The purposes of the study on influence of motivational factors towards on organizational loyalty and performance of operational personnel in health science group in an autonomous university were to 1) study the influence of motivational factors on organizational loyalty among operational personnel and 2) to study the influence of motivational factors on the performance of operational personnel. The questionnaire was applied for data collection with the reliability acquired through Alpha Coefficient of 0.982 which was used to tryout with 30 people and collect data from 124 operational staff in health science group in a state-run university located at Chulapat building (source: Office of Personnel of Faculty of Allied Health Sciences Faculty of Nursing Faculty of Nursing and Faculty of Sports Science January 31 2017). This research is a descriptive research. The data obtained from the researchers questionnaire was analyzed by statistical analysis program including percentage analysis is used to analyze the individual factors mean used for interpreting various data and standard deviation to interpret data in various areas and multiple linear regression for testing the hypothesis as well as Pearson correlation. The research revealed that the hypothesis testing on motivational factors towards organizational loyalty and work performance of operational personnel in health science group in an autonomous university included 1 ) work success 2) work progress 3) acceptance 4) responsibilities and 5) job description while supporting factors included 1) salaries 2) advancement opportunities 3) relationships with others 4) status 5) policy and administration 6) work environment 7) work security and safety which influenced on organizational loyalty and performance of operating personnel in health science group at the 0.05 level of significance. (R = .812)and (.624)

In this paper proposed remote sensing using Normalized Difference Vegetation Index from NOAA STAR cluster value from k-means temperature rainfall number of rainy days and runoff to create runoff prediction model using Artificial Neural Network (ANN) and evaluated runoff models with the R2 and RMSE. The results show that the using of cluster value with other parameters to create predictive models can enhance forecasting results. When using Normalized Difference Vegetation Index with temperature value at lag time 1-2 month and cluster value at lag time 1 month to create model with ANN we have got the best performance which are RMSE=0.09 and R2=0.743. The experimental results shows that remote sensing data and cluster value from k-means can be used to predictive the runoff effectively.

The purposes of this research were to design and create dyed silk yarn and cotton yarn machine for community enterprises of Ban Na Pho woven group Na Pho district Buriram province. All materials were made of stainless steel and the principle of rotation of the yarn skein which was hung with spindle yarn inside the dye tank. Dyeing process began by mixing color tanks in the exterior size for diameter ๓๐๐ mm. Adjust the temperature inside the dye bag by the boiler was attached below. Using pump in dye tank for rotating the heat with stainless steel pipe in ๑๑/๒ inches and ๓ inches x ๑/๒ inches and the rectangular tank was ๖๐ cm. wide ๙๐ cm long and ๑๖๐ cm. high. It had ๕ mm. of plastic lid cover in front of and a channel that looked at the attachment of color yarn. The lid had ๒ levels adjustable lift spring lock and ๒-axis spindle yarn. It was triangular shaped drilled holes spray to ๑ mm. on the spindle with a diameter of ๑๕ cm. and ๖๐ cm. long rotating at ๑๐ rpm strength by using electric motor size ๐.๕ HP used ๒๒๐ volts. It could be rotated left and right with the gear ratios around ๒๐:๑ ๒ adjustable that were automatic with programming on the control box and simple pattern. the spray dyed paint had ๑ liter water pump to control pressure valve for opening and closing to dyed water flow regularly by the heat from the LPG gas with a head size of ๓๐ cm. and adjust the temperature up to ๑๒๐ Celsius degree. It was showed the temperature measurement of water dye with pressure gauge and temperature gauge. The efficiency of this dye can be dyed silk yarn and cotton yarn per ๕ kg. to ๑๐ kg. which was a medium-sized textile production to the local community enterprise and applied in the preparation of yarns before dying such as peeling glue and bleaching.

The objectives of this study were to calculate the probability of type I error power of a test and to compare the performance of three test statistics: Z Student’s t and Welch’s t. Including the recommending the appropriate test statistic. Classification of the population according to five distribution. The ratios of mean group 1 per group 2 were three levels. The ratios of variance group 1 per group 2 were three levels. The sample sizes of two populations were nine sizes. The significance levels that to study were 0.01 and 0.05. The data were simulated by using SAS programming with 1000 replicates. Results of the research were Z test statistic could control the probability of type I error and had higher power of a test than other test statistics but this test is necessary to know the variances of the two groups. Therefore it was appropriate to apply the other test statistics i.e. Student’s t or Welch’s t. If the variances of the two groups were equal Student’s t was a more appropriate test statistic than Welch’s t. But if the variances of the two groups were not equal Welch’s t was a more appropriate. When both sample sizes were large and the population variances were equal we could use any tests since there is no difference in the performance.

This research aims to produce the T-BAR particleboard from Physic nuts for interior building which are brought agricultural wastes to used for beneficial materials. Under the Thailand industrial standard (TIS-876-2547) specified the evaluated values such as desnsity water content water absorption thickness swelling bending strength elastic modulus and internal bonded. The experiment and evaluation processes between Physic nuts per Urea Formaldehyde ratio and Physic nuts per Phenol-cyanate based on 90:10 92:8 95:5 and 97:3 in consequence that we found the thickness of particleboard not more than 2 cm. The suitable ratio for Phenol-cyanate 92:8 percentage (Physic nuts 92% with Phenol-cyanate 8%) and suitable ratio for Urea Formaldehyde 90:10 percentage (Physic nuts 90% with Urea Formaldehyde 10%) at 120 Celsius temperature on pressing process. The Phenol-cyanate glue ratio of 0.80 gram per cubic centimeter suited to produce the particleboards averaged water content before pressing 8.89% suitable pressure in process 150 pound per square inch water content 7.65% density 0.818 gram per cubic centimeter water absorption 14.23% during 2 hours thickness swelling 8.02% during 2 hours internal bond 0.56 MPa bending strength 21.45 MPa modulus 2116 MPa. The Urea Formaldehyde glue ratio of 0.82 gram per cubic centimeter suited to produce the particleboards averaged water content before pressing 9.84% suitable pressure in process 152 pound per square inch water content 8.63% density 0.833 gram per cubic centimeter water absorption 14.36% during 2 hours thickness swelling 8.95% during 2 hours internal bond 1.39 MPa bending strength 22.37 MPa modulus 2117 MPa. As the results shown that both of Urea Formaldehyde and Phenol-cyanate with Physic nuts passed the TIS 876-2547 standard. The Physic nuts can produce the particleboards for using inside building.