• Journal of Soil and Groundwater Environment
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• v.12 no.3
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• pp.53-65
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• 2007

Appropriate representation of hydrologic boundaries in groundwater models is critical to the development of a reliable model. This paper examines how the model predictions are affected by the uncertainty in the conceptualization of the hydrologic boundaries including groundwater divides, streams, and the lower boundaries of the flow system. The problem is analyzed for a study area where a number of field data for model inputs were available. First, a groundwater flow model is constructed and calibrated for the area using the Visual Modflow code. Recharge rate is used for the unknown variable determined through the calibration process. Secondly, a series of sensitivity analyses are conducted to evaluate the effects of model uncertainties embedded in specifying boundary conditions for streams and groundwater divides and specifying lower boundary of the bedrock. Finally, this paper provides some guidelines and discussions on how to deal with such hydrologic boundaries in view of developing a reliable conceptual model for the groundwater flow system of Korea.

• Information Systems Review
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• v.11 no.3
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• pp.125-146
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• 2009

The emergence of open source software(OSS) with its most prominent advantages creates a vast interest among practitioners. A study on Linux, the most well-known OSS, estimated that it would cost as 5.4 billion Euros taking over 73,000 person-years if it had been developed by conventional means. However, Linux has achieved only 0.65 percent of the operating system market for individual users while Microsoft windows family counts for nearly 90 percent of the market. Much of the effort being spent in the development of OSS is going to waste and potential value that OSS can bring to users is not being realized. Adoption of OSS is often accompanied by the discontinuance of existing software that is already in place. If users resist changing, they may not adopt OSS. Using the case of Linux, this study examines user resistance to change from the commercial operating software to the free operating system. This study identifies six sub-types of switching costs (uncertainty, emotional, setup, learning, lost benefit, and sunk costs) and tests their effects on user resistance to change based on a survey of 201 users. The results show that user resistance to change has a negative impact on the adoption of OSS. Further, this study shows that uncertainty and emotional costs have significant effects on user resistance to change. Beyond previous research on technology adoption, this research contributes towards an understanding of the switching costs leading to user resistance to change and offers suggestions to OSS practitioners for developing strategies to improve the adoption of OSS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.59-69
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• 2018

In this paper, we present a robust beamforming design to tackle the weighted sum-rate maximization (WSRM) problem in a multicell multiple-input multiple-output (MIMO) - non-orthogonal multipleaccess (NOMA) downlink system for 5G wireless communications. This work consider the imperfectchannel state information (CSI) at the base station (BS) by adding uncertainties to channel estimation matrices as the worst-case model i.e., singular value uncertainty model (SVUM). With this observation, the WSRM problem is formulated subject to the transmit power constraints at the BS. The objective problem is known as on-deterministic polynomial (NP) problem which is difficult to solve. We propose an robust beam forming design which establishes on majorization minimization (MM) technique to find the optimal transmit beam forming matrix, as well as efficiently solve the objective problem. In addition, we also propose a joint user clustering and power allocation (JUCPA) algorithm in which the best user pair is selected as a cluster to attain a higher sum-rate. Extensive numerical results are provided to show that the proposed robust beamforming design together with the proposed JUCPA algorithm significantly increases the performance in term of sum-rate as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1433-1446
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• 2013

In this study, we proposed a methodology to develop Rating Curves for high water level using rainfall generation by the Monte Carlo Simulation (MCS) technique, optimized rainfall-runoff model, and flood routing model in an urban stream. The developed stage discharge Rating Curve based on observed data was contained flow measurement errors and uncertainties. The standard error ($S_e$) for observations was 0.056, and the random uncertainty ($2S_{mr}$) was analyzed by ${\pm}1.43%$ on average, and up to ${\pm}4.27%$. Moreover, it was found that the Rating Curve extensions by way of logarithmic and Stevens methods were overestimated to compare with the urban basin scale. Finally, we confirmed that the high water level extension by random generation of hydrological data using MCS can be reduced uncertainty of the high water level, and it will consider as a more reliable approach for high water level extension. In the near future, this results can be applied to real-time flood alert system for urban streams through construction of the high water level extension system using MCS procedures.

• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.139-151
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• 2010

A quasi-two-dimensional unsteady flow model was developed for simulating the flow in a river system including artificial storage pockets with side weirs. It is a multiply-connected network which combines channels and storage pockets. The channel flow is described by the one-dimensional Saint Venant equations, and the weir overflow flow by the cell continuity and stage-discharge relations. The model was applied to the Imjin river system including six artificial storage pockets. Design flood peak reduction due to storage pockets is not sensitive to the side weir discharge coefficient. Storage pockets downstream are less effective than upstream ones in reducing peak stage as the backwater effect becomes more dominant. Simulated flood control effect is highly sensitive to the roughness coefficient. The uncertainty due to the roughness coefficient increases as the weir crest elevation gets higher. Because the best design alternative varies with the roughness coefficient, proper estimation of it is essential to the design of side weirs. Moreover, uncertainty of the estimation needs to be considered in the design process.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.75-88
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• 2009

The main purpose of the current research is to introduce the alternative algorithm of the non-recursive batch filter based on the unscented transformation in which the linearization process is unnecessary. The presented algorithm is applied to the orbit determination of a low earth orbiting satellite and compared its results with those of the well-known Bayesian batch least squares estimation and the iterative UKF smoother (IUKS). The system dynamic equations consist of the Earth's geo-potential, the atmospheric drag, solar radiation pressure and the lunar/solar gravitational perturbations. The range, azimuth and elevation angles of the satellite measured from ground stations are used for orbit determination. The characteristics of the non recursive unscented batch filter are analyzed for various aspects, including accuracy of the determined orbit, sensitivity to the initial uncertainty, measurement noise and stability performance in a realistic dynamic system and measurement model. As a result, under large non-linear conditions, the presented non-recursive batch filter yields more accurate results than the other batch filters about 5% for initial uncertainty test and 12% for measurement noise test. Moreover, the presented filter exhibits better convergence reliability than the Bayesian least squares. Hence, it is concluded that the non-recursive batch filter based on the unscented transformation is effectively applicable for highly nonlinear batch estimation problems.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.341-351
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• 2008

Since the damage from the torrential rain increases recently due to climate change and global warming, the significance of flood forecasting and warning becomes important in medium and small streams as well as large river. Through the preprocess and main processes for estimating runoff, diverse errors occur and are accumulated, so that the outcome contains the errors in the existing flood forecasting and warning method. And estimating the parameters needed for runoff models requires a lot of data and the processes contain various uncertainty. In order to overcome the difficulties of the existing flood forecasting and warning system and the uncertainty problem, ANFIS(Adaptive Neuro-Fuzzy Inference System) technique has been presented in this study. ANFIS, a data driven model using the fuzzy inference theory with neural network, can forecast stream level only by using the precipitation and stream level data in catchment without using a lot of physical data that are necessary in existing physical model. Time series data for precipitation and stream level are used as input, and stream levels for t+1, t+2, and t+3 are forecasted with this model. The applicability and the appropriateness of the model is examined by actual rainfall and stream level data from 2003 to 2005 in the Tancheon catchment area. The results of applying ANFIS to the Tancheon catchment area for the actual data show that the stream level can be simulated without large error.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.239-248
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• 2024

Radiation therapy uses high energy, which can have side effects on the human body. Therefore, it is important to ensure that the appropriate dose is set for irradiation and to have confidence in the radiation produced by the generator. The EPR/Alanine dosimetry system is characterized by water equivalence, dose response linearity, and low fading, which makes it useful for quality control of radiation therapy equipment. In this study, we compared the signal and dose response curves of EPR/Alanine dosimetry by mass of alanine using 6 MV energy of a LINAC. An alanine dosimeter and EPR spectrometer from Burker, and a LINAC from Elekta, were used. A dose response curve and a 1st order regression equation were constructed from the irradiated dose and the EPR signal from the alanine dosimeter. We compared the signal magnitude and dose response curve with mass and checked the confidence through the measurement uncertainty of the dose response curve. As a result, it was found that the magnitude of the EPR signal increased by about 1.3 times at 64.5 mg, and the sensitivity of the dose response curve increased as the mass increased. The measurement uncertainty was evaluated to be between 5.84 % and 8.93 %. Through this study, it is expected that the EPR/alanine dosimetry system can be applied to the quality assurance and quality control of a LINAC.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.2
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• pp.164-170
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• 2002

Sliding mode control, as a typical method of variable structure control, has the robust characteristics for the uncertainty and the disturbance of the nonlinear system. Because, however, sliding mode control input includes a sign function that Is discontinuous on the predefined switching surface, its applications are primarily limited by the need of alleviation or reduction of chattering. In this paper, we propose a chattering alleviation strategy based on a special nonlinear function and a fuzzy system. By using the proposed control scheme, we can reduce the steady state error. Its tracking performance is as fast as that of conventional method using the fixed boundary layer. Especially, in the proposed method, we can adjust the trade-off between the steady state error and the degree of chattering by regulating the proper range of the output variable of the fuzzy system. To verify the validity of the proposed algorithm, the analysis of the control method using the fixed boundary layer and the computer simulations are shown to compare with them.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1603-1623
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• 2020

Multiple Mobile Robots System (MMRS) has shown many attractive features in lots of real-world applications that motivate their rapid and wide diffusion. In MMRS, the Cooperative Localization (CL) is the basis and premise of its high-performance task. However, the statistical characteristics of the system noise should be already known in traditional CL algorithms, which is difficult to satisfy in actual MMRS because of the numerous of disturbances form the complex external environment. So the CL accuracy will be reduced. To solve this problem, an improved Adaptive Active Cooperative Localization (A²CL) algorithm based on information optimization strategy for MMRS is proposed in this manuscript. In this manuscript, an adaptive information fusion algorithm based on the variance component estimation under Extended Kalman filter (VCEKF) method for MMRS is introduced firstly to enhance the robustness and accuracy of information fusion by estimating the covariance matrix of the system noise or observation noise in real time. Besides, to decrease the effect of observation uncertainty on CL accuracy further, an observation optimization strategy based on information theory, the Model Predictive Control (MPC) strategy, is used here to maximize the information amount from observations. And semi-physical simulation experiments were carried out to verity the A²CL algorithm's performance finally. Results proved that the presented A²CL algorithm based on information optimization strategy for MMRS cannot only enhance the CL accuracy effectively but also have good robustness.