scholarly journals Overcoming the Challenges of Ocean Data Uncertainty

Eos ◽  
2022 ◽  
Vol 103 ◽  
Author(s):  
Shane Elipot ◽  
Kyla Drushka ◽  
Aneesh Subramanian ◽  
Mike Patterson
Keyword(s):  
Scientific Field ◽  
Data Uncertainty

In oceanography, as in any scientific field, the goal is not to eliminate uncertainty in data, but instead to better quantify and clearly communicate its size and nature.

Is Creativity Studies a Scientific Field? Mapping the History of the Discipline

2011 ◽  
Author(s):  
Haiying Long ◽  
Bing He ◽  
Ying Ding ◽  
Jonathan A. Plucker
Keyword(s):  
Scientific Field ◽  
Field Mapping ◽  
History Of ◽  
Creativity Studies

Analysis of Fibronectin and TGF-β1 Immunoexpression to Determination of Wound Vitality in Wistar Rats (Rattus norvegicus)

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Nita Novita ◽  
Hasrayati Agustina ◽  
Bethy S. Hernowo ◽  
Abdul H. Hassan
Keyword(s):  
Rattus Norvegicus ◽  
Wistar Rats ◽  
Age Determination ◽  
Scientific Field ◽  
Wound Age ◽  
Forensic Practice ◽  
Randomized Design ◽  
Completely Randomized Design ◽  
Tgf Β1

Wound examination is indispensable in forensic practice. The scientific field of wound age determination has advanced progressively during recent years.The purpose of this study was to determine the differences of fibronectin and TGF-β1 expression in both antemortem and postmortem wounds. This study was an experimental with completely randomized design.  The skin wounds (vital and postmortem) were taken from fourty Wistar rats and divided into 10 groups of rats. Immunohistochemical staining was performed to determine the differences between antemortem and postmortem wounds. The result showed that in 30 minutes after antemortem wound infliction, all of samples showed weak reactivity for fibronectin and TGF-β1 (100%).  In first hour after wound infliction, 3 samples (75%) showed weakly positive and 1 sample (25%) strongly positive for fibronectin and TGF-β1.  In 2 hour after wound infliction, 1 sample (25%) showed weakly positive and 3 sample (75%) strongly positive for fibronectin and TGF-β1.  In 3 and 4 hour after wound infliction, all of samples strongly positive for fibronectin and TGF-β1.  In postmortem wound, all of samples showed negativity for fibronectin and TGF-β1. In conclusion, fibronectin and TGF-β1 may be useful in the determination of wound vitality. Keywords: wound, fibronectin, TGF-β1, vitality

An Epistemological Criticism of Social Entrepreneurship: Is Social Entrepreneurship a Sound Scientific Field of Research

2018 ◽  
Author(s):  
Amir Forouharfar
Keyword(s):  
Social Entrepreneurship ◽  
Social Constructivism ◽  
Social Epistemology ◽  
American English ◽  
Meta Analysis ◽  
Research Question ◽  
Knowledge Structure ◽  
Scientific Field ◽  
The Other ◽  
First Time

The paper was shaped around the pivotal question: Is SE a sound and scientific field of research? The question has given a critical tone to the paper and has also helped to bring out some of the controversial debates in the realm of SE. The paper was organized under five main discussions to be able to provide a scientific answer to the research question: (1)<b> </b>is “social entrepreneurship” an oxymoron?, (2) the characteristics of SE knowledge, (3) sources of social entrepreneurship knowledge, (4) SE knowledge: structure and limitations and (5) contributing epistemology-making concepts for SE.<b> </b>Based on the sections,<b> </b>the study relied on the relevant philosophical schools of thought in <i>Epistemology </i>(e.g. <i>Empiricism</i>, <i>Rationalism</i>, <i>Skepticism</i>, <i>Internalism</i> vs. <i>Externalism</i>,<i> Essentialism, Social Constructivism</i>, <i>Social Epistemology, etc.</i>) to discuss these controversies around SE and proposes some solutions by reviewing SE literature. Also, to determine the governing linguistic discourse in the realm of SE, which was necessary for our discussion,<i> Corpus of Contemporary American English (COCA)</i> for the first time in SE studies was used. Further, through the study, SE buzzwords which constitute SE terminology were derived and introduced to help us narrowing down and converging the thoughts in this field and demarking the epistemological boundaries of SE. The originality of the paper on one hand lies in its pioneering discussions on SE epistemology and on the other hand in paving the way for a construction of sound epistemology for SE; therefore in many cases after preparing the philosophical ground for the discussions, it went beyond the prevalent SE literature through meta-analysis to discuss the cases which were raised. The results of the study verified previously claimed embryonic pre-paradigmatic phase in SE which was far from a sound and scientific knowledge, although the scholarly endeavors are the harbingers of such a possibility in the future which calls for further mature academic discussion and development of SE knowledge by the SE academia.

Where Are The Self-Correcting Mechanisms In Science?

2020 ◽  
Author(s):  
Simine Vazire ◽  
Alex O. Holcombe
Keyword(s):  
Peer Review ◽  
Critical Appraisal ◽  
Scientific Field ◽  
The Self ◽  
Replication Crisis

It is often said that science is self-correcting, but the replication crisis suggests that, at least in some fields, self-correction mechanisms have fallen short of what we might hope for. How can we know whether a particular scientific field has effective self-correction mechanisms, that is, whether its findings are credible? The usual processes that supposedly provide mechanisms for scientific self-correction – mainly peer review and disciplinary committees – have been inadequate. We argue for more verifiable indicators of a field’s commitment to self-correction. These include transparency, which is already a target of many reform efforts, and critical appraisal, which has received less attention. Only by obtaining Measurements of Observable Self-Correction (MOSCs) can we begin to evaluate the claim that “science is self-correcting.” We expect the validity of this claim to vary across fields and subfields, and suggest that some fields, such as psychology and biomedicine, fall far short of an appropriate level of transparency and, especially, critical appraisal. Fields without robust, verifiable mechanisms for transparency and critical appraisal cannot reasonably be said to be self-correcting, and thus do not warrant the credibility often imputed to science as a whole.

Monetary Policy and Data Uncertainty

2005 ◽  
Author(s):  
Jarkko P. P. Jääskelä ◽  
Anthony Yates
Keyword(s):  
Monetary Policy ◽  
Data Uncertainty

scholarly journals Post-Islamism and Intellectual Production: A Bibliometric Analysis of the Evolution of Contemporary Islamic Thought

Religions ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 49
Author(s):  
Mohamed Amine Brahimi ◽  
Houssem Ben Lazreg
Keyword(s):  
Social Sciences ◽  
Social Dynamics ◽  
Scientific Field ◽  
Social Sciences And Humanities ◽  
Islamic Reform ◽  
The Social ◽  
Islamic Thought ◽  
Thinking Differently ◽  
Intellectual Production ◽  
Representative Samples

The advent of the 1990s marked, among other things, the restructuring of the Muslim world in its relation to Islam. This new context has proved to be extremely favorable to the emergence of scholars who define themselves as reformists or modernists. They have dedicated themselves to reform in Islam based on the values of peace, human rights, and secular governance. One can find an example of this approach in the works of renowned intellectuals such as Farid Esack, Mohamed Talbi, or Mohamed Arkoun, to name a few. However, the question of Islamic reform has been debated during the 19th and 20th centuries. This article aims to comprehend the historical evolution of contemporary reformist thinkers in the scientific field. The literature surrounding these intellectuals is based primarily on content analysis. These approaches share a type of reading that focuses on the interaction and codetermination of religious interpretations rather than on the relationships and social dynamics that constitute them. Despite these contributions, it seems vital to question this contemporary thinking differently: what influence does the context of post-Islamism have on the emergence of this intellectual trend? What connections does it have with the social sciences and humanities? How did it evolve historically? In this context, the researchers will analyze co-citations in representative samples to illustrate the theoretical framework in which these intellectuals are located, and its evolution. Using selected cases, this process will help us to both underline the empowerment of contemporary Islamic thought and the formation of a real corpus of works seeking to reform Islam.

Assessment of Machine Learning-Based Audiovisual Quality Predictors

2021 ◽  
Vol 17 (2) ◽  
pp. 1-22
Author(s):  
Mythili K. ◽  
Manish Narwaria
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Quality Assessment ◽  
Computational Models ◽  
Model Development ◽  
Multimedia Communication ◽  
Current Approach ◽  
Learning Ability ◽  
Data Uncertainty ◽  
Attractive Alternative

Quality assessment of audiovisual (AV) signals is important from the perspective of system design, optimization, and management of a modern multimedia communication system. However, automatic prediction of AV quality via the use of computational models remains challenging. In this context, machine learning (ML) appears to be an attractive alternative to the traditional approaches. This is especially when such assessment needs to be made in no-reference (i.e., the original signal is unavailable) fashion. While development of ML-based quality predictors is desirable, we argue that proper assessment and validation of such predictors is also crucial before they can be deployed in practice. To this end, we raise some fundamental questions about the current approach of ML-based model development for AV quality assessment and signal processing for multimedia communication in general. We also identify specific limitations associated with the current validation strategy which have implications on analysis and comparison of ML-based quality predictors. These include a lack of consideration of: (a) data uncertainty, (b) domain knowledge, (c) explicit learning ability of the trained model, and (d) interpretability of the resultant model. Therefore, the primary goal of this article is to shed some light into mentioned factors. Our analysis and proposed recommendations are of particular importance in the light of significant interests in ML methods for multimedia signal processing (specifically in cases where human-labeled data is used), and a lack of discussion of mentioned issues in existing literature.

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