• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.131-139
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• 2019

From 2019, software education has become a required subject for all elementary school students. However, many teachers are still unfamiliar with how the classes should be instructed. So this paper presented the meaning, detailed competencies and achievement standard in order to help in the collection, analysis and representation of data among the computational thinking that are key to software education. And it also suggested the applicability of the classes. The full course of the paper is summarized as follows. First, existing studies have summarized the meaning, detail and achievement standard of data related competencies. Based on this, a preliminary investigation was instructed. Pilot study carried out both FGI and closed questions at the same time. This was done in response to the survey's questionnaire reflecting the opinions of experts. Second, the results of the questionnaire generated as a result of the above were verified for validity, stability, and reliability among the PhD, PhD courses, software education teachers, and software education workers. Third, I developed and applied the five lessons as a class objective as 'Choosing collection method-Select the collection method according to the problem situation.', 'Searching for meaning of data-Understand what the analyzed data mean..', 'Using various expression methods-Use a variety of expression tools.' using the backward design model to integrate education, class, and assessment. As a result, the detailed competencies of data collection, analysis, and representation and achievement standard were presented. This may help in setting specific and specific criteria for what direction classes are recommended when planning data-related classes in elementary schools.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.811-813
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• 2003

The Satellite Technology Research Centre (SaTReC), Korea Advanced Institute of Science and Technology (KAIST) has developed and is to launch STSAT-1 (Science and Technology Satellite - 1) on 27$^{th}$ September 2003. The data collection system (DCS) is the one of its payloads. The DCS is a data relay system used for transmission from ground-based sensors through satellite to receiving station. This is one of the important methods collecting global data from the remote locations. In this paper, the DCS on the STSAT-1 will be introduced and the development of the mobile terminal (MT) will be reported.

• 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 Korean Library and Information Science Society
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• v.44 no.1
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• pp.27-47
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• 2013

This study investigated the classification performance of a kNN classifier using the feature selection methods based on document frequency(DF) and collection frequency(CF). The results of the experiments, which used HKIB-20000 data, were as follows. First, the feature selection methods that used high-frequency terms and removed low-frequency terms by the CF criterion achieved better classification performance than those using the DF criterion. Second, neither DF nor CF methods performed well when low-frequency terms were selected first in the feature selection process. Last, combining CF and DF criteria did not result in better classification performance than using the single feature selection criterion of DF or CF.

• The Korean Journal of Nuclear Medicine
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• v.29 no.4
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• pp.478-483
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• 1995

We compared the influences of reconstruction methods using $180^{\circ}$ or $360^{\circ}$ data upon contrasts and discriminating capability and diagnostic accuracy in $^{99m}Tc-MIBI$ stress/rest myocardial SPECT. We reviewed SPECT images reconstructed only with $180^{\circ}$ projection data or with $360^{\circ}$ data in 18 patients and in 11 normal subjects. To compare counts of surface structures and deep structures, we measured ape# posterior wall ratios in 11 normal subjects. To compare the contrasts of images, we measured apex/ventricle ratios. To compare contrasts between normal and diseased myocardial segments, we measured count ratios of defect and normal segments in 4 patients who had single coronary artery diseases. To compare diagnostic accuracy, we scored SPECT images made with $180^{\circ}$ and $360^{\circ}$ data segmentally. Sensitivity and specificity for the diagnosis of coronary artery disease and for the revelation of diseased arteries with both $180^{\circ}$ and $360^{\circ}$ SPECT images. If involved coronary arteries had more narrowing than 50% In coronary angiogram, we considered them as diseased arteries Apex/posterior wall ratios were not different significantly in normal subjects. Apex/ ventricle ratios in normal subjects were different significantly between $180^{\circ}$ and $360^{\circ}$ SPECT images. Defect/normal ratios were different significantly between $180^{\circ}$ and $360^{\circ}$ SPECT images in single vessel disease patients. The overall diagnostic accurracy was the same between $180^{\circ}$ and $360^{\circ}$ data collection. Sensitivity was 94% and specificity was 91% for both types of data collection in this sample population. Sensitivity and specificity of each coronary artery territory were not significantly different between the images made with $180^{\circ}$ and $360^{\circ}$ data. The images made with $180^{\circ}$ data had better contrast between ventricle and myocardium and between hypoperfused and normal myocardium, though no difference was found between the ratios of the myocardial counts of surface and deep structures. However, diagnostic sensitivities of diseased artery territories were not different significantly and so were overall diagnostic accuracy between both methods of making images with $180^{\circ}$ and $360^{\circ}$ data.

• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.108-113
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• 2007

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

• The Journal of Information Systems
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• v.4
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• pp.65-82
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• 1995

This paper investigates the current status of the acquisition of information resources at the domestic hospitals. First of all, as a theoretical background, the concept of hospital information systems and the acquisition of information resources are reviewed. Second, as a research methodology, samples, data collection methods, and data analysis methods are discussed. Third, research hypotheses, operational definitions of the research variables and measurement are discussed. Fourth, as research results, characteristics of the samples and the current situations of the acquisition of information rourses are discussed based on the five research hypotheses.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.543-553
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• 2002

Principal component analysis is applied to reduce p-dimensions into q-dimensions ( $q {\leq} p$). Any partition of a collection of data points with p and q variables generated by the application of six hierarchical clustering methods is re-classified by discriminant analysis. From the application of discriminant analysis through each hierarchical clustering method, correct classification ratios are obtained. The results illustrate which method is more reasonable in exploratory data analysis.

• Women's Health Nursing
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• v.28 no.1
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• pp.65-73
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• 2022

Purpose: This study investigated Korean healthcare providers' attitudes toward sexual and gender minority (SGM) persons and their knowledge and behavior concerning the collection of data on sexual orientation and gender identity (SO/GI). Methods: In this cross-sectional, descriptive study, 137 Korean healthcare providers were recruited through convenience sampling from internet communities for medical professionals. A structured questionnaire was created using Google Surveys. The Mann-Whitney U-test, Kruskal-Wallis test, and Spearman correlation analysis were performed. Results: The sample was mostly women (80.3%) and nurses (83.9%), who had overall negative attitudes toward SGM persons and low levels of knowledge and behavior with regard to the collection of patients' SO/GI data. Participants in their 20s, who were religious, and had clinical experiences in treating or providing nursing care for SGM persons had higher levels of knowledge about the collection of SO/GI data. The level of engagement in collecting SO/GI data was higher among women and in their 20s and 30s, unreligious participants, nurses, and those with less than 10 years of clinical experience. Positive attitudes toward SGM persons were associated with higher levels of knowledge, but lower levels of behavior, regarding the collection of SO/GI data. Conclusion: It is important to recognize the diversity of patients' SO/GI and to collect the corresponding information. To this end, it is necessary to develop and use a standardized SO/GI form. Healthcare providers should also receive education and training related to the health of SGM persons to resolve health problems that disproportionately affect SGM persons and related health disparities.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9731-9737
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• 2014

Large scale secular registry or surveillance systems have been accumulating vast data that allow mathematical modeling of cancer incidence and mortality rates. Most contemporary models in this regard use time series and APC (age-period-cohort) methods and focus primarily on predicting or analyzing cancer epidemiology with little attention being paid to implications for designing cancer registry, surveillance or evaluation initiatives. This research models age-specific cancer incidence rates using logistic growth equations and explores their performance under different scenarios of data completeness in the hope of deriving clues for reshaping relevant data collection. The study used China Cancer Registry Report 2012 as the data source. It employed 3-parameter logistic growth equations and modeled the age-specific incidence rates of all and the top 10 cancers presented in the registry report. The study performed 3 types of modeling, namely full age-span by fitting, multiple 5-year-segment fitting and single-segment fitting. Measurement of model performance adopted adjusted goodness of fit that combines sum of squred residuals and relative errors. Both model simulation and performance evalation utilized self-developed algorithms programed using C# languade and MS Visual Studio 2008. For models built upon full age-span data, predicted age-specific cancer incidence rates fitted very well with observed values for most (except cervical and breast) cancers with estimated goodness of fit (Rs) being over 0.96. When a given cancer is concerned, the R valuae of the logistic growth model derived using observed data from urban residents was greater than or at least equal to that of the same model built on data from rural people. For models based on multiple-5-year-segment data, the Rs remained fairly high (over 0.89) until 3-fourths of the data segments were excluded. For models using a fixed length single-segment of observed data, the older the age covered by the corresponding data segment, the higher the resulting Rs. Logistic growth models describe age-specific incidence rates perfectly for most cancers and may be used to inform data collection for purposes of monitoring and analyzing cancer epidemic. Helped by appropriate logistic growth equations, the work vomume of contemporary data collection, e.g., cancer registry and surveilance systems, may be reduced substantially.