In: Administrative sciences, 2021, vol. 11, no. 4, p. 17
In this study, we investigate the consequences of organizational change that consist of adding new categories to the portfolio of humanitarian organizations. Our aim is to discern differences in these consequences between specialist and generalist organizations. Previous research has shown that spanning categories lead to disadvantages in the evaluation of organizations by audience members in...
|
In: Personality and individual differences, 2022, vol. 185, p. 10
The personality trait of neuroticism (N) has consistently shown to be a risk factor for Internet Addiction (IA). Review literature, however, looked at this in bivariate analyses only. To the best of our knowledge, we conducted the first review that systematically and conceptually summarized results based on the inclusion of additional factors, thus coming closer to the complex nature of the ...
|
In: Cancers, 2021, vol. 13, no. 19, p. 18
Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g., machine learning and deep learning, as well as the recently developed research field of radiomics have noticeable potential to transform medical diagnostics. AI-based techniques applied to medical imaging allow to detect biological abnormalities, to...
|
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...
|
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...
|
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...
|
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....
|
In: Philosophical studies, 2021, p. 26
This paper is concerned with two concepts of qualitativeness that apply to intensional entities (i.e., properties, relations, and states of affairs). I propose an account of pure qualitativeness that largely follows the traditional understanding established by Carnap, and try to shed light on its ontological presuppositions. On this account, an intensional entity is purely qualitative iff it...
|
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...
|
In: Journal of computational science, 2021, vol. 53, p. 13
The ℓ1-regularized Gaussian maximum likelihood method is a common approach for sparse precision matrix estimation, but one that poses a computational challenge for high-dimensional datasets. We present a novel ℓ1- regularized maximum likelihood method for performant large-scale sparse precision matrix estimation utilizing the block structures in the underlying computations. We identify the...
|