• Journal of Korean Elementary Science Education
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• v.24 no.4
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• pp.337-344
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• 2005

The purpose of this study is to analyze field trip activities in the elementary school science textbook developed under the 7th national curriculum. The results indicated there was an average of 4.25 field trip activities each semester presented in the textbook from the 3rd to 6th grade, mostly related to earth science and biology. The places for field trips were limited to in-school environment and natural sites in communities, and mostly purported to gain understanding of rudimentary concepts. Field trip activities were intended to facilitate science knowledge and understanding in order to integrate with the textbook content rather than offering students simple one-time activities. Most activities in the textbook guided students step by step. The starting or follow-up activities in the fields trips and reminder for cautions were not clearly presented. In order for the field trips to integrate with the content of the curriculum in the text book, they have to be presented in the textbook systematically. It is also imperative to find out various fold trip places related to the content in the curriculum, develop efficient activities dealing with science at the appropriate level for students and increasing interests in science and its teaming.

• Journal of Korean Elementary Science Education
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• v.24 no.4
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• pp.329-336
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• 2005

The purpose of this study was to investigate the elementary school student's recognition of informal science education program : 'Korea Junior Engineering Achievement (KJEA)'case. The subjects were 807, 4th, 5th, 6th grade elementary school students who participated KJEA program. We developed questionnaires and explored the students' preference and the reason to KJEA (compared with school science lesson), attitude on informal elements of KJEA (non-school teachers and non-curricular content), interest in the each KJEA program, outcome of the KJEA. The result of this study showed that the students' recognition of the informal science education program was strongly affirmative. Students preferred KJEA program to school science lessons for that reason why they could make and do by themselves and the KJEA program had novelty. They expected more teaming opportunities by non-school teachers on non-curricular content. Though KJEA had little effect on career interests, students showed willingness to continue to participate. We could get implication for informal science education that the quality of the program is the most important factors than others. The novelty and the doing by oneselves were also important factors for students.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.447-456
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• 2004

Information extraction is a process of recognizing and fetching particular information fragments from a document. In order to extract information uniformly from many heterogeneous information sources, it is necessary to produce information extraction rules called a wrapper for each source. Previous methods of information extraction can be categorized into manual wrapper generation and automatic wrapper generation. In the manual method, since the wrapper is manually generated by a human expert who analyzes documents and writes rules, the precision of the wrapper is very high whereas it reveals problems in scalability and efficiency In the automatic method, the agent program analyzes a set of example documents and produces a wrapper through learning. Although it is very scalable, this method has difficulty in generating correct rules per se, and also the generated rules are sometimes unreliable. This paper tries to combine both manual and automatic methods by proposing a new method of learning information extraction rules. We adopt the scheme of supervised learning in which a user-interface agent is designed to get information from the user regarding what to extract from a document, and eventually XML-based information extraction rules are generated through learning according to these inputs. The interface agent is used not only to generate new extraction rules but also to modify and extend existing ones to enhance the precision and the recall measures of the extraction system. We have done a series of experiments to test the system, and the results are very promising. We hope that our system can be applied to practical systems such as information-mediator agents.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.141-149
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• 2007

Associating the shoulder line with head location of the human body is useful in verifying, localizing and tracking persons in an image. Since the head line and the shoulder line, what we call ${\Omega}$-shape, move together in a consistent way within a limited range of deformation, we can build a statistical shape model using Active Shape Model (ASM). However, when the conventional ASM is applied to ${\Omega}$-shape fitting, it is very sensitive to background edges and clutter because it relies only on the local edge or gradient. Even though appearance is a good alternative feature for matching the target object to image, it is difficult to learn the appearance of the ${\Omega}$-shape because of the significant difference between people's skin, hair and clothes, and because appearance does not remain the same throughout the entire video. Therefore, instead of teaming appearance or updating appearance as it changes, we model the discriminative appearance where each pixel is classified into head, torso and background classes, and update the classifier to obtain the appropriate discriminative appearance in the current frame. Accordingly, we make use of two features in fitting ${\Omega}$-shape, edge gradient which is used for localization, and discriminative appearance which contributes to stability of the tracker. The simulation results show that the proposed method is very robust to pose change, occlusion, and illumination change in tracking the head and shoulder line of people. Another advantage is that the proposed method operates in real time.

• Journal of Elementary Mathematics Education in Korea
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• v.7 no.1
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• pp.45-64
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• 2003

This study analyzes divisor and multiple in elementary school mathematics textbooks published according to the first to the 7th curriculum, in a view point of the didactic transposition theory. In the first and second textbooks, the divisor and the multiple are taught in the chapter whose subject is on the calculations of the fractions. In the third and fourth textbooks, divisor and multiple became an independent chapter but instructed with the concept of set theory. In the fifth, the sixth, and the seventh textbooks, not only divisor multiple was educated as an independent chapter but also began to be instructed without any conjunction with set theory or a fractions. Especially, in the seventh textbook, the understanding through activities of students itself are strongly emphasized. The analysis on the each curriculum periods shows that the divisor and the multiple and the reduction of a fractions to the lowest terms and to a common denominator are treated at the same period. Learning activity elements are increase steadily as the textbooks and the mathematical systems are revised. The following conclusion can be deduced based on the textbook analysis and discussion for each curriculum periods. First, loaming instruction method also developed systematically with time. Second, teaching method of the divisor and multiple has been sophisticated during the 1st to 7th curriculum textbooks. And the variation of the teaching sequences of the divisor and multiple is identified. Third, we must present concrete models in real life and construct textbooks for students to abstract the concepts by themselves. Fourth, it is necessary to develop some didactics for students' contextualization and personalization of the greatest common divisor and least common multiple. Fifth, the 7th curriculum textbooks emphasize inquiries in real life which teaming activities by the student himself or herself.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.595-604
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• 2004

Automatic analysis of concepts or semantic relations from text documents enables not only an efficient acquisition of relevant information, but also a comparison of documents in the concept level. We present a multiple cause model-based approach to text analysis, where latent topics are automatically extracted from document sets and similarity between documents is measured by semantic kernels constructed from the extracted topics. In our approach, a document is assumed to be generated by various combinations of underlying topics. A topic is defined by a set of words that are related to the same topic or cooccur frequently within a document. In a network representing a multiple-cause model, each topic is identified by a group of words having high connection weights from a latent node. In order to facilitate teaming and inferences in multiple-cause models, some approximation methods are required and we utilize an approximation by Helmholtz machines. In an experiment on TDT-2 data set, we extract sets of meaningful words where each set contains some theme-specific terms. Using semantic kernels constructed from latent topics extracted by multiple cause models, we also achieve significant improvements over the basic vector space model in terms of retrieval effectiveness.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.344-355
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• 2002

Having a variety of good characteristics against other pattern recognition techniques, Multilayer Perceptron (MLP) has been used in wide applications. But, it is known that Error Backpropagation (EBP) algorithm which MLP uses in learning has a defect that requires relatively long leaning time. Because learning data in pattern recognition contain abundant redundancies, in order to increase learning speed it is very effective to use online-based teaming methods, which update parameters of MLP pattern by pattern. Typical online EBP algorithm applies fixed learning rate for each update of parameters. Though a large amount of speedup with online EBP can be obtained by choosing an appropriate fixed rate, fixing the rate leads to the problem that the algorithm cannot respond effectively to different leaning phases as the phases change and the learning pattern areas vary. To solve this problem, this paper defines learning as three phases and proposes a Instant Learning by Varying Rate and Skipping (ILVRS) method to reflect only necessary patterns when learning phases change. The basic concept of ILVRS is as follows. To discriminate and use necessary patterns which change as learning proceeds, (1) ILVRS uses a variable learning rate which is an error calculated from each pattern and is suppressed within a proper range, and (2) ILVRS bypasses unnecessary patterns in loaming phases. In this paper, an experimentation is conducted for speaker verification as an application of pattern recognition, and the results are presented to verify the performance of ILVRS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1227-1242
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• 2007

This study aims at grasping the influence of antecedents within SCM to information sharing and cooperation as well as the influence of information sharing on cooperation among the small & medium-sized manufacturing industries, thus ultimately opening the way to the study on the influence of major activities such as information sharing and cooperation within SCM on the business performance by classifying such influence into low perspectives of BSC. The results of this study revealed that the antecedents such as commitment and cultural similarities exercised a significant influence on information sharing while mutual trust and the size of a corporate weighing with cooperative activities. It also identified the fact that information sharing bore a significant influence on cooperation in terms of relationships among activities. For the relationships between the SCM activities and performance, cooperation proved significant to all four balanced scorecard performances with little significant influence of information sharing on balanced scorecard performance. However, taking into consideration of the significance of information sharing on cooperation as well as the significant influence of cooperation on balanced scorecard performance, it fumed out that information sharing also effected a indirect influence on such four types of balanced scorecard performance. In this regard, based on the results of this study, it was identified that information sharing and cooperation, major activities within SCM, had either direct or indirect influence, through the influence of antecedents, on the business balanced scoreboard performance measured from a customer perspective, a business process perspective, an innovation and teaming perspective and a financial perspective.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.6
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• pp.503-513
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• 2005

With the recognition of the importance of computational approach for protein-protein interaction prediction, many techniques have been developed to computationally predict protein-protein interactions. However, few techniques are actually implemented and announced in service form for general users to readily access and use the techniques. In this paper, we design and implement a protein interaction prediction service system based on the domain combination based protein-protein interaction prediction technique, which is known to show superior accuracy to other conventional computational protein-protein interaction prediction methods. In the prediction accuracy test of the method, high sensitivity($77\%$) and specificity($95\%$) are achieved for test protein pairs containing common domains with teaming sets of proteins in a Yeast. The stability of the method is also manifested through the testing over DIP CORE, HMS-PCI, and TAP data. Performance, openness and flexibility are the major design goals and they are achieved by adopting parallel execution techniques, web Services standards, and layered architecture respectively. In this paper, several representative user interfaces of the system are also introduced with comprehensive usage guides.

• Journal of the Korean Geographical Society
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• v.41 no.4 s.115
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• pp.491-506
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• 2006

In terms of the importance of ocean as a present and future resource and the Korean peninsular location, it is strongly urged to develop renewed recognition and educational programs on ocean, so as to respond properly to the newly emerging political changes surrounding the country. By setting up the purpose of marine education as engendering greater interests in and knowledge of ocean, this research suggests that the frame of marine education can be founded appropriately on four educational sub-categories: humanity education, territory education, economy education, and resources and environment education. At an operational scale, this paper particularly analyzed ocean- related contents in the 7th national curriculum in order to find substantial ways for strengthening marine education. The study simultaneously compared the result of content analysis with the curriculum of marine education in other countries, and founded that explicit ocean-related contents in the 7th curriculum were significantly limited. Yet, the study alternatively points out that it is possible to use a variety of teaching materials and apply them for writing textbooks or developing teaching-teaming curriculum. I provide some of the ways for strengthening marine education by using marine-related themes in the curriculum of geography education. Marine is not simply one of the key elements in the discipline of geography. But, more importantly, I suggest that geography is particularly useful in developing various and familiar themes such as swimming beach, fishing villages, ports, marine-bound industrial district and port cities into teaching materials.