• 대한산업공학회지
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• 제33권1호
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• pp.11-25
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• 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.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1338-1346
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• 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.

• 한국시뮬레이션학회논문지
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• 제28권1호
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• pp.81-91
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• 2019

한국군은 민간 자원과 선진 기법을 도입하는 방안의 하나로 PBL을 적용하고 있다. 그러나 한국군의 PBL은 수리부속 구매와 정비를 중심으로 시행하고 있어 PBL 적용 목적인 장비가동률 향상에 기여하지 못하고 있다. 본 연구는 한국군의 PBL이 장비가동률에 미치는 영향 요소를 분석하는 방법론을 제시하고자 한다. 이를 위해 한국군의 PBL 상황을 시뮬레이션 모델로 설계하고, 시뮬레이션 결과를 회귀분석하여 PBL 성과가 장비가동률에 미치는 영향을 분석할 수 있는 메타 모델을 제안한다. 연구 결과 수리부속 수준에만 제한적으로 PBL을 적용하면 성과가 장비가동률에 미치는 영향력은 크지 않았다. 또한, 메타 모델을 이용해 분석해 보면 적용품목 특성을 고려하지 않고 여러 품목에 동일한 성과지표를 설정할 경우 성과목표를 달성할 수 없었다. 따라서 장비가동률을 향상시키기 위해서는 장비가동률에 영향력이 큰 핵심구성품을 포함하는 체계 수준으로 PBL 적용범위를 확대해야 하며, PBL 적용범위에 다수 품목이 포함될 경우 품목별 특성을 고려해 성과지표를 차등 적용해야 한다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제29권12호
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• pp.907-925
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• 2002

J2EE(Java 2, Enterprise Edition)의 등장으로 국내.외 수많은 기업들이 J2EE의 모델에 맞게 엔터프라이즈 어플리케이션을 개발하고 있다. 이것은 J2EE의 핵심 기술 요소인 Enterprise Jana Beans(EJB)의 컴포넌트 모델이 분산 객체 어플리케이션의 개발을 간단하게 해주기 때문이다. EJB 어플리케이션은 컴포넌트 지향의 객체 트랜잭션 미들웨어를 사용하여 구현되며, 많은 어플리케이션이 분산 트랜잭션을 이용한다. EJB 서버는 이를 위한 미들웨어 서비스를 제공하여 EJB 개발자가 비즈니스 로직에 집중할 수 있도록 한다. 이러한 특징은 EJB 기술을 각광받게 하는 요인이 되었고, EJB 기반의 어플리케이션 개발에 관한 연구가 활발하게 이루어지게 하였다. 그러나 아직은 EJB 어플리케이션 운영 상태에서 성능을 측정하기 위한 메트릭에 대한 연구가 미흡하다. 본 논문에서는 운영 상태의 EJB 어플리케이션에서 서비스를 위한 워크플로우를 살펴보고, 어플리케이션 내부 작업을 여러 요소들로 분류한다. 분류된 여러 요소를 이용하여 빈(Bean) 레벨까지의 성능 측정을 위한 메트릭을 제시한다. 성능 측정에 사용되는 각 요소들을 추출하기 위해 우선 EJB 어플리케이션의 운영 상태에서 발생하는 빈의 종류에 따른 생명주기를 분석하고, 이를 기반으로 성능과 관련된 요인을 추출하여 빈의 종류에 따른 성능 요인을 메트릭에 부여할 수 있도록 한다. 또한 빈 메소드 호출시 발생하는 빈의 활성화와 메시지 전파 등의 특성을 파악하고, 어플리케이션 내에서 워크플로우에 참여하는 빈들 간의 관계를 분석하여 워크플로우에 대한 성능 측정이 가능하도록 한다. 또한 제안된 메트릭을 통하여 EJB 어플리케이션의 성능 향상을 도모할 수 있도록 한다.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.302-309
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• 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.

• 한국컴퓨터정보학회논문지
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• 제21권11호
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• pp.121-126
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• 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.

• 인터넷정보학회논문지
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• 제23권2호
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• pp.97-105
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• 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
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• 제8권2호
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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.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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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.

• Journal of Information Science Theory and Practice
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• 제11권4호
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• pp.40-50
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• 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.