The purpose of this research was to study coexistence of people with mangrove forest and wisdom of using resources for economic benefits in the Yisan community Samut Songkhram Province with qualitative research techniques. The sample groubs were 30 of people living in the Yisan community Tools used in data collection were structured interview participant and nonparticipant observation The results showed that coexistence of people with mangrove forest made Yisan people have wisdom concerning the amount of fish in each area by means of a color view of the water have wisdom concerning food processing of plants and aquatic animals for consumption and have wisdom concerning using resources from mangrove forest for economic benefits by making mangrove farming and producing charcoal for business The mangrove charcoal were traded domestically and internationally such as in Japan Korea Taiwan and the United States. They were main revenue for people in the community.

This research aimed to design and construct a forecasting support system on demand of fresh durian of Thailand by applying 2 mathematical models which were Time Series model and Artificial Neural Network model in order to find an accurate model of forecasting support system on demand of durian yield to forecast durian yield quantity of Thailand in advance and use the forecast results to plan and determine quantity of fresh durian and durian product conforming with domestic consumption and export in order not to be over demand and cheap durian sold price. The forecast models were applied with Time Series model by using Moving Average Weighted Moving Average Single Exponential Smoothing and Holt’s Linear Exponential Smoothing techniques and Back Propagation of Artificial Neural Network model which used 4 input variables relating to durian yield. All of the forecast models were used to forecast total durian yield quantity in 26 provinces of durian cultivated area all around Thailand. Durian yield quantity data used was from 1996 to 2008. After that the forecast results were used to find the errors of MAE MSE RMSE and MAPE. Then the errors of each forecast model were compared. The forecast model which had the least error was the most accurate forecast model. The research result is following. Back Propagation with 4-8-1 structure of Artificial Neural Network model had the least error so that it was the most accurate forecast model to forecast fresh durian yield quantity in advance.

The objective of this research is to design forecasting support models on demand of durian for domestic markets and export markets for durian gardeners durian entrepreneurs of domestic markets and export markets and the Office of Agricultural Economics to plan durian demand conforming with domestic markets and export markets because of Production and marketing main problems (The Agricultural Information Center The office of Agricultural Economics: 2008) such as over - much durian production during production capital increased farmers durian sold price tended to be lower and lower inefficient domestic market management and more export but cheaper price therefore after that to design forecasting for the purpose in order that durian would not be over demand which is containing factors of the demand of durian fresh durian frozen durian paste and durian chips for domestic markets and export markets exported to Asia America Australia and Africa. The research involves historical collection data in the period of 2002 to 2008. The basic of forecast models are the designed and improved models using an intelligent knowledge-based approach beginning Moving average Deseasonalized Exponential smoothing Double exponential smoothing and Artificial neural network (ANNs) program within the model of new value Creation and comparative accuracy models. The evaluation result of forecasting durian demand showed that lowest MAPE of Deseasonlized models at 3 month was durian fresh durian frozen and durian paste but durian chips showed that lowest MAPE of ANNs at 4 input 10 hidden layers and 1 output was high accurate forecasting and optimal models. The analysis recommendations and error forecast of durian demand are also presented.

In this research palm oil fuel ash was utilized as a pozzolanic material in blended Portland cement mortar. The mortar was tested on the normal compressive strength and the negative effect of carbonation in indoor environment using the accelerated carbonation test of 5% CO2 in 50% relative humidity. Three palm oil fuel ash fractions of different fineness viz. coarse original palm oil fuel ash (CPOA) medium palm oil fuel ash (MPOA) and fine palm oil fuel ash (FPOA) were used for the study. Ordinary Portland cement (OPC) was partially replaced by these palm oil fuel ashes at the dosages of 20% and 40% by weight of binder. The results showed that the incorporation of the ashes affected the strength and the carbonation depths of mortars. The strengths of mortar slightly decreased with the increases in the dosage of the ash. The fineness of ash on the other hand improved the strength and the carbonation of the mortars. The mortars containing FPOA exhibited high strength and relatively low carbonation in comparison to those using coarser MPOA and CPOA. The use of FPOA resulted in a strong and dense mortar owing to the increased packing effect and pozzolanic reaction. It was therefore demonstrated that the FPOA could be used as a pozzolanic material to replace part of Portland cement for use in the indoor environment.

The research aimed to: 1. study and compare food and nutrition knowledge of adolescence by looking at gender and level of education. 2. study and compare the awareness of food and nutrition by comparing gender and level of education. 3. study and compare the practice of food and nutrition by comparing gender and level of education. 4. study the relationship between knowledge awareness and practice of food and nutrition of the adolescence in Muang District Prachinburi Province. Tests and questionnaires were used to gather the data from 346 samples. The Stratified Random Sampling was used. The data were analyzed by using percentile mean standard deviation t-test one way analysis of variance and Pearson’s Product Moment correlation at 0.01 - 0.05 significant level. The study found that 1. 71.4% of the samples were female and 41.0% of the samples were high school graduates. 2. The sampling adolescence had good knowledge of food and nutrition. Different gender had significantly different level of food and nutrition knowledge at 0.01 while different level of study had no different level of food and nutrition knowledge. 3. The sampling adolescence had food and nutrition awareness at high level. Different gender had significantly different level of food and nutrition awareness at 0.01 while different level of study had no different level of food and nutrition awareness. 4. The sample group had good food and nutrition practice at moderate level with no difference between gender and level of study. 5. There was a positive relationship between food and nutrition knowledge awareness and practice of the adolescence at 0.05. The relationship between knowledge and awareness was moderate and the relationship between knowledge and practice was low.