An Assessment of Entropy-Based Data Reduction for SEI Within IoT Applications

The research community remains focused on addressing Internet of Things (IoT) security concerns due to its continued proliferation and use of weak or no encryption. Specific Emitter Identification (SEI) has been introduced to combat this security vulnerability. Recently, Deep Learning (DL) has been leveraged to accelerate SEI using the signals’ Time-Frequency (TF) representation. While TF representations improve DL-based SEI accuracy–over raw signal learning–these transforms generate large amounts of data that are computationally expensive to store and process by the DL network. This study investigates the use of entropy-based data reduction applied to “tiles” selected from the signals’ TF representations. Our results show that entropy-based data reduction lowers the average SEI performance by as little as 0.86% while compressing the memory and training time requirements by as much as 92.65% and 80.7%, respectively

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Entropy aided RF-DNA fingerprint learning from Gabor-based images

The number of devices connected to the internet have been increasing and shape Internet of Things (IoT). The security of IoT is an issue due to the use of weak or no encryption. Specific Emitter Identification (SEI) was introduced to overcome this issue by introduce RF-DNA fingerprinting exploring the PHY layer features. Recently, The SEI performance improved by the usage of the signal’s Time Frequency (TF) representation and accelerated using the Deep learning (DL) Convolutional Neural Network (CNN). While the classification accuracy has been improved from using raw signals learning the amount of data generated is large and computationally expensive. This work investigate the usage of statistical thresholds like entropy applied to ”tiles” selected from the signals’ TF representation to reduce the amount of data generated. The results show that the entropy based data reduction decrease the average classification accuracy by 0.86% compared to the usage of the full gray-scale image at 30dB. The usage of enhanced tiles selection algorithms shows an improvement in the average classification accuracy by 25% from the original tile selection procedure at 9dB

The educational value of ward rounds as a learning and teaching opportunity for house officers, medical officers, and registrars in Sudanese hospitals: a multi-center cross-sectional study

Abstract Background Ward rounds are a cornerstone in the educational experience of junior doctors and an essential part of teaching patient care. Here, we aimed to assess the doctors’ perception of ward rounds as an educational opportunity and to identify the obstacles faced in conducting a proper ward round in Sudanese hospitals. Method A cross-sectional study was conducted from the 15th to the 30th of January 2022 among house officers, medical officers, and registrars in about 50 teaching and referral hospitals in Sudan. House officers and medical officers were considered the learners, while specialist registrars were considered the teachers. Doctors’ perceptions were assessed using an online questionnaire, with a 5-level Likert scale to answer questions. Results A total of 2,011 doctors participated in this study (882 house officers, 697 medical officers, and 432 registrars). The participants were aged 26.9 ± 3.2 years, and females constituted about 60% of the sample. An average of 3.1 ± 6.8 ward rounds were conducted per week in our hospitals, with 11.1 ± 20.3 h spent on ward rounds per week. Most doctors agreed that ward rounds are suitable for teaching patient management (91.3%) and diagnostic investigations (89.1%). Almost all the doctors agreed that being interested in teaching (95.1%) and communicating appropriately with the patients (94.7%) make a good teacher in ward rounds. Furthermore, nearly all the doctors agreed that being interested in learning (94.3%) and communicating appropriately with the teacher (94.5%) make a good student on ward rounds. About 92.8% of the doctors stated that the quality of ward rounds could be improved. The most frequently reported obstacles faced during ward rounds were the noise (70%) and lack of privacy (77%) in the ward environment. Conclusion Ward rounds have a special value in teaching patient diagnosis and management. Being interested in teaching/learning and having good communication skills were the two major criteria that make a good teacher/learner. Unfortunately, ward rounds are faced with obstacles related to the ward environment. It is mandatory to ensure the quality of both ward rounds' teaching and environment to optimize the educational value and subsequently improve patient care practice