• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1283-1293
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• 2014

In ubiquitous environment, data are changing rapidly and new data is coming as times passes. And sometimes all of the past data will be lost if there is not sufficient space in memory. Therefore, there is a need to make rules and combine it with new data not to lose all the past data or to deal with large amounts of data. In making decision trees and extracting rules, the weight of each of rules is generally determined by the total number of the class at leaf. The computational problem of finding a minimum finite state acceptor compatible with given data is NP-hard. We assume that rules extracted are not correct and may have the loss of some information. Because of this precondition. this paper presents a new approach for refining rules. It controls their weight of rules of previous knowledge or data. In solving rule refinement, this paper tries to make a variety of rules with pruning method with majority and minority properties, control weight of each of rules and observe the change of performances. In this paper, the decision tree classifier with extended data expression having static weight is used for this proposed study. Experiments show that performances conducted with a new policy of refining rules may get better.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.4 s.74
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• pp.429-440
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• 2006

This paper comprises two specific objectives. The first is to examine the applicability of ordinary kriging interpolation(OK) to the p-adaptivity of the finite element method that is based on variogram modeling. The second objective Is to present the adaptive procedure by the hierarchical p-refinement in conjunction with a posteriori error estimator using the modified S.P.R. (superconvergent patch recovery) method. The ordinary kriging method that is one of weighted interpolation techniques is applied to obtain the estimated exact solution from the stress data at the Gauss points. The weight factor is determined by experimental and theoretical variograms for interpolation of stress data apart from the conventional interpolation methods that use an equal weight factor. In the p-refinement, the analytical domain has to be refined automatically to obtain an acceptable level of accuracy by increasing the p-level non-uniformly or selectively. To verify the performance of the modified S.P.R. method, the new error estimator based on limit value has been proposed. The validity of the proposed approach has been tested with the help of some benchmark problems of linear elastic fracture mechanics such as a centrally cracked panel, a single edged crack, and a double edged crack.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5D
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• pp.527-532
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• 2012

Terrestrial LiDAR emerges as a main mapping technology for indoor 3D cadastre, cultural heritage conservation and, building management in that it provides fast, accurate, and reliable 3D data. In this paper, a new 3D modeling method consisting of segmentation stage and outline extraction stage is proposed to develop indoor 3D model from the terrestrial LiDAR. In the segmentation process, RANSAC and a refinement grid is used to identify points that belong to identical planar planes. In the outline tracing process, a tracing grid and a data conversion method are used to extract outlines of indoor 3D models. However, despite of an improvement of productivity, the proposed approach requires an optimization process to adjust parameters such as a threshold of the RANSAC and sizes of the refinement and outline extraction grids. Furthermore, it is required to model curvilinear and rounded shape of the indoor structures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.677-687
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• 2006

Kriging interpolation is one of the generally used interpolation techniques in Geostatistics field. This technique includes the experimental and theoretical variograms and the formulation of kriging interpolation. In contrast to the conventional least square method for stress recovery, kriging interpolation is based on the weighted least square method to obtain the estimated exact solution from the stress data at the Gauss points. The weight factor is determined by variogram modeling for interpolation of stress data apart from the conventional interpolation methods that use an equal weight factor. In addition to this, the p-level is increased non-uniformly or selectively through a posteriori error estimation based on SPR (superconvergent patch recovery) technique, proposed by Zienkiewicz and Zhu, by auto mesh p-refinement. The cut-out plate problem under tension has been tested to validate this approach. It also provides validity of kriging interpolation through comparing to existing least square method.

• Economic and Environmental Geology
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• v.34 no.1
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• pp.1-12
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• 2001

The crystal structure of biotite-1M from Bancroft, Ontario, was determined by Rietveld refinement method using high-resolution neutron powder diffraction data at -26.3$^{\circ}C$, 2$0^{\circ}C$, 30$0^{\circ}C$, $600^{\circ}C$, 90$0^{\circ}C$. The crystal structure has been refined to a R sub(B) of 5.06%-11.9% and S (Goodness of fitness) of 2.97-3.94. The expansion rate of a, b, c unit cell dimensions with elevated temperature linearly increase to $600^{\circ}C$. The expansivity of the c dimension is $1.61{\times}10^{40}C^{-1}$, while $2.73{\times}10^{50}C^{-1}$ and $5.71{\times}10^{-50}C^{-1}$ for the a and b dimensions, respectively. Thus, the volume increase of the unit cell is dominated by expansion of the c axis as increasing temperature. In contrast to the trend, the expansivity of the dimensions is decreased at 90$0^{\circ}C$. It may be attributed to a change in cation size caused by dehydroxylation-oxidation of $Fe^{2+}$ to $Fe^{3+}$ in vacuum condition at such high temperature. The position of H-proton was determined by the refinement of diffraction pattern at low temperature (-2.63$^{\circ}C$). The position is 0.9103${\AA}$ from the O sub(4) location and located at atomic coordinates (x/a=0.138, y/b=0.5, z/c=0.305) with the OH vector almost normal to plane (001). According to the increase of the temperature, $\alpha$* (tetrahedral rotation angle), $t_{oct}$ (octahedral sheet thickness), mean distance increase except 90$0^{\circ}C$ data. But the trend is less clearly relative to unit cell dimension expansion because the expansion is dominant to the interlayer. Also, ${\Psi}$ (octahedral flattening angle) shows no trends as increasing temperature and it may be because the octahedron (M1, M2) is substituted by Mg and Fe.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.181-195
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• 2019

This study aims to analyze the spatial context by analyzing the flow characteristics of the walking tour course and visualizing effectively using the floating population data constructed through the communication data. The floating population data refinement algorithm was developed for estimation flow population along the road and the floating population data for each walking tour courses was constructed. In order to adopt the algorithm for forming suitable for the analysis of the walking tour courses, the estimation of floating population considering the area of the road and the estimation of floating population considering the value of floating population around the road were compared. As a result, the estimation of floating population considering ambient the values of flow population was adopted, which is more appropriate to apply analysis method due to the relatively consistent data. Then, a datamining algorithm for walking tour course was constructed according to the characteristics of the floating population data, the absence of missing values. Finally, this study analyzed the flow characteristics and spatial patterns of 18 walking trails in Seoul through the floating population data according to walking tour course. To do this, the kernel density analysis and the Getis-Ord $G^*_i$ statistical hotspot analysis were applied to visualize the main characteristics of each walking tour course.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.1
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• pp.99-112
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• 1994

This paper describe the development of a systematic method of slicing solid parts based on a data structure called Sliced Profile Data Structure(SPDS). SPDS is an augmented polygon data structure that allows multiple layers of sliced profiles to be connected together. The method consists of five steps: (1) Selection of slicing directions, (2) Determination of slicing levels, (3) Creation of sliced profiles, (4) Connection of sliced profiles, and (5) Refinement. The presented method is aimed at enhancing the applicability of CSG for manufacturing by overcoming the problem of non-uniqueness and global nature. The SPDS-based method of feature extraction is suitable for recognizing broad scope of features with detailed information. The method is also suitable for identifying the global relationships among features and is capable of incorporating the context dependency of feature extraction.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.2030-2038
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• 1995

In this study, three turbulent flame propagation models are compared using experimentally measured data of a 4 valves/cylinder spark-ignition engine. First two conventional models are B.K model and GESIM combustion model. The burning rates calculated from the two models are compared with the burning rates calculated from measured pressure data using the one-zone heat release analysis. GESIM combustion model predicts burning rates closer to the data acquired from the experiment in wide operating ranges than B-K model does. The third model is refined based on GESIM combustion model by including the effect of flame stretch, turbulent length scale band pass filter and a variable that considers flame size and the area of flame contacting the cylinder wall surface. The refined combustion model predicts burning rates closer to experimental results than GESIM combustion model does. Also, the refined combustion model predicts flame radius close to the experimental result measured by using optical fiber technique.

• Smart Structures and Systems
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• v.7 no.5
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• pp.349-363
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• 2011

To assess the performance of a structure requires the measurement of global and relative displacements at critical points across the structure. They should be obtained in real time and in all weather condition. A Global Navigation Satellite System (GNSS) could satisfy the last two requirements. The American Global Position System (GPS) provides long term acquisitions with sampling rates sufficient to track the displacement of long period structures. The accuracy is of the order of sub-centimetres. The steel building which hosts the authors' laboratory is the reference case-study within this paper. First a comparison of data collected by GPS sensor units with data recorded by tri-axial accelerometers is carried out when dynamic vibrations are induced in the structure by movements of the internal bridge-crane. The elaborations from the GPS position readings are then compared with the results obtained by a Finite Element (FE) numerical simulation. The purposes are: i) to realize a refinement of the structural parameters which characterize the building and ii) to outline a suitable way for processing GPS data toward structural monitoring.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.345-346
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• 2023

As the shape and size of detectable objects diversifying recognition and segmentation algorithms have been developed to acquire accurate shape information. Although a high density of data captured by the repetition of scanning improves the accuracy of algorithms the high dense data decreases the efficiency due to its large size. This paper proposes standardization algorithms using the feature of structural members on indoor point cloud data to improve the process. First of all we determine the reduction rate of the density based on the features of the target objects then the data reduction algorithm compresses the data based on the reduction rate. Second the data arrangement algorithm rotates the data until the normal vector of data is aligned along the coordinate axis to allow the following algorithms to operate properly. Final the data arrangement algorithm separates the rotated data into their leaning axis. This allows reverse engineering of indoor point clouds to obtain the efficiency and accuracy of refinement processes.