Abstract

Deep learning assisted diagnosis for assessing the severity of various respiratory infections using chest Computed Tomography (CT) scan images has gained much attention after the COVID-19 pandemic. Major tasks while building such models require an understanding of the characteristic features associated with the disease, patient-to-patient variations and changes associated with disease severity. In this work, an attention-based Convolutional Neural Network (CNN) model with customized bottleneck residual module (Attn-CNN) is proposed for classifying CT images into three classes: COVID-19, Normal, and other Pneumonia. The efficacy of the model is evaluated by carrying out various experiments, such as effect of class imbalance, impact of attention module, generalizability of the model and providing visualization of model’s prediction for the interpretability of results. Comparative performance evaluation with five state-of-the-art deep architectures such as MobileNet, EfficientNet-B7, Inceptionv3, ResNet-50 and VGG-16, and with published models such as COVIDNet-CT, COVNet, COVID-Net CT2, etc. is discussed.

Abstract

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Abstract

Monuments were built for thousands of years as the most enduring and well-known representations of past civilizations. It is crucial to preserve these because they are national symbols with unique cultural and historical significance. The deterioration of the structures happens as a result of weathering, fire, natural disasters like earthquakes, construction flaws, and numerous other factors. In general, the issue with repairing and reinforcing regular buildings is very different from the issue with restoring monument buildings. The goal of keeping a monumental structure in use may be viewed as secondary in importance and any event as a result of the effort made to fulfil the main task. In the case of monumental buildings, emphasis is placed on the preservation of their aesthetic and historical aspects. Therefore, the restoration strives to protect and highlight the monument’s or building’s aesthetic and historical aspects. Choosing the appropriate material for the restoration depends on how the original structure looks. New materials must be compatible with those already used in the building. The goal of the present study is to provide an overview of the materials used to restore the structural integrity of historic structures and monuments that have been damaged by seismic activity. All of these buildings need extra attention because of their specific historical or architectural value, or because they are significant because they are still standing examples of a former way of life.

Abstract

Masonry structures cover a very wide range of monumental works in space and time, covering almost 6,000 years. The structural assessment of the load-carrying capacity of such old structures depends on several parameters such as: (a) material strength; (b) texture of the structure; (c) geometrical form and dimensions; (d) existing loading and constraints; and (e) expected loadings at failure. Detailed calculations are also required for the structural evaluation using most of the above parameters firstly by considering the gravity loads and secondly by the combination of gravity load and lateral action in areas of high seismicity. However, at the same time, it is equally significant for the structural engineer, who is involved in structural restoration design, to know in depth qualitatively the basic forms and their structural behaviour of monumental buildings. The structural engineer in charge must understand from the beginning, qualitatively, the structural behaviour of a building under consideration to various basic actions so that one can make a preliminary diagnosis of the causes that are responsible for the existing damages (cracks, drifts, settlements, splitting etc.). In this way, one will be in a position to focus on the detailed research, in situ and laboratory, to the critical points of the building, and can conduct the analysis and design using suitable models for a credible safety evaluation. Therefore, an effort is made in the present study to give a qualitative approach to the structural behaviour of the basic structural forms of masonry monumental and historical buildings, where the consequences of the seismic action are traumatic now and then. This article gives an outline and creates background information for further structural evaluation of the monuments.

Abstract

The possibility of a quantum system to exhibit properties that are akin to both the classically held notions of being a particle and a wave, is one of the most intriguing aspects of the quantum description of nature. These aspects have been instrumental in understanding paradigmatic natural phenomena as well as to provide non-classical applications. A conceptual foundation for the wave nature of a quantum state has recently been presented, through the notion of quantum coherence. We introduce here a parallel notion for the particle nature of a quantum state of an arbitrary physical system. We provide elements of a resource theory of particleness, and give a quantification of the same. Finally, we provide evidence for a complementarity between the particleness thus introduced, and the coherence of an arbitrary quantum state.

Abstract

In today’s digital age, access to knowledge and information is crucial for societal growth. Although widespread resources like Wikipedia exist, there is still a linguistic barrier to breakdown for low-resource languages. In India, millions of individuals still lack access to reliable information from Wikipedia because they are only proficient in their regional language. To address this gap, our work focuses on enhancing the content and digital footprint of multiple Indian languages. The primary objective of our work is to improve knowledge accessibility by generating a substantial volume of high-quality Wikipedia articles in Telugu, a widely spoken language in India with around 95.7 million native speakers. Our work aims to create Wikipedia articles and also ensures that each article meets necessary quality standards such as a minimum word count, inclusion of images for reference, and an infobox. Our work also adheres to the five core principles of Wikipedia. We streamline our article generation process, leveraging NLP techniques such as translation, transliteration, and template generation and incorporating human intervention when necessary. Our contribution is a collection of 8,929 articles in the movie domain, now ready to be published on Telugu Wikipedia.

Abstract

Air Smart Vehicular Networks (ASVNs) have become increasingly essentials in military and commercial industries in recent years, where drones are deployed to interact among each other via wireless medium in airspace due to their agility and versatility. ASVNs can form a closed loop from data perception to final execution by integrating communication devices, computation tools, and control modules. However, the used unencrypted and publicly available navigational signals like Global Positioning System (GPS) and communication over (public) insecure Internet connections, including wireless networks and WiFi, make ASVNs vulnerable to security breaches. Attackers can easily gain access to a drone's configuration and take control remotely, by launching various attacks such as GPS spoofing, false sensor data injection, maldrone malware injection, eavesdropping, man-in-the-middle, Denial-of-Service (DoS), replay, forgery, and Skyjack attacks. This paper proposes a robust and efficient multi-factor biometric-based security mechanism using blockchain as a service to address the security and privacy breaches in ASVNs. A comparative study demonstrates that the proposed scheme provides superior security and better functionality features with low communication and computation overheads as compared to the existing analogous schemes. The feasibility of the proposed scheme in real-life drone applications is also demonstrated through a real-time testbed and blockchain simulation. Furthermore, a detailed security analysis using the automated software validation tool, namely Scyther, verifies the proposed scheme's significant level of security

Abstract

Owing to the growth of the intelligent Internet of Vehicles (IoV), the notion of the Social Internet of Vehicles (SIoV) has emerged. SIoV is based on the intelligent IoV combined with social needs, and it uses existing vehicle self-organizing network technologies to enable in-vehicle social networking platforms. The rapid development of the Internet of Things (IoT) has led to an explosion in the number of in-vehicle electronic devices, external facilities, vehicles, and a massive amount of real-time data generated by these vehicles, devices, drivers, passengers, and other social relationships. This explosion has put tremendous load pressure on servers; hence, researchers have started to apply fog computing to SIoV to spread server overload. However, there are still a number of risks and challenges associated with SIoV. Therefore, we propose an authentication scheme for fog computing-enabled SIoV that guarantees user anonymity and security. Detailed security analysis proves that the proposed scheme can secure against known attacks. Finally, we evaluate the performance of our scheme, and the results show that it has excellent security, computation, and communication performances.

Abstract

The key factor accelerating the development of intelligent transportation and reduced traffic congestion is the vehicle ad hoc network (VANET). However, the swift upsurge in the diversity of vehicles puts the development of the vehicle network's safety system through plentiful glitches. To receive the messages promptly, attain the confidentiality of vehicle identity, and authentication swiftly in VANET, we present a new identity-based aggregate signature (IBAGS) system using the lattices. The proposed lattice-based method presented in this article combines the batch verification and aggregate signature scheme (ASS), which finishes the authentication of several vehicular units and aggregates multiple users' signatures into a single (compact) signature. This boosts the competence of the verification process. Furthermore, the vehicle pseudo-identities are also utilized to meet the goals of vehicle identity and privacy protection. Finally, dependable cloud storage technology efficiently enables the secure storing of message signatures. This article demonstrates the lower storage overhead and increases authentication efficiency while maintaining security compared to similar competing schemes.

Abstract

The rise of smart cities is directly connected to the increasing use of vehicles. The growing vehicle utilization has driven the emergence of Vehicular Ad-hoc Networks (VANETs), facilitating instant information exchange among vehicles. The system provides essential information regarding road conditions, traffic patterns, and more relevant data. VANETs encompass two fundamental categories of communication exchanges, namely Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). V2I technology facilitates the integration of cars and transportation infrastructure, enabling effective communication between vehicles and infrastructure. Nevertheless, the potential of V2I communication has various security concerns arising from prevalent security threats. Current authentication techniques encounter challenges regarding complexity, security, and privacy considerations. We designed a hash-based lightweight and anonymous authentication scheme to address the aforementioned restrictions and enhance the effectiveness of authentication in V2I architecture. This scheme effectively combines identity, password, and bio-metric to enhance resistance against impersonation, denial of service, and privileged insider attacks. The devised scheme distinguishes itself by a comparative analysis and security proofs, highlighting its superior capability in guaranteeing secure authentication in V2I communication. The comprehensive security analysis conducted formally and informally showcases the robustness of the proposed solution against several threats. The performance evaluation results show that our scheme demonstrates a decrease in the computational cost of 51.40% approximately and a reduction in communication overhead of around 22.57%. These results establish the efficiency and scalability of the proposed scheme as a viable solution for V2I architecture.