Prediction of First-Order Vessel Responses with Applications to Decision Support Systems

2015 ◽  
Author(s):  
Ulrik D. Nielsen ◽  
Toshio Iseki
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Simple Approach ◽  
Full Scale ◽  
Uncertainty Measure ◽  
First Order ◽  
Future Developments ◽  
Vessel Response ◽  
Scale Data

The paper presents a practical and simple approach for making vessel response predictions. Features of the procedure include a) predictions which are scaled so to better agree with corresponding true, future values to be measured at the time the predictions apply at; and b) predictions that are assigned an uncertainty measure to reflect a level of confidence. The approach is tested with full-scale data and the obtained results/predictions agree well with measured values. Potentially, the procedure is therefore very useful in future developments of general decision support systems.

Decision Support Systems For Forest Management In Mexico

2011 ◽  
pp. 74-100 ◽  
Author(s):  
Rafael Moreno-Sánchez ◽  
Juan Manuel Torres-Rojo
Keyword(s):  
Developing Countries ◽  
Decision Support ◽  
Forest Management ◽  
Decision Support Systems ◽  
Support Systems ◽  
State Of The Art ◽  
Future Developments ◽  
Current State ◽  
Forestry Sector ◽  
The World

In the last 25 years there have been several efforts to create Decision Support Systems (DSS) for management of the forests in Mexico. Few references exists that document these experiences and that can assist in understanding their genesis, evolution, successes, shortcomings, or failures, as well as the factors that have led to these outcomes. This chapter fills this gap by presenting an overview of the DSS that have been created since the mid 1980’s. The characteristics of the Mexican forest ecosystems and the complex web of interactions and co-evolution of the contexts that frame the forestry activities in Mexico have influenced the characteristics, evolution, and current state of the art of the DSS for the management of the forest in the country. Similar characteristics and contexts are commonly found in developing countries around the world. Hence, the experiences, lessons, and recommendations for future developments presented in this chapter can be of value beyond the specific conditions of the Mexican forestry sector.

Assigning Value to Clinical Information – A Major Limiting Factor in the Implementation of Decision-Support Systems

1996 ◽  
Vol 35 (01) ◽  
pp. 1-4 ◽  
Author(s):  
F. T. de Dombal
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Clinical Information ◽  
Limiting Factor ◽  
Major Difficulty ◽  
Computer Aided ◽  
Computer Aided Decision

AbstractThis paper deals with a major difficulty and potential limiting factor in present-day decision support - that of assigning precise value to an item (or group of items) of clinical information. Historical determinist descriptive thinking has been challenged by current concepts of uncertainty and probability, but neither view is adequate. Four equations are proposed outlining factors which affect the value of clinical information, which explain some previously puzzling observations concerning decision support. It is suggested that without accommodation of these concepts, computer-aided decision support cannot progress further, but if they can be accommodated in future programs, the implications may be profound.

Architectures for Architects

1993 ◽  
Vol 32 (01) ◽  
pp. 12-13 ◽  
Author(s):  
M. A. Musen
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Design And Development

Abstract:Response to Heathfield HA, Wyatt J. Philosophies for the design and development of clinical decision-support systems. Meth Inform Med 1993; 32: 1-8.

Characterizing Decision Support Telemedicine Systems

2006 ◽  
Vol 45 (05) ◽  
pp. 523-527 ◽  
Author(s):  
A. Abu-Hanna ◽  
B. Nannings
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Literature Search ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Problem Dimension ◽  
Process Dimension

Summary Objectives: Decision Support Telemedicine Systems (DSTS) are at the intersection of two disciplines: telemedicine and clinical decision support systems (CDSS). The objective of this paper is to provide a set of characterizing properties for DSTSs. This characterizing property set (CPS) can be used for typing, classifying and clustering DSTSs. Methods: We performed a systematic keyword-based literature search to identify candidate-characterizing properties. We selected a subset of candidates and refined them by assessing their potential in order to obtain the CPS. Results: The CPS consists of 14 properties, which can be used for the uniform description and typing of applications of DSTSs. The properties are grouped in three categories that we refer to as the problem dimension, process dimension, and system dimension. We provide CPS instantiations for three prototypical applications. Conclusions: The CPS includes important properties for typing DSTSs, focusing on aspects of communication for the telemedicine part and on aspects of decisionmaking for the CDSS part. The CPS provides users with tools for uniformly describing DSTSs.

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