• 대한금속재료학회지
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• 제49권10호
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• pp.774-779
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• 2011

S-N fatigue behavior of cast 304 stainless steel was studied at 25, -50 and $-196^{\circ}C$ and at a stress ratio of -1 in uniaxial and bending loading condition. It was found that the resistance to S-N fatigue was greatly improved with decreasing testing temperature. The normalized S-N fatigue curves by tensile strength at three different testing temperatures matched each other, suggesting that tensile strength determines the S-N fatigue resistance of cast 304 stainless steel at low temperatures. The effects of different loading on the resistance to S-N fatigue of cast 304 stainless steel were quantified. The S-N fatigue curves at 25, -50 and $-196^{\circ}C$ were described by using Basquin's law the relationship between the S-N fatigue curve and the testing temperature was obtained by using a simple regression method.

• Communications for Statistical Applications and Methods
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• 제21권5호
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• pp.423-433
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• 2014

Test statistics using cumulative sums of residuals have been widely used in various regression models including generalized linear models(GLM). Recently, Pan and Lin (2005) extended this testing procedure to the generalized linear mixed models(GLMM) having random effects, in which we encounter difficulties in computing the marginal likelihood that is expressed as an integral of random effects distribution. The Gaussian quadrature algorithm is commonly used to approximate the marginal likelihood. Many commercial statistical packages provide an option to apply this type of goodness-of-fit test in GLMs but available programs are very rare for GLMMs. We suggest a computational algorithm to implement the testing procedure in GLMMs by a freely accessible R package, and also illustrate through practical examples.

• 비파괴검사학회지
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• 제31권6호
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• pp.616-625
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• 2011

Ensuring the designed prestress force is very important for the safety of prestressed concrete bridge. The loss of prestress force in tendon could significantly reduce load carrying capacity of the structure. In this study, an automated prestress-loss monitoring system for prestressed concrete girder using PZT-interface and wireless impedance sensor node is presented. The following approaches are carried out to achieve the objective. Firstly, wireless impedance sensor nodes are designed for automated impedance-based monitoring technique. The sensor node is mounted on the high-performance Imote2 sensor platform to fulfill high operating speed, low power requirement and large storage memory. Secondly, a smart PZT-interface designed for monitoring prestress force is described. A linear regression model is established to predict prestress-loss. Finally, a system of the PZT-interface interacted with the wireless sensor node is evaluated from a lab-scale tendon-anchorage connection of a prestressed concrete girder.

• 대한안전경영과학회지
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• 제12권4호
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• pp.199-206
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• 2010

In this era of globally competitive world market, many business firms have been using ISO 9000 quality management system, whose principles are leadership, customer focus, people involvement, etc., which are expected and desired to be attained for the various long/short term goals of the business firms. This paper studies whether and how those principles are implemented in the areas of service, manufacturing, etc., and researches the regression relations between business firm's performance and those principles. Using hypothesis testing, we found and showed results which can be referenced for the higher performance of business firms and those can be added to the pool of knowledge about the ISO principles implementation in service and manufacturing industries.

• 한국인쇄학회지
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• 제30권2호
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• pp.13-22
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• 2012

This research attempts to analyze communication effects of print ad having pictorial typography. 150 Questionnaires were distributed to respondents staying Daejeun City and 148 copies were retreated for five days from April 22nd to 26th, 2012. Frequency analysis, factor analysis, Cronbach's alpha for reliability analysis were utilized for data analysis with SPSS 12.0. For testing hypothesis, regression analysis was used. As result of testing hypothesis, 'informative, beneficial, creative, reliable' were partially significant to attitude towards print ad having pictorial typography. That means 'creative' and 'reliable' were insignificant, while 'informative' and 'beneficial' are significant. Variable of the most influencing on attitude towards advertising is 'informative.' 'Informative, beneficial, creative, and reliable' were partially significant to brand attitude, too. That means 'beneficial' and 'creative' were insignificant, while 'informative' and 'reliable' were significant. Variable of the most influencing on brand attitude was 'reliable.' Therefore, to enhance communication effect of print ad having pictorial typography, 'informative' and 'reliable' are most significant variables.

• International Journal of Contents
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• 제15권1호
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• pp.1-9
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• 2019

Since the VR market is expected to have a high growth, this study aimed to investigate the human factor-related determinants of user satisfaction with mobile VR headsets. A pre-study of customer reviews was conducted with the help of semantic network analysis to identify the core keywords for understanding negative and positive predictors of mobile VR headset experiences. Through laboratory testing with three different commercial models, the main study measured and identified the predictors of user satisfaction. From the results, five factors were extracted as valid predictor variables and used for regression analysis. These factors were immersion, VR sickness, usability, wear-ability and menu navigation interface. All the five predictors were proved to be significant determinants of the perceived user satisfaction with mobile VR headsets. Usability was the strongest predictor, followed by VR sickness and wear-ability. Practical and theoretical implications of the results were discussed.

• Structural Engineering and Mechanics
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• 제89권3호
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• pp.301-308
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• 2024

Concrete carbonation is a continuous and slow process from the outside to the inside, in which its penetration slows down with the increased depth of carbonation. In this paper, the results of the evaluation of the measurement of concrete carbonation depth using a non-destructive ultrasonic testing method are presented. According to the results, the relative nonlinear parameter caused more sensitivity in carbonation changes compared to Rayleigh's fuzzy velocity. Thus, the acoustic nonlinear parameter is expected to be applied as a quantitative index to recognize carbonation effects. In this research, combo diagrams were developed based on the results of ultrasonic testing and the experiment to determine carbonation depth using a phenolphthalein solution, which could be considered as instructions in the projects involving non-destructive ultrasonic test methods. The minimum and maximum accuracy of this method were 89% and 97%, respectively, which is a reasonable range for operational projects. From the analysis performed, some useful expressions are found by applying the regression analysis for the nonlinearity index and the carbonation penetration depth values as a guideline.

• 터널과지하공간
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• 제33권6호
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• pp.594-609
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• 2023

TBM 공법은 굴착면 안정성 확보 및 주변환경에 비치는 영향을 최소화하기 때문에 도심지나 하·해저터널 등에서 적용 사례가 증가하는 추세이다. 디스크 커터의 수명을 예측하는 대표적인 모델 중 NTNU모델은 커터수명지수(Cutter Life Index, CLI)를 주요 매개 변수로 활용하지만 복잡한 시험절차와 시험장비의 희귀성으로 측정에 어려움이 있다. 본 연구에서는 다중선형회귀분석과 트리 기반의 머신러닝 기법으로 암석물성을 활용하여 CLI를 예측하였다. 문헌 조사를 통해 암석의 일축압축강도, 압열인장강도, 등 가석영함량과 세르샤 마모지수 등을 포함한 데이터베이스를 구축하였고 파생변수를 계산하여 추가하였다. 다중선형회귀분석은 통계적 유의성과 다중공선성을 고려하여 입력 변수를 선정하였고 머신러닝 예측 모델은 변수 중요도를 기반으로 입력 변수를 선정하였다. 학습용과 검증용 데이터를 8:2로 나누어 모델 간 예측 성능을 비교한 결과 XGBoost가 최적의 모델로 선정되었다. 본 연구에서 도출된 다중선형회귀모델과 XGBoost모델을 선행 연구와 예측 성능을 비교하여 타당성을 확인하였다.

• Computers and Concrete
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• 제21권4호
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• pp.407-417
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• 2018

Concrete which is a composite material is one of the most important construction materials. Compressive strength is a commonly used parameter for the assessment of concrete quality. Accurate prediction of concrete compressive strength is an important issue. In this study, we utilized an experimental procedure for the assessment of concrete quality. Firstly, the concrete mix was prepared according to C 20 type concrete, and slump of fresh concrete was about 20 cm. After the placement of fresh concrete to formworks, compaction was achieved using a vibrating screed. After 28 day period, a total of 100 core samples having 75 mm diameter were extracted. On the core samples pulse velocity determination tests and compressive strength tests were performed. Besides, Windsor probe penetration tests and Schmidt hammer tests were also performed. After setting up the data set, twelve artificial intelligence (AI) models compared for predicting the concrete compressive strength. These models can be divided into three categories (i) Functions (i.e., Linear Regression, Simple Linear Regression, Multilayer Perceptron, Support Vector Regression), (ii) Lazy-Learning Algorithms (i.e., IBk Linear NN Search, KStar, Locally Weighted Learning) (iii) Tree-Based Learning Algorithms (i.e., Decision Stump, Model Trees Regression, Random Forest, Random Tree, Reduced Error Pruning Tree). Four evaluation processes, four validation implements (i.e., 10-fold cross validation, 5-fold cross validation, 10% split sample validation & 20% split sample validation) are used to examine the performance of predictive models. This study shows that machine learning regression techniques are promising tools for predicting compressive strength of concrete.

• Asian-Australasian Journal of Animal Sciences
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• 제31권10호
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• pp.1542-1549
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• 2018

Objective: Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a RR model. Methods: We analyzed test-day milk records from 85,690 Holstein cows in their first lactations and 131,727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. Results: The first-order Legendre polynomials were practical covariates of RR for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Conclusion: Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.