• Bulletin of the Korean Mathematical Society
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• v.54 no.4
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• pp.1293-1307
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• 2017

General (${\alpha},{\beta}$)-metrics form a rich class of Finsler metrics. They include many important Finsler metrics, such as Randers metrics, square metrics and spherically symmetric metrics. In this paper, we find equations which are necessary and sufficient conditions for such Finsler metric to be locally projectively flat. By solving these equations, we obtain all of locally projectively flat general (${\alpha},{\beta}$)-metrics under certain condition. Finally, we manufacture explicitly new locally projectively flat Finsler metrics.

• Journal of Information Technology Services
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• v.8 no.4
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• pp.141-150
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• 2009

There are no objective standards for selection and improvement of SLA evaluation metrics for IT service. In this study, we analyze the current IT maturity models for selection and improvement of the metrics and then we derive them according to the maturity levels and propose the redesigned maturity model. To verify whether the model is applicable, we execute a case study based on the D company. We apply the proposed evaluation metrics of the maturity models to the D company and evaluate the metrics. We select a proper level of the D company and an improvement line after measuring evaluation metrics in the maturity level 2. We propose improvement guidelines of evaluation metrics which score is less than the improvement line's and derive SLA evaluation metrics. By using the SLA evaluation metrics for a year, we prove that the way of selection and improvement is useful.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.48-55
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• 2016

Purpose: The purpose of this study is to identify the object-oriented metrics which have strong impact on the reliability and fault-proneness of software products. The reliability and fault-proneness of software product is closely related to the design properties of class diagrams such as coupling between objects and depth of inheritance tree. Methods: This study has empirically validated the object-oriented metrics to determine which metrics are the best to predict fault-proneness. We have tested the metrics using logistic regressions and artificial neural networks. The results are then compared and validated by ROC curves. Results: The artificial neural network models show better results in sensitivity, specificity and correctness than logistic regression models. Among object-oriented metrics, several metrics can estimate the fault-proneness better. The metrics are CBO (coupling between objects), DIT (depth of inheritance), LCOM (lack of cohesive methods), RFC (response for class). In addition to the object-oriented metrics, LOC (lines of code) metric has also proven to be a good factor for determining fault-proneness of software products. Conclusion: In order to develop fault-free and reliable software products on time and within budget, assuring quality of initial phases of software development processes is crucial. Since object-oriented metrics can be measured in the early phases, it is important to make sure the key metrics of software design as good as possible.

• Journal of the Korea Safety Management & Science
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• v.15 no.3
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• pp.151-161
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• 2013

This paper proposes a strategic model of linkage between productivity metrics and financial accounting metrics to properly evaluate the financial effect of TPM activities and the business performance. This linkage strategy provides a connection tool for clear communication between factory-level and headquarters that the metrics proposed by this paper ultimately improves a quality of support from the management by receiving the factors required for productivity activities in the practical field. This factor includes such as equipment, raw materials and labors. Here, we propose that chain reaction models using break down structure of productivity metrics and financial metrics enhance the knowledge sharing of KPI (Key Performance Indicator) which generally tend to create oversimplified communication between management in headquarters and employees in the practical fields. The productivity metrics include OEE(Overall Equipment Effectiveness) of TPM (Total Productive Maintenance), OLE (Overall Labor Effectiveness) of PAC(Performance and Analysis and Control) activities, and OYE (Overall Yield Effectiveness) of TMM(Total Material Management) activities. The financial accounting metrics include ROE(Return on Equity), ROA(Return on Asset), and AVR(Added-Value Rate). The suggested chain reaction model selects the financial metrics as initial stage and branch down until final stage of productivity metrics. When demand exceeds supply, an ideal speed rate, the lean OEE strategy can be initially applied to reduce the gap between the demand and supply, then apply variable costing to estimate correct amount of operating profit. In addition, the paper presents a new type of model for linkage between financial accounting metrics including CAPEX(Capital Expenditure), OPEX(Operating Expenditure), EVA(Economic Added Value), DCL(Degree of Combined Leverage), and TPM productivity activities including AM(Autonomous Maintenance), PM(Preventive Maintenance), MP(Maintenance Prevention) and QM(Quality Maintenance). In order to support the evidence of proposed linkage strategy, a case analysis on 52 projects from national TPM contest from 2011 to 2012 is analyzed. The case presents the classification of CAPEX and OPEX activities from TPM, and proposes the correct implementation of financial effect for TPM projects.

• Bulletin of the Korean Mathematical Society
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• v.56 no.2
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• pp.407-418
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• 2019

In this paper, we study conformal transformations between special class of Finsler metrics named C-reducible metrics. This class includes Randers metrics in the form $F={\alpha}+{\beta}$ and Kropina metric in the form $F={\frac{{\alpha}^2}{\beta}}$. We prove that every conformal transformation between locally dually flat Randers metrics must be homothetic and also every conformal transformation between locally dually flat Kropina metrics must be homothetic.

• Journal of the Korean Mathematical Society
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• v.60 no.1
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• pp.143-165
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• 2023

For each connected and simply connected three-dimensional non-unimodular Lie group, we classify the left invariant Lorentzian metrics up to automorphism, and study the extent to which curvature can be altered by a change of metric. Thereby we obtain the Ricci operator, the scalar curvature, and the sectional curvatures as functions of left invariant Lorentzian metrics on each of these groups. Our study is a continuation and extension of the previous studies done in [3] for Riemannian metrics and in [1] for Lorentzian metrics on unimodular Lie groups.

• Korean Management Science Review
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• v.32 no.2
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• pp.15-35
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• 2015

Large business groups typically have central firms through which their controlling families establish (or acquire) new firms and maintain control over other member firms. Research on corporate governance has developed metrics to identify those central firms and investigated an impact of the centrality on ownership structure and firm's financial performance. This paper introduces centrality metrics used in social network analysis (SNA) to measure how crucial a role each firm plays in the ownership structure of its business group. Then, the SNA centrality metrics are compared with the metrics developed in corporate governance field. Also, we test the relationship between the SNA centrality metrics and firm's value. Experimental results show that the SNA centrality metrics are closely correlated with the centrality metrics used in corporate governance and are significantly correlated with firm's value.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.187-193
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• 2023

Large software systems are being produced with a noticeably higher level of quality with component-based software engineering (CBSE), which places a strong emphasis on breaking down engineered systems into logical or functional components with clearly defined interfaces for inter-component communication. The component-based software engineering is applicable for the commercial products of open-source software. Software metrics play a major role in application development which improves the quantitative measurement of analyzing, scheduling, and reiterating the software module. This methodology will provide an improved result in the process, of better quality and higher usage of software development. The major concern is about the software complexity which is focused on the development and deployment of software. Software metrics will provide an accurate result of software quality, risk, reliability, functionality, and reusability of the component. The proposed metrics are used to assess many aspects of the process, including efficiency, reusability, product interaction, and process complexity. The details description of the various software quality metrics that may be found in the literature on software engineering. In this study, it is explored the advantages and disadvantages of the various software metrics. The topic of component-based software engineering is discussed in this paper along with metrics for software quality, object-oriented metrics, and improved performance.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.134-146
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• 2016

Purpose: Many domestic companies have to make out quantitative evaluation table in their proposal when they conduct the software R&D project. However, most of companies have a difficulty to select the evaluation items and criteria, also to derive a quantitative results. Therefore, we propose a method to derive the quantitative evaluation index by utilizing the ISO/IEC 9126-2. Methods: Analyzing ISO/IEC 9126-2, and we classify the quality metrics as high-classification and sub-classification for Web/App software, Embedded software and Installation software. Next, Conduct the metrics selection survey depending on importance and necessity. Then, carry out the case study. Verify the correspondence between evaluation items and criteria from original suggestion of company and from outcome by utilizing the ISO/IEC 9126-2 quality metrics. Results: It is possible to classify into two metrics, one for common software or one another for only special software. Furthermore, there is quality metrics that is more important and more necessary depending upon characteristics of the software. Conclusion: ISO/IEC 9126-2 quality metrics can be used to make an evaluation items and criteria for quantitative evaluation table of software product.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.