• Title/Summary/Keyword: Surrogate Variable

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The Optimization of Muffin with Yam Powder Using Response Surface Methodology (마분말 첨가 머핀 제조조건 최적화)

  • Joo, Na-Mi;Lee, Sun-Mee;Jeong, Hee-Sun;Park, Sang-Hyun;Jung, Ah-Ram;Ryu, Seung-Yeon;Lee, Ji-Hee;Jung, Hyeon-A
    • Journal of the Korean Society of Food Culture
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    • v.23 no.2
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    • pp.243-251
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    • 2008
  • This purpose of this study was to develop a functional muffin by adding yam powder in the shape of a muffin as a partial surrogate for wheat flour. The yam has been found to be effective for liver and kidney function, as well as the digestion of protein, since it produces glucuronic acid in the body. Therefore, the purpose of this study was to determine the optimal mixing conditions of yam muffins by adjusting the amounts yam powder, butter, and sugar. The mixing conditions for the yam muffins included 3 categories: yam powder $(X_1)$, sugar $(X_2)$, and butter $(X_3)$ by Central Composite Design (CCD) which was optimized by Response Surface Methodology (RSM). The effects of the three variable additions on muffin quality were examined via physical and chemical experiments, such as the analysis of texture (hardness, cohesiveness, springiness, gumminess), coloration (lightness, redness, yellowness), and height. Lastly, we performed a sensory test, which revealed significant findings for gumminess, color, appearance, flavor, softness (p<0.05), redness, and overall quality (p<0.01). Consequently, the optimal mixing rate which best satisfied the sensory items were 34.35g of yam powder, 80.15 g of sugar, and 80.55 g of butter.

Continuity Simulation and Trend Analysis of Water Qualities in Incoming Flows to Lake Paldang by Log Linear Models (로그선형모델을 이용한 팔당호 유입지류 수질의 연속성 시뮬레이션과 경향 분석)

  • Na, Eun-Hye;Park, Seok-Soon
    • Korean Journal of Ecology and Environment
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    • v.36 no.3 s.104
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    • pp.336-343
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    • 2003
  • Two types of statistical models, simple and multivariate log linear models, were studied for continuity simulation and trend analysis of water qualities in incoming flows to Lake Paldang. Water quality is a function of one independent variable (flow) in the simple log linear model, and of three different variables (flow, time, and seasonal cycle) in multivariate model. The independent variables act as surrogate variables of water quality in both models. The model coefficients were determined by the monthly data. The water qualities included 5-day Biochemical Oxygen Demand ($BOD_5$), Total Nitrogen (TN), and Total Phosphorus (TP) measured from 1995 to 2000 in the South and the North branches of Han River and the Kyoungan Stream. The results indicated that the multivariate model provided better agreements with field measurements than the simple one in a31 attempted cases. Flow dependency, seasonality, and temporal trends of water quality were tested on the determined coefficients of the multivariate model. The test of flow dependency indicated that BOD concentrations decreased as the water flow increased. In TN and TP concentrations, however, there were no discernible flow effects. From the temporal trend analyses, the following results were obtained: 1) no trends on BOD at all three upstreams, 2) increase on TN at the South Branch and the Kyoungan Stream, 3)decrease on TN at the North Branch,4) no trends on TP at the North and the South Branches and 5) increase on TP at the Kyoungan Stream by 3 to 8% per years. The seasonality test showed that there were significant seasonal variations in all three water qualities at three incoming flows.

Linear Model Predictive Control of an Entrained-flow Gasifier for an IGCC Power Plant (석탄 가스화 복합 발전 플랜트의 분류층 가스화기 제어를 위한 선형 모델 예측 제어 기법)

  • Lee, Hyojin;Lee, Jay H.
    • Korean Chemical Engineering Research
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    • v.52 no.5
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    • pp.592-602
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    • 2014
  • In the Integrated Gasification Combined Cycle (IGCC), the stability of the gasifier has strong influences on the rest of the plant as it supplies the feed to the rest of the power generation system. In order to ensure a safe and stable operation of the entrained-flow gasifier and for protection of the gasifier wall from the high internal temperature, the solid slag layer thickness should be regulated tightly but its control is hampered by the lack of on-line measurement for it. In this study, a previously published dynamic simulation model of a Shell-type gasifier is reproduced and two different linear model predictive control strategies are simulated and compared for multivariable control of the entrained-flow gasifier. The first approach is to control a measured secondary variable as a surrogate to the unmeasured slag thickness. The control results of this approach depended strongly on the unmeasured disturbance type. In other words, the slag thickness could not be controlled tightly for a certain type of unmeasured disturbance. The second approach is to estimate the unmeasured slag thickness through the Kalman filter and to use the estimate to predict and control the slag thickness directly. Using the second approach, the slag thickness could be controlled well regardless of the type of unmeasured disturbances.

Relationship between PM2.5 Mass Concentrations and MODIS Aerosol Optical Thickness at Dukjuk and Jeju Island (제주도와 덕적도에서 관측된 초미세입자(PM2.5) 농도와 MODIS 에어러솔 광학두께와의 관계)

  • Lee, Kwon-Ho;Park, Seung-Shik
    • Korean Journal of Remote Sensing
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    • v.28 no.4
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    • pp.449-458
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    • 2012
  • Using the MODerate resolution Imaging Spectro-radiometer (MODIS) retrieved aerosol optical thickness (AOT) along with ground measurements of PM2.5 mass concentration, we assessed local air quality over Dukjuk and Jeju island and estimated possibility of satellite derived PM2.5 during nine intensive observation periods in 15 October 2005 - 24 October 2007. Averaged PM2.5 mass concentrations showed relatively variable as $25.61{\pm}22.92{\mu}g/m^3$ at Dukjuk and $17.33{\pm}10.79{\mu}g/m^3$ at Jeju. The maximum values of $188.89{\mu}g/m^3$ (Dukjuk) and $50.46{\mu}g/m^3$ (Jeju) were recorded during Asian dust storm day. Similarly, the maximum values of MODIS AOT were found as 3.73 (Gosan) and 1.14 (Jeju). Averaged MODIS AOTs at Dukjuk ($0.79{\pm}0.81$) were larger than that at Jeju ($0.42{\pm}0.24$). An empirical relationship between MODIS AOT and PM2.5 mass was obtained and results show that there was a good correlation between satellite and ground based values with a linear correlation coefficient of 0.85 at Dukjuk. The result clearly demonstrates that satellite derived AOT is a good surrogate for monitoring PM air quality over study area. However, meteorological and other ancillary datasets are necessary to further apply satellite data for air quality research.

The Statistical Correlation Between Continuous Driving Time and Drowsy Accidents (연속주행시간과 졸음사고간 통계적 상관관계 분석)

  • KIM, Ducknyung;KIM, Sujin;CHOI, Jaeheon;CHO, Jongseok
    • Journal of Korean Society of Transportation
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    • v.35 no.5
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    • pp.423-433
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    • 2017
  • During recent 5 years, it was recorded that 20% of total accident frequency and 30% of total number of death have been occurred due to drowsy driving. Drowsy driving accident is result from the loss of driving ability due to driver's accumulated fatigue. Continuous driving time can be measured as a surrogate variable to quantify the level of fatigue. The main purpose of this research is to investigate statistical correlation between the proportion of continuous driving vehicle (more than 2 hours) and the number of drowsy accidents. To carry this out, continuous driving time was measured using GPS route-guidance trajectory data. Also, accident frequency, traffic volume and segment length were collected to estimate safety performance function (SPF) for Jungbunearuk expressway in Korea. Through various types of estimated SPFs, statistical correlation was analyzed based on estimated statistical indices. This research can provide theoretical background for enforcement to regulate commercial vehicle driver's continuous driving time. In addition, throughout the trajectory data expansion, it is expected that strategy for anti-drowsy driving facilities installation can be established based on the suggested methodology.

Effect of input variable characteristics on the performance of an ensemble machine learning model for algal bloom prediction (앙상블 머신러닝 모형을 이용한 하천 녹조발생 예측모형의 입력변수 특성에 따른 성능 영향)

  • Kang, Byeong-Koo;Park, Jungsu
    • Journal of Korean Society of Water and Wastewater
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    • v.35 no.6
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    • pp.417-424
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    • 2021
  • Algal bloom is an ongoing issue in the management of freshwater systems for drinking water supply, and the chlorophyll-a concentration is commonly used to represent the status of algal bloom. Thus, the prediction of chlorophyll-a concentration is essential for the proper management of water quality. However, the chlorophyll-a concentration is affected by various water quality and environmental factors, so the prediction of its concentration is not an easy task. In recent years, many advanced machine learning algorithms have increasingly been used for the development of surrogate models to prediction the chlorophyll-a concentration in freshwater systems such as rivers or reservoirs. This study used a light gradient boosting machine(LightGBM), a gradient boosting decision tree algorithm, to develop an ensemble machine learning model to predict chlorophyll-a concentration. The field water quality data observed at Daecheong Lake, obtained from the real-time water information system in Korea, were used for the development of the model. The data include temperature, pH, electric conductivity, dissolved oxygen, total organic carbon, total nitrogen, total phosphorus, and chlorophyll-a. First, a LightGBM model was developed to predict the chlorophyll-a concentration by using the other seven items as independent input variables. Second, the time-lagged values of all the input variables were added as input variables to understand the effect of time lag of input variables on model performance. The time lag (i) ranges from 1 to 50 days. The model performance was evaluated using three indices, root mean squared error-observation standard deviation ration (RSR), Nash-Sutcliffe coefficient of efficiency (NSE) and mean absolute error (MAE). The model showed the best performance by adding a dataset with a one-day time lag (i=1) where RSR, NSE, and MAE were 0.359, 0.871 and 1.510, respectively. The improvement of model performance was observed when a dataset with a time lag up of about 15 days (i=15) was added.

Factors Affecting Basilar Artery Pulsatility Index on Transcranial Doppler (뇌혈류 초음파 검사에서 기저동맥 박동지수에 영향을 미치는 인자)

  • Jeong, Ho Tae;Kim, Dae Sik;Kang, Kun Woo;Nam, Yun Teak;Oh, Ji Eun;Cho, Eun Kyung
    • Korean Journal of Clinical Laboratory Science
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    • v.50 no.4
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    • pp.477-483
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    • 2018
  • Transcranial doppler is a non-invasive method that measures the blood flow velocity and the direction of cerebral blood vessels through the doppler principle. The pulsatility index is an index for measuring the transcranial doppler that reflects the distal vascular resistance and is used as an index for the presence and diffusion of cerebral small vessel diseases. The purpose of this study was to evaluate the risk factors affecting the basilar artery pulsatility index in ischemic stroke patients. From January 2014 to May 2015, 422 patients were selected by measuring the transcranial doppler pulsatility index, considering their basilar artery pulsatility index. Univariate analysis was performed using the basilar artery pulsatility index as a dependent variable. Multiple regression analysis was performed considering the factors affecting the pulsatility index as variables. Univariate analysis revealed age, presence of hypertension, presence of diabetes mellitus, presence of hyperlipidemia, and hematocrit (P<0.1) as factors. Multiple regression analysis showed statistically significant results with age (P<0.001), presence of diabetes (P=0.004), and presence of hyperlipidemia (P=0.041). The risk factors affecting the basilar artery pulsatility index of transcranial doppler were age, diabetes, and hyperlipidemia. Further research will be needed to increase the cerebral pulsatility index as a surrogate marker of the elderly, diabetes, and hyperlipidemia.

Development of a surrogate model based on temperature for estimation of evapotranspiration and its use for drought index applicability assessment (증발산 산정을 위한 온도기반의 대체모형 개발 및 가뭄지수 적용성 평가)

  • Kim, Ho-Jun;Kim, Kyoungwook;Kwon, Hyun-Han
    • Journal of Korea Water Resources Association
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    • v.54 no.11
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    • pp.969-983
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    • 2021
  • Evapotranspiration, one of the hydrometeorological components, is considered an important variable for water resource planning and management and is primarily used as input data for hydrological models such as water balance models. The FAO56 PM method has been recommended as a standard approach to estimate the reference evapotranspiration with relatively high accuracy. However, the FAO56 PM method is often challenging to apply because it requires considerable hydrometeorological variables. In this perspective, the Hargreaves equation has been widely adopted to estimate the reference evapotranspiration. In this study, a set of parameters of the Hargreaves equation was calibrated with relatively long-term data within a Bayesian framework. Statistical index (CC, RMSE, IoA) is used to validate the model. RMSE for monthly results reduced from 7.94 ~ 24.91 mm/month to 7.94 ~ 24.91 mm/month for the validation period. The results confirmed that the accuracy was significantly improved compared to the existing Hargreaves equation. Further, the evaporative demand drought index (EDDI) based on the evaporative demand (E0) was proposed. To confirm the effectiveness of the EDDI, this study evaluated the estimated EDDI for the recent drought events from 2014 to 2015 and 2018, along with precipitation and SPI. As a result of the evaluation of the Han-river watershed in 2018, the weekly EDDI increased to more than 2 and it was confirmed that EDDI more effectively detects the onset of drought caused by heatwaves. EDDI can be used as a drought index, particularly for heatwave-driven flash drought monitoring and along with SPI.

Factors Affecting International Transfer Pricing of Multinational Enterprises in Korea (외국인투자기업의 국제이전가격 결정에 영향을 미치는 환경 및 기업요인)

  • Jun, Tae-Young;Byun, Yong-Hwan
    • Korean small business review
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    • v.31 no.2
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    • pp.85-102
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    • 2009
  • With the continued globalization of world markets, transfer pricing has become one of the dominant sources of controversy in international taxation. Transfer pricing is the process by which a multinational corporation calculates a price for goods and services that are transferred to affiliated entities. Consider a Korean electronic enterprise that buys supplies from its own subsidiary located in China. How much the Korean parent company pays its subsidiary will determine how much profit the Chinese unit reports in local taxes. If the parent company pays above normal market prices, it may appear to have a poor profit, even if the group as a whole shows a respectable profit margin. In this way, transfer prices impact the taxable income reported in each country in which the multinational enterprise operates. It's importance lies in that around 60% of international trade involves transactions between two related parts of multinationals, according to the OECD. Multinational enterprises (hereafter MEs) exert much effort into utilizing organizational advantages to make global investments. MEs wish to minimize their tax burden. So MEs spend a fortune on economists and accountants to justify transfer prices that suit their tax needs. On the contrary, local governments are not prepared to cope with MEs' powerful financial instruments. Tax authorities in each country wish to ensure that the tax base of any ME is divided fairly. Thus, both tax authorities and MEs have a vested interest in the way in which a transfer price is determined, and this is why MEs' international transfer prices are at the center of disputes concerned with taxation. Transfer pricing issues and practices are sometimes difficult to control for regulators because the tax administration does not have enough staffs with the knowledge and resources necessary to understand them. The authors examine transfer pricing practices to provide relevant resources useful in designing tax incentives and regulation schemes for policy makers. This study focuses on identifying the relevant business and environmental factors that could influence the international transfer pricing of MEs. In this perspective, we empirically investigate how the management perception of related variables influences their choice of international transfer pricing methods. We believe that this research is particularly useful in the design of tax policy. Because it can concentrate on a few selected factors in consideration of the limited budget of the tax administration with assistance of this research. Data is composed of questionnaire responses from foreign firms in Korea with investment balances exceeding one million dollars in the end of 2004. We mailed questionnaires to 861 managers in charge of the accounting departments of each company, resulting in 121 valid responses. Seventy six percent of the sample firms are classified as small and medium sized enterprises with assets below 100 billion Korean won. Reviewing transfer pricing methods, cost-based transfer pricing is most popular showing that 60 firms have adopted it. The market-based method is used by 31 firms, and 13 firms have reported the resale-pricing method. Regarding the nationalities of foreign investors, the Japanese and the Americans constitute most of the sample. Logistic regressions have been performed for statistical analysis. The dependent variable is binary in that whether the method of international transfer pricing is a market-based method or a cost-based method. This type of binary classification is founded on the belief that the market-based method is evaluated as the relatively objective way of pricing compared with the cost-based methods. Cost-based pricing is assumed to give mangers flexibility in transfer pricing decisions. Therefore, local regulatory agencies are thought to prefer market-based pricing over cost-based pricing. Independent variables are composed of eight factors such as corporate tax rate, tariffs, relations with local tax authorities, tax audit, equity ratios of local investors, volume of internal trade, sales volume, and product life cycle. The first four variables are included in the model because taxation lies in the center of transfer pricing disputes. So identifying the impact of these variables in Korean business environments is much needed. Equity ratio is included to represent the interest of local partners. Volume of internal trade was sometimes employed in previous research to check the pricing behavior of managers, so we have followed these footsteps in this paper. Product life cycle is used as a surrogate of competition in local markets. Control variables are firm size and nationality of foreign investors. Firm size is controlled using dummy variables in that whether or not the specific firm is small and medium sized. This is because some researchers report that big firms show different behaviors compared with small and medium sized firms in transfer pricing. The other control variable is also expressed in dummy variable showing if the entrepreneur is the American or not. That's because some prior studies conclude that the American management style is different in that they limit branch manger's freedom of decision. Reviewing the statistical results, we have found that managers prefer the cost-based method over the market-based method as the importance of corporate taxes and tariffs increase. This result means that managers need flexibility to lessen the tax burden when they feel taxes are important. They also prefer the cost-based method as the product life cycle matures, which means that they support subsidiaries in local market competition using cost-based transfer pricing. On the contrary, as the relationship with local tax authorities becomes more important, managers prefer the market-based method. That is because market-based pricing is a better way to maintain good relations with the tax officials. Other variables like tax audit, volume of internal transactions, sales volume, and local equity ratio have shown only insignificant influence. Additionally, we have replaced two tax variables(corporate taxes and tariffs) with the data showing top marginal tax rate and mean tariff rates of each country, and have performed another regression to find if we could get different results compared with the former one. As a consequence, we have found something different on the part of mean tariffs, that shows only an insignificant influence on the dependent variable. We guess that each company in the sample pays tariffs with a specific rate applied only for one's own company, which could be located far from mean tariff rates. Therefore we have concluded we need a more detailed data that shows the tariffs of each company if we want to check the role of this variable. Considering that the present paper has heavily relied on questionnaires, an effort to build a reliable data base is needed for enhancing the research reliability.