• Title/Summary/Keyword: statistical dependence

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A Study on Seniors' Fashion and Psychological Characteristics Shown at Overseas Social Media (해외 소셜 미디어에 나타난 시니어 패션과 심리적 특성)

  • Choi, Jung-Hee;Lee, Kyung-Hee
    • Fashion & Textile Research Journal
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    • v.18 no.6
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    • pp.858-868
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    • 2016
  • This study aims to examine the formative characteristics of seniors' fashion in overseas social media, and look into the psychological characteristics of seniors by analyzing the emotions and the characteristics of psychological mechanism in seniors' fashion. The study methods include statistical analysis and content analysis for literary study and data analysis. For data analysis, statistical and content analyses were conducted to analyze 992 data collected from Advanced style, Facebook, and Instagram for 4 years from 2013 to 2016. In formative features shown at overseas social media, circle and square silhouette, achromatic color and warm color, showy tone color, soft material, horizontal details, plain and natural patterns, cap and sunglasses production, and sophisticated elegance styles appeared high. The emotional characteristics in senior's fashion had a silhouette that expressed stability, color that expressed passion, love, happiness, joy, hope and comfort. Materials were expressed by the emotions of dependence and attachment, details were expressed by stable, maternal, calm, comfortable and harmonious emotions. Patterns were expressed by the images of beauty, love, fruit and psychological stability. Accessories were expressed by young and characterful images. Style expressed the emotions of trust, pride, longing, intoxication and ecstasy. The characteristics of psychological mechanism used such shapes and patterns as flower, heart and lips to symbolize the emotions of love, humor, and fun. Young and trendy fashion were expressed in compensation for aging. Kitsch and kidult style was expressed by regression. Elegance fashion was expressed by the sublimation of pride, trust and intoxication.

Statistical Analysis of Water Quality in the Downstream of the Han River (한강하류부 수질의 통계학적 해석)

  • 백경원;정용태;한건연;송재우
    • Water for future
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    • v.29 no.2
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    • pp.179-190
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    • 1996
  • The characteristics of water quality in the downstream of the Han River were analyzed by statistical techniques. Basic characteristics, areal and temporal variations, and correlations of water quality data were investigated. Monthly water quality data have been investigated systematically by exploring data analysis, including time series plot, summary statistics, distribution test, time dependence test, seasonality test and flow relatedness test. Results show that water quality data in this river have seasonality. And applicability of stochastic models such as Thomas-Fiering model and ARMA(1,1) model was identified. From the examination of water quality data related to discharge, it was found that DO and SS are sensitive to water temperature rather than discharge, while BOD and COD are sensitive to discharge at dry seasons. Seasonal periodicities were identified in all water quality variables from the cross correlation analysis.

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Interactive Visual Analytic Approach for Anomaly Detection in BGP Network Data (BGP 네트워크 데이터 내의 이상징후 감지를 위한 인터랙티브 시각화 분석 기법)

  • Choi, So-mi;Kim, Son-yong;Lee, Jae-yeon;Kauh, Jang-hyuk;Kwon, Koo-hyung;Choo, Jae-gul
    • Journal of Internet Computing and Services
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    • v.23 no.5
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    • pp.135-143
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    • 2022
  • As the world has implemented social distancing and telecommuting due to the spread of COVID-19, real-time streaming sessions based on routing protocols have increased dependence on the Internet due to the activation of video and voice-related content services and cloud computing. BGP is the most widely used routing protocol, and although many studies continue to improve security, there is a lack of visual analysis to determine the real-time nature of analysis and the mis-detection of algorithms. In this paper, we analyze BGP data, which are powdered as normal and abnormal, on a real-world basis, using an anomaly detection algorithm that combines statistical and post-processing statistical techniques with Rule-based techniques. In addition, we present an interactive spatio-temporal analysis plan as an intuitive visualization plan and analysis result of the algorithm with a map and Sankey Chart-based visualization technique.

A Spatial Statistical Approach to Residential Differentiation (II): Exploratory Spatial Data Analysis Using a Local Spatial Separation Measure (거주지 분화에 대한 공간통계학적 접근 (II): 국지적 공간 분리성 측도를 이용한 탐색적 공간데이터 분석)

  • Lee, Sang-Il
    • Journal of the Korean Geographical Society
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    • v.43 no.1
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    • pp.134-153
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    • 2008
  • The main purpose of the research is to illustrate the value of the spatial statistical approach to residential differentiation by providing a framework for exploratory spatial data analysis (ESDA) using a local spatial separation measure. ESDA aims, by utilizing a variety of statistical and cartographic visualization techniques, at seeking to detect patterns, to formulate hypotheses, and to assess statistical models for spatial data. The research is driven by a realization that ESDA based on local statistics has a great potential for substantive research. The main results are as follows. First, a local spatial separation measure is correspondingly derived from its global counterpart. Second, a set of significance testing methods based on both total and conditional randomization assumptions is provided for the local measure. Third, two mapping techniques, a 'spatial separation scatterplot map' and a 'spatial separation anomaly map', are devised for ESDA utilizing the local measure and the related significance tests. Fourth, a case study of residential differentiation between the highly educated and the least educated in major Korean metropolitan cities shows that the proposed ESDA techniques are beneficial in identifying bivariate spatial clusters and spatial outliers.

The Effects of Monoamine Oxidase A CA Repeat Polymorphism on Behavioral Trait and Clinical Characteristics in Korean Male Alcoholics (단가아민 산화제 A CA 반복 유전자 다형성이 한국 알코올의존 남자환자의 행동특성과 임상양상에 미치는 영향)

  • Lee, Jung-Sik;Yang, Byung-Hwan;Lee, Kyung-Mee;Kim, Hong-Kwan;Kim, Yong-In;Chai, Young-Gyu
    • Korean Journal of Biological Psychiatry
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    • v.7 no.1
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    • pp.64-73
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    • 2000
  • There are several candidate genes in genetic study of alcoholism. Among them, allelic associations have been reported between MAOA CA repeat polymorphism and alcohol dependence, recently. And also, several studies have been investigated genotype-phenotype relationships between MAOA CA repeat polymorphism and clinical manifestations. The authors tried to identify differences in allelic frequency of MAOA CA repeat polymorphism between alcohol dependence and controls, and in behavioral trait and clinical characteristics according to MAOA CA repeat polymorphism. We also tried to investigate genotype-phenotype relationships between MAOA CA repeat polymorphism and behavioral trait such as aggression. We examined 49 male patients with alcohol dependence(DSM-IV) who had been admitted in Yong-In Mental Hospital from June 1st 1998 to October 31th 1998. We performed semistructured interview for demographic and clinical characteristics. Self-report questionnaire for BDHI(Buss-Durkey Hostility Inventory) was given to all subject at least 4weeks later after admission. Using polymerase chain reaction and polyacrylamide gel electrophoresis, MAOA CA repeat polymorphism were observed in 52 male controls and 49 male patients with alcohol dependence. We devided alcoholic patients into two groups according to allelic length of MAOA CA repeat polymorphism ; alcoholics with short alleles(${\leq}$119bp, N=20) and alcoholics with long alleles(${\geq}$123bp, N=29). T-test, ${\chi}^2$-test and Fisher exact probability test were used for statistical analysis. There were no significant differences in frequency of each allele and short and long alleles of MAOA CA repeat polymorphism between alcoholics and controls. But there were significant differences in clinical symptoms and behavioral trait between alcoholics with short and long alleles. In clinical symptoms, alcoholics with long alleles used alcohol more frequently during one month before admission, had much more maximum amount of beer drinking and reported withdrawal seizure more frequently than with short alleles. In contrary, alcoholics with short alleles expressed depressed mood and guilty feeling more frequently and wanted complete abstinence as a treatment goal more frequently than with long alleles. In behavioral trait, alcoholics with long alleles had higher total aggression score and showed much more self-assertive attitude(subscale of expression of aggression) than with short alleles. Allelic length of MAOA CA repeat polymorphism was correlated with self-assertive attitude and accounted for 9% of the variance of self-assertive attitude. And also, predictable variables of allelic length of MAOA CA repeat polymorphism were drinking frequency and self-assertive attitude. Our findings suggest that MAOA CA repeat polymorphism may provide some behavior modifying role especially in self-assertive attitude and indirect symptom modifying role in Korean male alcoholics.

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Correlation Analyses of the Temperature Time Series Data from the Heat Box for Energy Modeling in the Automobile Drying Process (자동차 건조 공정 에너지 예측 모형을 위한 공조기 온도 시계열 데이터의 상관관계 분석)

  • Lee, Chang-Yong;Song, Gensoo;Kim, Jinho
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.37 no.2
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    • pp.27-34
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    • 2014
  • In this paper, we investigate the statistical correlation of the time series for temperature measured at the heat box in the automobile drying process. We show, in terms of the sample variance, that a significant non-linear correlation exists in the time series that consist of absolute temperature changes. To investigate further the non-linear correlation, we utilize the volatility, an important concept in the financial market, and induce volatility time series from absolute temperature changes. We analyze the time series of volatilities in terms of the de-trended fluctuation analysis (DFA), a method especially suitable for testing the long-range correlation of non-stationary data, from the correlation perspective. We uncover that the volatility exhibits a long-range correlation regardless of the window size. We also analyze the cross correlation between two (inlet and outlet) volatility time series to characterize any correlation between the two, and disclose the dependence of the correlation strength on the time lag. These results can contribute as important factors to the modeling of forecasting and management of the heat box's temperature.

A FUNCTIONAL CENTRAL LIMIT THEOREM FOR MULTIVARIATE LINEAR PROCESS WITH POSITIVELY DEPENDENT RANDOM VECTORS

  • KO, MI-HWA;KIM, TAE-SUNG;KIM, HYUN-CHULL
    • Honam Mathematical Journal
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    • v.27 no.2
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    • pp.301-315
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    • 2005
  • Let $\{A_u,\;u=0,\;1,\;2,\;{\cdots}\}$ be a sequence of coefficient matrices such that ${\sum}_{u=0}^{\infty}{\parallel}A_u{\parallel}<{\infty}$ and ${\sum}_{u=0}^{\infty}\;A_u{\neq}O_{m{\times}m}$, where for any $m{\times}m(m{\geq}1)$, matrix $A=(a_{ij})$, ${\parallel}A{\parallel}={\sum}_{i=1}^m{\sum}_{j=1}^m{\mid}a_{ij}{\mid}$ and $O_{m{\times}m}$ denotes the $m{\times}m$ zero matrix. In this paper, a functional central limit theorem is derived for a stationary m-dimensional linear process ${\mathbb{X}}_t$ of the form ${\mathbb{X}_t}={\sum}_{u=0}^{\infty}A_u{\mathbb{Z}_{t-u}}$, where $\{\mathbb{Z}_t,\;t=0,\;{\pm}1,\;{\pm}2,\;{\cdots}\}$ is a stationary sequence of linearly positive quadrant dependent m-dimensional random vectors with $E({\mathbb{Z}_t})={{\mathbb{O}}$ and $E{\parallel}{\mathbb{Z}_t}{\parallel}^2<{\infty}$.

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Characterization and antimicrobial efficacy of Portland cement impregnated with silver nanoparticles

  • Nam, Ki Young
    • The Journal of Advanced Prosthodontics
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    • v.9 no.3
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    • pp.217-223
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    • 2017
  • PURPOSE. This study investigated the effects of silver nanoparticle (SN) loading into hydraulic calcium silicate-based Portland cement on its mechanical, antibacterial behavior and biocompatibility as a novel dental bone substitute. MATERIALS AND METHODS. Chemically reduced colloidal SN were combined with Portland cement (PC) by the concentrations of 0 (control), 1.0, 3.0, and 5.0 wt%. The physico-mechanical properties of silver-Portland cement nanocomposites (SPNC) were investigated through X-ray diffraction (XRD), setting time, compressive strength, solubility, and silver ion elution. Antimicrobial properties of SPNC were tested by agar diffusion against Streptococcus mutans and Streptococcus sobrinus. Cytotoxic evaluation for human gingival fibroblast (HGF) was performed by MTS assay. RESULTS. XRD certified that SN was successfully impregnated in PC. SPNC at above 3.0 wt% significantly reduced both initial and final setting times compared to control PC. No statistical differences of the compressive strength values were detected after SN loadings, and solubility rates of SPNC were below 3.0%, which are acceptable by ADA guidelines. Ag ion elutions from SPNC were confirmed with dose-dependence on the concentrations of SN added. SPNC of 5.0 wt% inhibited the growth of Streptococci, whereas no antimicrobial activity was shown in control PC. SPNC revealed no cytotoxic effects to HGF following ISO 10993 (cell viability > 70%). CONCLUSION. Addition of SN promoted the antibacterial activity and favored the bio-mechanical properties of PC; thus, SPNC could be a candidate for the futuristic dental biomaterial. For clinical warrant, further studies including the inhibitory mechanism, in vivo and long-term researches are still required.

Residual spatial autocorrelation in macroecological and biogeographical modeling: a review

  • Gaspard, Guetchine;Kim, Daehyun;Chun, Yongwan
    • Journal of Ecology and Environment
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    • v.43 no.2
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    • pp.191-201
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    • 2019
  • Macroecologists and biogeographers continue to predict the distribution of species across space based on the relationship between biotic processes and environmental variables. This approach uses data related to, for example, species abundance or presence/absence, climate, geomorphology, and soils. Researchers have acknowledged in their statistical analyses the importance of accounting for the effects of spatial autocorrelation (SAC), which indicates a degree of dependence between pairs of nearby observations. It has been agreed that residual spatial autocorrelation (rSAC) can have a substantial impact on modeling processes and inferences. However, more attention should be paid to the sources of rSAC and the degree to which rSAC becomes problematic. Here, we review previous studies to identify diverse factors that potentially induce the presence of rSAC in macroecological and biogeographical models. Furthermore, an emphasis is put on the quantification of rSAC by seeking to unveil the magnitude to which the presence of SAC in model residuals becomes detrimental to the modeling process. It turned out that five categories of factors can drive the presence of SAC in model residuals: ecological data and processes, scale and distance, missing variables, sampling design, and assumptions and methodological approaches. Additionally, we noted that more explicit and elaborated discussion of rSAC should be presented in species distribution modeling. Future investigations involving the quantification of rSAC are recommended in order to understand when rSAC can have an adverse effect on the modeling process.

Probabilistic Safety Assessment for High Level Nuclear Waste Repository System

  • Kim, Taw-Woon;Woo, Kab-Koo;Lee, Kun-Jai
    • Journal of Radiation Protection and Research
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    • v.16 no.1
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    • pp.53-72
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    • 1991
  • An integrated model is developed in this paper for the performance assessment of high level radioactive waste repository. This integrated model consists of two simple mathematical models. One is a multiple-barrier failure model of the repository system based on constant failure rates which provides source terms to biosphere. The other is a biosphere model which has multiple pathways for radionuclides to reach to human. For the parametric uncertainty and sensitivity analysis for the risk assessment of high level radioactive waste repository, Latin hypercube sampling and rank correlation techniques are applied to this model. The former is cost-effective for large computer programs because it gives smaller error in estimating output distribution even with smaller number of runs compared to crude Monte Carlo technique. The latter is good for generating dependence structure among samples of input parameters. It is also used to find out the most sensitive, or important, parameter groups among given input parameters. The methodology of the mathematical modelling with statistical analysis will provide useful insights to the decision-making of radioactive waste repository selection and future researches related to uncertain and sensitive input parameters.

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