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Application Layer Security: MQTT Perspective with TLS Implementation and Analysis
Get PDFThe Internet of Things (IoT) has become ingrained in our daily lives, transforming the way we interact with technology. From smart homes to wearable devices, IoT enhances convenience and connectivity. However, this widespread adoption raises security concerns. Recent years have witnessed a surge in cyberattacks exploiting vulnerabilities in IoT devices. Security lapses in device development and the sheer volume of interconnected devices contribute to the challenges. Data breaches and privacy infringements also loom large, highlighting the need for a balanced approach to technological advancement and robust cybersecurity measures to safeguard personal information and ensure the positive impact of IoT on daily life. In this study, we reviewed IoT encryption algorithms with focus on the integration between the IoT application layer and some encryption algorithms with focus on the MQTT protocol. Additionally, we conducted a comparative performance analysis of MQTT with and without TLS, highlighting the impact of encryption on IoT communication in terms of different performance metrics like CPU cycles, memory consumption, latency and throughput
Graph-informed convolutional autoencoder to classify brain responses during sleep
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The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.An Erratum on:
Graph-informed convolutional autoencoder to classify brain responses during sleep
by Zakeri, S., Makouei, S., and Danishvar, S. (2025). Front. Neurosci. 19:1525417. doi: 10.3389/fnins.2025.1525417
Due to a production error, there was an error regarding the affiliation for Somayeh Makouei. Instead of having affiliation 2, they should have affiliation 1: “Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran”.
The publisher apologizes for this mistake. The original version of this article has been updated.
Keywords: auditory stimuli, convolutional neural network, EEG, functional connectivity, graphical representation, sleep
Citation: Frontiers Production Office (2025) Erratum: Graph-informed convolutional autoencoder to classify brain responses during sleep. Front. Neurosci. 19:1627975. doi: 10.3389/fnins.2025.1627975Automated machine-learning algorithms that analyze biomedical signals have been used to identify sleep patterns and health issues. However, their performance is often suboptimal, especially when dealing with imbalanced datasets. In this paper, we present a robust sleep state (SlS) classification algorithm utilizing electroencephalogram (EEG) signals. To this aim, we pre-processed EEG recordings from 33 healthy subjects. Then, functional connectivity features and recurrence quantification analysis were extracted from sub-bands. The graphical representation was calculated from phase locking value, coherence, and phase-amplitude coupling. Statistical analysis was used to select features with p-values of less than 0.05. These features were compared between four states: wakefulness, non-rapid eye movement (NREM) sleep, rapid eye movement (REM) sleep during presenting auditory stimuli, and REM sleep without stimuli. Eighteen types of different stimuli including instrumental and natural sounds were presented to participants during REM. The selected significant features were used to train a novel deep-learning classifiers. We designed a graph-informed convolutional autoencoder called GICA to extract high-level features from the functional connectivity features. Furthermore, an attention layer based on recurrence rate features extracted from EEGs was incorporated into the GICA classifier to enhance the dynamic ability of the model. The proposed model was assessed by comparing it to baseline systems in the literature. The accuracy of the SlS-GICA classifier is 99.92% on the significant feature set. This achievement could be considered in real-time and automatic applications to develop new therapeutic strategies for sleep-related disorders.This research is supported by the research grant of the University of Tabriz number s/2843
Stand-Up Comedy and Offence
No full textOffensiveness is a key issue in contemporary public discourse, especially in relation to media content. Stand-up comedy has provided an important site for discussions of offensiveness, both inside of performances and in the commentary on comedy in other forms of popular media. This chapter provides a brief summary of some well-known examples of stand-up comedy that are embroiled in debates on offensiveness, before engaging in a discussion of what constitutes offensive stand-up comedy. The chapter theorises the discursive work that offensive stand-up comedy does in contemporary contexts through concepts of rhetoric, the performative, and symbolic violence. Comedy and harm are discussed and an explanation of what researchers have described as the impacts of humour and comedy is given. Throughout the chapter, the points made are elaborated with extracts from British stand-up comedian Ricky Gervais’ Netflix special Supernature (2022), especially through an analysis of jokes made by Gervais about transgender people. These and other jokes are examined alongside the disclaimers used in the stand-up comedy performance
A fractional integration model and testing procedure with roots within the unit circle
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The data presented in this study are openly available in National Institute of Standards and Technology (NIST), www.nist.gov.JEL codes: C22.MSC: 62M10.In this paper we propose a statistical model that combines both autoregressions and fractional differentiation in a unified treatment. However, instead of imposing that the roots are strictly on the unit circle, we also allow them to be within the unit circle. This permits a higher degree of flexibility in the specification of the model, with rates of dependence combining exponential with hyperbolic decays. Monte Carlo experiments and empirical applications to climatological and financial data show that the proposed approach performs well.Luis A. Gil-Alana gratefully acknowledges financial support from the project from ‘Ministerio de Ciencia, Innovación y Universidades’ Agencia Estatal de Investigación’ (AEI) Spain and ‘Fondo Europeo de Desarrollo Regional’ (FEDER), Grant D2023-149516NB-I00 funded by MCIN/AEI/10.13039/501100011033. He also acknowledges support from an internal project of the Universidad Francisco de Vitoria
A 2-stage vision-based localization methodology for efficient automatic charging of electric vehicles in uncertain environments
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The data that support the findings of this study are available from the corresponding author upon reasonable request.Automatic visual localization of electric vehicle (EV) charging ports presents significant challenges in uncertain environments, such as varying surface textures, reflections, lighting and observation distance. Existing methods require extensive real-world training data and well-focused images to achieve robust and accurate localization. However, both requirements are difficult to meet under variable and unpredictable conditions. This paper proposes a 2-stage vision-based localization approach. Firstly, the image synthesis technique is used to reduce the cost of real-world data collection. A task-oriented parameterization protocol (TOPP) is proposed to optimize the quality of the synthetic images. Secondly, an autofocus and servoing strategy is proposed. A hybrid detector is employed to enhance sharpness assessment performance, while a visual servoing method based on single exponential smoothing (SES) is developed to enhance stability and efficiency during the search process. Experiments were conducted to evaluate image synthesis efficiency, detection accuracy, and servoing performance. The proposed method achieved 99% detection accuracy on the real-world port images, and guided the robot to the optimal imaging position within 16 s, outperforming comparable approaches. These results highlight its potential for robust automated charging in real-world scenarios.Funding Research supported by the State Key Laboratory of Digital Manufacturing Equipment and Technology, Grant No. DMETKF2021018. GJYC program of GuangZhou, Grant ID. 2024D03J0005. Chunhui Project Foundation of the Education Department of China, Grant No. 202201789
Conceptual Aircraft Design and AI: Developing a functional relationship for the rapid realisation of future drone concepts
Get PDFThe use of Unmanned Aerial Vehicles(UAVs) has expanded rapidly over the last decade. These systems have an almost limitless scope of application with resupply, surveillance, monitoring, and logistics representing but a few. Having such a wide scope, a means to rapidly, efficiently and accurately develop new designs fit-for-purpose would offer a significant advantage to developers given their inherent need to maximise potential within a competitive marketplace. This paper attempts to leverage the capabilities of Artificial Intelligence(AI) for this purpose through the development of functional synergies to predict maximum rated engine power from limited inputs and datasets. Overall, the use of AI techniques was found to offer the potential to substantial improve and enhance the design process with also the possibility for the creation of more cost-effective and efficient software tools that could significantly streamline the process.The work was financially supported under project “DATA3: Drone Design using AI for Transport Applications 3(Grant No 10126519)” as part of the UKRI Innovate UK Feasibility studies for AI solutions: Series 2 competition
Blockchain Developer Experience: A Multivocal Literature Review
Get PDFThe article version archived on this institutional repository is a preprint available at arXiv:2501.11431v1 [cs.SE], https://arxiv.org/abs/2501.11431 . Comments: 12 pages, 5 figures, 18th Conference on Cooperative and Human Aspects of Software Engineering (CHASE).The rise of smart contracts has expanded blockchain's capabilities, enabling the development of innovative decentralized applications (dApps). However, this advancement brings its own challenges, including the management of distributed architectures and immutable data. Addressing these complexities requires a specialized approach to software engineering, with blockchain-oriented practices emerging to support development in this domain. Developer Experience (DEx) is central to this effort, focusing on the usability, productivity, and overall satisfaction of tools and frameworks from the engineers' perspective. Despite its importance, research on Blockchain Developer Experience (BcDEx) remains limited, with no systematic mapping of academic and industry efforts. To bridge this gap, we conducted a Multivocal Literature Review analyzing 62 to understand the distribution of BcDEx sources, practical implementations, and their impact. Our findings revealed that academic focus on BcDEx is limited compared to the coverage in gray literature, which primarily includes blogs (41.8%) and corporate sources (21.8%). Particularly, development efficiency, multi-network support, and usability are the most addressed aspects in tools and frameworks. In addition, we found that BcDEx is being shaped through five key perspectives: complexity abstraction, adoption facilitation, productivity enhancement, developer education, and BcDEx evaluation.This work received partial funding from CNPq-Brazil, Universal grant 404406/2023-8, and support from CAPES - Funding Code 001
Multi-objective optimisation of electrolysis across diverse supply configurations in hydrogen–electricity coupled energy networks – A UK perspective
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The authors do not have permission to share data.The adaptability of hydrogen across sectors such as transportation, heavy industry, and its support for intermittent renewable generation through flexible storage has sparked growing interest in electrolysis-based hydrogen production. While large-scale electrolyser integration enhances network stability by aiding constraint management and reducing renewable curtailment through storage, it also places considerable demand on electricity networks. This makes understanding the role of electrolyser deployment on distribution networks (DNs) increasingly crucial. While existing studies on hydrogen-integrated DNs often target specific operational costs or isolated constraints, they typically lack a comprehensive view that considers broader economic, operational, and environmental impacts. This study offers an extensive analysis across these dimensions, exploring diverse hydrogen supply configurations, including hydrogen pipeline and storage unit availability, within a real UK DN to provide a practical perspective. This study introduces a conflicting multi-objective function that improves load factor (LF) by 85.516% and reduces power loss by 22.947%, all while managing operational costs effectively. Findings underline that deploying electrolysers with efficient management algorithms can significantly enhance the operations of DNs. Additionally, this paper contributes to the field by detailing recent UK-based electrolysis projects, providing insights into the future of hydrogen–electricity coupled multi-energy networks.This research was supported by Engineering and Physical Sciences Research Council (EPSRC) Grant Reference EP/W524542/1. The authors thank UK Power Networks DSO for providing data during the corresponding author’s employment, which contributed significantly to the analysis presented in this study
The Potential of Wood Ash to Be Used as a Supplementary Cementitious Material in Cement Mortars
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All results are presented in this article.Acknowledgments:
This article is based on work by COST Action (CircularB— Implementation of Circular Economy in the Built Environment, CA21103), supported by COST (European Cooperation in Science and Technology).This study explores the application of wood ash (WA) as a partial replacement for PC in mortar. Three pre-treatment methods were applied to WA to enhance its reactivity, and it was then incorporated into mortar at two different substitution levels of 10 and 30%. Tests on compressive and flexural strength were conducted on the hardened mortar samples. All hardened mortar samples containing WA showed a decrease in mechanical properties compared to the reference sample without WA. The highest compressive and flexural strength of the samples with WA were observed for those containing 10% of sieved and slaked WA. The compressive and flexural strength of these samples after 28 days were 56 and 9 MPa, respectively, whereas those of the reference samples were 62 and 10 MPa, respectively. Based on the results, the best-performing samples on the compressive test underwent additional testing for freeze–thaw resistance to assess their durability. The mass loss of the reference sample and that with 10% of sieved and slaked WA after 56 freeze–thaw cycles was 11,800 and 13,800 g/m2, respectively. The findings revealed that increasing the proportion of WA typically led to a decline in the mechanical properties of mortar compared to conventional mixtures. However, with appropriate pre-treatment techniques, the quality and performance of mortar containing WA were significantly improved, demonstrating its potential as a sustainable alternative in reducing the carbon footprint of PC production.This activity/work was supported by the EU Recovery and Resilience Facility within Project No 5.2.1.1.i.0/2/24/I/CFLA/003 “Implementation of consolidation and management changes at Riga Technical University, Liepaja University, Rezekne Academy of Technology, Latvian Maritime Academy and Liepaja Maritime College for the progress towards excellence in higher education, science and innovation” academic career doctoral grant (ID 1069)
Bridging the pulse: Exploring inequalities in diabetes and hypertension medication prescriptions in Spain's immigrant and native communities
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The authors do not have permission to share data.JEL classification:
F22; I12; I14; J15.Migrants often face barriers in accessing high quality healthcare, leading to unequal treatment. This research investigates the disparities in medication utilization for cardiovascular risk factors between immigrant and native-born populations in Spain. The study specifically examines differences in drug prescriptions for managing diabetes and hypertension, two key contributors to cardiovascular disease. We analyze administrative healthcare records to examine the probability of patients receiving prescriptions for antidiabetic and antihypertensive medications. Additionally, we assess the likelihood of patients undergoing tests to measure glycated hemoglobin levels and blood pressure, two crucial indicators for monitoring diabetes and hypertension management.The analysis is stratified across different levels of medical needs, by also controlling for individual socioeconomic status, physician diagnoses, biometric data and primary care centers fixed effects. The findings reveal that all immigrant groups have lower probabilities of being prescribed medications for diabetes and hypertension and this is especially true for people with higher levels of healthcare needs. These findings underscore the importance of addressing healthcare disparities to achieve more equitable outcomes for immigrant communities.Nicodemo has received funding from the Economic and Social Research Council (grant number ES/T008415/1)
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