The objectives of this research are to study the production step proper ratio physical properties mechanical properties and thermal insulation of concrete blocks mixed with waste ceramic powder. The ratios of concrete block mixed with waste ceramic powder include Portland cement type1: quarry dust: waste ceramic powder equal to1: 6.8: 0.2 1: 6.7: 0.3 1: 6.6: 0.4 1: 6.5: 0.5 and1: 6.4: 0.6 by weight. Water per cement ratio are 0.6 by weight. The concrete block samples were castedby the general production as same as the ordinary concrete blocks and were tested follow TIS.58. From the results the best amount of waste ceramic powder which put into concrete block is 1: 6.7: 0.3 of ratio. The proper ratios of waste ceramic powder can decrease the density or weight and increase the thermal insulation efficiency of concrete blocks. However the high amounts of waste ceramic powder effect to decrease the mechanical properties concrete blocks that are lower than TIS.58 standard.

This research aims to develop the coconut coir ceiling board mixed with natural latex. The 6 ratios of gypsum plaster: coconut coir: sodium silicate: natural rubber: tap water are equal to 1: 0.15: 0.03: 0.00: 1 1: 0.15: 0.03: 0.01: 1 1: 0.15: 0.03: 0.02: 1 1: 0.15: 0.03: 0.03: 1 1: 0.15: 0.03: 0.04: 1 and 1: 0.15: 0.03: 0.05: 1 by weight. The ceiling boards were produced by casting in normal temperature (30 – 35 degree of Celsius). The properties testing of coconut coir ceiling board mixed with natural latex followed the TIS 219-2009 standard (gypsum plasterboard) including: breaking load nail pull resistance deflection water absorption density thermal conductivity coefficient and real usage. From the results 1: 0.15: 0.03: 0.03: 1 ratio is the most suitable ratio of coconut coir ceiling board mixed with natural latex. This developed ceiling boards can reduce the quantity of coconut coir waste and get the good thermal insulation ceiling board products.

The objectives of this research were to create a model for time sereries data prices and yields of natural rubber to be more accurate prediction and to compare the proposed model with the classical time series models such as the Holt-Winters Additive Exponential smoothing model (Holt-Winters ES) and the seasonal autoregressive integrated moving average model (SARIMA). The proposed model was a linear mixed model (LMM) consisting with trend autoregression outliers and sesonal terms. Dummy varialbles and Fourier seasonal effects were studied. Bayesian estimation was used and the estimated prices and yields were used for prediction. The results show that the proposed model with a Fouries seasonal effect is the most appropriated comparing with the dummy seasonal effect the Holt-Winters ES and the SARIMA having the least mean absolute values (MAE) both fiting and validating parts. The proposed model with sesaonal dummy variables should be the first consideration for forecasting spatial time series with a seasonal component.

Since the details in quasi-homogeneous region will be degraded from a conventional global image enhancement methods such as histogram equalization. This degradation causes from the saturation of the gray levels in equalization process. Then the local histogram equalization for each quasi-homogeneous region will be used in order to improve the details in the regions. To obtain the quasi-homogeneous regions the image can be segmented by using a watershed transform. The watershed transform is based on mathematical morphology; therefore the segmented regions can be effectively separated meaningful. Two adjacent regions in images which almost similar in gray levels can be separted by the watershed transform. In the color image enhancement three spectral bands are enhanced independently. Then all the three bands are assigned to each processed image in order to produce a color composite image. By the proposed algorithm the result images show the better perception on image details. Therefore the high efficiency of image classification can be obtained by using this color image.

The objective of this research is to develop the high corrosion resistance and good thermal insulation precast adobe wall panels mixed with natural latex. The 6 ratios of Portland cement type1: clay: rice husk ash: straw: rice husk:waterproofed liquid: natural latex: tap water were designed including: 1: 3: 0.3:0.02: 0.02: 0.02: 0: 0.4 1: 3: 0.3: 0.02: 0.02: 0.02: 0.05: 0.4 1: 3: 0.3: 0.02: 0.02: 0.02:0.1: 0.4 1: 3: 0.3: 0.02: 0.02: 0.02: 0.15: 0.4 1: 3: 0.3: 0.02: 0.02: 0.02: 0.2: 0.4 and 1:3: 0.3: 0.02: 0.02: 0.02: 0.25: 0.4 by weight. The precast adobe wall panels castedas same as the common concrete and reinforced by the bamboo. From the resultsthe proper ratio of precast adobe wall panel mixed with natural latex was 1: 3: 0.3:0.02: 0.02: 0.02: 0.1: 0.4 ratio. The properties of the proper precast adobe wall panelincluded density 1810.83 kg/m3 water absorption 17.16 % compressive strength 15.13MPa bending strength 3.01 MPa thermal conductivity coefficient 0.234 watt/m.Kelvin. Moreover the proper precast adobe wall panel mixed with natural latex also was verified by TIS.2226-2548 with properties of impact resistance deflection and hardness in medium duty (MD) level. The proper amount of natural latex effected the precast adobe wall panels to improve the mechanical properties including: increase the compressive and tensile strength decrease the density thermal conductivity coefficient and water absorption.