This work presents a technique for classifying X-ray images of the chest (CXR) by applying deep learning-based techniques. The CXR will be classified into three different types, i.e. (i) normal, (ii) COVID-19, and (iii) pneumonia. The classification challenge is raised when the X-ray images of COVID-19 and pneumonia are subtle. The CXR images of the chest are first proceeded to be standardized and to improve the visual contrast of the images. Then, the classification is performed by applying a deep learningbased technique that binds two deep learning network architectures, i.e., convolution neural network (CNN) and long short-term memory (LSTM), to generate a hybrid model for the classification problem. The deep features of the images are extracted by CNN before the final classification is performed using LSTM. In addition to the hybrid models, this work explores the validity of image pre-processing methods that improve the quality of the images before the classification is performed. The experiments were conducted on a public image dataset. The experimental results demonstrate that the proposed technique provides promising results and is superior to the baseline techniques.

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The travel and tourism industry is one of the main sources of income in Thailand. People choose to travel around the world, as a way to relax and enjoy their time. Users search information from many resources before and during their travel. We grouped the mobile tourism applications into two main groups in order to analyse the nature of information in the tourism applications. Social network provides rich collaborative user-generated information. We found that most tourism applications require personal information and pre-existing association in order to get information. We argue that, in tourism, a user requires instant and easy access to information. So the social network might not be an appropriate option. Therefore we propose a simple collaborative user-generated content application, which has a location awareness chat system. We aim to provide an application with self-sufficient information that allows the user to instantly share, search, and comment on information at anytime and anywhere. Moreover, the location awareness chat system is introduced to provide instant firsthand information to the users as well.

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