Journal of The Korean Association For Science Education
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v.37
no.4
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pp.577-586
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2017
The purpose of this study is to try to structuralize the perception of the mothers of science-gifted elementary students using the concept mapping approach. The mothers who participated in this research had children who were 5th and 6th graders selected as science-gifted by a regional education office, a science high school and two national universities in a city. One of the authors interviewed 26 mothers, and extracted 50 general statements of their perceptions about the career path of their children. Ten mothers who participated in interviews sorted a shuffled pack of statement cards. The categorization of the statements into the dissimilarity matrix was carried out by SPSS multidimensional scaling analysis and hierarchical cluster analysis to generate a conceptual diagram. After that 140 mothers rated each statement using a Likert-type response scale from one to five. The result showed six clusters of parental views such as were 'Burden of private education, grades and going to the next grade,' 'Thinking about career guidance in gifted education and school,' 'Parental roles in child career education,' 'Difficulties in career guidance at home,' 'Demand for strengthening the parental capacity for career guidance,' and 'Demand for social support.' 'Demand for social support' obtained the highest sympathy from mothers of elementary science gifted.
Journal of the Economic Geographical Society of Korea
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v.4
no.1
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pp.61-76
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2001
The purposes of this research are to examine the theoretical background and industrial policy issues with regard to building a Innovation System for encouraging industrial competitiveness and fostering regional industry in Korea. Knowledge has become the driving force of economic growth and the primary source of competitiveness in the world market. So since 1990s, Innovation Systems have been put emphasis on as new industrial development strategy in a knowledge-based economy. It can be understood that Innovation System is composed of National Innovation System(NIS) and Regional Innovation System(RIS) and interrelated the concept of clusters and networks, which are contribute to industry development throughout boosting innovation. As for the Korean industrial policy, when the former centralized policy decision making process became decentralized through the implementation of local autonomy, the role of local or state government in relation to regional industrial promotion intensified. But with the impotance of for fostering strategic industry in the region. new industrial policy issues in Korea are needed as follows; $\circled1$ Building a market-oriented support system for industrial cluster through providing the resource of innovation. $\circled2$ Establishing agency for regional industrial development. $\circled3$ Making a evolutionary vision for broader region including 2 or 3 province, $\circled4$ Fostering strategic industry which is selected in term of specialization and potential of the region. The RIS model for industry development is outlined in this paper but policy initiatives for building a RIS have to be extracted from further case studies.
Due to recent increase in applications requiring huge amount of data such as spatial data analysis and image analysis, clustering on large databases has been actively studied. In a hierarchical clustering method, a tree representing hierarchical decomposition of the database is first created, and then, used for efficient clustering. Existing hierarchical clustering methods mainly adopted the bottom-up approach, which creates a tree from the bottom to the topmost level of the hierarchy. These bottom-up methods require at least one scan over the entire database in order to build the tree and need to search most nodes of the tree since the clustering algorithm starts from the leaf level. In this paper, we propose a novel top-down hierarchical clustering method that uses multidimensional indexes that are already maintained in most database applications. Generally, multidimensional indexes have the clustering property storing similar objects in the same (or adjacent) data pares. Using this property we can find adjacent objects without calculating distances among them. We first formally define the cluster based on the density of objects. For the definition, we propose the concept of the region contrast partition based on the density of the region. To speed up the clustering algorithm, we use the branch-and-bound algorithm. We propose the bounds and formally prove their correctness. Experimental results show that the proposed method is at least as effective in quality of clustering as BIRCH, a bottom-up hierarchical clustering method, while reducing the number of page accesses by up to 26~187 times depending on the size of the database. As a result, we believe that the proposed method significantly improves the clustering performance in large databases and is practically usable in various database applications.
Coping patterns were investigated in a sample of 126 patients with chronic low back pain by means of self-reported questionnaire. Based on the previous researches, coping pat terns were divided into the active cognitive coping, the active behavioral coping, the passive cognitive coping, and the passive behavioral coping. While all the above coping patterns were used, the passive behavioral coping was found to be used most frequently. Six subgroups were identified by cluster analytic procedure using their scores of the coping scale : active cognitive coper, general active coper, passive behavioral coper, general passive coper, multidimensional coper, and multi dimensional non-coper. Six subgroups were compared regarding locus of control, self-efficacy, pain and demographic variables. Distinct differences appeared among subgroups in internal locus of control, self-efficacy, and pain. General active coper and active cognitive coper had higher internal locus of control, higher self-efficacy, and lower pain. General passive coper and multidimensional non-coper had lower internal locus of control, lower self-efficacy, and higher pain. Passive behavioral coper had higher internal locus of control, lower self-efficacy, and higher pain. It supports the concept of learned helplessness due to prior experiences. Multi dimensional coper had higher internal, higher powerful others, and higher self-efficacy. So it corresponds to 'believer in control' group Identified by Wallston et at(1982). Unexpectedly this group also complained more pain. It could be interpreted in two ways. The more coping methods they use, the more they complain pain ; which is the result of Folkman et al (1986). Or they might be typical 'yea sayers'. These unique groups-passive behavioral coper and multidimensional coper-identified by this study supports the suggestion of Wallston et al(1982), about locus of control : individual's pattern of responses across the three scales may be more predictive than his or her scores on each of the scale seperately. The fact that passive coping was used more than active coping also suggests that self controlled active co ping is encouraged to chronic patients as well as acute patients. And it is necessary to articulate the coping scale and self-efficacy scale. It is also necessary to study the relationship of coping and adjustment by experimental design.
Purpose - The ICT market in the EU is lagging behind that of the US; however, algorithm and software development within the EU have grown steadily, and they involve focusing on the creative cultural convergence conceptualized as part of Horizon 2020 and connecting neighboring markets in the EE and the Mediterranean region. It is essential to study the requirements to market the EU's creative ICT development in emerging industrial countries after examining its applicability in these countries. Research design, data, and methodology - This study deals with data pertaining to the EU's creative industry and competitive edge. The global cultural expansion of the EU facilitates a new concept involving not only low-cost IT products to enhance local cultural artifacts through R&D and the construction of efficient infrastructure services, but also information exchange with a realistic commercialization of the technology that can be applied for creative cultural localization. In the European industry, research on algorithms has been applied for the benefit of consumers. We investigated how the process is conducted in the EU. Results - Europe needs to adjust its economic structure to the local culture as part of IT distribution convergence. The convergence has been converted into a production algorithm with IT in the form of low-cost production. This is because there is an attempt to improve the quality of transport infrastructure, workforce availability, and the distribution of the distance to the local industries and consumers, using IT algorithms. Integrated into the manufacturing industry, based on the ICT infrastructure and solutions, smart localized regional clusters are formed with the help of grafting. Europe has own strategy to increase the number of hub-and-spoke cities. Europe is now becoming integrated, with an EPC system for regional cooperation rather than national competition in ICT technology. Europe has also been recognized in this study as changing the step-by-step paradigm for global competitiveness through new creative culture industries. Conclusions - As a result, there are several ways of converging with others through EU R&D intensity; therefore, the EU can be seen as successfully increasing marginal value, which is useful in developing a special industrial cluster or local cultural cities that create converged development by connecting people and objects with IT. In fact, when compared to the US, Europe has a strong culture and the car industries have a tendency to overshadow the IT industries with integration of services in IT distribution. Considering the rapid environmental changes, the convergence of IT services is likely to take place in Europe, similar to the pharmaceutical industry and the automotive industry. This requires a focus on human resources and automated systems management. The trend is to move away from low-wage industries, switched to key personnel centers of the local university-industry. EU emphasizes the creation of IT market demand in Europe involving local cultural convergence for marketing as the second step to strengthen the economic hub-and-spoke areas.
The regional innovation policies so far have been separated from the social problems facing the local communities. The regional innovation policies, regarding the region as the location of the business, have focused on the invigoration of business innovation activities. However, as the recent emergence of the new paradigm of innovation policy aiming the sustainability, 'transformative innovation policy,' has led to a search for regional innovation policies that begin with solving the local social problems. This research paper deals with regional innovation theory that starts from searching for solutions and system transformation for social problems such as climate crisis and energy problems. The objective is to present a new framework called 'transformative regional innovation policy' and to improve its content through case studies by combining the results of the transformative innovation policy and the regional innovation policy studies. In particular, the contribution of this paper is to analyze and discuss the concept of the transition platform, which aims to solve the local social problems, through the case studies of Gussing, Austria and Esbjerg, Denmark. Lastly, it discusses the derived implications of the cases applied in Korean society.
The aim of this study is to demonstrate interaction as a describable field and tries to understand interaction from the perspective of attributes, thus building a theoretical to help interactive designer understand this field by common rule, rather than waste huge time and labor cost on iteration. Since the concept of interaction language has been brought out in 2000, there are varies of related academical studies, but all with defect such as proposed theoretical models are built on a non-uniform scale, or the analyzing perspective are mainly based on researcher's personal experience and being too unobjective. The value of this study is the clustered resource of research which mainly based on academical review. It collected 21 papers researched on interaction paradigm or interaction attributes published since 2000, extracting 19 interaction attribute models which contains 174 interaction attributes. Furthermore, these 174 attributes were re-clustered based on a more unified standard scale, and the two theoretical models summarized from it are respectively focuses on interaction control and interaction experience, both of which covered 6 independent attributes. The propose of this theoretical models and the analyzation of the cluster static will contribute on further revealing of the importance of interaction attribute, or the attention interaction attribute has been paid on. Also, in this regard, the interactive designer could reasonably allocate their energy during design process, and the future potential on various direction of interaction design could be discussed.
In the context of the increasing applications of voice assistants in vehicles, we focused on the association between the visual appeal of the cars and the acoustic characteristics of the voice assistants. This study aimed to investigate the relationship between the visual appeal of the vehicle and the voice assistant based on their emotional characteristics. A total of 15 adjectives were used to assess the emotional characteristics of 12 types of cars and six types of voices. An online interview was carried out, instructing participants to match three adjectives with the presented car images or voices. This was followed with a brief interview to allow the participants to reflect on the adjective matches. Based on the assessments, we performed principal component analysis (PCA) to determine factors. We aimed to deploy the cars and voices and analyze the patterns of clustering. The PCA analysis revealed two factors profiled as "Light-Heavy" and "Comfortable-Radical." Both car and voice stimuli were deployed in a two-dimensional space showing the internal relationship within and between the two substances. Based on the coordination data, a hierarchical cluster grouped the 18 stimuli into four groups labeled as challenge, elegance, majesty, and vigor. This study identified two latent factors describing the emotional characteristics of both car images and voice types clustered into four groups based on their emotional characteristics. The coherent matches between car style and voice type are expected to address the design concept more successfully.
The purpose of this study is to investigate various factors affecting the relationship between digital leadership and digital transformation in companies. In particular, focusing on the mediating effect of dynamic digital capabilities that quickly sensing and seizing advanced and convergent digital technologies and apply them to the organization, this study also intends to examine the moderating effect of the organization's acceptance intention. The hypotheses were verified with a sample of 258 copies of data collected by conducting a survey on companies participating in mini-clusters in industrial complexes nationwide. As a result of the study, dynamic digital capabilities showed a significant mediating effect in the relationship between digital leadership and digital transformation, and the effect of dynamic digital capabilities on the level of digital transformation differed according to the organization's digital acceptance intention. This study presented a new concept and measurement items of digital dynamic capabilities, and how to consider digital leadership, dynamic digital capabilities and acceptance level of organization when promoting digital transformation in companies.
New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.
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