• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.344-350
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• 2024

A Reference Sound Source (RSS) is an important standard device employed in measuring sound power. The specifications of RSS is specified in international standards, and it is classified as a major calibration item in the field of acoustic metrology. Since the output power of RSS is affected by the supply voltage, each country needs to secure its own calibration service system. In this study, a procedure for calibrating a RSS is established based on the reverberant room conditions and uncertainty evaluation is conducted. Basically, the calibration procedure can apply a precision measurement process of acoustic power, and here, the measurement method using the reverberation chamber of ISO 3741 is applied. For this purpose, a measurement system is constructed, measurements are conducted with two types of RSS, and measurement uncertainty is evaluated. Through measurement examples, it is confirmed that the non-uniformity of the sound pressure distribution in the reverberation room and the volume measurement uncertainty contributed significantly to the overall uncertainty. Additionally, the influence of input voltage is experimentally examined to examine the uncertainty contribution that can be reflected in acoustic power measurements.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.94-95
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• 2006

A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. In this study we develop a new fuzzy ranking model based on the user preference. Through the experiments on the TREC-2 collection of Wall Street Journal documents, we show that the proposed method outperforms the conventional fuzzy ranking models.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.326-331
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• 2006

A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. In this study we develop a new fuzzy ranking model based on the user preference. Through the experiments on the TREC-2 collection of Wall Street Journal documents, we show that the proposed method outperforms the conventional fuzzy ranking models.

• 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 Radiation Industry
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• v.17 no.4
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• pp.345-357
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• 2023

Nuclear forensics has been understood as a mendatory component in the international society for nuclear material control and non-proliferation verification. Radiochronometry of nuclear activities for nuclear forensics are decay series characteristics of nuclear materials and the Bateman equation to estimate when nuclear materials were purified and produced. Radiochronometry values have uncertainty of measurement due to the uncertainty factors in the estimation process. These uncertainties should be calculated using appropriate evaluation methods that are representative of the accuracy and reliability. The IAEA, US, and EU have been researched on radiochronometry and uncertainty of measurement, although the uncertainty calculation method using the Bateman equation is limited by the underestimation of the decay constant and the impossibility of estimating the age of more than one generation, so it is necessary to conduct uncertainty calculation research using computer simulation such as Monte Carlo method. This highlights the need for research using computational simulations, such as the Monte Carlo method, to overcome these limitations. In this study, we have analyzed mathematical models and the LHS (Latin Hypercube Sampling) methods to enhance the reliability of radiochronometry which is to develop an uncertainty algorithm for nuclear material radiochronometry using Bateman Equation. We analyzed the LHS method, which can obtain effective statistical results with a small number of samples, and applied it to algorithms that are Monte Carlo methods for uncertainty calculation by computer simulation. This was implemented through the MATLAB computational software. The uncertainty calculation model using mathematical models demonstrated characteristics based on the relationship between sensitivity coefficients and radiative equilibrium. Computational simulation random sampling showed characteristics dependent on random sampling methods, sampling iteration counts, and the probability distribution of uncertainty factors. For validation, we compared models from various international organizations, mathematical models, and the Monte Carlo method. The developed algorithm was found to perform calculations at an equivalent level of accuracy compared to overseas institutions and mathematical model-based methods. To enhance usability, future research and comparisons·validations need to incorporate more complex decay chains and non-homogeneous conditions. The results of this study can serve as foundational technology in the nuclear forensics field, providing tools for the identification of signature nuclides and aiding in the research, development, comparison, and validation of related technologies.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.119-123
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• 2009

Recently, a MEMS gyroscope has been broadly fabricated and used due to development of a micromachining. However, there is a difference between the modeling design and the actual product and this difference can lead to the performance variation of a MEMS gyroscope. A classical design method does not exactly estimate the performance of a MEMS gyroscope. Therefore a design process considering the design variable uncertainty has to be employed to design MEMS gyroscope model. In this paper, the equation of motion of a MEMS gyroscope model is obtained to analyze the performance of a MEMS gyroscope and the effects of the design variables on the MEMS gyroscope performance are investigated. Finally the performance of MEMS gyroscope is estimated through a statistical analysis based on sample statistics.

• Journal of Korea Multimedia Society
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• v.18 no.5
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• pp.575-582
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• 2015

Obtaining the complete trajectory of the object is a very important task in computer vision applications, such as video surveillance. Previous studies to recover the trajectory between two disconnected trajectory segments, however, do not takes into account the object's motion characteristics and uncertainty of trajectory segments. In this paper, we present a novel approach to recover the trajectory between two disjoint but associated trajectory segments, called goal-directed tracking. To incorporate the object's motion characteristics and uncertainty, the goal-directed state equation is first introduced. Then the goal-directed tracking framework is constructed by integrating the equation to the object tracking and trajectory linking process pipeline. Evaluation on challenging dataset demonstrates that proposed method can accurately recover the missing trajectory between two disconnected trajectory segments as well as appropriately constrain a motion of the object to the its goal(or the target state) with uncertainty.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.83-89
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• 2015

Selection of efficient supplier is a very important process as risk or uncertainty of a supply chain and its environment are increasing. Previous deterministic DEA and probabilistic DEAs are very limited to handle various types of risk and uncertainty. In this paper, I propose an improved probabilistic DEA which consists of two steps; Monte Carlo simulation and statistical decision making. The simulation results show that the proposed method is proper to distinguish supplier's performance and provide statistical decision background.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.2
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• pp.112-120
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• 2011

The early phase of design intrinsically contains multiple sources of uncertainty in describing design, and nevertheless the decision-making process at this phase exerts a critical effect upon drawing a successful design. This paper proposes a set-based design approach for multi-objective design problem under uncertainty. The proposed design approach consists of four design processes including set representation, set propagation, set modification, and set narrowing. This approach enables the flexible and robust design while incorporating designer's preference structure. In contrast to existing optimization techniques, this approach generates a ranged set of design solutions that satisfy changing sets of performance requirements.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2136-2141
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• 2009

Transmission planning is an important part of power system planning to meet an increasing demand for electricity. The objective of transmission expansion is to minimize operational and construction costs subject to system constraints. There is inherent uncertainty in transmission planning due to errors in forecasted demand and fuel costs. Therefore, transmission planning process is not reliable if the uncertainty is not taken into account. The paper presents a systematic method to find the optimal location and amount of transmission expansion using Cross-Entropy (CE) incorporating uncertainties about future power system conditions. Numerical results are presented to demonstrate the performance of the proposed method.