Smart imaging-based medical classification systems help the human diagnose the diseases and make better decisions about patient health. Recently, computer-aided classification of skin diseases has been a popular research area due to its importance in the early detection of skin diseases. This paper presents at its core, a system that exploits convolutional neural networks to classify color images of skin lesions. It relies on a pre-trained deep convolutional neural network to classify between six skin diseases: acne, athlete’s foot, chickenpox, eczema, skin cancer, and vitiligo. Additionally, we constructed a dataset of 3000 colored images from several online datasets and the Internet. Experimental results are encouraging, where the proposed model achieved an accuracy of 81.75%, which is higher than the state of the art researches in this field. This accuracy was calculated using the holdout method, where 90% of the images were used for training, and 10% of the images were used for out-of-sample accuracy testing.

Objectives. The demand for esthetic dentistry is growing, and social media constitute the main driving force behind this revolution. Twitter is a leading social media platform; however, there is a lack of research on the pattern of communications and the impact of Twitter on esthetic dentistry. The purpose of this study was to analyze the content of tweets related to esthetic dentistry and to investigate how Twitter has affected the perception of, and demand for, esthetic dentistry. Moreover, it aimed to assess the potential benefits and risks of esthetic dentistry advertising strategies on Twitter as a potential social media platform. Materials and Methods. Using a specialized web scrapping tool made available by the Python programming language, a total of 54,000 public tweets were downloaded from Twitter at real-time by matching specific keywords. The downloaded tweets were manually filtered, and 13,787 tweets were included and categorized into four tweet sets by content. Results. The main categories were tweets regarding specific cosmetic procedure, totaling 56.53 (43.2 for veneers, 13.3 for whitening), advertisements (36.72), information (5.53), and general cosmetic dentistry (1.22). Negative opinions towards veneers and whitening were the most common themes (68.03 and 43.44). For veneers, illegal use for kids was the most common negative theme (59.7) and being destructive for whitening (86.3). Positive opinions counted 6.26 of veneers and 4.3 of whitening tweets. Advertising for whitening products was the second most common between all tweets (16.6), and advertising for dental practices was the third (14.7). Presenting facilities/services was the most common marketing strategy for dental practices (49.7). Twitter was weakly used to circulate educational content (5.5) and to post reviews (0.75). Conclusion. Twitter was extensively used to share experiences/opinions towards dental cosmetic interventions. Advertising is another vital use of this platform. However, circulating information was the least common use of this social media. Additionally, tweeters were rarely to post online reviews and specific advices and recommendations regarding esthetic dentistry. Moreover, females tended to participate and tweet more significantly in cosmetic-related topics than males. This platform should be tailored efficiently to target users priorities and to improve health literacy and self-care. Twitter was weakly used to circulate educational content according to this study and rarely used to share online reviews.

This paper introduces an extensive overview of the Infrastructure as a Service offerings that are presented today by the top ranked cloud providers. It surveys their solutions related to Infrastructure as a Service and High Performance Computing, presenting their benefits and drawbacks from a cloud user perspective. Four leading cloud providers were chosen for this paper, Amazon Elastic Compute Cloud, Microsoft Azure Cloud, Google Cloud and Oracle Cloud. The selected service providers are compared to each other in this paper from many perspectives. The comparison was done from the IaaS perspective. Reviews about these providers are presented in addition to pricing and billing details. Each one of these providers has its competitive advantages that already persuade its existing customer to invest more in their cloud and to attract new ones to migrate their resources to. In addition to the IaaS perspective, we present a comparison between the selected cloud providers from the High Performance Computing user perspective. These solutions are discussed; features of these solutions such as virtual machines options, their operating systems, and networking are compared.