• 제목/요약/키워드: Data Comparison

검색결과 12,537건 처리시간 0.044초

A Study on Information Graphics in the Middle School Social Studies Textbooks

  • Lee, Sang-Bock
    • Journal of the Korean Data and Information Science Society
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    • 제16권3호
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    • pp.603-608
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    • 2005
  • The purpose of this qualitative case study is to understand how the idea of data view and information graphics is used in the social studios middle school textbooks. Data were collected through national curriculum documents and social studies middle textbooks for 7-9 grades. We set up three questions for this studies; what kinds of information graphics are used in the textbooks, how the graphics are organized in the social studies middle school, and how the 7th social studies curriculum is related with the 7th national mathematics curriculum. Through the data analysis, we found that 1) Photographs, illustrations, information maps, etc., are used and frequencies of their usages are in descending order, 2) double lines graphs, circle graphs, and stripe graphs nip often adopted for the comparison of populations, 3) the relation of the two subjects curricula is not so good, especially in the curriculum steps of information mads scatter diagrams, and comparison of populations. Finally we suggest that new web site of data view or information graphics be provided for two curricula, workshop of information graphics are needed for social studies teachers.

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A comparison of imputation methods using machine learning models

  • Heajung Suh;Jongwoo Song
    • Communications for Statistical Applications and Methods
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    • 제30권3호
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    • pp.331-341
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    • 2023
  • Handling missing values in data analysis is essential in constructing a good prediction model. The easiest way to handle missing values is to use complete case data, but this can lead to information loss within the data and invalid conclusions in data analysis. Imputation is a technique that replaces missing data with alternative values obtained from information in a dataset. Conventional imputation methods include K-nearest-neighbor imputation and multiple imputations. Recent methods include missForest, missRanger, and mixgb ,all which use machine learning algorithms. This paper compares the imputation techniques for datasets with mixed datatypes in various situations, such as data size, missing ratios, and missing mechanisms. To evaluate the performance of each method in mixed datasets, we propose a new imputation performance measure (IPM) that is a unified measurement applicable to numerical and categorical variables. We believe this metric can help find the best imputation method. Finally, we summarize the comparison results with imputation performances and computational times.

Quantifying Values from BIM-projects life cycle with cloud-based computing

  • Choi, Michelle Mang Syn;Kim, Inhan
    • 국제학술발표논문집
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    • The 6th International Conference on Construction Engineering and Project Management
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    • pp.271-275
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    • 2015
  • A variety of evaluation application and initiatives on the adoption of Building Information Modelling (BIM) have been introduced in recent years. Most of which however, focused mainly on evaluating design to construction phase-processes, or BIM utilization performances. Through studying existing publications, it is found that continuous utilization of BIM data throughout the building's life cycle is comparatively less explored or documented. Therefore, this study looks at improving this incomplete life cycle condition with the concept that accumulated BIM data should be carried forward and statistically quantified for cross comparison, in order to facilitate practitioners to better improve the projects the future. Based on this conceptual theory of moving towards a closedloop BIM building life cycle, this study explores, through existing literature, the use of cloud based computing as the means to quantify and adaptively utilize BIM data. Categorization of BIM data relations in adaptive utilization of BIM data is then suggested as a initial step for enhancing cross comparison of BIM data in a cloud environment.

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Social Comparison Information, Ethnocentrism, National Identity Associated with Purchase Intention in China

  • FANG, Yuantao;OH, Han-Mo;YOON, Ki-Chang;TENG, Zhuoqi
    • 유통과학연구
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    • 제17권5호
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    • pp.39-50
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    • 2019
  • Purpose - The purpose of our study is to provide an understanding of the relationships among consumer attention to social comparison information (ATSCI), consumer ethnocentrism (CET), national identity (NI), and consumer purchase intention to domestic brands (PIDB). Drawing on the social comparison theory (SCT) and social identity theory (SIT), we developed a model that is empirically testable and explains consumer behavior of domestic brands and products. Research design, data, and methodology - The conceptual framework was tested with primary data collected through a survey in China. Structural equation modeling was employed to test hypotheses. Results - The results from empirical analyses indicated that the ATSCI positively influenced CET and NI, and CET and NI affect consumer PIDB. In addition, the mediating effects of CET and NI on the relationship between ATSCI and PIDB were identified. Nonetheless, little direct impact of ATSCI on PIDB was reported. Conclusions - We suggested that international marketers use given information to attract consumer attention and develop appropriate promotions, especially for Chinese young generations that would pay much attention to social comparison information in their purchase decisions. Our study originally connected one socio-psychological antecedent, ATSCI, with CET and NI and estimated the relationships among the three antecedents and their effects on PIDB in order to predict consumer behavior in China.

간호대학생의 학업스트레스, 소셜네트워크서비스 중독경향, 상향비교성향이 우울에 미치는 영향 (The effects of academic stress, social network service addiction tendency, and upward social comparison on depression in nursing students)

  • 박승미;이정림;유수영
    • 한국간호교육학회지
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    • 제29권1호
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    • pp.41-50
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    • 2023
  • Purpose: The aim of this descriptive study was to identify the factors influencing depression risk among South Korean nursing students. Methods: The data were collected from nursing students attending two universities through web-based questionnaires that surveyed them about depression, academic stress, social network service (SNS) addiction tendency, and upward social comparison from August 22 to September 4, 2021. The collected data from 196 nursing students were analyzed by t-test, one-way ANOVA, Pearson's correlation coefficients, and multiple linear regression. Results: The mean score of depression (using CES-D Korean version) among nursing students was 13.91, which denotes probable depression. Concerning the variance with regard to depression among nursing students, 20.2% was explained by clinical practice period, academic stress, and upward social comparison. Conclusion: Programs to relieve academic stress and depression should be developed in a simple way and systematically provided at the organizational level so that nursing students secure sufficient support during the initial and continuing period of clinical practicums. Concomitantly, an attempt to reduce the upward social comparison should be highly considered.

XPERNATO-TOX: an Integrated Toxicogenomics Knowledgebase

  • Woo Jung-Hoon;Kim Hyeoun-Eui;Kong Gu;Kim Ju-Han
    • Genomics & Informatics
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    • 제4권1호
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    • pp.40-44
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    • 2006
  • Toxicogenomics combines transcriptome, proteome and metabolome profiling with conventional toxicology to investigate the interaction between biological molecules and toxicant or environmental stress in disease caution. Toxicogenomics faces the problems of comparison and integration across different sources of data. Cause of unusual characteristics of toxicogenomic data, researcher should be assisted by data analysis and annotation for getting meaningful information. There are already existing repositories which claim to stand for toxicogenomics database. However, those just contain limited abilities for toxicogenomic research. For supporting toxicologist who comes up against toxicogenomic data flood, now we propose novel toxicogenomics knowledgebase system, XPERANTO-TOX. XPERANTO-TOX is an integrated system for toxicogenomic data management and analysis. It is composed of three distinct but closely connected parts. Firstly, Data Storage System is for reposit many kinds of '-omics' data and conventional toxicology data. Secondly, Data Analysis System consists of analytical modules for integrated toxicogenomics data. At last, Data Annotation System is for giving extensive insight of data to researcher.

반복측정 자료에서 개체기울기를 이용한 집단간의 차이 검정법 (Trend Comparison of Repeated Measures Data between Two Groups)

  • 황금나;김동재
    • 응용통계연구
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    • 제19권3호
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    • pp.565-578
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    • 2006
  • 의약학 분야에서는 두 집단에서 하나의 반복요인을 가지는 반복측정 자료가 많이 사용된다. 이 논문에서는 반복측정된 자료에서 두 군의 시간에 따른 반응값의 선형추세를 비교하여 두 집단간의 차이를 검정하는 방법을 제안한다. 각 개체에서 회귀계수를 추정하고 추정된 회귀계수들에 의해 생성된 표본을 가지고 이표본 t검정(unpaired t-test), 윌콕슨 순위합 검정(Wilcoxon rank sum test), 위치검정(placement test)으로 두 집단간 기울기의 차이를 검정한다. 모의실험(Monte Carlo Simulation)을 통해 실험유의수준(experimental significance level)과 검정력 (power)을 비교하였다.

커널필터링 기법을 이용한 건강비용의 효과적인 지출에 관한 군집화 분석 (Clustering Analysis of Effective Health Spending Cost based on Kernel Filtering Techniques)

  • 정용규;최영진;차병헌
    • 서비스연구
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    • 제5권2호
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    • pp.25-33
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    • 2015
  • 데이터마이닝은 방대한 데이터를 기반으로 정보를 추출하는 방법으로 많은 분야에 적용하고 있으며 특히 보건의료 데이터를 다루는 기법으로 많이 활용 되고 있다. 하지만 데이터가 다양하고 방대해짐에 따라 데이터들을 완벽하게 다룰 수 있는 알고리즘이 개발되지 못한 현황이다. 따라서 본 논문에서는 군집화 알고리즘 중의 하나인 DBSCAN 알고리즘과 EM 알고리즘의 성능을 동일한 데이터에 대하여 분석을 시도하였다. 이를 위하여 DBSACN과 EM 알고리즘에 따른 변화를 Health expenditure 실험데이터의 결과를 기반으로 분석 하였고 더욱 정확한 실험과 더욱 정확한 결과를 알아내기 위하여 Kernel Filtering을 통하여 정확한 데이터분석을 시도하였다. 본 연구에서는 알고리즘의 기술적 성능을 비교한 것을 물론이고 성능을 높이기 위한 시도를 하였다. 이를 통하여 확장한 알고리즘에 따른 성능의 변화와 실험데이터의 적용결과를 기반으로 비교하고 이를 분석하게 되었다. 특히 의료기관을 이용하는 다양한 군집으로부터 데이터 레코드를 수집하여 의료 서비스에 대한 효과적인 비용 지출을 권장할 수 있도록 실험하였다.

와이블 수명자료들에 대한 베이지안 가설검정 (Bayesian Hypotheses Testing for the Weibull Lifetime Data)

  • 강상길;김달호;조장식
    • 품질경영학회지
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    • 제28권3호
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    • pp.1-10
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    • 2000
  • In this paper, we address the Bayesian hypotheses testing for the comparison of Weibull distributions. In Bayesian testing problem, conventional Bayes factors can not typically accommodate the use of noninformative priors which are Improper and are defined only up to arbitrary constants. To overcome such problem, we use the recently proposed hypotheses testing criterion called the intrinsic Bayes factor. We derive the arithmetic and median intrinsic Bayes factors for the comparison of Weibull lifetime model and we use these results to analyze real data sets.

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Comparison Study of Multi-class Classification Methods

  • Bae, Wha-Soo;Jeon, Gab-Dong;Seok, Kyung-Ha
    • Communications for Statistical Applications and Methods
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    • 제14권2호
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    • pp.377-388
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    • 2007
  • As one of multi-class classification methods, ECOC (Error Correcting Output Coding) method is known to have low classification error rate. This paper aims at suggesting effective multi-class classification method (1) by comparing various encoding methods and decoding methods in ECOC method and (2) by comparing ECOC method and direct classification method. Both SVM (Support Vector Machine) and logistic regression model were used as binary classifiers in comparison.