• Journal of the Korean earth science society
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• v.36 no.4
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• pp.404-416
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• 2015

We investigated the cognitive frame of high school students and inservice high school science teachers about effective teaching method, and we also explored how they understood about the teaching methods suggested by the 2009 revised Science Curriculum. Data were collected from 275 high school science teachers and 275 high school students. We analyzed data in terms of the words and the cognitive frame using the Semantic Network Analysis. The results were as follows. First, the teachers perceived that an activity oriented class was the effective science class that helped improve students' problem-solving abilities and their inquiry skills. The students had the cognitive frame that their teacher had to present relevant and enough teaching materials to students, and that they should also receive assistance from teachers in science class to better prepare for college entrance exam. Second, both students and teachers retained the cognitive frame about the efficient science class that was not reflected 2009 revised Science Curriculum exactly. Especially, neither groups connected the elements of 'convergence' as well as 'integration' embedded across science subject areas to their cognitive frame nor cognized the fact that many science learning contents were closed related to one another. Therefore, various professional development opportunities should be offered so that teachers succinctly comprehend the essential features and the intents of the 2009 revised Science Curriculum and thereby implement it in their science lessons effectively.

• Journal of Gifted/Talented Education
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• v.24 no.4
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• pp.561-576
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• 2014

The purpose of this study is to investigate the perception of the mothers of science gifted in respect to giftedness compared to the "Scale for Rating the Behavioral Characteristics of Superior Students-R(SRBCSS-R)". For that, a survey of 18 mothers of elementary school science gifted and 32 mothers of middle school science gifted was conducted in relation to giftedness. The words and frame of this survey were analyzed using the Semantic Network Analysis. The results are as follows : The mothers of Elementary school science gifted perception were found to have a connected giftedness with reading, science, making something, etc.. On the other hand, the mothers of middle school science gifted perception were found to have a connected giftedness with problem, solving problem, mathematics, etc. in words analysis. The mothers of Elementary school science gifted have a strong connection with category on creativity, motivation, etc.. On the other hand, the mothers of middle school science gifted were more inclined towards the category on learning, motivation, etc. in frame analysis. That is to say, the mothers of science gifted are perceptive about giftedness respect to some elements as the "Scale for Rating the Behavioral Characteristics of Superior Students-R" on the giftedness. Therefore, a correct understanding about giftedness in respect to the mothers of science gifted is required and parent education is needed for appropriate science gifted education.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.520-532
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• 2016

In this paper, we propose a novel method to analyze and quantitatively evaluate the impression of landscapes and soundscapes about traditional area of Chungnam Asan city in Korea. For this, we collated data about impression evaluation of Korean and Japanese students and, based on these result, we proved the validity and usefulness of the evaluation system that we proposed through this study. The research process conducted in this study as follows: first of all, we had selected five traditional places of interest in Asan City, and investigated various conditional elements of the area including soundscapes which is forming the landscape using video camera. And we made both Korean and Japanese students evaluate the impression for these videotaped landscape data through using the SD(semantic differential) method. And then, we quantified these qualitative data through applying the quantification theory and cluster analysis method to them. Though this process, we could obtain both data as a result derived by classifying each sample and categorizing levels of those impression evaluation. Because of totally difference between those two analyzing processes, which one is for sample classification and the other is for determining impression level, we could validate the usefulness of our evaluation system through conducting comparative analysis of results from both methods. Analysis showed that our novel evaluation system for landscape is effective and, in most part of the traditional landscape, Japanese students' responses are different far from the Korean students' responses.

• Journal of The Korean Association For Science Education
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• v.38 no.5
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• pp.753-763
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• 2018

The image of scientists that learners have has an important impact on science learning and on science-related career choices. The image of the scientist was mainly analyzed using the drawing analysis method. Drawing analysis has limitations on drawing, mainly analyzing the external image of scientist. Science teachers' images of scientists and their perception of science-related careers are important factors in students' science learning and science-related career choices. However, research on science teachers is lacking. Therefore, the purpose of this study is to investigate the usefulness of measurement tools by developing and applying a scientist image measurement tool through the semantic analysis method, and to discuss the educational implications of the research by investigating the image of scientists and science-related professions of secondary pre-service science teachers. The subjects of the study were 79 male and 55 female for a total of 134 students in the 2nd and 3rd grades majoring in science education at a teachers college. The results of the research show that the image measurement tool consisted of four components: 'ability,' 'evaluation,' 'activity,' and 'emotion,' in 24 items. As a result of applying the developed measurement tool to the secondary pre-service science teachers, the image of the 'evaluation,' 'ability,' and 'activity' elements of the scientist were high, but 'emotion' was low. There was no statistically significant difference according to gender. It is found that science-related career perceive them as 'hard,' 'professional,' 'smart,' and 'complex.' In particular, male students perceive themselves as 'hard and difficult' while female students perceive it as 'challenging and complicated'. Finally, we discussed the usefulness of using the image measurement tool of the scientists, the image of the scientists of the secondary pre-service science teachers, and the educational implications on science-related career.

• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.563-572
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• 2004

Sentence ion is a simplification of a sentence preserving its communicative function. It accomplishes sentence revision and concept ion simultaneously. Sentence revision is a method that resolves the discrepancy between human's thoughts and its expressed semantic in sentences. Concept ion is an expression of general ideas acquired from the common elements of concepts. Sentence ion selects the main constituents of given sentences and describes the upper concepts of them with detecting their semantic information. This enables sen fence revision and concept ion simultaneously. In this paper, a syntactic parser LGPI+ and an ontology OfN are utilized for sentence ion. Sentence abstracter SABOT makes use of LGPI+ and OfN. SABOT processes the result of parsing and selects the candidate words for sentence ion. This paper computes the sentence recall of the main sentences and the topic hit ratio of the selected sentences with the text understanding system using sentence ion. The sources are 58 paragraphs in 23 stories. As a result of it, the sentence recall is about .54 ～ 72% and the topic hit ratio is about 76 ～ 86%. This paper verified that sentence ion enables sentence revision that can select the topic sentences of a given text efficiently and concept ion that can improve the depth of text understanding.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.676-683
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• 2002

The success of XML(eXtensible Markup Language) is primarily based on its flexibility : everybody can define the structure of XML documents that represent information in the form he or she desires. XML is so flexible that XML documents cannot be automatically provided with an underlying semantics. Different tag sets, different names for elements or attributes, or different document structures in general mislead the task of classifying and clustering XML documents precisely. In this paper, we design and implement a system that allows checking the semantic-based similarity between XML tags. First, this system extracts the underlying semantics of tags and then expands the synonym set of tags using an WordNet thesaurus and user-defined word library which supports the abbreviation forms and compound words for XML tags. Seconds, considering the relative importance of XML tags in the XML documents, we extend a conventional vector space model which is the most generally used for document model in Information Retrieval field. Using this method, we have been able to check the similarity between XML tags which are represented different tags.

• Archives of design research
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• v.18 no.3 s.61
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• pp.45-54
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• 2005

Visual messages are fundamental elements for performing communication and indicate the signs which are delivered from the communicator to the communicatee via channels, Generally, we can classify visual messages into two groups; linguistic factors which are rational and deliver abstract concepts and unlinguistic factors which are mental and can be expressed concretely. Especially, web site with receivers' low attention and concentration need images which can attract their attention to visual messages. That is, web site is a medium which allows us to feel visual and emotional experiences. We can call it a standard of sign systems which are consisted of various styles of digital texts. The main purpose of this study lies in that we'll analyze how homepage introductory page as one of the forms of digital text conduces a meaning action to the receivers and that we'll apprehend the structures of images and different types of signs via a semiotic approach and analyze the underlying meaning of the messages. In order to survey the structures of images we'll look into the attitude toward perceiving messages by using semantic differential method which has been developed mostly by Osgood and analyze the visual images by adopting sign types of Fuss. As the signification is created by combining signs, it is significant that we'll analyze the meaning of sings between the transmitters and receivers from the semiotic viewpoint and study the signification systems.

• Journal of Software Engineering Society
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• v.23 no.4
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• pp.151-163
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• 2010

In the defense software domain where large-scale software products in various application areas need to be built, reusing software is regarded as one of the important practices to build software products efficiently and economically. There have been many efforts to apply various methods to support software reuse in the defense software domain. However, developers in the defense software domain still experience many difficulties and face obstacles in reusing software assets. In this paper, we analyze practical problems of software reuse in the defense software domain, and define core requirements to solve those problems. To meet these requirements, we are currently developing the Component Grid system, a reuse-support system that provides a developer-centric software reuse environment. We have designed an architecture of Component Grid, and defined essential elements of the architecture. We have also developed the core approaches for developing the Component Grid system: a semantic-tagging-based requirement tracing method, a reuse-knowledge representation model, a social-network-based asset search method, a web-based asset management environment, and a wiki-based collaborative and participative knowledge construction and refinement method. We expect that the Component Grid system will contribute to increase the reusability of software assets in the defense software domain by providing the environment that supports transparent and efficient sharing and reuse of software assets.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.397-412
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• 2023

In order for social robots to take root in human life, it is important to consider the technical implementation of social robots and human psychology toward social robots. This study aimed to derive potential social robot clusters based on the emotions consumers feel about social robot appearance design, and to identify and compare important design characteristics and emotional differences of each cluster. In our study, we established a social robot emotion framework to measure and evaluate the emotions consumers feel about social robots, and evaluated the emotions of social robot designs based on the semantic differential method, an kansei engineering approach. We classified 30 social robots into 4 clusters by conducting a multidimensional scaling method and K-means cluster analysis based on the emotion evaluation results, confirmed the characteristics of design elements for each cluster, and conducted a comparative analysis on consumer emotions. We proposed a strategic direction for successful social robot design and development from a human-centered perspective based on the design characteristics and emotional differences derived for each cluster.