• Journal of applied mathematics & informatics
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• v.35 no.1_2
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• pp.33-44
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• 2017

We review weighted power means of positive real numbers and see their properties including the convexity and concavity for weights. We study the mixed power means of positive real numbers related to majorization of weights, which gives us an extension of Muirhead's inequality. Furthermore, we generalize Holland's conjecture to the power means.

• Bulletin of the Korean Mathematical Society
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• v.50 no.2
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• pp.485-498
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• 2013

In this paper, the Schur convexity is generalized to Schur $f$-convexity, which contains the Schur geometrical convexity, harmonic convexity and so on. When $f$ : ${\mathbb{R}}_+{\rightarrow}{\mathbb{R}}$ is defined as $f(x)=(x^m-1)/m$ if $m{\neq}0$ and $f(x)$ = ln $x$ if $m=0$, the necessary and sufficient conditions for $f$-convexity (is called Schur $m$-power convexity) of Gini means are given, which generalize and unify certain known results.

• Journal of the Korean Mathematical Society
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• v.60 no.3
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• pp.503-520
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• 2023

In this paper, using the theory of majorization, we discuss the Schur m power convexity for L-conjugate means of n variables and the Schur convexity for weighted L-conjugate means of n variables. As applications, we get several inequalities of general mean satisfying Schur convexity, and a few comparative inequalities about n variables Gini mean are established.

• ETRI Journal
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• v.43 no.1
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• pp.17-30
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• 2021

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high-speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C-means algorithm. Next, cooperative and noncooperative clusters are extracted based on the distance measured using the kernel fuzzy C-means algorithm. The power is allocated to cooperative clusters using the Pareto optimality particle swarm optimization algorithm. In addition, the Nash equilibrium particle swarm optimization algorithm is used for allocating power in the noncooperative clusters. The process of allocating power to cooperative and noncooperative clusters reduces the overall transmission power of the radars. In the experimental section, the proposed method obtained the power consumption of 0.014 to 0.0119 at K = 2, M = 3 and K = 2, M = 3, which is better compared to the existing methodologies-generalized Nash game and cooperative and noncooperative game theory.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1960-1969
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• 2017

There have been ongoing researches to identify and analyze the patterns of electric power IoT data inside sensor nodes to supplement the stable supply of power and the efficiency of energy consumption. This study set out to propose an analysis process for electric power IoT data with the K-means algorithm, which is an unsupervised learning technique rather than a supervised one. There are a couple of problems with the old K-means algorithm, and one of them is the selection of cluster number K in a heuristic or random method. That approach is proper for the age of standardized data. The investigator proposed an analysis process of selecting an automated cluster number K through principal component analysis and the space division of normal distribution and incorporated it into electric power IoT data. The performance evaluation results show that it recorded a higher level of performance than the old algorithm in the cluster classification and analysis of pitches and rolls included in the communication bodies of utility poles.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1677-1685
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• 2014

Major problem in the high voltage power transmission line is the flashover due to polluted ceramic insulators which leads to failure of equipments, catastrophic fires and power outages. This paper deals with the development of a better diagnostic tool to predict the flashover and pollution severity of power transmission line insulators based on the wavelet transform and fuzzy c-means clustering approach. In this work, laboratory experiments were carried out on power transmission line porcelain insulators under AC voltages at different pollution conditions and corresponding leakage current patterns were measured. Discrete wavelet transform technique is employed to extract important features of leakage current signals. Variation of leakage current magnitude and distortion ratio at different pollution levels were analyzed. Fuzzy c-means algorithm is used to cluster the extracted features of the leakage current data. Test results clearly show that the flashover and pollution severity of power transmission line insulators can be effectively realized through fuzzy clustering technique and it will be useful to carry out preventive maintenance work.

• Journal of Korean Public Health Nursing
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• v.5 no.2
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• pp.37-44
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• 1991

This paper follows the Walker of Avant approach to concept analysis of the concept of power. For the purposes of the paper, power was defined as the actural or potential ability or capacity to achieve objectives through an interpersonal process in which the goals and means to achieve the goals are mutually established and worked toward. The distinction between the view of power as 'power to' versus 'power over' are addressed in the literature review. King's conceptual framework was used as a guide. The defining attributes of power are: 1. The actual or potential ablity or capacity to achieve objectives or attain goals. 2. An Interpersonal process, 3. Mutual establishment of goals and the means to achieve the goals and 4. Mutually working toward the goals. The antecedents for power were idntified in the literature review: 1. the presence of two or more people 2. acquisition of power skill 3. possession of the power sources 4. an orientation of power as good and 5. self-confidence. The concequences of power are the achievement of objectives or goal attainment. Finally Assumptions and testable hypothesis are proposed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.1
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• pp.1-9
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• 2021

This paper proposes to automate the process of predicting crypto-operations from the power signal generated in RSA decoding process by frequency analysis and K-means algorithm. RSA decoding process is divided into square and multiply operation, and if we can predict the type of operations over time, we will know the RSA key value. After converting the power signal generated in the process of decoding into two-dimensional frequency signal, this paper used K-means algorithm to classify the frequency vector according to the type of operation. these classified frequency vector were used to predict the types of operations.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.107-115
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• 2014

Offshore wind power has been extremely popular in recent years, and in the energy technology field, relevant research has been increasingly conducted. However, research regarding patent portfolios is still insufficient. The purpose of this research is to study the status of mainstream offshore wind power technology and patent portfolios and to investigate major assignees and countries to obtain a thorough understanding of the developmental trends of offshore wind power technology. The findings may be used by the government and industry for designing additional strategic development proposals. Data mining methods, such as multiple correspondence analyses and k-means clustering, were implemented to explore the competing technological and strategic-group relationships within the offshore wind power industry. The results indicate that the technological positions and patent portfolios of the countries and manufacturers are different. Additional technological development strategy recommendations were proposed for the offshore wind power industry.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2831-2833
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• 2000

Since the access to Station Control Computers(DCCs) is restricted to the main control room(MCR). the operating data of power plants can't be easily analyzed and effectively managed. It is possible to reduce waste of time and human energy by means of building the Remote Monitoring Network of DCCs connected to Local Area Network. automatizing collection and analysis of DCC data. gathering the operating state of power plants. and managing systematically. Furthermore. this system help preventing trip by means of analyzing the data promptly and watching main system continuously.