The objectives of this research is to study (1) The factor of decision making in Bangkok high school students affected to study in bachelor of Mass Communication (English Program) (2) The factor that is correlated in decision making in Bangkok high school students affected to study in bachelor of Mass Communication (English Program). The sample population consisted of four hundreds high school students in Bangkok. The instrument of research was a questionnaire. The Statistical Package for the Social Sciences (SPSS) for Windows computer program was applied for analyzing formulating and tabulating the data collected. The techniques of descriptive statistics used were percentage mean and standard deviation. Techniques of inferential statistics utilized were t-test one-way analysis of variance (ANOVA) in order to analyze differences between variables taken as a group. If there is a statistically significant differences found between pairs in a group Scheff?’s pair testing were deployed. Multiple Regression Analysis were applied in order to analyze the factors of decision making in Bangkok high school students affected to study in bachelor of Mass Communication (English Program). If there is a statistically significant found in Multiple Regression Coefficient of Correlation under paired testing will be used to identify the correlation between factors. The results were as following: 1. The factors of student program in high school affected the decision making to study in bachelor of Mass Communication (English Program) were high school program. 2. The marketing factor of Mass Communication Technology affected to Bangkok high school students decision making to study in Bachelor of Mass Communication (English Program) is product price place promotion.

This research aims to study strategies required for developing educational game for preschool students and the development processes involved. The sampling groups used in this research included 3 content specialists whose responsibility is to verify the content of the games and 17 specialists on educational game. The sampling groups are selected particularly from the central region of Thailand. The research findings reveal the insights from the majority of specialists on development of educational games for preschool children as follow: games such as picture-matching domino object ordering object categorizing detail observing and number addition & subtraction games are popular for teaching. Moreover the principles for applying educational games with lessons should be incorporated in the development of game strategies. In addition the main objectives and the development process of games should focus primarily on their ability to draw attention from students as well as the fun of playing and allowing students to practice lessons and participate in class activities. The tools used for developing games are computers and devices created by teachers themselves. As for the future of educational game the trend is the more involvement of technology through the use of computer or mobile devices. Problems in game development include limited budget for purchasing hardware and devices. On top of that training on game development is much needed among teachers. The research results can be concluded with the following 5 strategies for preschool students: 1) enhance teachers’ knowledge and skills 2) study details of different kinds of games 3) develop games 4) determine time used for playing game 5) evaluate the process of game development in 4 areas including type of game devices used rules and playing instruction.

This paper discusses the mixed alloy silver pink by spending innocent Alloy capital ratio of 58.00% and check the analysis of color against Silver 925 under the metal content of about 58.40% alloy 41.60% result. According to the study the researchers used to hold above ingredients prototype to develop a mixture of silver to feature pink by analyzing the color (Color Analysis) tested the color of silver mixed pink capital ratio of 116.80 alloy. 83.20 wt.% has a shiny bright color space the L 67.17 a = 9.60 b = 2.04 a compound that can be used to produce silver mixed pink. In the manufacturing industry has for the user.

The objectives of this research are to propose a proper model for defective products in an autoparts manufacturing industry to apply the proposed model to the defective products data to investigate the factors related to the machines producing defective products and to compare the proposed model with the generalized estimating equations model (GEE). The proposed model is a generalized linear mixed model (GLMM) in which the dependent variables have a Poisson distribution. The parameter are estimated using a Bayesian method. The data were collected from 12 machines 15 days for each machine from an autoparts manufacturing factory. The data collection dates vary depending on the working steps and the product types. The results show that the proposed model fits the data. The factors related to the machines producing defective products are working steps workers and product types. According to the estimates of the factors effects the working step producing the largest number of defective products is the working step 2 followed by the working steps 3 1 and 4 respectively. The worker producing the largest of defective products is the worker 4 followed by the workers 10 5 8 6 2 3 1 7 and 9 respectively. The product type 3 has the largest number of defective products followed by the product types 2 and 1 respectively. If the population-averaged effects are focused the GEE is applied. However the subject-specific is focused the GLMM is applied.

The objective of this research is to use a stochastic process for building a model using Bayesian parameter estimation. The model is applied to the of crash prices and future prices of rice in Thailand for 120 moths including monthly closing average price of white rice 5% non-glutinous paddy 15% and Hom Mali non-glutinous paddy 105. The data are time series data containing autocorrelation trend seasonality and outliers. The algorithms are turned into codes in OpenBugs and the performance of the model is evaluated using simulation in R. The model with a Weibull cumulative distribution function trend the model with an exponential cumulative distribution function trend and the exponential smoothing model are compared. The root mean squared error (RMSE) mean absolute percentage error (MAPE) and mean absolute error (MAE) are used as the criteria. The results show that the model with the model with an exponential cumulative distribution function trend gives smallest RMSE MAPE and MAE for the crash prices of non-glutinous paddy 15% and Hom Mali non-glutinous paddy 105 for both model fitting part and model validation part. The model with a Weibull cumulative distribution function trend gives the smallest RMSE MAPE and MAE for the closing average price of white rice 5% for both model fitting part and model validation part.