• Title/Summary/Keyword: Long-term decomposition

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A study on the mathematical model of the long-term track tamping scheduling problem (궤도 다짐작업의 장기 일정계획문제에 관한 수리적 모형 고찰)

  • Oh Seog- Moon;Lee Ji-Ha;Park Bum Hwan;Lee Hee-up;Hong Soon-Heum
    • Proceedings of the KSR Conference
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    • 2005.11a
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    • pp.1130-1137
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    • 2005
  • This paper addresses the mathematical model of the long-term track tamping scheduling problem in the railway system. The proposed model is analyzed in problem size, then three solution approaches (relaxation, decomposition, and heuristic) are presented at the sketch level.

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Hierarchical Smoothing Technique by Empirical Mode Decomposition (경험적 모드분해법에 기초한 계층적 평활방법)

  • Kim Dong-Hoh;Oh Hee-Seok
    • The Korean Journal of Applied Statistics
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    • v.19 no.2
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    • pp.319-330
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    • 2006
  • A signal in real world usually composes of multiple signals having different scales of frequencies. For example sun-spot data is fluctuated over 11 year and 85 year. Economic data is supposed to be compound of seasonal component, cyclic component and long-term trend. Decomposition of the signal is one of the main topics in time series analysis. However when the signal is subject to nonstationarity, traditional time series analysis such as spectral analysis is not suitable. Huang et. at(1998) proposed data-adaptive method called empirical mode decomposition (EMD) . Due to its robustness to nonstationarity, EMD has been applied to various fields. Huang et. at, however, have not considered denoising when data is contaminated by error. In this paper we propose efficient denoising method utilizing cross-validation.

The Mechanical Properties of High Strength Concrete in Massive Structures

  • Park, Ki-Bong
    • Architectural research
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    • v.15 no.1
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    • pp.53-58
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    • 2013
  • High strength concrete is being used increasingly in mass structure projects. The purpose of this study is to investigate the influence of temperature during mixing, placing and curing on the strength development, hydration products and pore structures of high strength concrete in mass structures. The experiments were conducted with two different model walls, viz.: 1.5 m and 0.3 m under typical summer and winter weather conditions. The final part of this study deal with the clarification of the relationship between the long-term strength loss and the microstructure of the high strength concrete at high temperatures. Test results indicated that high elevated temperatures in mass concrete structures significantly accelerate the strength development of concrete at the early ages, while the long-term strength development is decreased. The long-term strength loss is caused by the decomposition of ettringite and increased the total porosity and amount of small pores.

Long-term Environmental Changes and the Interpretations from a Marine Benthic Ecologist's Perspective (I) - Physical Environment

  • Yoo Jae-Won;Hong Jae-Sang;Lee Jae June
    • Fisheries and Aquatic Sciences
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    • v.2 no.2
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    • pp.199-209
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    • 1999
  • Before investigating the long-term variations in macrobenthic communities sampled in the Chokchon macrotidal flat in Inchon, Korea, from 1989 to 1996, we need to understand how environmental factors in the area vary. As potential governing agents of tidal flat communities, abiotic factors such as mean sea level, seawater, air temperature, and precipitation were considered. Data for these factors were collected at equal intervals from 1976 or 1980 to 1996, and were analyzed using a decomposition method. In this analysis, all the above variables showed strong seasonal nature, and yielded a significant trend and cyclical variation. Positive trends were seen in the seawater and air temperatures, and based upon this relationship, it was found that the biological sampling period of our program has been carried out during warmer periods in succession. This paper puts forth some hypotheses concerning the response of tidal flat macrobenthos communities to the changing environment including mild winters in succession.

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Sensor Fusion of GPS/INS/Baroaltimeter Using Wavelet Analysis (GPS/INS/기압고도계의 웨이블릿 센서융합 기법)

  • Kim, Seong-Pil;Kim, Eung-Tai;Seong, Kie-Jeong
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.12
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    • pp.1232-1237
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    • 2008
  • This paper introduces an application of wavelet analysis to the sensor fusion of GPS/INS/baroaltimeter. Using wavelet analysis the baro-inertial altitude is decomposed into the low frequency content and the high frequency content. The high frequency components, 'details', represent the perturbed altitude change from the long time trend. GPS altitude is also broken down by a wavelet decomposition. The low frequency components, 'approximations', of the decomposed signal address the long-term trend of altitude. It is proposed that the final altitude be determined as the sum of both the details of the baro-inertial altitude and the approximations of GPS altitude. Then the final altitude exclude long-term baro-inertial errors and short-term GPS errors. Finally, it is shown from the test results that the proposed method produces continuous and sensitive altitude successfully.

Short-term Wind Power Prediction Based on Empirical Mode Decomposition and Improved Extreme Learning Machine

  • Tian, Zhongda;Ren, Yi;Wang, Gang
    • Journal of Electrical Engineering and Technology
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    • v.13 no.5
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    • pp.1841-1851
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    • 2018
  • For the safe and stable operation of the power system, accurate wind power prediction is of great significance. A wind power prediction method based on empirical mode decomposition and improved extreme learning machine is proposed in this paper. Firstly, wind power time series is decomposed into several components with different frequency by empirical mode decomposition, which can reduce the non-stationary of time series. The components after decomposing remove the long correlation and promote the different local characteristics of original wind power time series. Secondly, an improved extreme learning machine prediction model is introduced to overcome the sample data updating disadvantages of standard extreme learning machine. Different improved extreme learning machine prediction model of each component is established. Finally, the prediction value of each component is superimposed to obtain the final result. Compared with other prediction models, the simulation results demonstrate that the proposed prediction method has better prediction accuracy for wind power.

A Study on the Characteristics of Long-term Settlement for Solid Waste Landfill (폐기물매립지의 장기침하 특성에 관한 연구)

  • Park, Jeong Jun;Shin, Eun Chul;Kim, Dong Sik
    • Journal of the Society of Disaster Information
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    • v.4 no.2
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    • pp.52-66
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    • 2008
  • It has been a growing concern about reusing Sudokwon landfill 2nd site and other sanitary landfills located around the metropolitan areas. In this paper, settlement characteristics of Sudokwon landfill 2nd site were studied by analyzing the data collected over the period of six years. Three equations are combined in order to modeling the long-term settlement behavior of refuse landfill caused by mechanical secondary composition and secondary composition caused by the decomposition of biodegradable refuse. It is suggested that mechanical secondary composition is linear with respect to the logarithm of time. The models proposed by hyperbolic method and Gibson & Lo model, power creep law are considered to be suitable for the long-term prediction value of Sudokwon landfill 2nd site. The fifteen-year-period prediction value of hyperbolic method and Gibson & Lo model is considerably different from that of power creep law model. The average settlement for Block I in Sudokwon 2nd site is approximately 3.9m with 4 steps of final landfill stages.

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Litter Decomposition Process in Coffee Agroforestry Systems

  • Petit-Aldana, Judith;Rahman, Mohammed Mahabubur;Parraguirre-Lezama, Conrado;Infante-Cruz, Angel;Romero-Arenas, Omar
    • Journal of Forest and Environmental Science
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    • v.35 no.2
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    • pp.121-139
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    • 2019
  • Decomposition of litter is a function of various interrelated variables, both biotic and abiotic factors. Litter decomposition acts like a natural fertilizer play a prime role in maintaining the productivity and nutrient cycling in agroforestry systems. There are few studies of decomposition carried out in agroforestry systems with coffee; so it is necessary to perform more research work to fill the research gap, which will allow a better understanding of the management of the coffee agroforestry systems. This paper is based on the theoretical and conceptual aspects of leaf litter decomposition in agroforestry systems, emphasizing the combination with coffee cultivation and critically examined the role of the different factors involved in the decomposition. This study made a comparison of different investigations with regards to weight loss, decomposition rates (k), initial chemical composition, and release of the main nutrients. This study suggested that it is necessary to implement studies of decomposition and mineralization, and the microflora and fauna associated with these processes, so that serves as an important tool to develop a model for enabling a description of the short, medium, and long-term dynamics of soil nutrients in coffee agroforestry systems.

Prediction of Landfill Settlement Using Gas Generation Characteristics (매립장의 발생가스특성을 이용한 매립장 침하예측)

  • 안태봉;박대효;공인철
    • Journal of the Korean Geotechnical Society
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    • v.20 no.8
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    • pp.29-39
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    • 2004
  • The prediction of landfill settlement is very important for managing land properly, especially in small national land like Korea. It is difficult to express settlement using the consolidation theory because biochemical decomposition is main reason of settlement, and organic materials in landfill are decomposed far long time. In this study, LFG (Landfill Gas) generation characteristics are studied to find long-term settlement analysing model landfills. Two lysimeters are made; one is leachate recycled, and the other is not leachate recycled. The relationship between gas generation and settlement is analysed as a function of time. A mathematical gas generation model is suggested to predict long-term settlement due to biodegradation, and correction coefficient is recommended for long term settlement through model tests. The leachate recirculation system is more effective to accelerate landfill settlement. The appropriate coefficients of gas correction for non-recycled leachate model are 1.4 and 1.7 for recycled system from tests showing 22% of acceleration.

Analysis about Effect for Stock Price of Korea Companies through volatility of price of USA and Korea (미국과 한국의 가격변수 변화에 따른 한국기업 주가에 대한 영향분석)

  • 김종권
    • Proceedings of the Safety Management and Science Conference
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    • 2002.11a
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    • pp.321-339
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    • 2002
  • The result of variance decomposition through yield of Treasury of 30 year maturity of USA, S&P 500 index, stock price of KEPCO has 76.12% of impulse of KEPCO stock price at short-term horizon, but they have 51.40% at long-term horizon. After one year, they occupy 13.65%, and 33.25%. So their effects are increased. By the way, S&P 500 index and yield of Treasury of 30 year maturity of USA have relatively more effect for forecast of stock price oi KEPCO at short-term & long-term. The yield of Treasury of 30 year maturity of USA more than S&P 500 index have more effect for stock price of KEPCO. It is why. That foreign investors through fall of stock price of USA invest for emerging market is less than movement for emerging market of hedge funds through effect of fall of yield of Treasury of 30 year maturity of USA, according to relative effects for stock price of Korea companies. The result of variance decomposition through won/dollar foreign exchange rate, yield of corporate bond of 3 year maturity, Korea Stock Price index(KOSPI), stock price of KEPCO has 81.33% of impulse of KEPCO stock price at short-term horizon, but they have 41.73% at long-term horizon. After one year, they occupy 23.57% and 34.70%. So their effects are increased. By the way, KOSPI and won/dollar foreign exchange rate have relatively more effect for forecast of stock price of KEPCO at short-term & long-term. The won/dollar foreign exchange rate more than KOSPI have more effect for stock price of KEPCO. It is why. The recovery of economic condition through improvement of company revenue causes of rising of KOSPI. But, if persistence of low interest rate continues, fall of won/dollar foreign exchange rate will be more aggravated. And it will give positive effect for stock price of KEPCO. This gives more positive effect at two main reason. Firstly, through fall of won/dollar foreign exchange rate and rising of credit rating of Korea will be followed. Therefore, foreign investors will invest more funds to Korea. Secondly, inflow of foreign investment funds through profit of won/dollar foreign exchange rate and stock investment will be occurred. If appreciation of won against dollar is forecasted, foreign investors will buy won. Through this won, investors will do investment. Won/dollar foreign exchange rate is affected through external factors of yen/dollar foreign exchange rate, etc. Therefore, the exclusion of instable factors for foreign investors through rising of credit rating of Korea is necessary things.

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