Thailand is an agricultural country. So that the water resources are important. The water management is very important for keep the water used in necessary time. The monsoon is causes a heavy rain. The monsoon prediction by the mathematical model is important. The accuracy of the forecasts by the predictability measurement method is very important. In this research improvement the predictability measurement for the winter monsoon prediction in the Southeast Asia by the shallow water model. The data from The Bjerknes Centre for Climate Research (BCCR) University of Bergen Norway. The global climate model is Bergen Climate Model (BCM) Version 2.0 (BCCR-BCM2.0) of the Intergovernmental Panel on Climate Change (IPCC) are used. The data for run the model on 19 December 2059 from the WCRP CMIP3 is the initial condition. The model is run for 7 days forecast. The Lyapunov exponent (LE) is the predictability measurement method for verify the efficiency of the model and improvement the largest Lyapunov exponent (LLE) by limit theorems for verify the efficiency of the model too. The results to show that the shallow water model can be prediction the winter monsoon for 4 days forecast is accuracy when compare with the BCCR-BCM2.0 model and measure the accuracy by LE. In addition the improvement the LLE by limit theorems can be measure the accuracy of the winter monsoon for 4 days forecast to same as the LE. Therefore the improvement the LLE by limit theorems can be measure the accuracy of the winter monsoon prediction in Thailand by the shallow water model are suitable.

On Earth all objects have a weight which Earths mass exerts on them to downward force of gravity. The weight of an object can find somethings weights in Newton unite. It calculated on multiply the mass in kilograms by the acceleration of gravity in the units of meters/seconds2. The purpose of this study was to design and develop an experimental setup for measuring the gravity acceleration. It involved designing by using free-fall motion method in vacuum tube based on digital Technology and photo gate sensor measured the velocity of the ball object. The data were analyzed by Microsoft Excel. The value of gravity acceleration obtained at 9.617 m/s2 from the experiment set up. The value from the experiment was compared with the obtained from true value at Bangkok Thailand. It found the error at 1.697 %. The assessment of the quality used a questionnaire for data collection. Five content experts in Physics teaching evaluated it. That found mean 4.89. The results of the study revealed that the experimental set up were excellent quality of and high efficiency. So that this experiment suitable to be used in physics classroom.

Rail transport is a type of transportation that strongly influences economic due to its ability to transport a large number of passengers and products per trip relying on diesel-electric engines. The objectives of this thesis were set to investigate and develop the electrical performance tracking system of long-distance diesel electric locomotives and compare the electrical performance measured by the diesel electric locomotive performance tracking system and measured from the measuring instrument at Diesel Engine Maintenance Station in Bang Sue. The electric diesel locomotive no. 4513 (Cummins KTA50-L) was selected as the study subject of the experimentation. The results showed that the power loss of the diesel electric locomotive from the conversion of alternating current to direct current was inversely proportional to the engine speed. The power losses between the low and high engine speeds were equal to 77.11 and 2.49 percent respectively. The above data reflects the limitation of diesel electric engine performance and should lead to the construction of a database for making decision on the right engine selection suitable for the towing load of the locomotive.

The objective of this research work was to arrange a performance measurement for finding factors which will have influence on the capacity of Faculty of Engineering Rajamangala University of Technology Phra Nakhon leading it to become a digital university. The results of making a survey on the data from the personnel of the Faculty of Engineering showed that: the factor that had the most influence on the capacity of the Faculty of Engineering Rajamangala University of Technology Phra Nakhon was the factor of knowledge and attitudes (the mean was 3.61 which stood at the level of comments very); regarding the level of comments this was followed by the factor that had influence on the capacity of the Faculty of Engineering in terms of the environment in the organization (the overall mean was 3.49 which stood at the level of comments moderate); the factor that had influence on the capacity of the Faculty of Engineering in terms of participation came in the last place (the mean was 3.41 which stood at the level of comments moderate). The basics results obtained from this research work will be partly used as an approach to help improve the processes of the Faculty of Engineering. This will support stepping into becoming a digital university in the future.

The forecasting method is important because it can predict phenomena in the future. The accuracy of the forecast depends on the model and the initial conditions. In addition the predictability measurement method is important can be check the accurate of forecasts. In this research is winter monsoon forecasts in Thailand by the shallow water model. The data from The Bjerknes Centre for Climate Research (BCCR) University of Bergen Norway. The global climate model is Bergen Climate Model (BCM) Version 2.0 (BCCR-BCM2.0) of the Intergovernmental Panel on Climate Change (IPCC) is used. The Lyapunov exponent (LE) is the predictability measurement method for verify the efficiency of model and establish the new predictability measurement method by the time series analysis. The result to show that the new predictability measurement method by the time series analysis can be measure the efficiency of the winter monsoon forecasts in Thailand by the shallow water model for December 2015 to December 2056 are suitable.