Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Transformer based Deep Intelligent Contextual Embedding for Twitter sentiment analysis

Social media (and the world at large) have been awash with news of the COVID-19 pandemic With the passage of time, news and awareness about COVID-19 spread like the pandemic itself, with an explosion of messages, updates, videos, and posts Mass hysteria manifest as another concern in addition to the health risk that COVID-19 presented Predictably, public panic soon followed, mostly due to misconceptions, a lack of information, or sometimes outright misinformation about COVID-19 and its impacts It is thus timely and important to conduct an ex post facto assessment of the early information flows during the pandemic on social media, as well as a case study of evolving public opinion on social media which is of general interest This study aims to inform policy that can be applied to social media platforms; for example, determining what degree of moderation is necessary to curtail misinformation on social media This study also analyzes views concerning COVID-19 by focusing on people who interact and share social media on Twitter As a platform for our experiments, we present a new large-scale sentiment data set COVIDSENTI, which consists of 90 000 COVID-19-related tweets collected in the early stages of the pandemic, from February to March 2020 The tweets have been labeled into positive, negative, and neutral sentiment classes We analyzed the collected tweets for sentiment classification using different sets of features and classifiers Negative opinion played an important role in conditioning public sentiment, for instance, we observed that people favored lockdown earlier in the pandemic; however, as expected, sentiment shifted by mid-March Our study supports the view that there is a need to develop a proactive and agile public health presence to combat the spread of negative sentiment on social media following a pandemic

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COVIDSenti: A Large-Scale Benchmark Twitter Data Set for COVID-19 Sentiment Analysis

Distance is an important parameter in any networks/ graphs. The idea of strong sum distance in the fuzzy graph was introduced by Tom and Sunitha (2015). A generalization of fuzzy graph called neutrosophic graph is more realistic to handle imprecise data. In this study, the weight of an edge of a neutrosophic graph is defined and hence defined sum distance in a neutrosophic graph based on the idea of strong sum distance. This distance is also metric and based on this metric, the concepts of degree, eccentricity, radius, diameter etc. are studied with some properties. At last, a real-life application on the travelling salesman problem is illustrated.

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A Study on Discrete Mathematics: Sum Distance in Neutrosophic Graphs with Application

Autonomous Vehicle (AV) is a rapidly evolving mobility technology with the potential to drastically alter the future of transportation. Despite the plethora of potential benefits that have prompted their eventual introduction, AVs may also be a source of unprecedented disruption for future travel eco-systems due to their vulnerability to cyber-threats. In this context, this work assesses AVs' cybersecurity readiness. It establishes a Causal Loop Diagram (CLD) based on the System Dynamics approach: a powerful technique inferred from system theory, which can synthesise the behaviour of complicated AV systems. Based on the CLD model, three feedback loops and a system archetype “Fixes-That-Fail” are envisioned, in which the growth in hacker capability, an unforeseen result of technology innovation, demands constant mitigation efforts. The most challenging aspect of this context is determining the trade-off between five components: i) the natural growth of AV technology; ii) stakeholders (communication service providers, road operators, automakers, AV consumers, repairers, and the general public) access to AV technology; iii) the measures to limit hackers' access to AV technology; iv) a pervasive dynamic strategy for circumventing hacker amplification; and v) the efficient usage of AV operating logfiles.

Shah Khalid Khan

Papers

A Study on Discrete Mathematics: Sum Distance in Neutrosophic Graphs with Application

Cybersecurity Readiness for Automated Vehicles