• Proceedings of the Korea Concrete Institute Conference
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• 2003.11a
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• pp.54-57
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• 2003

Scaling deterioration of port concrete structures due to the combined effects of chemical actions by seawater and the freeze-thaw action is also a problem which has not yet been fundamentally solved. Furthermore, deterioration of concrete surface was considered as accelerate factor of concrete durability tended to decrease. Therefore, we considered the scaling measuring method and decreasing influence of durability of concrete according to kind of binders, such as OPC, Slag, Slag+Fa, due to freeze and haw of sea water. As a results of this study, it was effective method of scaling deterioration of concrete, and confirmed the salt deterioration resistance effect to use slag binder against to sea water.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.348-351
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• 1995

This note proposes a robust LQR method for systems with structured real parameter uncertainty based on Riccati equation approach. Emphasis is on the reduction of design conservatism in the sense of quadratic performance by utilizing the uncertainty structure. The class of uncertainty treated includes all the form of additive real parameter uncertainty, which has the multiple rank structure. To handle the structure of uncertainty, the scaling matrix with block diagonal structure is introduced. By changing the scaling matrix, all the possible set of uncertainty structures can be represented. Modified algebraic Riccati equation (MARE) is newly proposed to obtain a robust feedback control law, which makes the quadratic cost finite for an arbitrary scaling matrix. The remaining design freedom, that is, the scaling matrix is used for minimizing the upper bound of the quadratic cost for all possible set of uncertainties within the given bounds. A design example is shown to demonstrate the simplicity and the effectiveness of proposed method.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.717-719
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• 1995

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy controller and propose the tuning method for them. The quantitative relation between input and output variables of a fuzzy controller is obtained by using a quasi-linear fuzzy model. An approximate transfer function of a fuzzy controller is derived from the comparison a fuzzy controller with the conventional PID controller. We analyze the effects of scaling factor using this approximate transfer function and propose a fuzzy tuning method based on that of Maeda et al[4].

• Structural Engineering and Mechanics
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• v.39 no.5
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• pp.733-750
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• 2011

Recently, identification of modal parameters using the response only data has attracted considerable attention particularly where the classic modal testing methods is difficult to conduct. One drawback of the response only data, also known as Operational Modal Analysis (OMA), is that only the unscaled mode shapes can be obtained which restricts the applications of OMA. The Mass change method is a usual way to scale the operational mode shapes. In this article a new method is proposed to optimize the additive mass for scaling of the unscaled mode shapes from OMA for which a priori knowledge of the Finite Element model of structure is required. It is shown that the total error of the scaled mode shapes is minimized using the proposed method. The method is validated using a numerical case study of a beam. Moreover, the experimental results of a clamped-clamped beam demonstrate the applicability of the method.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2003.11a
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• pp.322-327
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• 2003

It is important to know the accurate radionuclide inventory of radioactive waste for the reliable management. However, estimation of radionuclide concentrations in drummed radioactive waste is difficult and unreliable because of difficulties of direct detection, high cost, and radiation exposure of sampling personnel. In order to overcome these difficulties, scaling factors (SFs) have been used to assess the activities of radionuclides that could not be directly analyzed. A radionuclide assay system has been operated at KORI site since 1996 and consolidated scaling factor method has played a dominant role in determination of radionuclides concentrations. However, some problems are still remained such as uncertainty of estimated scaling factor values, inaccuracy of analyzed sample values, and disparity between the actual and ideal correlation pairs and the others. Therefore, it needs to improve the accuracy of scaling factor values. The scope of this paper is focused on the improvement of accuracy and representativeness of calculated scaling factor values based on statistical techniques. For the selection of reliable activity determination method, the accuracy of estimated SF values for each activity determination method is compared. From the comparison of each activity determination methods, it is recommended that SF determination method should be changed from the arithmetic mean to the geometrical mean for more reliable estimation of radionuclide activity. Arithmetic mean method and geometric mean method are compared based on the data set in KORI system.

• Journal of the Korean Society for information Management
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• v.23 no.4 s.62
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• pp.215-231
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• 2006

Recently there are many bibliometric studies attempting to utilize Pathfinder networks(PFNets) for examining and analyzing the intellectual structure of a scholarly field. Pathfinder network scaling has many advantages over traditional multidimensional scaling, including its ability to represent local details as well as global intellectual structure. However there are some limitations in PFNets including very high time complexity. And Pathfinder network scaling cannot be combined with cluster analysis, which has been combined well with traditional multidimensional scaling method. In this paper, a new method named as Parallel Nearest Neighbor Clustering (PNNC) are proposed for complementing those weak points of PFNets. Comparing the clustering performance with traditional hierarchical agglomerative clustering methods shows that PNNC is not only a complement to PFNets but also a fast and powerful clustering method for organizing informations.

• Horticultural Science & Technology
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• v.16 no.2
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• pp.242-243
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• 1998

This research was conducted to find the most effective and economical artificial propagation method of Lycoris squamigera among chipping, half-chipping, twin-scaling, coring, scooping and notching, in order to investigate the number of bulblets obtained from one bulb and the number of bulbs treated by a man in a day for artificial propagation. We got 42.2 bulblets from one bulb by twin-scaling, 23.2 bulblets by half-chipping, 18.2 bulblets by chipping, 14.3 bulblets by notching, 1 bulblet by coring and also 1 bulblet by scooping. Although we got the most bulblets by twin-scaling, it took the most time to treat the bulbs for artificial propagation (200 bulbs per day) and the bulblets formed were very small. But 400 bulbs were treated in a day by chipping and the bulblets formed were comparatively large. In addition, machines could be used for chipping, so chipping was considered to be the most effective and economical artificial propagation method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.4
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• pp.409-416
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• 2009

Standard procedures for a fracture toughness testing require very severe restrictions for the specimen geometry to eliminate a size effect on the measured properties. Therefore, the used standard fracture toughness data results in the integrity assessment being irrationally conservative. However, a realistic fracture in general structures, such as in nuclear power plants, may develop under the low constraint condition of a large scale yielding with a shallow surface crack. In this paper, cleavage fracture toughness tests have been made on side-grooved PCVN (precracked charpy V-notch) type specimens (10 by 10 by 55 mm) with various crack depths. The constraint effects on the crack depth ratios were evaluated quantitatively by the developed scaling method using the 3-D finite element method. After the fracture toughness correction from scaling model, the statistical size effects were also corrected according to the standard ASTM E 1921 procedure. The results were evaluated through a comparison with the $T_0$ of the standard CT specimen. The corrected $T_0$ for all of the PCVN specimens showed a good agreement to within $5.4^{\circ}C$ regardless of the crack depth, while the averaged PCVN $T_0$ was $13.4^{\circ}C$ higher than the real CT test results.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.793-803
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• 2021

The small PWR has been paid more and more attention due to its diversity of application and flexibility in the site selection. However, the large core power density, the small containment space and the rapid accident progress characteristics make it difficult to control the containment pressure like the traditional PWR during the LOCA. The pressure suppression system has been used by the BWR since the early design, which is a suitable technique that can be applied to the small PWR. Since the configuration and operating conditions are different from the BWR, the pressure suppression system should be redesigned for the small PWR. Conducting the experiments on the scale down test facility is a good choice to reproduce the prototypical phenomena in the test facility, which is both economical and reasonable. A systematic scaling method referring to the H2TS method was proposed to determine the geometrical and thermohydraulic parameters of the pressure suppression containment response test facility for the small PWR conceptual design. The containment and the pressure suppression system related thermohydraulic phenomena were analyzed with top-down and bottom-up scaling methods. A set of the scaling criteria were obtained, through which the main parameters of the test facility can be determined.

• International journal of advanced smart convergence
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• v.6 no.4
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• pp.67-72
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• 2017

Deep learning neural network becomes very popular nowadays due to the reason that it can learn a very complex dataset such as the image dataset. Although deep learning neural network can produce high accuracy on the image dataset, it needs a lot of time to reach the convergence stage. To solve the issue, we have proposed a scaling method to improve the neural network to achieve the convergence stage in a shorter time than the original method. From the result, we can observe that our algorithm has higher performance than the other previous work.