Artificial Swarm Intelligence—A Paradigm Shift in Prediction, Decision-Making and Diagnosis

Author(s):  
V. J. K. Kishor Sonti ◽  
G. Sundari
2001 ◽  
Vol 17 (1) ◽  
pp. 114-122 ◽  
Author(s):  
Steven H. Sheingold

Decision making in health care has become increasingly reliant on information technology, evidence-based processes, and performance measurement. It is therefore a time at which it is of critical importance to make data and analyses more relevant to decision makers. Those who support Bayesian approaches contend that their analyses provide more relevant information for decision making than do classical or “frequentist” methods, and that a paradigm shift to the former is long overdue. While formal Bayesian analyses may eventually play an important role in decision making, there are several obstacles to overcome if these methods are to gain acceptance in an environment dominated by frequentist approaches. Supporters of Bayesian statistics must find more accommodating approaches to making their case, especially in finding ways to make these methods more transparent and accessible. Moreover, they must better understand the decision-making environment they hope to influence. This paper discusses these issues and provides some suggestions for overcoming some of these barriers to greater acceptance.


2015 ◽  
Vol 1 (9) ◽  
Author(s):  
Brian YL Chan ◽  
Joanne EY Chin ◽  
Lalit Kumar Radha Krishna

2003 ◽  
Vol 1 (2) ◽  
pp. 199-215 ◽  
Author(s):  
Martin Kelly ◽  
Graham Oliver

Author(s):  
Gonçalo Sousa ◽  
José Carlos Sá ◽  
Gilberto Santos ◽  
Francisco J. G. Silva ◽  
Luís Pinto Ferreira

The main objective of the study is to minimize interdepartmental communication, potentiation of fast and efficient decision making, and computerization of data. Using software such as MS Excel® and MS Power BI®, a Power BI® tool was conceived to be capable of incorporating, for the entire company, the dashboards that collect the main KPIs of each department. After the tool was implemented, the company's paradigm shift was noticeable. Quickly, the weekly meeting of the planning team began to take place using the MS Power BI® dashboard. In this way, processes were automated and the important data for the normal functioning of the company became accessible to all departments, thus minimizing interdepartmental communication. The chapter shows an Obeya Digital that was implemented in a company in which all the performance indicators of each department are incorporated. In this way, information becomes accessible to all employees and manual data update processes are minimized.


Author(s):  
David M Moore

This chapter discusses the nature of professionalism generally and then in the contextual setting of defence acquisition. Changing socio-political and economic pressures have resulted in a paradigm shift in the way that the public sector based business of defence acquisition is undertaken. There is policy movement towards greater commercialism but the rhetoric has not necessarily led to improvement in performance. Indeed, criticism of acquisition performance has been constant for some time. With improved professionalism, and the legitimisation of the professional prerogative and practice of personnel within the acquisition community, a move away from reliance upon process led decision making, could result in enhanced acquisition performance. This requires the development of relevant knowledge, in a suitable format, such that acquisition professionalism can enable an ‘Intelligent Customer' perspective. It recognises the need for education and training, balanced with relevant experience as the basis of professional knowledge and the concept of an ‘Intelligent Customer'.


2019 ◽  
Vol 11 ◽  
pp. 184797901882504 ◽  
Author(s):  
Guido JL Micheli ◽  
Paolo Trucco ◽  
Yasmine Sabri ◽  
Mauro Mancini

This literature-grounded research contributes to a deeper understanding of modularization as a system life cycle management strategy, by providing a comprehensive view of its key barriers, drivers, possible mechanisms of implementation and impact. This comprehensive view, arranged into a decision-making–driven ontology, enables a decision maker to systematically identify modularization implementation opportunities in different industrial and service domains. The proposed ontology transforms modularization into a fully operationalizable strategy and contributes to a paradigm shift in the understanding of modularization, from a pure design option (i.e. modularity) to a fully strategic choice that, by nature, impacts on many of the system’s life cycle phases and involves a number of stakeholders.


2019 ◽  
Vol 127 (12) ◽  
pp. 125002 ◽  
Author(s):  
Gary L. Ginsberg ◽  
Kristi Pullen Fedinick ◽  
Gina M. Solomon ◽  
Kevin C. Elliott ◽  
John J. Vandenberg ◽  
...  

2019 ◽  
Vol 36 (06) ◽  
pp. 1940012
Author(s):  
Joost Berkhout ◽  
Bernd Heidergott ◽  
Henry Lam ◽  
Yijie Peng

In the past decades we have witnessed a paradigm-shift from scarcity of data to abundance of data. Big data and data analytics have fundamentally reshaped many areas including operations research. In this paper, we discuss how to integrate data with the model-based analysis in a controlled way. Specifically, we consider techniques to quantify input uncertainty and the decision making under input uncertainty. Numerical experiments demonstrate that different ways in decision making may lead to significantly different outcomes in a maintenance problem.


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