• Communications of Mathematical Education
• /
• v.25 no.4
• /
• pp.681-691
• /
• 2011

Mathematics curriculum according to 2009 Revised National Curriculum suggests that school mathematics must cultivate interest and curiosity about mathematics in addition to creative thinking ability of students, and ability and attitude of observing and analyzing many things happening around. Centroid of a triangle in 2007 Revised National Curriculum is defined as 'an intersection point of three median lines of a triangle' and it has been instructed focusing on proof study that uses characteristic of parallel lines and similarity of a triangle. This could not teach by focusing on the centroid itself and there is a problem of planting a miss concept to students. And therefore this writing suggests centroid must be taught according to its essence that centroid is 'a dot that forms equilibrium', and a justification method about this could be different.

• Journal of The Korean Astronomical Society
• /
• v.33 no.2
• /
• pp.89-95
• /
• 2000

As an efficient method to detect blending of general gravitational microlensing events, it is proposed to measure the shift of source star image centroid caused by microlensing. The conventional method to detect blending by this method is measuring the difference between the positions of the source star image point spread function measured on the images taken before and during the event (the PSF centroid shift, ${\delta}{\theta}$c,PSF). In this paper, we investigate the difference between the centroid positions measured on the reference and the subtracted images obtained by using the difference image analysis method (DIA centroid shift, ${\delta}{\theta}$c.DIA), and evaluate its relative usefulness in detecting blending over the conventional method based on ${\delta}{\theta}$c,PSF measurements. From this investigation, we find that the DIA centroid shift of an event is always larger than the PSF centroid shift. We also find that while ${\delta}{\theta}$c,PSF becomes smaller as the event amplification decreases, ${\delta}{\theta}$c.DIA remains constant regardless of the amplification. In addition, while ${\delta}{\theta}$c,DIA linearly increases with the increasing value of the blended light fraction, ${\delta}{\theta}$c,PSF peaks at a certain value of the blended light fraction and then eventually decreases as the fraction further increases. Therefore, measurements of ${\delta}{\theta}$c,DIA instead of ${\delta}{\theta}$c,PSF will be an even more efficient method to detect the blending effect of especially of highly blended events, for which the uncertainties in the determined time scales are high, as well as of low amplification events, for which the current method is highly inefficient.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.2
• /
• pp.199-209
• /
• 2022

Typical anomaly detection algorithms are trained by using prior data. Thus the batch learning based algorithms cause inevitable performance degradation when characteristics of newly incoming normal data change over time. We propose an online anomaly detection algorithm which can consider the gradual characteristic changes of incoming normal data. The proposed algorithm based on one-class classification model includes both offline and online learning procedures. In offline learning procedure, the algorithm learns the prior data to be close to centroid of the latent space and then updates the centroid of the latent space incrementally by new incoming data. In the online learning, the algorithm continues learning by using the updated centroid. Through experiments using public underwater acoustic data, the proposed online anomaly detection algorithm takes only approximately 2 % additional learning time for the incremental centroid update and learning. Nevertheless, the proposed algorithm shows 19.10 % improvement in Area Under the receiver operating characteristic Curve (AUC) performance compared to the offline learning model when new incoming normal data comes.

• Bulletin of the Korean Mathematical Society
• /
• v.44 no.2
• /
• pp.203-213
• /
• 2007

The aim of this paper is to introduce modules over the generalized of a semi-prime ${\Gamma}$-ring

• Korean Journal of Remote Sensing
• /
• v.29 no.1
• /
• pp.11-20
• /
• 2013

Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite's orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.248-251
• /
• 2004

Stability of truck and trailer are the most significance in Thai automotive industry. This paper presents the mathematical model of a six-degree-of-freedom semi-trailer vehicle. Search method was implemented to obtain the optimum design variables of the trailer which are the distance from the fifth wheel to the centroid of the trailer and the distance from the centroid of the trailer to the trailer axel. The objective function is to minimize the steady side slip velocity, steady-state yawing velocity and steady-state angle between the tractor and the trailer. From the calculation , the optimum distance from the fifth wheel to the centroid of the trailer and the optimum distance from the centroid of the trailer to the trailer axle are 5.50 and 3.25 meters respectively. The stability of the optimal semi-trailer vehicle was also examined in steady state. The steady side slip velocity, yawing velocity and the angle between tractor and trailer are also obtained using linearization technique under unit step disturbance of the tractor front wheel steering angle.

• Proceedings of the IEEK Conference
• /
• 2000.07a
• /
• pp.450-453
• /
• 2000

In this paper, an automated segmentation algorithm is proposed for MR brain images using T1-weighted, T2-weighted, and PD images complementarily. The proposed segmentation algorithm is composed of 3 steps. In the first step, cerebrum images are extracted by putting a cerebrum mask upon the three input images. In the second step, outstanding clusters that represent inner tissues of the cerebrum are chosen among 3-dimensional (3D) clusters. 3D clusters are determined by intersecting densely distributed parts of 2D histogram in the 3D space formed with three optimal scale images. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram. In the final step, cerebrum images are segmented using FCM algorithm with it’s initial centroid value as the outstanding cluster’s centroid value. The proposed segmentation algorithm complements the defect of FCM algorithm, being influenced upon initial centroid, by calculating cluster’s centroid accurately And also can get better segmentation results from the proposed segmentation algorithm with multi spectral analysis than the results of single spectral analysis.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.4
• /
• pp.530-536
• /
• 2008

Localization is one of the fundamental problems in wireless sensor networks (WSNs) that forms the basis for many location-aware applications. Localization in WSNs is to determine the position of node based on the known positions of several nodes. Most of previous localization method use triangulation or multilateration based on the angle of arrival (AOA) or distance measurements. In this paper, we propose an enhanced centroid localization method based on edge weights of adjacent nodes using fuzzy modeling and genetic algorithm when node connectivities are known. The simulation results shows that our proposed centroid method is more accurate than the simple centroid method using connectivity only.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.4
• /
• pp.511-518
• /
• 2007

This paper presents an efficient face recognition method by using both centroid shift and mutual information estimation of images. The centroid shift is to move an image to center coordinate calculated by first moment, which is applied to improve the recognition performance by excluding the needless backgrounds in face image. The mutual information which is a measurements of correlations, is applied to efficiently measure the similarity between images. Adaptive partition mutual information(AP-MI) estimation is especially applied to find an accurate dependence information by equally partitioning the samples of input image for calculating the probability density function(PDF). The proposed method has been applied to the problem for recognizing the 48 face images(12 persons * 4 scenes) of 64*64 pixels. The experimental results show that the proposed method has a superior recognition performances(speed, rate) than a conventional method without centroid shift. The proposed method has also robust performance to changes of facial expression, position, and angle, etc. respectively.

• Journal of KIISE:Information Networking
• /
• v.30 no.3
• /
• pp.424-436
• /
• 2003

In this paper, we propose the Centroid-based Backbone Core Tree(CBCT) generation algorithm for the shared tree-based IP multicasting. The proposed algorithm is based on the Core Based Tree(CBT) protocol. Despite the advantages over the source-based trees in terms of scalability, the CBT protocol still has the following limitations; first, the optimal core router selection is very difficult, and second, the multicast traffic is concentrated near a core router. The Backbone Core Tree(BCT) protocol, as an extension of the CBT protocol has been proposed to overcome these limitations of the CBT Instead of selecting a specific core router for each multicast group, the BCT protocol forms a backbone network of candidate core routers which cooperate with one another to make multicast trees. However, the BCT protocol has not mentioned the way of selecting candidate core routers and how to connect them. The proposed CBCT generation algorithm employs the concepts of the minimum spanning tree and the centroid. For the performance evaluation of the proposed algorithm, we showed the performance comparison results for both of the CBT and CBCT protocols.