• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.3_4
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• pp.396-402
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• 2004

The purpose of this study was to investigate the difference of cotton fabric texture perceived between on-line(screening fabric) and off-line(real fabric), and to analyze fabric characteristics having an effect on the difference. The similarity of 55 various cotton fabrics perceived between on-line and on-line were measured showing simultaneously real fabrics and screening fabrics by 7-scale questionnaire. And the characteristics of cotton fabrics such as weave structure, thickness, weight, fabric density, stiffness, Hunter's L, a, b, and hue were measured. Cotton fabrics were classified into 3 groups by extent of similarity. There were no significant differences in weft density, stiffness, Hunter's L, a, b, and hue among 3 groups. But there were significant differences in weave structure, thickness, weight, warp density, and difference of warp ＆ weft density. The fabrics having large similarity were thick and heavy, had small warp density and difference of warp ＆ weft density, and distinct surface texture. The group having medium similarity included fabrics of medium thickness and weight, having weak surface texture, large warp density and difference of warp ＆ weft density. The group having small similarity, which the differences between on-line and off-line were large, included thin and light fabrics having smooth surface and large warp density and difference of warp ＆ weft density.

• Communications of Mathematical Education
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• v.28 no.1
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• pp.97-130
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• 2014

The purpose of the study was to investigate the aspects of analogy of high school student's thinking process revealed in the inquiry activity with synthetic division. The case study method of qualitative research was conducted with two high school 10th grade students. Structure-mapping model(SMM) of Gentner and similarity frames which were proposed by other researchers were utilized to analyze the data. Two students used analogy as a tool and they could discover synthetic division of more than 2 degrees, but they revealed different levels of mathematics discovery depending on the different degree of analogical thinking. Surface similarity in the process of inquiry activity played a vital role in analogical thinking. We asked students to explore and discover analogy based on structure similarity. Analogy based on the systematic approach made it possible to predict upper domain. Analogy based on the procedure similarity induced internalization. We could conclude that analogy has instrumental, heuristic and reflective characteristics.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.4
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• pp.310-316
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• 2014

The location template matching(LTM) method is a technique of identifying an impact location on a structure, and requires a certain measure of similarity between two time signals. In general, the correlation coefficient is widely used as the measure of similarity, while the group delay based method is recently proposed to improve the accuracy of the impact localization. Another possible measure is the frequency response assurance criterion(FRAC), though this has not been applied yet. In this paper, these three different measures of similarity are examined comparatively by using experimental data in order to understand the properties of these measures of similarity. The comparative study shows that the correlation coefficient and the FRAC give almost the same information while the group delay based method gives the shape oriented information that is best suitable for the location template matching method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.506-511
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• 2014

The location template matching (LTM) method is a technique of identifying an impact location on a structure, and requires a certain measure of similarity between two time signals. In general, the correlation coefficient is widely used as the measure of similarity, while the group delay based method is recently proposed to improve the accuracy of the impact localization. Another possible measure is the frequency response assurance criterion (FRAC), though this has not been applied yet. In this paper, these three different measures of similarity are examined comparatively by using experimental data in order to understand the properties of these measures of similarity. The comparative study shows that the correlation coefficient and the FRAC give almost the same information while the group delay based method gives the shape oriented information that is best suitable for the location template matching method.

• Journal of KIISE:Software and Applications
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• v.29 no.6
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• pp.367-376
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• 2002

XML allows users to define elements using arbitrary words and organize them in a nested structure. These features of XML offer both challenges and opportunities in information retrieval and document management. In this paper, we propose a new methodology for computing similarity considering XML semantics - meanings of the elements and nested structures of XML documents. We generate extended-element vectors, using thesaurus, to normalize synonyms, compound words, and abbreviations and build similarity matrix using them. And then we compute similarity between XML elements. We also discover and minimize XML structure using automata(NFA(Nondeterministic Finite Automata) and DFA(Deterministic Finite automata). We compute similarity between XML structures using similarity matrix between elements and minimized XML structures. Our methodology considering XML semantics shows 100% accuracy in identifying the category of real documents from on-line bookstore.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.297-304
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• 2010

Clustering method which based on sentence type or document genre is a technique used to improve translation quality of SMT(statistical machine translation) by domain-specific translation. But there is no previous research using sentence type and document genre information simultaneously. In this paper, we suggest an integrated clustering method that classifying sentence type by syntactic structure similarity and document genre by word similarity information. We interpolated domain-specific models from clusters with general models to improve translation quality of SMT system. Kernel function and cosine measures are applied to calculate structural similarity and word similarity. With these similarities, we used machine learning algorithms similar to K-means to clustering. In Japanese-English patent translation corpus, we got 2.5% point relative improvements of translation quality at optimal case.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.455-462
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• 2012

The loss due to caching replacement in the wireless mobile proxy caching structure has a significant effect on streaming QoS. This paper proposes a similarity-based caching loss minimization (SCLM) for minimizing the loss caused by the caching replacement. The proposed scheme divides object segments, and then it performs the similarity relation about them. Segments that perform the similarity relation generates similarity relation tree (SRT). The similarity is an important metric for deciding a relevance feedback, and segments that satisfy these requirements in the cache block for caching replacement. Simulation results show that the proposed scheme has better performance than the existing prefix caching scheme, segment-based caching scheme, and bi-directional proxy scheme in terms of QoS, average delayed startup ratio, cache throughput, and cache response ratio.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.256-261
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• 2014

The problem of top-${\kappa}$ set similarity joins finds the top-${\kappa}$ pairs of records ranked by their similarities between two sets of input records. We propose an efficient algorithm to return top-${\kappa}$ similarity join pairs using a sampling technique. From a sample of the input records, we construct a histogram of set similarity joins, and then compute an estimated similarity threshold in the histogram for top-${\kappa}$ join pairs within the error bound of 95% confidence level based on statistical inference. Finally, the estimated threshold is applied to the traditional similarity join algorithm which uses the min-heap structure to get top-${\kappa}$ similarity joins. The experimental results show the good performance of the proposed algorithm on large real datasets.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.1
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• pp.60-67
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• 2015

This paper proposes an image-dependent color image enhancement method that uses adaptive luminance enhancement and color emphasis. It effectively enhances details of low-light regions while maintaining well-balanced luminance and color information. To compare the structure similarity and naturalness, we used the tone mapped image quality index (TMQI). The proposed method maintained better structure similarity in the enhanced image than did the space-variant luminance map (SVLM) method or the adaptive and integrated neighborhood dependent approach for nonlinear enhancement (AINDANE). The proposed method required the smallest computation time among the three algorithms. The proposed method can be easily implemented using the field-programmable gate array (FPGA), with low hardware resources and with better performance in terms of similarity.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1108-1118
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• 2019

Non-local means (NLM) algorithm is an effective and successful denoising method, but it is computationally heavy. To deal with this obstacle, we propose a novel NLM algorithm with fuzzy metric (FM-NLM) for image denoising in this paper. A new feature metric of visual features with fuzzy metric is utilized to measure the similarity between image pixels in the presence of Gaussian noise. Similarity measures of luminance and structure information are calculated using a fuzzy metric. A smooth kernel is constructed with the proposed fuzzy metric instead of the Gaussian weighted L2 norm kernel. The fuzzy metric and smooth kernel computationally simplify the NLM algorithm and avoid the filter parameters. Meanwhile, the proposed FM-NLM using visual structure preferably preserves the original undistorted image structures. The performance of the improved method is visually and quantitatively comparable with or better than that of the current state-of-the-art NLM-based denoising algorithms.