• Journal of Korea Society of Industrial Information Systems
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• v.12 no.2
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• pp.60-67
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• 2007

This paper describes the development of on-line computer vision laboratories to teach the detailed image processing and pattern recognition techniques. The computer vision laboratories include distant image acquisition method, basic image processing and pattern recognition methods lens and light, and communication. This study introduces a case study that teaches computer vision in distance learning. environment. It shows a schematic of a distant teaming workstation and contents of laboratories with image processing examples. The study focus more on the contents of the vision Labs rather than internet application method. The study proposes the ways to improve the on-line computer vision laboratories and includes the further research perspectives.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.211-213
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• 1993

In this paper, we proposed a design method of self-learning fuzzy logic controller using fuzzy neural network. The parameters of membership function in premise are modified by descent method and also consequent parameters by learning mechanism of animal conditioning theory. The proposed method is applied to pole balancing system in order to confirm the feasibility.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.369-378
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• 2004

In partially free word order languages like Korean and Japanese, the rule-based method is effective for text chunking, and shows the performance as high as machine learning methods even with a few rules due to the well-developed overt Postpositions and endings. However, it has no ability to handle the exceptions of the rules. Exception handling is an important work in natural language processing, and the exceptions can be efficiently processed in memory-based teaming. In this paper, we propose a hybrid of rule-based method and memory-based learning for Korean text chunking. The proposed method is primarily based on the rules, and then the chunks estimated by the rules are verified by memory-based classifier. An evaluation of the proposed method on Korean STEP 2000 corpus yields the improvement in F-score over the rules or various machine teaming methods alone. The final F-score is 94.19, while those of the rules and SVMs, the best machine learning method for this task, are just 91.87 and 92.54 respectively.

• Journal of Elementary Mathematics Education in Korea
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• v.8 no.1
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• pp.89-108
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• 2004

Elementary mathematics education in the 7th mathematics curricula has been emphasized to foster ‘mathematical power’. For establishing this purpose, we need to provide the opportunities inducing to students' thoughts and to study leaching-learning methods to make structuring for their thinking process. Using to writing activities in students' mathematics learning, we think that we can find out their thinking process and this writing mathematics learning method is effective to promote their communication. Through analysing to six grade mathematics textbooks, we devised to mathematical writing types and teaching/learning models could being utilized in mathematics classes. And we investigated the influence of mathematical writing on the learning ability of students. We have experimented and investigated to after dividing experimental objects into two groups, experimental group and comparative group. We founded out, through these researches for mathematical writing teaming, that the experimental group of the former had obtained greatly better results than the latter in mathematical learning abilities and studying achievements. Based on these result, it is required to have an accumulation of research on teaching-teaming methods by using various types of mathematical writing study.

• Journal of the Korean Home Economics Association
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• v.41 no.11
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• pp.135-150
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• 2003

This research was to verity the effects of ICT teaching method in high school home economics. The research questions for this study were as follows: 1. Is the ICT teaching method effective in increasing students' interest in home economics and consciousness on traditional culture in teaming the unit of ‘Korean traditional culture of home life’？ 2. Is the ICT teaching method effective in improving students' achievement test and performance assessment in teaming the unit of ‘Korean traditional culture of home life’？ This study is carried out with following procedure: developing the homepage and lesson plans for ICT teaching, constructing questionnaire, and testing its reliability, pre-testing, treatment for 8 weeks, and post-testing. Two groups were arranged for 8 weeks experiment from May 7,2001 through June 30,2001. Sixteen hours of ICT teaching and 8 hours of traditional lecture for experiment group whereas 8 hours of ICT teaching and 16 hours of traditional lecture for comparison group were input. SAS program was used for statistical analysis, and independent sample t-test and matched pairs t-test were peformed for answering research questions. The results of this study were as following: 1. Sixteen hours of ICT teaching and 8 hours of traditional lecture for experiment group was effective in increasing consciousness on traditional culture and performance assessment. 2. Eight hours of ICT teaching and 16 hours of traditional lecture for comparison group was not effective in learning home economics. This means that at least 2 hours of ICT teaching is demanding for effective learning. This study concluded that ICT teaching will be effectively applied in high school home economic with well developed ICT teaching materials. And home economics educators should continuously put effort in developing curricular, teaching materials, and teaching methods to raise students' interest in home economics.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.65-79
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• 2003

In general, the extraction and recognition of identifier is very hard work, because the scale or location of identifier is not fixed-form. And, because the provided image is contained by camera, it has some noises. In this paper, we propose methods for automatic detecting edge using canny edge mask. After detecting edges, we extract regions of identifier by detected edge information's. In regions of identifier, we extract each identifier using contour tracking algorithm. The self-generation supervised learning algorithm is proposed for recognizing them, which has the algorithm of combining the enhanced ART1 and the supervised teaming method. The proposed method has applied to the container images. The extraction rate of identifier obtained by using contour tracking algorithm showed better results than that from the histogram method. Furthermore, the recognition rate of the self-generation supervised teaming method based on enhanced ART1 was improved much more than that of the self-generation supervised learning method based conventional ART1.

• The Journal of the Acoustical Society of Korea
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• v.19 no.6
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• pp.62-70
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• 2000

In usual language models(LMs), the probability has been estimated by selecting highly frequent words from a large text side database. However, in case of adopting LMs in a specific task, it is unnecessary to using the general method; constructing it from a large size tent, considering the various kinds of cost. In this paper, we propose a construction method of LMs using a small size text database in order to be used in specific tasks. The proposed method is efficient in increasing the low frequent words by applying same sentences iteratively, for it will robust the occurrence probability of words as well. We carried out continuous speech recognition(CSR) experiments on 200 sentences uttered by 3 speakers using LMs by iterative teaming(IL) in a air flight reservation task. The results indicated that the performance of CSR, using an IL applied LMs, shows an 20.4% increased recognition accuracy compared to those without it. This system, using the IL method, also shows an average of 13.4% higher recognition accuracy than the previous one, which uses context-free grammar(CFG), implying the effectiveness of it.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.211-217
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the teaming control field was teaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• Korean Journal of Computational Design and Engineering
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• v.5 no.2
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• pp.127-135
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• 2000

Emergent computing paradigms such as genetic algorithms have found increased use in problems in engineering design. These computational tools have been shown to be applicable in the solution of generically difficult design optimization problems characterized by nonconvexities in the design space and the presence of discrete and integer design variables. Another aspect of these computational paradigms that have been lumped under the bread subject category of soft computing, is the domain of artificial intelligence, knowledge-based expert system, and machine learning. The paper explores a machine learning paradigm referred to as teaming classifier systems to construct the high-quality global function approximations between the design variables and a response function for subsequent use in design optimization. A classifier system is a machine teaming system which learns syntactically simple string rules, called classifiers for guiding the system's performance in an arbitrary environment. The capability of a learning classifier system facilitates the adaptive selection of the optimal number of training data according to the noise and multimodality in the design space of interest. The present study used the polynomial based response surface as global function approximation tools and showed its effectiveness in the improvement on the approximation performance.

• Hwankyungkyoyuk
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• v.19 no.2 s.30
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• pp.133-146
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• 2006

The purpose of this study was to examine how environmental education teachers think about environmental teaching materials of their use in primary and secondary schools. For this purpose, six primary and secondary school teachers were selected for focus group discussion on October 17th, 2005. The discussion of focus group was recorded both on video and audio tapes. Teachers' discussion could be analyzed in the perspectives of two big ideas, 'content selection' and 'content organization and presentation'. The big ideas were categorized into several areas: 1) The idea of 'content selection' was classified into 4 areas such as integration, difficulty level, locality, and timeliness, 2) The idea of 'content organization and presentation' was classified into 4 areas such as learning motivation, teaching and teaming strategy, evaluation method, application of teaching materials. This study provided meaningful ideas, which can be used in developing environmental education materials as well as effective teaching and teaming strategies for school environmental educators.