• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.66-74
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• 2014

Recently a variety of study of Korean parsing system is carried out by many software engineers and linguists. The parsing system mainly uses the method of machine learning or symbol processing paradigm. But the parsing system using machine learning has long training time because the data of Korean sentence is very big. And the system shows the limited recognition rate because the data has self error. In this thesis we design system using feature module which can reduce training time and analyze the recognized rate each the number of training sentences and repetition times. The designed system uses the separated modules and sorted table for binary search. We use the refined 36,090 sentences which is extracted by Sejong Corpus. The training time is decreased about three hours and the comparison of recognized rate is the highest as 84.54% when 10,000 sentences is trained 50 times. When all training sentence(32,481) is trained 10 times, the recognition rate is 82.99%. As a result it is more efficient that the system is used the refined data and is repeated the training until it became the steady state.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.11a
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• pp.53-62
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• 1997

본 논문에서는 전자문서의 개념적 분류기법을 제안한다. 기존의 문서분류는 대부분 문서에 나타난 용어를 기반으로 분류하므로 개념적인 분류가 불가능하다. 제안된 기법에서는 한국어 시소러스를 사용하여 문서에 나타난 용어 뿐 아니라 용어의 상하위 개념을 기준으로 문서를 분류할 수 있다. 특히, 제안된 방법은 확률 벡터를 사용하는 방식으로써 점진적인 학습이 가능하다는 장점도 가진다.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.449-456
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• 2019

This paper is a study on the construction of a wall-climbing mobile robot using vacuum suction and wheel-type movement, and a comparison of the performance of an automatic wall crack detection algorithm based on machine learning that is suitable for such an embedded environment. In the embedded system environment, we compared performance by applying recently developed learning methods such as YOLO for object learning, and compared performance with existing edge detection algorithms. Finally, in this study, we selected the optimal machine learning method suitable for the embedded environment and good for extracting the crack features, and compared performance with the existing methods and presented its superiority. In addition, intelligent problem - solving function that transmits the image and location information of the detected crack to the manager device is constructed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.151-162
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• 1994

A new neural network structure called Self-organized Distributed Networks (SODN) is proposed for developing the neural network-based multidimensional system models. The learning with the proposed networks is fast and precise. Such properties are caused from the local learning mechanism. The structure of the networks is combination of dual networks such as self-organized networks and multilayered local networks. Each local networks learns only data in a sub-region. Large number of memory requirements and low generalization capability for the untrained region, which are drawbacks of conventional local network learning, are overcomed in the proposed networks. The simulation results of the proposed networks show better performance than the standard multilayer neural networks and the Radial Basis function(RBF) networks.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.3
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• pp.17-24
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• 2004

We present a P-type iterative learning control(ILC) scheme for uncertain robotic systems that perform the same tasks repetitively. The proposed ILC scheme comprises a linear feedback controller consisting of position error, and a feedforward and feedback teaming controller updated by current velocity error. As the learning iteration proceeds, the joint position and velocity mrs converge uniformly to zero. By adopting the learning gain dependent on the iteration number, we present joint position and velocity error bounds which converge at the arbitrarily tuned rate, and the joint position and velocity errors converge to zero in the iteration domain within the adopted error bounds. In contrast to other existing P-type ILC schemes, the proposed ILC scheme enables analysis and tuning of the convergence rate in the iteration domain by designing properly the learning gain.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.281-292
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• 2008

The purpose of this study is to implement a visual organizer which enables learners to support web navigation as well as visual understandings in the electronic document space. I developed a visual organizer according to design principles of visual organizer, and then analysed the effect of a visual organizer on the students' disorientation, perceived usefulness, perceived usability, satisfaction and use intention. According to the result, using the visual organizer was more effect than conventional web-based instruction in view of navigation and visual understandings.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.2 s.302
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• pp.21-30
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• 2005

Development of both multimedia technology and communication network technology has accomplished many changes through the field of learning system. For the construction of a more efficient and clever learning system there is a research being done by the use of the Web and the telephone network. But until now, the case of current implemented teaming system is single system and so it has each merits and demerits. That is to say, when we use the learning system through the Web, the demerit is only possible by the static states using computer. For those who do not use the computer, the demerit is that the user must learn the use of the new system. Also, the case of using telephone network has merits that one can use the system anyplace, anytime by the telephone. But it has the problem of not being able to transmit information very efficiently. From these, this paper proposes the learning system that can be used efficiently and conveniently anyplace, anytime by connecting both telephone network and web. Also, we propose a new algorithm of user ID, password and name registration function using teaming system using VoiceXML and individual learning progress save function using VoiceXML and web.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.675-680
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• 2018

In this paper, we propose a hand gesture recognizer using restricted coulomb energy (RCE) neural network, and present hardware implementation results for real-time learning and recognition. Since RCE-NN has a flexible network architecture and real-time learning process with low complexity, it is suitable for hand recognition applications. The 3D number dataset was created using an FPGA-based test platform and the designed hand gesture recognizer showed 98.8% recognition accuracy for the 3D number dataset. The proposed hand gesture recognizer is implemented in Intel-Altera cyclone IV FPGA and confirmed that it can be implemented with 26,702 logic elements and 258Kbit memory. In addition, real-time learning and recognition verification were performed at an operating frequency of 70MHz.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.707-710
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• 2023

관계추출은 문장 내 두 개체 간의 의미적 관계를 추론하는 자연어분석 태스크이다. 딥러닝의 발전과 더불어 관계추출은 BERT 계열의 이해형 언어모델을 이용하였다. 그러나, ChatGPT의 혁신적인 등장과 함께, GPT계열의 생성형 언어모델에 대한 연구가 활발해졌다. 본 논문에서는 소규모의 생성형 언어모델(Kebyt5)을 이용하여 관계추출 성능개선을 위한 프롬프트 구성 및 생각의 사슬(CoT) 학습 방법을 제안한다. 실험결과 Kebyt5-large 모델에서 CoT 학습을 수행하였을 경우, Klue-RoBERTa-base 모델보다 3.05%의 성능개선이 있었다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.31-39
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• 2008

Until now, there are many technologies to improve studying ability using e-learning system. In most of e-learning system, learners are studying through the lecture materials and studying problems. The studying ability and intention, however, can be improved through the shared materials and discussion. In this case, learning materials are shared by the learners' discussion and shared materials through the board Internet and MSN. Such data was not classified by learners; it was not easy for the learners to search related valuable information. Therefore, it was not helping to learning. The technologies of most text mining extract summary data from the collection of document or classify into similar document from the complex document. In this paper, we implemented e-learning system for learners to improve learning abilities and especially, applied text mining technology to classify learning material for helping learners.