• The Journal of Small Business Innovation
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• v.19 no.2
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• pp.53-68
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• 2016

Motivation and activities for technological learning, entrepreneurship, innovation, and creativity are driving forces of economic development in Asian countries. In the early stages of technological development, technological learning and entrepreneurship are efficient ways in which to catch up with advanced countries because firms can accumulate skills and knowledge quickly at relatively low risk. In the later stages of technological development, however, innovation and creativity become more important. This study aims to identify a) the factors (learning capabilities) that influence technological learning performance and b) barriers to enhancing innovation capabilities for the creative economy and organizations. The major part of this study is related to learning capabilities in the post-catch-up era. Based on a literature review and observations from Korean experiences, this study proposes a technological learning model composed of various influencing factors on technological learning. Three hypotheses are derived, and data are collected from Korean machine tool manufacturers. Intense interviews with CEOs and R&D directors are conducted using structured questionnaires. Statistical analysis, such as correlation and ANOVA are then carried out. Furthermore, this study addresses how to enhance innovation capabilities to move forward. Innovation enablers and barriers are identified by case studies and policy analysis. The results of the empirical study identify several levels of firms' learning capabilities and activities such as a) stock of technology, b) potential of technical labor, c) explicit technological efforts, d) readiness to learn, e) top management support, f) a formal technological learning system, g) high learning motivation, h) appropriate technology choice, and i) specific goal setting. These learning capabilities determine firms' learning performance, especially in the early stages of development. Furthermore, it is found that the critical factors for successful technological learning vary along the stages of technology development. Throughout the statistical and policy analyses, this study confirms that technological learning can be understood as an intrinsic principle of the technology development process. Firms perform proactive and creative learning in the late stages, while reactive and imitative learning prevails in the early stages. In addition, this study identifies the driving forces or facilitating factors enhancing innovation performance in the post catch-up era. The results of the preliminary case studies and policy analysis show some facilitating factors such as a) the strategic intent of the CEO and corporate culture, b) leadership and change agents, c) design principles and routines, d) ecosystem and collaboration with partners, and e) intensive R&D investment.

• The Korean Journal of Food And Nutrition
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• v.11 no.1
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• pp.61-67
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• 1998

Effects of various jelly prepared with different concentrations of agar and sugars on overall acceptability of the peach jelly were investigated. The preparations of peach for experimental jelly were carried by the mixture of peach pulp and juice(MPJ), and the extract form peach(EP). The results were summarized as follows ; 1. The pH for MPJ and EP were 3.95 to 4/31, respectively, and the brix degree were 13.0% and 11.5%, respectively. 2. The jelly prepared with MPJ added 3% agar and 30% sugar were most effective in appearance, hardness, springiness and overall acceptability. The relation of samples(P<0.001) was found to be significant. On the other hand, the jelly prepared with EP was higher scored than that with MPJ in overall acceptability, but there was no significant differences between samples. 3. The Hunter values of L*, a* and b* were the highest in both the jelly prepared with MPJ and that with EP, added 2% agar and 10% sugar. However, the L*, a* and b* values of the jelly added MPJ were higher than those of the sample added EP. 4. Texture and color scores of both the jelly added EP became higher as the concentrations of agar and sugars increased and there was significant differences between samples. 5. The relation between springiness and overall acceptability, and L* value of the jelly added MPJ showed negative at P<0.05 and that between springiness and overall acceptability of the jelly added EP also showed negative.

• The Korean Journal of Food And Nutrition
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• v.11 no.1
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• pp.11-19
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• 1998

This study was performed to investigate the information of food preference of workers for meal served by industry foodservice. The subjects were composed of 212 office workers and 220 laborers. The results were obtained as follows : 50.7% of the subjects were 30∼39 years old ; 72.0% of them had high school education ; the type of favored food was Korean style cooked rice ; food taste was the most important point in food selection. Preference form main foods : Cooked rice was preferred the most by the subjects. Both office workers and laborers liked Kalkooksoo and vegetable bread and cooked rice covered with beef was preferred by office workers and cooked rice covered with raw fish pieces was preferred by laborers. Also they disliked Hash rice, Curry rice and rice-cake soup in the pattern. Preference for side-dish : The Acceptances for side-dishes were high in soybean paste soup(office workers : 37.5%, laborers : 31.5%), hot chowder of corvina(26.1%, 25.7%), kimchi stew(30.5%, 28.8%), beef broiled in soy(32.5%, 30.5%), baked fish(32.5%, 31.9%), pachon(20.7%, 25.9%), a meat inside a razor clam(25.1$, 29.2%) and Chinese cabbage kimchi(44.5%, 46.3%), in that order by both of them. But in office workers, seasoned bean sprouts and steamed beef-rib were shown to have high preference and in laborers seasoned spinach and steamed pork-rib were high. Preference of snacks : The preferences for snacks were high in milk(office workers : 50.3%, laborers : 48.5%), Songpean(28.9%, 30.1%), coffee(30.8%, 32.5%), Sikhye(18.8%, 17.5%), in that order by two groups.

• Cartoon and Animation Studies
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• s.24
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• pp.173-197
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• 2011

Through a story, the audience moves between fiction and reality. A story is an emotional experience that appeals to human feeling. The rational function of a story is to convey knowledge and information, and its emotional function is to touch the audience. Moreover, these aspects of a story are linked to its language, text, and imagery. This paper focuses on the emotional function of a story. In a experiential story, the audience's emotional response is a result of maximum dramatic communication between them and the characters. Through psychological and mental communion with the characters, the audience becomes immersed in the story when they emotionally identify with the characters, and dramatic communication is achieved. However, dramatic communication is mostly achieved instantaneously. The elements of a film need to be realized to sustain dramatic communication such that the audience continues to be immersed in the story. The audience can identify with the characters who are placed in real-life situations by considering the characters' external and internal aspects. External search pertains to the tangible aspects of the character such as its background, life, and conversation. Through the audience's external search, the characters communicate with the audience. Internal search deals with aspects of the characters' personality such as their self-concept, desires, and internal conflicts. Through internal search, the audience understands the inner side of the characters. In this process, a film director should ensure that the acting depicts the inner side of the characters. In other words, the director should perfectly depict the internal and external elements of a human on screen. Appropriate visualization can lead to dramatic communication with the characters and thereby create the audience's emotional response. Considering these techniques, this paper focuses on the scenes of the film "Poetry" in which dramatic communication with the characters creates the audience's emotional response. Accordingly, the audience plays a role in sustaining dramatic communication for the physical screen time of a film.

• The Journal of Art Theory & Practice
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• no.2
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• pp.75-120
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• 2004

Studies on western art in Korea has been caught in a dilemma that they could deal with only those things which had been arranged according to their 'historical generalization' in their contexts because of the bounds of time and space. It is not trivial that such conditions affect art studies in Korea. Access to the original texts and to their contexts of production is so restricted that the studies on them are prone to he superficial. And it is not independent on the politics of Korean art scene. Such factors are on the background of Korean art's excessive 'assimilation or accordance' with western art. The domestic studies on western art history and art theory have failed to notice the differences in context and Korean art has simply mediated or reproduced the restricted information by those studies. Also the studies on western art in Korea have been made use of as a justifying method of one's own academic domains. In such situations we should lead the studies on western art history and western art theory to a more reflective direction and confirm that the studies should not have any privileges of the realities. And we should try to reform a scholarship which participates in our life and existence. The field of domestic studies on western art history and western art theory should free itself from the invention of objectivity or the neutrality of mechanical reading and turn its eyes to the realities of life where events happens. Constantly suggesting which way Korean art and world art should go has to be the field's new coordinates.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.227-240
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• 2011

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.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of radiological science and technology
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• v.37 no.3
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• pp.211-221
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• 2014

The clinical practices provide the students with a good opportunity to study the practical experiences in their field through the clinical training education in hospital. Now, in this study, comparing the perceptions of the clinic teachers with those of students at the clinical site. The study was conducted to the students attending universities located in Seoul and who finished the clinical practices in 2013. The questionnaires were distributed to the student and collected from them. The study were conducted to 275 questionnaires with frequency analysis, crosstabs, chi-square test and McNemar test. The major motivation was of the select radiography course was high employment rate(44.0%) and the satisfaction of radiography course was general(53.1%). 51.3% of the study answered 8 weeks current duration of clinical practices is proper. The 3-year course students answered that the period of clinical practices would be proper if it is performed in the winter vacation in their second year in college(47.3%). The 4-year course students answered that the first semester in their third years is proper for clinical practices( 27.7%). The students answered that they felt the lack in their knowledge on the professional field(32.4%) during the clinical practices and some of the practical training is different from the education performed at school(68.4%). Most of answered that they were satisfied with the clinical practices and among them they recognized the importance of the clinical practices ($3.94{\pm}0.89$). After the clinical practices, their desire for getting job as a radiography has changed from 84.1% to 82.9%. The reason why they want the job related to the radiation is because the job is stable (changed from 49.0% to 46.0% after the clinical practice) while the reason why they don't want be a radigrapher because that job is not proper for them (changed from 37.0% to 40.7% after the clinical practice) The effort should be made to enhance the position of radiation professionals through the improved education system to the students, rather giving them education for just employment.

• Journal of The Korean Association For Science Education
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• v.32 no.5
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• pp.903-927
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• 2012

The study aimed to analyze middle school students construction of physics inquiry problems for open inquiry from the viewpoint of variable isolation and clarification, and investigate students' difficulties during the processes of variable isolation and clarification to get implications for teaching and learning strategies for small group open inquiry activities which have been included in the 2007 national curriculum. The participants were 4 students who had attended an outreach program for the science gifted run by a university institution located in Seoul area. They performed an open inquiry on egg drop for 13 lessons for 30 hours. Level descriptions for variable isolation and clarification have been developed and applied to analyze students' inquiry problems and variables included by the problems. Students iterated inquiry processed 5 times and the inquiry problem showed progress gradually. Dependent variables have been isolated ahead and the levels of variable isolation and clarification showed higher than the independent variables. Many kinds of independent variables isolated extensively and the independent variables and control variables have been mingled. One of the reasons why students had some difficulties in isolation of independent variables could be the absence of theoretical models. The realities of school lab could restrict the variable isolation and clarification as well as topic selections. Some sensory or extensive variables such as broken eggs and drop height seem to be salient to be focused on as core variables. Lack of background knowledges could be one of the reasons for students' difficulties in variable clarification, such as theoretical definitions and operational definitions. As a result of lacking background knowledges, students could not construct theoretical models even though they could isolate and clarify variables as scientific lexical definitions. Some perceptions of inquiry as trial and error or reckless establishment of causal relations between variables could be accounted as one reason.