• Computers and Concrete
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• v.19 no.5
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• pp.467-475
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• 2017

The purpose of this study is to establish a prediction model for the electrical resistivity ($E_r$) of self-consolidating concrete by using waste LCD (liquid crystal display) glass as part of the fine aggregate and then, to analyze the results obtained from a series of laboratory tests. A hyperbolic function is used to perform nonlinear multivariate regression analysis of the electrical resistivity prediction model, with parameters such as water-binder ratio (w/b), curing age (t) and waste glass content (G). Furthermore, the relationship of compressive strength and electrical resistivity of waste LCD glass concrete is also found by a logarithm function, while compressive strength is evaluated by the electrical resistivity of non-destructive testing (NDT). According to relative regression analysis, the electrical resistivity and compressive strength prediction models are developed, and the results show that a good agreement is obtained using the proposed prediction models. From the comparison between the predicted analysis values and test results, the MAPE value of electrical resistivity is 17.0-18.2% and less than 20%, the MAPE value of compressive strength evaluated by $E_r$ is 5.9-10.6% and nearly less than 10%. Therefore, the prediction models established in this study have good predictive ability for electrical resistivity and compressive strength of waste LCD glass concrete. However, further study is needed in regard to applying the proposed prediction models to other ranges of mixture parameters.

• Explosives and Blasting
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• v.21 no.1
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• pp.69-76
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• 2003

Test blasting has been performed with V-cut to investigate the characteristics. Blasting vibrations were measured at two directions, the proceed direction and side direction. Propagation characteristics were determined by regression analysis; square root scaled distance and cube root scaled distance with maximum charge per delay of the blast. Testing result, The cross point was 62m in the allowable vibration velocity of 3mm/sec and 46m In 5mm/sec. Also, vibration level with measuring point was highest and decayed fastest, adapting to cube root scaled distance, for the proceed direction on ground.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.687-695
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• 2020

The study attempts to assess the level of environmental sustainability awareness in the Kingdom of Saudi Arabia. In the process, the study tries to assess the impact of extracurricular activities in increasing awareness of environmental sustainability. A survey questionnaire was administered to the students of Prince Sattam University and other universities of Saudi Arabia. The questionnaire comprises statements on simple environmental conservation activities, which we come across on a daily basis. Hypothesis testing is used to identify significant differences across different categories of respondents. Further, the method of binary logistic regression is used to analyze the data. Though all the respondents agree that conserving the environment is important still there are significant differences across categories when it comes to believing in and practicing environmentally-responsible behavior. The results show that environmental awareness can be increased using awareness activities on sustainability issues in a University setting. The study concludes that increasing the number of extracurricular activities on environmental topics as only 38% of the respondents reported any activity related to the environment in the past year. The findings of this study suggest that increased awareness of environmental issues can boost the sustainability awareness, which will ultimately lead to a sustainable environment.

• Near Infrared Analysis
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• v.1 no.2
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• pp.35-39
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• 2000

The purpose of this research was to find out suitable soil sample preparation and sample holding tools for NIR reflection radiation for estimating soil components. NIR reflectance was scanned at 2nm intervals from 1,100 to 2,500nm with an InfraAlyzer 500(Bran+Luebbe Co.). Coarse(2.0mm) and fine(0.5mm) soil sample and various sample holding tools were used to obtain mean diffuse reflection of the soil for the calibration and validation of the calibration set in estimating moisture, organic matter and total nitrogen of the soils. Multiple linear regression was used to obtain the best correlation of NIR spectroscopy method. Correlation of NIR spectroscopy method. Correlation of NIR spectra for finely and coarsely sized soil did not show much difference. The standard errors of prediction(SE) using different types of sample holding tools for organic matter, total nitrogen and soil moisture were better than 0.765, 0.041 and 0.63% respectively. From the results it can be concluded that NIR spectroscopy with flow type cell could be used as a fast routine testing method in quantitative determination of organic matter, total nitrogen and soil moisture.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.1
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• pp.75-82
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• 2020

To compare and analyze the differences between flight simulation and actual flight among 130 army helicopter pilot training subjects, the correlation analysis was performed first through t-testing and multiple regression analysis of individual characteristics and flight simulation and actual instrument flight training, which were analyzed significantly in the age (a3) and service classification (a5) of the six verification factors. This has been shown to be significant, with no difference between the flight simulator and the actual flight. Second, in order to study the correlation between aircraft types, the flight evaluation (v1) was analyzed as a dependent variable for the performance of the flight simulator (KUH: s2, UH60: s3, AH-1S: s5, UH-1H: s6), and the results of the multiple regression analysis of the flight simulator evaluation (s1) were analyzed, in contrast, as a dependent variable, and in conclusion, the training of the flight simulator provided statistical data on the possibility of replacing the actual flight training, which is thought to contribute to the orientation, budget reduction and aviation safety of the pilot training.

• Journal of Families and Better Life
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• v.31 no.3
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• pp.141-151
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• 2013

The purpose of this study is to test the economic rationality hypothesis of the low fertility trap among 412 college students at 13 private universities located in Seoul. The respondents were requested to complete the self-administered questionnaire, and the hierarchical multiple regression analyses were performed for analyzing the data. The major findings of this study were as follows: First, the students' views on the prospects for their future employability were 54.6% for big business, 64.51% for medium-sized business, and 49.63% for public sector. In the most employable job, the mean desired monthly salary was 3,505,400 won, while the mean expected monthly salary 2,753,600 won. Second, hierarchical regression analyses revealed that the family income in parental home was positively related to youths' consumption aspirations. Finally, the gap between youths' consumption aspirations and their expected income was negatively related to their desired number of children, while not significantly related to their planned age of first child birth. Thus, the low fertility trap hypothesis was supported in terms of birth rate drop, but not supported in terms of childbearing postponement. The implications of the study results are discussed.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.675-677
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• 1998

In this paper, we propose the fuzzy inference algorithm with multi-layer structure. MFIS(Multi-layer Fuzzy Inference System) uses PNN(Polynomial Neural networks) structure and the fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Hendling), and uses several types of polynomials such as linear, quadratic and cubic, as well as the biquadratic polynomial used in the GMDH. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here, the regression polynomial inference is based on consequence of fuzzy rules with the polynomial equations such as linear, quadratic and cubic equation. Each node of the MFIS is defined as fuzzy rules and its structure is a kind of neuro-fuzzy structure. We use the training and testing data set to obtain a balance between the approximation and the generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

• Structural Engineering and Mechanics
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• v.66 no.3
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• pp.399-409
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• 2018

This paper demonstrates the potential application of machine learning algorithms for approximate prediction of the load and deflection capacities of the novel type of Laced Steel Concrete-Composite (LSCC) beams proposed by Anandavalli et al. (Engineering Structures 2012). Initially, global and local responses measured on LSCC beam specimen in an experiment are used to validate nonlinear FE model of the LSCC beams. The data for the machine learning algorithms is then generated using validated FE model for a range of values of the identified sensitive parameters. The performance of four well-known machine learning algorithms, viz., Support Vector Regression (SVR), Minimax Probability Machine Regression (MPMR), Relevance Vector Machine (RVM) and Multigene Genetic Programing (MGGP) for the approximate estimation of the load and deflection capacities are compared in terms of well-defined error indices. Through relative comparison of the estimated values, it is demonstrated that the algorithms explored in the present study provide a good alternative to expensive experimental testing and sophisticated numerical simulation of the response of LSCC beams. The load carrying and displacement capacity of the LSCC was predicted well by MGGP and MPMR, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.254-259
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• 1998

A new design methology is proposed to identify the structure and parameters of fuzzy model using PNN and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and cubic besides the biquadratic polynomial used in the GMDH. The FPNN(Fuzzy Polynomial Neural Networks) algorithm uses PNN(Polynomial Neural networks) structure and a fuzzy inference method. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here a regression polynomial inference is based on consequence of fuzzy rules with a polynomial equations such as linear, quadratic and cubic equation. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture. In this paper, we will consider a model that combines the advantage of both FPNN and PNN. Also we use the training and testing data set to obtain a balance between the approximation and generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.87-92
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• 2002

A stochastic process {$A_n$, n = 1, 2, ...} is an arithmetic process (AP) if there exists some real number, d, so that {$A_n$ + (n-1)d, n =1, 2, ...} is a renewal process (RP). AP is a stochastically monotonic process and can be used for modeling a point process, i.e. point events occurring in a haphazard way in time (or space), especially with a trend. For example, the vents may be failures arising from a deteriorating machine; and such a series of failures id distributed haphazardly along a time continuum. In this paper, we discuss estimation procedures for an AP, similar to those for a geometric process (GP) proposed by Lam (1992). Two statistics are suggested for testing whether a given process is an AP. If this is so, we can estimate the parameters d, ${\mu}_{A1}$ and ${\sigma}^{2}_{A1}$ of the AP based on the techniques of simple linear regression, where ${\mu}_{A1}$ and ${\sigma}^2_{A1}$ are the mean and variance of the first random variable $A_1$ respectively. In this paper, the procedures are, for the most part, discussed in reliability terminology. Of course, the methods are valid in any area of application, in which case they should be interpreted accordingly.