• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.61-74
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• 2009

With an exponential growth of blogs, lots of important data have appeared on blogs. However, since main topics mentioned in blog pages are quite different from general web pages, there are problems which can't be solved by general search engines. Therefore, many researchers have studied searching methods only for blogs to help users who want to have useful information on blog. We also present a blog classifying method based on similarity of titles. First, we analyze blogs and blog search engines to find problems and solution of current blog search. Second, applying our similarity algorithm on blog titles, we discuss a way to develop clustering method only for blog. Finally, by making a prototype system of our algorithm, we evaluate our algorithm's effectiveness and show conclusion and future work. We expect this algorithm could add its power to current search engine.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.660-669
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• 2020

Objective: To evaluate the accuracy of a deep learning-based automated segmentation of the left ventricle (LV) myocardium using cardiac CT. Materials and Methods: To develop a fully automated algorithm, 100 subjects with coronary artery disease were randomly selected as a development set (50 training / 20 validation / 30 internal test). An experienced cardiac radiologist generated the manual segmentation of the development set. The trained model was evaluated using 1000 validation set generated by an experienced technician. Visual assessment was performed to compare the manual and automatic segmentations. In a quantitative analysis, sensitivity and specificity were calculated according to the number of pixels where two three-dimensional masks of the manual and deep learning segmentations overlapped. Similarity indices, such as the Dice similarity coefficient (DSC), were used to evaluate the margin of each segmented masks. Results: The sensitivity and specificity of automated segmentation for each segment (1-16 segments) were high (85.5-100.0%). The DSC was 88.3 ± 6.2%. Among randomly selected 100 cases, all manual segmentation and deep learning masks for visual analysis were classified as very accurate to mostly accurate and there were no inaccurate cases (manual vs. deep learning: very accurate, 31 vs. 53; accurate, 64 vs. 39; mostly accurate, 15 vs. 8). The number of very accurate cases for deep learning masks was greater than that for manually segmented masks. Conclusion: We present deep learning-based automatic segmentation of the LV myocardium and the results are comparable to manual segmentation data with high sensitivity, specificity, and high similarity scores.

• Journal of Educational Research in Mathematics
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• v.20 no.1
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• pp.57-71
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• 2010

Similarity between concept and concept, principle and principle, theory and theory is known as a strong motivation to mathematical knowledge construction. Metaphor and analogy are reasoning skills based on similarity. These two reasoning skills have been introduced as useful not only for mathematicians but also for students to make meaningful conjectures, by which mathematical knowledge is constructed. However, there has been lack of researches connecting the two reasoning skills. In particular, no research focused on the interplay between the two in didactic transposition. This study investigated the process of knowledge construction by metaphor and analogy and their roles in didactic transposition. In conclusion, three kinds of models using metaphor and analogy in didactic transposition were elaborated.

• YAKHAK HOEJI
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• v.42 no.6
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• pp.627-633
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• 1998

Impurity profiling analysis of methamphetamine seized in Korea was investigated for the evidential and intelligent purpose. Samples were extracted with ethylacetate which contai ns internal standard of dioctylsebacate under basic condition and extracts were analyzed by GC-FID. Ephedrine, chloroephedrine & 1,2-dimethyl-3-phenylaziridine were identified impurities in illicit methamphetamine by GC-MS. These impurities revealed that most of abused methamphetamine in Korea were synthesized from ephedrine as a starting material. For the classification of samples. firstly, 24 impurity peaks were selected after inspection of every peak in 50 samples as the specific markers of impurities. Secondly, corresponding peak retention time and area ratio to the internal standard were calculated and database was created with values of 24 peaks by in-house program. Finally, cluster analysis was attempted with the resultant profiles using the STAR plot, which was based on the Euclidian distance for evaluating similarity among samples. A total of 76 samples were divided into 8 different groups within 90% statistical similarity and inter-batch samples showed similar impurity patterns by this procedure. In conclusion, the analysis of impurities is a suitable index for estimation the common or different origin of methamphetamine sample.

• Korean Journal of Cognitive Science
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• v.12 no.4
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• pp.29-39
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• 2001

Kaplan(2000) reported that instances were categorized more accurate in the aligned condition than in the non-aligned condition irrespective of similarity between instances[16]. This study investigated wether Kaplan(2000)\\`s results could be explained by stimulus types she used and alignment effects in categorization were due to selective attention to aligned attributes. In Experiment 1. I examined whether attribute alignment produced significant effects on similarity and categorization and aligned attributes were recalled more than non-aligned ones. Results showed that instances were rated more similar and categories were learned more rapidly in the aligned condition than in the non-aligned condition. It can be explained that categories are learned rapidly in the aligned condition because attribute alignment increases within-category similarity. But. the result that aligned attributes were recalled more than non-aliened ones in the attribute recall test implies that alignment effects in categorization can be independent of similarity between instances partially. In Experiment 2. I used equal numbed of attributes defining two categories and instructed subjects to pay their attention to categorization-relevant dimensions only. Results showed that dimension instruction facilitated category learning in the non-aligned condition only but categories were learned more rapidly in the aligned condition than in the non-aliened condition irrespective of instruction types. In conclusion. attribute alignment in categorization may facilitate paying selective attention to categorization-relevant attributes.

• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.153-158
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• 2021

X-ray image analysis is a very important field to improve the early diagnosis rate and prediction accuracy of periodontal disease. Research on the development and application of artificial intelligence-based algorithms to improve the quality of such dental X-ray images is being widely conducted worldwide. Thus, the aim of this study was to design a super-resolution algorithm for predicting periodontal disease and to evaluate its applicability in dental X-ray images. The super-resolution algorithm was constructed based on the convolution layer and ReLU, and an image obtained by up-sampling a low-resolution image by 2 times was used as an input data. Also, 1,500 dental X-ray data used for deep learning training were used. Quantitative evaluation of images used root mean square error and structural similarity, which are factors that can measure similarity through comparison of two images. In addition, the recently developed no-reference based natural image quality evaluator and blind/referenceless image spatial quality evaluator were additionally analyzed. According to the results, we confirmed that the average similarity and no-reference-based evaluation values were improved by 1.86 and 2.14 times, respectively, compared to the existing bicubic-based upsampling method when the proposed method was used. In conclusion, the super-resolution algorithm for predicting periodontal disease proved useful in dental X-ray images, and it is expected to be highly applicable in various fields in the future.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.97-100
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• 2002

The purpose of this paper is to investigate the unit of neighbor of Korean words. In English, a word's orthographic neighborhood is defined as the set of words that can be created by changing one letter of the word while preserving letter positions. For example, the words like pike, pole, and tile are all orthographic neighbors of the word 'pile'. In this study, 2 experiments were performed. In these experiments, 4 conditions of prime were included: primes sharing first letter of first syllable(1), first syllable(2), first syllable and the first letter of second syllable with target(3) and with no formal similarity with target(4). In Exp.1, RT was shortest in condition 3. In Exp.2, condition 2 had the shortest RT. We came to the conclusion that in Korean, a word's neighbor is words that share at least one syllable with the word.

• School Mathematics
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• v.3 no.2
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• pp.447-473
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• 2001

Since the greater part of mathematical concepts have been developed in the direction of “from the concrete and realistic aspects to the abstract level”, children should be secured to learn mathematics genetically with various manipulative materials. The aim of this study is to instigate the active use of geoboards in mathematics classroom. To achieve this arm, we first embodied the several significances on the use of geoboards in mathematics instruction. And we then performed an instruction that children discover and justify the formula related to the area of trapezoid by exploring with geoboards, and analyzed the instructional episode to support our assertion about some secure merit accompanied by using geoboards. From this study, we obtained the conclusion that geoboard activity contains many significances such as children can explore congruence, symmetry, similarity, fundamental properties of figures, and pattern. Futhermore, geoboard activity enable children to transform a figure into other equivalently, develop spatial sense, have basic experiences for coordinate geometry, build a concrete model to explain abstract ideas, and foster the ability of problem solving and mathematical thinking.

• Food Science of Animal Resources
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• v.35 no.1
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• pp.86-90
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• 2015

In this study, we reported the morphogenetic analysis and genome sequence by genomic analysis of the newly isolated staphylococcal phage SMSAP5 from soil of slaughterhouses for cattle. Based on transmission electron microscopy evident morphology, phage SMSAP5 belonged to the Siphoviridae family. Phage SMSAP5 had a double-stranded DNA genome with a length of 45,552 bp and 33 % G+C content. Bioinformatics analysis of the phage genome revealed 43 open reading frames. A blastn search revealed that its nucleotide sequence shared a high degree of similarity with that of the Staphylococcus phage tp310-2. In conclusion, this study is the first report to show the morphological features and the complete genome sequence of the phage SMSAP5 from soil of slaughterhouses for cattle.

• Korean Journal of Adult Nursing
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• v.17 no.5
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• pp.783-792
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• 2005

Purpose: This study was conducted to meta-analyze the effects of hardiness on health-related variables. Method: After review of 19 studies performed by Korean nurses, research variables, statistical data(r or F), and other methodological data were extracted and coded. Research variables were categorized under 5 groups such as health-related behavior, well-being, adaptation, stress, and support according to conceptual similarity. Using SAS program, 20 research variables and 34 effect sizes were calculated after eliminating heterogeneous data by Q-test, Results: Effects of hardiness on whole research variables was .512 and ranged from .322 to .643 by categories. The greatest effect was obtained from well-being category, whereas the smallest effect from stress category. All effect sizes were statistically significant. But fail-safe numbers were small and failed to achieve reasonable tolerance level. Conclusion: Results of meta-analysis indicated that hardiness has a moderate effect on health-related variables. But for improving the reliability of the results by minimizing publication bias, the more hardiness studies should be done.