• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1073-1079
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• 2007

The purpose of this study is to present the relationship between the computer learning and the paper and pencil learning through the math learning (simple computation and complex computation) and the cartoon learning and text learning. The canonical correlation and pairwise t-test of the SMR asymmetry brainwaves of the left and the right brain show the brainwaves with the respect to the manner in which they process information during the specified task by identifying the relative activity of the brainwaves of the left and the right brain. SMR brainwave which known as the scientific measure tool for the activity and the function of the neuronal cell were found to predict the level of the awakening to check the readiness of study preparation. Computer education as a medium of the individualized and the repetitive education shows the difference from the paper and the pencil test in the respect of the differences and the relationship of the SMR brainwave of the learning process.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.160-169
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• 2022

This qualitative study aimed to investigate ways to improve effective cooperative learning from students' perspective by understanding and analyzing the learning experiences of nursing students who participated in a collaborative problem-solving learning model. Data were collected through focus group interviews and reflection journals of six second-year nursing students from G-university in J-city who participated in a collaborative problem-solving learning model course. The interview data were analyzed and divided into 3 categories and 10 subcategories according to the six-step thematic analysis method proposed by Braun and Clarke. The results of analyzing the interviews were considered based on three areas: preparation before learning, the process of collaborating as a cooperative learning experience, and solutions and expectations after learning. The participants felt frustrated because collaborative problem-solving took more time for individual learning than traditional methods did and would not allow them to check the correct answers immediately. However, they gained new experiences by solving problems and engaging in discussions within their learning community. The participants' expectations included material that could help their learning, measures to prevent free-riders, and consideration of the learning process in evaluation factors. Although this study has sample limitations by targeting nursing students in only one region, it can be used to help operate collaborative problem-solving classes, as it reflects the real experiences and opinions of students.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.143-148
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• 2021

The article considers the training of specialists in education in the conditions of distance learning. It is lights up the advantages of distance learning and determined the characteristic features of distance learning of students training in the implementation of these technologies in the educational process. The article focuses on the main aspects of computerization of studies as a technological breach in methodology, organization and practical realization of educational process and informative culture of a teacher. Information technologies are intensive involved in life of humanity, educational process of schools and higher educational establishments. Intercommunication is examined between the processes of informatization of the society and education.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1061-1065
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• 2004

The knowledge-based society of the 21st century requires effective education and learning methods in each professional field because the development of human resource determines its competence more than any other factors. It is highly desirable to develop an intelligent tutoring system, which meets ever increasing demands of education and learning. Such a system should be adaptive to each individual learner's demands as well as the continuously changing state of the learning process, thus enabling the effective education. The development of a learning environment based on learner modeling is necessary in order to be adaptive to individual learning variants. An intelligent learning environment is being developed targeting the heritage education, which is able to provide a customized and refined learning guide by storing the content of interactions between the system and the learner, analyzing the correlations in learning situations, and inferring the learning preference from the learner's learning history. This paper proposes a heritage learning system of Bulguksa temple, integrating the ontology-based learner modeling and the learning preference which considers perception styles, input and processing methods, and understanding process of information.

• Asia Marketing Journal
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• v.15 no.3
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• pp.79-95
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• 2013

New product innovation is a process of embodying new knowledge in a product and technology licensing is getting popular as a means to innovations and introduction of new product to the market in today's competitive global market environment. Incumbents often rely on technology licensing to access new product opportunities created by other firms. Prior research has examined various aspects of technology licensing agreements such as specific contract terms of licensing agreements, e.g., distribution of control rights, exclusivity of licensing agreements, cross-licensing, and the scope of licensing agreements. This study aims to provide answers to an important, but under-researched question: why do some incumbents initiate more licensing agreement for exploratory learning while others do it for exploitative learning along the innovation process? We attempt to extend our knowledge of licensing agreements from an organizational learning perspective. Technology licensing as a specific form of interfirm linkages can be initiated with different learning objectives along the process of new product innovation. The exploratory stages of the innovation process such as discovery or research stages involve extensive searches to create new knowledge or capabilities, whereas the exploitative stages of the innovation process such as application or test stages near the commercialization are more focused on developing specific applications or improving their efficiency or reliability. Thus, different stages of the innovation process generate different types of learning and the resulting technological resources. We examine when incumbents as licensees initiate more licensing agreements for exploratory learning objectives and when more for exploitative learning objectives, focusing on two factors that may influence a firm's formation of exploratory and exploitative licensing agreements: 1) its past radical and incremental innovation experience and 2) its internal investments in R&D and marketing. We develop and test our hypotheses regarding the relationship between a firm's radical and incremental new product experience, R&D investment intensity and marketing investment intensity, and the likelihood of engaging in exploratory and exploitive licensing agreements. Using data collected from various secondary sources (Recap database, Compustat database, and FDA website), we analyzed technology licensing agreements initiated in the biotechnology and pharmaceutical industries from 1988 to 2011. The results of this study show that incumbents initiate exploratory rather than exploitative licensing agreements when they have more radical innovation experience and when they invest in R&D activities more intensively; in contrast, they initiate exploitative rather than exploratory licensing agreements when they have more incremental innovation experience and when they invest in marketing activities more intensively. The findings of this study contribute to the licensing and interfirm cooperation studies. First, this study lays a foundation to understand the organizational learning aspect of technology licensing agreements. Second, this study sheds lights on how a firm's internal investments in R&D and marketing are linked to its tendency to initiate licensing agreements along the innovation process. Finally, the findings of this study provide important insight to managers regarding which technologies to gain via licensing agreements. This study suggests that firms need to consider their internal investments in R&D and marketing as well as their past innovation experiences when they initiate licensing agreements along the process of new product innovation.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1820-1831
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• 2010

When interacting with unknown environments, an autonomous agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. The traditional multiple sequential learning model requires predefined probability of the states' transition. This paper proposes a multiple sequential learning and prediction system with definition of autonomous states to enhance the automatic performance of existing AI algorithms. In sequence learning process, the sensed states are classified into several group by a set of proposed motivation filters to reduce the learning computation. In prediction process, the learning agent makes a decision based on the estimation of each state's cost to get a high payoff from the given environment. The proposed learning and prediction algorithms heightens the automatic planning of the autonomous agent for interacting with the dynamic unknown environment. This model was tested in a virtual library.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.234-239
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• 1990

A neural controller for process control was proposed that combines a simple feedback controller with a neural network. This control was applied to distillation control. The feedback error learning technique was used for on-line learning. Important characteristics on neural controller were analyzed. The proposed neural controller can cope well with strong interactions, significant time delays, sudden changes in process dynamics without any prior knowledge of the process. It was shown that the neural controller has good features such as fault tolerance, interpolation effect and random learning capability

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.11
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• pp.95-103
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• 1997

A robust center estimation tecnique of n-fold engineering parts is presented, which use self-organizing neural networks with generating and merging learning for training neural units. To estimate the center of the n-fold engineering parts using neural networks, the segmented boundaries of the interested part are approximated to strainght lines, and the temporal estimated centers by thecosine theorem which formed between the approximaged straight line and the reference point, , are indexed as (.sigma.-.theta.) parameteric vecstors. Then the entries of parametric vectors are fed into self-organizing nerual network. Finally, the center of the n-fold part is extracted by mean of generating and merging learning of the neurons. To accelerate the learning process, neural network uses an adaptive learning rate function to the merging process and a self-adjusting activation to generating process. Simulation results show that the centers of n-fold engineering parts are effectively estimated by proposed technique, though not knowing the error distribution of estimated centers and having less information of boundaries.

• Polymer(Korea)
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• v.32 no.6
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• pp.537-543
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• 2008

Crosslinked agar-g-poly(acrylic acid) (x-agar-g-PAA) super absorbent with a water absorbency ($Q_{H2O}$) of approximately 660 g/g was synthesized by the copolymerization of agar with an acrylic acid monomer. KPS and MBA were used as the initiator and crosslinker, respectively. Grafting was performed in air. Infrared spectroscopy was used to identify the product of copolymerization. The optimum conditions to synthesize the x-agar-g-PAA superabsorbent were 0.1 g of agar, 0.1 g of the KPS initiator, for 15 min; 50% AA monomer, 0.005 g of the MBA crosslinker, for a propagation time of 5 min; and 1 M NaOH for 15 min to allow for saponification. The reaction temperature was $80{^\circ}C$.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.420-426
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• 2022

Developing a machine learning model and putting it into production goes through a number of steps. Automated Machine Learning(AutoML) appeared to increase productivity and efficiency by automating inefficient tasks that occur while repeating this process whenever machine learning is applied. The high degree of automation of AutoML models allows non-experts to use machine learning models and techniques without the need to become machine learning experts. Automating the process of applying machine learning end-to-end with AutoML models has the added benefit of creating simpler solutions, generating these solutions faster, and often generating models that outperform hand-designed models. In this paper, the AutoML data is collected and AutoML's Color Petri net model is created and analyzed based on it.