• 제목/요약/키워드: Seasonal Use

검색결과 464건 처리시간 0.033초

해수냉열원을 이용한 태양열계간축열시스템의 건물냉방 적용에 관한 연구 (A Study on the Application of the Solar Energy Seasonal Storage System Using Sea water Heat Source in the Buildings)

  • 김명래;윤재옥
    • 한국태양에너지학회:학술대회논문집
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    • 한국태양에너지학회 2009년도 추계학술발표대회 논문집
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    • pp.56-61
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    • 2009
  • Paradigm depending only on fossil fuel for building heat source is rapidly changing. Accelerating the change, as it has been known, is obligation for reducing green house gas coming from use of fossil fuel, i.e. reaction to United Nations Framework Convention on Climate Change. In addition, factors such as high oil price, unstable supply, weapon of petroleum and oil peak, by replacing fossil fuel, contributes to advance of environmental friendly renewable energy which can be continuously reusable. Therefore, current new energy policies, beyond enhancing effectiveness of heat using equipments, are to make best efforts for national competitiveness. Our country supports 11 areas for new renewable energy including sun light, solar heat and wind power. Among those areas, ocean thermal energy specifies tidal power generation using tide of sea, wave and temperature differences, wave power generation and thermal power generation. But heat use of heat source from sea water itself has been excluded as non-utilized energy. In the future, sea water heat source which has not been used so far will be required to be specified as new renewable energy. This research is to survey local heating system in Europe using sea water, central solar heating plants, seasonal thermal energy store and to analyze large scale central solar heating plants in German. Seasonal thermal energy store necessarily need to be equipped with large scale thermal energy store. Currently operating central solar heating system is a effective method which significantly enhances sharing rate of solar heat in a way that stores excessive heat generating in summer and then replenish insufficient heat for winter. Construction cost for this system is primarily dependent on large scale seasonal heat store and this high priced heat store merely plays its role once per year. Since our country is faced with 3 directional sea, active research and development for using sea water heat as cooling and heating heat source is required for seashore villages and building units. This research suggests how to utilize new energy in a way that stores cooling heat of sea water into seasonal thermal energy store when temperature of sea water is its lowest temperature in February based on West Sea and then uses it as cooling heat source when cooling is necessary. Since this method utilizes seasonal thermal energy store from existing central solar heating plant for heating and cooling purpose respectively twice per year maximizing energy efficiency by achieving 2 seasonal thermal energy store, active research and development is necessarily required for the future.

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GDAPS 앙상블 예보 시스템을 이용한 북서태평양에서의 태풍 발생 계절 예측 (Seasonal Prediction of Tropical Cyclone Frequency in the Western North Pacific using GDAPS Ensemble Prediction System)

  • 김지선;권혁조
    • 대기
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    • 제17권3호
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    • pp.269-279
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    • 2007
  • This study investigates the possibility of seasonal prediction for tropical cyclone activity in the western North Pacific by using a dynamical modeling approach. We use data from the SMIP/HFP (Seasonal Prediction Model Inter-comparison Project/Historical Forecast Project) experiment with the Korea Meteorological Administration's GDAPS (Global Data Assimilation and Prediction System) T106 model, focusing our analysis on model-generated tropical cyclones. It is found that the prediction depends primarily on the tropical cyclone (TC) detecting criteria. Additionally, a scaling factor and a different weighting to each ensemble member are found to be essential for the best predictions of summertime TC activity. This approach indeed shows a certain skill not only in the category forecast but in the standard verifications such as Brier score and relative operating characteristics (ROC).

Time series analysis of patients seeking orthodontic treatment at Seoul National University Dental Hospital over the past decade

  • Lim, Hyun-Woo;Park, Ji-Hoon;Park, Hyun-Hee;Lee, Shin-Jae
    • 대한치과교정학회지
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    • 제47권5호
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    • pp.298-305
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    • 2017
  • Objective: This paper describes changes in the characteristics of patients seeking orthodontic treatment over the past decade and the treatment they received, to identify any seasonal variations or trends. Methods: This single-center retrospective cohort study included all patients who presented to Seoul National University Dental Hospital for orthodontic diagnosis and treatment between January 1, 2005 and December 31, 2015. The study analyzed a set of heterogeneous variables grouped into the following categories: demographic (age, gender, and address), clinical (Angle Classification, anomaly, mode of orthodontic treatment, removable appliances for Phase 1 treatment, fixed appliances for Phase 2 treatment, orthognathic surgery, extraction, mini-plate, mini-implant, and patient transfer) and time-related variables (date of first visit and orthodontic treatment time). Time series analysis was applied to each variable. Results: The sample included 14,510 patients with a median age of 19.5 years. The number of patients and their ages demonstrated a clear seasonal variation, which peaked in the summer and winter. Increasing trends were observed for the proportion of male patients, use of non-extraction treatment modality, use of ceramic brackets, patients from provinces outside the Seoul region at large, patients transferred from private practitioners, and patients who underwent orthognathic surgery performed by university surgeons. Decreasing trends included the use of metal brackets and orthodontic treatment time. Conclusions: Time series analysis revealed a seasonal variation in some characteristics, and several variables showed changing trends over the past decade.

초등학생의 계절 변화 원인에 관한 지구본 활용 모델링 분석 (Analysis of Elementary Students Modeling Using the Globe on the Cause of Seasonal Change)

  • 석윤수;윤혜경
    • 한국초등과학교육학회지:초등과학교육
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    • 제41권4호
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    • pp.673-689
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    • 2022
  • 계절 변화를 이해하기 위해서는 3차원 공간 속에서 천체들의 관계를 이해하는 것이 필요하며 이를 위해 학생들이 직접 3차원 모델을 구성하여 사용하고, 평가 및 수정하는 모델링 활동이 중요하다. 이 연구에서는 초등학생이 지구본과 전구를 사용하여 계절 변화 원인으로서 지구의 운동을 3차원 공간에서 모델링하는 과정을 분석하였다. 초등학교 6학년 17명이 참여하였으며 모델링 수업은 계절 변화와 관련된 현상과 개념을 탐색한 뒤 현상의 원인이 되는 지구의 운동을 지구본과 전구를 사용하여 학생들이 직접 모델을 구성하고 이를 활용하여 계절 변화를 설명하는 과정으로 진행되었다. 학생들의 모델링 과정을 녹화한 비디오 자료, 학생들의 활동지, 사후 면담 전사본을 연구 자료로 사용하였고, 삼각 검증을 통해 자료의 신빙성을 확보하였다. 모델링 수준 분석 틀은 선행 연구를 기초로 구성하였으며 모델에 대한 이해와 모델링 실행뿐만 아니라 지구의 운동 관련 개념을 고려하여 구성하였다. 최종 확정된 분석틀에서는 3차원 모델링 수준을 1수준부터 3수준까지 구분하였고 각 수준에서 나타날 수 있는 학생의 수행을 구체화하였다. 연구 결과, 계절 변화를 설명하기 위한 초등학생의 지구본 활용 모델링 수준은 크게 두 가지로 나타났다. 지구의 자전 및 자전축의 기울기, 지구의 공전을 고려하였으나 경험적 증거를 활용하지 못하는 수준(2수준)과 지구의 자전 및 자전축의 기울기, 공전을 고려하고 경험적 증거를 활용하는 수준(3수준)으로 나타났다. 그러나 학생들이 경험적 증거를 활용하여 모델링을 하는 경우도 과학적 모델 구성으로 이어지지 못하였는데, 이 연구에서는 그 원인을 모델링 시 사용하는 도구의 특징과 관련지어 탐색하였다.

결합예측 방법을 이용한 인터넷 트래픽 수요 예측 연구 (A Study on Internet Traffic Forecasting by Combined Forecasts)

  • 김삼용
    • 응용통계연구
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    • 제28권6호
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    • pp.1235-1243
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    • 2015
  • 최근 들어 ICT 분야의 발달에 따라 데이터 사용량의 급격한 증가로 인터넷 트래픽 사용량 예측은 중요성은 강조되고 있다. 이러한 예측치를 적절한 트래픽 관리와 제어를 위한 계획 수립에 도움을 준다. 본 논문은, 5분 단위의 인터넷 트래픽 자료를 이용하여 결합 예측 모형을 제안하고자 한다. 이에 대하여 시계열의 대표적인 3개 모형인 Seasonal ARIMA, Fractional ARIMA(FARIMA), Taylor의 수정된 Holt-Winters 모형을 적용하였다. 모형 간 결합 예측 방법으로 예측치 간의 SA(Simple Average) 결합 예측 방법과 OLS(Ordinary Least Square)를 이용한 결합방법, ERLS(Equality Restricted Least Squares)를 이용한 결합 예측 방법, Armstrong(2001)이 제안한 MSE 기반 결합 예측 방법을 사용한다. 이에 따른 결과로서 3시간에서의 예측은 Seasonal ARIMA가 선택된 반면, 6시간 이후 예측에서는 결합 예측 방법이 좋은 예측 성능을 보여준다.

Multicity Seasonal Air Quality Index Forecasting using Soft Computing Techniques

  • Tikhe, Shruti S.;Khare, K.C.;Londhe, S.N.
    • Advances in environmental research
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    • 제4권2호
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    • pp.83-104
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    • 2015
  • Air Quality Index (AQI) is a pointer to broadcast short term air quality. This paper presents one day ahead AQI forecasting on seasonal basis for three major cities in Maharashtra State, India by using Artificial Neural Networks (ANN) and Genetic Programming (GP). The meteorological observations & previous AQI from 2005-2008 are used to predict next day's AQI. It was observed that GP captures the phenomenon better than ANN and could also follow the peak values better than ANN. The overall performance of GP seems better as compared to ANN. Stochastic nature of the input parameters and the possibility of auto-correlation might have introduced time lag and subsequent errors in predictions. Spectral Analysis (SA) was used for characterization of the error introduced. Correlational dependency (serial dependency) was calculated for all 24 models prepared on seasonal basis. Particular lags (k) in all the models were removed by differencing the series, that is converting each i'th element of the series into its difference from the (i-k)"th element. New time series is generated for all seasonal models in synchronization with the original time line & evaluated using ANN and GP. The statistical analysis and comparison of GP and ANN models has been done. We have proposed a promising approach of use of GP coupled with SA for real time prediction of seasonal multicity AQI.

이노베이션 상태공간 지수평활 모형을 이용한 시간별 전력 수요의 예측 (Hourly electricity demand forecasting based on innovations state space exponential smoothing models)

  • 원다영;성병찬
    • 응용통계연구
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    • 제29권4호
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    • pp.581-594
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    • 2016
  • 본 논문은 이노베이션 상태공간모형을 근간으로 기존의 지수평활법을 포괄할 수 있는 다중 계절형 모형을 소개한다. 특히 이 모형은, 기존 모형의 한계를 극복하고 동일한 계절 내의 다양성을 표현할 수 있도록 계절 성분을 행렬로 표현하는 정교한 구조를 가지고 있다. 이런 구조를 이용하면 비슷한 패턴을 가지는 계절 성분의 모수를 그룹별로 분류할 수 있다. 따라서, 다중 계절형 모형은 모수절약 원칙을 달성할 수 있으며 모형의 해석이 용이한 장점을 가지고 있을 뿐만 아니라, 잠재적으로 임의의 개수의 계절성도 수용 가능하다. 본 연구에서는 다중 계절형 모형을 이용하여 시간 단위로 관측된 한국 전력 수요량을 분석하고 예측한다. 특히, 시간별 전력 수요량의 계절성은 1일 및 1주일의 두 가지로 고려되었고 이를 토대로 유사한 요일들은 공통 계절로 그룹화하였다. 모형의 예측 성능을 평가하기 위하여 기존 지수평활법의 예측 결과와 비교하였다. 그 결과, 다중 계절형 모형이 기존 지수평활법보다 예측력이 우수함을 확인하였다.

봄 가을 피부특성 및 서시옥용산(西施玉容散) 저온숙성비누의 계절별 효능연구 (Study of Skin Characteristics in Spring·Autumn and seasonal efficacy of Seosiokyongsan CP soap)

  • 최상락;구진숙
    • 대한한의학회지
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    • 제40권2호
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    • pp.133-141
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    • 2019
  • Objectives: The condition of the skin is greatly influenced by seasonal changes. We wanted to know the seasonal change of skin condition and to find out the difference in the efficacy of Seoshiokyongsan (SSOOS) CP soap in spring and autumn. We are to help people who use soap to make a wise choice in choosing a cleanser according to the season. Methods: To investigate the seasonal skin condition, this experiment was conducted to examine the skin condition of spring and autumn in 20 students at A university. To compare the seasonal efficacy of Seosiokyongsan (SSOOS) CP soap, we had skin test 10 students in spring and autumn. We made herbal fermented soaps using SSOOS and distributed them to experiment participants. We let them wash their face in the morning and evening for 6 weeks using herbal fermented soap. Prior to the experiment, their skin condition was checked and assessed using A-ONE Smart One-Click Automatic Facial Diagnosis System three times at 3-week intervals. After the experiment, the changes of skin were measured and analyzed through facial analysis test. Results: In spring and autumn, the oil of T zone and U zone was significantly less and the water content was significantly higher in autumn than in spring. In the case of using the SSOOS CP soap, water content increased and oil content decreased in spring, oil content and elasticity increased in autumn. Conclusion: There is a difference in the skin condition according to the season and SSOOS CP soap showed difference in efficacy in spring and autumn. So we should pay attention to seasonal soap selection.

대전지역 대학생들에 의한 대학 급식소의 급식평가 (Assessment of University Food Service by Students in Daejeon Area)

  • 박상욱;하귀현
    • 한국식품영양학회지
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    • 제11권5호
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    • pp.528-535
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    • 1998
  • This study was conducted to provide some basic information for promoting efficiency in university food services. Subjects were 309 students of A, B and C university. The survey was done by questionaires, and the data were analyzed by SAS program. The quantity and nutritional values of food was evaluated as appropriate but temperature and freshness of food, use of seasonal food, variety of menu were indicated as unsatisfactory. Male students marked lower points on the price but female students gave lower scores for variety of menu and use of seasonl food. Employee hygiene fast service and neatness and kindness of workers were evaluated as appropriate but food sanitation and cleanness of dishes were indicated as unsatisfactory. A and B university students scored low marks on food sanitation. Female students scored higher marks on the employee's neatness. Arrangement of tables and chairs, location of returning utensils, location of counter use of menu board and ventilation facilities were scored as average but interior decoration and heating facilities were scored as low level. Students of a school scored low mark on the arrangement of tables, location of counter, heating facilities and interior decoration but students of B school scored low mark on the use of menu board. Calmness and comfortableness of dining hall was unsatisfactory but location of dining hall, serving time and waiting time were evaluated as appropriate. In conclusion improvements for temperature and freshness of food, use of seasonal food, variety of menu, food sanitation, cleanness of dishes, interior decoration, heating facility and resting area were indicated as necessary.

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Fault Detection in the Semiconductor Etch Process Using the Seasonal Autoregressive Integrated Moving Average Modeling

  • Arshad, Muhammad Zeeshan;Nawaz, Javeria Muhammad;Hong, Sang Jeen
    • Journal of Information Processing Systems
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    • 제10권3호
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    • pp.429-442
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    • 2014
  • In this paper, we investigated the use of seasonal autoregressive integrated moving average (SARIMA) time series models for fault detection in semiconductor etch equipment data. The derivative dynamic time warping algorithm was employed for the synchronization of data. The models were generated using a set of data from healthy runs, and the established models were compared with the experimental runs to find the faulty runs. It has been shown that the SARIMA modeling for this data can detect faults in the etch tool data from the semiconductor industry with an accuracy of 80% and 90% using the parameter-wise error computation and the step-wise error computation, respectively. We found that SARIMA is useful to detect incipient faults in semiconductor fabrication.