scholarly journals A Vectorial Framework for Ray Traced Diffusion Curves

2014 ◽  
Vol 34 (1) ◽  
pp. 253-264 ◽  
Author(s):  
Romain Prévost ◽  
Wojciech Jarosz ◽  
Olga Sorkine-Hornung
Keyword(s):  
2012 ◽  
pp. 403-411 ◽  
Author(s):  
Charalampos Z. Patrikakis ◽  
Lemonia Argyriou ◽  
Agis Papantoniou

In this chapter, the authors present the general framework for assessing collaborative work group behaviour over the Internet and their social or asocial behaviour based on previous studies. Following this approach, the authors first give reference to a related study on social and asocial learning and how they can be distinguished through the analysis of data diffusion curves and other mathematical models. As a next step, a used method on group collaboration over a digital content publication platform is presented. Finally, the authors state a new direction on collaborative work groups, and the idea of Collaborative Innovation Networks is presented. The paper ends with directions for future research on social networking and human-machine collaboration.


2008 ◽  
Vol 38 (1) ◽  
pp. 201-230 ◽  
Author(s):  
Gabriel Rossman ◽  
Ming Ming Chiu ◽  
Joeri M. Mol
Keyword(s):  

2012 ◽  
Vol 32 (4) ◽  
pp. 68-78 ◽  
Author(s):  
Wai-Man Pang ◽  
Jing Qin ◽  
Michael Cohen ◽  
Pheng-Ann Heng ◽  
Kup-Sze Choi

Author(s):  
Alexandrina Orzan ◽  
Adrien Bousseau ◽  
Holger Winnemöller ◽  
Pascal Barla ◽  
Joëlle Thollot ◽  
...  
Keyword(s):  

2009 ◽  
Vol 28 (5) ◽  
pp. 1-8 ◽  
Author(s):  
Stefan Jeschke ◽  
David Cline ◽  
Peter Wonka
Keyword(s):  

1969 ◽  
Vol 46 (2) ◽  
pp. 237-242 ◽  
Author(s):  
M. Timothy O'Keefe

No support is found here for certain regularity hypotheses, while others may be valid. Doubt is cast on the reliability of diffusion curves. Belief in the report proves to be based strongly on the credibility of the first-report medium.


2006 ◽  
Vol 20 (2) ◽  
pp. 248-259 ◽  
Author(s):  
J. Thomas Yokum ◽  
Juan J. Gonzalez ◽  
Tom Badgett

We are interested in forecasting or predicting the long-term viability of a minor league baseball team. The research question is whether this minor league team will be successful in attracting attendance over an extended period of time. An important financial issue is if the team is predicted to fail, then exactly how long will it last? A variety of methods are used in a step-by-step procedure to evaluate this viability. We first test whether attendance is evolving or stable through a unit root test, a test of market persistence. We then use the Bass model to assess whether the projected product life cycle is turning up or down. The Gompertz and logistic (Pearl) diffusion curves are next applied to home stand data of various lengths in order to make forecasts of an eventual dissolution point at which the team would financially collapse. Market saturation is not estimated, but set at the stadium capacity. Forecasting principles involving diffusion models are implemented. Analogies are used as a complementary forecasting technique to assess whether there is long-term potential for survival. Finally, logistic regression on cross-sectional data is used to supplement the forecasts. The results of the triangulation of diffusion curves, analogies, and logistic regression predict a decline in the minor league team’s ability to capture attendance.


2018 ◽  
Vol 4 (2) ◽  
pp. 149-160 ◽  
Author(s):  
Hongwei Lin ◽  
Jingning Zhang ◽  
Chenkai Xu

2011 ◽  
Vol 30 (4) ◽  
pp. 1345-1352 ◽  
Author(s):  
John C. Bowers ◽  
Jonathan Leahey ◽  
Rui Wang
Keyword(s):  

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