• Korean Journal of Cognitive Science
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• v.9 no.1
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• pp.13-29
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• 1998

This literature review explores the possibilities for the automatic processing to account for the people's responses to emotional stimuli. The most fundamental question is if some parts of emotions are experienced without any intrusion of cognitions. In other words. can emotions be processed completely implicitly$\ulcorner$ Some studies advocate emotion related processes are much more immediate and primary than semantic processes. The phenomena to catch up the emotive values of stimuli even subliminally suggest that the implicit knowledge structure takes charge of this automatic processes of emotional information. This study summarizes the explanatory scheme of emotional processing by means of applying implicit memory principle and physiological evidences related to e emotional memories.

• Journal of the Korean Magnetic Resonance Society
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• v.26 no.1
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• pp.1-9
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• 2022

There are two distinct approaches to improving the quality of protein NMR structures during refinement: all-atom force fields and accumulated knowledge-assisted methods that include Rosetta. Mao et al. reported that, for 40 proteins, Rosetta increased the accuracies of their NMR-determined structures with respect to the X-ray crystal structures (Mao et al., J. Am. Chem. Soc. 136, 1893 (2014)). In this study, we calculated 32 structures of those studied by Mao et al. using all-atom force field and implicit solvent model, and we compared the results with those obtained from Rosetta. For a single protein, using only the experimental NOE-derived distances and backbone torsion angle restraints, 20 of the lowest energy structures were extracted as an ensemble from 100 generated structures. Restrained simulated annealing by molecular dynamics simulation searched conformational spaces with a total time step of 1-ns. The use of GPU-accelerated AMBER code allowed the calculations to be completed in hours using a single GPU computer-even for proteins larger than 20 kDa. Remarkably, statistical analyses indicated that the structures determined in this way showed overall higher accuracies to their X-ray structures compared to those refined by Rosetta (p-value < 0.01). Our data demonstrate the capability of sophisticated atomistic force fields in refining NMR structures, particularly when they are coupled with the latest GPU-based calculations. The straightforwardness of the protocol allows its use to be extended to all NMR structures.

• Knowledge Management Research
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• v.2 no.1
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• pp.83-94
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• 2001

It is a challenging task to introduce and apply a theoretical concept like KM (Knowledge Management) to the corporate management by formulating such notion into a computer-based system. Apart from that, a company who suffers financially will be very much reluctant to employ KM, a solution that will not make an immediate impact on profit generation. Nonetheless, the perception of life-long workplace is being replaced by that of life-long career in today's society, and consequently it has become a key importance for the management to minimizing the Joss of valuable knowledge that results from frequent shift of manpower. Furthermore, knowledge is now regarded as a key to corporate competitiveness as its value has become a more important factor than that of physical resource in estimating a company's value. It is therefore necessary to transform such implicit knowledge that one possesses in his/her mind to a formation so that a company can achieve the ultimate goal of implementing KM: increase of profit and cost reduction. The objective of this research is to look into the case examples of the way in which Samsung Electronics implemented KM and help set the direction for those companies who consider employing KM into their corporate system.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.2
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• pp.73-78
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• 2022

Since Traditional Korean medicine (TKM) doctors use various knowledge systems during treatment, diagnosis results may differ for each TKM doctor. However, it is difficult to explain all the reasons for the diagnosis because TKM doctors use both explicit and implicit knowledge. In this study, an upgraded random forest (RF)-based evaluation tool was proposed to extract clinical knowledge of TKM doctors. Also, it was confirmed to what extent the professor's clinical knowledge was delivered to the trainees by using the evaluation tool. The data used to construct the evaluation tool were targeted at 106 people who visited the Sasang Constitutional Department at Kyung Hee University Korean Medicine Hospital at Gangdong. For explicit knowledge extraction, four TKM doctors were asked to express the importance of symptoms as scores. In addition, for implicit knowledge extraction, importance score was confirmed in the RF model that learned the patient's symptoms and the TKM doctor's constitutional determination results. In order to confirm the delivery of clinical knowledge, the similarity of symptoms that professors and trainees consider important when discriminating constitution was calculated using the Jaccard coefficient. As a result of the study, our proposed tool was able to successfully evaluate the clinical knowledge of TKM doctors. Also, it was confirmed that the professor's clinical knowledge was delivered to the trainee. Our tool can be used in various fields such as providing feedback on treatment, education of training TKM doctors, and development of AI in TKM.

• English Language & Literature Teaching
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• v.8 no.1
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• pp.39-53
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• 2002

Recently much research has investigated the role of attention in L2 learning, comparing the effects of explicit learning with those of implicit learning. With this background the research aims at examining the effects explicit focus on form has on L2 learning based on the acquisition of the English article system. The participants were 70 Korean college students who enrolled in English Composition classes. The experimental group received explicit focus on form including grammatical explanation, input enhancement, output practice, and negative evidence (corrective feedback) for two weeks, while the control group was exposed to sufficient input and negative evidence. Completion tasks were administered at the beginning and the end of the semester. In addition, errors in the use of English articles were analysed on their compositions both before and after the different treatments. The analyses of the results show that the explicit focus on form group improved significantly more than the control group, particularly for the definite article 'the', and some changes occurred in the distribution of article errors. These findings suggest that explicit teaching plays a more contributory role than implicit teaching in acquiring L2 knowledge in classroom-based L2 learning.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.764-770
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• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.

• Physical Therapy Korea
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• v.13 no.3
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• pp.24-32
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• 2006

Theoretical framework of motor learning is used to enhance perceptual motor skill in physical therapy intervention, which can be subdivided into two main types-explicit and implicit. The purpose of this study was to examine whether stroke patients with unilateral brain damage learn implicitly a motor skill using the arm ipsilateral to the damaged hemisphere. Speculation then followed as to the formation of therapeutic plans and instructions provided to patients with stroke. 20 patients with stroke and 20 normal participants were recruited. All the subjects practiced serial reaction time tasks for 30 minutes a day and retention tests on the following day. The tasks and tests involved pressing the corresponding buttons to 4 colored circles presented on a computer screen as quickly and accurately as possible. Patients with stroke responded more slowly than controls. However, both groups showed decreased reaction time in the experimental and retention periods. Also, there was no significant difference between both groups regarding explicit knowledge of consecutive order. Therefore, patients with stoke had the ability to learn implicitly a perceptual motor skill. Prescriptive instruction using implicit and explicit feedback may be beneficial for motor skill learning in physical therapy intervention for patients with brain damage.

• Environmental and Resource Economics Review
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• v.17 no.3
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• pp.61-89
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• 2008

In this study, by extending the model proposed by Fullerton and Kim(2006), we explored the tax interdependency effect to examine the relationship between environmental tax and economic growth. The theoretical model shows that environmental tax cannot always stimulate economic growth if other taxes such as labor or income tax are distorted by environmental taxes. However, environmental tax can boost economic growth if cutting distortionary taxes offset the distortion of taxes, or improvement of abatement knowledge can sufficiently reduce the cost of production. An empirical analysis using 14 OECD countries shows a positive relationship between the increase of implicit energy tax rate and the increase of implicit income tax rate. Meanwhile, empirical analysis does not provide enough evidence to claim that the increase of implicit energy tax decreases implicit labor tax. We can presume that environmental tax policy in Europe did not necessarily mitigate the burden of labor tax.

• Archives of design research
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• v.15 no.1
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• pp.27-36
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• 2002

To do this, study of human memory and theoretical approach on form in general is carried out to compare the types of memories and the stage of perceive theoretically to discover the relationship between psychological perceive and form. In the second please, scenario of form recognition in cultural aspect is studied through various written records to obtain unbiased critics on what a person can feel from a form through various analysis and experiment. Examples will be given on products designed on the basis of correlation with form through analysis. Through this procedure, elements of reactions on implicit and explicit is derived (Data obtained from experiments on computers and inquiries are used) Analyzed elements are than divided into, general knowledge, memories of reality and subconsciousness memories and basic mental image and user mental image and mental image of form of each products are analyzed. In the third phase, the way of adapting of the elements obtained from the analysis of implicit and explicit reaction to the field of design is predicted. Together with this, future theme this the study will be suggested. Confusions obtained from this study can be listed as below.

• Journal for History of Mathematics
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• v.22 no.3
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• pp.113-130
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• 2009

It can be said that the teaching and learning of mathematical problem solving has been greatly influenced by G. Polya. His heuristics shows down the explicit process of mathematical problem solving in detail. In contrast, Polanyi highlights the implicit dimension of the process. Polanyi's theory can play complementary role with Polya's theory. This study outlined the epistemology of Polanyi and his theory of problem solving. Regarding the knowledge and knowing as a work of the whole mind, Polanyi emphasizes devotion and absorption to the problem at work together with the intelligence and feeling. And the role of teachers are essential in a sense that students can learn implicit knowledge from them. However, our high school students do not seem to take enough time and effort to the problem solving. Nor do they request school teachers' help. According to Polanyi, this attitude can cause a serious problem in teaching and learning of mathematical problem solving.