Model‐based Commissioning, a New Methodological Approach for Commissioning of Nuclear Basic Facilities

Insight ◽  
2021 ◽  
Vol 24 (4) ◽  
pp. 34-37
Author(s):  
Alan Gaignebet ◽  
Vincent Chapurlat ◽  
Grégory Zacharewicz ◽  
Robert Plana ◽  
Victor Richet
2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S810-S810
Author(s):  
Nelson A Roque ◽  
Martin J Sliwinski

Abstract We forward a methodological approach, using model-based cluster analyses, and ambulatory assessments of cognition (2 indicators from each task), to derive subgroups of interest for tailored clinical follow-up in a longitudinal framework. Community dwelling adults were asked to complete 14 consecutive days of ecological momentary assessments (EMAs) using smartphones, including measures of cognitive performance, and self-reported physical and mental health outcomes (e.g., stress, memory complaints, depression, pain). A stable four-cluster solution emerged, labelled as: (1) a high-risk cognitive group (13%; most memory complaints, slowest performing, more memory errors); (2) subjective risk group (42%; highest levels of somatic and cognitive complaints); (3) normative aging (28%; intermediate cognitive performance -- speed/accuracy); (4) super-cognitive agers (17%; fastest speed, best memory). In conclusion, these findings highlight the potential of a cluster-based approach for risk classification, uncovering different profiles of poor performance that may represent different etiologies.


2010 ◽  
pp. 121-131
Author(s):  
G. Boush

The article presents the author's approach to typology of clusters of firms based on the categorical model "Row of informational criteria" (RIC). The sequence of informational criteria reflecting the logic of qualitative characteristics of clusters of firms is developed in the framework of the RIC categorical model. Based on the proposed approach the typology of clusters of firms, identification and primary diagnostics of Omsk agricultural cluster are implemented.


Author(s):  
Teeba Ismail Kh. ◽  
Ibrahim I. Hamarash

<p class="0abstractCxSpFirst">The number of applications incorporating Internet of Things (IoT) concepts increases extraordinarily. This increase cannot continue without high-quality assurance. There are some difficulties in testing IoT applications; the system heterogeneity, test cost and time are taken to test the system, and the precision percentage of test results.</p><p class="0abstractCxSpLast">A well-known and possibly the best solution to overcoming these difficulties is to model the system for evaluation purposes, known as model-based testing (MBT). This paper aims to design a model-based testing approach to assess IoT applications performance quality attributes. The ISO 25000 quality model is used as a standard for software quality assurance applications. IoTMaaS is used as a case study to implement the methodological approach. The possible test cases were generated using the ACTS combinatorial test generation tool. The performance metrics of each test case were monitored until the optimum test case was identified, with the shortest response time and the least amount of resources used. The proposed testing method appears to be successful, according to the results.</p>


2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.


2001 ◽  
Vol 7 (S2) ◽  
pp. 578-579
Author(s):  
David W. Knowles ◽  
Sophie A. Lelièvre ◽  
Carlos Ortiz de Solόrzano ◽  
Stephen J. Lockett ◽  
Mina J. Bissell ◽  
...  

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.


Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery

Author(s):  
Jonathan Jacky ◽  
Margus Veanes ◽  
Colin Campbell ◽  
Wolfram Schulte
Keyword(s):  

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