• Journal of Educational Research in Mathematics
• /
• v.16 no.2
• /
• pp.95-113
• /
• 2006

The study tries to differentiate the levels of mathematical reasoning from inductive reasoning to formal reasoning for teaching gradually. Because the formal point of view without the relation to objects has limitations in the creation of a new knowledge, our mathematics education needs consider the such characteristics. We propose an intuitive level of proof related in concrete operations and perceptual experiences as an intermediating step between inductive and formal reasoning. The key activity of the intuitive level is having insight on the generality of reasoning. The details of the process should pursuit the direction for going away from objects and near to formal reasoning. We need teach the mathematical reasoning gradually according to the appropriate level of reasoning more differentiated.

• Korean Institute of Interior Design Journal
• /
• no.19
• /
• pp.160-165
• /
• 1999

이 연구의 목적은 실내디자인 학생들간에 나타나는 CAD에 대한 태도, 적성과 그들의 성격 유형간의 관련성을 알아보고 이들 성향이 CAD 교수법에 미치는 영향을 조사하기 위한 것이다. 연구방법은 설문조사, 성격 유형 검사, CAD 성적, 그리고 교과목 성적을 통한 통계분석으로 이루어졌으며, 실험은 실내디자인 전공 3학년 학생 56명을 대상으로 실시되었다. 실험 실시 환경은 CAD가 디자인 도구로 쓰여지는 실내 디자인 실기 수업으로 구성되었으며, 정확한 실험 결과 분석을 위해 CAD 숙련도 성적과 종합 교과목 성적이 분리. 채점되었다. 연구 결과 학생들의 성격 유형은 의향형, 직관형, 느낌형, 및 판단형(ENEJ)을 선호하는 것으로 나타났다. 이는 실험에 참여할 실내디자인 전공 학생들이 직관에 의해 사물을 인지하고, 문제 해결을 하는데 있어 감성에 의지하며, 체계적이고 조직적인 판단력을 가지고 있음을 의미한다. CAD에 대한 태도와 성격유형의 관계에서는 CAD가 유용하다고 생각한 학생들이 느낌형에 강한 선호도를 보였으며, CAD 적성과 성격 유형의 관계에서는 CAD 숙련도 성적이 높은 학생이 판단형에 강한 선호도를 나타내었다. 또한, CAD 성적이 뛰어난 학생이 종합 교과목 성적도 좋은 것으로 나타났다. 이는 CAD 숙련도의 차이가 학생들의 전반적 디자인 능력에도 영향을 끼칠 수 있음을 시사한다. 결론적으로, 이 연구 결과는 학생들의 성격과 학습인지 성향이 컴퓨터 교육의 효율성에 영향을 미친다는 기존의 타 분야에서의 연구결과가 실내디자인 분야에도 타당성을 지님을 증명해주었으며, 실내디자인 수업에 있어 컴퓨터 관련 교과목의 교수법이 실내디자인 학생들의 성격 유형을 바탕으로 개발이 될 때 그 활용 효과를 극대화 할 수 있음을 제시하고 있다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.12
• /
• pp.6484-6487
• /
• 2013

This paper reports the direct controller for nonlinear plants using a neural network. The controller was composed of an approximate controller and a neural network auxiliary controller. The approximate controller provides rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not place too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network was trained and the system showed stable performance for the inputs it has been trained for. The simulation results showed that it was quite effective and could realize satisfactory control of the nonlinear system.

• The KIPS Transactions:PartB
• /
• v.9B no.1
• /
• pp.23-28
• /
• 2002

A fundamental problem in building an intelligent agent is that an agent does not understand the meaning of its perception or its action. One reason that an agent cannot understand the world is partially caused by a syntactic approach that converts a semantic feature into a simple string. To solve this problem, Cohen introduces a semantic approach that an agent autonomously learns a meaningful representation of physical schemas, on which some advanced conceptual structures are built, from physically interacting with environment using its own sensors and effectors. However, Cohen does not deal with a meta level of conceptual primitive that makes recognizing a schema possible. We propose that negation is a meta schema that enables an agent to recognize a physical schema. We prove some semantic aspects of negation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.9A
• /
• pp.1329-1338
• /
• 1999

In this paper, an efficient signal interference control technique to improve the convergence speed of LMS algorithm is introduced. The convergence characteristics of the proposed algorithm, whose coefficients are multiply adapted in a symbol time period by recycling the received data, are analyzed to prove theoretically the improvement of convergence speed. According as the step-size parameter $\mu$ is increased, the rate of convergence of the algorithm is controlled. Also, a increase in the step-size parameter $\mu$ has the effect of reducing the variation in the experimentally computed learning curve. Increasing the eigenvalue spread has the effect of controlling down the rate of convergence of the adaptive equalizer and also increasing the steady-state value of the mean squared error and also demonstrate the superiority of signal interference control to the filter algorithm increasing convergence speed by (B+1) times due to the data-recycling LMS technique.

• Korean Journal of Cognitive Science
• /
• v.6 no.2
• /
• pp.27-45
• /
• 1995

In this paper, we suggest the "Fuzzy Behavior Knowledge Space(FBKS)" and explain how to utilize the FBKS when aggregating decisions of individual classifiers. The concept of "Behavior Knowledge Space(BKS)" is known to be the best method in the context that each classifier offers only one class label as its decision. However. the BKS does not considers measurement value of class label. Furthermore, it does not allow the heuristic knowledge of human experts to be embedded when combining multiple decisions. The FBKS eliminates such drawbacks of the BKS by adapting the fwzy concepts. Our method applies to the classification results that contain both class labels and associated measurement values. Experimental results confirm that the FBKS could be a very promising tool in pattern recognition areas.

• The Journal of Korean Association of Computer Education
• /
• v.10 no.3
• /
• pp.1-8
• /
• 2007

In this paper, we introduce a new measure called surprisal that estimates the informativeness of transactional instances and attributes in the item response dataset and improve the quality of association rules. In order to this, we set artificial dataset and eliminate noisy and uninformative data using the surprisal first, and then generate association rules between items. And we compare the association rules from the dataset after surprisal-based pruning with support-based pruning and original dataset unpruned. Experimental result that the surprisal-based pruning improves quality of association rules in question item response datasets significantly.

• KIISE Transactions on Computing Practices
• /
• v.21 no.2
• /
• pp.160-165
• /
• 2015

Traditional speech emotion recognition techniques recognize emotions using a general training model based on the voices of various people. These techniques can not consider personalized speech character exactly. Therefore, the recognized results are very different to each person. This paper proposes an adaptive speech emotion recognition framework made from user's' immediate feedback data using a prompted labeling technique for building a personal adaptive recognition model and applying it to each user in a mobile device environment. The proposed framework can recognize emotions from the building of a personalized recognition model. The proposed framework was evaluated to be better than the traditional research techniques from three comparative experiment. The proposed framework can be applied to healthcare, emotion monitoring and personalized service.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.4
• /
• pp.653-658
• /
• 2015

Cloud service is one of major challenges in IT industries. In cloud environment, service providers predict dynamic user demands and provision resources to guarantee the QoS to cloud users. The conventional prediction models guarantee the QoS to cloud user, but don't guarantee profit of service providers. In this paper, we propose a new resource allocation mechanism using Q-learning algorithm to provide the QoS to cloud user and guarantee profit of service providers. To evaluate the performance of our mechanism, we compare the total expense and the VM provisioning delay with the conventional techniques with real data.

• The Journal of Korean Association of Computer Education
• /
• v.3 no.1
• /
• pp.75-86
• /
• 2000

No matter how a great value the classwork through Internet may be, the value of Internet can be of negative value if teachers do not intend to make good use of it. Based on this assumption, this research is to show how to draw up a plan for utilizing a effective course of the classwork in high school through Internet, which is now being given attention to an educational environment as a innovative way supporting various educational possibilities compared with a traditional system of education. In addition, this study focuses on the investigation on the classwork through Internet by on-the-spot teachers as a part of all possible efforts for spreading the classwork with network.