• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.4
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• pp.550-556
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• 1986

This paper proposes a two-layer channel routing algorithm using the division of signal nets in LSI/VLSI layout design. To solve the vertical constraint problem, the doglegging method is used. Although signal net division and the dogleg are used, the routing is accomplished within local channel density and the increase in vias is repressed by assining the vertical segments to the metal layer and the horizontal segments to the poly layer. The algorithm was implemented on a VAX 11/780 computer. The effectiveness of the proposed algorithm is proved by appling this algorithm to Deutch's difficult example.

• School Mathematics
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• v.7 no.2
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• pp.103-121
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• 2005

This article compares and analyzes mathematics textbooks of North Korea, South Korea, China and Japan and draws meaningful ways for introducing the division algorithm of fractions. The analysis is based on the five contexts: 'measurement division', 'determination of a unit rate', 'reduction of the quantities in the same measure', 'division as the inverse of multiplication or Cartesian product', 'analogy with multiplication algorithm of fractions'. The main focus of the analysis is what context is used to introduce the algorithm and how much it can appeal to students. This analysis supports that there is a few differences of introducing methods the division algorithm of fractions among those countries and more meaningful way can be considered than ours. It finally suggests that we teach the algorithm in a way which can have students easily see the reason of multiplying the reciprocal of a divisor when they divide with fractions. For this, we need to teach the meaning of a reciprocal of fraction and consider to use the context of determination of a unit rate.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.535-543
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• 2022

A drone is used to diagnose crop growth and to provide information through images in the agriculture field. In the case of using high spatial resolution drone images, growth information for each object can be produced. However, accurate object detection is required and adjacent objects should be efficiently classified. The purpose of this study is to develop a Chinese cabbage object detection algorithm using multispectral reflectance images observed from drone and computer vision techniques. Drone images were captured between 7 and 15 days after planting a Chinese cabbage from 2018 to 2020 years. The thresholds of object detection algorithm were set based on 2019 year, and the algorithm was evaluated based on images in 2018 and 2019 years. The vegetation area was classified using the characteristics of spectral reflectance. Then, morphology techniques such as dilatation, erosion, and image segmentation by considering the size of the object were applied to improve the object detection accuracy in the vegetation area. The precision of the developed object detection algorithm was over 95.19%, and the recall and accuracy were over 95.4% and 93.68%, respectively. The F1-Score of the algorithm was over 0.967 for 2 years. The location information about the center of the Chinese cabbage object extracted using the developed algorithm will be used as data to provide decision-making information during the growing season of crops.

• Transactions of the Korean hydrogen and new energy society
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• v.27 no.3
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• pp.318-327
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• 2016

In order to improve the performance of temperature field measurements by CT-TDLAS (Computer Tomography Tunable Diode Laser Absorption Spectroscopy), a new reconstruction algorithm, named two-ratios-of-three-peaks method is proposed in this paper. Further, two methods for selecting appropriate initial values of the iterative calculation of CT-TDLAS are proposed. One is MLOS (multiplicative line of sight) method and the other one is ALOS (additive line of sight) method. Two-ratios-of-three-peaks (2R3P) algorithm combined with MART (multiplicative algebraic reconstruction technique) is finally developed for the enhancements of reconstructive calculations. The results have been compared with those obtained by the conventional one-ratio-of-two-peaks (1R2P) algorithm. In order to evaluate the performance of this algorithm, numerical test has been performed using phantom Gaussian temperature distributions with $11{\times}11$ square mesh. The performance of the constructed algorithm has been demonstrated by comparing the results obtained in actual burner experiments with those obtained by thermocouples. It has been verified that 2R3P algorithm with MART and MLOS showed best performance than that of 1R2P algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.530-535
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• 2004

This paper considers a state set estimation (SSE) based model predictive control (MPC) for linear parameter- varying (LPV) systems with input constraint. We estimate, at each time instant, a feasible set of all states which are consistent with system model, measurements and a priori information, rather than the state itself. By combining a state-feedback MPC and an SSE, we design an SSE-based MPC algorithm that stabilizes the closed-loop system. The proposed algorithm is solved by semi-de�nite program involving linear matrix inequalities. A numerical example is included to illustrate the performance of the proposed algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.211-216
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• 2011

The detection of defective parts in a factory is usually performed by the human eye. Therefore, heavy manpower is in demand for minor enterprises. An image processing system is desired to solve this drawback. However, due to the variety of the products characteristics, an general algorithm is needed that can adapt to these characteristics. Therefore, in this paper, the key pad parts' characteristics which need to be dealt with are analyzed in order to embody the image processing algorithm that is suggested. The experimental results show the probability of detecting a defective part is 95% with a detection time of 0.203 seconds, on the average.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.10-15
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• 2012

This paper considers an economic design problem of a tree-based network which is a kind of computer network. This problem can be modeling to be an objective function to minimize installation costs, on the constraints of spanning tree and maximum traffic capacity of sub tree. This problem is known to be NP-hard. To efficiently solve the problem, a tabu list coupled genetic algorithm approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic algorithm approach.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.3
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• pp.176-180
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• 2001

In this papers, we derive a simple kinematic and dynamic formulation of an unmanned electric bicycle. We also check the controllability of the stabilization problem of bicycle. We propose a new control algorithm for the self stabilization of unmanned bicycle with bounded wheel speed and steering angle by using nonlinear control based on the sliding patch and stuck phenomena which was introduced by W. Ham. We also propose a sort of optimal control strategy for steering angle and driving wheel speed that make the length of bicycle\`s path be the shortest. From the computer simulation results, we prove the validity of the proposed control algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.783-786
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• 2008

외판원문제(Traveling Salesman problem: TSP)는 전형적인 조합최적화 문제로 위치하는 n개의 모든 지점을 오직 한번씩만 방문하는 순회경로를 결정하는 과정에서 순회비용 또는 순회거리를 최소화한다. 따라서 본 논문에서는 종래의 NP-hard문제로 널리 알려진 TSP를 해결하기 위해서 메타 휴리스틱기법 중에서 가장 널리 이용되고 있는 유전 알고리즘(Genetic Algorithm: GA)을 이용한다. 마지막으로, 유전 알고리즘을 이용해 외판원문제에 적합한 성능을 보이는 유전 연산자를 찾아내기 위해 수치 실험을 통해 그 성능에 대한 평가를 한다.

• Journal of the Optical Society of Korea
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• v.18 no.2
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• pp.118-123
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• 2014

For multi parameter optimization of Raman Fiber Amplifier (RFA), a simple genetic algorithm is presented in the scenario of a 320 channel Dense Wavelength Division Multiplexed (DWDM) system at channel spacing of 25 GHz. The large average gain (> 22 dB) is observed from optimized RFA with the optimized parameters, such as 39.6 km of Raman length with counter-propagating pumps tuned to 205.5 THz and 211.9 THz at pump powers of 234.3 mW, 677.1 mW respectively. The gain flattening filter (GFF) has also been optimized to further reduce the gain ripple across the frequency range from 190 to 197.975 THz for broadband amplification.