This paper presents a mathematical modelling for design the control system of a liquid. The system are consists of one and two tanks of a liquid. To confirm the achieved mathematical modelling is used to design P PI PD and PID controller in the frequency domain. The experimental results are indicated as the following. An one tank of a liquid controlling The controller can be control the liquid level to set point with in 100s. In the case of a disturbance occurs in the system it is perform by drain a liquid. As same as the controller it can be control the liquid level into the steady state. In the part of the liquid control this is the interaction between two tanks. The experimental results of the system operation the controller can be control the liquid into the set point both occur disturbance and without disturbance respectively

The objectives of this research are to estimate the morbidity rate of Dengue Hemorrhagic fever in each province of Thailand and to construct the map of the Dengue Hemorrhagic fever. A Bayesian model is used for the data analysis. The data are mathematical spatial correlated in the form of the conditional autoregressive model (CAR). The secondary data were collected at a provincial level. They were the number of Dengue Hemorrhagic fever patients rainfall and average temperature. The research found that the rainfall (RR = 1.0026) and the average temperature (RR = 1.2681) had influence on the morbidity of Dengue Hemorrhagic fever. The season during July to September had more influence on the morbidity of Dengue Hemorrhagic fever than during the other seasons. The top 5 highest morbidity rates per 100000 population were Chiangmai in October (1288.00) July (1096.00) September (804.30) Surin in October (772.30) and Nakhon Si Thammarat in August (666.20). The disease map constructed for showing the distribution of the disease is easy to understand and useful for public health.

The objectives of this research were to investigate risk factors for Dengue fever in Thailand and to select an appropriate model. The generalized estimating equation (GEE) whose dependent variable has a Poisson distribution and a negative binomial distribution were studied. The secondary data consisting of the number of Dengue fever patients rainfall average temperature forest area household income were collected. Regions and seasons were also considered. The research found that the GEE whose dependent variable has a negative binomial is more appropriate to be used for Dengue patient data analysis. Central region and the season during Feb-Apr were assigned to be reference groups. Risk factors for Dengue fever were rainfall (Relative Risk (RR) = 1.0009) average temperature (RR = 1.1736) forest area (RR = 1.0482) southern region (RR = 2.7390) eastern region (RR = 2.0489) western region (RR = 1.4051) the season during May-Jul (RR = 3.0526) and Aug-Oct (RR = 3.2677)

Blends of R22/R152a/R124 have been proposed to replace R12 in refrigeration systems.In this research work a technique to simply evaluate thermodynamic properties of refrigerant mixtures has been developed from Raoults Law.the method has been approached to evaluate the properties of the refrigerant blends avalable in the market such as MP39( R22/R152/R124 53/13/34)MP52 (R22/R152a/R124 33/15/52)and MP66 (R22/R152/R124 61/11/28) .The results agree well with those given by the manufacture within 5 % error The method has also been used to evaluate the properties of the ( R32/R125/R134a 23/25/52)refrigerant agree wall with those given from the manufacture with in 3 % error The thermodynamic property dlagrams of these refrigerant blends are also proposed.

Differential evolution is one of the most efficient optimization algorithms for solving complication problems including single objective multiobjective and many-objective optimization. It is a stochastic population-based search approach for optimization over the continuous space. The main advantages of differential evolution are simplicity robustness and high speed of convergence. The Advanced Fuzzy-based Multiobjective Differential Evolution (AFMDE) that exploits three performance metrics specifically hypervolume spacing and maximum spread to measure the state of the evolution process. The fuzzy inference rules are applied to these metrics in order to adaptively adjust the associated control parameters of the chosen mutation strategy used in AFMDE. The optimization algorithm will stop the evolution process if the number of iterations reaches the stopping criteria which usually is the maximum number of iterations. Then the optimization algorithm delivers the optimal solution founded. However sometimes if the maximum number of iterations is not appropriately defined the found solutions may not be the optimal ones. In case of the optimization algorithm has found the optimal solutions but it must continue the evolution process because the stopping criteria are not met. This can cause unnecessary using of high computational resources and time-consuming. Therefore this research study proposed the stopping criteria based on performance metrics feedback for AFMDE. The efficiency of the proposed criteria combined with AFMDE is evaluated on the well-known ZDT benchmark test suites.