This research has the objectives for studying the information and communication technology (ICT) usage of university students and relationships between factors of information and communication technology (ICT) usage those affecting the digital university policy of Rajamangala University of Technology Phra Nakhon. Samples are students who are studying bachelor degree in 9 faculties at Rajamangala University of Technology Phra Nakhon and are systematically randomed from the population of 11899 at 95% confidential level with the sample size of 387 from the calculation. Questionnaires about the information and communication technology usage of the students related with the Digital University policy have been used in this research. Descriptive statistics used in this research are Frequency Percentage Means (𝑥𝑥̅) and Standard Deviations. Referential statistics used are t-test Independent and One-Way Analysis of Variance. The research found that different personal factors including genders ages classes and faculties did not vary the opinions of the students about their planned behaviors. Different personal factors including genders ages classes and faculties did not vary their opinions about the intention of information and communication technology usages. Different personal factors including genders ages classes and faculties did not vary their opinions about the information and communication technology usage behaviors. Different personal factors including genders ages classes and faculties did not vary their opinions about the Digital University policy. Opinions about the planned behaviors are positively related in low level to the opinions about the intention of information and communication technology usages statistically significant at the .01 level. Opinions about the intention of information and communication technology usages are positively related in moderate level to the opinions about the information and communication technology usage behaviors statistically significant at the .01 level. Finally opinions about the information and communication technology usage behaviors are positively related in low level to the opinions about the Digital University policy statistically significant at the .01 level.

Voltage drop is one of the power quality problems affecting power users. This happens due to the higher demand for electric power. Or a short circuit in the transmission system. This causes a voltage drop is one of the power quality problems affecting power users. This happens due to the higher demand for electric power. Or a short circuit in the transmission system. This results in drop in Solving of voltage drop problems in power distribution model with distributed generator were presented with MATLAB program by installing a generator in the distribution system. Therefore simulated a case study 5 case 1 simulation by not installing a generator at any bus case 2 simulation by installing a Generator at bus 1 case 3 Simulation by installing a Generator at bus 18 case 4 simulation by Generator installed at bus 33 and case 5 simulation by Generator installed at bus 13 17 21 31 to study the suitable location of generator installation to solve the problem of voltage drop.

In this work solar erythemal ultraviolet radiation (EUV) which affects human skin and skin cancer was investigated at Songkhla province (7.2°N 100.6°E). EUV was converted to UV index then the data was used for model development and forecasting of hourly UV index using Artificial Neural Network (ANN). The ANN model has one input layer two hidden layers and one output layer. This input layer consists of extraterrestrial erythemal ultraviolet radiation solar zenith angle aerosol optical depth and cloud index which affect ultraviolet radiation and the output layer is hourly UV index. The results show that hourly UV index obtained from ANN and that from the measurement are in reasonable agreement with root mean square difference of 12.8% and mean bias difference of -2.4%. For forecasting of the hourly UV index the data for 7 days earlier was used for forecasting the next UV index for one day or nine-hour (08:00 am.-16:00 pm.). Multi-layer perceptron and back propagation algorithm were used in the model forecasting. The results show that the UV index from the model forecasting is reasonable agrees with UV index from measurement with root mean square difference of 17.0% and mean bias difference of 0.3%.

This study aimed to use Poka-Yoke techniques to help prevent errors and reduce loss in Front Side Fender Model assembly process. The researchers used four tools in the 7QC tools which were Check Sheet Cause-and-Effect Diagram and Graphs to search for causes and ways to solve problems and Cause and Effect Matrix and ECRS Techniques. The study revealed that the main cause of the problems was that the incorrect assembled side fenders were submitted to another department. This mistake had bad effects on time and workforce spent for correcting work including more expenses. The mistakes occurred because there was no tool for detecting errors in the work piece. Therefore the researchers use Poka-Yoke techniques in order to decrease errors by designing a control system for target detection while it was moving through the process. After collecting data the study showed that before the improvement during January to August 2019 the number of problems caused by the process were 0.093. However the number of problems after the improvement during September to December 2019 reduced to 0. It was obvious that this improvement reduced the loss from the front side fender assembly process up to 100.

The objective of this study is to obtain a model that maximize production of γ-linolenic acid (GLA) by the moss Physcomitrella patens employing response surface methodology (RSM). The RSM with a three-variables (sucrose potassium nitrate and glutamate concentrations) and five-level (-2 -1 0 1 and 2) central composite design (CCD) including 20 experimental runs was employed to optimize the medium composition. Results showed that the experimental data could be appropriately fitted into a second-order polynomial model with a coefficient of determination (R2) more than 0 .9 5 for GLA production. Analysis of variance (ANOVA) revealed that the model was highly significant (p<0.0001) and the effects of the sucrose (20-100 g/L) and glutamate (0.5-2.5 g/L) concentrations on GLA production were significant (p<0.05). The GLA production with the optimized culture medium (sucrose concentration of 62.92 g/L potassium nitrate of 0.80 g/L and glutamate concentration of 1 .4 2 g/L) by RSM increased 4.61 folds when compared with the standard BCD medium. This experimental value (16.37 mg GLA/L) fit well with the predicted values (16.20 mg GLA/L).