The data fusion is implement to take the survey data remotely from difference sources and have various looks to be combined to get a new agents. To get better quality of data we will present a method of fusion by wavelet transform with IHS Transformation method or PCA Transformation method. From the results showed that both IHS and PCA Transformation method able to be gotten high quality but the specifications of wave from damage is different.

The objective of this research was presented a decision support making process for efficiency improvement of drinking water processing using retrofit technique for machine and equipment rehabilitate. This methodology was applied Analytic Hierarchy Process (AHP) for selecting an appropriate maintenance sub-contractor. To complete the research existing water purifying machine and tools were inspected to assess its capacity. Future capacity of the purifying machine was also identified. Consequently machine and tools such as water tank and water filter were inspected for retrofitting for the example water tank water filter water quality control and bottle packing. Finally the analytic hierarchy process was utilized to select the most appropriate maintenance sub-contractor. In this process both qualitative and quantitative processes were analysed. The result of this research has been found that this multicriteria decision making process could be used to support the decision making investment process of water purification retrofit unit at Faculty of Engineering Rajamangala University of Technology Phra Nakorn efficiently. Furthermore it could be reduced bias from decision makers while the decision was accepted by all stakeholders.

CO2 emission of rail transportation system plays more important role including the expansion of BTS route that consume the energy and emit CO2 gas more and more. The purpose of this research was to find out amount of CO2 emission from travelling by BTS train and determine specific CO2 emission per product in the form of gCO2e/passenger/km then forecasting on CO2 emission from BTS operations. Research process was initiated from collecting monthly data on ridership distance and electricity for 55 months continuously then regression analysis CUSUM and time series analysis were used for prediction and analysis of CO2 emission. The finding indicated that BTS’s specific CO2 emission was 24.7 gCO2e/passenger/km. Forecasting CO2 Emission from BTS result that Winters Exponential Smoothing Method is most accuracy then Double Exponential Smoothing Method Trend Analysis Method and Decomposition Method respectively. The result of these analysis could be used to calculate carbon footprint from staff travelling by BTS train and promote people to use public transport by government as sustainable transportation concept.

The creation of nightgown decorated by woven silk yarn scrap from Baan Krua Cottage Industrial Village in Ratchathewi Bangkok Thailand. Objectives are: 1) to study the weaving technique using the silk yarn scrap 2) to design a nightgown decorated with woven silk yarn scrap and 3) to study the overall satisfaction of nightgown designs which utilize silk yarn scrap. The sample population in this research is 250 women found on Silom Road central Bangkok. The research instrument is a questionnaire with 9 prototype nightgowns decorated with woven silk yarn scrap. The collection consists of 3 sets one set with 3 short nightgowns another set with 3 long nightgowns and the last set with 3 short nightgowns with long tails. The research methodology is to hand out the questionnaire to 250 non-specific women on Silom Road. Data analysis is done by statistic percentage average and standard deviation. Results of studying the survey show that most of the sample populations are women age between 31 -35 years old with bachelor degrees or the equivalent. Most are married and work as state enterprise officers. Incomes are between 20001 - 30000 baht. Most of them have bought a silk nightgown before and chosen to buy at department stores. The reason that they do not prefer silk nightgowns is because most in the current market are not innovative enough. Most of the sample populations have never seen a nightgown decorated with woven silk yarn scrap before. The results of studying the satisfaction of the sample population found that for the short nightgown set most of the sample population prefer number 2 standard deviation is 4.48. For the long nightgown set most of the sample populations prefer number 2 standard deviation is 4.44. And for the short nightgown with long tail set most of the sample populations prefer number 2 standard deviation is 4.46.