• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.377-382
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• 2003

In our previous study, we have developed sound quality index for steady rumbling sound of passenger car. In this paper, we will study sound quality index for transient rumbling noise. The subjective evaluation of rumbling sound can be indicated to objective parameters by sound metrics of psychoacoustics and principal rumble component. And artificial neural network can be estimated complexity and nonlinear characteristics of relation between subjective evaluation and sound metrics. We applied to sound metrics and artificial neural network to development of sound quality index for transient rumbling sound of passenger car.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.241-262
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• 2012

An understanding of quality attributes is relevant for the software organization to deliver high software reliability. An empirical assessment of metrics to predict the quality attributes is essential in order to gain insight about the quality of software in the early phases of software development and to ensure corrective actions. In this paper, we predict a model to estimate fault proneness using Object Oriented CK metrics and QMOOD metrics. We apply one statistical method and six machine learning methods to predict the models. The proposed models are validated using dataset collected from Open Source software. The results are analyzed using Area Under the Curve (AUC) obtained from Receiver Operating Characteristics (ROC) analysis. The results show that the model predicted using the random forest and bagging methods outperformed all the other models. Hence, based on these results it is reasonable to claim that quality models have a significant relevance with Object Oriented metrics and that machine learning methods have a comparable performance with statistical methods.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.63-70
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• 2013

The multimedia data of game affects the immersion of the game depending on its quality. It is difficult to design the evaluation criteria of artistic quality of the data. But, in a technical point of view, it is possible to evaluate its quality. Thus, the design of evaluation standard can ensure the reliability and objectivity of quality. However, multimedia data quality evaluation metrics had not yet been designed. Therefore, in this study, we extracted quality evaluation elements of Game Multimedia Data, and verified the reliability of the elements. And we defined detailed evaluation items of each element, developed Multimedia Data Quality Evaluation Metrics. We expect that the results of this study will serve as a guide in the development of high-quality games, have a positive impact on the growth of the game industry.

• The Journal of Information Technology and Database
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• v.3 no.2
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• pp.97-118
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• 1996

Information systems quality engineering is one of the most problematic areas in practice and research, and needs cooperative efforts between practice and theory [Glass, 1996]. A model for evaluating the quality of system development process and ensuing success is proposed based on information processing theory of project unit design. A nomological net among a set of quality variables is identified from prior research in the areas of organization science, software engineering, and management information systems. More specifically, system development success was modelled as a function of project complexity, system development modelling environment, user participation, project unit structure, resource availability, and the level of iterative nature of development methodology. Based on the model developed from the information processing theory of project unit design in organization science. appropriate quality metrics for each variable in the proposed model are matched. In this way, a framework of relevant systems development and success quality metrics for controlling systems development processes and ensuing success is proposed. The causal relationships among the constructs in the proposed model are proposed as future empirical research for academicians and as managerial tools for quality managers. The framework and propositions help quality manager to select more parsimonious quality metrics for controlling information systems development processes and project success in an integrated way. Also this model can be utilized for evaluating software quality assurance programmes, which are developed and marketed by many vendors.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.2
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• pp.151-164
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• 2001

Java, used as the most representative object-oriented language, isil becoming the popular language for Internet/Intranet based program development. Moreover, it is used for development language in a variety of areas such as component based development language. In the view of reuse and maintenance of developed program, quality evaluation of program is becoming a more important issue. So, metrics measurement for quality evaluation of program that is developed at present including existing Java application is necessary. However, it is necessary that whether existing object-oriented software metrics is suitable on Java program is to be validated So, in this paper, we build an automated metrics measurement system that needs to validate on object-oriented software metrics and wish to support metrics measurement that is to determine it. The purpose of this system is to support a precise quality evaluation tool. In this system, we apply the metrics classified by Briand. Briand classified the metrics by formalizing mathematically them to verify feasibility of existing object-oriented software metrics. Using the proposed system, we can make comparison and analysis of validation on existing object-oriented metrics by calculating quantitative information more rapidly from Java source program. If there is any problem in feasibility of the metrics, we can establish a suitable metrics on Java program by considering reiJ,1forcement of the existing metrics or proposing new metrics.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3
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• pp.129-136
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• 2006

For the environmental noise assessments. A weighted equivalent noise level (LeqA) is used to measure the time varying environmental noise. However, it is not appropriately reflect various environmental noise features and human emotions. The human perception of the noise is affected largely by the psychoacoustic characteristics of noise as well as the sound pressure level In this study, the effective factors of noise qualify are analyzed using the subjective assessment and statistical analysis of environmental noise, such as road traffic noise. construction site noise, noise in daily living. and other. The analysis methodology is composed to three steps as follows : firstly, the values of the sound qualify metrics of various noise sources were analyzed. And to classify the noise sources, we conducted a cluster analysis using sound quality metrics. Secondly, subjective jury testing was carried out using the methods of paired comparisons and semantic differential. Finally, the correlation between the subjective parameters and the noise quality metrics were analyzed. As a result. the human perception characteristics of the various environmental noise are described in some physical parameters of the noise qualify metrics.

• 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.

• Journal of Korean Society for Quality Management
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• v.31 no.4
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• pp.117-126
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• 2003

In order to maximize the effect of TQM in the Korean industry, quality circle activity as a bottom­up management should be expanded and revitalized. Quality circle activity can be regarded as a kind of knowledge activity where new knowledge is created and knowledge is shared in the economy. This paper proposes new metrics of intangible effect as knowledge assessment focusing on the intellectual capital aspect of quality circle activity, that may be useful for revitalizing quality circle activity from viewpoints not only of financial effect but also of intellectual capital aspect. New metrics of intangible effect consist of two factors： the intellectual capital effect and the intellectual maturity effect. In order to test the validity of new metrics, a case study of 11 companies was done. The result of the case study is that two factors as an intangible effect of quality circle activity should be evaluated to identify the total effect of quality circle activity correctly.

• Journal of Information Technology Services
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• v.7 no.4
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• pp.151-165
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• 2008

This study suggests the organization-level standard(model and process) for quality evaluation of information systems(IS) in non-use organizations despite international standards(ISO/IEC 9126 and ISO/IEC 14598) and national standards(KS X 9126 and KS X 14598) related to quality evaluation of IS. The standard in this study is composed of quality evaluation processes, a quality model, and quality metrics. The weights of the attributes and the sub-attributes in the quality model were calculated by an analytic hierarchy process(AHP). The minimum level and the target level of each metrics were determined by brainstorming of the committee. Furthermore, the case study for the investigation of the applicability and the usability of the suggested organizational standard in the real IS development project was performed. For gaining significant benefits of the standard, both the diffusion and the experience accumulation by its continuous use are needed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.5 s.110
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• pp.457-469
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• 2006

In automotive engineering, the brand sound is one of the important advantage strategies in a car company. For the design of brand sound, the selection of descriptive word for a car sound is one of major works in automotive sound quality research. In this paper, booming and rumbling sound, which are professional words used by sound and vibration engineers are used for the design of brand sound. We employed sound quality metrics, which are used in the psychoacoustics. By most research results, the relationship between subjective evaluations and sound quality metrics has nonlinear characteristics. In order to correlate these subjective evaluations with sound quality metrics, the artificial neural network technology has been applied to two-dimensional sound quality index for a passenger car. These indexes are used for 46 passenger cars, which are samples of the famous cars around the world. Also a preference evaluation for car sound was carried out by sound and vibration engineers. We coupled this preference with booming and rumbling sounds by using artificial neural network. In future, the two dimensional sound and preference index will be very useful to develop brand sound in passenger cars.