• Computers and Concrete
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• v.29 no.4
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• pp.219-235
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• 2022

Strengthening slender reinforced concrete (RC) columns is a challenge. They are susceptible to overall buckling that induces bending moment and axial compression. This study presents the precise three-dimensional finite element modeling of slender RC columns strengthened with fiber-reinforced polymer (FRP) composites sheets with various patterns under concentric or eccentric compression. The slenderness ratio λ (height/width ratio) of the studied columns ranged from 15 to 35. First, to determine the optimal modeling procedure, nine alternative nonlinear finite element models were presented to simulate the experimental behavior of seven FRP-strengthened slender RC columns under eccentric compression. The models simulated concrete behavior under compression and tension, FRP laminate sheets with different fiber orientations, crack propagation, FRP-concrete interface, and eccentric compression. Then, the validated modeling procedure was applied to simulate 58 FRP-strengthened slender RC columns under compression with minor eccentricity to represent the inevitable geometric imperfections. The simulated columns showed two cross sections (square and rectangular), variable λ values (15, 22, and 35), and four strengthening patterns for FRP sheet layers (hoop H, longitudinal L, partial longitudinal L_w, and longitudinal coupled with hoop LH). For λ=15-22, pattern L showed the highest strengthening effectiveness, pattern L_w showed brittle failure, steel reinforcement bars exhibited compressive yielding, ties exhibited tensile yielding, and concrete failed under compression. For λ>22, pattern L_w outperformed pattern L in terms of the strengthening effectiveness relative to equivalent weight of FRP layers, steel reinforcement bars exhibited crossover tensile strain, and concrete failed under tension. Patterns H and LH (compared with pattern L) showed minor strengthening effectiveness.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.27-43
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• 2005

This paper presents a new hybrid data mining technique using error pattern modeling to improve classification accuracy when the data type of a target variable is binary. The proposed method increases prediction accuracy by combining two different supervised learning methods. That is, the algorithm extracts a subset of training cases that are predicted inconsistently by both methods, and models error patterns from the cases. Based on the error pattern model, the Predictions of two different methods are merged to generate final prediction. The proposed method has been tested using practical 10 data sets. The analysis results show that the performance of proposed method is superior to the existing methods such as artificial neural networks and decision tree induction.

• Korean Journal of Computational Design and Engineering
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• v.14 no.5
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• pp.330-337
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• 2009

Nowadays a lot of high-tech electronic products such as TVs, monitors and camcorders are being developed. The more functions the electronic devices have, the more heat problems occur. Therefore, most of electronic products have air-ventilation holes to eliminate heat that is generated inside the products. The shapes of ventilation holes are usually complicated since aesthetic appearance of the products is important these days. In order to create those complicated shapes, designers should do time-consuming jobs because most of commercial CAD systems do not provide the functions that create patterns of lofted parts along freeform surfaces. In this research, an automated air-ventilation hole modeling system was proposed. The system generates patterns of lofted objects on freeform surfaces. Standard process to create air-ventilation holes manually was established, and vent-hole types and pattern types were classified into several categories. Designers can create many kinds of vent-holes by combining vent-hole types and pattern types. Users can also utilize user-defined pattern which can give users more flexibility. Developed system was applied to several design examples and the results are presented.

• Structural Engineering and Mechanics
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• v.16 no.4
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• pp.441-468
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• 2003

This paper investigates the structural behavior of modular falsework system under sequential pattern loads. Based on the studies of 25 construction sites, the pattern load sequence modeling is defined as models R (rectangle), L and U. The study focuses on the system critical loads, regions of largest reaction forces, discrepancy between the pattern load and the uniform load, and the warning-system plan. The analysis results show that the critical loads of modular falsework systems with sequential pattern loads are very close to those with the uniform load used in design. The regions of largest reaction forces are smaller than those calculated by the uniform load. However, the regions of largest reaction forces of three models under sequential pattern loads can be considered as the crucial positions of warning-system based on the measured index of loading. The positions of the sensors for the warning-system for these three different models are not identical.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.257-261
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• 2003

In this study, we investigated the modeling and design of an Intelligent Agent System (IAS). To achieve this goal, we introduced several kinds of agents that exhibit intelligent features. These are the main agent, management agent, watcher agent, report agent and application agent. We applied the intelligent agent concept to two different application fields, i.e. the intelligent agent system for pattern classification and the intelligent agent system for bank asset management modeling.

• The Mathematical Education
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• v.49 no.3
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• pp.313-328
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• 2010

Mathematical modeling has been observed in the way of a possibility to contribute in improving students' problem solving abilities. One of the important views of real life problem context could be described such as a useful ways to interpret the real life leading to children's abstraction process. The problem contexts for the grade 6 with mathematical modeling perspectives were developed by reviewing the current 7th National Mathematics Curriculum of Korea. Those include the 5 content areas such as number & operation, geometry, measurement, probability & statistics, and pattern & problem solving. One of problem contexts, "Space", specially designed for pattern & problem solving area, was applied to the grade 6 students and analyzed in detail to understand student's mathematical modeling progress.

• Journal of Environmental Impact Assessment
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• v.8 no.1
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• pp.1-16
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• 1999

The acid deposition and photochemical modeling study was performed on the Eastern Asia using Regional Acid Deposition Model(RADM). The results of this study show that horizontal distribution of $SO_2$, concentration and dry deposition flux was higher in Beking, Shanghai and central part of Korea. However distribution pattern of sulfate and $O_3$ concentration calculated by RADM were not similar to emission pattern. In daytime, $SO_2$, sulfate and $O_3$ were mixed to whole PBL but in nighttime because of inversion layer these pollutants were suppressed to lower level.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.73-78
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• 2004

By modeling the block matching algorithm as a function of the correlation of image blocks, we derive search patterns for fast block matching motion estimation. The proposed approach provides an analytical support lot the diamond-shape search pattern, which is widely used in fast block matching algorithms. We also propose a new fast motion estimation algorithm using adaptive search patterns and statistical properties of the object displacement. In order to select an appropriate search pattern, we exploit the relationship between the motion vector and the block differences. By changing the search pattern adaptively, we improve motion prediction accuracy while reducing required computational complexity compared to other fast block matching algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.16-22
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• 2012

In this paper, we present spiral pattern which suits for optical simulator to calibrate fisheye lens and compensate geometric distortion. Using spiral pattern, we present calibration without mathematical modeling in advance. Proposed spiral pattern used to input image of optical simulator. Using fisheye lens image, we calibrate a fisheye lens by matching geometrically moved dots to corresponding original dots which leads not to need mathematical modeling. Proposed algorithm calibrates using dot matching which matches spiral pattern image dot to distorted image dot. And this algorithm does not need modeling in advance so it is effective. Proposed algorithm is enabled at processing of pattern recognition which has to get the exact information using fisheye lens for digital zooming. And this makes possible at compensation of geometric distortion and calibration of fisheye lens image applying in various image processing.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.225-242
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• 2008

PM (Inconsistency Pattern Modeling) is a hybrid supervised learning technique using the inconsistence pattern of input variables in mining data sets. The IPM tries to improve prediction accuracy by combining more than two different supervised learning methods. The previous related studies have shown that the IPM was superior to the single usage of an existing supervised learning methods such as neural networks, decision tree induction, logistic regression and so on, and it was also superior to the existing combined model methods such as Bagging, Boosting, and Stacking. The objectives of this paper is explore the characteristics of the IPM. To understand characteristics of the IPM, three experiments were performed. In these experiments, there are high performance improvements when the prediction inconsistency ratio between two different supervised learning techniques is high and the distance among supervised learning methods on MDS (Multi-Dimensional Scaling) map is long.