• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.504-506
• /
• 1999

In this paper, we propose a method which control parametric uncertainty systems using PID controller by fuzzy auto tuning. We get the error and the error change rate of plant output correspond to the initial value of parameter using the Ziegler-Nickols tuning and determine the new proportional gain$(K_p)$ and the integral time $(T_i)$ from fuzzy tuner by the error and error change rate of plant output as a membership function of fuzzy theory. The Fuzzy Auto-tuning algorithm for PID controller operate to adapt variable parameter of plant in parametric uncertainty systems. It is shown this method considerably improve the transient response at computer simulation.

• Korean Journal of Adult Nursing
• /
• v.20 no.1
• /
• pp.1-9
• /
• 2008

Purposes: This study examined uncertainty and nursing need according to illness phases(phase I, II, III) in cancer patients, and investigated relationships between uncertainty and nursing need. Methods: A cross-sectional descriptive study was conducted with a sample of 121 adult cancer patients treated in two hospitals. Results: As for the total score, the uncertainty was not significantly different across the subgroups by illness phase. As for the subscale score, however, two sub-scales of the uncertainty were different across the subgroups. 'The unpredictability' was highest in illness phase I and II groups, while 'the lack of information' was highest in the illness phase III group. Nursing need as the total score was not significantly different across the subgroups by illness phase. However, all subscale scores of the nursing need were significantly different across the subgroups. Educational need was highest in the illness phase I group; physical and emotional needs were highest in the illness phase III group. Uncertainty and nursing need were not related to each other at any illness phase. Conclusion: The results suggest that nursing need and uncertainty may change across illness phases. Clinicians need to consider this pattern in caring for cancer patients.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.55 no.4
• /
• pp.55-63
• /
• 2013

This study investigates the trends and uncertainty of the impacts of climate change on paddy rice production in the Geumho river basin. The Long Ashton Research Station stochastic Weather Generator (LARS-WG) was used to derive future climate data for the Geumho river basin from 15 General Circulation models (GCMs) for 3 Special Report on Emissions Scenarios (SRES) (A2, A1B and B1) included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. The Food and Agricultural Organization (FAO) AquaCrop, a water-driven crop model, was statistically calibrated for the 1982 to 2010 climate. The index of agreement (IoA), prediction efficiency ($R^2$), percent bias (PBIAS), root mean square error (RMSE) and a visual technique were used to evaluate the adjusted AquaCrop simulated yield values. The adjusted simulated yields showed RMSE, NSE, IoA and PBIAS of 0.40, 0.26, 0.76 and 0.59 respectively. The 5, 9 and 15 year central moving averages showed $R^2$ of 0.78, 0.90 and 0.96 respectively after adjustment. AquaCrop was run for the 2020s (2011-2030), 2050s (2046-2065) and 2090s (2080-2099). Climate change projections for Geumho river basin generally indicate a hotter and wetter future climate with maximum increase in the annual temperature of $4.5^{\circ}C$ in the 2090s A1B, as well as maximum increase in the rainfall of 45 % in the 2090s A2. The means (and ranges) of paddy rice yields are projected to increase by 21 % (17-25 %), 34 % (27-42 %) and 43 % (31-54 %) for the 2020s, 2050s and 2090s, respectively. The A1B shows the largest rice yield uncertainty in all time slices with standard deviation of 0.148, 0.189 and $0.173t{\cdot}ha^{-1}$ for the 2020s, 2050s and 2090s, respectively.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.226-226
• /
• 2015

The complex climate system regarding human actions is well represented through global climate models (GCMs). The output from GCMs provides useful information about the rate and magnitude of future climate change. Especially, the temperature variable is most reliable among other GCM outputs. However, hydrological variables (e.g. precipitation) from GCM outputs for future climate change contain too high uncertainty to use in practice. Therefore, we propose a method that simulates temperature variable with increasing in a certain level (e.g. 0.5oC or 1.0oC increase) as a global warming scenario from observed data. In addition, a hydrometeorological variable can be simulated employing block-wise sampling technique associated with the temperature simulation. The proposed method was tested for assessing the future change of the seasonal precipitation in South Korea under global warming scenario. The results illustrate that the proposed method is a good alternative to levy the variation of hydrological variables under global warming condition.

• Structural Engineering and Mechanics
• /
• v.29 no.5
• /
• pp.469-488
• /
• 2008

Finite element methods have often been used for structural analyses of various mechanical problems. When finite element analyses are utilized to resolve mechanical systems, numerical uncertainties in the initial data such as structural parameters and loading conditions may result in uncertainties in the structural responses. Therefore the initial data have to be as accurate as possible in order to obtain reliable structural analysis results. The typical finite element method may not properly represent discrete systems when using uncertain data, since all input data of material properties and applied loads are defined by nominal values. An interval finite element analysis, which uses the interval arithmetic as introduced by Moore (1966) is proposed as a non-stochastic method in this study and serves a new numerical tool for evaluating the uncertainties of the initial data in structural analyses. According to this method, the element stiffness matrix includes interval terms of the lower and upper bounds of the structural parameters, and interval change functions are devised. Numerical uncertainties in the initial data are described as a tolerance error and tree graphs of uncertain data are constructed by numerical uncertainty combinations of each parameter. The structural responses calculated by all uncertainty cases can be easily estimated so that structural safety can be included in the design. Numerical applications of truss and frame structures demonstrate the efficiency of the present method with respect to numerical analyses of structural uncertainties.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.162-165
• /
• 2004

The authors' previous study found an interannual covariability between actual evapotranspiration (ET) and the Normalized Difference Vegetation Index (NDVI) over northern Asia. This result suggested that vegetation controls interannual variation in ET. In this prior study, NDVI data from the Pathfinder AVHRR Land (PAL) dataset were analyzed. However, studies of NDVI interannual change are subject to uncertainty, because NDVI data often contain errors associated with sensor- and atmosphere-related effects. This study is aimed toward reducing this uncertainty by employing NDVI dataset, from the Global Inventory Monitoring and Modeling Studies (GIMMS) group, in addition to PAL. The analysis was carried out for the northern Asia region from 1982 to 2000. 19-year interannual change in PAL-NDVI and GIMMS-NDVI were both compared with interannual change in model-assimilated ET. Although the correlation coefficient between GIMMS-NDVI and ET is slightly less than for PAL-NDVI and ET, for both NDVI datasets the annual maximum correlation with ET occurs in June, which is near the central period of the growing season. A significant positive correlation between GIMMS-NDVI and ET was observed over most of the vegetated land area in June as well as PAL-NDVI and ET. These results reinforce the authors' prior research that indicates the control of interannual change in ET is dominated by interannual change in vegetation activity.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.6
• /
• pp.231-243
• /
• 2022

The objective of this study is to analyze the impact of conservative financial reporting on investment during uncertainty. It was assumed that during uncertainty conservative financial reporting can play an important role to improve investment decision-making. For our analysis, data sets from 2005-2020 of nonfinancial companies are used. To measure the impact of conservative financial reporting in the non-financial sector of Pakistan, Khan and Watts' (2009) model is applied. "Prospector" and "Defender" Business strategy is applied for measuring firm-level uncertainty. Investment is measured by adding the change in fixed assets (property, plant, and equipment). To check the robustness of conservative financial reporting, Givoly and Hayn's (2000) Negative Accruals measure is applied. To measure the robustness of uncertainty, environmental scanning and alertness technique is applied. According to environmental scanning and alertness technique, companies are divided into two groups named 'inert' and 'alert'. 'Inert' are those firms that are not scanning their environment, and 'alert' are those firms who continuously analyze their environment. The empirical estimations support our hypothesis. The empirical findings provide the proof that in the wake of uncertainty conservative financial reporting may facilitate to take optimal investment decisions in the developing economy of Pakistan. Our results provide critical and practical implications for investors, researchers, and standard setters.

• Journal of Korea Water Resources Association
• /
• v.48 no.10
• /
• pp.817-830
• /
• 2015

This study performed prediction of extreme rainfall uncertainty and its frequency analysis based on climate change scenarios by Coupled Model Intercomparison Project Phase 5 (CMIP5) for the selected nine-General Circulation Models (GCMs) in the near future (2011-2040) over the Korean Peninsula (KP). We analysed uncertainty of scenarios by multiple model ensemble (MME) technique using non-parametric quantile mapping method and bias correction method in the basin scale of the KP. During the near future, the extreme rainfall shows a significant gradually increasing tendency with the annual variability and uncertainty of extreme ainfall in the RCP4.5, and RCP8.5 scenarios. In addition to the probability rainfall frequency (such as 50 and 100-year return periods) has increased by 4.2% to 10.9% during the near future in 2040. Therefore, in the longer-term water resources master plan, based on the various climate change scenarios (such as CMIP5 GCMs) and its uncertainty can be considered for utilizing of the support tool for decision-makers in water-related disasters management.

• Journal of Climate Change Research
• /
• v.9 no.2
• /
• pp.143-156
• /
• 2018

Evapotranspiration is a key element in designing and operating agricultural hydraulic structures. The profound effect of climate change to local agro-hydrological systems makes it inevitable to study the potential variability in evapotranspiration rate in order to develop policies on future agricultural water management as well as to evaluate changes in agricultural environment. The APEX-Paddy model was used to simulate local evapotranspiration responses to climate change scenarios. Nine Global Climate Models(GCMs) downscaled using a non-parametric quantile mapping method and a Multi?Model Ensemble method(MME) were used for an uncertainty analysis in the climate scenarios. Results indicate that APEX-Paddy and the downscaled 9 GCMs reproduce evapotranspiration accurately for historical period(1976~2005). For future periods, simulated evapotranspiration rate under the RCP 4.5 scenario showed increasing trends by -1.31%, 2.21% and 4.32% for 2025s(2011~2040), 2055s(2041~2070) and 2085s(2071~2100), respectively, compared with historical(441.6 mm). Similar trends were found under the RCP 8.5 scenario with the rates of increase by 0.00%, 4.67%, and 7.41% for the near?term, mid?term, and long?term periods. Monthly evapotranspiration was predicted to be the highest in August, July was the month having a strong upward trend while. September and October were the months showing downward trends in evapotranspiration are mainly resulted from the shortening of the growth period of paddy rice due to temperature increase and stomatal closer as ambient $CO_2$ concentration increases in the future.

• Smart Structures and Systems
• /
• v.21 no.6
• /
• pp.727-740
• /
• 2018

Tuned mass dampers (TMDs) are passive damping devices widely employed to mitigate the pedestrian-induced vibrations on footbridges. The TMD design must ensure an adequate performance during the overall life-cycle of the structure. Although the TMD is initially adjusted to match the natural frequency of the vibration mode which needs to be controlled, its design must further take into account the change of the modal parameters of the footbridge due to the modification of the operational and environmental conditions. For this purpose, a motion-based design optimization method is proposed and implemented herein, aimed at ensuring the adequate behavior of footbridges under uncertainty conditions. The uncertainty associated with the variation of such modal parameters is simulated by a probabilistic approach based on the results of previous research reported in literature. The pedestrian action is modelled according to the recommendations of the Synpex guidelines. A comparison among the TMD parameters obtained considering different design criteria, design requirements and uncertainty levels is performed. To illustrate the proposed approach, a benchmark footbridge is considered. Results show both which is the most adequate design criterion to control the pedestrian-induced vibrations on the footbridge and the influence of the design requirements and the uncertainty level in the final TMD design.