• Korean Journal of Child Studies
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• v.27 no.5
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• pp.49-65
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• 2006

This attitudes scale for prediction of mathematics achievement by elementary school students was developed from 50 initial items from the literature rated for content validity by 30 experts. The ratings rendered 31 revised items used for exploratory factor analysis and reliability tests. The 31 items were administered to 183 elementary students in 4th, 5th, and 6th grades, yielding 4 factors : enjoyment, confidence, value, and motivation with high inter-items consistency. To confirm appropriateness of the constructed model and to test its predictability in mathematics achievements, confirmative factor analysis and discriminant analysis were performed on 693 cases. Results showed that the attitude scale model of 4 factors can be recommended for use in the measurement of elementary school students' attitudes toward mathematics.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.83-89
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• 1988

Optimal screening procedures with dichotomous performance variable T and continuous screening variable X are presented for assuring with a specified degree of confidence that at least ${\ell}$ out of m items found acceptable in screening inspection are conforming. It is assumed that T is a Bernoulli random variable and that the conditional distribution of X given T=t is normal. When m is also to be determined, optimal m and cut-off value of X minimizing the total expected cost are obtained. Cases of known and unknown parameters are considered and for unknown parameter cases, Bayesian approaches are used to find the optimal screening procedures.

• MALSORI
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• no.66
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• pp.87-103
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• 2008

We describe a new active learning method in conditional random fields (CRFs) framework for keyphrase extraction. To save elaboration in annotation, we use diversity and representative measure. We select high diversity training candidates by sentence confidence value. We also select high representative candidates by clustering the part-of-speech patterns of contexts. In the experiments using dialog corpus, our method achieves 86.80% and saves 88% training corpus compared with those of supervised method. From the results of experiment, we can see that the proposed method shows improved performance over the previous methods. Additionally, the proposed method can be applied to other applications easily since its implementation is independent on applications.

• Journal of Korean Institute of Industrial Engineers
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• v.5 no.1
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• pp.19-25
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• 1979

This paper presents an analysis of the contents of job for the sensory inspection on the basis of the probability theory, and the new determination for an index(d') of the testing power precision in carrying out sensory inspections. Also presented are the evaluation method of determining the ability of inspector by presuming the confidence interval for the average record of inspector, and the computation method for the index (de') of the testing power precision required as the goal-value in accordance with quality character, process inferior ratio, and required AOQ.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.2
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• pp.51-57
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• 2010

Many models have been used to represent the effects of confining stress, bulk stress, and shear stress on the value of the resilient modulus (Mr). This study was conducted to estimate Mr of the recycled materials such as recycled concrete aggregate (RCA) and recycled asphalt pavement (RAP) through the repeated load cyclic test. Also, two models were applied to estimation of Mr for comparing between measured Mr values and predicted Mr values. The first model (A-model) can provide a quick and easy estimation of the Mr based on the bulk stress, while the second model (N-model) includes not only the bulk stress but also the shear stress. Statistical analysis indicated that all results using the both of models are significant at a 95 % confidence level. Therefore, the both of models could be used as an effective prediction model of Mr for RCA and RAP. Especially, the Model 2 including the parameters of the bulk stress and the shear stress could give more reliable estimation at the high range of Mr values.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.511-514
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• 2003

This study was conducted to estimate the design rainfall by the determination of best fitting order for Higher Probability Weighted Moments of the annual maximum series according to consecutive duration at sixty-five rainfall stations in Korea. Design rainfalls were obtained by generalized extreme value distribution which was selected to be suitable distribution in 4 applied distributions and by L, L1, L2, L3 and L4-moment. The best fitting order for Higher Probability Weighted Moments was determined with the confidence analysis of estimated design rainfall.

• Structural Engineering and Mechanics
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• v.46 no.6
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• pp.853-868
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• 2013

The comparison of the effectiveness of artificial neural network (ANN) and linear regression (LR) in the prediction of strain in tie section using experimental data from eight high-strength-self-compact-concrete (HSSCC) deep beams are presented here. Prior to the aforementioned, a suitable ANN architecture was identified. The format of the network architecture was ten input parameters, two hidden layers, and one output. The feed forward back propagation neural network of eleven and ten neurons in first and second TRAINLM training function was highly accurate and generated more precise tie strain diagrams compared to classical LR. The ANN's MSE values are 90 times smaller than the LR's. The correlation coefficient value from ANN is 0.9995 which is indicative of a high level of confidence.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.2 no.2
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• pp.33-38
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• 1979

This thesis aimed at studying the development of the engineering manpower in industrial society today. In order to achieve the purpose, we must to be supported by its training to be based on the continuous government planning for the development of manpower It is proper that strategic management should be conducted for the vocational engineer training. In the view of the present situation, we dare assert that the following management should be followed ; 1. We believe that the motives of the engineer will be caused by the law of official rearing, 2. For the manager's concern, it is need for the system of accounting in the manpower to be established, 3. For the efficiency each other, it is urgent to take a trianqular position for the confidence through the value of rationalism above all mentioned words are concerned with having high morale and a normal act for the engineer.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.625-636
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• 2013

In this paper we study four kernel machines for estimating expected shortfall, which are constructed through combinations of support vector quantile regression (SVQR), restricted SVQR (RSVQR), least squares support vector machine (LS-SVM) and support vector expectile regression (SVER). These kernel machines have obvious advantages such that they achieve nonlinear model but they do not require the explicit form of nonlinear mapping function. Moreover they need no assumption about the underlying probability distribution of errors. Through numerical studies on two artificial an two real data sets we show their effectiveness on the estimation performance at various confidence levels.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1430-1435
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• 2003

Satellite upper platform is optimized by response surface method which has non-gradient, semi-glogal, discrete and fast convergency characteristics. Sampling points are extracted by design of experiments using Central Composite Method and Factorial Design. Also response surface is generated by the various regression functions. Structure analysis is execuated with regard for static and dynamic environment in launching stage. As a result response surface method is superior to other optimization method with respect to optimum value and cost of computation time. Also a confidence is varified in the various regression models.