1,720,972 research outputs found
A new practical physical layer secret key generation in the presence of an untrusted relay
No full textPhysical layer secret key generation (SKG) has recently been introduced as a lightweight and efficient solution for sixth-generation (6G) networks. In this area, schemes based on local random generators are used for high-rate key generation. One of these schemes is random phase injection, where channel probe signals with random phases are exchanged between communication parties (source and destination). This paper proposes an SKG scheme in the presence of an untrusted relay, which helps the SKG process while cannot extract the secret key. To make the scheme operational, for the first time, the channel probe signals are considered discrete random phase based on M-PSK signals and a multi-bit quantizer is used in the reception. In addition, to reduce the key error rate, quantization with guard bands (GB) is used for key extraction. For such a scenario, we derive expressions for key agreement rate, key mismatch rate (KMR), key discarding rate (KDR) and key generation rate (KGR). Additionally, for the first time, this work examines the context of geometric secrecy for the proposed discrete phase key generation scheme for both direct and relaying scenarios. Through simulations, several engineering insights are presented to enhance the quality of the proposed SKG and its security
Intelligent secure transmission in untrusted relaying systems with hardware impairments
No full textEnsuring secure communication in wireless networks remains a significant challenge, especially in the presence of untrusted relays. This study addresses this challenge by employing an intelligent Transmit Antenna Selection (TAS) technique, integrated with machine learning (ML) and deep learning (DL) models, including the Transformer architecture, to optimize secure transmission over Rician fading channels with hardware impairments (HWIs). Simulation results demonstrate that the Transformer-based model achieves state-of-the-art performance, consistently surpassing traditional ML models in classification accuracy and security metrics. Specifically, the Transformer achieves an average Area Under the Curve (AUC) of 0.90 and classification accuracy of 83.5%, significantly outperforming the Support Vector Machine (SVM) (AUC: 0.87, accuracy: 41.5%), k-nearest Neighbors (KNN) (AUC: 0.69, accuracy: 46%), and Naive Bayes (NB) (AUC: 0.53, accuracy: 18%). Furthermore, the Transformer model approximates the performance of exhaustive search methods in terms of average secrecy rate and secrecy outage probability, highlighting its ability to capture complex dependencies and adapt to diverse scenarios. These findings establish the Transformer as a robust and scalable solution for secure communication in challenging wireless environments, paving the way for future advancements in physical layer security (PLS) and intelligent TAS strategies
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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