• Journal of Integrative Natural Science
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• v.7 no.2
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• pp.124-129
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• 2014

In this paper, we construct an logarithmic spiral-like curve using curvature-continuous quadratic spline and quadratic rational spline. The quadratic (rational) spline has self-similarity. We present some properties of the quadratic spline. Also using this $G^2$ quadratic spline, an approximation of logarithmic spiral is proposed and error analysis is obtained.

• Bulletin of the Korean Mathematical Society
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• v.52 no.6
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• pp.2071-2093
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• 2015

In this paper, we investigate the similarity transformations in the Minkowski n-space. We study the geometric invariants of non-null curves under the similarity transformations. Besides, we extend the fundamental theorem for a non-null curve according to a similarity motion of ${\mathbb{E}}_1^n$. We determine the parametrizations of non-null self-similar curves in ${\mathbb{E}}_1^n$.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.37-46
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• 2013

Similarity measure of catchments is essential for regionalization studies, which provide in depth analysis in hydrological response and flood estimations at ungauged catchments. However, this similarity measure is often biased to the selected catchments and is not clearly explained in hydrological sense. This study applied a type of hydrological similarity distance measure-Flood Estimation Handbook to 25 Geum River catchments, Korea. Three Catchment Characteristics, Area(A)-Annual precipitation(SAAR)-SCS Curve Number(CN), are used in Euclidian distance measures. Furthermore, six index of Flow Duration Curve are applied to clustering analysis of SPSS. The catchments' grouping of hydrological similarity measures suggests three groups (H1, H2 and H3) and the four catchments are not grouped in this study. The clustering analysis of FDC provides four Groups; F1, F2, F3 and F4. The six catchments (out of seven) of H1 are grouped in F1, while Sangyeogyo is grouped in F2. The four catchments (out of six) of H2 are also grouped in F2, while Cheongju and Guryong are grouped in F1. The catchments of H3 are categorized in F1. The authors examine the results (H1, H2 and H3) of similarity measure based on catchment physical descriptors with results (F1 and F2) of clustering based on catchment hydrological response. The results of hydrological similarity measures are supported by clustering analysis of FDC. This study shows a potential of hydrological catchment similarity measures in Korea.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1-6
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• 2008

Due to the self-similarity of Berkovich and conical indenters, different materials may show the same loaddepth curve for single indentation. In this study, we first compare the load-depth characteristics of conical and Berkovich indenters via finite element method. We also analyze the variation of load-depth curves with angle of Berkovich indenter, indentation parameters, and material properties. With numerical regressions of obtained data, we then propose dual-Berkovich indentation formulae for material property evaluation. The proposed approach provides the values of elastic modulus, yield strength and strain-hardening exponent and corresponding stress-strain curve with an average error of less than 3%. The method is valid for any elastic indenters made of tungsten carbide and diamond for instance.

• Journal of the Korean Society of Safety
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• v.17 no.4
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• pp.38-44
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• 2002

The application of fractal concept provides an useful method in the study for the quantitative analysis of irregular variations like the fracture surfaces and crack profiles. Fractal curves have characteristics that represents a self-similarity based on the fractal dimension. The fractal dimensions were obtained by the box counting method. In this report, we obtained the nearly stable fractal dimensions of fracture crack profiles for STS316 with CT specimen as the crack advances and the relationships between crack length and fractal dimension. Moreover fractal fracture parameter that corresponds to J-R curve is shown by the relationships between fractal dimension and crack extension. From the results, we concluded that crack extension of high toughness material also shows the fractal characteristics, which can be used in order to evaluate the crack life precisely.

• 유체기계공업학회:학술대회논문집
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• 2005.12a
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• pp.393-400
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• 2005

As one of the useful and powerful methods for designing the optimum pump is using model pump, it is based on the similarity characteristics of turbomachinery. With this theory, we can predict the performance of various pumps. In fact we have performed huge pumps using this, the experimental results were to be sufficient to prove the similarity characteristics. In this study, we predicted the performance of the huge proto-type pump that cannot be installed and made a test. First of all, we had calculated the model ratio between proto-type and model. There were two ways to estimate the performance. One was the application of CFD code, and the other way was model field test. So We selected both of them to guarantee the dependable data and evaluated each other.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.49-55
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• 2013

In this paper, we proposed a good classifier to match different spatial data sets by applying evaluation of classifiers performance in data mining and biometrics. For this, we calculated distances between a pair of candidate features for matching criteria, and normalized the distances by Min-Max method and Tanh (TH) method. We defined classifiers that shape similarity is derived from fusion of these similarities by CRiteria Importance Through Intercriteria correlation (CRITIC) method, Matcher Weighting method and Simple Sum (SS) method. As results of evaluation of classifiers performance by Precision-Recall (PR) curve and area under the PR curve (AUC-PR), we confirmed that value of AUC-PR in a classifier of TH normalization and SS method is 0.893 and the value is the highest. Therefore, to match different spatial data sets, we thought that it is appropriate to a classifier that distances of matching criteria are normalized by TH method and shape similarity is calculated by SS method.

• The Transactions of the Korea Information Processing Society
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• v.1 no.4
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• pp.551-558
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• 1994

This paper proposes the algorithm of the feature extraction, making polyline- shape according to extracted points and similarity test on the object represented by contour. The control points which can make approximate curve are extracted as features of the object. Experiments show that this algorithm is a effective method for identification between different shapes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2101-2123
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• 2023

Recent studies have shown that the neural network-based binary code similarity detection technology performs well in vulnerability mining, plagiarism detection, and malicious code analysis. However, existing cross-architecture methods still suffer from insufficient feature characterization and low discrimination accuracy. To address these issues, this paper proposes a cross-architecture binary function similarity detection method based on composite feature model (SDCFM). Firstly, the binary function is converted into vector representation according to the proposed composite feature model, which is composed of instruction statistical features, control flow graph structural features, and application program interface calling behavioral features. Then, the composite features are embedded by the proposed hierarchical embedding network based on a graph neural network. In which, the block-level features and the function-level features are processed separately and finally fused into the embedding. In addition, to make the trained model more accurate and stable, our method utilizes the embeddings of predecessor nodes to modify the node embedding in the iterative updating process of the graph neural network. To assess the effectiveness of composite feature model, we contrast SDCFM with the state of art method on benchmark datasets. The experimental results show that SDCFM has good performance both on the area under the curve in the binary function similarity detection task and the vulnerable candidate function ranking in vulnerability search task.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.415-421
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• 2014

In this paper, we proposed problem and improvement of halftoning using random space filling curve. Random space filling curve is developed as a solution for shortcoming which space filling curve has self-similarity. It is used to reduce regular pattern can be occurred in constant brightness area in order that randomness apply to scanning path. But there is a problem that some area along scanning path can show too bright result in halftoning using random space filling curve. In this paper, we analyzed cause of problem and proposed single pixel error diffusion as a solution method. This method can avoid over-accumulated error and show better result in halftoning.