Today used of smartphone or mobile phone are popular for users who eager in new technology. Smartphone are similar to a small notebook that have many kinds of functions of mobile phone. Android is the popular operation that used in smartphone and mobile phone because it can be used to increase abilities with many applications that suitable with phones.

This study was aimed to examine the marketing mix factors affecting the decision to study at the Doctor of Business Administration Program of Rajamangala University of Technology Phra Nakhon graduate students. 287 samples used in this study were students attended the program during 2006 – 2014. The data were collected by a questionnaire and analyzed by mean standard deviation (S.D.) Pearson’s Product Moment Correlation Coefficient regression analysis and Binary logistic regression analysis. The research showed that marketing mix affecting the decision to study at the Doctor of Business Administration Program of Rajamangala University of Technology Phra Nakhon graduate students in the overall were high at statistically significant of 0.05 level including the personnel (People) and the image of the university (Product) with a mean of 4.16 followed by the physical image (Physical) of 4.14. The marketing mix factors that influenced the students’ decision making to study for a PhD. degree in Doctor of Business Administration Program MBA students with the following prediction equations Logit = 5.371-1.604 (Product) -0.073 (Price) -0.339 (Place) -0.481 (Promotion) + 0.189. (People) + 1.122 (Process) - 0.139 (Physical). The independent variables that affected the decision making included the image of the university (Product) in terms of the instructor qualifications and their academic quality as required by the market the reputation of the university known and recognized for its curriculum diversity and the high ranking. Also the university extracurricular activities were as well accepted in accordance with the requirements such as the study abroad and academic progress over time. However if interested people had received negative information about the university they would have been uninterested to further their study for a PhD. degree in Doctor of Business Administration Program

This study the purpose of this research is to study a network of tourism of the central provinces in Thailand by topological analysis. Using the Gephi program to find that the trip by car or tour bus connects each province in the central region. Either 22 provinces. When analyzed with Gephi there are Nodes: 22 Edges: 43 and Undirected Graph. The results of the analysis concluded that Phranakhon Si Ayutthaya and Nakhon Sawan provinces are the provinces with the most significant relationships with the provinces. There are many routes connecting to various tourist attractions. It can travel to many provinces. And to study was conducted to analyze the tourist information of each province in the central region. Either 22 provinces. When analyzed with Gephi there are Nodes: 122 Edges: 145 and Undirected Graph. The overall conclusion was that Bangkok is the province with the most influential relationships with the nearest tourist attractions. The province is a popular tourist destination of the tour. There are tourist attractions that are of interest. It is a center that can travel to many provinces.

The image enhancement process of a digital image is a part of digital signal processing which it plays an important role in some industrial segments for instance object classification or bio-identification satellite exploration or aerial images robot vision cancer treatment etc. These image applications are necessary to consume many resources in physical hardware and computer programming including the intelligent algorithm development of complexly advanced processing in order to enhance digital images – as well as be easy to analyse by humans. This research is aimed to present on Contrast Enhancement using Bi-Histogram Equalization via Two Dimensional Discrete Wavelet Transform (BHE2DWT) in order to compose the coefficient wavelet from other signals. At the end of the process information on the approximation band from DWT will be divided into two sub-histograms and then histograms will be independently equalized. After that resulting histograms will be decomposed by IDWT. Resulting images will be not only more displaying in high contrast than their original images but also preserve the absolute mean brightness error (AMBE) to close their original images.