• Journal of Information Processing Systems
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• v.11 no.4
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• pp.573-582
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• 2015

Edit distance metrics are widely used for many applications such as string comparison and spelling error corrections. Hamming distance is a metric for two equal length strings and Damerau-Levenshtein distance is a well-known metrics for making spelling corrections through string-to-string comparison. Previous distance metrics seems to be appropriate for alphabetic languages like English and European languages. However, the conventional edit distance criterion is not the best method for agglutinative languages like Korean. The reason is that two or more letter units make a Korean character, which is called as a syllable. This mechanism of syllable-based word construction in the Korean language causes an edit distance calculation to be inefficient. As such, we have explored a new edit distance method by using consonant normalization and the normalization factor.

• Journal of the Korean Mathematical Society
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• v.59 no.4
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• pp.651-684
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• 2022

Let G be an arbitrary, connected, simply connected and unimodular Lie group of dimension 3. On the space 𝔐(G) of left-invariant Lorentzian metrics on G, there exists a natural action of the group Aut(G) of automorphisms of G, so it yields an equivalence relation ≃ on 𝔐(G), in the following way: h₁ ≃ h₂ ⇔ h₂ = 𝜙^*(h₁) for some 𝜙 ∈ Aut(G). In this paper a procedure to compute the orbit space Aut(G)/𝔐(G) (so called moduli space of 𝔐(G)) is given.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.355-356
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• 2023

The ripple effect is analyzed in the post-construction evaluation phase, but only the qualitative analysis and simple numerical fluctuations are analyzed, thus, no reliable ripple-effect analysis has been conducted. Therefore, in this study, a focus group interview was conducted with 10 experts to propose a plan to improve the ripple effect metrics. Consequently, by linking with the policy-effect metrics of the pre-feasibility study, it is expected that the utilization of the analysis results will be improved and objective and quantitative analysis will be possible.

• Bulletin of the Korean Mathematical Society
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• v.60 no.6
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• pp.1641-1650
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• 2023

It is our goal in this study to present the structure of isotropic mean Berwald Finsler warped product metrics. We bring out the rich class of warped product Finsler metrics behaviour under this condition. We show that every Finsler warped product metric of dimension n ≥ 2 is of isotropic mean Berwald curvature if and only if it is a weakly Berwald metric. Also, we prove that every locally dually flat Finsler warped product metric is weakly Berwaldian. Finally, we prove that every Finsler warped product metric is of isotropic Berwald curvature if and only if it is a Berwald metric.

• Honam Mathematical Journal
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• v.30 no.3
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• pp.551-556
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• 2008

In this paper, we prove the product properties of the singular Kobayashi metrics relative to the higher order Kobayashi metric.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.75-84
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• 2007

Due to the increasing complexity and shorter life cycle of web applications, web applications need to be restructured to improve flexibility and extensibility. These days approaches are being used where systems are understood and restructured through clustering techniques. In this paper, the coupling metrics are proposed for clustering web pages more effectively. To achieve this, web application models are defined, where the relationship between web pages and the numbers of parameters are included. Considering direct and indirect coupling strength based on these models, coupling metrics are defined. The more direct relations between two pages and the more parameters they have, the stronger direct coupling is. The higher indirect connectivity strength between two pages is, the more similar the patterns of relationships among other web pages are. We verify the suggested metrics according to the well known verification framework and provide a case study to show that our metrics complements some existing metrics.

• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.233-240
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• 2001

As software technology is in progress and software quantification is getting more important, many metrics have been proposed to quantify a variety of system entities. These metrics can be classified into two different forms : scalar metric and metric vector. Though some recent studies pointed out the composition problem of the scalar metric form, many scalar metrics are successfully used in software development organizations due to their practical applications. In this paper, it is concluded that hybrid metric form weighting external complexity is most suitable for scalar metric form. With this concept, a general framework for hybrid metrics construction independent of the development methodologies and target system type is proposed. This framework was successfully used in two projects that quantify the analysis phase of the structured methodology and the design phase of the object oriented real-time system, respectively. Any organization can quantify system entities in a short time using this framework.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.373-384
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• 2000

There are many researches about metrics to measure a quality of Object-Oriented(OO) software. However, most of them have only discussed a concept or properties of metrics, and have not shown the detailed procedure for measuring them. They also define a measurement indicator as a threshold, but it has been influenced on a project size or application domains. In this paper, we propose metrics based on characteristics of OO design such as size, complexity, coupling and cohesion, and use a propotion to an average as the measurement indicator. It is easy to classify classes which have a result above the average, and to predict classes which reduced the quality of OO design. They will be modified to hold the average. Proposed metrics are analytically evaluated by Weyuker's nine properties. They are satisfied with seven properties except two properties co not apply to OO metrics. Also, we design a quality assessment system, ASSOD(ASsessment System of Object oriented Design), to measure the quality of the OO design independent of the platform.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.751-770
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• 2018

Web applications are indispensable in the software industry and continuously evolve either meeting a newer criteria and/or including new functionalities. However, despite assuring quality via testing, what hinders a straightforward development is the presence of defects. Several factors contribute to defects and are often minimized at high expense in terms of man-hours. Thus, detection of fault proneness in early phases of software development is important. Therefore, a fault prediction model for identifying fault-prone classes in a web application is highly desired. In this work, we compare 14 machine learning techniques to analyse the relationship between object oriented metrics and fault prediction in web applications. The study is carried out using various releases of Apache Click and Apache Rave datasets. En-route to the predictive analysis, the input basis set for each release is first optimized using filter based correlation feature selection (CFS) method. It is found that the LCOM3, WMC, NPM and DAM metrics are the most significant predictors. The statistical analysis of these metrics also finds good conformity with the CFS evaluation and affirms the role of these metrics in the defect prediction of web applications. The overall predictive ability of different fault prediction models is first ranked using Friedman technique and then statistically compared using Nemenyi post-hoc analysis. The results not only upholds the predictive capability of machine learning models for faulty classes using web applications, but also finds that ensemble algorithms are most appropriate for defect prediction in Apache datasets. Further, we also derive a consensus between the metrics selected by the CFS technique and the statistical analysis of the datasets.

• Journal of KIISE:Software and Applications
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• v.33 no.3
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• pp.301-315
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• 2006

In component-based system, the qualities of components as reusable units are the most important to success the component-based development. Therefore, before software implementation phase, the designed components should be measurable to improve the qualities of the components and the measured results should be reflected in the component-based development phase. In addition, the qualities of the components should be measured accurately. Accordingly, this paper proposes cohesion and coupling metrics applying static and dynamic dependency characteristics by the interdependence between classes. We prove the theoretical soundness of the proposed metrics by the axiom of briand et al. A case study and a comparison with the conventional metrics verify the practicality of the proposed metrics. The development times and endeavors to design the components is reduced, because the proposed metrics measure the qualities of components accurately.