This research aims to study the demographic characteristics affecting the decision-making of the working-age group in Ratchathewi District Bangkok Thailand to buy clean food and examine the marketing mix influencing their decision-making. The study population comprised 68635 people aged between 21 and 59 years in the group mentioned above. The sample consisted of 397 people. Descriptive statistics frequency percentage mean and standard deviation (SD) and inferential statistics i.e. independent samples t-test one-way ANOVA Pearson correlation coefficient analysis and multiple regression analysis were used to analyze the collected data. The research results illustrated that demographic factors like the different ages and educational backgrounds caused differences in the decision-making to buy clean food at a statistically significant level of 0.05. Moreover the marketing mix involving product price and promotion positively impacted the overall decision-making to buy clean food. It also positively affected the decision process of the need arousal or problem recognition (ND) information search (IS) evaluation of alternatives (EA) purchasing decision (PD) and post-purchase behavior (PB). Furthermore the place positively impacted the overall decision-making only in the PB process. Since the product price and promotion affected each aspect of the decisionmaking process (ND IS EA PD and PB) it was recommended that the clean food shops should pay more attention to these aspects

The objective of this research was to study the relationship between working principles. human resource management practices and the learning organization of personnel in Rajamangala University of Technology Phra Nakhon by collecting data from a sample of 360 people by using a questionnaire using descriptive and inferential statistics. Personnel of Rajamangala University of Technology Phra Nakhon used in this research study. mostly female accounted for 67.80% aged between 36 - 45 years equivalent to 34.20% Single status accounting for 64.70% had a masters degree. 48.10% have work experience between 11-20 years representing 40.30 percent and most of them are support personnel accounting for 58.60% Analyzing the relationship of working principles and human resource management practices that affect the organization of learning. In summary the implementation of the working principles of His Majesty King Bhumibol Adulyadej the Great principles of human resource management practices and learning organizations It is a challenge for management in terms of the survival of the organization. which must be integrated and applied The university has to step into the learning organization. It must start with the importance of human resources in the organization. has been developed appropriately. Because the organization relies on human resources to develop the organization. Also it must make people learn to happen. It may be learning at the individual level group level connected to the organization level. through various methods including education development training and learning by creating a learning organization as one of the heart of organizational management. Knowledge ideas and experiences are mobilized from each employee in order to integrate them for maximum benefit. and knowledge management properly and appropriately The organization will surely achieve its goals.

The purposes of this research were to compare the differences of the individual characteristics with performance of employees in state- owned enterprises. To study motivation affecting the work efficiency of the employees in the state enterprise unit. To study the principles of good governance affecting the work efficiency of employees in state enterprise agencies. To study of motivation and good governance principles affecting the efficiency of work performance of employees in state enterprise units The sample used in this study was 56 employees of state enterprise organizations in Thailand. 370 people by distributing questionnaires as data for data collection. The statistics used for data analysis were frequency percentage mean and standard deviation t-test f-test (One Way ANOVA). The relationships were used in Pearson s correlation analysis. Multiple linear regression analysis. The analysis results showed that personal characteristics such as gender age education level Income per month job position job duration. There are no significant differences in the efficiency of the performance of the employees in state enterprise units. Motivation affects the efficiency of work performance (quality of work) of employees in state enterprise units at a moderate level. Motivation affects the efficiency of work performance (quantity of work) of employees in state enterprise units at a moderate level. Motivation affects the efficiency of work performance (time) of employees in state enterprise units at a moderate level. Motivation affects the efficiency of work performance (operating cost) of employees in state enterprise units at a moderate level. Good governance affects work efficiency (quality of work) of employees in state enterprises are at a high level. Good governance affects work efficiency (the quantity of work) of the employees in the state enterprise department is at a medium level. Good governance affects work efficiency (time) of the employees in the state enterprise department was at a medium level. Good governance affects work efficiency (operating expenses) of employees in state enterprise departments are at a medium level. Motivation and good governance principles affect work efficiency (quality of work) of employees in state enterprises are at a high level. Motivation and good governance principles affect work efficiency (the amount of work) of employees in state enterprise departments at a medium level. Motivation and good governance affect the efficiency of work (time) of employees in the department at a moderate level. Motivation and good governance principles affect work efficiency (operating expenses) of employees in state enterprises at a medium level. With a statistical significance of 0.05 .

This Project ‘Thai Ikat Fabric Woman Working Suit from Sub-Ra-Wing Village’ aims for 1) to design the woman working suit that made from Sub-Ra-Wing Village’s fabric 2) to examine satisfaction of paticipants toward the designing processes of the woman suit according to 4 processes which are 1) the selection of Sub-Ra-Wing Village’s fabric that will mostly suit for the project 2) the process of design and selection woman working pattern 3) dressmaking and 4) examing the satisfaction of the viewers and paticipants toward the completed suit. Moreover the participant are 120 people aging 25-35 years old. The data was calculated by statistic percentage and mean as a result. The participants are; 87 people (72.50 percentages) are female. 85 people (70.80 percentages) are aging between 25 - 29 years old. 99 people (82.5 percentages) are undergraduated. 30 people (25.00 percentages) are students which equals to participants who have personal business. Lastly 55 people (45.80 percentages) are workers who have monthly income during 10001 - 20000 baht. The result of overall ‘Thai Ikat Fabric Woman Working Suit from Sub-Ra-Wing Village project ’ show that satisfaction at hight level (mean 4.46). Eaeh design it was found that. participants satisfaction to design 1 of coat and design 3 of shit and skirt at most level (mean 4.57 and 5.45 respectively). And design 2 of shirt and long pant design 4 of dress and design 5 of sweatpant. satisfaction at hight level (mean 4.47 4.41 and 4.32 respectively)

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%.