participating in OSS evolves over time and experiences. Given that changing over time or over experiences is the natural in the perception of motivation, studies in an attempt to understand how the motivation changes or evolves are in need. In this study, we aimed to explain how the perception about OSS from past usage or related experiences leads to the intention to sustain OSS participations. By doing so, we try to bridge the gap between previous studies and the actual phenomenon. We argued that perceived instrumentality about OSS learned from past experiences will first affect the formation of organizational identity towards general OSS community. And once the organizational identity is formed, it will affect the one's following behaviors related to OSS development, most likely to sustain the favoring stance toward OSS community. Our research distinguishes itself from previous one in that it divides the paths from organizational identity formed to the intention to sustain the voluntary helping behaviors, by altruistic and conforming intentions. Drawing on this structural model, we could explain how organizational identity engages in forming the sustaining intention from past experiences, and that the intention to help at individual level and organizational level works at different level in OSS community. We grounded our arguments on Social identity theory and Organizational Citizenship theory. We examined our assumption by constructing a structural equation model (SEM) and had 88 developers to answer our online surveys. The result is analyzed by PLS (partial least square) method. Consequently, all paths but one in our model are supported, the one which assumed the association between perceived instrumentality and altruistic intention. Our results provide directions in designing online collaborative platforms where open access collaboration is meant to occur. Theoretically, our study suggests that organizational citizenship behavior can occur from organizational identity, even in bottom-up organizational settings. More specifically, we also argue to consider both organizational level and individual level of motivation in inducing sustained participations within the platforms. Our result can be interpreted to indicate the importance of forming organizational identity in sustaining the participatory behaviors. It is because there was no direct association between perceived instrumentality from past experiences and altruistic behavior, but the perception of organizational identity bridges the two constructs. This means that people with no organizational identity can sustain their participations through conforming intention from only the perception of instrumentality, but it needs little more than that for the people to feel the intention to directly help someone in the community-first to form the self-identity as a member of the given community.
We have suggested three learning rules and implemented an experimental system that automatically restructures hypertext networks according to their user browsing behavior. The system applies link weights to the hypertext networks and updates these weights according to the learning rules. The learning rules are based on how often a particular hyperlink is being traversed and operate on strictly local information of link traversals. Changes in network structure are fed back to users by dynamic link ordering according to descending link weight. This approach is used collaborative filtering and navigation support techniques. The system has been investigation to be able to structure random hypertext networks into valid representations of their user browsing preferences in experiments.
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