• Journal of Korean Institute of Industrial Engineers
• /
• v.33 no.1
• /
• pp.11-25
• /
• 2007

Despite surging interests in analyzing business processes, there are few scientific approaches to analysis and redesign of organizational structures which can greatly affect the performance of business processes. This paper presents a method for deriving and analyzing organizational relations from process models using social network analysis techniques. Process models contain information on who performs which processes and activities, along with the assignment of organizational units such as departments and roles to related activities. To derive social relations between organizational units from process models, three types of metrics are formally defined: transfer of work metrics, subcontracting metrics, and cooperation metrics. By applying these metrics, various relations among organizational units can be derived and analyzed. To verify the proposed method and metrics, they are applied to standard process models of the semiconductor and electronic, and automotive industry in Korea. This paper presents a taxonomy for diagnosing organization structure based on the presented approach. The paper also discusses how to combine analyses in the taxonomy for redesign of organizational structures.

• Journal of Korea Multimedia Society
• /
• v.20 no.8
• /
• pp.1338-1346
• /
• 2017

To achieve software quality and human-centred design for electronic ship navigation called e-navigation, an international guideline of software quality assurance and human-centred design was approved in 2015. Usability is a common goal of both software quality assurance and human-centred design as developing e-navigation system and software developments. Therefore, research is needed to evaluate the usability of e-navigation systems and software such as metrics that can use usability testing. This paper derives effectiveness metrics for e-Navigation usability testing based on international standards. The research method is to analyses and compares the effectiveness measurement and metrics in ISO 9241-11 for human-centered design and ISO/IEC 25022 and 25023 for software quality to find out measurements and metrics being defined commonly. The derived metrics are applied to Electronic Chart Display and Information System as a case study based on performance standard.

• Journal of the Korea Society for Simulation
• /
• v.28 no.1
• /
• pp.81-91
• /
• 2019

The ROK military uses Performance Based Logistics(PBL) as one of the ways to utilize civilian resources and advanced techniques. However, the Korean PBL is mainly focused on purchasing and repairing parts, which is not contributing to the improvement of the availability of overall system. The objective of this study is to suggest the methodology to evaluate the PBL metrics using the simulation and meta model. A meta model is a regression model to analyze the effect of the PBL through simulating various scenarios with performance metrics. As a result, if the PBL is limited to the part level, the performance has little influence on the availability of overall system. In addition, analysis using the meta model shows that it cannot achieve the performance targets when the same metrics are applied to various items without considering the characteristics of the applied items. Therefore, in order to improve availability, PBL coverage should be extended to a system level that includes key components that have a large impact on availability. If multiple items are included in the PBL coverage, the metrics should be applied differently, taking into account the characteristics of each item.

• Journal of KIISE:Software and Applications
• /
• v.29 no.12
• /
• pp.907-925
• /
• 2002

Due to the emersion of J2EE(Java 2, Enterprise Edition), many enterprises inside and outside of the country have been developing the enterprise applications appropriate to the J2EE model. With the help of the component model of Enterprise Java Beans(EJH) which is the J2EE core technology, we can develop the distributed object applications quite simple. EJB application can be implemented by using the component-oriented object transaction middleware and the most applications utilize the distributed transaction. EJB developers can concentrate on the business logic because the EJB server covers the middleware service. Due to these characteristics, EJB technology became popular and then the study for EJB based application has been done quite actively However, the research of metrics for measuring the performance during run-time of the EJB applications has not been done enough. Tn this paper, we explore the workflow for the EJB application service on the run-time and classify the internal operation into several elements. We propose the metrics for evaluating the performance up to the bean level by using the classified elements. First, we analyze the lifecycle according to the bean types which comes from the EJB application on the run-time as to extract each factor used in performance measurement. We also find factors related to a performance and allocate the Performance factors to the metrics as the bean types. We also consider the characteristics like the bean's activation and message passing which happens during bean message call and then analyze the relations of the beans participating in the workflow of the application to make the workflow performance measurement possible. And we devise means to bring performance enhancement of the EJB application using the propose.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.302-309
• /
• 2009

The effectiveness of Building Information Modeling (BIM) tools and processes has been recognized by the industry and owners are beginning to adopt Triple Bottom Line accounting practices, to enhance economic performance and environmental and social performance. However, the widespread and practical application of Green BIM remains largely unrealized. The authors identify that lack of understanding of the applicability of sustainability metrics to BIM design process is a significant barrier to this adoption. Through literature review this paper outlines the various sustainability metrics available to construction and elaborates on the potential of BIM for sustainable design. The paper maps and correlates applicable concepts of sustainability evaluation systems to BIM and describes the constraints in current BIM tools.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.11
• /
• pp.121-126
• /
• 2016

In recommender systems based on collaborative filtering, measuring similarity is very critical for determining the range of recommenders. Data sparsity problem is fundamental in collaborative filtering systems, which is partly solved by Jaccard coefficient combined with traditional similarity measures. This study proposes a new coefficient for improving performance of Jaccard coefficient by compensating for its drawbacks. We conducted experiments using datasets of various characteristics for performance analysis. As a result of comparison between the proposed and the similarity metric of Pearson correlation widely used up to date, it is found that the two metrics yielded competitive performance on a dense dataset while the proposed showed much better performance on a sparser dataset. Also, the result of comparing the proposed with Jaccard coefficient showed that the proposed yielded far better performance as the dataset is denser. Overall, the proposed coefficient demonstrated the best prediction and recommendation performance among the experimented metrics.

• Journal of Internet Computing and Services
• /
• v.23 no.2
• /
• pp.97-105
• /
• 2022

Web services show a rapid evolution and integration to meet the increased users' requirements. Thus, web services undergo updates and may have performance degradation due to undetected faults in the updated versions. Due to these faults, many performances and regression anomalies in web services may occur in real-world scenarios. This paper proposed applying the deep learning model and innovative explainable framework to detect performance and regression anomalies in web services. This study indicated that upper bound and lower bound values in performance metrics provide us with the simple means to detect the performance and regression anomalies in updated versions of web services. The explainable deep learning method enabled us to decide the precise use of deep learning to detect performance and anomalies in web services. The evaluation results of the proposed approach showed us the detection of unusual behavior of web service. The proposed approach is efficient and straightforward in detecting regression anomalies in web services compared with the existing approaches.

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

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

• Journal of Information Science Theory and Practice
• /
• v.11 no.4
• /
• pp.40-50
• /
• 2023

Research in interdisciplinary fields like biomechanics is published in a variety of journals whose visibility depends on bibliometric indexing that is often driven by citation analysis of bibliometric databases. This study documented variation in publication metrics and research subject categories assigned to 14 biomechanics journals. Authors, citation, and citation rate (CR) were collected for the top 15 cited articles in the journals retrieved from the Google Scholar service. Research subject categories were also extracted for journals from three databases (Dimensions, Journal Citation Reports, and Scopus). Despite the focus on biomechanics for the journals studied, these biomechanics journals have widely varying CR and subject categories assigned to them. There were significant (p=0.001) and meaningful (77-108%) differences in median CR between average, low, and high CR groups of these biomechanics journals. Since CR are primary data used to calculate most journal metrics and there is no one biomechanics subject category, field normalization for journal citation metrics in biomechanics is difficult. Care must be taken to accurately interpret most citation metrics of biomechanics journals as biased proxies of general usage of research, given a specific database, time frame, and area of biomechanics research.