• Journal of the Ergonomics Society of Korea
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• v.23 no.2
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• pp.25-36
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• 2004

The effects of task characteristics on the relative efficiency of visual display dimension were studied using a simulated tele-robotic task. Through a conventional method of task analysis. the tele-robotic task was divided into two categories: the task element requiring focused attention (FA task) and the task element requiring global attention (CA task). Time-ta-completion data were collected for a total of 120 trials involving 10 participants. For the CA task. there was no significant difference between the multiple two-dimensional (20) display and the three-dimensional (3D) monocular display. For the FA task. however. the multiple 20 display was superior to the 3D monocular display. The results suggest that the characteristics of a given task have a considerable effect on the choice of display dimensionality and the multiple 3D display is better for human operators to effectively judge depth if the task requires frequent use of focused attention.

• Korean Journal of Social Welfare
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• v.58 no.3
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• pp.27-49
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• 2006

The purpose of the present study was to investigate dimensionality and psychometric properties of identified theoretical constructs of the 'Life Satisfaction Scale for Elderly(LSSE)', which was developed by Choi, Sung-Jae in 1986. Data was obtained from 'The survey of health and welfare status of the elderly aged 65 or older in Chung-Choo city'. The subjects were 275 elderly. Results showed that LSSE had a multi-dimensional structure with three theoretical constructs. Each theoretical construct was named as 'positive affect and subjective satisfaction', 'negative self image and affect', and 'self-value'. Three theoretical constructs had high levels of reliability and validity based on internal construct. 'Positive affect and subjective satisfaction' and 'negative self image and affect' showed high levels of convergent and discriminant validity. 'Self-value' had a high level of convergent validity but acceptable level of discriminant validity. Results of this study revealed that there was a difference in theoretical dimensionality of LSSE between this study and Choi's study, which explained the dimensionality of LSSE as a single dimension. However, the result of this study regarding theoretical dimensionality supported findings from existing studies which insisted that life satisfaction had a multi-dimensional structure.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.6
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• pp.784-788
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• 2008

Studies to detect genes responsible for economic traits in farm animals have been performed using parametric linear models. A non-parametric, model-free approach using the 'expanded multifactor-dimensionality reduction (MDR) method' considering high dimensionalities of interaction effects between multiple single nucleotide polymorphisms (SNPs), was applied to identify interaction effects of SNPs responsible for carcass traits in a Hanwoo beef cattle population. Data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, and comprised 299 steers from 16 paternal half-sib proven sires that were delivered in Namwon or Daegwanryong livestock testing stations between spring of 2002 and fall of 2003. For each steer at approximately 722 days of age, the Longssimus dorsi muscle area (LMA) was measured after slaughter. Three functional SNPs (19_1, 18_4, 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the QTL for meat quality were previously detected, were assessed. Application of the expanded MDR method revealed the best model with an interaction effect between the SNPs 19_1 and 28_2, while only one main effect of SNP19_1 was statistically significant for LMA (p<0.01) under a general linear mixed model. Our results suggest that the expanded MDR method better identifies interaction effects between multiple genes that are related to polygenic traits, and that the method is an alternative to the current model choices to find associations of multiple functional SNPs and/or their interaction effects with economic traits in livestock populations.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.158-163
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• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.82-86
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• 2006

The design of a pattern recognition system generally involves the three aspects: preprocessing, feature extraction, and decision making. Among them, a feature extraction method determines an appropriate subspace of dimensionality in the original feature space of dimensionality so that it can reduce the complexity of the system and help to improve successful recognition rates. Linear transforms, such as principal component analysis, factor analysis, and linear discriminant analysis have been widely used in pattern recognition for feature extraction. This paper shows that singular value decomposition (SVD) can be applied usefully in feature extraction stage of pattern recognition. As an application, a remote sensing problem is applied to verify the usefulness of SVD. The experimental result indicates that the feature extraction using SVD can improve the recognition rate about 25% compared with that of PCA.

• Journal of Fashion Business
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• v.23 no.6
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• pp.27-36
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• 2019

This study aimed to analyze the color differences by warp direction of textile mosaics by focusing on two representative textile wallcovering types, woven and string. Mosaics made of string can be expressed as having three-dimensionality based on color differences resulting from the warp direction of the string. String wallcoverings, unlike woven or non-woven wallcoverings, only have vertically oriented warp lamination on the backing paper without weft, and therefore, the reflection and backing color can be expressed differently depending on the angle of the mosaic. In this study, two identical wallcoverings were manufactured using the same materials but using different textile types, woven and string. The wallcoverings underwent die-cutting by each angle and were deployed in cube form. The analysis was based on ISO 5631-1:2015. The color difference between the two wallcoverings, woven and string, was shown as ΔE* 9.29. Based on the standard deviation of the color difference for each mosaic angle, woven ranged from ΔE* 0.09 to 0.94 and string ranged from ΔE* 1.92 to 3.74, showing a larger color difference. Thus, using the color differences of string to create a mosaic wallcovering improved dimensionality.

• Genomics & Informatics
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• v.18 no.4
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• pp.38.1-38.9
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• 2020

Chronotype is an important moderator of psychiatric illnesses, which seems to be controlled in some part by genetic factors. Clock genes are the most relevant genes for chronotype. In addition to the roles of individual genes, gene-gene interactions of clock genes substantially contribute to chronotype. We investigated genetic associations and gene-gene interactions of the clock genes BHLHB2, CLOCK, CSNK1E, NR1D1, PER1, PER2, PER3, and TIMELESS for chronotype in 1,293 healthy Korean individuals. Regression analysis was conducted to find associations between single nucleotide polymorphism (SNP) and chronotype. For gene-gene interaction analyses, the quantitative multifactor dimensionality reduction (QMDR) method, a nonparametric model-free method for quantitative phenotypes, were performed. No individual SNP or haplotype showed a significant association with chronotype by both regression analysis and single-locus model of QMDR. QMDR analysis identified NR1D1 rs2314339 and TIMELESS rs4630333 as the best SNP pairs among two-locus interaction models associated with chronotype (cross-validation consistency [CVC] = 8/10, p = 0.041). For the three-locus interaction model, the SNP combination of NR1D1 rs2314339, TIMELESS rs4630333, and PER3 rs228669 showed the best results (CVC = 4/10, p < 0.001). However, because the mean differences between genotype combinations were minor, the clinical roles of clock gene interactions are unlikely to be critical.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.1
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• pp.1-11
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• 1999

The three-dimensional laminar mixed convection flow between the conductive printed circuit boards. on which the heat generating rectangular blocks are uniformly distributed, has been examined in the present study. The flow and heat-transfer characteristics are assumed to be pseudo periodic in the streamwise direction and symmetric in the cross-stream direction. Using an algorithm of SIMPLER, the continuity equation. the Navier-Stokes equations and the energy equation are solved numerically in the three-dimensional domain Inside the channel. The convective derivative terms are discretized by the QUICK scheme to accurately capture the flow field. The flow and the heat transfer characteristics are thoroughly examined for various Re and Gr.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4522-4533
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• 2022

For severe accident assessment of reactor pressure vessel (RPV), it is important to develop an accurate model that can predict transient thermo-mechanical behavior of the RPV lower head under the given condition. The present study revisits the lower head failure with two- and three-dimensional finite element models. In particular, we aim to give clear insight regarding the effect of the three-dimensionality present in the distribution of the thickness and thermal load of the lower head. For a rigorous validation of the result, both the OLHF-1 and the OLHF-2 tests are considered in this study. The result suggests that the three-dimensional effect is not negligible as far as the failure location is concerned. The non-uniformity of the thickness distribution is found to affect the failure location and time. The thermal load, which may not be axisymmetric in general, has the most significant effect on the failure assessment. We also observe that the creep property can affect the global deformation of the lower head, depending on the applied mechanical load.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1505-1514
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• 2004

Sequence matching in time-series databases is an operation that finds the data sequences whose changing patterns are similar to that of a query sequence. Typically, sequence matching hires a multi-dimensional index for its efficient processing. In order to alleviate the dimensionality curse problem of the multi-dimensional index in high-dimensional cases, the previous methods for sequence matching apply the Discrete Fourier Transform(DFT) to data sequences, and take only the first two or three DFT coefficients as organizing attributes of the multi-dimensional index. This paper first points out the problems in such simple methods taking the firs two or three coefficients, and proposes a novel solution to construct the optimal multi -dimensional index. The proposed method analyzes the characteristics of a target database, and identifies the organizing attributes having the best discrimination power based on the analysis. It also determines the optimal number of organizing attributes for efficient sequence matching by using a cost model. To show the effectiveness of the proposed method, we perform a series of experiments. The results show that the Proposed method outperforms the previous ones significantly.