• 한국항공운항학회지
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• 제11권2호
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• pp.93-107
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• 2003

This study is performed to secure the safety of civil aviation by establishing systematic analysis ability of Flight Data Recorder. Through this study, readouting UFDR(Universal Flight Data Recorder) to personal computer, flight data numerical analysis and regulations of Missed Approach. In the analysis, the flight data of B747-400 model aircraft with Missed Approach in San Francisco(KSFO) was selected.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 춘계공동학술대회
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• pp.51-56
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• 2006

Recently data mining techniques have been used for analysis and classification of data related to industrial accidents. The main objective of this study is to compare performance of algorithms for data analysis of industrial accidents and this paper provides a comparative analysis of 5 kinds of algorithms including CHAID, CART, C4.5, LR (Logistic Regression) and NN (Neural Network) with ROC chart, lift chart and response threshold. In this study, data on 67,278 accidents were analyzed to create risk groups for a number of complications, including the risk of disease and accident. The sample for this work chosen from data related to manufacturing industries during three years $(2002\sim2004)$ in korea. According to the result analysis, NN has excellent performance for data analysis and classification of industrial accidents.

• 시스템엔지니어링워크숍
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• 통권4호
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• pp.135-140
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• 2004

Defense analysis & evaluation includes menace analysis, validation analysis, problem analysis, scientific technical analysis, technical trad-off analysis, alternative analysis, cost analysis, etc. Reliable related data is required to perform these analysis activities efficiently. but in case of these defense analysis & evaluation data acquisition system, the data is insufficient and scattered about each organization. the data of database system is also not utilized sufficiently. abroad technical data is also low level data such as catalog or military officer's collection. therefore, this paper propose defense analysis & evaluation data acquisition system by systems engineering process. we also propose construction method of data acquisition system.

• 시스템엔지니어링학술지
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• 제1권2호
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• pp.69-76
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• 2005

Defense analysis & evaluation includes menace analysis, validation analysis, problem analysis, scientific technical analysis, technical trade-off analysis, alternative analysis, cost analysis, etc. Reliable related data is required to perform these analysis activities efficiently. but in case of these defense analysis & evaluation data acquisition system, the data is insufficient and scattered about each organization. The data of database system is also not utilized sufficiently. Abroad technical data is also low level data such as catalog or military officer's collection. Therefore, this paper propose defense analysis & evaluation data acquisition system by systems engineering process. we also propose construction method of data acquisition system.

• International journal of advanced smart convergence
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• 제11권4호
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2001년도 추계학술대회 논문집
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• pp.411-415
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• 2001

Advances in computer and sensor technology have made it possible to obtain superlarge manufacturing process data in real time, letting us to extract meaningful information from these superlarge data sets. We propose a systematic data analysis procedure which field engineers can apply easily to manufacture quality products. The procedure consists of data cleaning and data analysis stages. Data cleaning stage is to construct a database suitable for statistical analysis from the original superlarge manufacturing process data. In the data analysis stage, we suggest a graphical easy-to-implement approach to extract practical information from the cleaned database. This study will help manufacturing companies to achieve six sigma quality.

• Communications for Statistical Applications and Methods
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• 제25권6호
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• pp.619-631
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• 2018

Functional data analysis continues to attract interest because advances in technology across many fields have increasingly permitted measurements to be made from continuous processes on a discretized scale. Particulate matter is among the most harmful air pollutants affecting public health and the environment, and levels of PM10 (particles less than 10 micrometers in diameter) for regions of California remain among the highest in the United States. The relatively high frequency of particulate matter sampling enables us to regard the data as functional data. In this work, we investigate the dominant modes of variation of PM10 using functional data analysis methodologies. Our analysis provides insight into the underlying data structure of PM10, and it captures the size and temporal variation of this underlying data structure. In addition, our study shows that certain aspects of size and temporal variation of the underlying PM10 structure are associated with changes in large-scale climate indices that quantify variations of sea surface temperature and atmospheric circulation patterns.

• 문화기술의 융합
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• 제10권1호
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• pp.443-451
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• 2024

본 연구는 데이터 스칼라십을 이해하기 위하여 데이터 논문으로 색인되는 저널의 지적 구조를 분석 및 시각화하고 데이터 리포지토리의 운영을 비교하였다. 동료 평가(peer review) 유형을 살펴보고, 공동 출현 분석(co-occurence analysis) 및 네트워크 분석(network analysis)을 실시하였다. WoS에 데이터 논문으로 색인되는 상위 10위 저널은 전통적인 유형과 데이터 논문 유형을 혼재해서 발간하고 있었다. DCI에 색인되는 데이터 리포지토리는 대부분 북미 및 유럽 국가에서 운영하고 있다. 국내의 데이터 리포지토리는 대부분 연구원에서 운영하고 있다. 본 연구의 결과는 데이터 저널, 데이터 리포지토리 등 데이터 스칼라십의 관행을 이해하는 데 도움이 되기를 바란다.

• 품질경영학회지
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• 제47권4호
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• pp.713-723
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• 2019

Purpose: The purpose of this study is to develop a statistical program for capability analysis of measuring system and measurement process based upon KS Q ISO 22514-7. Methods: R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Therefore, in this study, we will develop the statistical program using R language. Results: The R program developed in this study consists of the following five modules. ① Measuring system capability analysis with Type 1 study data: MSCA_Type1.R ② Measuring system capability analysis with Linearity study(Type 4 study) data: MSCA_Type4.R ③ Measurement process capability analysis with Type 1 study & Gage R&R study data: MPCA_T1GRR.R ④ Measurement process capability analysis with Type 4 study & Gage R&R study data: MPCA_T4GRR.R ⑤ Attribute measurement processes capability analysis : AttributeMP.R Conclusion: KS Q ISO 22514-7 evaluates measuring systems and measurement processes on the basis of the measurement uncertainty that was determined according to the GUM(KS Q ISO/IEC Guide 98-3). KS Q ISO 22514-7 offers precise procedures, however, computations are more intensive. The R program of this study will help to evaluate the measurement process.

• 한국생활과학회지
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• 제19권5호
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• pp.817-833
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• 2010

This study was dedicated to searching better course of low birth rate study in Korea by carefully analyzing past and present low birth rate researches. For this 179 studies(101 master thesis and 78 journal articles) from 1991 to 2009 were analyzed. Next, using SPSS Win 12.0, the research type, topic, participants, data collection and method of data analysis were compared to the studies' years of publication. The most frequently applied research approach, topic, sampling method, data collection procedure and data analysis method in the research was found to be a literature study, solution and prevention of low birth rate related policy, literature study, literacy analysis. In conclusion, low birth rate studies should become more diversified in terms of types of the research, data collection method, and data analysis. Additionally, research topics should become more realistic and specified. Moreover, research results should be verified before they are applied to the policy.