• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.176-183
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• 1995

Mean opinion score (MOS) method has been used in many areas to quantify opinions of respondents not only in survey research but in evaluating the parameters of population that are not measurable of are technically hard to be measured. Histogram is an important graphical technique because of the role it plays in describing categorical data as well as quantitative. In MOS method, subjective opinions of respondents are quantified by opinion scores and the arithmetic means of opinion scores have been used to describe the interesting population. Since opinion scores are polytomous, the values of arithmetic means have little meanings. In this paper, cumulative percentage curves as a function of the means of opinion scores are derived by combining means of opinion scores and histograms. It is proposed for better interpretation to opinion scores in MOS method, one of subjective evaluation methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.4
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• pp.89-95
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• 2007

There are various methods constructing correlation immune functions such as Siegenthaler's, Camion et al's and Seberry et al's. In particular, Soberry et al's is a method which directly constructs balanced correlation immune functions of any order using the theory of Hadamard matrices. In this paper, we have studied Seberry et al's method for constructing a correlation immune function on a higher dimensional space by combining known correlation immune functions on a lower dimensional space. Futhermore, we calculated the nonlinearity of functions which are constructed by combining of several correlation immune functions. That is, we have shown that the direct sum of two correlation immune functions and a combination of four correlation immune functions have higher nonlinearity in comparison with each functions. This functions in stream cipher are safe against correlation attacks.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.825-835
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• 2017

Significant improvements to methodologies on structural damage detection (SDD) have emerged in recent years. However, many methods are related to inversion computation which is prone to be ill-posed or ill-conditioning, leading to low-computing efficiency or inaccurate results. To explore a more accurate solution with satisfactory efficiency, a PSO-INM algorithm, combining particle swarm optimization (PSO) algorithm and an improved Nelder-Mead method (INM), is proposed to solve multi-sample objective function defined based on Bayesian inference in this study. The PSO-based algorithm, as a heuristic algorithm, is reliable to explore solution to SDD problem converted into a constrained optimization problem in mathematics. And the multi-sample objective function provides a stable pattern under different level of noise. Advantages of multi-sample objective function and its superior over traditional objective function are studied. Numerical simulation results of a two-storey frame structure show that the proposed method is sensitive to multi-damage cases. For further confirming accuracy of the proposed method, the ASCE 4-storey benchmark frame structure subjected to single and multiple damage cases is employed. Different kinds of modal identification methods are utilized to extract structural modal data from noise-contaminating acceleration responses. The illustrated results show that the proposed method is efficient to exact locations and extents of induced damages in structures.

• Structural Engineering and Mechanics
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• v.20 no.6
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• pp.713-726
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• 2005

Based on the improved first order Taylor interval expansion, a new interval analysis method for the static or dynamic response of the structures with interval parameters is presented. In the improved first order Taylor interval expansion, the first order derivative terms of the function are also considered to be intervals. Combining the improved first order Taylor series expansion and the interval extension of function, the new interval analysis method is derived. The present method is implemented for a continuous beam and a frame structure. The numerical results show that the method is more accurate than the one based on the conventional first order Taylor expansion.

• Korean Institute of Interior Design Journal
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• v.21 no.1
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• pp.170-176
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• 2012

Korean living culture raised the users' needs for sub-kitchen. In the traditional Korean house, there was large space related to kitchen area for preparing food and stock big and bulky housing stuffs. As apartment housing became dominant as Korean dwelling, sub-kitchen has been planed in the balcony that is not included in the sales area. In this study, the case of the apartment housing in Esiapolis, Daegu was analyzed. To plan the user-oriented sub-kitchen, the consumer research was carried out. Consumers needed a pantry, more storage near the kitchen, and wanted to place washing machine and washing stand in a sub-kitchen. Sub-kitchens were planed to meet those consumers' needs. Through this case study and former studies analysis, sub-kitchen's function unit was derived: wash, storage, auxiliary work. By combining each function unit, sub-kitchen was classified into 3 types, wash & auxiliary work, wash & storage, and wash & storage & auxiliary work. For each sub-kitchen type, components of function units, available layouts, and minimum size were recommended.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.549-557
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• 2016

In this paper we propose multiclassification method for large data sets by ensembling least squares support vector machines (LS-SVM) with principal components instead of raw input vector. We use the revised one-vs-all method for multiclassification, which is one of voting scheme based on combining several binary classifications. The revised one-vs-all method is performed by using the hat matrix of LS-SVM ensemble, which is obtained by ensembling LS-SVMs trained using each random sample from the whole large training data. The leave-one-out cross validation (CV) function is used for the optimal values of hyper-parameters which affect the performance of multiclass LS-SVM ensemble. We present the generalized cross validation function to reduce computational burden of leave-one-out CV functions. Experimental results from real data sets are then obtained to illustrate the performance of the proposed multiclass LS-SVM ensemble.

• ETRI Journal
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• v.30 no.3
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• pp.355-364
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• 2008

Multiple-input multiple-output (MIMO) systems can provide significant increments in capacity; however, the capacity of MIMO systems degrades severely when spatial correlation among multipath channels is present. This paper demonstrates that the influence of shadowing on the channel capacity is more substantial than that of multipath fading; therefore, the shadowing effect is actually the dominant impairment. To overcome the composite fading effects, we propose combining macroscopic selection diversity (MSD) schemes with MIMO technology. To analyze the system performance, the capacity outage expression of MIMO-based MSD (MSD-MIMO) systems using a characteristic function is applied. The analytic results show that there are significant improvements when MSD schemes are applied, even for the two-base-station diversity case. It is also observed that the effect of spatial correlation due to multipath fading is almost negligible when multiple base stations cooperatively participate in the mobile communication topology.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.5
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• pp.123-130
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• 2001

The purpose of this paper is to reduce the level of idling vibration on a steering wheel. In some cases, vibration on steering wheel is amplified due to the resonance between the first natural frequency of T-beam and engine idling speed. Using SDM(structural dynamic modification) technique, T-beam is redesigned to reduce its vibration. This paper used FRF(frequency response function) synthesis technique which is entirely dependent on experiment. But this method requires lots of test efforts to enhance its reliability of design. While combining this method with an analytic method. the experimental burden, the major drawback of FRP synthesis method, can be considerably relieved. Using ana1ytic sensitivity analysis, some effective modification regions are preliminarily chosen as candidate Positions where SDM can be applied to modify T-beam\`s dynamic characteristics.

• Journal of International Academy of Physical Therapy Research
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• v.6 no.2
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• pp.871-877
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• 2015

This research was conducted to investigate the effect of continuous antagonistic muscle strengthening exercise and Evjenth-Hamberg stretching on the pulmonary function of university students with abnormal transformation of forward head posture(FHP). The results of study subject to the continuous antagonistic muscle strengthening(CAS) group(n=10) and Evjenth- Hamberg stretching(EHS) group(n=10) that was conducted 3 times a week for 6 weeks are as follow. FVC, IVC, and MVV all were shown to be significant in the pre post comparison between the CAS group and EHS group(p<.05), and significant difference was shown for MW between the two groups(p<.05) in which the CAS group showed better effect. Based on the results above, it is considered that combining continuous antagonistic muscle strengthening exercise has better effect on pulmonary function compared to application of only Evjenth-Hamberg stretching.