• Title/Summary/Keyword: rank analysis

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A Study on the Relationship of [i] Sound Wave to Sasang Constitution - by Sasang Constitution Analysed with PSSC-2004 ([i]음성파형과 사상체질과의 상관성연구 - 사상체질음성분석기(四象體質音聲分析機)(PSSC-2004)를 이용하여)

  • Song, Hak-Soo;Jung, Woon-Ki;Choi, Min-Ki;Kim, Jong-Chae;Kim, Dal-Rae;Yoo, Jun-Sang
    • Journal of Sasang Constitutional Medicine
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    • v.18 no.2
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    • pp.68-82
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    • 2006
  • 1. Objectives and Methods The purpose of this study was to objectify the diagnosis of Sasang constitution. It was analyzed the adult men and women's [i] sound into 23 factors with PSSC-2004. The study was conducted by subjects inputting 2.5-3 sec of [i] of 586 adult men and women's voices to PSSC-2004. The statistical analysis are applied to three groups : total group, male group, female group. The group of total 586 was composed with 155 Soyangin, 230 Taeumin and 201 Soeumin. The male group was composed with 61 Soyangin, 127 Taeumin and 87 Soeumin. The female group was composed with 94 Soyangin, 103 Taeumin and 114 Soeumin. 2. Results (1) In total group, the Soyangin's code3 was significantly low compared with the others(P=0.011). In total group, the Taeumin's code2 and the Soyangin's code1 were significantly high compared with the others(p=0.007)(P=0.030). (2) In total group, the Soyangin's peak, 50 up in peak and under 3 in peak were significantly low compared with the others(P=0.003) (P=0.005)(P=0.023). (3) In total group, the Taeumin's rank7, rank8, rank9 and rank10 were significantly high compared with the others (P=0.013)(P=0.015) (P=0.016)(P=0.003). (4) In male group, the Soeumin's code3 was significantly high compared with the others(P=0.002). (5) In male group, the Soeumin's peak sum was significantly high compared with the others(P=0.009). It was significant for distinction between Soeumin and Soyangin at the result of post mortem. In male group, the Soeumin's 50 up in peak, 50 down in peak were significantly high compared with the others(P=0.049)(p=0.037). In male group, the Soeumin's under 3 in peak was significantly high compared with the others(P=0.016). It was significant for distinction between Soeumin and Soyangin at the result of post mortem. (6) In male group, the Soeumin's rank 2, rank 3 and rank 4 were significantly low compared with the others(P=0.011) (0.011)(0.024). (7) In female group, the Taeumin's code2 was significantly high compared with the others(P=0.023). In female group, the Soyangin's code1 was significantly low compared with the others (P=0.046). In female group, Soyangin's code-1 was significantly high compared with the others(P=0.024). It was significant for distinction between Taeumin and Soyangin at the result of post mortem. (8) In female group, the Taeumin's peak sum was significantly high compared with the others(P=0.024). It was significant for distinction between Taeumin and Soyangin at the result of post mortem. In female group, the Taeumin's 50 up in peak was significantly high compared with the others(P=0.012). (9) In female group, the Taeumin's rank 7, rank 8, rank 9 and rank 10 were significantly high compared with the others (P=0.009) (P=0.013)(P=0.016)(P=0.023). 3. Conclusion From above result, there is the possibility of efficiency standardguide for constitutional diagnosis by analyzation of the voices.

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Computer-Aided Decision Analysis for Improvement of System Reliability

  • Ohm, Tai-Won
    • Journal of the Korea Safety Management & Science
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    • v.2 no.4
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    • pp.91-102
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    • 2000
  • Nowadays, every kind of system is changed so complex and enormous, it is necessary to assure system reliability, product liability and safety. Fault tree analysis(FTA) is a reliability/safety design analysis technique which starts from consideration of system failure effect, referred to as “top event”, and proceeds by determining how these can be caused by single or combined lower level failures or events. So in fault tree analysis, it is important to find the combination of events which affect system failure. Minimal cut sets(MCS) and minimal path sets(MPS) are used in this process. FTA-I computer program is developed which calculates MCS and MPS in terms of Gw-Basic computer language considering Fussell's algorithm. FTA-II computer program which analyzes importance and function cost of VE consists. of five programs as follows : (l) Structural importance of basic event, (2) Structural probability importance of basic event, (3) Structural criticality importance of basic event, (4) Cost-Failure importance of basic event, (5) VE function cost analysis for importance of basic event. In this study, a method of initiation such as failure, function and cost in FTA is suggested, and especially the priority rank which is calculated by computer-aided decision analysis program developed in this study can be used in decision making determining the most important basic event under various conditions. Also the priority rank can be available for the case which selects system component in FMEA analysis.

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Analyzing the Main Paths and Intellectual Structure of the Data Literacy Research Domain (데이터 리터러시 연구 분야의 주경로와 지적구조 분석)

  • Jae Yun Lee
    • Journal of the Korean Society for information Management
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    • v.40 no.4
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    • pp.403-428
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    • 2023
  • This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

Empirical Analysis of DEA models Validity for R&D Project Performance Evaluation : Focusing on Rank Correlation with Normalization Index (R&D 프로젝트 성과평가를 위한 DEA모형의 타당성 실증분석 : 정규화지표와의 순위상관을 중심으로)

  • Park, Sung-Min
    • IE interfaces
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    • v.24 no.4
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    • pp.314-322
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    • 2011
  • This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.

Innovation of technology and social changes - quantitative analysis based on patent big data (기술의 진보와 혁신, 그리고 사회변화: 특허빅데이터를 이용한 정량적 분석)

  • Kim, Yongdai;Jong, Sang Jo;Jang, Woncheol;Lee, Jongsu
    • The Korean Journal of Applied Statistics
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    • v.29 no.6
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    • pp.1025-1039
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    • 2016
  • We introduce various methods to investigate the relations between innovation of technology and social changes by analyzing more than 4 millions of patents registered at United States Patent and Trademark Office(USPTO) from year 1985 to 2015. First, we review the history of patent law and its relation with the quantitative changes of registered patents. Second, we investigate the differences of technical innovations of several countries by use of cluster analysis based on the numbers of registered patents at several technical sectors. Third, we introduce the PageRank algorithm to define important nodes in network type data and apply the PageRank algorithm to find important technical sectors based on citation information between registered patents. Finally, we explain how to use the canonical correlation analysis to study relationship between technical innovation and social changes.

Analysis on Correlation between Prescriptions and Test Results of Diabetes Patients using Graph Models and Node Centrality (그래프 모델과 중심성 분석을 이용한 당뇨환자의 처방 및 검사결과의 상관관계 분석)

  • Yoo, Kang Min;Park, Sungchan;Rhee, Su-jin;Yu, Kyung-Sang;Lee, Sang-goo
    • KIISE Transactions on Computing Practices
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    • v.21 no.7
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    • pp.482-487
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    • 2015
  • This paper presents the results and the process of extracting correlations between events of prescriptions and examinations using graph-modeling and node centrality measures on a medical dataset of 11,938 patients with diabetes mellitus. As the data is stored in relational form, RDB2Graph framework was used to construct effective graph models from the data. Personalized PageRank was applied to analyze correlation between prescriptions and examinations of the patients. Two graph models were constructed: one that models medical events by each patient and another that considers the time gap between medical events. The results of the correlation analysis confirm current medical knowledge. The paper demonstrates some of the note-worthy findings to show the effectiveness of the method used in the current analysis.

Open Space Spacial Pattern Analysis from the Perspective of Urban Heat Mitigation (도시 열저감 관점에서의 오픈스페이스 토지이용 공간패턴분석)

  • Sangjun Kang
    • Journal of Environmental Impact Assessment
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    • v.33 no.4
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    • pp.155-163
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    • 2024
  • The purpose is to explore the meaning of the open space land use space pattern from the perspective of urban heat reduction using the land-use scenario. The employed methods are as follows: (1) to calculate the cooling capacity Index for each of five land use scenarios, using the InVEST Urban Cooling Model, (2) to calculate open space entropy & morphological spatial pattern for each land use scenario, using the Guidos Spatial Pattern Toolbox, and (3) to perform a Spearman rank correlation analysis between the InVEST and Guidos results. It is found that the rank correlation is moderate between the cooling capacity Index and the open space area ratio (rho=0.50). However, other relations are low. It is observed that only the total amount of open space is likely to have a meaning from the perspective of urban heat reduction, and that other open space location spatial patterns may not have much meaning from the perspective of urban thermal environment management.

An Experimental Study on Combustion Behavior of Different Ranks of Coals and Their Blends (저등급탄과 혼탄의 연소거동에 관한 실험적 연구)

  • Moon, Cheoreon;Sung, Yonmo;Ahn, Seongyool;Kim, Taekyung;Choi, Gyungmin;Kim, Duckjool
    • 한국연소학회:학술대회논문집
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    • 2012.04a
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    • pp.205-208
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    • 2012
  • In this study, the thermal behavior and combustion characteristics of different ranks of coals and their blends were investigated to obtain information necessary for the evaluation of the co-processing of blends with low-rank coals. Thermogravimetric analysis(TGA) and differential thermal analysis(DTA) were carried out at different temperature from ambient temperature to $800^{\circ}C$, and a laboratory-scale pulverized coal combustion burner was used with coal feeing rate of $1.04{\times}10^{-4}kg/s$.

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Cross platform classification of microarrays by rank comparison

  • Lee, Sunho
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.475-486
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    • 2015
  • Mining the microarray data accumulated in the public data repositories can save experimental cost and time and provide valuable biomedical information. Big data analysis pooling multiple data sets increases statistical power, improves the reliability of the results, and reduces the specific bias of the individual study. However, integrating several data sets from different studies is needed to deal with many problems. In this study, I limited the focus to the cross platform classification that the platform of a testing sample is different from the platform of a training set, and suggested a simple classification method based on rank. This method is compared with the diagonal linear discriminant analysis, k nearest neighbor method and support vector machine using the cross platform real example data sets of two cancers.

Comparative Statistic Module (CSM) for Significant Gene Selection

  • Kim, Young-Jin;Kim, Hyo-Mi;Kim, Sang-Bae;Park, Chan;Kimm, Kuchan;Koh, InSong
    • Genomics & Informatics
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    • v.2 no.4
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    • pp.180-183
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    • 2004
  • Comparative Statistic Module(CSM) provides more reliable list of significant genes to genomics researchers by offering the commonly selected genes and a method of choice by calculating the rank of each statistical test based on the average ranking of common genes across the five statistical methods, i.e. t-test, Kruskal-Wallis (Wilcoxon signed rank) test, SAM, two sample multiple test, and Empirical Bayesian test. This statistical analysis module is implemented in Perl, and R languages.