• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.795-835
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• 2019

Big data has been generated in various fields. Many companies have now tried to make profits by building a system capable of analyzing big data based on artificial intelligence (AI) techniques. Integrating AI technology has made analyzing and utilizing vast amounts of data increasingly valuable. In particular, demand forecasting with maximum accuracy is critical to government and business management in various fields such as finance, procurement, production and marketing. In this case, it is important to apply an appropriate model that considers the demand pattern for each field. It is possible to analyze complex patterns of real data that can also be enlarged by a traditional time series model or regression model. However, choosing the right model among the various models is difficult without prior knowledge. Many studies based on AI techniques such as machine learning and deep learning have been proven to overcome these problems. In addition, demand forecasting through the analysis of stereotyped data and unstructured data of images or texts has also shown high accuracy. This paper introduces important areas where demand forecasts are relatively active as well as introduces machine learning and deep learning techniques that consider the characteristics of each field.

• Journal of Energy Engineering
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• v.17 no.3
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• pp.145-152
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• 2008

Approaching to the era of high energy price and energy sources scarcity, the demand for governmental intervention to mitigate the short-term shocks is highly increasing. When any energy policy is implemented, double-side effects would be derived. To begin with positive aspect, by decreasing energy import, unnecessary currency outflow can be prevented and the resultant saved money will be appropriately allocated. Furthermore, industrial competitiveness will be assured by reducing use of expensive energy. On the contrary, inappropriate energy saving policy may lead to unexpected negative effects that would hinder improvement in productivity due to indiscreet replacing energy by equipments. In order to enhance effectiveness of energy policy, efforts should be made in advance to understand the energy use pattern of each industry sector which composes the economy. Therefore, in this study, an energy input-output method, one of the macroscopic approaches, is applied to analyze energy use patterns of each industry sector in Korea. Using this method, a quantitative assessment is performed to obtain the energy use intensity and the amount of energy uses with respect to energy types.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.177-181
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• 2009

Developing u-Public facilities for application u-City is to combine both the state-of-the art of the construction and ubiquitous computing and must be flexibly comprised of the facilities for the basic service of the building such as air conditioning, heating, lighting and electric equipments to materialize a new format of spatial planning and the public facilities inside or outside. Accordingly, in this paper we suggested the time pattern system for predicting the most basic power system loads for the basic service. To application the tim e pattern we applied SOM algorithm and k-means method and then clustered the data each weekday and each time respectively. The performance evaluation results of suggestion system showed that the forecasting system better the ARIMA model than the exponential smoothing method. It has been assumed that the plan for power supply depending on demand and system operation could be performed efficiently by means of using such power load forecasting.

• Design & Manufacturing
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• v.14 no.3
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• pp.63-70
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• 2020

As the consumer market in the VR(virtual reality) and the head-up display industry grows, the demand for 5-axis machines and grooving machines using on a ultra-precision machining increasing. In this paper, ultra-precision diamond tools satisfying the cutting edge width of 500 nm were developed through the process research of a focused ion beam. The material used in the experiment was a single-crystal diamond tool (SCD), and the equipment for machining the SCD used a focused ion beam. In order to reduce the influence of the Gaussian beam emitted from the focused ion beam, the lift-off process technology used in the semiconductor process was used. 2.9 ㎛ of Pt was coated on the surface of the diamond tool. The sub-micron tool with a cutting edge of 492.19 nm was manufactured through focused ion beam machining technology. Toshiba ULG-100C(H3) equipment was used to process fine-pattern using the manufactured ultra-precision diamond tool. The ultra-precision machining experiment was conducted according to the machining direction, and fine burrs were generated in the pattern in the forward direction. However, no burr occurred during reverse machining. The width of the processed pattern was 480 nm and the price of the pitch was confirmed to be 1 ㎛ As a result of machining.

• Journal of ILASS-Korea
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• v.21 no.4
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• pp.214-222
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• 2016

Changes in road infrastructure affect driving patterns and pollutant emission characteristics. we analyzed the changes in driving patterns and pollutant emission characteristics of the driving route via measured driving patterns at year 2009 and 2016. Since 2009, there has been an increase in population and traffic demand, including residential areas and industrial facilities. Traffic conditions were improved such as the opening of the highway Inter-Change to Seoul and the construction of underground driveway. As a result, the average vehicle speed increased. More detail comparisons have made on the changes of the underground driveway section and the crossroad section, which are expected to have significant changes in the transportation infrastructure. The vehicle speed distribution of the underground driveway changed from low speed to high speed, and the increase of the time spent at the high speed and high load caused the increase of NOx emissions. The vehicle speed also increased at the crossroad section, and the consequence NOx and $CO_2$ emissions decreased. It is mainly because the decreased time spent at idle, which results from the proper traffic demand management at this area.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1455-1462
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• 2018

As the interests in eco-friendly energy has increased, the interests in Electric Vehicles(EVs) are increasing as well. Moreover, due to the government's economic support for EVs, penetration level of it has rapidly increased. These sharp increases, however, induce various problems in distribution system, such as voltage/frequency variations, peak demand increasement, demand control, etc. To minimize these possible matters, lots of research have conducted. Nevertheless, most of it assumed extremely important factors, such as numbers and charging patterns of EVs. It inevitably results in errors in their research, and thus make it difficult to prevent the possible matters from EVs. In this paper, therefore, we use actual EVs charging data from KEPCO, and analysis and deduction of it were conducted. The simulations were carried out for four aspect(season, region, purpose).

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.547-550
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• 2011

플래시 메모리는 낮은 전력 소비와 높은 성능으로 인해 휴대용 기기에 널리 사용되고 있다. FTL은 플래시 내 자료를 관리하는 소프트웨어 계층으로 플래시 전체의 성능에 영향을 끼친다. 그 중 페이지 레벨 매핑 기법을 적용한 FTL은 유연성이 높고 속도가 빠르나 주소 변환 테이블의 크기가 큰 단점이 있다. 이를 해결하기 위해 자주 접근되는 영역의 매핑 주소만을 매핑 테이블 캐시에 올려놓는 Demand-based FTL(DFTL)이 제안되었다. DFTL 에서는 CMT(Cache Mapping Table)의 참조율이 떨어지는 경우 빈번한 플래시 메모리 접근 오버헤드가 발생하게 된다. 이러한 문제는 흔히 발생하는 일반적인 순차 접근에서조차 문제가 된다. 이에 본 논문에서는 저장 장치의 접근 패턴을 예측하여 CMT의 참조 엔트리를 미리 읽어오는 기법을 제안한다. 제안하는 기법은 저장 장치 접근 패턴의 순차성을 판단하여 연속된 매핑 주소를 미리 CMT에 올려놓고, 읽어오는 매핑 주소 엔트리의 양은 동적으로 관리한다. 추가적으로 CMT에서 발생하는 스래싱(thrashing) 을 파악하기 위해 쫓겨나는 희생 엔트리의 접근 여부를 분석하여 이를 활용하였다. 실험 결과에서 본 기법은 기존의 DFTL에 비해 약간의 공간 오버헤드와 함께 평균 50% 증가한 참조율을 보였다.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.772-774
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• 2005

Interstate electric power system, as an alternative for energy cooperation under regional economic bloc, has been hotly debated before progressing the restructure in electric power industry and rapidly expanded in many regions after 1990s. Especially, since northeast asia has strong supplementation in resource, load shape, fuel mix etc., electric power system interconnection in this region may bring considerable economic benefits. Moreover, since Korean electric power system has a great difficulty in a geographical condition to interrupt electricity transaction with other countries, it has been expanded as an independent system to supply all demand domestically. As a result, Korean electric power system makes considerable payment for maintaining system security and reliability and expands costly facilities to supply a temporary summer peak demand. Under this inefficiency, if there are electricity transactions with Russia via the North Korea route then economic electric power system operation may be achieved using seasonal and hourly differences in electricity price and/or load pattern among these countries. In this paper, we estimate price cap of transacted electricity via interstate electric power system in northeast asia. For this study, we perform quantitative economic analysis on various system interconnection scenarios.

• Korean Journal of Occupational Health Nursing
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• v.20 no.2
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• pp.119-129
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• 2011

Purpose: This study firstly examined the pattern and prevalence of drinking. Secondly, we investigated the association between various psychosocial work environment and problem drinking among Korean male workers in different age groups. Methods: The study sample was a weighted population of 3,289 (3,289 survey samples) men aged 20 to 64 years who responded to the 2006 Korean Working Condition Survey. Social support from colleague and supervisor, work autonomy, psychological wellbeing at work, and intellectual and emotional work demand were assessed. Results: After considering sociodemographic factors, smoking, occupational characteristics and other psychosocial work environment factors, problem drinking was associated with "intellectual work demand" for the 20~34 year old group. Social support from colleague and supervisor was significantly associated with problem drinking in the 35~49 year old group. For the 50~64 year old group, problem drinking was associated with 'work autonomy'. Conclusion: The present study clarified that certain psychosocial work environmental factors relate to problem drinking, and the association varies among different age groups.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2008.11a
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• pp.159-162
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• 2008

Recently, people's attitude toward residential environment has been changed from a simple shelter to a place affecting their mental function, and the change has increased demand for high quality of residential environment. Nevertheless, a number of unsatisfactory elements that do not meet the demand of residents for residential environment have continuously caused them to be exposed to stress. The purpose of this study is to explore the importance of residential environment by examining stress factors from the residential environment and finding out the effects of the residential environment stress on human emotional intelligence quotient and its application pattern. This study was carried out using not only self-report questionnaires with the Likert 5-point scale to find out the origin of residential environment stress factors, but the emotional intelligence quotient measuring device developed by Wong & Low (2000) to analyse correlations between the residential environment stress and emotional intelligence quotient. The questionnaire survey in this study was carried our among students of D College, and data were analysed using the statistical program SPSS, version 14.0.