• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1496-1499
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• 2004

The paper persents an efficient method of extracting line segment in a grid map. The grid map is composed of 2-D grids that have both the occupancy and orientation probabilities based on the simplified Bayesian updating model. The probabilities and orientations of cells in the grid map are continuously updated while the robot explorers to their values. The line segments are, then, extracted from the clusters using Hough transform methods. The eng points of a line segment are evaluated from the cells in each cluster, which is simple and efficient comparing to existing methods. The proposed methods are illustrated by sets of experiments in an indoor environment.

• Journal of Environmental Science International
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• v.24 no.6
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• pp.807-817
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• 2015

In this study the urban atmospheric environment map in Busan was made and it consist of the atmospheric environment element map and the atmospheric environment analysis map. The atmospheric environment element map covered the topography, the urban climate, the air pollutant emission, ozone and PM10 concentrations in Busan and the atmospheric environment analysis map included the thermal environment and the wind flow by using WRF meteorological numerical simulation. The meteorological elements from 2007 to 2011 in Busan were used in this study. As a result, in the center of Busan and Buk-gu along to the Nakdong river was the temperature high. To analyze the air flow of Busan 3 clusters depending on the wind direction were extracted with the cluster analysis. The results of the analysis on the detailed wind field of each cluster showed that the weak ventilation could be happened locally at the specific meteorological condition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6B
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• pp.534-543
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• 2006

As the topology frequently varies, more cluster reconstructing is needed and also management overheads increase in the wireless ad hoc/sensor networks. In this paper, we propose a multi-hop clustering algorithm for wireless sensor network topology management using dynamic pre-clusterhead scheme to solve cluster reconstruction and load balancing problems. The proposed scheme uses weight map that is composed with power level and mobility, to choose pre-clusterhead and construct multi-hop cluster. A clusterhead has a weight map and threshold to hand over functions of clusterhead to pre-clusterhead. As a result of simulation, our algorithm can reduce overheads and provide more load balancing well. Moreover, our scheme can maintain the proper number of clusters and cluster members regardless of topology changes.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.42.1-42.1
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• 2014

A gravitational weak-lensing map provides a weighted "picture" of the projected surface mass density and is to be an important tool for identifying "mass-selected" clusters of galaxies. However, weak-lensing maps have a limitation due to the projection of large-sclae structure along the line-of-sight. Geller et al. (2010) and Kurtz et al. (2012) compared massive clusters identified in a dense redshift survey with significant weak-lensing map convergence peaks. Both assessments of the efficiency of weak-lensing map for cluster identification did not draw a general conclusion, because the sample is so small. Thus, we additionally perform deep imaging observations of fields in a dense galaxy redshift survey that contain galaxy clusters at z~0.2-0.5, using CFHT Megacam. Our study will provide an important opportunity to examine the efficiency and completeness of a weak-lensing selection, and further to improve the method of cluster identification in future weak-lensing surveys.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.9-13
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• 2014

The performance of large scale software applications has been automatically increasing for last few decades under the influence of Moore's law - the number of transistors on a microprocessor roughly doubled every eighteen months. However, on-chip transistors limitations and heating issues led to the emergence of multicore processors. The energy efficient ARM based System-on-Chip (SoC) processors are being considered for future high performance computing systems. In this paper, we present a case study of two widely used parallel programming models i.e. MPI and MapReduce on distributed memory cluster of ARM SoC development boards. The case study application, Black-Scholes option pricing equation, was parallelized and evaluated in terms of power consumption and throughput. The results show that the Hadoop implementation has low instantaneous power consumption that of MPI, but MPI outperforms Hadoop implementation by a factor of 1.46 in terms of total power consumption to execution time ratio.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.5 s.153
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• pp.699-710
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• 2006

The objective of this study was to identify the texture-related components of woven fabrics and to develop a multidimensional perceptual structure map to represent the tactile textures. Eighty subjects in clothing and tektite industries were selected for multivariate data on each fabric of 30 using the questionnaire with 9 pointed semantic differential scales of 20 texture-related adjectives. Data were analyzed by factor analysis, hierarchical cluster analysis, and multidimensional scaling(MDS) using SPSS statistical package. The results showed that the five factors were selected and composed of density/warmth-coolness, stiffness, extensibility, drapeability, and surface/slipperiness. As a result of hierarchical cluster analysis, 30 fabrics were grouped by four clusters; each cluster was named with density/warmth-coolness, surface/slipperiness, stiffness, and extensibility, respectively. By MDS, three dimensions of tactile texture were obtained and a 3-dimensional perceptual structure map was suggested. The three dimensions were named as surface/slipperiness, extensibility, and stiffness. We proposed a positioning perceptual map of fabrics related to texture naming system(TNS). To classify the textural features of the woven fabrics, hierarchical cluster analysis containing all the data variations, even though it includes the errors, may be more desirable than texture-related multidimensional data analysis based on factor loading values in respect of the effective variables reduction without losing the critical variations.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.42.6-42
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• 2002

Kohonen's self organizing feature map (SOFM) converts arbitrary dimensional patterns into one or two dimensional arrays of nodes. Among the many competitive learning algorithms, SOFM proposed by Kohonen is considered to be powerful in the sense that it not only clusters the input pattern adaptively but also organize the output node topologically. SOFM is usually used for a preprocessor or cluster. It can perform dimensional reduction of input patterns and obtain a topology-preserving map that preserves neighborhood relations of the input patterns. The traditional SOFM algorithm[1] is a competitive learning neural network that maps inputs to discrete points that are called nodes on a lattice...

• Proceedings of the KOSOMBE Conference
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• v.1991 no.11
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• pp.38-43
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• 1991

In order to cluster the Input pattern neatly, some neural network modified from Kohonen's self organizing feature map is introduced and Korean phoneme recognition experiments are performed using the modified self organizing feature map(MSOFM) and the auditory model.

• International Journal of Internet, Broadcasting and Communication
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• v.4 no.1
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• pp.13-17
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• 2012

Indexing allows converting raw document collection into easily searchable representation. Web searching by Google or Yahoo provides subsecond response time which is made possible by efficient indexing of web-pages over the entire Web. Indexing process gets challenging when the scale gets bigger. Parallel techniques, such as MapReduce framework can assist in efficient large-scale indexing process. In this paper we propose PDFindexer, system for indexing scientific papers in PDF using MapReduce programming model. Unlike Web search engines, our target domain is scientific papers, which has pre-defined structure, such as title, abstract, sections, references. Our proposed system enables parsing scientific papers in PDF recreating their structure and performing efficient distributed indexing with MapReduce framework in a cluster of nodes. We provide the overview of the system, their components and interactions among them. We discuss some issues related with the design of the system and usage of MapReduce in parsing and indexing of large document collection.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.549-557
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• 2011

In this paper, we apply cluster analysis to "Okayama parking data" that is one of the spatial point patterns data that includes locations and the fare structure of car parking space in Okayama central area. This study classifies the characteristics of small areas through Okayama parking data as well as visualizes the results of the cluster analysis. We develop web applications that connect the results of a cluster analysis and overlay objects including points of balloons and rectangles of small areas over a map of Okayama central area.