17,476 research outputs found
A Comparative Usability Study of Two-Factor Authentication
Two-factor authentication (2F) aims to enhance resilience of password-based
authentication by requiring users to provide an additional authentication
factor, e.g., a code generated by a security token. However, it also introduces
non-negligible costs for service providers and requires users to carry out
additional actions during the authentication process. In this paper, we present
an exploratory comparative study of the usability of 2F technologies. First, we
conduct a pre-study interview to identify popular technologies as well as
contexts and motivations in which they are used. We then present the results of
a quantitative study based on a survey completed by 219 Mechanical Turk users,
aiming to measure the usability of three popular 2F solutions: codes generated
by security tokens, one-time PINs received via email or SMS, and dedicated
smartphone apps (e.g., Google Authenticator). We record contexts and
motivations, and study their impact on perceived usability. We find that 2F
technologies are overall perceived as usable, regardless of motivation and/or
context of use. We also present an exploratory factor analysis, highlighting
that three metrics -- ease-of-use, required cognitive efforts, and
trustworthiness -- are enough to capture key factors affecting 2F usability.Comment: A preliminary version of this paper appears in USEC 201
Data Innovation for International Development: An overview of natural language processing for qualitative data analysis
Availability, collection and access to quantitative data, as well as its
limitations, often make qualitative data the resource upon which development
programs heavily rely. Both traditional interview data and social media
analysis can provide rich contextual information and are essential for
research, appraisal, monitoring and evaluation. These data may be difficult to
process and analyze both systematically and at scale. This, in turn, limits the
ability of timely data driven decision-making which is essential in fast
evolving complex social systems. In this paper, we discuss the potential of
using natural language processing to systematize analysis of qualitative data,
and to inform quick decision-making in the development context. We illustrate
this with interview data generated in a format of micro-narratives for the UNDP
Fragments of Impact project
Natural Language Generation and Fuzzy Sets : An Exploratory Study on Geographical Referring Expression Generation
This work was supported by the Spanish Ministry for Economy and Competitiveness (grant TIN2014-56633-C3-1-R) and by the European Regional Development Fund (ERDF/FEDER) and the Galician Ministry of Education (grants GRC2014/030 and CN2012/151). Alejandro Ramos-Soto is supported by the Spanish Ministry for Economy and Competitiveness (FPI Fellowship Program) under grant BES-2012-051878.Postprin
Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines
A cross-disciplinary examination of the user behaviours involved in seeking
and evaluating data is surprisingly absent from the research data discussion.
This review explores the data retrieval literature to identify commonalities in
how users search for and evaluate observational research data. Two analytical
frameworks rooted in information retrieval and science technology studies are
used to identify key similarities in practices as a first step toward
developing a model describing data retrieval
An exploratory study to design an adaptive hypermedia system for online-advertisement
The revolutionary world of the World Wide Web has created an open space for a multitude of fields to develop and propagate. One of these major fields is advertisement. Online advertisement has become one of the main activities conducted on the web, heavily supported by the industry. Importantly, it is one of the main contributors to any businesses’ income. However, consumers usually ignore the great majority of adverts online. This research paper studies the field of online advertisement, by conducting an exploratory study to understand end users’ needs for targeted online advertisement using adaptive hypermedia techniques. Additionally, we explore social networks, one of the booming phenomena of the web, to enhance the appropriateness of the advertising to the users. The main current outcome of this research is that end users are interested in personalised advertisement that tackles their needs and that they believe that the use of social networks and social actions help in the contextualisation of advertisement
The memory space: Exploring future uses of Web 2.0 and mobile internet through design interventions.
The QuVis Quantum Mechanics Visualization project aims to address challenges
of quantum mechanics instruction through the development of interactive
simulations for the learning and teaching of quantum mechanics. In this
article, we describe evaluation of simulations focusing on two-level systems
developed as part of the Institute of Physics Quantum Physics resources.
Simulations are research-based and have been iteratively refined using student
feedback in individual observation sessions and in-class trials. We give
evidence that these simulations are helping students learn quantum mechanics
concepts at both the introductory and advanced undergraduate level, and that
students perceive simulations to be beneficial to their learning.Comment: 15 pages, 5 figures, 1 table; accepted for publication in the
American Journal of Physic
The memory space: Exploring future uses of Web 2.0 and mobile internet through design interventions.
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