• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.307-316
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• 2009

In this paper, the spatiotemporal data mining methodology for detecting a cycle of power consumption pattern with the change of time and spatial was proposed, and applied to the power consumption data collected by GIS-AMR system with an aim to use its resulting knowledge in real world applications. First, partial clustering method was applied for cluster analysis concerned with the aim of customer's power consumption. Second, the patterns of customer's power consumption data which contain time and spatial attribute were detected by 3D cube mining method. Third, using the calendar pattern mining method for detection of cyclic patterns in the various time domains, the meanings and relationships of time attribute which is previously detected patterns were analyzed and predicted. For the evaluation of the proposed spatiotemporal data mining, we analyzed and predicted the power consumption patterns included the cycle of time and spatial feature from total 266,426 data of 3,256 customers with high power consumption from Jan. 2007 to Apr. 2007 supported by the GIS-AMR system in KEPRI. As a result of applying the proposed analysis methodology, cyclic patterns of each representative profiles of a group is identified on time and location.

• Journal of Family Resource Management and Policy Review
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• v.8 no.1
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• pp.101-116
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• 2004

This study analyze using pattern of the Korean elderly leisure time to know their leisure lifestyle. In order to do this study, we analysed the time use dairy which were collected by Korean National Statistical Office in 1999 and analysis of data was done through mean of time, percentage of acting people hourly. The result of this study were as follows : 1) The elderly spend leisure time average 6 hours 34 minute in a day and enjoy leisure activities from A.M. 11:00 to P.M. 12:00 and from P.M. 8:00 to P.M:. 10:00 mainly. 2) The elderly spend leisure time for acquaintance, using mass media, sports leisure activity and dilettante life. Especially the elderly associate with more others than their family, use more TV than others and spend time for break and amusement as dilettante life.

• Journal of KIISE:Software and Applications
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• v.37 no.7
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• pp.584-589
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• 2010

The dynamic time warping algorithm generally used in time series pattern recognition spends most of the time in generating the correlation table, and it establishes the global path constraint to reduce the corresponding time complexity. However, the constraint restrains just in terms of the time axis, not considering the contents of input patterns. In this paper, we therefore propose an efficient branch and bound dynamic time warping algorithm which sets the global constraints by adaptively reflecting the patterns. The experimental results show that the proposed method outperforms conventional methods in terms of the speed and accuracy.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.601-608
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• 2021

This study was conducted using data from the 2019 National Statistical Office's Life Time Survey, It was to investigate the effect of time-perception on the time-use pattern of 594 single middle-aged women in the city. This study found that there were differences of time management for daily behaviors between the insufficiently-percieved group and the sufficiently-percieved group. The both spent the most time with personal management. Secondly, the sufficiently-perceived group spent the more time with leisure activities than the insufficiently one did; the insufficiently-perceived one did the more work than the sufficiently-perceived one. The founding suggested the difference of time-use pattern by time-perception of the middle-aged women in the city. Also, the leisure activities and work were key factors to understand the daily life of the city-living middle-aged women.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.87-92
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• 2019

This paper describes the pattern analysis for data of the factory energy consumption by using machine learning method. While usual statistical methods or approaches require specific equations to represent the physical characteristics of the plant, machine learning based approach uses historical data and calculate the result effectively. Although rule-based approach calculates energy usage with the physical equations, it is hard to identify the exact equations that represent the factory's characteristics and hidden variables affecting the results. Whereas the machine learning approach is relatively useful to find the relations quickly between the data. The factory has several components directly affecting to the electricity consumption which are machines, light, computers and indoor systems like HVAC (heating, ventilation and air conditioning). The energy loads from those components are generated in real-time and these data can be shown in time-series. The various sensors were installed in the factory to construct the database by collecting the energy usage data from the components. After preliminary statistical analysis for data mining, time-series clustering techniques are applied to extract the energy load pattern. This research can attributes to develop Factory Energy Management System (FEMS).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1792-1798
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• 2010

Home Gateway is always on for continuous services of home networks. Ubiquitous home networks are extended. so power consumption of home gateways increases by geometric progression. Our algorithm is for home gateway to sleep, listen or wakeup according to network traffic adaptively, as well as to keep always-on service. To do this, it traces the accumulated average of previous sleep periods. In addition to this basic algorithm, we make the profiles for user's living pattern per the day to reflect network usages in detail and adaptively. As the simulation results by comparing with overall accumulated average and per-day accumulated average, in case of the overall accumulated average, the difference the estimation and real value is distributed from 0.43% to 4%. In contrast of this, in case of the per-day accumulated average is distributed from 0.06% to 2%. From this results, we know the profiling of per-day usage pattern can help reduce the difference of the real sleep period and the estimated sleep period.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2B
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• pp.111-119
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• 2011

As Green-IT has attracted a lot of attention in recent years, many researches have been interested in reducing the energy consumption of network equipments. In this paper, we analyze the energy saving ratio and delay performance according to various traffic patterns and burst assemble algorithms in OBS network with sleeping mode. To do this, we design the traffic generators, which are based on exponential distribution and Pareto distribution, and the router model, which has the time based and length based burst assemble algorithms by using OPNET modeler. Through OPNET simulator, we evaluate the energy saving performance in terms of the sleeping time, the number of transitions and packet delay.

• Electric Engineers Magazine
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• s.152
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• pp.58-59
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• 1995

공장설비, 빌딩설비 및 일반 산업설비에 사용되고 있는 전동기는 일정부하에서 연속적으로 사용되고 있을 뿐만 아니라, 단속적인 변동부하가 많고 특히 펜, 블로어, 펌프 등은 시간 및 계절에 따라 변동되고 있다. 일반적으로 최적의 유량(공기, 물)을 얻기 위해서 유량제어를 하고 있지만 종래부터 택하여 오던 패턴 및 조정변에 의한 방법에 비하여 인버터에 의한 회전수 제어에서는 소비전력이 대폭적으로 줄어든다.

• Vending industry
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• v.1 no.3 s.3
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• pp.96-99
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• 2001

사회생활을 하는 사람이라면 하루에 꼭 한번 정도는 하는 일이 있다. 출퇴근, 회의, 그리고 자판기 이용이 그것이다. 이른아침 출근을 위해 지하철 무인 패스 판매기를 이용하고 출근해서는 나른한 오후시간을 깨우기위해 으례 커피자판기를 이용하기 일수이고 여가시간을 이용해서는 친구들과 가벼운 스티커 사진촬영을 하는 등 우리의 자판기 이용 문화는 이미 현대인 너무나도 보편화되고 친숙해져버린 생활의 한 단면이 되어버렸다. 그렇다면 자판기는 언제쯤 인간의 일상사 속에 등장하기 시작했을까? 놀랍게도 자판기의 기원은 기원전 215년으로 거슬러 올라간다. 당시 이집트 사원에서 `성수(聖水)`를 판매하기 위해 만들어졌던 동전식 조작장치가 최초의 자판기라는게 정설로 받아들여온 사실로서 동전을 넣으면 투입된 동전이 받치고 있던 접시가 기울어져 그 기울기가 원래대로 돌아올 때까지 출구로 물이 나오는 원리를 이용한 것이다. 누가 만든것인지는 명확히 밝혀지지 않았으나 확실한 것은 자판기의 역사가 이미 기원전으로 거슬러 올라가고 인간생활에 뿌리내린 역사가 깊다는 것이다. 아무튼 이렇게 자판기가 나타난 이래로 17세기에 키산드리아 과학자 헤론이 쓴 책이 발견되기 이전까지 자판기는 잊혀진 발명품이었다. 그러나 그 책의 발견과 함께 사람들은 옛문헌 속의 발명품의 실용성에 관심을 기울이기 시작했고 차츰 영국의 선술집과 여관 담배 자판기가 등장하기 시작했으며 자판기는 식민지까지 보급될 정도로 선풍적인 인기를 끌었다. 19세기에 들어서는 담배 이외의 물건을 판매할 수 있는 자판기에 관심을 두기 시작했고, 자유주의 사상이 풍미하던 시절, 영국에서 나타난 금서(禁書)자판기에서부터 상업문화가 발달한 미국의 껌볼 자판기에 이르기까지 자판기는 점차로 그 영역을 넓혀갔고 또한 발전해 왔던 것이다. 그러나 자동판매기의 이러한 급속한 발전과 소비영역에서 역량의 강화는 비단 단순한 소비패턴의 변화에서 기인하는 것이라고는 보기 어렵다. 이는 노동집약적 산업구조에서 기술집약적 산업사회로의 전환에 따른 대량생산, 대량소비, 소비패턴 변화 등의 마케팅 환경의 변화에 따라 새로운 유통구조의 출현이 요망되었기 때문이었다. 따라서 슈퍼마켓, 쇼핑센터 등의 새로운 유통구조의 출현 외에도 인건비의 상승, 장소의 제한 및 구입의 편리성 등에 따라 무인 자동판매기의 등장은 필연적이었다고 볼수 있다. 이후 자판기의 판매상품의 범위는 더욱 넓어졌고 컵라면, 인형, 마음에 드는 음악만을 골라담는 CD,휴지,구두광택기,사진스티커,콘돔,장난감,담배,여행용품,스낵,아이스크림 등등 소액권과 손가락만 있으면 살 수 있는 물건의 가짓수는 헤아리기 어려울 정도가 되었으며, 그만큼 유통혁신의 기구로서 산업에 미치는 영향 역시 증대되고 있으며, 이러한 경향은 21세기 정보화,첨단화 경향에 발맞추어 더욱 진보된 형태로 발전해오고 있다.

• Journal of Broadcast Engineering
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• v.13 no.3
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• pp.319-327
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• 2008

The purpose of study is to investigate the customer oriented transaction environment for the customers' convenience, the plan of public policy in regard to the customer oriented T-Commerce, and the consumption pattern of customers' commercial transaction, necessary for the marketing strategy by analyzing the demand for the T-Commerce with the purchase intention and maximum willingness to pay according to the demographic factors, the pattern of commercial transaction, and the technology innovation types. The results showed that there were statistically significant relations between consumer's willingness price to pay for the T-commerce and the consumer's technology adoption types, monthly internet shopping amounts, and weekly TV-home shopping hours. The simulations on a basis of multiple regression analysis for the T-commerce were illustrated by those factors.