1,721,014 research outputs found
A cooperative spectrum sensing with multi-agent reinforcement learning approach in cognitive radio networks
No full textCognitive radio networks (CRNs) can greatly improve the temporal and spatial spectrum utilization by identifying and exploring spectrum holes of the licensed primary users (PUs). However, since the occupation of primary channels changes dynamically, a swift and accurate spectrum sensing is crucial especially in the multi-channel multi-secondary users (SUs) environment, where the number of channels is much larger than that of SUs. To improve the sensing accuracy, a cooperative sensing algorithm is proposed in this letter, where multiple SUs can share their spectrum detection results for a more effective spectrum holes search. This letter further employs multi-agent deep deterministic policy gradient (MADDPG) algorithm with the feature of centralized training and decentralized execution to reduce the synchronization and communication overhead caused by the sensing cooperation of SUs. The numerical simulation demonstrates that with the combination of cooperative sensing and multi-agent reinforcement learning, the proposed algorithm can greatly enhance the sensing accuracy in comparison to other non-cooperative learning or centralized learning approaches.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Exploiting Meta-Path with Attention Mechanism for Fine-Grained User Location Prediction in LBSNs
No full textAbstract Based on the huge volumes of user check-in data in LBSNs, users’ intrinsic mobility patterns can be well explored, which is fundamental for predicting where a user will visit next given his/her historical check-in records. As there are various types of nodes and interactions in LBSNs, they can be treated as Heterogeneous Information Network (HIN) where multiple semantic meta-paths can be extracted. Inspired by the recent success of meta-path context based embedding techniques in HIN, in this paper, we design a deep neural network framework leveraging various meta-path contexts for fine-grained user location prediction. Experimental results based on two real-world LBSN datasets demonstrate the best effectiveness of the proposed approach using various evaluation metrics than others
Cooperative cache in cognitive radio networks: A heterogeneous multi-agent learning approach
No full textDeploying distributed cache in cognitive radio networks (CRNs), which spreads popular contents to the edge of network during the off-peak time through spectrum sharing, can reduce the deliver delay to users nearby without causing severe interference to the primary network. However, due to the un-predicable contents requirement as well as the band occupation of primary users, it is non-trivial to optimize the cache storage and contents fetching strategy of users dynamically. The letter proposes a heterogeneous multi-agent deep deterministic policy gradient (MADDPG) approach, which takes users and cache servers as two different types of agents to learn the cooperation and competition for mutual benefits. The numeral simulation demonstrates that comparing with the other single or homogeneous deep reinforcement learning (DRL) approaches, the proposed heterogeneous MADDPG can further reduce the delivery delay of users and enhance the cache efficiency of SBSs.</p
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe 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
- …
