• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.47-56
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• 1998

Zero-Inflated Poisson models are mixed models of the Poisson and Bernoulli models. Recently Zero-Inflated Poisson distributions have been used frequently rather than previous Poisson distributions because the developement of industrial technology make few defects in manufacturing process. It is important that univariate Zero-Inflated Poisson distributions are extended to bivariate distributions to generalize the multivariate distributions. In this paper we proposed three types of the bivariate Zero-Inflated Poisson distributions and obtained these moments. We compared the three types of distributions by using the moments.

• Safety and Health at Work
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• v.9 no.1
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• pp.109-114
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• 2018

Background: Although work absenteeism is in the focus of occupational health, longitudinal studies on organizational absenteeism records in hospital work are lacking. This longitudinal study tests time pressure and lack of time autonomy to be related to higher sickness absenteeism. Methods: Data was collected for 180 employees (45% nurses) of a Swiss hospital at baseline and at follow-up after 1 year. Absent times (hours per month) were received from the human resources department of the hospital. One-year follow-up of organizational absenteeism records were regressed on self-reported job satisfaction, time pressure, and time autonomy (i.e., control) at baseline. Results: A multivariate regression showed significant prediction of absenteeism by time pressure at baseline and time autonomy, indicating that a stress process is involved in some sickness absenteeism behavior. Job satisfaction and the interaction of time pressure and time autonomy did not predict sickness absenteeism. Conclusion: Results confirmed time pressure and time autonomy as limiting factors in healthcare and a key target in work redesign.

• Korean Journal of Remote Sensing
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• v.5 no.2
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• pp.109-122
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• 1989

The ISODATA method, which is one of the most famous of the square-error clustering methos, has been applied to two Chungju multivariate data sets in order to evaluate the effectiveness of the regional lithological mapping. One is an airborne radiometric data set and the other is a mixed data set of the airborne radiometric and Landsat TM data. In both cases, the classification of the Bulguksa granite and the Kyemyongsan biotite-quartz gneiss are the most successful. Hyangsanni dolomitic limestone and neighboring Daehyangsan quartzite are also classified by their typical lowness of the radioactive intensities, though it is still confused with some others such as water-covered areas and nearby alluvials, and unaltered limestone areas. Topographically rugged valleys are also classified as the same cluster as above. This could be due to unavoidable variations of flight height and the attitude of the airborne system in such rugged terrains. The regional geological mapping of sedimentary rock units of the Ockchun System is in general confused. This might be due to similarities between different sediments. Considarable discrepancies occurred in mapping some lithological boundaries might also be due to secondary effects such as contamination or smoothing in digitizing process. Further study should be continued in the variable selection scheme as no absolutely superior method claims to exist yet since it seems somewhat to be rather data dependent. Study could also be made on the data preprocessing in order to reduce the erratic effects as mentioned above, and thus hoprfully draw much better result in regional geological mapping.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.1073-1081
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• 2018

In this study, an operational data set was analysed by establishing a path model to figure out the actual cause-effect relationship of a wastewater treatment plant (WWTP); in particular, for the effluent concentrations of T-N and T-P. To develop the path models, data sets of operational records including effluent concentrations and operational factors were obtained from a field scale WWTP of $680,000m^3$ of treatment capacity. The models showed that the relationship networks with the correlation coefficients between variables for objective expressions indicated the strength of each relationship. The suggested path models were verified according to whether the analyzation results matched known theories well, but sophisticated minute theoric relationships could not be cropped out distinctly. This indicates that only a few paths with strong theoric casual relationships were represented as measured data due to the high non-linearity of the mechanism of the removal process in a biological wastewater treatment.

• Computers and Concrete
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• v.27 no.4
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• pp.305-317
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• 2021

The bond between the concrete and bar is a main factor affecting the performance of the reinforced concrete (RC) members, and since the steel corrosion reduces the bond strength, studying the bond behavior of concrete and GFRP bars is quite necessary. In this research, a database including 112 concrete beam test specimens reinforced with spliced GFRP bars in the splitting failure mode has been collected and used to estimate the concrete-GFRP bar bond strength. This paper aims to accurately estimate the bond strength of spliced GFRP bars in concrete beams by applying three soft computing models including multivariate adaptive regression spline (MARS), Kriging, and M5 model tree. Since the selection of regularization parameters greatly affects the fitting of MARS, Kriging, and M5 models, the regularization parameters have been so optimized as to maximize the training data convergence coefficient. Three hybrid model coupling soft computing methods and genetic algorithm is proposed to automatically perform the trial and error process for finding appropriate modeling regularization parameters. Results have shown that proposed models have significantly increased the prediction accuracy compared to previous models. The proposed MARS, Kriging, and M5 models have improved the convergence coefficient by about 65, 63 and 49%, respectively, compared to the best previous model.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.335-346
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• 2022

Profile control chart aims to detect a change in the functional relationship of multivariate characteristics in the statistical process control. In monitoring two variables, a linear profile is of interest composed of the intercept and slope of one variable (response variable) against the other (explanatory variable). The previous studies on monitoring of the linear profile mostly assume that the explanatory variables are the same for all profiles. However, there are also cases where they vary depending on profiles. This paper intends to extend the monitoring method to where explanatory variables are different for each profile. We compare the new method's performance through simulation and apply it to monitoring a network intrusion using NSL-KDD data.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.294-303
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• 2022

The purpose of this study is to examine the effects of sensory integration training on children with developmental delays. To achieve this goal, an educational experiment is conducted in five main areas: gross motor ability, fine motor ability, adaptive ability, language and social ability in children with developmental delay. The study subjects were children with developmental delays aged 3-6 years diagnosed at Beijing Institute of Pediatrics and Beijing Medical University and received sensory integration intervention and homebased training at the Golden Rain Forest Beijing Tongzhou Center from 2018 to 2021. According to the purpose of the analysis, the data collected are subjected to descriptive statistics using SPSS 21.0 statistical program, Two-way MANOVA analysis, and data analysis method of multivariate analysis is used to process the collected data. In addition, a total of 39 subjects were selected, including 19 children who received sensory integration training and 20 children who only received family training. The results show that the sensory integration training group outperformed the home training group in all aspects and developmental quotient, but the home training group also showed higher levels of significance for improvements in gross motor, fine motor and developmental quotient.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.902-907
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• 2023

To understand the eutectic reaction mechanism and the relocation behavior of the core debris is indispensable for the safety assessment of core disruptive accidents (CDAs) in sodium-cooled fast reactors (SFRs). This paper addresses reaction products and their distribution of the eutectic melting/solidifying reaction of boron carbide (B₄C) and stainless-steel (SS). The influence of the existence of carbon on the B₄C-SS eutectic reaction was investigated by comparing the iron boride (FeB)-SS reaction by Raman spectroscopy with Multivariate Curve Resolution (MCR) analysis. The scanning electron microscopy with dispersive X-ray spectrometer was also used to investigate the elemental information of the pure metals such as Cr, Ni, and Fe. In the B₄C-SS samples, a new layer was formed between B₄C/SS interface, and the layer was confirmed that the formed layer corresponded to amorphous carbon (graphite) or FeB or Fe₂B. In contrast, a new layer was not clearly formed between FeB and SS interface in the FeB-SS samples. All samples observed the Cr-rich domain and Fe and Ni-rich domain after the reaction. These domains might be formed during the solidifying process.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.373-373
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• 2021

Rainfall forecasting is an important issue that is applied in many areas, such as agriculture, flood warning, and water resources management. In this context, this study proposed a statistical and machine learning-based forecasting model for monthly rainfall. The Bayesian Gaussian process was chosen to optimize the hyperparameters of the Stacked Long Short-term memory (SLSTM) model. The proposed SLSTM model was applied for predicting monthly precipitation of Seoul station, South Korea. Data were retrieved from the Korea Meteorological Administration (KMA) in the period between 1960 and 2019. Four schemes were examined in this study: (i) prediction with only rainfall; (ii) with deseasonalized rainfall; (iii) with rainfall and minimum temperature; (iv) with deseasonalized rainfall and minimum temperature. The error of predicted rainfall based on the root mean squared error (RMSE), 16-17 mm, is relatively small compared with the average monthly rainfall at Seoul station is 117mm. The results showed scheme (iv) gives the best prediction result. Therefore, this approach is more straightforward than the hydrological and hydraulic models, which request much more input data. The result indicated that a deep learning network could be applied successfully in the hydrology field. Overall, the proposed method is promising, given a good solution for rainfall prediction.

• Educational Technology International
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• v.6 no.2
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• pp.113-130
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• 2005

The purpose of this study was to determine the teaching styles of professors who teach adult students in selected higher institutions. It also identified whether professors' teaching styles were teacher-centered or learner-centered and examined the relationship between instructors' teaching styles and such instructor demographic variables as gender, years of teaching experience, and taught level of courses. This study used The Principles of Adult Learning Scale(PALS) (Conti,1983) to measure instructional preferences. Demographic characteristics were collected through a personal data inventory. The analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA) tests were used to analyze the data. The data were examined for significance at the .05 level of confidence by means of analysis of variance. The dependent variables in this study were teaching styles of full-time professor, as represented by the seven subscores from the standardized instrument on the PALS. The seven subscores were: (1) learner-centered activities, (2) personalizing instruction, (3) relating to experience, (4) assessing student needs, (5) climate building, (6) participation in the learning process, and (7) flexibility for personal development. The study established that there was a significant difference in mean scores on the PALS between participants when examined by the number of years of teaching experiences.