• Journal of computational fluids engineering
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• v.5 no.2
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• pp.20-27
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• 2000

An unstructured implicit Euler solver is parallelized on a Cray T3E. Spatial discretization is accomplished by a cell-centered finite volume formulation using an upwind flux differencing. Time is advanced by the Gauss-Seidel implicit scheme. Domain decomposition is accomplished by using the k-way n-partitioning method developed by Karypis. In order to analyze the parallel performance of the solver, flows over a 2-D NACA 0012 airfoil and 3-D F-5 wing were investigated.

• Journal of the Korean Home Economics Association
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• v.46 no.9
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• pp.33-45
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• 2008

The purpose of this study was to investigate the tendency and characteristics of behavior problems in preschool children. The aim was to acquire basic information that could be used in diagnosis and intervention strategies. The target of this study were 823 preschoolers, the reporting on which was conducted through the responses of 81 teachers. Analysis consisted of partitioning behavioral problems by demographic variables in order to ascertain differences by age, sex, and cut-off score of the high risk group. Overall results indicate significant differences in behavioral problems according to socio-demographic variable. The conclusions of this study offer a foundation for diagnosis, intervention, and therapy for preschoolers with problem behaviors.

• 한국전산유체공학회:학술대회논문집
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• 1999.11a
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• pp.193-200
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• 1999

An unstructured implicit Euler solver is parallelized on a Cray T3E. Spatial discretization is accomplished by a cell-centered finite volume formulation using an unpwind flux differencing. Time is advanced by the Gauss-Seidel implicit scheme. Domain decomposition is accomplished by using the k-way N-partitioning method developed by Karypis. In order to analyze the parallel performance of the solver, flows over a 2-D NACA 0012 airfoil and a 3-D F-5 wing were investigated.

• Journal of Computing Science and Engineering
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• v.2 no.4
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• pp.340-356
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• 2008

The cognitive constraints of the human mind must drive the decisions in architecture and methodology design in order that the systems we build are comprehensible. This paper presents a methodology for the design of time-triggered embedded systems that leads to understandable artifacts. We lift the design process to a higher level of abstractionto the level of computational components that interact solely by the exchange of messages. The time-triggered architecture makes it possible to specify the temporal properties of component interfaces precisely and provides temporally predictable message communication, such that the precise behavior of a large design can be studied in the early phases of a design on the basis of the component interface specifications. This paper shows how the cognitive simplification strategies of abstraction, partitioning and segmentation are supported by the time-triggered architecture and its associated design methodology to construct evolvable embedded systems that can be readily understood and modified.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1563-1570
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• 1999

In this paper, we proposed the FPA(Fixed Partition Averaging) algorithm in order to improve the storage requirement and classification time of Memory Based Reasoning method. The proposed method enables us to use the storage more efficiently by extracting representatives out of training patterns. After partitioning the pattern space into a fixed number of equally-sized hyperrectangles, it averages patterns in each hyperrectangle to extract a representative. Also we have used the mutual information between the features and classes as weights for features to improve the classification performance.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.366-366
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• 2000

In this paper, an adaptive neuro-fuzzy filter using the conditional fuzzy c-means(CFCM) methods is proposed. Usualy, the number of fuzzy rules exponentially increases by applying the grid partitioning of the input space, in conventional adaptive neuro-fuzzy inference system(ANFIS) approaches. In order to solve this problem, CFCM method is adopted to render the clusters which represent the given input and output data. Parameter identification is performed by hybrid learning using back-propagation algorithm and total least square(TLS) method. Finally, we applied the proposed method to the nonlinear channel equalization problem and obtained a better performance than previous works.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7C
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• pp.592-600
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• 2012

In this paper, we proposed that decentralized frequency allocation scheme(DFAS) without network entry procedure between relays in mobile relay system. Frequency Indicator(FI) signal which is the reference signal of frequency division of each relay and Energy Detection(ED) region are defined. In addition, the mobile connected to the relay transmits the FI signal to neighbor relays in order to facilitate communication between relays. Finally, by using this scheme, the cell throughput improvement is confirmed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.6
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• pp.36-41
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• 2002

We consider the Fuzzy clustering which is devised for partitioning a set of objects into a certain number of groups by assigning the membership probabilities to each object. The researches carried out in this field before show that the Fuzzy clustering concept is involved so much that for a certain set of data, the main purpose of the clustering cannot be attained as desired. Thus we propose a new objective function, named as Fuzzy-Entroppy Function in order to satisfy the main motivation of the clustering which is classifying the data clearly. Also we suggest Mean Field Annealing Algorithm as an optimization algorithm rather than the ISODATA used traditionally in this field since the objective function is changed. we show the Mean Field Annealing Algorithm works pretty well not only for the new objective function but also for the classical Fuzzy objective function by indicating that the local minimum problem resulted from the ISODATA can be improved.

• Management & Information Systems Review
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• v.14
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• pp.51-65
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• 2004

We consider the Fuzzy clustering which is devised for partitioning a set of objects into a certain number of groups by assigning the membership probabilities to each object. The researches carried out in this field before show that the Fuzzy clustering concept is involved so much that for a certain set of data, the main purpose of the clustering cannot be attained as desired. Thus we Propose a new objective function, named as Fuzzy-Entroppy Function in order to satisfy the main motivation of the clustering which is classifying the data clearly. Also we suggest Mean Field Annealing Algorithm as an optimization algorithm rather than the ISODATA used traditionally in this field since the objective function is changed. We show the Mean Field Annealing Algorithm works pretty well not only for the new objective function but also for the classical Fuzzy objective function by indicating that the local minimum problem resulted from the ISODATA can be improved.

• Transactions of the Korean hydrogen and new energy society
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• v.9 no.3
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• pp.119-125
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• 1998

The modified statistical-mechanical theory for dense fluid mixtures of rigid spheres has been applied to rigid sphere fluids in the nonoverlapping pore model. The resulting expressions for the partition coefficient and diffusivity illustrate the influence of steric hindrance on the thermodynamic and transport properties in such systems. The open membrane model without the size-exclusion and shielding effects shows considerable overestimation of the diffusion flux when the effective mean pore radii of the order of $20{\AA}$ or less are involved. Theoretical predictions investigated here were also compared with experimental data for hydrogen gases in inorganic porous membranes and it was observed a qualitative agreement in the low pressure limit.