No abstract

Museums have adapted their traditional ways of providing services with the advent of novel digital technologies to match up with the pace and growing needs of current industry revolution. Mixed Reality has revitalized interpretation of numerous domains by offering immersive experiences in digital and real world. In the proposed study, an attempt was made to enrich user's museum experience with relevant multimedia information and for building a better connection with the artifacts with in Taxila Museum in Pakistan, which has beautifully preserved the Gandhara civilization. The proposed solution is an Augmented Reality (AR)-based smartphone application which recognizes artifacts using Deep Learning in real time and retrieve supportive multimedia information for the visitors. To provide user with exact content, convolutional neural networks (CNN) will be applied to correctly recognize artifacts. The significance of proposed application is compared with traditional human guided or free user tours through user-centric questionnaire-based survey. The evaluation is carefully performed using relevant evaluation models including Museum Experience Scale (MES) and triptych model of interactivity. The findings of the study are discussed and assessed comprehensively using statistical methods to highlight its significance.

The emergence of augmented reality (AR) and virtual reality (VR) has revolutionized the trends in computing devices and modern technologies drastically. With this revolution, there is a need to extend existing architectures of security to serve as the key protective feature in all computing devices. In this experimental study, the aim is to develop a novel authentication technique with a fusion of graphical doodle password approach and AR environments. The mash-up of both doodle passwords and AR in a 3D space gives a promising direction to set off to a modern, more usable, and satisfying authentication techniques. The proposed approach works on real-time size and coordinate matching of doodles in an AR environment for the authentication of users. The creation of doodle passwords in an AR space is carried on by touchgesture-recognition on a smartphone. The usability and usefulness of the proposed technique is evaluated by conducting an extensive survey, based on tasks and user experience assessments. The randomizedpost-test-only study model is used to conduct experimentation that is also followed by the analysis of security parameters with the help of confusion matrix. The obtained results predict the use of AR during the authentication process more satisfying for users, where the proposed technique is useful, usable, and secure in comparison to the existing authentication approaches. This paper also highlights the importance of research needed for the utilization of modern techniques during the creation of security frameworks.

Social communication has evolved, with e-mail still being one of the most common communication means, used for both formal and informal ways. With many languages being digitized for the electronic world, the use of English is still abundant. However, various native languages of different regions are emerging gradually. The Urdu language, coming from South Asia, mostly Pakistan, is also getting its pace as a medium for communications used in social media platforms, websites, and emails. With the increased usage of emails, Urdu’s number and variety of spam content also increase. Spam emails are inappropriate and unwanted messages usually sent to breach security. These spam emails include phishing URLs, advertisements, commercial segments, and a large number of indiscriminate recipients. Thus, such content is always a hazard for the user, and many studies have taken place to detect such spam content. However, there is a dire need to detect spam emails, which have content written in Urdu language. The proposed study utilizes the existing machine learning algorithms including Naive Bayes, CNN, SVM, and LSTM to detect and categorize e-mail content. According to our findings, the LSTM model outperforms other models with a highest score of 98.4% accuracy.

The Internet of medical things (IoMT) provides an ecosystem in which to connect humans, devices, sensors, and systems and improve healthcare services through modern technologies. The IoMT has been around for quite some time, and many architectures/systems have been proposed to exploit its true potential. Healthcare through the Internet of things (IoT) is envisioned to be efficient, accessible, and secure in all possible ways. Even though the personalized health service through IoT is not limited to time or location, many associated challenges have emerged at an exponential pace. With the rapid shift toward IoT-enabled healthcare systems, there is an extensive need to examine possible threats and propose countermeasures. Authentication is one of the key processes in a system’s security, where an individual, device, or another system is validated for its identity. This survey explores authentication techniques proposed for IoT-enabled healthcare systems. The exploration of the literature is categorized with respect to the technology deployment region, as in cloud, fog, and edge. A taxonomy of attacks, comprehensive analysis, and comparison of existing authentication techniques opens up possible future directions and paves the road ahead.