• Journal of Forest and Environmental Science
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• v.39 no.3
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• pp.180-194
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• 2023

This study characterize, classify and evaluates the function of topography on spatial variability of some selected soil properties to assist in designing land management that support uniform agricultural production. The study site, an agricultural land, was part of the derived savanna zone in southwest Nigeria. Four soil profile pits each were established along two delineated toposequence and described following the FAO/UNESCO guidelines. Samples were collected from the identified genetic horizons. Properties of four soil series developed on different positions of the two delineated Toposequence viz upper, middle, lower slopes and valley bottom positions respectively were studied. The soil samples were analysed for selected physical and chemical properties and data generated were subjected to descriptive and inferential statistics. The results showed that soil colour, depth and texture varied in response to changes in slope position and drainage condition. The sand content ranged from 61 to 90% while the bulk density ranged between 1.06 g cm^-3 to 1.68 g cm^-3. The soils were neutral to very strongly acid with low total exchangeable bases. Available phosphorus value were low while the extractable micronutrient concentration varied from low to medium. Soils of Asejire and Iwo series mapped in the study area were classified as Typic isohyperthermic paleustult, Apomu series as Plinthic isohyperthermic paleustult and Jago series as Aquic psamment (USDA Soil Taxonomy). These soils were correlated as Lixisol, Plinthic Lixisol and Fluvisol (World Reference Based), respectively. Major agronomic constraints of the soils associations mapped in the study area were nutrient availability, nutrient retention, slope, drainage, texture, high bulk density and shallow depth. The study concluded that the soils were not homogenous, shows moderate spatial variation across the slope, had varying potentials for sustainable agricultural practices, and thus, the agronomic constraints should be carefully addressed and managed for precision agriculture.

• Korean Management Science Review
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• v.8 no.1
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• pp.3-11
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• 1991

Non-Stationary transition probabilities models which is incorporated into a Markov framework with exogenous variables to account for some of variability are discussed, and extended for alternative procedure. Also as an application of the methodology, the size change of aggregate time-series data on the planted system of agricultural crops is estimated, and evaluated for the precision of time-varying evolution statistically.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.495-498
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• 1996

Regression model with nested error structure interval estimations about variability on different stages are proposed. This article derives an approximate confidence interval on the variance in the first stage and an exact confidence interval on the variance in the second stage in two stage regression model. The approximate confidence interval is based on Ting et al. (1990) method. Computer simulation is provided to show that the approximate confidence interval maintains the stated confidence coefficient.

• Journal of Korean Society for Quality Management
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• v.16 no.1
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• pp.8-14
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• 1988

Because of demand pattern variability and Product Liability pursuance for products, it is necessary to convert from Product Liability Defence to Product Liability Prevention. For aggravation of company environment, automation, mechanization and FMS are required, to reduce quality cost in this situation, we present the following two alternatives. (1) We solidify the PL policy by process improvement. (2) We set up sensor equipment for defective detection in its early stage.

• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.165-194
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• 1999

Taguchi's parameter design seeks proper choice of levels of controllable factors (Parameters in Taguchi's terminology) that makes the qualify characteristic of a product optimal while making its variability small. This aim can be achieved by response surface techniques that allow flexibility in modeling and analysis. In this article, a collection of response surface modeling and analysis techniques is proposed to deal with the multiresponse optimization problem in experimentation with Taguchi's signal and noise factors.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.3
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• pp.135-150
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• 2012

This paper presents a portfolio model for a long-term power generation mix problem. The proposed portfolio model evaluates generation mix by considering the tradeoffs between the expected cost for power generation and its variability. Unlike conventional portfolio models measuring variance, we introduce Conditional Value-at-Risk (CVaR) in designing the variability with aims to considering events that are enormously expensive but are rare such as nuclear power plant accidents. Further, we consider uncertainties associated with future electricity demand, fuel prices and their correlations, and capital costs for power plant investments. To obtain an objective generation by each energy source, we employ the sample average approximation method that approximates the stochastic objective function by taking the average of large sample values so that provides asymptotic convergence of optimal solutions. In addition, the method includes Monte Carlo simulation techniques in generating random samples from multivariate distributions. Applications of the proposed model and method are demonstrated through a case study of an electricity industry with nuclear, coal, oil (OCGT), and LNG (CCGT) in South Korea.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.254-261
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• 2000

Soil chemical properties, relief of field surface, SPAD values and grain yield were investigated in a 0.5ha paddy field in 1999 to obtain basic field information for precision agriculture. Descriptive statistics of field information showed that the coefficient of variation ranged from 1.63% to 38.7%. Field information showed a high spatial dependence for within paddy field. The ranges of spatial dependence were from 15m to 60m, respectively. Kriged maps enable the visualization and comparison the spatial variability of field information. The causes of spatial variability of the field information could be explained rationally by a field management map. Grain yield was negatively correlated with pH, relief values, whereas, was positively correlated with total C, total N, C/N ratio, mineralizable N, available P and exchangeable K, Ca at the significant level of 1 %.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.75-83
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• 2009

PPC stands for the percentage of weekly assignments completed. It makes it possible to improve the performance of production planning and control systems. Recently, the cases of PPC application have been increasing because PPC is easy to apply to construction site. However, to evaluate the average of PPC or analyze PPC as time passes has some problem ; if PPC is the same, the average it is evaluated equally although there are variabilities in production system. Therefore, In order to evaluate the character of PPC in process of production this paper suggests the method of the evaluating PPC by using coefficient of variability besides PPC measurement.

• Korean Management Science Review
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• v.31 no.3
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• pp.1-12
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• 2014

This study suggests the two types DEA models such as DEA CCR model and Super Efficiency model to evaluate the value of a company and to apply them for the investments. 14 kinds of real data of companies such as EV/EBITDA, EPS growth rate, PCR, PER, dividend yield, PBR, stock price/net current asset, debt ratio, current ratio, ROE, operating margin, inventory turnover, accounts receivable turnover, and sales growth ratio were used as input variables of DEA models. 12 year data from December 30, 2000 up to December 30, 2012 were collected, and the data with negative, missing and 0 values were removed reflecting the characteristics of the DEA. In order to verify the effectiveness of the models, we compared the historical variability and rate of return of both models those of the market. Study results are as follows. First, two DEA models are more stable than market in terms of rate of return because the historical variability of both models are less than that of market. Second, Super Efficiency model is more stable than CCR model. Lastly, the cumulative rate of return of Super Efficiency model (434%) is greater than that of the CCR model (420%) and that of the market (269%).

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.140-140
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• 2022

Recently an accurate quantification of streamflow under various climatological and anthropogenic factors and separation of their relative contribution remains challenging, because variation in streamflow may result in hydrological disasters. In this study, we evaluated the factors responsible for variation in streamflow in Korean watersheds, quantified separately their contribution using different Budyko-based functions, and identified hydrological breakpoint points. After detecting that the hydrological break point in 1995 and time series were divided into natural period (1966-1995), and disturbed period (1996-2014). During the natural period variation in climate tended to increase change in streamflow. However, in the disturbed period both climate variation and anthropogenic activities tended to increase streamflow variation in the watershed. Subsequently, the findings acquired from different Budyko-based functions were observed sensitive to selection of function. The variation in streamflow was observed in the response of change in climatic parameters ranging 46 to 75% (average 60%). The effects of anthropogenic activities were observed less compared to climate variation accounts 25 to 54% (average 40%). Furthermore, the relative contribution was observed to be sensitive corresponding to Budyko-based functions utilized. Moreover, relative impacts of both factors have capability to enhance uncertainty in the management of water resources. Thus, this knowledge would be essential for the implementation of water management spatial and temporal scale to reduce the risk of hydrological disasters in the watershed.