• 한국경영과학회지
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• 제42권1호
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• pp.53-63
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• 2017

Managing the quantitative measurement of the data control activities in enterprise wide is important to secure management of data governance. However, research on data governance is limited to concept definitions and components, and data governance research on evaluation models is lacking. In this study, we developed a model of quantitative assessment for data governance including the assessment area, evaluation index and evaluation matrix. We also, proposed a method of developing the model of quantitative assessment for data governance. For this purpose, we used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a quantitative evaluation model for data governance at the early stage of the study. This paper can be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

• 한국BIM학회 논문집
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• 제14권2호
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• pp.25-34
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• 2024

This study proposes a new methodology to increase the flexibility and efficiency of the design data evaluation system by combining Building Information Modeling (BIM) technology in the architectural industry, OpenAI's interactive artificial intelligence, and ChatGPT. BIM technology plays an important role in digitally modeling and managing architectural information. Since architectural information is included, research and development are underway to review and evaluate BIM data according to conditions through program development. However, in the process of reviewing BIM design data, if the review criteria or evaluation criteria according to design change occur frequently, it is necessary to update the program anew. In order for designers or reviewers to apply the changed criteria, requesting a program developer will delay time. This problem was studied by using ChatGPT to modify and update the design data evaluation program code in real time. In this study, it is aimed to improve the changing standards and accuracy by enabling programming non-professionals to change the design regulations and calculation standards of the BIM evaluation program system using ChatGPT. In this study, in the BIM-based design certification automation evaluation program, a program in which the automation evaluation method is being studied based on the design certification evaluation manual was first used. In the design certification automation evaluation program, the programming non-majors checked the automation evaluation code by linking ChatGPT, and the changed calculation criteria were created and modified interactively. As a result of the evaluation, the change in the calculation standard was explained to ChatGPT and the applied result was confirmed.

• 한국소음진동공학회논문집
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• 제16권2호
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• pp.124-131
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• 2006

This study introduces an environmental noise evaluation procedure for wind turbines(W/T) and the evaluation result of a 750 kW wind turbine(W/T) system. Test and evaluation are performed according to the international standard IEC 61400-11 on J48 W/T which is under operation in Daekwanryung W/T test site. With the meteorological data and W/T operational data, noise data are monitored and analysed. An integrated monitoring system is constructed in the test site and is utilized for the evaluation. From the measured noise data, acoustic power level, directivity and tonality of the W/T are estimated under the wind speeds required fly the International standard. The purpose of the study is to establish an W/T noise evaluating system satisfying the international standard and to obtain noise data for home made 750 kW W/T.

• 한국군사과학기술학회지
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• 제17권4호
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• pp.471-478
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• 2014

Navy forces of ROK asked for more than 90% operational availability in the requirement document of combat ship. This study proposes the evaluation methodology of operational availability with the evaluation process, calculation formula, analysis of operational test data. As the case study, the developed methodology is proved to apply for 00 batch-I naval ship using the data to be acquired during the operational test period. The operational availability by test data was 90.03%, and it was satisfied with objective value 90%. The paper will contribute not only to establish the evaluation methodology of operational availability for combat ship but also other general weapon system.

• 의학교육논단
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• 제22권2호
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• pp.131-142
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• 2020

A systematic educational program evaluation system for continuous quality improvement in undergraduate medical education is essential. Monitoring and evaluation (M&E) are two distinct but complementary processes referred to in an evaluation system that emphasizes formative purpose. Monitoring involves regular data collection for tracking process and results, while evaluation requires periodic judgment for improvement. We have recently completed implementing an educational evaluation using the M&E concept in a medical school. The evaluation system consists of two loops, one at the lesson/course level and the other at the phase/graduation level. We conducted evaluation activities in four stages: planning, monitoring, evaluation, and improvement. In the planning phase, we clarified the purpose of evaluation, formulated a plan to engage stakeholders, determined evaluation criteria and indicators, and developed an evaluation plan. Next, during the monitoring phase, we developed evaluation instruments and methods and then collected data. In the evaluation phase, we analyzed results and evaluated the criteria of the two loops. Finally, we reviewed the evaluation results with stakeholders to make improvements. We have recognized several problems including excessive burden, lack of expertise, insufficient consideration of stakeholders' evaluation questions, and inefficient data collection. We need to share the value of evaluation and build a system gradually.

• 대한산업공학회지
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• 제28권2호
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• pp.216-222
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• 2002

The ergonomic human model can be considered as a tool for the evaluation of ergonomic factors in vehicle design process. The proper anthropometric data on driver's postures are needed in order to apply a human model to vehicle design. Although studies on driver's posture have been carried out for the last few decades, there are still some problems for the posture data to be applied directly to the human model due to the lack of fitness because such studies were not carried out under the conditions for the human model application. In the traditional researches, the joint angles were evaluated by the categorized data, which are not appropriate for the human model application because it is so extensive that it can not explain the posture evaluation data in detail. And the human models require whole-body posture evaluation data rather than joint evaluation data. In this study a postural evaluation function was developed not by category data but by the concept of the loss function in quality engineering. The loss was defined as the discomfort in driver's posture and measured by the magnitude estimation technique in the experiment using a seating buck. Four loss functions for the each joint - knee, hip, shoulder, and elbow were developed and a whole-body postural evaluation function was constructed by the regression analysis using these loss functions as independent factors. The developed postural evaluation function shows a good prediction power for the driver's posture discomfort in validation test. It is expected that the driver's postural evaluation function based on the loss function can be used in the human model application to the vehicle design process.

• 대한공간정보학회지
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• 제4권2호
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• pp.123-136
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• 1996

최근 날로 정보기술이 발전하고 사회가 다양화되면서 다양한 데이터를 공유하기 위한 데이터 표준화에 대한 요구가 증대되고 있어 이와 같은 표준화를 위해 우선적으로 지형공간데 이터의 정확성과 신뢰도를 나타내는 데이터품질의 정의 및 평가과정에 관한 연구가 요망되고 있다. 본 연구에서는 세계 각 국에서 채택하고 있는 대표적인 데이터 품질요소의 정의 및 평가방법을 비교 고찰하여 다음과 같은 결과를 얻었다. 첫째, 우리나라의 국가지형공간데이터 교환포멧의 표준내에 데이터의 품질을 평가하기 위한 요소의 정의는 평가기준이 명확한 ISO/TC211의 안을 수용하는 것이 바람직하다고 판단된다. 둘째, 본 연구를 통하여 품질평가요소에 따른 보다 합리적인 지형공간정보 데이터의 품질평가과정을 제시하였으며, 이를 KSDTS에도 적용할 것과 데이터 품질평가결과의 보고형식 등을 더욱 더 명확히 하여 국립지리원의 수치지도작성 규칙 등에도 포함시키는 것을 제안하고자 한다. 셋째, 다양한 sampling방법에 관한 연구 및 우리나라에 적합한 품질허용기준(AQL)의 정립과 대량의 데이터품질을 신속하게 자동 평가할 수 있는 컴퓨터 프로그램 작성 등이 요망된다.

• 의학교육논단
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• 제25권2호
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• pp.126-131
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• 2023

The aim of this study was to systematically collect data for evaluating short- and long-term outcomes using Kirkpatrick's four-level evaluation model, Chonnam National Medical School has established plans for developing and managing a database of student and graduate cohorts. The Education Evaluation Committee, with assistance from the Medical Education Office, manages the development and maintenance of cohort data. Data collection began in the 2022 academic year with first- through fourth-year medical students and graduates of the year 2022. The collected data include sociodemographic characteristics, admission information, psychological test results, academic performance data, extracurricular activity data, scholarship records, national medical licensing exam results, and post-graduation career paths. The Education Evaluation Committee and the Medical Education Office analyze the annually updated student and graduate cohort data and report the results to the dean and relevant committees. These results are used for admissions processes, curriculum improvement, and the development of educational programs. Applicants interested in using the student and graduate cohort data to evaluate the curriculum or conduct academic research must undergo review by the Educational Evaluation Committee before being granted access to the data. It is expected that the collected data from student and graduate cohorts will provide a sound and scientific basis for evaluating short- and long-term achievements based on student, school, and other characteristics, thereby supporting medical education policies, innovation, and implementation.

• Smart Structures and Systems
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• 제33권4호
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• pp.263-279
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• 2024

With the increasing diversity of internet media, available video data have become more convenient and abundant. Related video data-based research has advanced rapidly in recent years owing to advantages such as noncontact, low-cost data acquisition, high spatial resolution, and simultaneity. Additionally, structural nonlinearity extraction has attracted increasing attention as a tool for damage evaluation. This review paper aims to summarize the research experience with the recent developments and applications of video data-based technology for structural nonlinearity extraction and damage evaluation. The most regularly used object detection images and video databases are first summarized, followed by suggestions for obtaining video data on structural nonlinear damage events. Technologies for linear and nonlinear system identification based on video data are then discussed. In addition, common nonlinear damage types in disaster events and prevalent processing algorithms are reviewed in the section on structural damage evaluation using video data uploaded on online platform. Finally, a discussion regarding some potential research directions is proposed to address the weaknesses of the current nonlinear extraction technology based on video data, such as the use of uni-dimensional time-series data as leverage to further achieve nonlinear extraction and the difficulty of real-time detection, including the fields of nonlinear extraction for spatial data, real-time detection, and visualization.

• Management Science and Financial Engineering
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• 제11권3호
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• pp.19-45
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• 2005

Collaborative filtering is one of the most common methods that e-commerce sites and Internet information services use to personalize recommendations. Collaborative filtering has the advantage of being able to use even sparse evaluation data to predict preference scores for new products. To date, however, no in-depth investigation has been conducted on how the data sparsity effect in customers' evaluation data affects collaborative filtering-based recommendation performance. In this study, we analyzed the sparsity effect and used a hybrid method based on customers' evaluations and purchases collected from an online bookstore. Results indicated that recommendation performance decreased monotonically as sparsity increased, and that performance was more sensitive to sparsity in evaluation data rather than in purchase data. Results also indicated that the hybrid use of two different types of data (customers' evaluations and purchases) helped to improve the recommendation performance when evaluation data were highly sparse.