• 전기학회논문지P
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• 제53권2호
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• pp.43-50
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• 2004

Percentage differential characteristic relaying(PDR) has been recognized as the principal basis for power transformer protection. Second harmonic restraint PDR has been widely used for magnetizing inrush in practice. Nowadays, relaying signals can contain 2nd harmonic component to a large extent even in a normal state, and 2nd harmonic ratio indicates a tendency of relative reduction because of the advancement of material. Further, as the power system voltage becomes higher and more underground cables are used, larger 2nd harmonic component in the differential current under internal fault is observed. And then, conventional 2nd harmonic restraint PDR exposes some doubt in reliability. It is, therefore, necessary to develop a new algorithm for performance improvement of conventional protective relaying. This paper proposes an advanced protective relaying algorithm by using voltage-current trend and flux-differential current slope characteristic. To evaluate the performance of the proposed algorithm, we have made comparative studies of PDR, fuzzy relaying and DWT relaying. The paper is constructed power system model including power transformer, utilizing the WatATP, and data collection is made through simulation of various internal faults and inrush. As the results of test, the new proposed algorithm was proven to be faster and more reliable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.3862-3879
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• 2019

More and more problems for public security have occurred due to the limited solutions for drone detection especially for micro-drone in long range conditions. This paper aims at dealing with drones detection using a radar system. The radio frequency (RF) signals emitted by a controller can be acquired using the radar, which are usually too weak to extract. To detect the drone successfully, the static clutters and linear trend terms are suppressed based on the background estimation algorithm and linear trend suppression. The principal component analysis technique is used to classify the noises and effective RF signals. The automatic gain control technique is used to enhance the signal to noise ratios (SNR) of RF signals. Meanwhile, the empirical mode decomposition (EMD) based wavelet transform (WT) is developed to decrease the influences of the Gaussian white noises. Then, both the azimuth information between the drone and radar and the bandwidth of the RF signals are acquired based on the statistical analysis algorithm developed in this paper. Meanwhile, the proposed accumulation algorithm can also provide the bandwidth estimation, which can be used to make a decision accurately whether there are drones or not in the detection environments based on the probability theory. The detection performance is validated with several experiments conducted outdoors with strong interferences.

• 한국의상디자인학회지
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• 제25권4호
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• pp.77-92
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• 2023

The purpose of this study is to investigate the public perception of Gorpcore through Big Aata analytics. The study was conducted based on the collection of Big Data on the word 'Gorpcore' through Textom from July 24, 2017 to March 31, 2023. As a result, 63,386 words were collected from a total of 18,879 posts, and the top 50 words were determined based on frequency of appearance. Based on the collected words, centrality measures and CONCOR algorithm were performed in Ucinet 6. The research results are as follows. 1) The frequency of appearance was high in the order of 'Gorpcore look', 'fashion', 'coordination', 'clothes', 'outdoor', 'Musinsa', 'look', 'trend', 'brand' and 'ahjussi (middle-aged old man in Korean)'. These words had high TF-IDF scores, which leads to the conclusion that these are key words that are recognized as important. 2) Network centrality shows that 'Gorpcore look', 'fashion', 'outdoor', 'coordination', 'clothes', 'trend', 'look' and 'style' have a high correlation with other words. Through this, it was found that the public thinks it is important to create a variety of fashions by styling high-performance outdoor wear and casual wear, and that they are highly interested in clothes and in brands leading the Gorpcore trend. 3) As a result of the CONCOR algorithm, four significant groups were formed. The words that appear in each group are as follows. Group 1 - 'outdoor', 'Gorp', 'Normcore', 'hiking', 'functionality', 'new', 'sports', 'casual wear', 'activity', 'generation', 'collaboration'. Group 2 - 'fashion', 'trend', 'look', 'brand', 'style', 'shoes', 'ugly', 'item', 'trend', 'product', 'Salomon', 'padded jacket', 'stylishness', 'utilization', 'Winter', 'street', 'design', 'retro', 'popular', 'styling'. Group 3 - 'Gorpcore look', 'coordination', 'Musinsa', 'windbreaker', 'recommendation', 'Arcteryx', 'pants', 'man'. Group 4 - 'clothes' 'ahjussi', 'jacket', 'launching', 'spring', 'The North Face', 'collection', 'utility', 'jumper'. As a result, it can be seen that the Gorpcore is also regarded as a part of outdoor, fashion, coordination, and casual wear.

• 전기전자학회논문지
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• 제12권1호
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• pp.27-33
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• 2008

The demand of wireless communication is increased rapidly due to the development of wireless communication systems, and many people have the great interest about the "RF system". The trend of the RF audio system is to design the system with less power consumption. In this paper, we explain the Software Algorithm Design of RF systems that is suitable for low power consumption.

• 대한전기학회논문지
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• 제34권10호
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• pp.389-398
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• 1985

Recently maximum power demand of our country has become to be under the great in fluence of electric cooling and air conditioning demand which are sensitive to weather conditions. This paper presents the technique and algorithm to forecast the long-term maximum power demand considering the characteristics of electric power and weather variable. By introducing a weather load model for forecasting long-term maximum power demand with the recent statistic data of power demand, annual maximum power demand is separated into two parts such as the base load component, affected little by weather, and the weather sensitive load component by means of multi-regression analysis method. And we derive the growth trend regression equations of above two components and their individual coefficients, the maximum power demand of each forecasting year can be forecasted with the sum of above two components. In this case we use the coincident dry bulb temperature as the weather variable at the occurence of one-day maximum power demand. As the growth trend regression equation we choose an exponential trend curve for the base load component, and real quadratic curve for the weather sensitive load component. The validity of the forecasting technique and algorithm proposed in this paper is proved by the case study for the present Korean power system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 춘계학술대회 논문집 전기설비전문위원
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• pp.109-112
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• 2004

In this study, the applicability of SOM(Self Organizing Map) algorithm to partial discharge pattern recognition have been investigated. For the purpose, using acquired data from the artificial defects in GIS, SOM algorithm which has some advantages such as data accumulation ability and the degradation trend trace ability was compared with conventionally used BP(Back Propagation) algorithm. As a result, basically BP algorithm was found out to be better than SOM algorithm. Therefore, it is needed to apply SOM algorithm in combination with BP algorithm in order to improve on-site applicability using the advantages of SOM. Also, for the pattern recognition by use of PRPDA(Phase Resolved Partial Discharge Analysis) it is required the normalization of the PRPDA graph. However, in case of the normalization both BP and SOM algorithm have shown worse results, so that it is required further study to solve the problem.

• International Journal of Contents
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• 제10권1호
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• pp.29-35
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• 2014

This paper proposes an approach for visualizing research trends using theme maps and extra information. The proposed algorithm includes the following steps. First, text mining is used to construct a vector space of keywords. Second, correspondence analysis is employed to reduce high-dimensionality and to express relationships between documents and keywords. Third, kernel density estimation is applied in order to generate three-dimensional data that can show the concentration of the set of documents. Fourth, a cartographical concept is adapted for visualizing research trends. Finally, relative vitalization information is provided for more accurate research trend analysis. The algorithm of the proposed approach is tested using papers about Traditional Korean Medicine.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 추계학술발표논문집
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• pp.299-306
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• 2000

General definition of data mining is the knowledge discovery or is to extract hidden necessary information from large databases. Its technique can be applied into decision making, prediction, and information analysis through analyzing of relationship and pattern among data. One of the most important work is to find association rules in data mining. The objective of this paper is to find customer's trend using association rule from analysis of database and the result can be used as fundamental data for CRM(Customer Relationship Management). This paper uses Apriori algorithm and FoodMart data in order to find association rules.

• Journal of the Korean Statistical Society
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• 제15권1호
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• pp.31-45
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• 1986

It is often necessary to obtain some run orders in factorial designs which have a small number of factor level changes and a small linear time trend. In this paper we propose an algorithm to find optimal or near-optimal run orders for $2^4, 2^5, 3^2$ and $2\cdot 3^2$ factorial designs under the criterion that the number of factor level changes and the linear time trend should be simultaneously small.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1999년도 추계학술대회 논문집
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• pp.63-69
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• 1999

The research trend of the simulation optimization has been focused on exploring continuous decision variables. Yet, the research in discrete decision variable area has not been fully studied. A new research trend for optimizing discrete decision variables ha just appeared recently. This study, therefore, deals with a discrete simulation method to get the system evaluation criteria required for designing a complex probabilistic discrete event system and to search the effective and reliable alternatives to satisfy the objective values of the given system through a on-line, single run with the short time period. Finding the alternative, we construct an algorithm which changes values of decision variables and a design alternative by using the stopping algorithm which ends the simulation in a steady state of system. To avoid the loss of data while analyzing the acquired design alternative in the steady state, we provide background for estimation of an auto-regressive model and mean and confidence interval for evaluating correctly the objective function obtained by small amount of output data through simulation with the short time period. In numerical experiment we applied the proposed algorithm to (s, S) inventory system problem with varying Δt value. In case of the (s, S) inventory system, we obtained good design alternative when Δt value is larger than 100.