• 제목/요약/키워드: implicit knowledge

검색결과 124건 처리시간 0.025초

정서의 자동처리기제 (The Automatic Processing of Emotion)

  • 이수정;권준모;이훈구
    • 인지과학
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    • 제9권1호
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    • pp.13-29
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    • 1998
  • 이 문헌 연구는 정보처리 기제 중 자동적인 처리과정의 원리로 다양한 정서 자극에 대한 반응양식이 과연 설명될 수 있을지를 타진해 보고자 한다. 인지적인 판단이 필요한 통제과정이 전혀 개입되지 않고서도 정서 유발 자극이 Bargh(1989)가 제시한 자동처리의 원리에 따라 암묵적으로 처리될 수 있을 것인가$\ulcorner$ 몇몇 연구들은 정서 유발 자극에 대한 자동적인 처리과정은 의미론적인 처리과정보다 훨씬 우선적이며 즉각적으로 처리된다고 주장한다. 자각이 없는 상태에서도 정서 가를 파악하는 현상은 우리의 정보처리과정 중 의식적이며 인지적인 개입이 필요한 명시적인 지식 체계에 의해서가 아니라 스스로의 자각이 없이도 처리가 이루어지는 암묵적인 지식의 체계에 의해 담당될 것이라 이해할 수 있을 것이다. 이 연구에서는 이러한 암묵적인 기억과정의 원리와 그에 대한 생리학적인 근거도 제시함으로써 정서가 가미된 정보의 처리과정이 어떠한 경로를 통하여 이루어질 지에 대해 요약하여 보았다.

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Refinement of protein NMR structures using atomistic force field and implicit solvent model: Comparison of the accuracies of NMR structures with Rosetta refinement

  • Jee, Jun-Goo
    • 한국자기공명학회논문지
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    • 제26권1호
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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.

삼성전자(주) 정보통신부문 지식경영시스템 구축 방안 연구 (A Study of Knowledge Management System Construction Plan for the Information & Communications of Samsung Electronics)

  • 이호성;김진봉
    • 지식경영연구
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    • 제2권1호
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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.

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인공지능 기반 평가 도구를 이용한 한의사의 체질 진단 평가 및 활용 방안에 대한 연구 (Research on the Evaluation and Utilization of Constitutional Diagnosis by Korean Doctors using AI-based Evaluation Tool)

  • 박무순;황민우;이정윤;김창업;권영규
    • 동의생리병리학회지
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    • 제36권2호
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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.

The Effects of Explicit Focus on Form on L2 Learning

  • Park, Hye-Sook
    • 영어어문교육
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    • 제8권1호
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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.

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하이브리드 데이터마이닝 메커니즘에 기반한 전문가 지식 추출 (Extraction of Expert Knowledge Based on Hybrid Data Mining Mechanism)

  • 김진성
    • 한국지능시스템학회논문지
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    • 제14권6호
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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.

편측 뇌손상 환자에서 시각적 정보에 의한 운동 순서의 내잠 학습에 대한 분석 (Implicit Motor Sequence Learning During Serial Reaction Time Tasks Induced by Visual Feedback in Patients With Stroke)

  • 이미영;박래준;권용현;박지원;장성호
    • 한국전문물리치료학회지
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    • 제13권3호
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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.

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친환경 조세정책이 경제성장에 미치는 영향 : 내생적 성장모형을 중심으로 (The Effect of Environmental Tax Policy on Economic Growth : An Endogenous Growth Approach)

  • 강성훈;홍종호
    • 자원ㆍ환경경제연구
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    • 제17권3호
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    • pp.61-89
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    • 2008
  • 환경세를 포함한 친환경 조세정책이 경제성장에 미치는 영향에 관한 논쟁은 현재 진행형이다. 본 연구의 목적은 소득세와 노동세가 존재하는 상황에서 친환경 조세정책을 도입했을 때 그것이 경제성장에 미치는 영향을 내생적 성장모형을 통해 이론적 실증적으로 규명하는 데 있다. 본 논문은 이론적으로 크게 두 가지에 초점을 맞추고 있다. 첫째, 환경세수가 오염저감기술 개발을 위한 R&D 투자를 충분히 감당하지 못할 경우 다른 조세의 왜곡이 발생하게 되는데, 이 때 왜곡이 발생하는 조건과 왜곡의 정도를 분석하였다. 둘째, 세수 중립하에서 환경세율이 증가할수록 조세간의 상호작용으로 인해 일부 조세의 세율이 인상될 경우 환경세가 경제성장에 미치는 영향을 살펴보았다. 또한 환경세를 도입한 유럽의 14개 OECD 국가들을 대상으로 실증분석을 수행한 결과, 첫째, 환경세로 인한 다른 조세의 왜곡을 완화시키기 위해 추가적인 조세인하 정책이 필요할 경우 노동세가 소득세보다 효율적인 것으로 나타났다. 둘째, 유럽 국가들이 친환경 조세정책을 도입하는 과정에서 오히려 소득세에 대한 부담은 증가한 반면, 노동세에 대한 부담이 경감되었다는 실증적 근거는 충분하지 않은 것으로 분석되었다.

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사용자 심리적 연상에 의한 제품형태 접근 방법에 관한연구 -암묵기억과 외현기억을 중심으로- (A Study on the Approach Method of Product Form by User Mental -Concentrated on Implicit & Explicit memory-)

  • 안철홍;정도성
    • 디자인학연구
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    • 제15권1호
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    • pp.27-36
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    • 2002
  • 본 연구는 경험에 의한 기억간의 상관관계에 대하여 기초적 연구와 접근방법을 모색하여, 제품의 형태의 구축단계에서의 적용가능성을 예시하였으며, 이를 통해 기억에 의한 디자인 행위와 관련하여 향후연구과제의 초석을 마련하는 데 목격을 두었다. 첫째, 인간의 기억과 형태에 대한 학문적, 이론적 고찰을 통해서 본 연구에 필요한 기억의 유형과 사물에 대한 인지과정을 이론적으로 비교 고찰하였다. 둘째, 실험과 분석을 통해 사물에 있어서의 느껴지는 형태가 무엇인지에 대한 주관적 평가 반응을 알아보고 그 과정의 분석을 통하여 제품에서 느끼는 형태의 연상으로, 암묵적/외현적 반응에 대한 요소(설문과 컴퓨터 실험을 통하여 수집된 데이터를 이용)를 추출하고, 분석된 요소들을 칼융의 심상구분인 보편적 지식과 현실 기억, 그리고 잠재기억과 원시심상으로 구별하여, 형태심상 및 대별 사용자 심상이 디자인에 어떤 영향을 주는가를 분석 정의하였다. 셋째, 이러한 정의를 바탕으로 암묵적/외현적 반응에 대한 요소 특성의 디자인 활용가능성과 통한 접근방법을 예시하고, 결론과 아울러 향후 연구되어질 과제에 대한 가이드라인을 제시하였다.

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폴라니의 인식론과 문제해결의 암묵적 차원 (Polanyi's Epistemology and the Tacit Dimension in Problem Solving)

  • 남진영;홍진곤
    • 한국수학사학회지
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    • 제22권3호
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    • pp.113-130
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    • 2009
  • 수학 문제해결 교육에 가장 많은 영향을 끼친 것은 폴리아(G. Polya)의 이론이다. 폴리아가 제시하는 발견술은 수학 문제해결 과정을 명시적으로 세분화여 드러내고 정리한 것이다. 이와는 달리, 수학 문제해결 과정의 암묵적 차원을 강조하고 있는 폴라니(M. Polanyi)의 이론은 폴리아의 이론과 상보적 관계에 있는 것으로 조명될 필요가 있다. 이 글에서는 폴라니의 인식론을 개관하고, 이를 바탕으로 하는 그의 문제해결 교육 이론을 고찰한다. 지식과 앎을 개인의 마음의 총체적 작용으로 보는 폴라니는 문제해결에 있어서 지적, 정서적 부분과 함께 헌신과 몰두를 강조한다. 또한 명시적 앎 이면에 있는 묵식에 있어서 교사의 역할을 중시한다. 이와 같은 폴라니의 관점은 현재 우리나라 학생들의 수학 문제 해결 양상을 이해하고 문제점을 파악하는 데에도 의미 있는 시사를 제공한다.

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