A theoretical framework for improving the schedulability of hard and soft real-time tasks on heterogeneous network of workstations (NOWs)

2011 ◽  
Author(s):  
Nitin Auluck
Keyword(s):  
Real Time ◽  
Heterogeneous Network ◽  
Theoretical Framework ◽  
Network Of Workstations

Prospects of Open Source Software for Maximizing the User Expectations in Heterogeneous Network

2021 ◽  
pp. 257-271
Author(s):  
Pushpa Singh ◽  
Rajeev Agrawal
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Real Time ◽  
Open Source Software ◽  
Heterogeneous Networks ◽  
Heterogeneous Network ◽  
Research Work ◽  
Software Tool ◽  
Knn Classifier ◽  
User Expectations

This article focuses on the prospects of open source software and tools for maximizing the user expectations in heterogeneous networks. The open source software Python is used as a software tool in this research work for implementing machine learning technique for the categorization of the types of user in a heterogeneous network (HN). The KNN classifier available in Python defines the type of user category in real time to predict the available users in a particular category for maximizing profit for a business organization.

The Probabilistic Innovation Field of Scientific Enquiry

2017 ◽  
Vol 9 (2) ◽  
pp. 56-72 ◽  
Author(s):  
Chris William Callaghan
Keyword(s):  
Real Time ◽  
Citizen Science ◽  
Theoretical Framework ◽  
Innovation Theory ◽  
Theoretical Frameworks ◽  
Academic Fields

This paper outlines a developing stream of literature related to a theoretical framework, namely probabilistic innovation, relating it to certain literature critiquing developing academic fields and offering criteria against which a developing field can be held to be scientific or not. With ontological and epistemological roots in citizen science, participant-research and other emerging academic movements, probabilistic innovation theory is underpinned by a shift toward the democratisation of knowledge, increasing inclusivity and transparency in its processes, and a novel methodology drawing from methods such as expert crowdsourcing, crowdfunding, swarm solving and maximisation of efficiencies related to collaborations in research. With the enablement of real time research capability, or ability to solve serious scientific problems in hours and days instead of years and decades as its primary raison d'être, probabilistic innovation seeks to maximise probability of scientific breakthroughs. However, for this stream of literature to develop, it is important to proactively identify academic or scientific pitfalls facing developing areas of enquiry, and this paper attempts to offer this, deriving propositions potentially useful for developing fields in general. It is hoped real time research capability will one day become a reality, and to increase the likelihood of this, theoretical frameworks seeking this end need to face useful critique to ensure their robust development, and this paper proposed four core tensions such fields need to manage in order to successfully evolve.

scholarly journals The probabilistic innovation theoretical framework

2017 ◽  
Vol 20 (1) ◽  
Author(s):  
Chris W. Callaghan
Keyword(s):  
Knowledge Management ◽  
Problem Solving ◽  
Real Time ◽  
Theory Development ◽  
Research Problem ◽  
Theoretical Framework ◽  
Management Theory ◽  
Effective Theory ◽  
Knowledge Management Theory ◽  
Knowledge Problem

Background: Despite technological advances that offer new opportunities for solving societal problems in real time, knowledge management theory development has largely not kept pace with these developments. This article seeks to offer useful insights into how more effective theory development in this area could be enabled.Aim: This article suggests different streams of literature for inclusion into a theoretical framework for an emerging stream of research, termed ‘probabilistic innovation’, which seeks to develop a system of real-time research capability. The objective of this research is therefore to provide a synthesis of a range of diverse literatures, and to provide useful insights into how research enabled by crowdsourced research and development can potentially be used to address serious knowledge problems in real time.Setting: This research suggests that knowledge management theory can provide an anchor for a new stream of research contributing to the development of real-time knowledge problem solving.Methods: This conceptual article seeks to re-conceptualise the problem of real-time research and locate this knowledge problem in relation to a host of rapidly developing streams of literature. In doing so, a novel perspective of societal problem-solving is enabled.Results: An analysis of theory and literature suggests that certain rapidly developing streams of literature might more effectively contribute to societally important real-time research problem solving if these steams are united under a theoretical framework with this goal as its explicit focus.Conclusion: Although the goal of real-time research is as yet not attainable, research that contributes to its attainment may ultimately make an important contribution to society.

The Impact of Location-Aware Systems in Hospitals

2011 ◽  
Vol 3 (2) ◽  
pp. 1-12 ◽  
Author(s):  
Lorraine S. Lee ◽  
Kirk D. Fiedler
Keyword(s):  
Information Systems ◽  
Real Time ◽  
Qualitative Interview ◽  
Theoretical Framework ◽  
Core Model ◽  
Operational Effectiveness ◽  
Information Transparency ◽  
Location Aware ◽  
The Impact

This paper focuses on the impact of information systems providing real-time or near real-time knowledge of location, described as location-aware systems. The study utilizes a qualitative, interview-based approach to guide our understanding of the benefits associated with the increased information transparency made available with location-aware information systems. The goal of this study is to examine the benefits of location-aware information systems on managing mobile assets in the hospital context. The Swanson’s tri-core model of innovation is used as the theoretical framework. The tri-core model provides a framework for understanding the role innovations play in administrative, technical and operational effectiveness. This distinction is important for the regulatory intensive environment of hospitals.

The Probabilistic Innovation Field of Scientific Enquiry

Crowdsourcing ◽  
2019 ◽  
pp. 1660-1677
Author(s):  
Chris William Callaghan
Keyword(s):  
Real Time ◽  
Citizen Science ◽  
Theoretical Framework ◽  
Innovation Theory ◽  
Theoretical Frameworks ◽  
Academic Fields

This paper outlines a developing stream of literature related to a theoretical framework, namely probabilistic innovation, relating it to certain literature critiquing developing academic fields and offering criteria against which a developing field can be held to be scientific or not. With ontological and epistemological roots in citizen science, participant-research and other emerging academic movements, probabilistic innovation theory is underpinned by a shift toward the democratisation of knowledge, increasing inclusivity and transparency in its processes, and a novel methodology drawing from methods such as expert crowdsourcing, crowdfunding, swarm solving and maximisation of efficiencies related to collaborations in research. With the enablement of real time research capability, or ability to solve serious scientific problems in hours and days instead of years and decades as its primary raison d'être, probabilistic innovation seeks to maximise probability of scientific breakthroughs. However, for this stream of literature to develop, it is important to proactively identify academic or scientific pitfalls facing developing areas of enquiry, and this paper attempts to offer this, deriving propositions potentially useful for developing fields in general. It is hoped real time research capability will one day become a reality, and to increase the likelihood of this, theoretical frameworks seeking this end need to face useful critique to ensure their robust development, and this paper proposed four core tensions such fields need to manage in order to successfully evolve.

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