• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.127-134
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• 2009

RAM(Reliability, Availability, Maintainability) is important performance factor to keep combat readiness and optimize operational and maintenance cost of weapon systems. This paper discusses the method to establish RAM for combat readiness by using field failure data from similarity equipments. Operational availability is estimated from a binomial distribution function of user's operational conditions such as combat readiness preservation probability, operational rate, operational availability and total number of equipment. Reliability and maintainability is estimated from field failure data from similarity equipment to accomplish operational availability. The effectiveness of established RAM is verified through analysis of combat readiness preservation probability and mission reliability. A case study of weapon system illustrates the process of the proposed method.

• Proceedings of the Korean Geotechical Society Conference
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• 2007.09a
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• pp.431-439
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• 2007

Data logger is generally needed for gathering field information automatically(or manually), using various sensors. However it, currently used in the county, is produced and developed by overseas. It is difficult to upgrade related program due to developed system and limited user in terms of environment it is used. On the other hand, several companies developed and sold unique data logger based their technique expertise in the country. But enhancement and practical use of related technology has much difficulties because feasibility, marketability and demand for technique are uncertain. In this study, it is the main purpose to offer basic information to select equipment suitable for field characteristic through analysis and comparison with features about method of information collection, operating program and process technique data logger which is used primarily in geotechnical engineering in both domestic and international.

• Journal of Applied Reliability
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• v.8 no.1
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• pp.1-13
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• 2008

A methodology for collection and analysis of automotive field reliability data is presented. Automotive warranty system usually covers a pre-determined period of time and/or mileage accumulation. Therefore mileage information for the vehicles that have not experienced any failure or problems during the warranty period is not available. In this paper, a reliability analysis method using the estimated mileage distribution from an additional survey for vehicles that have not any record during the warranty period is proposed. Methods of reliability analysis using the warranty information collected under the EU and US warranty policies are also provided.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.594-600
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• 2010

In this paper, we introduced non-parametric statisticals method that could analyse the field data and proposed application ways such as repair-part demand forcasting, MTBF estimation and trend analysis, identity comparison with two populations using the analytical results. In addition, we applied that to real field data which has been collected for about ten years from K series tracked vehicle. After that, we compared the results with those using traditional parametric statistical method, and verified the usability of them.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.176-183
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• 2003

This paper presents a neural network based approach to disseminating information relating to experimental and field observations in engineering. Although the methodology is generic and can be applied to many areas of engineering science, attention is focussed here solely on geotechnical engineering applications. Field data relating to the settlement of foundations presented by Burland and Burbidge (1985) which led to their well known equation for calculation of settlement, now included in most text books, is re-visited. A part of the data, chosen randomly, is used to train an Artificial Neural Network (ANN), which relates foundation settlement to various causes as identified by the authors. Predictions are made for situations for which data were not used in training. These indicate sufficient accuracy when compared to the original field data. Accuracy of predictions is further improved when all the data are included in the training set. The finally trained ANN is shown to represent these data more accurately than the Burland and Burbidge equation. Based on the above heuristic example, an ANN is presented as an alternative to developing equations and design rules in geotechnical engineering practice. Significant advantages are shown to arise by using this methodology. Ease of updating the ANN, as and when additional data becomes available, being the most important one. Loss of transparency, however, seems to be the main disadvantage.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2001.11a
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• pp.142-147
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• 2001

Recently, as the field of construction industrial is enlarged and the blanket control system is formed, the process plan considered from initial process formation to construction cost must be systematic and rational. So we have to propose and compose the new process formation system that divides the intention decisive property of construction data, its relationship and the data property according to process definitely and can express and control easily the public ownership of construction data and network process under the peculation control. So this study decides the field formation and construction data of the work according to the ordering and contract way to establish the process data system for the process plan, shows that the lot theory is necessary to form the economical construction field and proposes that the integrated formation system of construction data that is made by code system must be established.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.171-191
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• 2022

The purpose of this study is to explore inductively learning effects of virtual field trips(VFTs) programs developed by elementary school students under the theme of minerals and rocks, focusing on learning in virtual geological components. Ten students attending 'H' elementary school in the metropolitan area voluntarily participated. In order to develop a virtual field trips programs, pre-actual outdoor geological field trips were conducted and virtual field trips programs were developed. In this process, written data of students observing, all video recording and voice recording materials of the course in which students participated, VR development data, and post-interview data were collected. Data were inductively analyzed focusing on four areas(cognitive, psychological, geography, and technical components) of learning in virtual geological field trips. As a result, there were positive learning effects for students in four areas. This study revealed that the study participants were not just participants in virtual learning, but rather developed classes for virtual field trips programs, which had significant results in terms of authentic inquiry.

• Wind and Structures
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• v.4 no.2
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• pp.101-118
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• 2001

This paper reports the field measurements concerning pressure equalization of rainscreen facades carried out at the Technical University of Eindhoven (TUE) in the Netherlands. The field facility including the details of test panel, meteorological tower, instrumentation, data collection and analysis is presented. Results of investigations into cavity response for various leakage and venting configurations are discussed. Frequency domain techniques have been utilized to show the influence of wind as well as facade characteristics on the pressure equalization performance. Further, this paper presents an early attempt to synthesize the experimental results into existing building codes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.698-701
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• 2004

In many literatures, data mining has been used as a utilization of data warehouse and data collection. The biggest utilizations of data mining are for marketing and researches. This is solely because of the data available for this field is usually in large amount. The usability of the data mining is expandable also to the production process. While the object of research of the data mining in marketing is the customers and products, data mining in the production field is object to the so called 4MlE, man, machine, materials, method (recipe) and environment. All of the elements are important to the production process which determines the quality of the product. Because the final aim of the data mining in production field is the quality of the production, this data mining is commonly recognized as quality data mining. As the variables researched in quality data mining can be hundreds or more, it could take a long time to reveal the information from the data warehouse. Feature selection methodology is proposed to help the research take the best performance in a relatively short time. The usage of available simple statistical tools in this method can help the speed of the mining.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.4
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• pp.169-194
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• 2020

Recently, many academic fields are developing metadata to manage data produced in the field. Metadata to support a specific academic field beyond the general field is considered essential for searching, managing, sharing, and reusing research data in the field. Therefore, in this study, metadata items were derived to manage research data produced in forestry engineering. In order to derive metadata items, mapping work was performed on 7 metadata such as FGDC-CSDGM, ISO 19115, NEFIS, INSPIRE, ANZLIC, DataCite 4.3, and TTA.KO-10.0976. As a result of this study, 6 mandatory, 13 recommendations and 9 optional elements were derived. The derived metadata can be used as an item to systematically manage research data in the field of forestry engineering.