• Health Policy and Management
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• v.8 no.2
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• pp.149-165
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• 1998

The purpose of this study is to examine the effect of the health status on the quality of life of the rural elderly, and to examine the conditional effect of socialsupport for that influence. 'Quality of life' used in this study was defined by unidimensional approach. The data were collected by conducting individual interviews with 296 rural elderly people aged 60 and the above who were living in one township of Kangwondo, between the time period of October and November 1995. The main findings are as follows: 1. Hierarchical regression analyses were carried out to examine the relative contribution of three set of variables on the quality of life. The first step, which included sociodemographic factors showed that the coefficient of determination (R$^{2}$) was 8% and income was a statisically significant variable. The second step, by adding health related factors, revealed that the R$^{2}$ was increased to 34% by 26% point and the degree of health recognition was the statistically significant variable. The third step, by projecting additionall social support related variables revealed that the R$^{2}$ was 42% 2. The conditional effect of social support was analyzed to examine the influence the health status has on the quality of life. The results are as follows: 1) The IADL and the degree of social contact interacted, resulting in that the higher degree of social contact boosted the stronger effect of IADL. 2) The effect of subjective health recognition on the quality of life is depended upon degree of family ontact. 3) The effect of eyesight on the quality of life is depended upon degree of satisfaction in social relation. The lower the degree of social support was, the bigger the influence of health related variables affecting quality of life became. This study explains that health status is a major factor in predicting the quality of life of the aged. Particularly the subjective health recognition was an important factor as the perception of quality of life.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.127-139
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• 2023

Numerous genuine issues, for example, financial exchange expectation, climate determining and so forth has inalienable arbitrariness related with them. Receiving a probabilistic system for forecast can oblige this dubious connection among past and future. Commonly the interest is in the contingent likelihood thickness of the arbitrary variable included. One methodology for expectation is with time arrangement and auto relapse models. In this work, liner expectation technique and approach for computation of forecast coefficient are given and likelihood of blunder for various assessors is determined. The current methods all need in some regard assessing a boundary of some accepted arrangement. In this way, an elective methodology is proposed. The elective methodology is to gauge the restrictive thickness of the irregular variable included. The methodology proposed in this theory includes assessing the (discretized) restrictive thickness utilizing a Markovian definition when two arbitrary factors are genuinely needy, knowing the estimation of one of them allows us to improve gauge of the estimation of the other one. The restrictive thickness is assessed as the proportion of the two dimensional joint thickness to the one-dimensional thickness of irregular variable at whatever point the later is positive. Markov models are utilized in the issues of settling on an arrangement of choices and issue that have an innate transience that comprises of an interaction that unfurls on schedule on schedule. In the nonstop time Markov chain models the time stretches between two successive changes may likewise be a ceaseless irregular variable. The Markovian methodology is especially basic and quick for practically all classes of classes of issues requiring the assessment of contingent densities.

• Fashion & Textile Research Journal
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• v.14 no.3
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• pp.430-437
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• 2012

This study analyzed the sensibility of eco-friendly fabrics for college students and investigated their attitude on environmental problems, trust reliability onto eco-apparel products, and their purchase state. We tested 6 eco-friendly fabrics (recycled polyester, organic cotton, green tea, charcoal, bamboo, and nettle) through a survey using the Likert scale of 12 polar sensibility words. Most fabrics showed feelings that were smooth, natural, female, and country these were followed by fashion, cheap, functional, sustainable, warm, and vintage. In addition, nettle fabric showed 'rough' feeling, and recycled polyester fabric showed an 'artificial' feeling. Correspondence analysis showed the distance and direction between fabric types and sensibility words with a 2D diagram where the X axis was named with 'Soft <-> Hard' and Y axis was with 'Environmental <-> Manmade' to represent the relationship between fabric types and the sensibility words. According to the results of the multiple regression analysis, the cognition level of the consumer for environmental problems was found to be the most influential variable on the loyalty purchase of eco-friendly products; however, the trust reliability level of consumer onto eco-friendly apparel products was found to be the most influential variable on the conditional purchase of eco-friendly apparel products.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.72-80
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• 1998

A method is proposed for directional vector quantization using the wavelet packets. After partitioning the wavelet packet coefficients into 9 edges according to the corresponding directions, it encodes and transmits locally dominant edges. The directions of the edges are encoded with a variable length coding and conditional switching of codebooks, while the contents of them with the vector quantization followed by the variable length index coding. The proposed algorithm is superior to various conventional image coding algorithms in the sense of PSNR, which is relatively more significant at very low bit rate such as 0.1~0.3 bpp. As the proposed algorithm preserves the edges which is the most important for the human visual system, it also provides the reconstructed images of good subjective quality even at very low bit rate.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.99-100
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• 2022

As the danger of exposure to the asbestos has been revealed, the importance of demolition asbestos in existing buildings has been raised. Extensive body of study has been conducted to evaluate the risk of demolition asbestos, but there were confined types of variables caused by not reflecting categorical information and limitations in collecting quantitative information. Thus, this study aims to derive a model that predicts the risk in workplace of demolition asbestos by collecting categorical and continuous variables. For this purpose, categorical and continuous variables were collected from asbestos demolition reports, and the risk assessment score was set as the dependent variable. In this study, the influence of each variable was identified using logistic regression, and the risk prediction model methodologies were compared through decision tree regression and artificial neural network. As a result, a conditional risk prediction model was derived to evaluate the risk of demolition asbestos, and this model is expected to be used to ensure the safety of asbestos demolition workers.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.123-130
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• 2003

The estimation of key soil properties and subsequent quantitative assessment of the associated uncertainties has always been an important issue in geotechnical engineering. It is well recognized that soil properties vary spatially as a result of depositional and post-depositional processes. The stochastic nature of spatially varying soil properties can be treated as a random field. A practical statistical approach that can be used to systematically model various sources of uncertainty is presented in the context of reliability analysis of slope stability Newly developed expressions for probabilistic characterization of soil properties incorporate sampling and measurement errors, as well as spatial variability and its reduced variance due to spatial averaging. Reliability analyses of the probability of slope failure using the different statistical representations of soil properties show that the incorporation of spatial correlation and conditional simulation leads to significantly lower probability of failure than obtained using simple random variable approach.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.550-555
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• 2002

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller or the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed for a hierarchical control structure consisting of basic level and high level that modify control rules.

• IE interfaces
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• v.15 no.4
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• pp.426-431
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• 2002

In many cases, the result of a road traffic accident can be described with more than one response variables. Nonetheless, most of the existing road accident data analysis deal with only one response variable and try to explain why it occurs. In this paper, we train association rules for a set of more than two response variables conditional on personal, environmental and vehicular/behavioral aspects of accident. Association rules are derived at 8% support and 70% confidence from the 1996 data of three police stations in Korea. We expect that these rules can contribute to effective safety practice in Korea.

• The Journal of Asian Finance, Economics and Business
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• v.2 no.3
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• pp.17-22
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• 2015

This paper examines the effect of impulsiveness of euro on Indian stock market. In order to examine the problem, we select rupee-euro exchange rates and S&P CNX NIFTY and BSE30 SENSEX to represent stock price. We select euro as it considered as second most widely used currency at the international level after dollar. The data are collected a daily basis over a period of 3-Apr-2007 to 30-Mar-2012. The statistical and time series properties of each and every variable have examined using the conventional unit root such as ADF and PP test. Adopting a generalized autoregressive conditional heteroskedasticity (GARCH) and exponential GARCH (EGARCH) model, the study suggests a negative relationship between exchange rate and stock prices in India. Even though India is a major trade partner of European Union, the study couldn't find any significant statistical effect of fluctuations in Euro-rupee exchange rates on stock prices. The study also reveals that shocks to exchange rate have symmetric effect on stock prices and exchange rate fluctuations have permanent effects on stock price volatility in India.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.523-532
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• 1999

Generalized linear models have various applications for data arising from many kinds of statistical studies. Although the response variable is generally assumed to be generated from a wide class of probability distributions we focus on count data that are most often analyzed using binomial models for proportions or poisson models for rates. The methods and results presented here also apply to many other categorical data models in general due to the relationship between multinomial and poisson sampling. The novelty of the approach suggested here is that all conditional distribution s can be specified directly so that staraightforward Gibbs sampling is possible. The prior distribution consists of two stages. We rely on a normal nonconjugate prior at the first stage and a vague prior for hyperparameters at the second stage. The methods are demonstrated with an illustrative example using data collected by Rosenkranz and raftery(1994) concerning the number of hospital admissions due to back pain in Washington state.