• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1936-1939
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• 2002

Much recent attention on wireless technologies s put on topology-less wireless network, in which all nodes an be mobile and can communicate over wireless links, due to its ease of deployment, high flexibility and low expenses. One key in topology-less wireless network is mobile base stations (MBSs), which provides access points or mobile terminals (MTs) to wireless backbone network. MBSs can move to anywhere in accordance with changes in geographical distribution of MTs. They serve as dynamic odes. However, in order to utilize network resources and take full advantage of this topology-less network, MBSs must move to suitable position according to the current tate of network use. Moreover, MBSs have to consider the distance among them to avoid the crash and gap area of MBSs. Therefore, this paper proposes MBS movement algorithm by implementing push-pull method to fulfill the corporation of MBSs and considering the center of covered MTs or centroid to satisfy the MT coverage. From the simulation results, the proposed algorithm increases the performance of system when comparing with the centroid-based algoriom〔7〕, such as coverage area, MT coverage and call drops rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.4
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• pp.301-314
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• 1990

This paper is an attempt to use vision-pattern recognition technique to analyzation on a hidden rigid body motion. Specially shaped rod, rigidly connected to the hidden body is extended to the ouside of hiding object so that a camera may catch the motion data. Every motion can be described with translatio and rotation. But translation can be explanied with ratation with a infinitly far centroid. Motion analysis is to find the instantaneous centroid and ratation angle. With this theory jaw motion is analyzed in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1684-1690
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• 2003

In this paper, we proposed a fuzzy controller for the evaluation of the quantization Parameters in the H.263 coder to optimize the subjective quality of each coded frame, keeping the transmission rate constant. We adopted the Mamdani method for fuzzification and the centroid method for defuzzification. The energy and entropy are correlated to features of the HVS in spatial domain, while motion vectors are used to estimate the temporal characteristics of the signal. And then, the fuzzy inputs adapted the variance and the entropy in spatial domain, and the motion vector in temporal domain. We induced the fuzzy membership function and decided the fuzzy relevance to be compatible in visual characteristics. And then, we designed FAM banks. The fuzzy technology has been applied to a practical video compression. This results is obtained an effective rate control technique, an optimum bit allocation and a high subjective quality using fuzzy quantization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.469-478
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• 2010

This paper proposes the effective shape descriptor for 3D foot pose estimation. To reduce processing time, silhouette-based foot image database is built and meta information which involves the 3D pose of the foot is appended to the database. And we proposed a modified Centroid Contour Distance whose size of the feature space is small and performance of pose estimation is better than the others. In order to analyze performance of the descriptor, we evaluate time and spatial complexity with retrieval accuracy, and then compare with the previous methods. Experimental results show that the proposed descriptor is more effective than the previous methods on feature extraction time and pose estimation accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.91-95
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• 2004

In this paper, we propose a fuzzy controller for the evaluation of the quantization parameters in the H.263 coder. Our method adopts the Mamdani method for fuzzification and adopts the centroid method for defuzzification respectively. The inputs are variance, entropy in the spatial domain, current motion vector and previous motion vector in the temporal. Fuzzy variables are determined to be compatible in visual characteristics and fuzzy membership function is induced and then, FAM banks are designed to reduce the number of rules. In this paper, fuzzy quantization has been applied to a practical video compression. This results show that the quality of decode image enhances and the rate control method using fuzzy quantization is effective.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.83-84
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• 2006

In this paper, we examine discharge characteristics of cross-linked polyethylene (since then; XLPE) according to thickness. Voltage was applied to power frequency by step method, and calibration of discharge was set to 50[pC] (slope=8.333). After the voltage was applied, for 10 [sec] (600 [cycle]), occurring discharge and number were detected. Determine of input pattern is difficult because discharge pattern is irregular. Therefore we investigated pattern using the K-means Analysis and Weibull function. Also we investigated variation of centroid and cluster.

• Journal of Information Science Theory and Practice
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• v.9 no.4
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• pp.15-34
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• 2021

Text clustering is one of the most commonly used methods for detecting themes or types of documents. Text clustering is used in many fields, but its effectiveness is still not sufficient to be used for the understanding of Arabic text, especially with respect to terms extraction, unsupervised feature selection, and clustering algorithms. In most cases, terms extraction focuses on nouns. Clustering simplifies the understanding of an Arabic text like the text of the Quran; it is important not only for Muslims but for all people who want to know more about Islam. This paper discusses the complexity and limitations of Arabic text clustering in the Quran based on their themes. Unsupervised feature selection does not consider the relationships between the selected features. One weakness of clustering algorithms is that the selection of the optimal initial centroid still depends on chances and manual settings. Consequently, this paper reviews literature about the three major stages of Arabic clustering: terms extraction, unsupervised feature selection, and clustering. Six experiments were conducted to demonstrate previously un-discussed problems related to the metrics used for feature selection and clustering. Suggestions to improve clustering of the Quran based on themes are presented and discussed.

• Communications of the Korean Mathematical Society
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• v.34 no.1
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• pp.83-93
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• 2019

Let R be a noncommutative prime ring of characteristic different from 2, U the Utumi quotient ring of R, C the extended centroid of R and f($x_1,{\ldots},x_n$) a noncentral multilinear polynomial over C in n noncommuting variables. Denote by f(R) the set of all the evaluations of f($x_1,{\ldots},x_n$) on R. If d is a nonzero derivation of R and G a nonzero generalized derivation of R such that $$d(G(u)u){\in}Z(R)$$ for all $u{\in}f(R)$, then $f(x_1,{\ldots},x_n)^2$ is central-valued on R and there exists $b{\in}U$ such that G(x) = bx for all $x{\in}R$ with $d(b){\in}C$. As an application of this result, we investigate the commutator $[F(u)u,G(v)v]{\in}Z(R)$ for all $u,v{\in}f(R)$, where F and G are two nonzero generalized derivations of R.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.1-10
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• 2022

Nowadays software defect prediction (SDP) is most active research going on in software engineering. Early detection of defects lowers the cost of the software and also improves reliability. Machine learning techniques are widely used to create SDP models based on programming measures. The majority of defect prediction models in the literature have problems with class imbalance and high dimensionality. In this paper, we proposed Centroid and Nearest Neighbor based Class Imbalance Reduction (CNNCIR) technique that considers dataset distribution characteristics to generate symmetry between defective and non-defective records in imbalanced datasets. The proposed approach is compared with SMOTE (Synthetic Minority Oversampling Technique). The high-dimensionality problem is addressed using Ant Colony Optimization (ACO) technique by choosing relevant features. We used nine different classifiers to analyze six open-source software defect datasets from the PROMISE repository and seven performance measures are used to evaluate them. The results of the proposed CNNCIR method with ACO based feature selection reveals that it outperforms SMOTE in the majority of cases.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.375-382
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• 2009

This paper proposes a new audio fingerprinting method based on compressed-domain features. By basing on the compressed domain, the computational efficiency of the proposed method can be greatly enhanced. Especially we deal with MDCT domain, which is widely employed in audio compression, and extract three kinds of subband features; energy, centroid, and flatness. By taking signs after differentially filtering each feature, binary audio fingerprints are obtained. The identification performance of the three kinds of fingerprints are experimentally compared. Among the considered compressed-domain subband features, the subband energy showed the best performance for fingerprinting.