• Korean Institute of Interior Design Journal
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• v.23 no.3
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• pp.173-180
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• 2014

Dwelling connotes characteristics like social and cultural and technical climatic conditions, lifestyles and demands of regions, and especially, apartment, as one of dwelling types, shows various aspects of modern society. With the economic development centering on large cities, apartments have been established as universal housing forms in Seoul and Shanghai. The deepening of economic development in cities has increased small households consisting of one or two persons by affecting the population and household structure, and they've become information consumer groups. This has also influenced the size of apartment and increased the demand for small-sized housing. If the floor area is small, it is possible to use space widely according to the plan composition, so there is a need for floor planning to understand natural environment, physical environment and residents.This study compared and analyzed plan compositions of small-sized apartments which have been parceled out for the recent three years in Seoul and Shanghai. This study aims to understand housing cultures and users in the two countries depending on natural environments, living habits and spatial functions by analyzing common points and differences of public spaces like living room, dining room and kitchen, and private spaces like bedroom which have absolute effects on room arrangement and traffic line. The study results are as follows. From the perspective of natural environments, in Seoul, two-sided open cross-ventilation structure where is favorable to lighting and ventilation, occupied the biggest proportion of public space, while in Shanghai, most public spaces had lighting and ventilation structures through windows in each room. In Seoul, 3R type occupied the largest proportion of private space(87.7%), and privacy was maintained and space scale was adjusted using spaces with diverse functions such as bathroom in the couple bedroom, dress room and powder room and variable walls. But 2R type occupied the largest proportion of private space(60.2%) in Shanghai, and they emphasized private space and privacy of each room depending on major living habits. In conclusion, this study for comparing and analyzing common points and differences of small-sized apartment plan compositions in Seoul and Shanghai will provide proper guidelines for small-sized apartments to be built in Seoul and Shanghai in the future, if strong points and weak points of plan compositions in the two countries will be additionally analyzed and remedied.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.4
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• pp.227-238
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• 2008

In this paper we extend primal-dual interior point algorithm for linear optimization (LO) problems to $P_*({\kappa})$ linear complementarity problems(LCPs) ([1]). We define proximity functions and search directions based on kernel functions, ${\psi}(t)=\frac{t^{p+1}-1}{p+1}-{\log}\;t$, $p{\in}$[0, 1], which is a generalized form of the one in [16]. It is the first to use this class of kernel functions in the complexity analysis of interior point method(IPM) for $P_*({\kappa})$ LCPs. We show that if a strictly feasible starting point is available, then new large-update primal-dual interior point algorithms for $P_*({\kappa})$ LCPs have $O((1+2{\kappa})nlog{\frac{n}{\varepsilon}})$ complexity which is similar to the one in [16]. For small-update methods, we have $O((1+2{\kappa})\sqrt{n}{\log}{\frac{n}{\varepsilon}})$ which is the best known complexity so far.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.425-429
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• 2014

The visibility range is defined from where one can see. And it can be changed by illuminance, the character size, and eyesight and so on. In this paper the visibility range of 120 students is measured for 4 character sizes and 3 illuminations in a classroom. In order to forecast the visibility range of unmeasured data, using least square approximation theory, functions whose independent variable is illuminance and whose dependent variable is the visibility range is proposed. Because the visibility range is invariant according to illuminance, common logarithmic functions for 4 character sizes are used. The small difference between the postulated functions and the measured data verifies the accuracy of the functions.

• BMB Reports
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• v.45 no.11
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• pp.612-622
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• 2012

Olfactory receptors (ORs) detect volatile chemicals that lead to the initial perception of smell in the brain. The olfactory receptor (OR) is the first protein that recognizes odorants in the olfactory signal pathway and it is present in over 1,000 genes in mice. It is also the largest member of the G protein-coupled receptors (GPCRs). Most ORs are extensively expressed in the nasal olfactory epithelium where they perform the appropriate physiological functions that fit their location. However, recent whole-genome sequencing shows that ORs have been found outside of the olfactory system, suggesting that ORs may play an important role in the ectopic expression of non-chemosensory tissues. The ectopic expressions of ORs and their physiological functions have attracted more attention recently since MOR23 and testicular hOR17-4 have been found to be involved in skeletal muscle development, regeneration, and human sperm chemotaxis, respectively. When identifying additional expression profiles and functions of ORs in non-olfactory tissues, there are limitations posed by the small number of antibodies available for similar OR genes. This review presents the results of a research series that identifies ectopic expressions and functions of ORs in non-chemosensory tissues to provide insight into future research directions.

• The Transactions of the Korea Information Processing Society
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• v.4 no.5
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• pp.1182-1195
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• 1997

When we present some information, we can use application programs through multinedia-based authoring tools. Especially.many programers proposed to improve its intergration time and reduce programming speed and easy to use. However, multimedia based authoring tools have not all of programming methodolgies and do not supply special functions from user's request. Therefore, we have to apply effective functions through high-level programming languages.In this paper, we propose to use small appkication prograns through linking methods, So we reduce overhead from memory loading In authoring tools, we can use MCI(media control interface) call functions for playback audio files.we development ATS(Auto Transition System) for several functions-close MCI call audio files, get object status, page-to page trancition.We evidently show that an optimal configuration of presentation obtained by ATS algorithm.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.565-572
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• 2001

Analyzing functions with small values of the product of position and frequency uncertainties have many advantages in image processing and data compression. Until now, this values has been computed based on the uncertainty principle, but the computed frequency uncertainty is not practical the human visual filters which have on-zero peak response frequencies. A new metric for the frequency uncertainty is used to calculate a deviation about the frequency which has maximum response. The joint effective widths for various functions are derived. As the result of analysis, the joint uncertainty for many functions converges to 0.5 as the joint parameter increases. Furthermore. Gabor cosine function shows an excellent performance among the mentioned functions.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.599-604
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• 2005

This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer with minimized number of feature in put using the neural network with weighted fuzzy membership functions (NEWFM) and the non-overlap area distribution measurement method. NEWFM is capable of self-adapting weighted membership functions from the given the Wisconsin breast cancer clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from n set of enhanced bounded sums of n set of small, medium, and large weighted fuzzy membership functions. Then, the non-overlap area distribution measurement method is applied to select important features by deleting less important features. Two sets of prediction rules extracted from NEWFM using the selected 4 input features out of 9 features outperform to the current published results in number of set of rules, number of input features, and accuracy with 99.71%.

• Journal of the Ergonomics Society of Korea
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• v.12 no.2
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• pp.45-62
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• 1993

This study was aimed to obtain the available information for the clothing constru- ction according to the traits of the cerebral palsied. For this purpose, their abilities of eleven methods seven of fastening performance and seven finger functions were tested and their correlationships were clarified. The results are as follows : 1. The length of time needed to perform each fastening method in descending order is as follows : small button > small snap > culumn button > large button > middle button > large snap > separating zipper > velcro. As the spastic has better function than the athetoid in the performance of all fastening methods, there was a significant difference between the types of handicap and between the handi- capped and the normal, except for velcro fastening style in which there was no significant differ- ence between the types of handicap. 2. In finger functions of the cerebral palsied, according to the types of handicap there was no significant difference among grip, palm fixation and hands coordination, howefer there were significant differences among pulp pinching, lateral pinching, finger rolling and lifting control. As to the correlation between the ability of fastening performance and finger function, there was a high significant correlation between the length of time needed to perform each fastenting and finger function of hands co ordination, and that of finger rolling; and there was a significant correlation between the length of time and pulp pinching, and laternal pinching.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.2
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• pp.56-64
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• 1998

Multi-layered perceptrons that are a nonlinear neural network model, have been widely used for various applications mainly thanks to good function approximation capability for nonlinear fuctions. However, for digital hardware implementation of the multi-layere perceptrons, the quantization scheme using "look-up tables (LUTs)" is commonly employed to handle nonlinear signmoid activation functions in the neworks, and thus requires large amount of storage to prevent unacceptable quantization errors. This paper is concerned with a new effective methodology for digital hardware implementation of multi-layered perceptrons, and proposes a "piecewise affine approximation" method in which input domain is divided into (small number of) sub-intervals and nonlinear sigmoid function is linearly approximated within each sub-interval. Using the proposed method, we develop an expression and an error backpropagation type learning algorithm for a multi-layered perceptron, and compare the performance with the quantization method through Monte Carlo simulations on XOR problems. Simulation results show that, in terms of learning convergece, the proposed method with a small number of sub-intervals significantly outperforms the quantization method with a very large storage requirement. We expect from these results that the proposed method can be utilized in digital system implementation to significantly reduce the storage requirement, quantization error, and learning time of the quantization method.quantization method.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.709-720
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• 2017

In healthcare and medical research, many important variables have a measurement error such as body mass index and laboratory data. It is also not easy to collect samples of large size because of high cost and long time required to collect the target patient satisfied with inclusion and exclusion criteria. Beside, the demand for solving a complex scientific problem has highly increased so that a semiparametric regression approach could be of substantial value solving this problem. To address the issues of measurement error, small domain and a scientific complexity, we conduct a multivariable Bayesian smoothing under structural measurement error covariate in this article. Specifically we enhance our previous model by incorporating other useful auxiliary covariates free of measurement error. For the regression spline, we use a radial basis functions with fixed knots for the measurement error covariate. We organize a fully Bayesian approach to fit the model and estimate parameters using Markov chain Monte Carlo. Simulation results represent that the method performs well. We illustrate the results using a national survey data for application.