Benchmarking and Performance Modelling of Dataflow with Cycles

2021 ◽  
Author(s):  
Sheriffo Ceesay ◽  
Yuhui Lin ◽  
Adam Barker
Author(s):  
CS. Jordan ◽  
E.W. Farmer ◽  
A.J. Belyavin ◽  
S.J. Selcon ◽  
A.J. Bunting ◽  
...  

This paper describes an experiment conducted to validate the Prediction of Operator Performance (POP) model in a flight simulation context. The POP model uses subjective ratings of the demand imposed by single tasks to predict both the demand and performance associated with concurrent tasks. Previous experiments on the POP model have investigated a wide range of experimental tasks including tracking and verbal reasoning. In this experiment eight subjects performed flight control, threat assessment and threat identification tasks singly and in combination. Performance measures and POP scores were collected at the completion of each task condition. The results demonstrated performance decrements in the dual task conditions that were consistent with the predictions. The implications for the POP model are discussed in terms of workload modelling and human performance modelling within the context of the Integrated Performance Modelling Environment (IPME) currently being developed within the Defence Evaluation and Research Agency


IERI Procedia ◽  
2013 ◽  
Vol 4 ◽  
pp. 59-67
Author(s):  
Ayyoub Akbari-Moghanjoughi ◽  
Aduwati Sali ◽  
José Roberto Amazonas ◽  
Burhanuddin Mohd Ali ◽  
Shamala Subramaniam ◽  
...  

2009 ◽  
Vol 43 (3/4) ◽  
pp. 421-437 ◽  
Author(s):  
Manuela Silva ◽  
Luiz Moutinho ◽  
Arnaldo Coelho ◽  
Alzira Marques

PurposeThis paper aims to investigate the impact of market orientation (MO) on performance using a neural network model in order to find new linkages and new explanations for this relationship.Design/methodology/approachThis investigation is based on a survey data collection from a sample of 192 Portuguese companies. A neural network model has been developed to identify the effects of each dimension of MO on each dimension of performance.FindingsRelationship among MO and performance was corroborated but MO's impact is poor and based on its first dimension, market intelligence generation.Research limitations/implicationsFurther research in this field should be conducted using other tools offered by neural network modelling.Practical implicationsManagers should give more attention to cross‐functional co‐ordination in order to improve market intelligence dissemination and responsiveness and, thus, global performance.Originality/valueThe paper presents the development of a neural network model to analyse this relationship.


1993 ◽  
Author(s):  
Chris Harland ◽  
Pascal Novaria ◽  
Mark Robinson

Author(s):  
I. Roumeliotis ◽  
N. Aretakis ◽  
K. Mathioudakis ◽  
E. A. Yfantis

Any prime mover exhibits the effects of wear and tear over time, especially when operating in a hostile environment. Marine gas turbines operation in the hostile marine environment results in the degradation of their performance characteristics. A method for predicting the effects of common compressor degradation mechanisms on the engine operation and performance by exploiting the “zooming” feature of current performance modelling techniques is presented. Specifically a 0D engine performance model is coupled with a higher fidelity compressor model which is based on the “stage stacking” method. In this way the compressor faults can be simulated in a physical meaningful way and the overall engine performance and off design operation of a faulty engine can be predicted. The method is applied to the case of a twin shaft engine, a configuration that is commonly used for marine propulsion. In the case of marine propulsion the operating profile includes a large portion of off-design operation, thus in order to assess the engine’s faults effects, the engine operation should be examined with respect to the marine vessel’s operation. For this reason, the engine performance model is coupled to a marine vessel’s mission model that evaluates the prime mover’s operating conditions. In this way the effect of a faulty engine on vessels’ mission parameters like overall fuel consumption, maximum speed, pollutant emissions and mission duration can be quantified.


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