scholarly journals Building Interactive Communication Tools to Support Interdisciplinary Responsible Innovation

2016 ◽  
Vol 3 (4) ◽  
pp. 119-133 ◽  
Author(s):  
Steven Flipse ◽  
Joric Oude Vrielink ◽  
Maarten Van der Sanden
Keyword(s):  
Decision Support Tool ◽  
Interdisciplinary Teams ◽  
Responsible Innovation ◽  
Interactive Communication ◽  
Support Tool ◽  
Societal Challenges ◽  
Development Teams ◽  
Societal Actors ◽  
Innovation Project ◽  
Scientific Context

Recent science policy encourages the installation of Responsible Research & Innovation (RRI) practices, which should help solve grand societal challenges and be more readily adopted by society. RRI may be implemented by setting up interdisciplinary innovation development teams, bringing together technical and non-technical experts from various disciplines and backgrounds, enabling engineers to let their work become inspired by – or even partly co-shaped by – societal insights and viewpoints, while societal actors get acquainted with techno-scientific context. We developed a Decision Support Tool to support interdisciplinary innovation teams, that visualizes innovation project performance and success chances. It supports communication and collaboration in interdisciplinary teams by proposing practical improvement areas, based on shared expertise, including socio-ethical, societal, economic and management related aspects. Still, further investigation is needed to learn how such a tool can be used to systematically integrate RRI in practice, to harness its full innovative potential.

A protocol for sampling pastures in hill country

2016 ◽  
Vol 78 ◽  
pp. 203-209 ◽  
Author(s):  
K.J. Hutchinson ◽  
D.R. Scobie ◽  
J. Beautrais ◽  
A.D. Mackay ◽  
G.M. Rennie ◽  
...  
Keyword(s):  
Random Sampling ◽  
Geographical Information Systems ◽  
Field Measurements ◽  
Decision Support Tool ◽  
Accurate Estimate ◽  
Ease Of Use ◽  
Geographical Information ◽  
Support Tool ◽  
Topographic Complexity ◽  
Hill Country

To develop a protocol to guide pasture sampling for estimation of paddock pasture mass in hill country, a range of pasture sampling strategies, including random sampling, transects and stratification based on slope and aspect, were evaluated using simulations in a Geographical Information Systems computer environment. The accuracy and efficiency of each strategy was tested by sampling data obtained from intensive field measurements across several farms, regions and seasons. The number of measurements required to obtain an accurate estimate was related to the overall pasture mass and the topographic complexity of a paddock, with more variable paddocks requiring more samples. Random sampling from average slopes provided the best balance between simplicity and reliability. A draft protocol was developed from the simulations, in the form of a decision support tool, where visual determination of the topographic complexity of the paddock, along with the required accuracy, were used to guide the number of measurements recommended. The protocol was field tested and evaluated by groups of users for efficacy and ease of use. This sampling protocol will offer farmers, consultants and researchers an efficient, reliable and simple way to determine pasture mass in New Zealand hill country settings. Keywords: hill country, feed budgeting, protocol pasture mass, slope

Neural Network Ensemble Approach to Pushed Convoys Dispatching Problems

2020 ◽  
Vol 27 (1) ◽  
pp. 70-82 ◽  
Author(s):  
Aleksandar Radonjić ◽  
Danijela Pjevčević ◽  
Vladislav Maraš
Keyword(s):  
Neural Network ◽  
Decision Support Tool ◽  
Primary Objective ◽  
Danube River ◽  
Decision Making Process ◽  
Neural Network Ensemble ◽  
Support Tool ◽  
Shipping Company ◽  
The Republic ◽  
Power Measurements

AbstractThis paper investigates the use of neural networks (NNs) for the problem of assigning push boats to barge convoys in inland waterway transportation (IWT). Push boat–barge convoy assignmentsare part of the daily decision-making process done by dispatchers in IWT companiesforwhich a decision support tool does not exist. The aim of this paper is to develop a Neural Network Ensemble (NNE) model that will be able to assist in push boat–barge convoy assignments based on the push boat power.The primary objective of this paper is to derive an NNE model for calculation of push boat Shaft Powers (SHPs) by using less than 100% of the experimental data available. The NNE model is applied to a real-world case of more than one shipping company from the Republic of Serbia, which is encountered on the Danube River. The solution obtained from the NNE model is compared toreal-world full-scale speed/power measurements carried out on Serbian push boats, as well as with the results obtained from the previous NNE model. It is found that the model is highly accurate, with scope for further improvements.

A Decision Support Tool for Evaluating Big Data Investment in Transport: Empirical evidence from European use cases of NOESIS project

2020 ◽  
Author(s):  
Christos Katrakazas ◽  
Natalia Sobrino ◽  
Ilias Trochidis ◽  
Jose Manuel Vassallo ◽  
Stratos Arampatzis ◽  
...  
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Empirical Evidence ◽  
Decision Support Tool ◽  
Use Cases ◽  
Support Tool
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