Virtual Reality and Augmented Reality, these days, is offering many useful applications that is attracting greater attention from tourism researchers and professionals. As, AR and VR technologies are evolving, the number of scientific applications is also at increase. VR and AR are proving their worth especially when planning, marketing, education, tourist sport preservation coming to light. The aim of this research paper is to highlight top technologies for Tourism and Hospitality with regard to AR and VR.
epidemic outbreak has devastating effects on daily lives and healthcare systems worldwide. This newly recognized virus is highly transmissible, and no clinically approved vaccine or antiviral medicine is currently available. Early diagnosis of infected patients through effective screening is needed to control the rapid spread of this virus. Chest radiography imaging is an effective diagnosis tool for COVID-19 virus and followup. Here, a novel hybrid multimodal deep learning system for identifying COVID-19 virus in chest X-ray (CX-R) images is developed and termed as the COVID-DeepNet system to aid expert radiologists in rapid and accurate image interpretation. First, Contrast-Limited Adaptive Histogram Equalization (CLAHE) and Butterworth bandpass filter were applied to enhance the contrast and eliminate the noise in CX-R images, respectively. Results from two different deep learning approaches based on the incorporation of a deep belief network and a convolutional deep belief network trained from scratch using a large-scale dataset were then fused. Parallel architecture, which provides radiologists a high degree of confidence to distinguish healthy and COVID-19 infected people, was considered. The proposed COVID-DeepNet system can correctly and accurately diagnose patients with COVID-19 with a detection accuracy rate of 99.93%, sensitivity of 99.90%, specificity of 100%, precision of 100%, F1-score of 99.93%, MSE of 0.021%, and RMSE of 0.016% in a large-scale dataset. This system shows efficiency and accuracy and
Cloud computing has emerged as one of the most groundbreaking technologies to have redefined the bounds of conventional computing techniques. It has ushered in a paradigm shift and pushed the frontiers of how computing assets, inclusive of infrastructure resources, software, and applications can be used, adopted, and purchased. The economic benefits or rather the fundamental economic shift offered by cloud computing in reducing capital expenditure and converting it to operational expenditure has been a primary motivating factor for early adopters. However, despite its inherent advantages that include better access and control, there exist several reservations around cloud computing that have impeded its growth. The control, elasticity, and ease of use that cloud computing is associated with also engender many security issues. Security is considered to be the topmost hurdle out of the nine identified challenges of cloud computing as underlined by the study conducted by the International Data Corporation. It therefore follows that an exceedingly secure system is essential for the safeguarding of an organizational entity, its resources, and assets. In this article, it is our endeavor to offer insights into the implementation of a novel architecture that can deliver an enhanced degree of security for outsourcing information in a cloud computing environment while involving numerous independent cloud providers. The framework comprises of dual encryption and data fragmentation techniques that envision the secure distribution of information in a multicloud environment. The various concerns surrounding this area, specifically, the challenges of integrity, security, confidentiality, and authentication have been addressed. All simulations and scrutiny have been accomplished on an Oracle virtual machine Virtual‐Box and a Fog environment on an Ubuntu 16.04 platform. Extensive safety measures and performance analysis that take into account diverse parameters, especially execution time, integrity, throughput, entropy, transfer rate, and delay demonstrate that our projected proposal is vastly proficient and satisfies the security prerequisites of secure data sharing and can efficiently withstand security attacks.
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