• Speech Sciences
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• v.8 no.4
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• pp.17-33
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• 2001

In this paper, we implement the large variable vocabulary speech recognition system, which is characterized by no additional pre-training process and no limitation of recognized word list. We have designed the system in order to achieve the high recognition rate using the decision tree based state tying algorithm and in order to reduce the processing time using the gaussian selection based variable flooring algorithm, the limitation algorithm of the number of nodes and ENNS algorithm. The gaussian selection based variable flooring algorithm shows that it can reduce the total processing time by more than half of the recognition time, but it brings about the reduction of recognition rate. In other words, there is a trade off between the recognition rate and the processing time. The limitation algorithm of the number of nodes shows the best performance when the number of gaussian mixtures is a three. Both of the off-line and on-line experiments show the same performance. In our experiments, there are some differences of the recognition rate and the average recognition time according to the distinction of genders, speakers, and the number of vocabulary.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.18-21
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• 2003

We propose some properties of fuzzy conditional expectation of hybrid number the addition of fuzzy number and random variable using Cartesian product distance for ${\alpha}$-level sets.

• Korea Journal of Hospital Management
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• v.13 no.4
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• pp.1-26
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• 2008

This study examines the statistical relationship between medical specialists and managerial performance, using regression analysis with the number of medical specialists per 100 beds as the independent variable and the managerial performance index as the dependent variable. Managerial performance index incorporated the number of out-patients per specialist, the number of in-patients per specialist, the volume of revenue per specialist, the number of beds per specialist, and the average length of stay. To compare different groups of hospitals, dummy variable was applied to five groups of hospitals according to size: 100-299 beds, 300-599 beds, 600-899 beds, 900-1199 beds, and more than 1200 beds. The data consisted of 181 general hospitals with more than 100 beds, which included 28 public hospitals, 73 corporate hospitals, 64 university hospitals and 16 private hospitals. Of those, 87 hospitals were located in big cities and 94 hospitals in medium to small cities. This study used hospitals from the Korean Hospital Association, and data published in 2004. The collected data sample was analyzed using the SPSSWIN 12.0 version, and the study hypothesis was tested using regression analysis. The findings of this study are summarized as follows: Hypothesis 1 predicting a negative effect of the number of medical specialists on the number of out-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in all the hospital groups larger than the group of 100-299 beds. Hypothesis 2 predicting a negative effect of the number of medical specialists on the number of in-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds when compared to the group of 100-299 beds. Hypothesis 3 predicting a negative effect of the number of medical specialists on the volume of revenue per specialist was not supported. However, the analysis of dummy variable showed that the volume of revenue per specialist increased in the hospital groups of 600-899 beds, 900-1199 beds, and over 1200 beds, when compared to the group of 100-299 beds. Hypothesis 4 predicting a negative effect of the number of medical specialists on the average length of stay was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds, when compared to the group of 100-299 beds. Results of this study show that the number of the medical specialists per 100 beds is an important factor in hospital managerial performance. Most hospitals have tried to retain as many medical specialists as possible to keep the number of patients stable, to ensure adequate revenue, and to maintain efficient managerial performance. Especially, the big hospitals with greater number of beds and medical specialists have shown greater revenue per medical specialist despite the smaller number of patients per medical specialist. Findings of this study explains why hospitals in Korea are getting bigger.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.200-205
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• 2000

An economic process monitoring procedure is presented using a surrogate variable for the case where performance variable is dichotomous. Every item is inspected with a surrogate variable and determined whether it should be accepted or rejected. When an item is rejected, the previous number of consecutively accepted items is compared with a predetermined number r to decide whether there is a shift in fraction nonconforming or not. The conditional distribution of the surrogate variable given the performance variable is assumed to be normal. A cost model is constructed which includes costs of inspection, misclassification, illegal signal, undetected out-of-control state, and correction. Methods of finding the optimum number r and screening limit are provided. Numerical studies on the effects of cost coefficients are also performed.

• Korea Journal of Hospital Management
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• v.11 no.3
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• pp.73-93
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• 2006

This study aims at providing necessary informations for management decision-making to the hospital manager, such as ratios of fixed and variable cost to total operating expense, and variable cost ratio to operating revenues, and determinant factors affecting cost behavior. A study model and related hypotheses were established, data were collected from 41 private university hospitals for the 6years from 1998 to 2003, and regression analyses were performed to test the hypotheses. The results of the analyses and conclusions are as follows; First, labor cost and administration cost within the same number of beds have not only fixed quality of the cost, but variable quality of that. Also, the ratio of the variable costs to operating revenue of the metropolitan was estimated 76.9% and that of other area hospitals was 80.1%. Second, the major factors affecting the increase rate of the operating expense were the increase rates of the number of inpatients, the number of employee, and the number of hospital operating bed. This result implies that maintaining a optimal hospital bed size and efficient operation of the beds are important strategic factors of hospital management.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.471-483
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• 2012

One of the most important problems in cluster analysis is the selection of variables that truly define cluster structure, while eliminating noisy variables that mask such structure. Brusco and Cradit (2001) present VS-KM(variable-selection heuristic for K-means clustering) procedure for selecting true variables for K-means clustering based on adjusted Rand index. This procedure starts with the fixed number of clusters in K-means and adds variables sequentially based on an adjusted Rand index. This paper presents an updated procedure combining the VS-KM with the automated K-means procedure provided by Kim (2009). This automated variable selection procedure for K-means clustering calculates the cluster number and initial cluster center whenever new variable is added and adds a variable based on adjusted Rand index. Simulation result indicates that the proposed procedure is very effective at selecting true variables and at eliminating noisy variables. Implemented program using R can be obtained on the website "http://faculty.knou.ac.kr/sskim/nvarkm.r and vnvarkm.r".

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.7
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• pp.706-717
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• 1991

In order to remove the assumption of full state availability which is one of the major difficulties with the practical realization of variable structure control systems,a new switching function with a dynamic structure is proposed. And the control performances of the output feedback variable structure control systems with the dynamic switching function are evaluated through simulation studies. The proposed dynamic switching function is driven by small number of measured output and input variables while conventional static switching function requires full state information. Therefore, the proposition of the dynamic swiching function makes practical implementation of output feedback variable structure control scheme possible for the systems with unmeasurable state variables, high order systems and large scale systems that the conventional variable structure control schemes with static switching function cannot be applied. In the variable structure control systems with the dynamic switching function, desired control performance can be guaranteed by proper choice of design parameters such as poles of switching function dynamic equation and switching control gains even though small number of measured output and input variables are provided as shown in simulation resuls.

• Industrial Engineering and Management Systems
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• v.14 no.2
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• pp.210-219
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• 2015

A classification task requires an exponentially growing amount of computation time and number of observations as the variable dimensionality increases. Thus, reducing the dimensionality of the data is essential when the number of observations is limited. Often, dimensionality reduction or feature selection leads to better classification performance than using the whole number of features. In this paper, we study the possibility of utilizing the Markov blanket discovery algorithm as a new feature selection method. The Markov blanket of a target variable is the minimal variable set for explaining the target variable on the basis of conditional independence of all the variables to be connected in a Bayesian network. We apply several Markov blanket discovery algorithms to some high-dimensional categorical and continuous data sets, and compare their classification performance with other feature selection methods using well-known classifiers.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.232-239
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• 1994

This paper presents an effective way of improving fuel consumption for a variable displacement engine. The improvement of fuel consumption can be accomplished by means of deactivating inlet and exhaust valves, reducing the number of effective cylinders of a four-cylinder gasoline engine that is mounted on a domestic compact automobile.

• Journal of the Korean Institute of Navigation
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• v.25 no.4
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• pp.461-469
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• 2001

The purpose of this paper is the optimum modification of dynamic characteristics of stiffened plate structure including the number of stiffener. This paper shows the optimum structural modification method by dynamic sensitivity analysis and quasi-least squares method and considers it's validity. In the method of the optimization, finite element method, sensitivity analysis and optimum structural modification method are used. The change of natural frequency and total weight are made to be an objective function. Thickness of plate, the number of stiffener and cross section moment of stiffener become a design variable. The dynamic characteristics of stiffened plate structure is analyzed using finite element method. Next, rate of change of dynamic characteristics by the change of design variable is calculated using the sensitivity analysis. Then, amount of change of design variable is calculated using optimum structural modification method. It is shown that the results are effective in the optimum modification for dynamic characteristics of the stiffened plate structure including the number of stiffener.