• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1018-1023
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• 1993

In mechanical structure design area, many FEM (Finite Element Method) packages are used. But the design using FEM packages depends on an iterative trial and error manner and general CAD systems cannot cope with the change of parameters. This paper presents a methodology for building a designing system of a mechanical structure. This system can generate the drawing for a designed structure automatically. It consists of three steps: generation of a structure by selection of the parameters, stress analysis, and generation of a drawing using CAD system. FEM module and parametric CAD module are developed for this system. Inference engine module generates the parameters with a rule base and a model base, and also evaluates the current structure. The parametric design module generates geometric shapes automatically with given dimension. Parametric design is implemented with the artificial intelligent technique. In older to the demonstrate the effectiveness of the developed system, a frame set of bicycle was designed. The system was implemented on an SUN workstation using C language under OpenWindows environment.

• International Journal of Knowledge Content Development & Technology
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• v.3 no.1
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• pp.19-29
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• 2013

Insights from the recent wealth of popular books on neuroscience are offered to suggest a strengthening of theory in information science. Information theory has traditionally neglected the human dimension in favour of 'scientific' theory often derived from the Shannon-Weaver model. Neuroscientists argue in excitingly fresh ways from the evidence of case studies, non-intrusive experimentation and the measurements that can be obtained from technologies that include electroencephalography, positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG). The way in which the findings of neuroscience intersect with ideas such as those of Kahneman on fast and slow thinking and Csikszentmihalyi on flow, is tentatively explored as lines of connection with information science. It is argued that the beginnings of a theoretical underpinning for current web-based information searching in relation to established information retrieval methods can be drawn from this.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.467-468
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• 2016

The importance of the recent manufacturing industry have been made to invest in a lot of assistance and human resource development at the national dimension in which to rise again. However Learned in actual school education kinetic, and the use to how product design structural knowledge, Often it feels vague unlikely whether it is possible to derive an optimal product. In this study, by using the simulation-based Jansen Mechanism designed a walking robot, after optimization of the numerical consideration when designing for optimum walking motion, through simulation through the actual production resulting numerical information is examined whether valid. In addition, through the actual production was walking robot, to verify the validity of the simulation-based design.

• Journal of Korean Elementary Science Education
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• v.24 no.5
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• pp.612-619
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• 2005

Dimensions of learning, based on the vast studies on teaming psychology and teaming processes, have been played an important role as one of the frameworks of curriculum and teaming strategies. Dimensions of Learning consist of 5 Dimensions, each of 'Attitudes and Perceptions', 'Acquire and Integrate Knowledge', 'Extend and Refine Knowledge', 'Use Knowledge Meaningfully', 'Habits of Mind'. And each dimension has $3\~8$ lower categories in itself, The elementary 5th grade science lesson emphasizing upon Dimensions of Learning was developed in this study. The lessons dealt with almost every lower categories of Dimensions of learning. We analysed students' scientific attitude and scientific achievement quantitatively after the lesson emphasized upon Dimensions of Learning in comparison with typical lesson laying stress on teachers' guides. The results are as follows; Students' scientific attitude was significantly changed after the lesson emphasized upon Dimensions of Learning. The willingness, positiveness, straightforwardness, and openness of lower categories of students' scientific attitude were more significantly changed especially. But students' scientific achievement was not significantly changed after the lesson emphasized upon Dimensions of Learning.

• The Journal of Information Systems
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• v.16 no.3
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• pp.45-68
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• 2007

This study aims to explore factors of Assimilation Gap(AG) which is proposed and illustrated by Fichman and Kemerer(1997). AG is defined as the time delay between adoption and deployment and mainly studied at the organizational level. This study derives the factor affecting AG through a review of technology acceptance models and agency theory. The research model consists of three groups of independent variables(IT knowledge burden, Individual characteristics, and organization characteristics) and a moderator, which is goal incongruence. Using multiple regression analyses, four groups of hypotheses are tested with data of 221 knowledge workers from various organizations through e-mail survey. The result shows that radicalness(a dimension of knowledge burden), personal innovativeness, self-efficacy, and organizational support are statistically significant factors while complexity, experience, and perceived critical mass are not supported. The moderator effects of goal incongruence are found in personal innovativeness and organizational support. The results of this study demonstrate that agency theory is a useful perspective to deal with AG, especially in radical innovation. In addition, IT practitioners should consider not only user training but also incentives and possible organizational controls in implementing a new information technology.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.55-66
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• 2023

Community portraits can deeply explore the characteristics of community structures and describe the personalized knowledge needs of community users, which is of great practical significance for improving community recommendation services, as well as the accuracy of resource push. The current community portraits generally have the problems of weak perception of interest characteristics and low degree of integration of topic information. To resolve this problem, the reader community portrait method based on the thematic and timeliness characteristics of interest labels (UIT) is proposed. First, community opinion leaders are identified based on multi-feature calculations, and then the topic features of their texts are identified based on the LDA topic model. On this basis, a semantic mapping including "reader community-opinion leader-text content" was established. Second, the readers' interest similarity of the labels was dynamically updated, and two kinds of tag parameters were integrated, namely, the intensity of interest labels and the stability of interest labels. Finally, the similarity distance between the opinion leader and the topic of interest was calculated to obtain the dynamic interest set of the opinion leaders. Experimental analysis was conducted on real data from the Douban reading community. The experimental results show that the UIT has the highest average F value (0.551) compared to the state-of-the-art approaches, which indicates that the UIT has better performance in the smooth time dimension.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.905-922
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• 2021

Cluster analysis is one of unsupervised learning techniques used for discovering clusters when there is no prior knowledge of group membership. K-means, one of the commonly used cluster analysis techniques, may fail when the number of variables becomes large. In such high-dimensional cases, it is common to perform tandem analysis, K-means cluster analysis after reducing the number of variables using dimension reduction methods. However, there is no guarantee that the reduced dimension reveals the cluster structure properly. Principal component analysis may mask the structure of clusters, especially when there are large variances for variables that are not related to cluster structure. To overcome this, techniques that perform dimension reduction and cluster analysis simultaneously have been suggested. This study proposes probabilistic reduced K-means, the transition of reduced K-means (De Soete and Caroll, 1994) into a probabilistic framework. Simulation shows that the proposed method performs better than tandem clustering or clustering without any dimension reduction. When the number of the variables is larger than the number of samples in each cluster, probabilistic reduced K-means show better formation of clusters than non-probabilistic reduced K-means. In the application to a real data set, it revealed similar or better cluster structure compared to other methods.

• STI Policy Review
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• v.5 no.1
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• pp.34-56
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• 2014

This paper reviews the most central analytical and methodological issues that arise in developing national STI strategies. First, an outline of the relationship between national innovation systems and the strategic dimension is presented. The paper shows that science, technology and innovation strategy are often used in different forms and that there is no common understanding yet of the actual meaning and coverage of these strategies. The paper develops the terminology from a discussion of different approaches towards company innovation processes analyzing their evolution in different socioeconomic environments and the role and impact of science, technology and innovation policy on company innovation processes. Based on this conceptual understanding the paper defines national science, technology, innovation, and STI strategy and explains the basic terminology. From these definitions, the strategic dimension including the impact on the stakeholders is discussed. It is shown that a major success factor for STI strategy development is the involvement of stakeholders to vary and extend their use of their portfolio of instruments. Moreover it becomes evident that stakeholders follow their own interests which aren't necessarily in the interest of the national STI strategies. The analysis shows advantages and disadvantages as well as potentials and limitations of different approaches to develop STI strategies in their ability to describe the reality of innovation processes and to allow conclusions about the relationship between innovation policy and the innovation processes implemented by companies. It is shown that knowledge of these limitations is an important factor to consider in designing consistent and coherent national STI policy which aims at supporting innovation eventually. Finally the paper concludes that the STI policy mix concept needs a more systemic development approach which is integrated in the national STI strategy development and implementation.

• Journal of Science Education
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• v.34 no.1
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• pp.164-174
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• 2010

The purpose of this study was to find out taxonomic characteristics of objectives infered from questions of summative evaluation by analyzing those objectives with Bloom's revised taxonomy of educational objectives. 1,711 questions of midterm and final examinations collected from 25 middle schools were analyzed to classify objective of each question. The major findings of the study were as follows: first, from the analysis of objectives in the knowledge dimension, the assessment of factual knowledge was most prevailing(67.6%) in the biology summative evaluation. In the cognitive process dimension, memory assessment was most dominant(76.1%). Thus, the main objectives of evaluation leaned toward particular classes in the Bloom's revised taxonomy, which was different from the findings of earlier studies on the weights of evaluation areas. Second, the level of the objectives should be determined in consideration of the grade of middle schoolers, as their cognitive level improves with grade. In fact, however, there was no difference among three grades in characteristics of objective taxonomy.

• Journal of Technology Innovation
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• v.25 no.3
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• pp.299-331
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• 2017

This research details firm knowledge search types based on the locus and features for Korean firms in the knowledge-based industry, and then analyzes differences in innovation performance according to the types from the view of a configurational approach. Existing research has mainly concentrated on establishing a relation between knowledge search and outcome variables. Consequently, firms have relatively insufficient understanding of how to systematize knowledge search. Hence, this research classifies knowledge search into four dimensions-external search breadth, external search depth, internal search breadth, and internal search depth-by the locus and features of search. Furthermore, the research draws actual types of knowledge search of firms and analyzes differences in innovation performance. The main result of the research is as follows. First, the research reasons out six clusters of firms which have a dissimilar knowledge search type. Each cluster shows differences while participating in every dimension of knowledge search or few dimensions. Second, as for innovation performance, each cluster shows different exploitative and exploratory innovation performance according to their knowledge search type. This research applies a configurational approach while existing research applied a reductionistic approach, thereby establishing the major contribution which enables us to study a phenomenon as it comes, not to analyze variables and relationships of variables. Lastly, the research suggests a future direction of research based on the result of this research.