• Journal of Information Management
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• v.21 no.1
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• pp.34-52
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• 1990

The probabilistic reasoning method using Bayesian theory is studied to use uncertain or incomplete knowledge in ways that take the uncertainty into account. This method presented for knowledge acquisition process of expert system to evaluate certainty degree of input knowledge.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.140-146
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• 1995

In case the uncertainty existing in a system is assumed to satisfy the matching condition and to be come-bounded. Y. H. Chen proposed an adaptive robust control algorithm which introduced adaptive sheme for a design parameter into robust deterministic controls. In this paper, the adaptive robust control algorithm is applied to the position tracking control of direct drive robots, and simulation and experimental studies are conducted to evaluate control performance.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.33-38
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• 1996

In this paper, we present a robust H\ulcorner control design method for parameter uncertain systems that have delay in both state and control input. Through a certain algebraic Riccati inequality approach, a state feedback controller is obtained. The proposed state feedback controller stabilizes parameter uncertain delay systems and guarantees disturbance attenuation within a prescribed level. An illustrative example is given to demonstrate the results of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1147-1155
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• 2014

Biomechanical models are often used to predict muscle and joint forces in the human body. For estimation of muscle forces, the body and muscle properties have to be known. However, these properties are difficult to measure and differ from person to person. Therefore, it is necessary to predict the change in muscle forces depending on the body and muscle properties. The objective of the present study is to develop a numerical procedure for estimating the muscle forces in the human lower extremity under uncertainty of body and muscle properties during rising motion from a seated position. The human lower extremity is idealized as a multibody system in which eight Hill-type muscle force models are employed. Each model has four degrees of freedom and is constrained in the sagittal plane. The eight muscle forces are determined by minimizing the metabolic energy consumption during the rising motion. Uncertainty analysis is performed using a first-order reliability method. The one-standard-deviation range of agonistic muscle forces is calculated to be about 150-300 N.

• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.316-329
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• 2008

Recently the increased attention pays on the processing of multiple, relatively low quantity, high value-added products resulted in adoption of batch process in the chemical process industry such as pharmaceuticals, polymers, bio-chemicals and foods. As there are more possibilities of the improvement of operations in batch process than continuous processes, a lot of effort has been made to enhance the productivity and operability of batch processes. But the chemical process industry faces a range of uncertainties factors such as demands for products, prices of product, lead time for the supply of raw materials and in the production, and the distribution of product. And global competition has made it imperative for the process industries to manage their supply chains optimally. Supply chain management aims to integrate plants with their supplier and customers so that they can be managed as a single entity and coordinate all input/output flows (of materials, information) so that products are produced and distributed in the right quantities, to the right locations, and at the right time.The objective of this study is to solve the purchase, distribution, production planning and scheduling problem, which minimizes the total costs of production, inventory, and transportation under uncertainty. And development of SCM model in chemical industry including batch mode operations. Through that, the enterprise can respond to uncertainty. Also integrated process optimal planning and scheduling model for manufacturing supply chain. The result shows that, the advantage of supply chain integration are quality matters seen by customers and suppliers, order schedules, flexibility, cost reduction, and increase in sales and profits. Also, an integration of supply chain (production and distribution system) generates significant savings by trading off the costs associated with the whole, rather than minimizing supply chain costs separately.

• Journal of Korea Water Resources Association
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• v.47 no.5
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• pp.435-446
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• 2014

Various drought indices developed from previous studies can not consider the inherent uncertainty of drought because they assess droughts using a pre-defined threshold. In this study, to consider inherent uncertainty embedded in monthly streamflow data, Hidden Markov Model (HMM) based drought index (HMDI) was proposed and then probabilistic assessment of hydrologic drought was performed using HMDI instead of using pre-defined threshold. Using monthly streamflow data (1966~2009) of Pyeongchang river and Upper Namhan river provided by Water Management Information System (WAMIS), applying the HMM after moving-averaging the data with 3, 6, 12 month windows, this study calculated the posterior probability of hidden state that becomes the HMDI. For verifying the method, this study compared the HMDI and Standardized Streamflow Index (SSI) which is one of drought indices using a pre-defined threshold. When using the SSI, only one value can be used as a criterion to determine the drought severity. However, the HMDI can classify the drought condition considering inherent uncertainty in observations and show the probability of each drought condition at a particular point in time. In addition, the comparison results based on actual drought events occurred near the basin indicated that the HMDI outperformed the SSI to represent the drought events.

• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.15-31
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• 2009

The next generation IT environment is expected to be an open computing environment based on Grid computing technologies, which allow users to access to any type of computing resources through networks. The open computing environment has benefits in aspects of resource utilization, collaboration, flexibility and cost reduction. Due to the variation in performance of open computing resources, however, resource allocation simply based on users' budget and time constraints often fails to meet the Service Level Agreement(SLA). This paper proposes the Mean-Absolute Deviation(MAD) portfolio optimization approach, in which service brokers consider the uncertainty of performance of resources, and compose resource portfolios that minimize the uncertainty. In order to investigate the effect of this approach, we simulate an open computing environment with varying uncertainty levels, users' constraints, and brokers' optimization strategies. The simulation result concludes threefolds. First, the MAD portfolio optimization improves the success ratio of delivering the required performance to users. Second, the success ratio depends on the accuracy in predicting the variability of performance. Thirdly, the measured variability can also help service brokers expand their service to cost-critical users by discounting the access cost of open computing resources.

• Journal of Korea Water Resources Association
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• v.40 no.1 s.174
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• pp.89-99
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• 2007

Uncertainty analysis is used to eliminate the climatic variables of input nodes and construct the model of an optimal type from COMBINE-GRNNM-GA(Type-1), which have been developed in this issue(2007). The input variable which has the lowest smoothing factor during the training performance, is eliminated from the original COMBINE-GRNNM-GA (Type-1). And, the modified COMBINE-GRNNM-GA(Type-1) is retrained to find the new and lowest smoothing factor of the each climatic variable. The input variable which has the lowest smoothing factor, implies the least useful climatic variable for the model output. Furthermore, The sensitive and insensitive climatic variables are chosen from the uncertainty analysis of the input nodes. The optimal COMBINE-GRNNM-GA(Type-1) is developed to estimate and calculate the PE which is missed or ungaged and the $ET_r$ which is not measured with the least cost and endeavor Finally, the PE and $ET_r$. maps can be constructed to give the reference data for drought and irrigation and drainage networks system analysis using the optimal COMBINE-GRNNM-GA(Type-1) in South Korea.

• Journal of IKEEE
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• v.21 no.4
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• pp.408-411
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• 2017

In this paper, we propose an integrated control system that measures neutrons, gamma ray, and x-ray. The proposed system is able to monitor and control the data measured and analyzed on the remote or network, and can monitor and control the status of each part of the system remotely without remote control. The proposed system consists of a gamma ray/x-ray sensor part, a neutron sensor part, a main control embedded system part, a dedicated display device and GUI part, and a remote UI part. The gamma ray/x-ray sensor part measures gamma ray and x-ray of low level by using NaI(Tl) scintillation detector. The neutron sensor part measures neutrons using Proportional Counter Detector(low-level neutron) and Ion Chamber Type Detector(high-level neutron). The main control embedded system part detects radiation, samples it in seconds, and converts it into radiation dose for accumulated pulse and current values. The dedicated display device and the GUI part output the radiation measurement result and the converted radiation amount and radiation amount measurement value and provide the user with the control condition setting and the calibration function for the detection part. The remote UI unit collects and stores the measured values and transmits them to the remote monitoring system. In order to evaluate the performance of the proposed system, the measurement uncertainty of the neutron detector was measured to less than ${\pm}8.2%$ and the gamma ray and x-ray detector had the uncertainty of less than 7.5%. It was confirmed that the normal operation was not less than ${\pm}15$ percent of the international standard.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1417-1423
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• 1999

Distribution system can experience the diverse events instantly and permanently. Also, it can experience high impedance fault or line drop under unbalanced situation, Accordingly, it is difficulty to identify the fault location because that data collected from distribution SCADA system may include uncertainty. This paper proposes an expert system, which can infer the faulted location the quickly and exactly for the diverse events in the distribution system. The expert system utilizes distribution SCADA function and collected data, especially, the monitoring mechanism for the normal open position switches is adopted newly in order to recognize the fault type exactly. Also, automated fault location diagnosis strategy is developed in order to minimize the spreading effect of fault obtained from the error of the system operator. The proposed strategy is implemented in C language. Especially, in order to prove the effectiveness of proposed expert system, the several scenario is simulated for the given model system. The real feeders are selected as model system for the simulation.