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 research has focused on the efficiency of using online media computer graphics based on concepts and theories of learning networks for students in computer science faculty of science and technology Rajamangala University of technology Phra nakhon because at present the network access can be accessed anytime the researcher has the idea to measure the effectiveness of learning in computer graphic courses. that students will have much interest 1) The population of this study consisted of 30 undergraduate students who attended the Computer Education and Training subject. The instruments utilized to design the lesson included. Tools used to develop lessons consist of a system LMS 2) The tools employed in evaluating quality of the online lesson consisted of the learning management plans a 20-item pre-and post-test an authentic assessment with rubric scores and a students’ satisfaction questionnaire. The results revealed that 1) The efficiency of the online lesson constructed was at 85/84 which was higher than the criterion set (80/80) 2) The students’ learning achievement was higher at .05 level of significance 3) The students’ satisfaction on the online lesson was at high level 4.31

he monthly rainfall forecasts are very important in Thailand because the most of people has a career in agriculture. The monthly rainfall forecasts can be analyzed for manage water resources. In addition the monthly rainfall forecasting is used to manage water for consume in Thailand. This research is forecasting monthly rainfall under the global warming using a multilayer neural network. It is a network with one hidden layer. The data from the Meteorological Department is use. Imported variables include temperature humidity and wind. The forecast from January to December 2018. The mean square error (MSE) to measure forecasting accurate and found that the value is suitable error (10.25). The neural network can provide accurate monthly rainfall forecasts from January to December. It was found that the southern region had the highest rainfall and the eastern region northeastern region northern region central and western regions respectively. Therefore neural networks can be forecast rainfall accurately and efficiently. It can be used to analyze and manage water resources effective.

Thailand is one of the few countries in the world that provides the whole value chain of the textile industry with over 4700 local textile producers and 800000 to one million workers making this industry the second-most important employment sector. In 2016 the industry’s export revenue was valued at almost USD 7 billion contributing to over 3% of total exports. The Association of Southeast Asian Nations (ASEAN) is the biggest international market for Thailand clothing export (23%) and expected to become the worlds fourth largest market by 2030. However Thai cloth entrepreneurs are facing major problems that demand attention including labour costs new design and product development and in particular online marketing. The Thai fashion and textile industries should define a clear strategic move through integrating textile with fashion with a view “toward sustainable creative industries with strong soft power”. The purpose of this study is to analyse competitiveness of Thai cloth entrepreneurs in relation to online management and integrated marketing communications (IMC) in the ASEAN market. The research instrument involves a descriptive cross-sectional mixed-method study in Thailand. For quantitative data 60 cloth entrepreneurs are invited to complete a questionnaire before and after our “online management and IMC” training programme and a qualitative in-depth interview study is conducted with 10 cloth entrepreneurs. The 2017 survey returned 100% participation with general agreement that a website and Facebook are the most important IMC tools for online marketing in the ASEAN market. Before training the participants had knowledge and skills regarding the ASEAN Free Trade Area (AFTA) online communication and social media tools in intermediate level while they had less knowledge and skills concerning social media web design and online gallery. After training the statistics show an increase in entrepreneurs’ level for all knowledge and skills. Furthermore the findings from in-depth interviews show that with regard to entrepreneurial competitiveness in relation to the ability of online management and IMC there is a requirement for further training and government support. In addition the 10 cloth entrepreneurs agree that time management and quality of product and service control are very important for online business.

The main objectives of this study were to study 1) problems of administration 2)the improvement guidelines and 3) comparing some sample groups’ comments to the overview of the administration improvement guidelines by the uses of modern technology and social network for people services of the police hospital. This study was a survey research using questionnaires which passed through quality including validity check and reliability check at 0.89 level. Total samples of 625 were patients receiving all outpatient services calculated by taro Yamane’s formula at the confidence level 94% The 458 sets of questionnaire were collected equal to 73.28% of the total samples. Statistics used in this study were percentage mean standard deviation and t-test. The study results showed that 1) the main problem was the Police Hospital operating by bringing modern technology and social network for people services is lack of an endeavor and care for the people; 2) the main improvement guidelines is the top executives of the police hospital should create knowledge understanding and be a good role model serving people with honestly endeavor and empathy. Meanwhile Police Hospital should set policies and plans which are clear and continuous to use modern technology training and develop all staffs to be ready for effective communication by using modern and universal hardware/software technology and social network for people services; 3) males and females undergraduate and bachelor’s degree or higher have no different opinions on the overall management improvement approach.