• Journal of Korea Water Resources Association
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• v.49 no.10
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• pp.835-849
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• 2016

Accurate drought outlook and drought monitoring have been preceded recently to mitigate drought damages that further deepen. This study improved the limitations of the previous MSWSI (Modified Surface Water Supply Index) used in Korea and carried out probabilistic drought forecasts based on ensemble technique with the improved MSWSI. This study investigated available hydrometeorological components in Geum river basin and supplemented appropriate components (dam water level, dam release discharge) in addition to the four components (streamflow, groundwater, precipitation, dam inflow) usedin the previous MSWSI to each sub-basin. Although normal distribution was fitted in the previous MSWSI, the most suitable probabilistic distributions to each meteorological component were estimated in this study, including Gumbel distribution for precipitation and streamflow data; 2-parameter log-normal distribution for dam inflow, water level, and release discharge data; 3-parameter log-normal distribution for groundwater. To verify the improved MSWSI results using historical precipitation and streamflow, simulated drought situations were used. Results revealed that the improved MSWSI results were closer to actual drought than previous MSWSI results. The probabilistic forecasts based on ensemble technique with improved MSWSI were performed and evaluated in 2006 and 2014. The accuracy of the improved MSWSI was better than the previous MSWSI. Moreover, the drought index of actual drought was included in ranges of drought forecasts using the improved MSWSI.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1347-1353
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• 2004

With respect to the researches of the optical flying head(OFH) , the head-gimbal assembly should be analyzed to guarantee the stable fabrication and the characteristics of shock resistance. The suitable design is proved through the Probabilistic analysis of the design parameters and material properties of the model. Probabilistic analysis is a technique that be used to assess the effect of uncertain input parameters and assumptions on your analysis model. Using a probabilistic analysis you can find out how much the results of a finite elements analysis are affected by uncertainties in the model. Another factor is analysis of the dynamic shock analysis. For the mobile application, one of the important requirements is durability under severe environmental condition, especially, resistance to mechanical shock. An important challenge in the disk recording is to improve disk drive robustness in shock environments. If the system comes in contact with outer shock disturbance. the system gets critical damage in head-gimbal assembly or disk. This paper describes probabilistic and dynamic shock analysis of head-gimbal assembly in micro MO drives using OFH slider.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.112-115
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• 2001

This paper illustrates a new nodal effective load model for nodal probabilistic production cost simulation of the load point in a composite power system. The new effective load model includes capacities and uncertainties of generators as well as transmission lines. The CMELDC based on the new effective load model at HLII has been developed also. The CMELDC can be obtain from convolution integral processing of the outage capacity probabilistic distribution function of the fictitious generator and the original load duration curve given at the load point. It is expected that the new model for the CMELDC proposed. In this study will provide some solutions to many problems based on nodal and decentralized operation and control of an electric power systems under competition environment in future. The CMELDC based on the new model at HLII will extend the application areas of nodal probabilistic production cost simulation, outage cost assessment and reliability evaluation etc. at load points. The characteristics and effectiveness of this new model are illustrated by a case study of a test system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.406-411
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• 2003

One of the trends on information storage device is focused on the development of micro-optical devices with OFH (Optical Flying Head). Many different types of sliders for OFH and optical component systems have been introduced in the literature. However, the important issue on the mechanical system, which consists of suspension, swing arm and VCM (Voice Coil Motor) part has not been discussed up to date. In this research, we analyses the suspension, which is used for the small form factor MO drive. The analysis is in process two ways. One is probabilistic analysis, another is dynamic shock analysis. Probabilistic analysis is a technique you can use to assess the effect of uncertain input parameters and assumptions on your analysis model. Using a probabilistic analysis you can and out how much the results of a finite elements analysis are affected by uncertainties in the model. Dynamic shock analysis is used for the mobile applications. The mechanical robustness of the suspension simulating the shock responses of a disk-suspension is proposed in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.154-160
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• 2001

For major structural components periodic inspections and integrity assessments are needed for the safety. However, many flaws are undetectable because sampling inspection is carried out during in-service inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties and undetectable cracks. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on the Monte Carlo(MC) algorithms. Taking a number of sampling data of probabilistic variables such as fracture toughness value, crack depth and aspect ratio of an initial surface crack, a MC simulation of failure judgement of samples is performed. for the verification of this analysis, a comparison study of the PFM analysis using a commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.461-470
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• 2014

This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.653-659
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• 2002

This paper describes a probabilistic fracture mechanics(PFM) analysis based on Monte Carlo(MC) simulation. In the analysis of CANDU pressure tube, the depth and aspect ratio of an initial semi-elliptical surface crack, a fracture toughness value and delayed hydride cracking(DHC) velocity are assumed to be probabilistic variables. As an example, some failure probabilities of piping and CANDU pressure tube are calculated using MC method with the stratified sampling MC technique, taking analysis conditions of normal operations. In the stratified MC simulation, a sampling space of probabilistic variables is divided into a number of small cells. For the verification of analysis results, a comparison study of the PFM analysis using other commercial code is carried out and a good agreement was observed between those results.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.1-12
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• 2018

Mixed-criticality systems consist of components with different criticality. Recently, components are categorized depending on criticality by ISO 26262 standard and DO-178B standard in automotive and avionic domain. Existing mixed-criticality system research achieved efficient and safe scheduling through system-level criticality mode. The drawback of these approaches is performance degradation of low-criticality tasks on high-criticality mode. Task-level criticality mode is one method to address the problem and improve the performance of low-critical tasks. In this paper, we propose probabilistic performance metric for the approach. In simulation results with probabilistic performance metric, we showed that our approach has better performance than the existing approaches.

• The Journal of the Acoustical Society of Korea
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• v.25 no.8
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• pp.375-382
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• 2006

This paper is about how to identify emotional information and how to detect a specific emotion from speech signals. For emotion identification and detection task. we use long-term acoustic feature parameters and select the optimal Parameters using the feature selection technique based on F-score. We transform the conventional SVM into probabilistic output SVM for our emotion identification and detection system. In this paper we propose three approximation methods for log-likelihoods in a hypothesis test and compare the performance of those three methods. Experimental results using the SUSAS database showed the effectiveness of both feature selection and Probabilistic output SVM in the emotion identification task. The proposed methods could detect anger emotion with 91.3% correctness.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1121-1137
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• 2015

This study presents probabilistic-based damage identification technique for highlighting damage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate and monitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define the scatter signals of different paths. The energy of scatter signals till different times were calculated by taking root mean square of the scatter signals. For each pair of parallel paths an error function based on the energy of scatter signals is introduced. The resultant error function then is used to estimate the probability of the presence of damage in the monitoring area. The presented method with an autofocusing feature is applied to aluminum plates for method verification. The results identified using both simulation and experimental Lamb wave signals at different central frequencies agreed well with the actual situations, demonstrating the potential of the presented algorithm for identification of damage in metallic structures. An obvious merit of the presented technique is that in addition to damages located inside the region between transducers; those who are outside this region can also be monitored without any interpretation of signals. This novelty qualifies this method for online structural health monitoring.