232,915 research outputs found
Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures
Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, SlepianâWolf and WynerâZiv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs
Effectiveness and Content Analysis of Interventions to Enhance Oral Antidiabetic Drug Adherence in Adults with Type 2 Diabetes : Systematic Review and Meta-Analysis
We thank Frederic Bergeron, information scientist, for assistance in search strategies. We thank American Journal Experts for editing the text. Source of financial support: This study was funded by the Laval University Chair on Adherence to Treatments. This Chair is supported by nonrestricted grants from AstraZeneca Canada, Merck Canada, Sanofi Canada, and Pfizer Canada and from the Prends soin de toi program (a Quebec provincial program for the improvement of public health).Peer reviewedPostprin
Naming the Pain in Requirements Engineering: A Design for a Global Family of Surveys and First Results from Germany
For many years, we have observed industry struggling in defining a high
quality requirements engineering (RE) and researchers trying to understand
industrial expectations and problems. Although we are investigating the
discipline with a plethora of empirical studies, they still do not allow for
empirical generalisations. To lay an empirical and externally valid foundation
about the state of the practice in RE, we aim at a series of open and
reproducible surveys that allow us to steer future research in a problem-driven
manner. We designed a globally distributed family of surveys in joint
collaborations with different researchers and completed the first run in
Germany. The instrument is based on a theory in the form of a set of hypotheses
inferred from our experiences and available studies. We test each hypothesis in
our theory and identify further candidates to extend the theory by correlation
and Grounded Theory analysis. In this article, we report on the design of the
family of surveys, its underlying theory, and the full results obtained from
Germany with participants from 58 companies. The results reveal, for example, a
tendency to improve RE via internally defined qualitative methods rather than
relying on normative approaches like CMMI. We also discovered various RE
problems that are statistically significant in practice. For instance, we could
corroborate communication flaws or moving targets as problems in practice. Our
results are not yet fully representative but already give first insights into
current practices and problems in RE, and they allow us to draw lessons learnt
for future replications. Our results obtained from this first run in Germany
make us confident that the survey design and instrument are well-suited to be
replicated and, thereby, to create a generalisable empirical basis of RE in
practice
A checklist for choosing between R packages in ecology and evolution
The open source and free programming language R is a phenomenal mechanism to address a multiplicity of challenges in ecology and evolution. It is also a complex ecosystem because of the diversity of solutions available to the analyst.
Packages for R enhance and specialize the capacity to explore both niche data/experiments and more common needs. However, the paradox of choice or how we select between many seemingly similar options can be overwhelming and lead to different potential outcomes.
There is extensive choice in ecology and evolution between packages for both fundamental statistics and for more specialized domainâlevel analyses.
Here, we provide a checklist to inform these decisions based on the principles of resilience, need, and integration with scientific workflows for evidence.
It is important to explore choices in any analytical coding environmentânot just Râfor solutions to challenges in ecology and evolution, and document this process because it advances reproducible science, promotes a deeper understand of the scientific evidence, and ensures that the outcomes are correct, representative, and robust.York University Librarie
Influence of developer factors on code quality: a data study
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Automatic source-code inspection tools help to assess,
monitor and improve code quality. Since these tools only
examine the software projectâs codebase, they overlook other
possible factors that may impact code quality and the assessment of the technical debt (TD). Our initial hypothesis is that human factors associated with the software developers, like coding expertise, communication skills, and experience in the project have some measurable impact on the code quality. In this exploratory study, we test this hypothesis on two large open source repositories, using TD as a code quality metric and the data that may be inferred from the version control systems. The preliminary results of our statistical analysis suggest that the level of participation of the developers and their experience in the project have a positive correlation with the amount of TD
that they introduce. On the contrary, communication skills have
barely any impact on TD.Peer ReviewedPostprint (author's final draft
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