• Journal of Plant Biotechnology
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• v.39 no.3
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• pp.121-126
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• 2012

To determine whether FT-IR spectroscopy combined with multivariate analysis for whole cell extracts can be used to discriminate major leguminous plant at metabolic level, seed extracts of six leguminous plants were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR spectral data from seed extracts were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). The PCA could not fully discriminate six leguminous plants, however PLS-DA could successfully discriminate six leguminous plants. The hierarchical dendrogram based on PLS-DA separated the six leguminous plants into four branches. The first branch was consisted of all three Vigna species including Vigna radiata var. radiate, Vigna angularis var. angularis and Vigna unguiculata subsp. Unguiculata. Whereas Pisum sativum var. sativum, Glycine max L and Phaseolus vulgaris var. vulgaris were clustered into a separate branch respectively. The overall results showed that metabolic discrimination system were in accordance with known phylogenic taxonomy. Thus we suggested that the hierarchical dendrogram based on PLS-DA of FT-IR spectral data from seed extracts represented the most probable chemotaxonomical relationship between six leguminous plants.

• Journal of the Korean Chemical Society
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• v.56 no.6
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• pp.739-750
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• 2012

The purpose of this study is to analyze the cognitive demands level of the description about 'pure substance and mixture compound', 'ionic compound', 'molecule' on the 'science2' textbooks by the 2007 revised curriculum. The three types of Curriculum Analysis Taxonomy have been used to analyze the cognitive demands level of those contents on the 6 kinds of 'science2' textbooks. The first, the cognitive demand level about 'pure substance and mixture compound' on many textbooks is a late concrete operational stage because of class inclusion and hierarchical classification. And the descriptions as 'pure substance is conserved even when mixed with other pure substance' is a early formal operational stage. The second, the cognitive demand level about 'ionic compound' and 'molecule' is a early formal operational stage, because of "Formal modeling is the indirect interpretation of reality by deductive comparison from a postulated system with its own rules" and "Atoms have a structure". The third, the terms as 'ionic bonding', 'ionic compound', 'chemical formula', 'covalent bonding', 'covalent compound', and 'molecular formula' have been used on many 'science2' textbooks. Those terms would be used later on 'chemistry I' and 'chemistry II' in senior high school but not even 'science3' and 'science'.

• Journal of the Korean Chemical Society
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• v.56 no.4
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• pp.518-529
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• 2012

The purpose of this study is to analyze the cognitive demands level of the description about 'element', 'periodic table', and 'atom' on the 'science 2' textbooks by the 2007 revised curriculum. The three types of CAT (Curriculum Analysis Taxonomy) have been used to analyze the cognitive demands level of those contents on the 6 kinds of 'science 2' textbooks. The cognitive demands level about 'elements' on many textbooks is a late concrete operational stage, because the descriptions of 'element' are pure substances or no more split into anything simpler substances. That cognitive demands level about one textbook is a early formal operational stage, because the descriptions 'element' are a substance of one kind of atom. The cognitive demands level of 'periodic table' on many textbooks is a late concrete operational stage, because the descriptions about 'periodic table' are the hierarchical classification for the categorizing reality. And the cognitive demands level of 'periodic table' is a early formal operational stage, because the descriptions about 'periodic table' are a collection of 'families' or two-way gradation of elements. That cognitive demands level about one textbook is a late formal operational stage, because the descriptions of 'periodic table' are a complex classificatory structure linking atomic structure. The cognitive demands level about 'atom' is a early formal operational stage because of the descriptions as "atoms have structure, some atoms are the same, or others are different".

• Journal of the Economic Geographical Society of Korea
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• v.26 no.1
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• pp.1-22
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• 2023

This study proposes an integrated use of region and industry as a way to classify firms' innovation activities by type. Existing studies have used the method of determining innovative activities according to the components of the technological regimes and aggregating them by industry classification, but this method cannot fully reflect the heterogeneity within industries in an increasingly sophisticated innovation environment. Therefore, this study divides firms by region and industry and conducts a cluster analysis on the proportion of innovative activities by the components of the technological regimes to derive a total of four innovation types. Using the 2016 Korean Innovation Survey to classify innovation types in the manufacturing industry, we found that innovation activities are concentrated in Seoul, Busan, Incheon, and Chungnam/ Sejong/ Daejeon area, with different deviations by region and industry. The results of the aggregation of industrial innovation activities, weighted by corporate activity by region, show that the level of innovation activity in some manufacturing industries, such as petrochemicals, manufacturing of medical, precision and optical instruments, watches and clocks, is high, but the level of innovation in other sectors within the manufacturing industry is generally low.

• Journal of KIISE:Databases
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• v.37 no.3
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• pp.127-136
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• 2010

With rapid growth of information and computer communication technologies, the numbers of digital documents including multimedia data have been recently exploded. In particular, news video database and news video mining have became the subject of extensive research, to develop effective and efficient tools for manipulation and analysis of news videos, because of their information richness. However, many research focus on browsing, retrieval and summarization of news videos. Up to date, it is a relatively early state to discover and to analyse the plentiful latent semantic knowledge from news videos. In this paper, we propose the news video mining system based on multi-modal approach and text mining, which uses the visual-textual information of news video clips and their scripts. The proposed system systematically constructs a taxonomy of news video stories in automatic manner with hierarchical clustering algorithm which is one of text mining methods. Then, it multilaterally analyzes the topics of news video stories by means of time-cluster trend graph, weighted cluster growth index, and network analysis. To clarify the validity of our approach, we analyzed the news videos on "The Second Summit of South and North Korea in 2007".

• Journal of the Korea Convergence Society
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• v.6 no.3
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• pp.127-134
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• 2015

In this paper, we design a semantic-based syllabus template including learning ontologies. A syllabus has been considered as a important blueprint of teaching in universities. However, the current syllabus has no importance in real world because most of all syllabus management systems provide simple functionalities such as, creation, modification, and retrieval. In this paper, our approach consists of definition of hierarchical structure of syllabus and semantic relationships of syllabuses, formalization of learning goals, learning activity, and learning evaluation using Bloom's taxonomy and design of learning subject ontologies for improving the usability of syllabus. We prove the correctness of our proposed methods according to implementing a real syllabus for JAVA programing course and experiments for retrieving syllabuses.

• Journal of The Korean Association For Science Education
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• v.32 no.6
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• pp.1039-1049
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• 2012

The first category of Affective Domain objectives in Bloom's Taxonomy is about "Receiving". In it, the first subdivision listed is "Awareness" (Krathwohl, Bloom & Masia, 1964). Since these categories are intended to be hierarchical in ascending order of internalization, it is important that young learners be given ample opportunities in their learning experiences in class to be aware of positive values and effective life skills. This paper reports a feasibility study on the adoption of an integrative cognitive-affective learning approach in a primary school science lesson. 37 primary six students in a Singapore primary school were taught the concept of centre of gravity, including a hands-on activity to find the centre of gravity of an irregularly shaped cardboard by using a plumbline. After reviewing how a plumbline works, their teacher then led them into a discussion on the question "Who is the plumbline in your life?" a reference to identifying positive role models in their lives. From the transcript of the students' in-class sharing and their written responses to the question, it is clear that the integrative cognitive-affective learning approach did enable students to present their ideas and learning experiences in the affective domain quite readily. This conclusion provides a valuable lead to a follow-up project on whether students who are exposed to such integrative learning approaches will be more capable and more aware of identifying important positive social habits or values. If so, then the teaching of values in schools could take on a whole new dimension, that of borrowing students' learning energy in the cognitive domain to learn values and life skills in the affective domain.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.111-123
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• 2013

Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

• Journal of Life Science
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• v.12 no.6
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• pp.821-834
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• 2002

In order to measure the inter- and intraspecific genetic divergences within the genus Alexandrium, the variations within the internal transcribed spacer (ITS1 and ITS2) regions and 5.85 ribosomal RNA gene of eight Alexandrium species were examined for 33 strains from diverse geographical locations by direct sequencing. Five isolates of A. tamarense (AT-2, AT-6, AT-10, AT-A and AT-B) from Jinhae Bay, Korea were found to be completely identical to a Japanese strain OFX151-A. The length of the amplified ITSI-5.85-ITS2 region varied from 481 nucleotides (in A. margalefi) to 528 nucleotides (in A. affine CU1-1). ITS1 and ITS2 nucleotide lengths were negatively correlated, whereas a positive correlation was found between their G＋C content. The degree of sequence divergence ranged from 0.3% (1 bp) to a maximum of 53% (305 Up). Pairwise sequence comparisons revealed a small degree of divergence between A. tamarense and A. Pundyense isolates (1.2 - 2.3% ＝ 6-12 bp), but a high degree of divergence between A. tamarense and A. catenella (19.8% ＝ 102 bp), and between A. catenella and A. Pundyense (19.7%). Although most nodes were weakly supported by bootstrap values, some types tend to form independent molecular groups. A. catenella isolates also formed an independent molecular sub-group, with relaticula strong bootstrap values (94% or 85% and 79% or 98%, respectively in PAUP and NJ trees). Interestingly, A. cohorticula and A. frateculus always clustered within the same sub-group, this result being supported by strong bootstrap values. Our results indicate that the ITS regions provide useful informations on hierarchical population genetic structure and a high phylogenetic resolution in intraspecific and interspecific Alexandrium population.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.119-134
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• 2018

A knowledge map as the taxonomy used in a knowledge repository should be structured to support and supplement knowledge activities of users who sequentially inquire and select knowledge for problem solving. The conventional knowledge map with a hierarchical structure has the advantage of systematically sorting out types and status of the knowledge to be managed, however it is not only irrelevant to knowledge user's process of cognition and utilization, but also incapable of supporting user's activity of querying and extracting knowledge. This study suggests a methodology for constructing a networked knowledge map that can support and reinforce the referential navigation, searching and selecting related and chained knowledge in term of contents, between knowledge. Regarding a keyword as the semantic information between knowledge, this research's networked knowledge map can be constructed by aggregating each set of knowledge links in an automated manner. Since a keyword has the meaning of representing contents of a document, documents with common keywords have a similarity in content, and therefore the keyword-based document networks plays the role of a map expressing interactions between related knowledge. In order to examine the feasibility of the proposed methodology, 50 research papers were randomly selected, and an exemplified networked knowledge map between them with content relevance was implemented using common keywords.