• East Asian mathematical journal
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• v.25 no.3
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• pp.247-262
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• 2009

Permutation and combination are the part of mathematics which can be introduced the pliability and diversity of thought. In prior studies of permutation and combination, there treated difficulties of learning, strategy of problem solving, and errors that students might come up with. This paper provides the method so that meaningful teaching and learning might occur through the systematic approach of permutation and combination. But there were little prior studies treated counting numbers that basic of mathematics' action. Therefore this paper tries to help the understanding of permutation and combination with the process of changing from informal knowledge to formal knowledge.

• Korean Journal of Cognitive Science
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• v.13 no.2
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• pp.47-59
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• 2002

Three experiments were conducted to investigate whether different types (common vs. uncommon) of prior-examples entail different effects in creative problem solving, and whether types/levels (rich or lean. common or uncommon) of background knowledge interact with types of prior-examples. It was found that the example types and the types/levels of background knowledge do interact and have some differential effects on generating novel and useful ideas. In Experiment 1 and 2. uncommon examples had a positive effect - generating many novel and useful ideas. regardless of background knowledge types. while common examples had positive effects, only when the background knowledge was somewhat uncommon In Experiment 3 it was also found that types (irrelevant,. single common. single uncommon, or multiple common + uncommon) of background knowledge seemed to influence differently on the ease of finding solutions: when background knowledge is diverse or not directly related to the task problem, uncommon prior examples produced much greater number of novel ideas than it was with single common or sin91e uncommon background knowledge. Implications of the present study were discussed. in relation to mental sets and fixation.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.1048-1057
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• 2013

This study aims to evaluate the effect on the academic achievement and satisfaction of the learner's prior knowledge level and segmenting time of video lectures in an learning environment using smartphones. Depending on the level of prior knowledge, learners were divided into two groups of the upper 35% and the lower 35%. Each group was offered video lectures by a 5-min, 10-min, 15-min, and 20-min length. As a result, a high level of prior knowledge only had a positive effect on the academic achievement. With respect to the segmentation time of video lectures, 10-min, 15-min lectures were effective to the academic achievement and 15-min, 20-min lectures influenced positively the learners' satisfaction. Moreover, the interaction between the level of learners' prior knowledge and the segmentation time of video lectures only had an impact on their academic achievement. The results of the simple effect analysis conducted to examine the effect of interaction carefully show that 15-min, 20-min video lectures are more effective for the upper 35% in prior knowledge and 10-min ones are better for its' lower 35%. In a nutshell, these findings suggest that the high-prior knowledge groups could be provided with a longer video lectures, and furthermore, 5-min video lectures are not adequate in a mobile learning environment with smartphones.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.295-306
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• 2012

This study analyzed empirically difference of purchase intention about price raising of luxury brand according to consumer characteristics such as consumption value, prior knowledge. and perceived risk. Fist, groups according to consumption value showed obvious differences. Group of pursuing uniqueness and ostentation value and group of pursuing quality and pleasure value showed positive purchase intention but group of pursuing social recognition value showed negative purchase intention. Second, groups according to perceived risk. didn't show difference and groups according to prior knowledge showed obvious difference. group of high prior knowledge showed positive purchase intention but group of low prior knowledge showed negative purchase intention. Third, analyzed result about interaction effect of consumer characteristics, Classified group of pursuing uniqueness and ostentation value, expressing high prior knowledge and Classified group of pursuing quality and pleasure value, expressing high perceived risk only showed positive purchase intention, The results of this study present implication to domestic companies aiming luxury brand that performing differently strategy of product and price according to target characteristics is more effective way in differentiating oneself from existing luxury brands and expanding market.

• Journal of Korean Society of Rural Planning
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• v.24 no.2
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• pp.31-45
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• 2018

The study aims to predict the behavior of tourists in Hadong County, which is registered as KIAHS. Based on the theory of planning behavior, we intend to verify the theory of planned behaviour, which adds descriptive parameters of the perceived value and prior knowledge of an agricultural heritage. In detail, first, the perceived value and prior knowledge of tourists about an agricultural heritage understand the influence of tourists' Attitude. Second, we could see the role of the behavioral factors in the causal relationship of the planned behavioral theory. We have identified the planned behavioral theory that attitudes, subjective norms, and perceptual behavior controls affect the intention of the revisit. Hadong should remember that by sending and providing various information about Hadong Green Tea and World Agricultural Heritage sites, it is possible to elicit changes in visitor attitudes and revisit visits.

• Journal of the Korean earth science society
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• v.32 no.1
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• pp.140-151
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• 2011

This study is to search the problems of schoolyard teaching material developed by pre-service earth science teachers and the critical factors affecting material making. The 258 schoolyard teaching materials was collected from 54 pre-service earth science teachers (male: 18, female: 36) major in Earth Science Education in Jeonju, Korea. The schoolyard teaching materials was greatly influenced by making process type of it and the prior knowledge of pre-service earth science teachers. As schoolyard preference exploratory type rely on their prior knowledge to develop the schoolyard teaching materials, they made use of the limited concepts like fault in material making. But the concept preference exploratory type made use of concepts not accessible to majority of pre-service earth science teachers because they selected a concept from the earth science textbook first of all. The pre-service earth science teachers having wrong prior knowledge selected inappropriate resources, as well as fell into the error of concept connecting. The pre-service earth science teachers having right prior knowledge partly considered only shape of resources, but had a disregard for formation process of it in material making. Accordingly, we need to reflect richly Geological Field Trip and Solid Earth Science to curriculum for earth science teacher education. And we have to educate pre-service earth science teachers to create holistic concept on the geological subject matter knowledge, field based teaching and learning strategy, material making process.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.145-162
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• 1992

This paper proposes two design principles for expert systems to solve a stock market timing (SMART) problems : machine knowledge and fuzzy post-adjustment, Machine knowledge is derived from past SMART instances by using an inductive learning algorithm. A knowledge-based solution, which can be regarded as a prior SMART strategy, is then obtained on the basis of the machine knowledge. Fuzzy post-adjustment (FPA) refers to a Bayesian-like reasoning, allowing the prior SMART strategy to be revised by the fuzzy evaluation of environmental factors that might effect the SMART strategy. A prototype system, named K-SISS2 (Knowledge-based Stock Investment Support System 2), was implemented using the two design principles and tested for solving the SMART problem that is aimed at choosing the best time to buy or sell stocks. The prototype system worked very well in an actual stock investment situation, illustrating basic ideas and techniques underlying the suggested design principles.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.366-370
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• 2005

Tissue microarry is one of the high throughput technologies in the post-genomic era. Using tissue microarray, the researchers are able to investigate large amount of gene expressions at the level of DNA, RNA, and protein The important aspect of tissue microarry is its ability to assess a lot of biomarkers which have been used in clinical practice. To manipulate the categorical data of tissue microarray, we applied Bayesian network classifier algorithm. We identified that Bayesian network classifier algorithm could analyze tissue microarray data and integrating prior knowledge about gastric cancer could achieve better performance result. The results showed that relevant integration of prior knowledge promote the prediction accuracy of survival status of the immunohistochemical tissue microarray data of 18 tumor suppressor genes. In conclusion, the application of Bayesian network classifier seemed appropriate for the analysis of the tissue microarray data with clinical information.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.890-900
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• 2010

The Bayesian networks methods provide an efficient tool for performing information fusion and decision making under conditions of uncertainty. This paper proposes Bayes estimators for the system effectiveness in energy saving of the wireless sensor networks by use of the Bayesian method under the non-informative prior knowledge about means of active and sleep times based on time frames of sensor nodes in a wireless sensor network. And then, we conduct a case study on some Bayesian estimation models for the system energy saving effectiveness of a wireless sensor network, and evaluate and compare the performance of proposed Bayesian estimates of the system effectiveness in energy saving of the wireless sensor network. In the case study, we have recognized that the proposed Bayesian system energy saving effectiveness estimators are excellent to adapt in evaluation of energy efficiency using non-informative prior knowledge from previous experience with robustness according to given values of parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.461-484
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• 2021

Compressed sensing in image reconstruction has attracted attention and many studies are proposed. As we know, adding prior knowledge about the distribution of the support on the original signal to CS can improve the quality of reconstruction. However, it is still difficult for a recovery framework adjusts its strategy for exploiting the prior knowledge efficiently according to the current estimated signals in serial iterations. With the theory of information geometry, we propose an adaptive strategy based on the current estimated signal in each iteration of the recovery. We also improve the performance of existing algorithms through the adaptive strategy for exploiting the prior knowledge according to the current estimated signal. Simulations are presented to validate the results. In the end, we also show the application of the model in the image.