• Research in Mathematical Education
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• v.11 no.1
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• pp.65-74
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• 2007

The algorithmic idea has been a kind of necessary mathematics quality for modern people in this information society. In China the algorithm was represented fully as one of the new mathematics contents in the secondary level for the first time when The Standards of Mathematics Curriculum for the Senior High School was promulgated in 2003, so the research about the teaching algorithm undoubtedly has its practical implications for mathematics education. In this paper, with the conceptual framework of The Mathematics Task Framework as the research tool, an algorithmic teaching case based on LOGO software was introduced in detail, and data by ways of observations, interviews and worksheets were collected, then the case was analyzed. The results showed that the teaching of algorithm is feasible and effective in the LOGO environment. Some beneficial implications about the instructional design of algorithm were also discussed.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.418-422
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• 2016

A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.

• Journal of Satellite, Information and Communications
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• v.5 no.1
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• pp.85-89
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• 2010

This paper proposes a new QRD-LS adaptive algorithm with computational complexity of O(N). The main idea of proposed algorithm(D-QR-RLS) is based on the fact that the computation for the unit vector of is made from the process during Givens Rotation. The performance of the algorithm is evaluated through computer simulation of FIR system identification problem. As verified by simulation results, this algorithm exhibits a good performance. And, we can see the proposed algorithm converges to optimal coefficient vector theoretically.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.162-165
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• 2003

Differential learning relies on the differentiated values of nodes, whereas the conventional learning depends on the values themselves of nodes. In this paper, I elucidate the differential learning in the framework maximum likelihood learning of linear generative model with latent variables obeying random walk. I apply the idea of differential learning to the problem independent component analysis(ICA), which leads to differential ICA. Algorithm derivation using the natural gradient and local stability analysis are provided. Usefulness of the algorithm is emphasized in the case of blind separation of temporally correlated sources and is demonstrated through a simple numerical example.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.60-61
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• 2006

An unwanted trip of backup distance relays often lead to a blackout. This paper presents investigation report on involvement of backup distance relays in the past blackouts and sensitivity-factor based algorithm to make a distinction between a fault and overload caused by line tripping. A preliminary idea to prevent deterioration of the situation due to unwanted trip of distance relays by utilizing the proposed algorithm is presented.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.847-857
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• 2007

This paper provides a statistical algorithm which detects COD (chemical oxygen demand) measurement machine error on real-time. For this we propose to use regression model fitting and check its validity against the current observations. The main idea is that the normal regression relation between COD measurement and other parameters inside the machine will be violated when the machine is out of order.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.686-688
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• 1993

This paper proposes a robust speed control algorithm of Induction Motor. The main idea of this paper is to compensate the torque component of motor current with load torque observer and feedforward control. The speed response of the conventional PI controller is affected by variation of system parameters. However the proposed system has robust characteristics against the variation of system parameters. The simulation results and experiment prove the validity of proposed algorithm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.75-77
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• 2020

There was an outbreak of COVID-19 on the Diamond Princess cruise ship. Distinguishing close contacts is the important problem to be addressed. Close contacts mean people who stays with the patients of disease like COVID-19 over a period of time. The passenger position on board can be obtained by indoor positioning technology. The feature of close contacts is similar location with COVID-19 patients. Therefore, this paper proposed the idea of distinguishing close contacts on board based on DBSCAN algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1748-1751
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• 1991

Generally, we can't acquire clear boundary or area from an image having obscure boundary like allergy image by using Sobel or Lapalace operator. Also, when the image not uniform in some part of a image in brightness, there are difficulties to use the global operator such as histogram, for the contour line doesn't have the same grey level. In this paper, we will propose an algorithm to improve those difficulties. The main idea of the algorithm is that we divide the image into many rectangular parts like a chess board, calculate the average of each part, and decide the local threshold for each pixel on the calculated value. In experiment, we can get the contour and area by this algorithm which is much like to the contour and area measured by a doctor. Also, This algorithm has many advantages such as short processing time and little influences of noises and can be used in the robot vision, etc..

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.95-101
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• 2020

In this paper, we consider a group testing (GT) framework which is to find a set of defective samples out of a large number of samples. To handle this framework, we propose a maximum product detection algorithm (MPDA) which is based on maximum a posteriori probability (MAP). The key idea of this algorithm exploits iterative detection to propagate belief to neighbor samples by exchanging marginal probabilities between samples and output results. The belief propagation algorithm as a conventional approach has been used to detect defective samples, but it has computational complexity to obtain the marginal probability in the output nodes which combine other marginal probabilities from the sample nodes. We show that the our proposed MPDA provides a benefit to reduce computational complexity up to 12% in runtime, while its performance is only slightly degraded compared to the belief propagation algorithm. And we verify the simulations to compare the difference of performance.