Development of table cloth products from Batik tie-dyed cotton fabric with waterproof finishes aimed 1) to study waterproof finishes process to Batik tie-dyed cotton fabric 2) to test physical properties of Batik tie-dyed cotton fabric and 3) to study satisfaction of consumer to table cloth products from Batik tie-dyed cotton fabric with waterproof finishes. Prototype of table cloth products and questionnaire was used as the tools in this research. The samplings for this study were the 323 consumers from accidental sampling in Faculty of Home Economics Technology and Faculty of Architecture and Design Rajamangala University of Technology Phra Nakhon. Data was analyzed by percentage mean and standard deviation. Reported of physical properties testing of Batik tie-dyed cotton fabric with waterproof finishes as follows; colorfastness to water testing changed in color was grade 4-5 dimensional changes after laundering testing decrease 1.14 percentage in the length and 0.48 percentage in the width colorfastness by hot pressing testing; dry pressing damp pressing and wet pressing changed in color was grade 4-5 and water resistance testing found that surface area having wet patches small. The results from study satisfaction of development of table cloth products from Batik tie-dyed cotton fabric with waterproof finishes were found that; the sample age between 21-30 years bachelor degree education level status of student and monthly income 100001-20000 baht. Consumers purchased and used Batik tie-dyed product categories of clothing agree with table cloth products from Batik tie-dyed cotton fabric with waterproof finishes and selected to buy after this product launch to market from personal preference reason. Color and design price appearance and special properties are the reasons to choose. The total satisfaction to products was highly satisfied (mean 3.65).

Objectives of this study were to design and develop seamless womens wear using pattern techniques and to study customers satisfaction of seamless womens wear using pattern techniques. The researcher designed 5 categories of womens wear coat blouse dress skirt and pants. Proper designs for sewing prototypes were selected by experts. These were made from three types of fabrics light medium and heavy. Customers satisfaction survey was made from 385 women working in private companies in Bang Rak Bang Kapi and Pathum Wan Districts of Bangkok. Accidental sampling of participants were asked to answer questionnaires. Data was analyzed by using packaged computer program. Statistics used were frequencies percentages means and standard deviations. The results showed that the majority of samples were aged between 26-30 years educational levels were bachelors degrees monthly income was between 15001-25000 Bahts never bought or used seamless womens wear consideration in buying was by preference bought every month at prices between 501-1000 Bahts per item. The overall customers satisfaction to seamless womens wear was at a very satisfied level at the mean of 4.12.

The research was aimed to: 1) create a standard formula of Sangyod brown-rice flour Thai Lodchong 2) study the change during storage and 3) study the consumers’ acceptance. The physical properties chemical composition sensory evaluation and microbiological quality were determined. The study showed that Lodchong in which the substitution of Sangyod brown rice flour at 50% by weight of rice flour and 30% of arowroot flour for the total flour weight were used was most accepted in all aspects. The product has a slight physical conversion at 7 °C for not longer than 48 hours. All the microorganisms yeast and mold found were still safe for consumers and none of Escherichia coli was detected in the product. Nutritional analysis results revealed that 100 grams of the product contained 78.64 kcal energy 0.98 g protein0.07 g fat 18.03 g carbohydrate dietary fiber 0.71 g and 11.63 mg anthocyanin. For consumers’ acceptance it was found that the product was much accepted and 99% of the consumers were interested to buy the product at 22 bath per 180 ml cup.

The purposes of this research were developing for health Thai custard dessert (Khanom Maw Kaeng) by using the Jerusalem artichoke powder and cereal cream instead of coconut cream. By using Jerusalem artichoke powder 3 types and 3 levels at 2 % 4 % and 6% the result of sensory evaluation from 40 nutrition experts had showed that using Jerusalem artichoke powder at 2% and 4% had been no significant difference at P<.05. The testing of custard with 4% of Jerusalem artichoke powder was receiving the result from a hundred consumers by the overall liking test using 9-point hedonic scale a hundred consumers rated the products like moderately to very and 100% of consumers accepted the product. Hardness of product was being 319.72 firmness was being 230.83 cohesiveness was being 0.17 and difficulty of crunch was being 24.85. The result of a physical attributes; the facial color was being bright at L* 37.13 the color value of green to red was being a* 8.27 and blue to yellow was being b* 12.15. But the color of product was being bright at L* 46.52 the color value of green to red at a* 5.06 and blue to yellow at b* 14.34 and the results of chemical factor were being; relative humidity was being 37.71 protein was being 14.36 fat 3.21 Ash 0.79 dietary fiber 3.23 total dissolved solid was being 33.27 carbohydrate was being 40.70 and total energy was being 249.13 respectively.

In this paper proposed remote sensing using Normalized Difference Vegetation Index from NOAA STAR cluster value from k-means temperature rainfall number of rainy days and runoff to create runoff prediction model using Artificial Neural Network (ANN) and evaluated runoff models with the R2 and RMSE. The results show that the using of cluster value with other parameters to create predictive models can enhance forecasting results. When using Normalized Difference Vegetation Index with temperature value at lag time 1-2 month and cluster value at lag time 1 month to create model with ANN we have got the best performance which are RMSE=0.09 and R2=0.743. The experimental results shows that remote sensing data and cluster value from k-means can be used to predictive the runoff effectively.