The purposes of the research were; 1) to study the relative rotation of AC-generator 2) to study the angular velocities of magnetic coil and permanent magnetic influence generating voltage of AC-generator and 3) to construct predictive equations of generating voltage of AC-generator. By the 12-V 6-pole alternator of motorcycle Pearson’s correlation and regression analysis the findings revealed that: 1) At the lowest relative angular velocity of 376 rpm the generating voltage is 3.28 V. While the highest relative angular velocity of 2280 rpm the generating voltage is 22.98 V. 2) The angular velocity of permanent magnetic has great influences on generating voltage than the angular velocities of magnetic coil at the .01 level of significant and 3) function as below : Generating voltage = 0.806 (Velocity of permanent magnetic) + 0.634 (Velocity of magnetic coil)

A solar energy is most popular renewable energy source which can reduce usage of fuel in thermal generation and impact on environment. The solar energy is a clean and sustainable source. This paper proposed method of finding optimal locating and sizing of PV solar farm on the power system with minimize fuel costs by considering solar radiation in each location of solar farm. The bees algorithm (BA) is used to minimize fuel cost of thermal units by changing location and varying sizes of solar farm with security constraints of power system and solar radiation. IEEE 30 bus test system is used to verify the proposed method. The results show that the proposed method found the optimal position of solar farm with minimum economic cost

The climate change is a natural phenomenon and effect on atmospheric which is the media of wireless communication. For the high performance in the telecommunication system this study therefore aimed to study the variables affecting to signal strength of wireless networks. The values of temperature humidity pressure and the signal strength of wireless networks 5 GHz were measured. The sample of this study was 148 access-points of TOT in Yasothon Province. For statistical analyses Pearsons correlation and regression were employed. The findings revealed that: 1) the average level of signal strength was 69.44 –dBm. The average levels of temperature humidity and pressure were 28.085 ?C 73.145% and 1004.246 hPa respectively 2) variables that had great influences on signal strength of wireless networks consisted of temperature humidity and pressure and 3) ambient variables of temperature humidity and pressure could predict the level of signal strength at 76.8%

This paper presents a CMOS voltage reference design which is widely used in electronic circuits both analog and digital circuits. In the conventional a CMOS voltage reference circuit design composed of several MOS transistors and complicated circuits the output voltage cannot be adjusted to any levels. Therefore in this paper proposed the CMOS voltage reference circuit design technique based on a new current combination circuit which it was reduced number of MOS transistors and the proposed circuit is able to operate without complex startup circuit. The performance of the proposed circuit is confirmed through PSPICE simulation results the circuit can be operated with supply voltage varies from 2V to 4V the output voltage reference is about 231 2mV at wide temperature range of -80 to 120 it has very low temperature coefficient of about 37.65 ppm/ and a total power dissipation of 7.37 W

The study aimed to investigate and compare the back-pain level peak-to-peak voltage and period time of Electromyography (EMG). The sample of this study was 31 patients of Yasothon Hospital. The instrument consisted of an electrocardiography (EKG monitor). For statistical analysis t-test and f-test were employed. The findings revealed that mean is The Back-Pain level of most patients was 2 (35.5 %). The peak-to-peak voltage of Back-Pain levels (1-5) were 0.11 0.12 0.21 0.25 and 0.20 mV. While period time of Back-Pain levels (1-5) were 0.85 0.86 0.86 0.62 and 0.68 s. respectively. The peak-to-peak voltage of Back-Pain levels (1 and 2) were different levels (3 and 4) at .05 level of significant. In addition the period time of Back-Pain level (4) was different levels (1 2 and 3) at .05 level of significant