In: Algorithms, 2021, vol. 14, no. 9, p. 25
Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with the issues. A CL is defined as a subset of all the edges linked to a given vertex such that it contains mainly edges that are believed to be...
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In: Public integrity, 2021, p. 13
This article explores how risk rationales affect and alter national security secrecy. While the transformation of defense and security policy has been widely discussed by security theorists, transparency scholars have not yet considered the notion of risk in their conceptualizations of national security secrecy. This article draws on security studies literature to outline the divergences...
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In: International journal of fashion design, technology and education, 2021, vol. 14, no. 3, p. 293-301
This paper focuses on the field of digital fashion and its development by providing an overview regarding fashion design and culture. It is part of a larger research that involved a literature review of 491 relevant papers. From the analysis of this corpus, three main categories were identified: Communication and Marketing, Design and Production and Culture and Society. This study focuses on...
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In: Journalism practice, 2021, p. 23
Diaspora journalists and digital media play an important role as stakeholders for war-ridden homeland media landscapes such as Syria. This study analyzes, from a safety in practice perspective, the physical and digital threats that challenge the work of Syrian citizen journalists examining the role of three online advocacy networks created by Syrian diaspora journalists to promote newsafety....
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In: International journal, 2021, vol. 76, no. 2, p. 238-256
This essay investigates justifications for the “necessity” of official secrecy, by tracing and structuring the rationales underlying it. Justifications will be investigated through the case of “national security secrecy,” a prominent example of official secrecy. While the literature generally treats “national security secrecy” as unidimensional, this analysis demarcates several...
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In: Algorithms, 2020, vol. 13, no. 12, p. 17
Incomplete data are a common feature in many domains, from clinical trials to industrial applications. Bayesian networks (BNs) are often used in these domains because of their graphical and causal interpretations. BN parameter learning from incomplete data is usually implemented with the Expectation-Maximisation algorithm (EM), which computes the relevant sufficient statistics (“soft EM”) ...
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In: Journal of travel & tourism marketing, 2021, vol. 38, no. 3, p. 326-340
A lack of cross-cultural research has been identified regarding cultural tourism promotion on social media. Using the dimensions of Collectivism-Individualism, Power Distance, and High-Context vs. Low-Context communication, we content analyze cultural value differences in Instagram posts promoting cultural tourism – published by the national tourism organizations of Chile, Portugal, USA, and...
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In: Journal of pragmatics, 2021, vol. 174, no. March, p. 55-67
In light of the ongoing public controversy surrounding fashion sustainability, this paper sets out to identify misalignments that relate to the definitions of sustainable fashion. It does so by examining the discourse of different agents in this polylogical argumentation - fashion companies and the European Parliament as well as citizens, small brands and NGOs - as revealed through documents...
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In: Scientometrics, 2021, vol. 126, no. 2, p. 1311–1328
The aim of this study was to examine how institutional barriers arising from policy decisions influence the level of participation of third- party countries in European Framework Programs (EU-FPs). To achieve this, we contrasted the effect of EU funding restrictions following Switzerland’s 2014 reclassification as a “third country” in Horizon 2020, and the political uncertainties resulting...
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In: Entropy, 2021, vol. 23, no. 1, p. 27 p
Recent advances in statistical inference have significantly expanded the toolbox of probabilistic modeling. Historically, probabilistic modeling has been constrained to very restricted model classes, where exact or approximate probabilistic inference is feasible. However, developments in variational inference, a general form of approximate probabilistic inference that originated in statistical...
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