• Computers and Concrete
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• v.24 no.4
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• pp.379-397
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• 2019

Steel-concrete composite beams are widely employed in constructions and their performance at the serviceability stage is of concern among practitioners and design regulations. In this context, an accurate evaluation of long-term deflections via various rheological concrete models is needed. In this work, the performance and predict capability of some concrete creep and shrinkage models ACI, CEB, B3, FIB and GL2000 are ascertained, and compared by using statistical bias indicators. Ten steel-concrete composite beams with existing experimental and numerical results are then modeled for this purpose. The proposed modeling technique uses the finite element method, where the concrete slab and steel beam are modeled with shell finite elements. Concrete is considered as an aging viscoelastic material and cracking is treated with the common smeared approach. The results show that when the experimental ultimate shrinkage strain is used for calibration, all studied rheological models predict nearly similar deflections, which agree with the experimental data. In contrast, significance differences are encountered for some models, when none calibration is made prior to. A value between twenty and thirty times the cracking strain is recommended for the ultimate tensile strain in the tension stiffening model. Also, increasing the relative humidity and decreasing the ambient temperature can lead to a substantial reduction of slab cracking for beams under negative flexure. Finally, there is not a unique rheological model that clearly excels in all scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.159-159
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• 2023

The Amazon River basin is one of the largest basins in the world, and its ecosystem is vital for biodiversity, hydrology, and climate regulation. Thus, understanding the hydrometeorological process is essential to the maintenance of the Amazon River basin. However, it is still tricky to monitor the Amazon River basin because of its size and the low density of the monitoring gauge network. To solve those issues, remote sensing products have been largely used. Yet, those products have some limitations. Therefore, this study aims to do bias corrections to improve the accuracy of Satellite Precipitation Products (SPPs) in the Amazon River basin. We use 331 rainfall stations for the observed data and two daily satellite precipitation gridded datasets (CHIRPS, TRMM). Due to the limitation of the observed data, the period of analysis was set from 1st January 1990 to 31st December 2010. The observed data were interpolated to have the same resolution as the SPPs data using the IDW method. For bias correction, we use convolution neural networks (CNN) combined with an autoencoder architecture (ConvAE). To evaluate the bias correction performance, we used some statistical indicators such as NSE, RMSE, and MAD. Hence, those results can increase the quality of precipitation data in the Amazon River basin, improving its monitoring and management.

• Journal of Environmental Health Sciences
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• v.42 no.5
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• pp.302-313
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• 2016

Objectives: This study was conducted to assess environmental health status on a local scale using environmental health-related indicators. It demonstrated the possibility of using a structural equation model, a methodological approach to provide synthesized information. Methods: Eighteen indicators were selected from official statistical data published by local governments. Each environmental health-related indicator was classified according to the PSR (pressure-state-response) model. Aggregation methods were performed using principal component analysis and fuzzy sets. Results: The five principal components were classified through principal component analysis (PCA) and obtained eigenvalues >1.0 from the initial 18 indicators. The aggregated index was obtained by condensing the original information into two broad and simple categories through fuzzy sets. Conclusion: This could be useful in that the aggregation procedure may provide a basis for establishing environmental health policies and a decision-making process. However, the availability and quality of indicators, assessment of aggregation method bias, choice of weighted scores for indicators, and other factors should be examined in future studies.

• Food Science and Biotechnology
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• v.15 no.5
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• pp.715-720
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• 2006

This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of $R^2{\geq}0.9192$. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ($R^2\;=\;0.97$ for SGR and $R^2\;=\;0.86$ for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor ($B_f$ was 0.6 for SGR and 0.97 for LT).

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.53-59
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• 2021

This research aims to examine the model of investor herding behavior in making investment decisions in the Indonesian capital market, which is influenced by social and information impacting on the value of the Book Value Per Share (BVPS). The latest stock market conditions show that most investors make the same error pattern in making investment decisions that result in losses. The experiment involves two independent variables, namely, information about BVPS and social influence. This study used a 2×2 factorial design laboratory experimental method. Data collection was carried out through treatment of a sample of 100 individual investors listed on the Indonesia Stock Exchange. Univariate Two-Way Analysis of Variance (ANOVA) statistical tool was used to test the independent variable on the dependent variable. Research results showed that the social influence originating from expert investors is more influential than the Book Value Per Share (BVPS) information on the behavior of herding investors in making investment decisions. These findings suggest that investors know their psychological factors, thereby increasing self-control and investment analysis skills. Further research can use psychological bias and other indicators of accounting relevant information such as Earning Per Share (EPS) to test herding behavior in investment decision making in the capital market.

• The Journal of Korean Association of Computer Education
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• v.6 no.1
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• pp.41-54
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• 2003

Educational web sites are proliferating at an astonishing rate, however many of those web sites are of poor or unknown quality. Educators are in need of instruments to assist in evaluating educational web sites for authenticity, applicability, authorship, bias, and usability, etc. The ability to critically evaluate educational content form numerous web sites is an important skill in this information age. In this paper, indicators of educational web site quality have been identified from literature review and our own research, and classified within 8 categories. To test the relative contribution of each indicator to the satisfaction level from using educational web sites, a questionnaire survey was administered. Subjects were asked to visit the educational web site of his or her choice and rate the quality level of each indicator. 255 completed questionnaires were turned in for analysis. Cronbach's Alpha test and factor analysis were applied to test the reliability and validity of the data. Stepwise regression analysis was applied to test the relationship between the satisfaction level and 14 independent factors. Implications from the statistical analysis as well as the guidelines for evaluating educational web sites were provided.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.157-166
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• 2021

Forecasting dam inflow based on high reliability is required for efficient dam operation. In this study, deep learning technique, which is one of the data-driven methods and has been used in many fields of research, was manipulated to predict the dam inflow. The Long Short-Term Memory deep learning with Sequence-to-Sequence model (LSTM-s2s), which provides high performance in predicting time-series data, was applied for forecasting inflow of Soyang River dam. Various statistical metrics or evaluation indicators, including correlation coefficient (CC), Nash-Sutcliffe efficiency coefficient (NSE), percent bias (PBIAS), and error in peak value (PE), were used to evaluate the predictive performance of the model. The result of this study presented that the LSTM-s2s model showed high accuracy in the prediction of dam inflow and also provided good performance for runoff event based runoff prediction. It was found that the deep learning based approach could be used for efficient dam operation for water resource management during wet and dry seasons.

• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.617-631
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• 2022

In this paper the viscoelastic responses of four experimental steel-concrete composite beams subjected to highly variable environmental conditions are investigated by means of a finite element (FE) model. Concrete specimens submitted to stepped stress changes are also evaluated to validate the current formulations. Here, two well-known approaches commonly used to solve the viscoelastic constitutive relationship for concrete are employed. The first approach directly solves the integral-type form of the constitutive equation at the macroscopic level, in which aging is included by updating material properties. The second approach is postulated from a rate-type law based on an age-independent Generalized Kelvin rheological model together with Solidification Theory, using a micromechanical based approach. Thus, conceptually both approaches include concrete hardening in two different manners. The aim of this work is to compare and analyze the numerical prediction in terms of long-term deflections of the studied specimens according to both approaches. To accomplish this goal, the performance of several well-known model codes for concrete creep and shrinkage such as ACI 209, CEB-MC90, CEB-MC99, B3, GL 2000 and FIB-2010 are evaluated by means of statistical bias indicators. It is shown that both approaches with minor differences acceptably match the long-term experimental deflection and are able to capture complex oscillatory responses due to variable temperature and relative humidity. Nevertheless, the use of an age-independent scheme as proposed by Solidification Theory may be computationally more advantageous.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.141-157
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• 2023

Start-ups are the driving force of economic development and play an important role in improving national competitiveness. The country's start-up support policies are increasing every year, but indicators that do not challenge them and do not consider future start-ups can predict employment reduction and unemployment can increase further. You can. The increase in the number of young people doing nothing is causing economic hardship and neglect of future precious human resources, which calls for a more realistic national entrepreneurship policy. Accordingly, this study sought to identify bias and environmental factors in order to reveal factors that influence the will to start a business among potential entrepreneurs in Korea. For this purpose, descriptive statistical analysis was performed using SPSS on a sample of 227 responses from the general public who are potential entrepreneurs interested in starting a business. As a result, prejudice decreased the will to start a business and increased fear of failure. On the other hand, the entrepreneur's environmental factors reduced the fear of failure and increased the will to start a business. Lastly, fear of failure was found to play a mediating role between the two independent variables and the will to start a business. The results of this study showed that prejudice was a negative factor in the will to start a business, and the environment was a positive factor. These research results suggest that in order to revitalize entrepreneurship, positive environmental factors that can provide entrepreneurs' correct recognition and support for entrepreneurship are necessary.

• Journal of Global Scholars of Marketing Science
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• v.20 no.3
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• pp.269-277
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• 2010

Previous studies have shown that the most important factor affecting customer loyalty in the service industry is service quality. However, on the subject of whether service quality has a direct or indirect effect on customer loyalty, scholars' views apparently vary. Some studies suggest that service quality has a direct and fundamental influence on customer loyalty (Bai and Liu, 2002). However, others have shown that service quality not only directly affects customer loyalty, it also has an indirect impact on customer loyalty by influencing customer satisfaction and perceived value (Cronin, Brady, and Hult, 2000). Currently, there are few domestic articles that specifically address the relationship between service quality and customer loyalty in the mobile communication industry. Moreover, research has studied customer loyalty as a whole variable, rather than breaking it down further into multiple dimensions. Based on this analysis, this paper summarizes previous study results, establishes an effect mechanism model among service quality, customer satisfaction, and customer loyalty in the mobile communication industry, and presents a statistical test on model assumptions by using customer investigation data from Heilongjiang Mobile Company. It provides theoretical guidance for mobile service management based on the discussion of the hypothesis test results. For data collection, the sample comprised mobile users in Harbin city, and the survey was taken by random sampling. Out of a total of 300 questionnaires, 276 (92.9%) were recovered. After excluding invalid questionnaires, 249 remained, for an effective rate of 82.6 percent for the study. Cronbach's ${\alpha}$ coefficient was adapted to assess the scale reliability, and validity testing was conducted on the questionnaire from three aspects: content validity, construct validity. and convergent validity. The study tested for goodness of fit mainly from the absolute and relative fit indexes. From the hypothesis testing results, overall, four assumptions have not been supported. The ultimate affective relationship of service quality, customer satisfaction, and customer loyalty is demonstrated in Figure 2. On the whole, the service quality of the communication industry not only has a direct positive significant effect on customer loyalty, it also has an indirect positive significant effect on customer loyalty through service quality; the affective mechanism and extent of customer loyalty are different, and are influenced by each dimension of service quality. This study used the questionnaires of existing literature from home and abroad and tested them in empirical research, with all questions adapted to seven-point Likert scales. With the SERVQUAL scale of Parasuraman, Zeithaml, and Berry (1988), or PZB, as a reference point, service quality was divided into five dimensions-tangibility, reliability, responsiveness, assurance, and empathy-and the questions were simplified down to nineteen. The measurement of customer satisfaction was based mainly on Fornell (1992) and Wang and Han (2003), ending up with four questions. Based on the study’s three indicators of price tolerance, first choice, and complaint reaction were used to measure attitudinal loyalty, while repurchase intention, recommendation, and reputation measured behavioral loyalty. The collection and collation of literature data produced a model of the relationship among service quality, customer satisfaction, and customer loyalty in mobile communications, and China Mobile in the city of Harbin in Heilongjiang province was used for conducting an empirical test of the model and obtaining some useful conclusions. First, service quality in mobile communication is formed by the five factors mentioned earlier: tangibility, reliability, responsiveness, assurance, and empathy. On the basis of PZB SERVQUAL, the study designed a measurement scale of service quality for the mobile communications industry, and obtained these five factors through exploratory factor analysis. The factors fit basically with the five elements, indicating the concept of five elements of service quality for the mobile communications industry. Second, service quality in mobile communications has both direct and indirect positive effects on attitudinal loyalty, with the indirect effect being produced through the intermediary variable, customer satisfaction. There are also both direct and indirect positive effects on behavioral loyalty, with the indirect effect produced through two intermediary variables: customer satisfaction and attitudinal loyalty. This shows that better service quality and higher customer satisfaction will activate the attitudinal to service providers more active and show loyalty to service providers much easier. In addition, the effect mechanism of all dimensions of service quality on all dimensions of customer loyalty is different. Third, customer satisfaction plays a significant intermediary role among service quality and attitudinal and behavioral loyalty, indicating that improving service quality can boost customer satisfaction and make it easier for satisfied customers to become loyal customers. Moreover, attitudinal loyalty plays a significant intermediary role between service quality and behavioral loyalty, indicating that only attitudinally and behaviorally loyal customers are truly loyal customers. The research conclusions have some indications for Chinese telecom operators and others to upgrade their service quality. Two limitations to the study are also mentioned. First, all data were collected in the Heilongjiang area, so there might be a common method bias that skews the results. Second, the discussion addresses the relationship between service quality and customer loyalty, setting customer satisfaction as mediator, but does not consider other factors, like customer value and consumer features, This research will be continued in the future.