• 제목/요약/키워드: combining function

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On Combining MOS and Histogram in a Subjective Evaluation Method

  • Sehyug Kwon
    • Communications for Statistical Applications and Methods
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    • 제2권2호
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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.

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스트림 암호에서 높은 비선형도의 상관면역함수의 설계와 그의 안전성 분석 (The Security analysis and construction of correlation immune function with higher nonlinearity on stream cipher)

  • 양정모
    • 정보보호학회논문지
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    • 제17권4호
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    • pp.89-95
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    • 2007
  • 상관면역함수 f를 만드는 방법으로 Siegenthaler의 방법, Camion의 방법과 Seberry의 방법 등이 있다. 이 중에서 Seberry의 방법은 Hadamard 행렬이론을 이용하여 상관면역함수를 만드는 것으로, 임의의 상관면역도의 균형상관면역함수를 만드는 방법을 제공하였다. 본 논문에서는 저차원의 벡터공간에서 만들어진 여러 개의 상관면역함수를 조합하여 고차원 벡터공간위에서 상당히 비도가 높은 함수를 설계하는 Seberry의 방법들을 연구하였고, 그 함수들의 비선형도를 계산하였다. 즉, 두 개의 함수의 직합으로 설계된 새로운 상관면역함수와 네 개의 함수의 조합으로 설계된 새로운 상관면역함수의 비선형도가 각각의 이전 함수들과 비교하여 더 높은 비선형도를 갖는다는 것을 보였다. 또한 위의 방법을 응용하여 상대적으로 비도가 높은 상관공격으로부터 안전한 스트림암호에서 사용되는 함수들을 설계하였다.

Reliability-based combined high and low cycle fatigue analysis of turbine blade using adaptive least squares support vector machines

  • Ma, Juan;Yue, Peng;Du, Wenyi;Dai, Changping;Wriggers, Peter
    • Structural Engineering and Mechanics
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    • 제83권3호
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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.

A novel PSO-based algorithm for structural damage detection using Bayesian multi-sample objective function

  • Chen, Ze-peng;Yu, Ling
    • Structural Engineering and Mechanics
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    • 제63권6호
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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.

An improved interval analysis method for uncertain structures

  • Wu, Jie;Zhao, You Qun;Chen, Su Huan
    • Structural Engineering and Mechanics
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    • 제20권6호
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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.

소비자 요구를 반영한 아파트 보조주방 모듈 개발에 고한 연구 (A Study on the planning of the Sub-kitchen Module Meeting Consumer Needs for the Apartment Unit Plan)

  • 방희조
    • 한국실내디자인학회논문집
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    • 제21권1호
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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.

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LS-SVM for large data sets

  • Park, Hongrak;Hwang, Hyungtae;Kim, Byungju
    • Journal of the Korean Data and Information Science Society
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    • 제27권2호
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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.

Characteristic-Function-Based Analysis of MIMO Systems Applying Macroscopic Selection Diversity in Mobile Communications

  • Jeong, Wun-Cheol;Chung, Jong-Moon;Liu, Dongfang
    • ETRI Journal
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    • 제30권3호
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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.

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주파수응답함수 결합법을 이용한 승용차 핸들지지 T 빔의 진동저감 재설계 (Redesign of Steering Wheel Support T-beam Structure to Reduce its Vibration Using Frequency Response Function Synthesis Technique)

  • 변성준;박남규;박윤식
    • 한국소음진동공학회논문집
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    • 제11권5호
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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.

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Effect of Continuous Antagonistic Muscle Strengthening and Evjenth-Hamberg Stretching on Pulmonary Function of Forward Head Posture Subjects

  • Park, Joo Hyun
    • 국제물리치료학회지
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    • 제6권2호
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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.