• Journal of Advanced Technology Convergence
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• v.1 no.1
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• pp.25-31
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• 2022

This study is a descriptive survey study conducted with the aim of analyzing differences in consumption patterns according to the personality types of the Enneagram and providing basic data that can be used for advertising and branding based on it. 43 people who explained the purpose of the study and agreed to participate were conveniently recruited. The research tools were investigated online with the type of personality of the Enneagram of Joo (2003) and the consumption pattern of Jeon (2013). The data analysis utilizes statistical methods such as descriptive statistics, frequency analysis, and one-way ANOVA in the IBM SPSS Statistics 23 program. For consumption patterns 1, 2, 3, and 6, there were statistically significant differences between personality types 1, 2, 3, 5, 7, and 9 (p<.050). Through this study, it was confirmed that consumption patterns vary depending on the type of personality of the Enneagram. The results of this study are expected to provide basic data in establishing effective strategies for branding and advertising of the design that consumers want.

• 한국태양에너지학회:학술대회논문집
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• 2008.04a
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• pp.336-341
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• 2008

For the last half a century, Korea has been experienced rapid economic growth and industrialization development, however they cause serious problems that environment pollution and energy shortage are appeared, and the biggest problem that we are now confronted are required solutions through all over the world. Now, Korea's energy consumption is the 10th in the whole world. Among them, energy for buildings, about 25% in the whole Energy which spend in Korea, is very serious. Especially, the energy consumption of school buildings which have heating & cooling system according to improvements of educational environment are rapidly increasing. These features are explicit in the University, Because it has lots of colleges and facilities for lecture, experiment, and research. Especially, electric power consumption account for 75 percent of energy consumption in educational institutions. Accordingly, it is important to understand and analyze the pattern of electricity energy consumption which is used. This study attempts to appoint the place which is one of university and to investigate the characteristics of energy consumption like electricity, gas, oil.

• Journal of the Korean Home Economics Association
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• v.27 no.4
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• pp.21-39
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• 1989

This paper is to determine the clothing and footwear of urban household consumption expenditures and an analysis of historical data from relevant literature. Particularly, time-series and cross sectional analysis techniques are adopted in analysing the patterns of clothing and footwear consumption expenditures of urban households. Finally, this paper estimates consumption expenditures in the future by comparing these revealed data with the Korea and Japan. Annual Report on the family Income and Expenditure Survey and M.R.A. in S.P.S.S. were used. The results can be summarized as follows: 1. The proportion of the clothing and footwear expenditure has decreased with the increase of income in urban household during 1976-1987. 2.1) Household consumption function by Income group, the Lower group is higher than the other group. 2) Household consumption function by Occupation of household head. Income elasticity estimation in administrative managerial workers is higher than the other group. 3) Household consumption function by Family size. Income elasticity estimation in 6 Persons is higher than the other group. But 4 Persons is higher in 1986. 4) Household consumption function by Age of household head. Income elasticity estimation in 50 Years and over is higher than the other group. 3. Comparison of characteristics of clothing and footwear consumption expenditures in Korea and Japan were M.R.A. Generally, the priority correlation order for Korea is Outwear, Sweaters and Shirt, Other clothing. For Japan, the order is Sweaters and Shirts, Underwear, Services.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.100-107
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• 1994

This article describes the hardware design scheme of Hamming MAXNET algorithm which is appropriate for binary pattern classification with minimum HD measurement between stimulus vector and storage vector. Circuit integration is profitable to Hamming MAXNET because the structure of hamming network have a few connection nodes over the similar neuro-algorithms. Designed hardware is the two-layered structure composed of hamming network and MAXNET which enable the characteristics of low power consumption and fast operation with biline volgate sensing scheme. Proposed Hamming MAXNET hardware was designed as quantize-level converter for simulation, resulting in the expected binary pattern convergence property.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1071-1078
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• 2014

Recently, information providing service using Big Data is being expanded. Big Data processing technology is actively being academic research to an important issue in the IT industry. In this paper, we analyze a skilled pattern of welder through Big Data analysis or extraction of welding based on R programming. We are going to reduce cost on welding work including weld quality, weld operation time by providing analyzed results non-skilled welder. Welding has a problem that should be invested long time to be a skilled welder. For solving these issues, we apply connection rules algorithms and regression method to much pattern variable for welding pattern analysis of skilled welder. We analyze a pattern of skilled welder according to variable of analyzed rules by analyzing top N rules. In this paper, we confirmed the pattern structure of power consumption rate and wire consumption length through experimental results of analyzed welding pattern analysis.

• The Research Journal of the Costume Culture
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• v.19 no.4
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• pp.674-696
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• 2011

Recent change in consumption patterns, casual clothing market share is growing. Awareness about the quality of the product for a variety of consumer needs are becoming. Accordingly, stretch material items that satisfy modern production and consumption is increasing. Among them, circular knit and woven fabrics with different characteristics have. However, this requires a consideration of the pattern graphics, this study is not getting enough. The purpose of this study is to develop a T-shirt using circular knit pattern for women in early twenties. Through the research of literature and a survey on T-shirt patterns of ready-to-wear manufactures and training for the pattern 4 T-shirt patterns were selected. Eight women in early twenties who fit the bodily standard were selected for the test. Subjects who were tested by wearing a T-shirt made of 30's cotton circular knit. Drafting method of T-shirt pattern which were closed to the optimum value three, derived from the five point rating scale outfit test were selected and the differences between the values of the selected drafting methods and the optimum three were verified. Passed by the test of 2 times and the final research T-shirt pattern was developed through adjusting from the optimum value three. The form which is whole is a silhouette closely in the body and drafting method the elasticity and drapery considered the quality of the circular knit where the characteristic is excellent.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.41-52
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• 2013

One of the obstacles preventing the Zigbee protocol from being widely used is the excessive power consumption of Zigbee devices in low bandwidth and low power requirement applications. This paper proposes a protocol that resolves the power efficiency problem. The proposed protocol reduces the power consumption of Zigbee devices in beacon-enabled networks without increasing the time taken by Zigbee peripherals to communicate with their coordinator. The proposed protocol utilizes a beacon control mechanism called a "sleep pattern," which is updated based on the previous event statistics. It determines exactly when Zigbee peripherals wake up or sleep. A simulation of the proposed protocol using realistic parameters and an experiment using commercial products yielded similar results, demonstrating that the protocol may be a solution to reduce the power consumption of Zigbee devices.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1511-1514
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• 2007

KORAIL is one of the biggest consumer in electric power market so it is necessary to investigate power consumption pattern and optimize power rates. This paper presents simulation program for electric power rates define program based on billing system database. Base on the substation annual power usage DB data, the characteristic of the substation power consumption are investigated and effective electrical billing system are compared each other. Through this program it is verified that we can save more then several hundred million won for a year. Also electric train air condition power consumption was measured to figure the method how to reduce peak energy consumption.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.10
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• pp.966-973
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• 2001

In this study, measurement and analysis of energy consumption of an office building with cleanroom and laboratory have been conducted. Data acquisition system for collecting energy consumption data of the whole building including air-conditioning equipments has been installed in a building located in Seoul. Data are collected for a period of one year in 2000 and analyzed for studying the energy consumption pattern. The percentage of electrical energy used for air-conditioning system is measured to be 46.1%. The collected data will serve as valuable information for diagnosing and improving the energy system of the building.

• Communications for Statistical Applications and Methods
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• v.27 no.6
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• pp.589-602
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• 2020

The development of smart grids has enabled the easy collection of a large amount of power data. There are some common patterns that make it useful to cluster power consumption patterns when analyzing s power big data. In this paper, clustering analysis is based on distance functions for time series and clustering algorithms to discover patterns for power consumption data. In clustering, we use 10 distance measures to find the clusters that consider the characteristics of time series data. A simulation study is done to compare the distance measures for clustering. Cluster validity measures are also calculated and compared such as error rate, similarity index, Dunn index and silhouette values. Real power consumption data are used for clustering, with five distance measures whose performances are better than others in the simulation.