Unified measures of target detection system performance evaluation

2006 ◽  
Author(s):  
David R. Parker ◽  
Steven C. Gustafson ◽  
Timothy D. Ross
Keyword(s):  
Performance Evaluation ◽  
Target Detection ◽  
System Performance ◽  
Detection System ◽  
System Performance Evaluation

scholarly journals An Indonesian Hoax News Detection System Using Reader Feedback and Naïve Bayes Algorithm

2020 ◽  
Vol 20 (1) ◽  
pp. 82-94
Author(s):  
Badrus Zaman ◽  
Army Justitia ◽  
Kretawiweka Nuraga Sani ◽  
Endah Purwanti
Keyword(s):  
Performance Evaluation ◽  
System Performance ◽  
Naive Bayes ◽  
Detection System ◽  
Naïve Bayes ◽  
Bayes Algorithm ◽  
F Measure ◽  
System Performance Evaluation

AbstractHoax news in Indonesia spread at an alarming rate. To reduce this, hoax news detection system needs to be created and put into practice. Such a system may use readers’ feedback and Naïve Bayes algorithm, which is used to verify news. Overtime, by using readers’ feedback, database corpus will continue to grow and could improve system performance. The current research aims to reach this. System performance evaluation is carried out under two conditions ‒ with and without sources (URL). The system is able to detect hoax news very well under both conditions. The highest precision, recall and f-measure values when including URL are 0.91, 1, and 0.95 respectively. Meanwhile, the highest value of precision, recall and f-measure without URL are 0.88, 1 and 0.94, respectively.

Extension of the IWA/COST simulation benchmark to include expert reasoning for system performance evaluation

2006 ◽  
Vol 53 (4-5) ◽  
pp. 331-339 ◽  
Author(s):  
J. Comas ◽  
I. Rodríguez-Roda ◽  
M. Poch ◽  
K.V. Gernaey ◽  
C. Rosen ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
System Performance ◽  
Control Strategies ◽  
Point Of View ◽  
Plant Performance ◽  
Flow Diagram ◽  
Biological Origin ◽  
Cost Simulation ◽  
Expert Reasoning ◽  
System Performance Evaluation

In this paper the development of an extension module to the IWA/COST simulation benchmark to include expert reasoning is presented. This module enables the detection of suitable conditions for the development of settling problems of biological origin (filamentous bulking, foaming and rising sludge) when applying activated sludge control strategies to the simulation benchmark. Firstly, a flow diagram is proposed for each settling problem, and secondly, the outcome of its application is shown. Results of the benchmark for two evaluated control strategies illustrate that, once applied to the simulation outputs, this module provides supplementary criteria for plant performance assessment. Therefore, simulated control strategies can be evaluated in a more realistic framework, and results can be recognised as more realistic and satisfactory from the point of view of operators and real facilities.

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