scholarly journals A Model for Performance Evaluation

Author(s):  
Amir Antonie ◽  
Andrew Mathus

As a result of the parallel element setting, performance assessment and model construction are constrained. Component functions should be observable without direct connections to programming language, for example. As a result of this, solutions that are constituted interactively at program execution necessitate recyclable performance-monitoring interactions. As a result of these restrictions, a quasi, coarse-grained Performance Evaluation (PE) approach is described in this paper. A performance framework for the application system can be polymerized from these data. To validate the evaluation and model construction techniques included in the validation framework, simplistic elements with well-known optimization models are employed.

Synthese ◽  
2021 ◽  
Author(s):  
Matti Sarkia

AbstractThis paper analyzes three contrasting strategies for modeling intentional agency in contemporary analytic philosophy of mind and action, and draws parallels between them and similar strategies of scientific model-construction. Gricean modeling involves identifying primitive building blocks of intentional agency, and building up from such building blocks to prototypically agential behaviors. Analogical modeling is based on picking out an exemplary type of intentional agency, which is used as a model for other agential types. Theoretical modeling involves reasoning about intentional agency in terms of some domain-general framework of lawlike regularities, which involves no detailed reference to particular building blocks or exemplars of intentional agency (although it may involve coarse-grained or heuristic reference to some of them). Given the contrasting procedural approaches that they employ and the different types of knowledge that they embody, the three strategies are argued to provide mutually complementary perspectives on intentional agency.


2014 ◽  
Author(s):  
C. Shannon ◽  
K. Radecker ◽  
M.W. Waite ◽  
J. Munoz ◽  
O. Leon ◽  
...  

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
J. A. Tsanakas ◽  
P. N. Botsaris

Today, to ensure efficient operation of a photovoltaic (PV) system renders as an undoubtedly major concern. Toward this direction, scope of this work is the assessment of infrared thermography as a PV module’s condition monitoring and, subsequently, performance evaluation method. The idea is based on the fact that any abnormality to the temperature pattern of an under inspection equipment implies a dysfunction case. In particular, specific thermographic measurements were applied to a PV module with known, abnormally low performance. Following the basic processing of the acquired thermal images, the extracted temperature data were contrasted with the PV module’s expected operating temperature. The results validated the presence of a problematic solar cell that refers to a “hot spot” within the tested PV module. This paper concludes with a discussion regarding the advantages, the limitations, and, ultimately, the potentiality of the intended approaches as reliable condition monitoring method through performance evaluation of PV modules.


2021 ◽  
Vol 41 (13) ◽  
pp. 65-99
Author(s):  
Desirée H van Dun ◽  
Celeste P.M. Wilderom

PurposeWhy are some lean workfloor teams able to improve their already high performance, over time, and others not? By studying teams' and leaders' behaviour-value patterns, this abductive field study uncovers a dynamic capability at the team level.Design/methodology/approachVarious methods were employed over three consecutive years to thoroughly examine five initially high-performing lean workfloor teams, including their leaders. These methods encompassed micro-behavioural coding of 59 h of film footage, surveys, individual and group interviews, participant observation and archival data, involving objective and perceptual team-performance indicators. Two of the five teams continued to improve and perform highly.FindingsContinuously improving high lean team performance is found to be associated with (1) team behaviours such as frequent performance monitoring, information sharing, peer support and process improvement; (2) team leaders who balance, over time, task- and relations-oriented behaviours; (3) higher-level leaders who keep offering the team face-to-face support, strategic clarity and tangible resources; (4) these three actors' endorsement of self-transcendence and openness-to-change work values and alignment, over time, with their behaviours; and (5) coactive vicarious learning-by-doing as a “stable collective activity pattern” among team, team leader, and higher-level leadership.Originality/valueSince lean has been undertheorised, the authors invoked insights from organisational behaviour and management theories, in combination with various fine- and coarse-grained data, over time. The authors uncovered actors' behaviour-value patterns and a collective learning-by-doing pattern that may explain continuous lean team performance improvement. Four theory-enriching propositions were developed and visualised in a refined model which may already benefit lean practitioners.


Author(s):  
Peter Hartner ◽  
Josef Petek ◽  
Peter Pechtl ◽  
Patrick Hamilton

Accurate on-line plant and equipment performance evaluation is becoming critical in the power generation industry as operators seek to optimize their plants, particularly in competitive power markets. The analysis accuracy of an on-line performance monitoring system is directly dependent on the quality of the input data and usually suffers because installed plant sensors are not high-precision instruments. The inherent measurement uncertainties can be overcome by using a readily available heat balance program in combination with a least square solver. This data reconciliation system will provide the performance evaluation system with data that better reflects the plant’s current operating point, thus improving the performance evaluation system’s output and allowing for better plant optimization. Additionally, the reconciliation system can identify broken, biased or highly noisy sensors. These improvements can be obtained without installing additional precision sensors or putting unreasonable efforts into sensor calibration.


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