scholarly journals Analysis and Modeling of Academia's Collaborative Decision Support System Based on Key Performance Indicators and Degree of Certainty

2015 ◽  
Vol 3 ◽  
pp. 4084-4089
Author(s):  
Umer Asgher ◽  
Margarida Romero
Author(s):  
Svetlana E. Vecherskaya

A prototype of an automated decision support system for creative universities has been developed, which will allow assessing the achievements particularly talented students and identifying the needs in the learning process in order to help organize the educational process in accordance with identified capabilities. Use of a decision support system based on the Bayesian classifier is suggested which will allow to evaluate factors contributing to the progress in teaching students particular techniques, and in perspective to assess the possible resources that will be required to make changes to the learning. The list of specific performance indicators is given. The system should contribute to the formation of the learning plan, taking into account the capabilities of both a group art workshop as a whole, and special needs of an individual to develop, if necessary an individual approach.


2022 ◽  
Vol 14 (1) ◽  
pp. 0-0

This article has developed specifications for a new model-driven decision support system (DSS) that aids the key stakeholders of public hospitals in estimating and tracking a set of crucial performance indicators pertaining to the patients flow. The developed specifications have considered several requirements for ensuring an effective system, including tracking the performance indicator on the level of the entire patients flow system, paying attention to the dynamic change of the values of the indicator’s parameters, and considering the heterogeneity of the patients. According to these requirements, the major components of the proposed system, which include a comprehensive object-based queuing model and an object-oriented database, have been specified. In addition to these components, the system comprises the equations that produce the required predictions. From the system output perspective, these predictions act as a foundation for evaluating the performance indicators as well as developing policies for managing the patients flow in the public hospitals.


2012 ◽  
Vol 39 (9) ◽  
pp. 7637-7651 ◽  
Author(s):  
Farzad Shafiei ◽  
David Sundaram ◽  
Selwyn Piramuthu

2011 ◽  
Vol 23 (6) ◽  
pp. 2085-2100 ◽  
Author(s):  
Laura Irina Rusu ◽  
Wenny Rahayu ◽  
Torab Torabi ◽  
Florian Puersch ◽  
William Coronado ◽  
...  

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