Appendix B: Development of System Performance Indices

2014 ◽  
pp. 203-204
Keyword(s):  
System Performance ◽  
Performance Indices

Performance indices for water network partitioning and sectorization

2014 ◽  
Vol 15 (3) ◽  
pp. 499-509 ◽  
Author(s):  
A. Di Nardo ◽  
M. Di Natale ◽  
G. F. Santonastaso ◽  
V. G. Tzatchkov ◽  
V. H. Alcocer-Yamanaka
Keyword(s):  
System Performance ◽  
Pressure Variation ◽  
Fire Fighting ◽  
Water Supply Systems ◽  
Network Resilience ◽  
Network Partitioning ◽  
Performance Indices ◽  
Water Network ◽  
Water Age ◽  
Water Network Partitioning

Water network partitioning in district metering areas, or sectorization, is an important process for improving water network management. It can help water utilities to implement active leakage control, conduct pressure management, and prevent network contamination. It is generally achieved by closing some network pipes, thus reducing pipe redundancy and affecting system performance. No systematic set of performance indices has been defined to evaluate a sectorization design and thus allow for a comparison of different possible sectorizations on a formal basis. In this paper, several performance indices for water network partitioning are proposed and tested using two real water supply systems: Parete in Italy and Matamoros in Mexico. Both systems' sectorizations were previously designed by a novel effective automatic technique recently developed by the authors. For both the original and sectorized networks, the proposed performance indices considered energy dissipated in the network, network resilience, pressure variation, fire-fighting capacity, water age, and mechanical redundancy. Network resilience appears to be the most representative index for the entire network, whereas pressure variation indices are more appropriate for describing individual districts. Except for fire-fighting capacity in one network, system performance did not appear to be affected significantly after sectorization.

scholarly journals Visualizing Non-Linear Control System Performance by Means of Multidimensional Scaling

2013 ◽  
Vol 8 (4) ◽  
Author(s):  
J. A. Tenreiro Machado
Keyword(s):  
Control System ◽  
Multidimensional Scaling ◽  
Performance Measures ◽  
System Performance ◽  
Numerical Experiments ◽  
Closed Loop ◽  
Time Response ◽  
Linear Control ◽  
Performance Indices ◽  
Controller Performance

This paper addresses the use of multidimensional scaling in the evaluation of controller performance. Several nonlinear systems are analyzed based on the closed loop time response under the action of a reference step input signal. Three alternative performance indices, based on the time response, Fourier analysis, and mutual information, are tested. The numerical experiments demonstrate the feasibility of the proposed methodology and motivate its extension for other performance measures and new classes of nonlinearities.

Reliability as a Figure of Merit

2016 ◽  
pp. 231-261
Keyword(s):  
Electric Power ◽  
Design Process ◽  
Power Supply ◽  
System Performance ◽  
Figure Of Merit ◽  
High Efficiency ◽  
Power Converter ◽  
Good Choice ◽  
Performance Indices ◽  
Reliability Based Design

An electric power converter is specified by its system performance indices. Many system performance indices like efficiency are important in design process of system. However, that doesn't mean the converter performance is necessarily adequate for a practical application. At the end of design process of a converter, some desired specifications may not be achieved. In this chapter, reliability as a figure of merit in design of a system is presented and compared with other indices. We want to highlight the effect of reliability considerations on the design methodology of a power converter. The most important specification of a power supply or power converter is its robustness. Because any failure in power supply leads to failure of the whole of the system. A power converter may have poor performance but operate reliably and vice versa. In fact, this is a reliability based design approach to achieve a long useful life. It is shown that in many systems, high efficiency is not a good choice for selection of system operating point. A system can be inefficient but very reliable. Two complex examples are presented to show undesired results of neglecting reliability in design process. Methods for more reliable operation of electric power converters than high performance operation are proposed. A discussion about correct and intelligent optimization of a system parameters and operating set point is presented.

Artificial Intelligence for the Identification of Endometrial Malignancies

2018 ◽  
Vol 7 (2) ◽  
pp. 37-50 ◽  
Author(s):  
Abraham Pouliakis ◽  
Niki Margari ◽  
Effrosyni Karakitsou ◽  
Evangelia Alamanou ◽  
Nikolaos Koureas ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Vector Quantization ◽  
System Performance ◽  
Patient Classification ◽  
Morphometric Characteristics ◽  
Cell Nuclei ◽  
Performance Indices ◽  
And Performance

Aim of this article is to investigate the potential of Artificial Intelligence (AI) in the discrimination between benign and malignant endometrial nuclei and lesions. For this purpose, 416 histologically confirmed liquid-based cytological smears were collected and morphometric characteristics of cell nuclei were measured via image analysis. Then, 50% of the cases were used to train an AI system, specifically a learning vector quantization (LVQ) neural network. As a result, cell nuclei were classified as benign or malignant. Data from the remaining 50% of the cases were used to evaluate the AI system performance. By nucleic classification, an algorithm for the classification of individual patients was constructed, and performance indices on patient classification were calculated. The sensitivity for the classification of nuclei was 77.95%, and the specificity was 73.93%. For the classification of individual patients, the sensitivity was 90.70% and the specificity 82.79%. These results indicate that an AI system can have an important role in endometrial lesions classification.

Artificial Intelligence for the Identification of Endometrial Malignancies

2020 ◽  
pp. 266-279
Author(s):  
Abraham Pouliakis ◽  
Niki Margari ◽  
Effrosyni Karakitsou ◽  
Evangelia Alamanou ◽  
Nikolaos Koureas ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Image Analysis ◽  
Vector Quantization ◽  
System Performance ◽  
Morphometric Characteristics ◽  
Cell Nuclei ◽  
Performance Indices ◽  
And Performance

Aim of this article is to investigate the potential of Artificial Intelligence (AI) in the discrimination between benign and malignant endometrial nuclei and lesions. For this purpose, 416 histologically confirmed liquid-based cytological smears were collected and morphometric characteristics of cell nuclei were measured via image analysis. Then, 50% of the cases were used to train an AI system, specifically a learning vector quantization (LVQ) neural network. As a result, cell nuclei were classified as benign or malignant. Data from the remaining 50% of the cases were used to evaluate the AI system performance. By nucleic classification, an algorithm for the classification of individual patients was constructed, and performance indices on patient classification were calculated. The sensitivity for the classification of nuclei was 77.95%, and the specificity was 73.93%. For the classification of individual patients, the sensitivity was 90.70% and the specificity 82.79%. These results indicate that an AI system can have an important role in endometrial lesions classification.

scholarly journals An uncertainty assessment of reservoir system performance indices under the climate change effect

2020 ◽  
Vol 11 (4) ◽  
pp. 889-904 ◽  
Author(s):  
Avin Hakami-Kermani ◽  
Hossein Babazadeh ◽  
Jahangir Porhemmat ◽  
Mahdi Sarai-Tabrizi
Keyword(s):  
Climate Change ◽  
System Performance ◽  
Uncertainty Assessment ◽  
Performance Indices ◽  
Reservoir System ◽  
Change Effect ◽  
Climate Change Effect
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