• Environmental Analysis Health and Toxicology
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• v.23 no.4
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• pp.231-245
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• 2008

Various methods for detecting changes in response behaviors of indicator specimens are presented for monitoring effects of toxic treatments. The movement patterns of individuals are quantitatively characterized by statistical (i.e., ANOVA, multivariate analysis) and computational (i.e., fractal dimension, Fourier transform) methods. Extraction of information in complex behavioral data is further illustrated by techniques in ecological informatics. Multi-Layer Perceptron and Self-Organizing Map are applied for detection and patterning of response behaviors of indicator specimens. The recent techniques of Wavelet analysis and line detection by Recurrent Self-Organizing Map are additionally discussed as an efficient tool for checking time-series movement data. Behavioral monitoring could be established as new methodology in integrative ecological assessment, tilling the gap between large-scale (e.g., community structure) and small-scale (e.g., molecular response) measurements.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.6 no.1
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• pp.22-26
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• 1995

Change of voice, espicially hoarseness show irregular vibration of vocal cord. So, computerized acoustic analysis has presented many acoustic parameters for objective evaluation of voice. We objectively investigated the vocal vibration of normal persons and hoarseness patients in Korea. The RAP(relative average perturbation), PPQ(pitch period perturbation quotient) and APQ(amplitude perturbation quotient) of normal persons were compared with that of hoarseness patients with multidimensional voice program for the possibility of distinguishing the pathologic vocal vibration from normal. Authors agree that RAP, PPQ and APQ showed interesting differences between the normal and the hoarseness patients by the multivariate statistical analysis. In conculusion, relative average perturbation, pitch period perturbation and amplitude perturbation quotient might be meangingful screening parameters distinguishing hoarseness patients from normal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.3952-3961
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• 2012

Developing computational methods for identifying cell cycle-regulated genes has been one of important topics in systems biology. Most of previous methods consider the periodic characteristics of expression signals to identify the cell cycle-regulated genes. However, we assume that cell cycle-regulated genes are relatively active having relatively many interactions with each other based on the underlying cellular network. Thus, we are motivated to apply the theory of multivariate phase synchronization to the cell cycle expression analysis. In this study, we apply the method known as "Self-Organizing Maps with statistical Phase Synchronization (SOMPS)", which is the combination of self-organizing map and multivariate phase synchronization, producing several subsets of genes that are expected to have interactions with each other in their subset (Kim, 2008). Our evaluation experiments show that the SOMPS algorithm is able to detect cell cycle-regulated genes as much as one of recently reported method that performs better than most existing methods.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.83-97
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• 2019

As society develops, the dissemination of microdata has increased to respond to diverse analytical needs of users. Analysis of microdata for policy making, academic purposes, etc. is highly desirable in terms of value creation. However, the provision of microdata, whose usefulness is guaranteed, has a risk of exposure of personal information. Several methods have been considered to ensure the protection of personal information while ensuring the usefulness of the data. One of these methods has been studied to generate and utilize synthetic data. This paper aims to understand the synthetic data by exploring methodologies and precautions related to synthetic data. To this end, we first explain muptiple imputation, Bayesian predictive model, and Bayesian bootstrap, which are basic foundations for synthetic data. And then, we link these concepts to the construction of fully/partially synthetic data. To understand the creation of synthetic data, we review a real longitudinal synthetic data example which is based on sequential regression multivariate imputation.

• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.118-128
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• 2021

Purpose: To investigate the value of MR textural analysis, including use of diffusion-weighted imaging (DWI) to differentiate malignant from benign soft-tissue tumors on 3T MRI. Materials and Methods: We enrolled 69 patients (25 men, 44 women, ages 18 to 84 years) with pathologically confirmed soft-tissue tumors (29 benign, 40 malignant) who underwent pre-treatment 3T-MRI. We calculated MR texture, including mean, standard deviation (SD), skewness, kurtosis, mean of positive pixels (MPP), and entropy, according to different spatial-scale factors (SSF, 0, 2, 4, 6) on axial T1- and T2-weighted images (T1WI, T2WI), contrast-enhanced T1WI (CE-T1WI), high b-value DWI (800 sec/mm²), and apparent diffusion coefficient (ADC) map. We used the Mann-Whitney U test, logistic regression, and area under the receiver operating characteristic curve (AUC) for statistical analysis. Results: Malignant soft-tissue tumors had significantly lower mean values of DWI, ADC, T2WI and CE-T1WI, MPP of ADC, and CE-T1WI, but significantly higher kurtosis of DWI, T1WI, and CE-T1WI, and entropy of DWI, ADC, and T2WI than did benign tumors (P < 0.050). In multivariate logistic regression, the mean ADC value (SSF, 6) and kurtosis of CE-T1WI (SSF, 4) were independently associated with malignancy (P ≤ 0.009). A multivariate model of MR features worked well for diagnosis of malignant soft-tissue tumors (AUC, 0.909). Conclusion: Accurate diagnosis could be obtained using MR textural analysis with DWI and CE-T1WI in differentiating benign from malignant soft-tissue tumors.

• The Korean Journal of Applied Statistics
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• v.9 no.2
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• pp.55-72
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• 1996

It is essential in modern industry that quality and procuctivity are improved continuously. To accomplish this purpose, quality control must be maintained in all parts of a company. Recently, some tire manufacture companies are beginning to show interest in quality control. They have tried to achive some results through the statistical analysis for the experimental data which has accumulated up to now and then they strive to determine the structural relationship between the design factors in tire construction and tire performance characteristics. The measurement data obtained from the construction engineering is given in multivariate form owing to the various properties found in tire design components as wll as in performance. Also it may be existed the relationship among the multimple response variables. Thus we proposes the use of the biplot graphical display as an analytic tool of data matrices with complex respects. The proposed biplots are also availalbe to understand both the underlying structure of the data and the roles played by the different components. In particular, we consider the matter of how best to use the biplots in the maltivariate analysis of variance and multiple response data. Finally we apply this method to analyze the actual data.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.297-306
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• 2000

Many users have made the most often use of the SAS system in statistical data analysis all over the world. But it is difficult to use the grand procedures and language of the SAS system. Therefore the side of program development has changed in the graphic-oriented and menu-centered way like SASj ASSIST, SASjINSICHT after a version 6.08 turned into the Window environment. A biplots is a multivariate data analysis technique that graphically describes both relationships among the multidimensional observations and relationships among the variables. But there were not the procedure and graphic interface for a biplots algorithm in the SAS system. In this paper, there are two objects. First, we supply users with the convenience of the environment of CLI, which is constructed with SASj AF and SCL, to solve the problem that we have programed a biplots algorithm with the SASjIML one by one. Second, we reflect the current of the Information Age which means the spread of various kinds of system construction to extract useful information from data with the help of the development of hardware and software.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.223-236
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• 2013

Various statistical classification methods to predict election to the Major League Baseball hall of fame of are implemented and their accuracies are compared. Seventeen independent variables are selected from the data of candidates eligible for the hall of fame and well-known classification methods such as discriminant analysis and logistic regression as well as the recently proposed Mahalanobis-Taguchi system(MTS). The MTS showed a better performance than the others in classification accuracy because it is especially efficient in cases where multivariate data does not constitute directionally geographical groups according to attributes.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.707-714
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• 2024

Different degrees of natural radioactivity found in quartz can have negative consequences on health. Quartz vein along the investigated Abu Ramad area, Egypt, had its natural radioactivity assessed. The HPGe spectrometer was used to determine the role played by the radionuclides ²³⁸U, ²³²Th, and ⁴⁰K in the gamma radiation that was emitted, and the results showed that these concentrations are 484.64 ± 288.4, 36.8 ± 13.1 and 772.2 ± 134.6 Bq kg^-1 were higher than the corresponding reported global limits of 33, 45, and 412 Bq kg^-1 for each radionuclide (²³⁸U, ²³²Th, and ⁴⁰K). Among the radiological hazard parameters, the excess lifetime cancer risk (ELCR) is estimated and it's mean value of ELCR (1.2) is higher than the permissible limit of 0.00029. The relationship between the radionuclides and the associated radiological hazard characteristics was investigated based on multivariate statistical methods including Pearson correlation, principal component analysis (PCA), and hierarchical cluster analysis (HCA). According to statistical research, the radioactive risk of quartz is primarily caused by the ²³⁸U, ²³²Thand ⁴⁰K. Finally, applying quartz to building materials would pose a significant risk to the public.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.309-324
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• 2015

In this paper we introduce how to analyze survival data via a SRC-Stat statistical package. This provides classical survival analysis (e.g. Cox's proportional hazards models for univariate survival data) as well as advanced survival analysis such as shared and nested frailty models for multivariate survival data. We illustrate the use of our package with practical data sets.