Admission to higher education By students who come to study later from different institutions Different residence But have to live in the same university Which must meet An environment with a difference Social trends or values of the current society that have Quick change Friends that have a wide variety of family and social basics are also popular. The lifestyle which students who come to study in the Faculty of Engineering must have patience there is discipline and responsibility; there is morality ethics and sacrifice. Therefore it will succeed as a good and qualified engineer. Creative recruitment process it is considered that it is important to the lifestyle of a new group of students to have the opportunity to build a good relationship with their studies in engineering. Able to develop good relationship in future career in engineer A creative approach to recruiting to build relationships towards engineering studies. By organizing seminars to guide creative recruiting from people related to students Which consists of administrators teachers And staff of the Faculty of Engineering the objective of the official recruitment is creatively to find ways to create creative recruiting in the Faculty of Engineering and to create positive values for the Faculty of Engineering students. So that students are conscious of building a good relationship to study engineering.

Continuing Professional Development for Engineers is any structured process or activity that enhances the competence and quality of a person necessary to perform a professional job. The continuing engineering profession is a useful tool for professionals. The objectives of the research is to find a short course approach for the continuous development of the engineering profession to meet the needs of industrial engineers in the current era to have knowledge and ability in technology continuously it is important that all engineers have to attend training to enhance their knowledge. Which the development of the knowledge of the engineer As part of the promotion of license for professional practice at the ordinary level and degree engineer Including the registration as an ASEAN Engineer and APEC Engineer.

The objectives of this research were to propose a model with some functions including CAR spatial effects and to select a proper model for predicting rince and rubber yields in southern provices of Thailand. A linear mixed model (LMM) with spatial effects and dummy varables and Fourier seasonal effects was proposed. Bayesian estimation was used and the estimated rice and rubber yields were used for prediction. The dependent variables were rice and rubber yields in southern provinces of Thailand. Factors considered were rain temperature soil fertilizer soil organic matter trend and also sesonal effects. The results show that rain temperature soil fertilizer soil organic matter trend and sesonal effects influence on rice and rubber yields. The proposed model with Fourier seasonal term is the most appropriate comparing to the model with dummy variable for season effects and the Holt-Winters model. Therefore the proposed model with Fourier sesaonal term should be the first consideration for prediction.

This research aims to apply the principle of stochastic process for modeling. The parameters are estimated using Bayesian methods. The monthly average real price of paddy rice 15% and yield of paddy rice in Thailand were studied. The price and the yield of paddy rice which are time series data consisting of four components autocorrelation an exponential cumulative distribution function for trend outliers and two different types of seasons: the dummy seasons and Fourier function seasons. Writing algorithms programming in OpenBUGS and evaluating the performance of models from simulation programming in R were conducted. After that Bayesian methods with dummy seasons and Fourier function season were compared using RMSE MSE and MAE as the criteria. The results show that the Bayesian model with an exponential cumulative distribution function for trend and dummy seasons give the lowest RMSE MSE and MAE for both model fitting and model validating.

The objectives of this research are to propose a Bayesian model for spatial time series analysis to apply the proposed model to forecast a monthly rubber yield in Southern provinces of Thailand and to compare the performance of the proposed model with the classical Holt-Winters Additive Exponential smoothing. The proposed model is a linear mixed model (LMM) with spatial effects which follow a conditional autoregressive model (CAR). Dummy variables are used for seasonal effects. A Bayesian method is used for parameter estimation. The estimated monthly yields are used for the monthly rubber yield forecasting. The dependent variables are the rubber yield in each month of each province. The data are secondary data at a provincial level. The factors considered are spatial effects heterogeneity effects and seasonal effects. The results show that the factors influencing on the amount of rubber yields are spatial heterogeneity and seasonal effects. The proposed model is proper and forecast accurately. Using the mean absolute error (MAE) the proposed model has a better performance compared to the classical Holt-Winters Additive Exponential smoothing in both model fitting and model validating. The proposed model should be the first consideration for spatial time series forecasting.