• 대한수학회논문집
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• 제32권3호
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• pp.709-714
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• 2017

For every interval [a, b], we denote by (${\bar{x}}_A,{\bar{y}}_A$) and (${\bar{x}}_L,{\bar{y}}_L$) the geometric centroid of the area under a catenary y = k cosh((x - c)/k) defined on this interval and the centroid of the curve itself, respectively. Then, it is well-known that ${\bar{x}}_L={\bar{x}}_A$ and ${\bar{y}}_L=2{\bar{y}}_A$. In this paper, we show that one of ${\bar{x}}_L={\bar{x}}_A$ and ${\bar{y}}_L=2{\bar{y}}_A$ characterizes the family of catenaries among nonconstant $C^2$ functions. Furthermore, we show that among nonconstant and nonlinear $C^2$ functions, ${\bar{y}}_L/{\bar{x}}_L=2{\bar{y}}_A/{\bar{x}}_A$ is also a characteristic property of catenaries.

• Steel and Composite Structures
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• 제22권5호
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• pp.1073-1084
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• 2016

Rectangular concrete-filled steel tubular columns with unequal wall thickness were investigated in the paper. The physical centroid, the centroidal principal axes of inertia, and the section core were given. The generalized bending formula and the generalized eccentric compression formula were deduced, and the equation of the neutral axis was also provided. The two rectangular concrete-filled steel tubular stub specimens subjected to the compression load on the physical centroid and the geometric centroid respectively were tested to verify the theoretical formulas.

• 전자공학회논문지B
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• 제33B권8호
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• pp.114-123
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• 1996

In this paper, we propose an automatic recognition algorithm using the object centroid of a facial image. First, we separate the facial image from the background image using the chroma-key technique and we find the centroid of the separated facial image. Second, we search nose in the facial image based on knowledge of human faces and the coordinate of the object centroid and, we calculate 17 feature parameters automatically. Finally, we recognize the facial image by using feature parameters in the neural networks which are trained through error backpropagation algorithm. It is illustrated by experiments by experiments using the proposed recogniton system that facial images can be recognized in spite of the variation of the size and the position of images.

• East Asian mathematical journal
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• 제29권4호
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• pp.425-447
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• 2013

Since the center of mass of mathematics curriculum in middle school is dealt with only on triangle and it is defined as just an intersection point of median lines without any physical experiments, students sometimes have misconception of the centroid as well as it is difficult to promote divergent thinking that enables students to think the centroids of various figures. To overcome these problems and to instruct effectively the centroid unit in middle school mathematics classroom, this study suggests a teaching and learning method for the unit which uses physical experiments, drawing, and calculation methods sequentially based on the investigation of students' understanding on the centroid of triangle and the analysis of the mathematics textbooks.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2007년도 추계학술대회 논문집
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• pp.203-204
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• 2007

This paper investigated the influence on partial discharge distribution of various defects at the model power cable joints interface using K-means clustering. As the result of analyzing discharge number distribution of ${\Phi}-n$ cluster, clusters shifted to $0^{\circ}\;and\;180^{\circ}$ with increasing applying voltage. It was confirmed that discharge quantity and euclidean distance between centroids were increased with applying voltage from the analyzing centroid distribution of ${\Phi}-q$ cluster. The degree of dispersion was increased with calculating standard deviation of ${\Phi}-q$ cluster centroid. The tendency both number of discharge and mean value of ${\Phi}-q$ cluster centroid were some different with defect types.

• 대한수학회논문집
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• 제33권1호
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• pp.237-245
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• 2018

For every interval [a, b], we denote by $({\bar{x}}_A,{\bar{y}}_A)$ and $({\bar{x}}_L,{\bar{y}}_L)$ the geometric centroid of the area under a catenary curve y = k cosh((x-c)/k) defined on this interval and the centroid of the curve itself, respectively. Then, it is well-known that ${\bar{x}}_L={\bar{x}}_A$ and ${\bar{y}}_L=2{\bar{y}}_A$. In this paper, we fix an end point, say 0, and we show that one of ${\bar{x}}_L={\bar{x}}_A$ and ${\bar{y}}_L=2{\bar{y}}_A$ for every interval with an end point 0 characterizes the family of catenaries among nonconstant $C^2$ functions.

• International Journal of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.156-165
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• 2021

In this paper, we propose an histogram weighted centroid based Siamese region proposal network for object tracking. The original Siamese region proposal network uses two identical artificial neural networks which take two different images as the inputs and decide whether the same object exist in both input images based on a similarity measure. However, as the Siamese network is pre-trained offline, it experiences many difficulties in the adaptation to various online environments. Therefore, in this paper we propose to incorporate the histogram weighted centroid feature into the Siamese network method to enhance the accuracy of the object tracking. The proposed method uses both the histogram information and the weighted centroid location of the top 10 color regions to decide which of the proposed region should become the next predicted object region.

• Communications for Statistical Applications and Methods
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• 제30권3호
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• pp.245-258
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• 2023

This study proposes a modification to the objective function of the support vector machine for the linearly non-separable case of a binary classifier y_i ∈ {-1, 1}. The modification takes into account the position of each data item x_i from its corresponding class centroid. The resulting optimization function involves the centroid mean vector, and the spread of data besides the support vectors, which should be minimized by the choice of hyper-plane β. Theoretical assumptions have been tested to derive an optimal separable hyperplane that yields the minimal misclassification rate. The proposed method has been evaluated using simulation studies and real-life COVID-19 patient outcome hospitalization data. Results show that the proposed method performs better than the classical linear SVM classifier as the sample size increases and is preferred in the presence of correlations among predictors as well as among extreme values.

• 전기전자학회논문지
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• 제26권1호
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• pp.67-76
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• 2022

In this paper, we propose a new algorithm to improve the accuracy of the Wi-Fi access point (AP) positioning technique. The proposed algorithm based on evaluating the trustworthiness of the signal strength quality of each measurement node is superior to other existing AP positioning algorithms, such as the centroid, weighted centroid, multilateration, and radio distance ratio methods, owing to advantages such as reduction of distance errors during positioning, reduction of complexity, and ease of implementation. To validate the performance of the proposed algorithm, we conducted experiments in a complex indoor environment with multiple walls and obstacles, multiple office rooms, corridors, and lobby, and measured the corresponding AP signal strength value at several specific points based on their coordinates. Using the proposed algorithm, we can obtain more accurate positioning results of the APs for use in research or industrial applications, such as finding rogue APs, creating radio maps, or estimating the radio frequency propagation properties in an area.

• 한국통신학회논문지
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• 제32권9C호
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• pp.861-866
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• 2007

본 논문은 가우시안 확률분포함수 (Gaussian Probability Distribution Function) 데이터 군집화를 위해 중심신경망 (Centroid Neural Network, CNN)에 Bhattacharyya 커널을 적용한 군집화 알고리즘 (Bhattacharyya Kernel based CNN, BK-CNN)을 제안한다. 제안된 BK-CNN은 무감독 알고리즘인 중심신경망을 기반으로 하고 있으며, 커널 방법을 이용하여 데이터를 특징공간에서 투영한다. 입력공간의 비선형 문제를 선형적으로 해결하기 위해 제안한 커널 방법인데, 확률분포 사이의 거리측정을 위해 Bhattacharyya 거리를 이용한 커널방법을 사용하였다. 제안된 BK-CNN을 영상데이터 분류의 문제에 적용했을 때, 제안된 BK-CNN 알고리즘이 Bhattacharyya 커널을 적용한 k-means, 자기조직지도(Self-Organizing Map)와 중심 신경망등의 기존 알고리즘보다 1.7% - 4.3%의 평균 분류정확도 향상을 가져옴을 확인할 수 있었다.