• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.164-172
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• 2005

A loss function approach to a multiresponse problem is considered, when process parameters are regarded as random variables. The variation of each response may be amplified through so called propagation of error (POE), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. The forms of POE for each response and for a pair of responses are proposed and they are reflected in our loss function approach to determine the optimal condition. The proposed method is illustrated using a polymer case. The result is compared with the case where parameter fluctuation is not considered.

• Structural Engineering and Mechanics
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• v.36 no.4
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• pp.421-445
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• 2010

In this paper the formulation of an efficient frame element applicable for nonlinear analysis of 3D reinforced concrete (RC) frames is outlined. Interaction between axial force and bending moment is considered by using the fibre element approach. Further, section warping, effect of normal and tangential forces on the torsional stiffness of section and second order geometrical nonlinearities are included in the model. The developed computer code is employed for nonlinear static analysis of RC sub-assemblages and a simple approach for extending the formulation to dynamic cases is presented. Dynamic progressive collapse assessment of RC space frames based on the alternate path method is undertaken and dynamic load factor (DLF) is estimated. Further, it is concluded that the torsional behaviour of reinforced concrete elements satisfying minimum standard requirements is not significant for the framed structures studied.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 1997.11a
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• pp.484-491
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• 1997

In this paper, an approach to determine the in-ordinal condition of a room, which is based on multi variable analysis, is proposed. According to this approach, the distance of a state from the ordinal condition is thought to be evaluated by the Mahalanobis' distance. The temperature changes of a room were measured and their statistical characteristics such as distribution type, the mean value and the standard deviation are studied. The applicability of the method for the fire detection is also investigated.

• Journal of the Korean Society of Combustion
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• v.13 no.1
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• pp.17-22
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• 2008

A partly implicit/quasi-explicit method is introduced for the solution of detailed chemical kinetics with stiff source terms based on the standard fourth-order Runge-Kutta scheme. Present method solves implicitly only the stiff reaction rate equations, whereas the others explicitly. The stiff equations are selected based on the survey of the chemical Jaconian matrix and its Eigenvalues. As an application of the present method constant pressure combustion was analyzed by a detailed mechanism of hydrogen-air combustion with NOx chemistry. The sensitivity analysis reveals that only the 4 species in NOx chemistry has strong stiffness and should be solved implicitly among the 13 species. The implicit solution of the 4 species successfully predicts the entire process with same accuracy and efficiency at half the price.

• Journal of Communications and Networks
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• v.11 no.6
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• pp.556-563
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• 2009

A side channel analysis is a very efficient attack against small devices such as smart cards and wireless sensor nodes. In this paper, we propose an efficient key detection method using a peak selection algorithm in order to find the advanced encryption standard secret key from electromagnetic signals. The proposed method is applied to a correlation electromagnetic analysis (CEMA) attack against a wireless sensor node. Our approach results in increase in the correlation coefficient in comparison with the general CEMA. The experimental results show that the proposed method can efficiently and reliably uncover the entire 128-bit key with a small number of traces, whereas some extant methods can reveal only partial subkeys by using a large number of traces in the same conditions.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3229-3232
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• 2012

In this study, cancer incidence data were assessed to provide various rates of five year age groups for a given year, lying between two census years. The individual exponential growth rate method is most useful in both population-based and non-population cased cancer registries in India to estimate the population by five yearly age groups and also find the rates of crude rates, age standard rates and cumulative rates. This method has been shown to endure from bias and often results sacrificing the overall growth rate and correction factor must be needful in five year age group population to maintain it. A second method, the difference distribution method is also able to maintain the overall growth rate and overcome the bias in estimation of five yearly age group populations. From this point of view these methods serving a new technique for population estimation by five yearly age groups for inter census years.

• Journal of Biomedical Engineering Research
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• v.30 no.6
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• pp.510-515
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• 2009

In this paper, variable characteristic ratio algorithm based on oscillometric method is proposed to enhance the accuracy of blood pressure measurement. We combined the slope-based approach and fuzzy inference technique to change the characteristic ratios of height-based method. The proposed algorithm was assessed on 255 measurements from 85 subjects and compared with the conventional height-based algorithm. The testing results showed that the developed algorithm achieved an overall grade A for both systolic and diastolic blood pressures according to the BHS protocol. And, mean standard deviation between the observers and the developed algorithm were 5.71mmHg and 6.29mmHg for systolic and diastolic pressures respectively, which also fulfilled the AAMI criteria. In conclusion, this algorithm was successfully developed and recommended for further clinical trials with the wider adult population.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.997-1004
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• 2009

A standard approach is to classify all of future observations. In some cases, however, it would be desirable to defer a decision in particular for observations which are hard to classify. That is, it would be better to take more advanced tests rather than to make a decision right away. This motivates a classifier with a reject option that reports a warning for those observations that are hard to classify. In this paper, we present the method which gives efficient computation with a reject option. Some numerical results show strong potential of the propose method.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.353-357
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• 2011

Although the intensity-hue-saturation (IHS) method for pan-sharpening has a spectral distortion problem, it is a popular method in the remote sensing community and has been used as a standard procedure in many commercial packages due to its fast computing and easy implementation. Recently, IHS-like approaches have tried to overcome the spectral distortion problem inherited from the IHS method itself and yielded a good result. In this paper, a similar IHS-like method with least squares for WorldView-2 pan-sharpening is presented. In particular, unlike the previous methods with three or four-band multispectral images for pan-sharpening, six bands of WorldView-2 multispectral image located within the range of panchromatic spectral radiance responses are considered in order to reduce the spectral distortion during the merging process. As a result, the new approach provides a satisfactory result, both visually and quantitatively. Furthermore, this shows great value in spectral fidelity of WorldView-2 eight-band multispectral imagery.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.832-854
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• 2019

Action recognition has been studied in computer vision field for years. We present an effective approach to recognize actions using a dimension reduction method, which is applied as a crucial step to reduce the dimensionality of feature descriptors after extracting features. We propose to use sparse matrix and randomized kd-tree to modify it and then propose modified Local Fisher Discriminant Analysis (mLFDA) method which greatly reduces the required memory and accelerate the standard Local Fisher Discriminant Analysis. For feature encoding, we propose a useful encoding method called mix encoding which combines Fisher vector encoding and locality-constrained linear coding to get the final video representations. In order to add more meaningful features to the process of action recognition, the convolutional neural network is utilized and combined with mix encoding to produce the deep network feature. Experimental results show that our algorithm is a competitive method on KTH dataset, HMDB51 dataset and UCF101 dataset when combining all these methods.