1,721,025 research outputs found
PROTECTION: Provably Robust Intrusion Detection system for IoT through recursive Delegation
No full textThe security of Internet of Things (IoT) ecosystems is crucial for maintaining user trust and facilitating widespread adoption. Machine Learning (ML) based Intrusion Detection and Prevention Systems (IDS/IPS) are frequently used to protect IoT networks, yet they are susceptible to adversarial attacks (AAs) and lack formal verifiability of their robustness. It has been demonstrated that meticulously designed AAs can alter the classification of ML-based IDSs, rendering them ineffective and posing risks to lives and physical infrastructure in safety-critical systems. This paper addresses these issues by introducing PROTECTION: a Provably RObust Intrusion DeTECTion system for IoT through recursive delegatION, which combines formal methods with ensemble machine learning. To enhance the robustness of ensemble ML models, we utilise Satisfiability-Modulo-Theory (SMT) to formally verify the classifier’s robustness, ensuring that output probabilities remain outside a thick decision boundary even when small perturbations are applied to the inputs. If a classifier fails to meet this criterion on any training sample, we reassign the training task to other classifiers that are iteratively trained until all samples are trained in accordance with the required property. The efficacy of the final ensemble model is thoroughly tested against various input perturbations and AAs using SMT based formal verification
Towards defect-free lattice structures in additive manufacturing: A holistic review of machine learning advancements
No full textAdditive manufacturing has transformed modern production by enabling the fabrication of complex and lightweight structures, particularly lattice geometries, which are widely used in aerospace, automotive, medical, and energy industries. Renowned for their superior strength-to-weight ratios and energy absorption properties, lattice structures have unlocked new possibilities for weight-critical, high-performance applications. However, their intricate geometries and susceptibility to defects, such as surface roughness, voids, and porosity, pose significant challenges to ensuring mechanical integrity and functional reliability. Traditional methods of defect mitigation, process control and optimization, are often constrained by high computational costs and limited adaptability to complex defect mechanisms. To address these challenges, machine learning (ML) has emerged as a transformative tool, offering data-driven solutions for defect prediction, detection, and minimization. These techniques excel in optimizing designs, tuning process parameters, and enabling real-time adjustments to mitigate defects, thereby enhancing manufacturing outcomes. While numerous studies have explored ML applications in additive manufacturing, current literature lacks a specific focus on its use for defect minimization in lattice structures, which require defect-free fabrication to achieve optimal performance. This review paper fills this critical research gap by investigating the application of advanced ML techniques across key areas: design optimization, properties prediction, process parameter tuning, and defect detection and real-time monitoring for lattice structures. In doing so, it gives a comprehensive outline of lattice structures, the challenges posed by manufacturing defects, and state-of-the-art ML applications in AM. This study paves the way for defect-free lattice structures, maximizing their industrial potential
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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