• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.833-841
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• 1998

The ann of this study is 10 propose all eff'tcient mclhod for partition of multi-dimensIOnal feature space into pattern subspace for automated generation of fuzzy rule. The suggested mclhod predicates on sequential subdivision of the fuzzy subspacc. and the size of construc1cd pattern space is variable. Under this procedure, n-dimensional pattern space, after considering the distributional characteristic patterns, is partitioned into two different pattern subspaces. From the two subspaces, the pattern space for further subdivision is chosen; then, this subdivision procedure recursively repeats itself until the stopping condition is fulfilled. The result of this study is applied to 2, 4, 7 band of satellite Landsat TM and satisfac10ry result is acquired.

• The Korean Journal of Nuclear Medicine
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• v.32 no.1
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• pp.32-49
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• 1998

For estimation of regional myocardial blood flow with O-15 water PET, a few modifications considering partial volume effect based on single compartment model have been proposed. In this study, we attempted to quantify the degree of heterogeneity and to show the effect of tissue flow heterogeneity on partition coefficient(${\lambda}$) and to find the relation between perfusable tissue index(PTI) and ${\lambda}$ by computer simulation using two modified models. We simulated tissue curves for the regions with homogeneous and heterogeneous blood flow over a various flow range(0.2-4.0ml/g/min). Simulated heterogeneous tissue composed of 4 subregions of the same or different size of block which have different homogeneous flow and different degree of slope of distribution of blood flow. We measured the index representing heterogeneity of distribution of blood flow for each heterogeneous tissue by the constitution heterogeneity(CH). For model I, we assumed that tissue recovery coefficient ($F_{MME}$) was the product of partial volume effect($F_{MMF}$) and PTI. Using model I, PTI, flow, and $F_{MM}$ were estimated. For model II, we assumed that partition coefficient was another variable which could represent tissue characteristics of heterogeneity of flow distribution. Using model II, PTI, flow and ${\lambda}$ were estimated. For the simulated tissue with homogeneous flow, both models gave exactly the same estimates, of three parameters. For the simulated tissue with heterogeneous flow distribution, in model I, flow and $F_{MM}$ were correctly estimated as CH was increased moderately. In model II, flow and ${\lambda}$ were decreased curvi-linearly as CH was increased. The degree of underestimation of ${\lambda}$ obtained using model II, was correlated with CH. The degree of underestimation of flow was dependent on the degree of underestimation of ${\lambda}$. PTI was somewhat overestimated and did not change according to CH. We conclude that estimated ${\lambda}$ reflect the degree of tissue heterogeneity of flow distribution. We could use the degree of underestimation of ${\lambda}$ to find the characteristic heterogeneity of tissue flow and use ${\lambda}$ to recover the underestimated flow.

• Journal of Environmental Health Sciences
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• v.25 no.3
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• pp.36-43
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• 1999

The present study was performed to investigate biodegradation rate of dichlorvos and methidathion. In the biodegradation test of two pesticides by the modified river die-away method from June 17 to August 22, 1998, the biodegradation rate constants and half-life were determined in Nakdong(A) and Kumho River(B). Biodegradation rate of dichlorvos was 4.51% in A sampling point, 6.88% in B sampling point after 7 days. Biodegradation rate constants and half-life of dichlorvos were 0.0066 and 105 days in A sampling point, 0.0102 and 67.9 days in B sampling point, respectively. Biodegradation rate of methidathion was 23% in A sampling point, 36% in B sampling point after 7 days. Biodegradation rate constants and half-life of methidathion were 0.0377 and 18.4 days in A sampling point, 0.0641 and 10.8 days in B sampling point, respectively. Biodegradation rate of methidathion was faster than that of dichlorvos. This suggested that the difference in biodegradation of pesticides was due to difference in the water quality and standard plate counts in the Nackdong and Kumho Rivers. The result of correlation analysis between biodegradation rate constants of the pesticides and water quality(DO, BOD, SS, ABS, NH$_3$-N, and NO$_3$-N) showed significant correlation with BOD, SS and NH$_3$-N at the 5% significant level. A significant linear equation was obtained from regression analysis at the 5% significant level, whereas, dependent variables were BOD, SS and NH$_3$-N, and the biodegradation rate constant was independent variable. It is suggested that dichlorvos will be mainly degraded by hydrolysis, and for methidathion was both hydrolysis and biodegradation. A significant QSAR equation was obtained from regression analysis at the 10% significant level, whereas, dependent variable is biodegradation rate constants of BPMC, chlorothalonil, dichlorvos and methidathion, vapor pressures, partition coefficients and water solubilities of the pesticides are independent variables. Also, a significant linear equation was obtained from regression analysis at the 1% significant level, whereas, dependent variable is biodegradation rate constants of BPMC, chlorothalonil, dichlorvos and methidathion, hydrolysis rate constants of the pesticides are independent variables. It is suggested that the pesticides will be degraded by main degradation factor when the pesticides was affected both hydrolysis and biodegradation.

• Korean Institute of Interior Design Journal
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• v.20 no.1
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• pp.154-164
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• 2011

The purpose of this study is to identify more types of residents in medium-sized apartments in Seoul by lifestyle that has been used as a variable of space planning and to investigate and present bathroom design appropriate for characteristics of each resident type. The article examines the general characteristics, lifestyle types, and preference for the bathroom design. A total of 642 samples, acquired via internet survey, were analyzed with the statistical computer program SPSS PC+ window version 16.0. The conclusion of the article are as follows: 1) The lifestyle of users living in medium-sized apartments are categorized into 4 types: trend seeking, aesthetic seeking, family seeking, information seeking types. 2) The preference for the bathroom design of trend seeking type, the toilet is a bidet-builtin type and the washstand is a semi-counter type and the bathtub is a spa type and the shower booth is a bathtub-extending type. The storage closet is a upper-fixed type with two sides, the finishing materials are tiles and PVC monorium, and light built in a wall. 3) The preference for the bathroom design of aesthetic seeking type, the toilet is a bidet-builtin type and the washstand is a semi-counter type and the bathtub is a whirlpool type and the shower booth is a steam-sauna type. The storage closet is a upper-fixed with one side and opened closet, the finishing materials are tiles. 4) The preference for the bathroom design of family seeking type, the toilet is a bidet-builtin type and the washstand is a stand type and the bathtub is a reclamation type and the shower booth is a partition type. The storage closet is a upper-fixed with three sides. 5) The preference for the bathroom design of information seeking type, the toilet is a bidet-builtin type and the washstand is a semi-counter and the bathtub is a spa type and the shower booth is a partition type. The storage closet is a upper-fixed type with two sides. The results of this study may be used as basic data in planning bathroom design for housing supply for housing suppliers, and used as significant information for residents to identify their own types that can be referred when they select apartments to live in.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.627-630
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• 2014

The latest video coding standard, high efficiency video coding (HEVC) achieves high coding efficiency by employing a quadtree-based coding unit (CU) block partitioning structure which allows recursive splitting into four equally sized blocks. At each depth level, each CU is partitioned into variable sized blocks of prediction units (PUs). However, the determination of the best CU partition for each coding tree unit (CTU) and the best PU mode for each CU causes a dramatic increase in computational complexity. To reduce such computational complexity, we propose a fast PU decision algorithm that early terminates PU search. The proposed method skips the computation of R-D cost for certain PU modes in the current CU based on the best mode and the rate-distortion (RD) cost of the upper depth CU. Experimental results show that the proposed method reduces the computational complexity of HM12.0 to 18.1% with only 0.2% increases in BD-rate.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.277-283
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• 2014

Fuzzy modeling is generally using the given data and the fuzzy rules are established by the input variables and the space division by selecting the input variable and dividing the input space for each input variables. The premise part of the fuzzy rule is presented by selection of the input variables, the number of space division and membership functions and in this paper the consequent part of the fuzzy rule is identified by polynomial functions in the form of linear inference and modified quadratic. Parameter identification in the premise part devides input space Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. In this paper, membership function of the premise part is dividing input space by using trapezoid-type membership function and by using gas furnace process which is widely used in nonlinear process we evaluate the performance.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.39-57
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• 2001

Categorical data has sometimes misclassification errors. If this data will be analyzed, then estimated cell probabilities could be biased and the standard Pearson X2 tests may have inflated true type I error rates. On the other hand, if we regard wellclassified data with misclassified one, then we might spend lots of cost and time on adjustment of misclassification. It is a necessary and important step to ask whether categorical data is misclassified before analyzing data. In this paper, when data is misclassified at one of two variables for two-dimensional contingency table and marginal sums of a well-classified variable are fixed. We explore to partition marginal sums into each cells via the concepts of Bound and Collapse of Sebastiani and Ramoni (1997). The double sampling scheme (Tenenbein 1970) is used to obtain informations of misclassification. We propose test statistics in order to solve misclassification problems and examine behaviors of the statistics by simulation studies.

• Journal of Broadcast Engineering
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• v.14 no.1
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• pp.28-35
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• 2009

H.264/AVC, a recently developed video compression standard, is used for various applications because of its high coding efficiency. Variable block mode plays important role in the high coding efficiency of H.264/AVC but involves significant computations to select the optimal mode. In this paper, a fast mode decision method for H.264/AVC P slices is presented. To reduce computations for mode decision, the proposed mode decision method skips the mode decision processes for small partition modes using distortions of SKIP mode and intra16x16 mode. The experimental results show that the proposed method can reduce encoding time up to 66.41% while maintaining compression efficiency.

• Journal of Korea Water Resources Association
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• v.37 no.6
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• pp.449-460
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• 2004

The purpose of this study is to test the applicability of neuro-fuzzy system for monthly dam inflow forecasts by using weather forecasting information. The neuro-fuzzy algorithm adopted in this study is the ANFIS(Adaptive neuro-fuzzy Inference System) in which neural network theory is combined with fuzzy theory. The ANFIS model can experience the difficulties in selection of a control rule by a space partition because the number of control value increases rapidly as the number of fuzzy variable increases. In an effort to overcome this drawback, this study used the subtractive clustering which is one of fuzzy clustering methods. Also, this study proposed a method for converting qualitative weather forecasting information to quantitative one. ANFIS for monthly dam inflow forecasts was tested in cases of with or without weather forecasting information. It can be seen that the model performances obtained from the use of past observed data and future weather forecasting information are much better than those from past observed data only.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.7-13
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• 2002

Almost applications using fuzzy theory are based on the fuzzy inference. However fuzzy inference needs much time in calculation process for the fuzzy system with many input variables or many fuzzy labels defined on each variable. Inference time is dependent on the number of arithmetic Product in computation Process. Especially, the inference time is a primary constraint to fuzzy control applications using microprocessor or PC-based controller. In this paper, a simple fast fuzzy inference algorithm(FFIA), without loss of information, was proposed to reduce the inference time based on the fuzzy system with triangular membership functions in antecedent part of fuzzy rule. The proposed algorithm was induced by using partition of input state space and simple geometrical analysis. By using this scheme, we can take the same effect of the fuzzy rule reduction.