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Network performance evaluation

Peh KK, Lim CP, Qwek SS, Khoti KH. Use of artificial networks to predict drug dissolution profiles and evaluation of network performance using similarity profile. Pharm Res 2000 17 1386-98. [Pg.701]

Quality assessment is performed by including pooled plasma as an internal control in every run. External quality control is achieved using samples obtained from the European Research Network for evaluation and improvement of screening, Diagnosis and treatment of Inherited disorders of Metabolism (ERNDIM) Special Assays Scheme, run according the scheme schedule. [Pg.96]

Duprat, A. F., Huynh, T. Dreyfus, G. (1998). Toward a principled methodology for neural network design and performance evaluation in QSAR. Application to the prediction of logP. J. Chem. Inf. Comput Sci. 38,586-94. [Pg.150]

PERT (Performance Evaluation and Review Technique) charts primarily show how the different tasks are connected by presenting these as a network of boxes (activities) linked with lines. Due to a lack of a common time scale, start and finish dates have to be added to each individual task box. Complex PERT charts are difficult to survey and are less suitable for presentation purposes of the entire project. However, they are commonly used during the establishment of a project plan and to illustrate dependencies within a selected part of the project, because they expose the logic of a project. [Pg.22]

The performance evaluation results of the interlaboratory comparison exercises performed in the frame of the ALMERA network are not anonymous for those laboratories nominating to participate as ALMERA members. [Pg.209]

A variety of biomarkers have been shown to be valuable individually for one or several toxicant or disease situations. Few of these biomarkers have been systematically evaluated for the plethora of situations that might provoke false positive responses. Acceleration of the current pace of biomarker evaluation and qualification demands (a) the availability of panels of biomarker-assays that can be comparatively evaluated on well-defined common sample sets, (b) fit-for-purpose performance evaluation in controlled animal studies with carefully benchmarked histological endpoints and samples from well-defined focused clinical trial cohorts, and (c) ready availability of banked blood and urine sample archives from clinical trial populations with carefully documented morbidities such as the Framingham Heart Study,45 or the Drug-Induced Liver Injury Network (DILIN) prospective study,46 to name a few. Availability of such panels of validated biomarker assays and well-documented preclinical and clinical samples, as well as increased cooperation between animal model researchers and clinical researchers will enable individual biomarkers to be qualified for sensitivity of specifically defined adverse events, qualified for appropriate specificity using samples of defined benign events, and collected into panels that yield complementary information about the health and safety of animals and patients. [Pg.310]

These studies suggest that studying post-training hidden unit activity is a valuable technique for inferring what a network has learned. Builders of neural networks might do well to consider this technique as standard operating procedure in evaluating their networks performance. [Pg.66]

Robertazzi, T. 1994. Computer networks and systems Queuing theory and performance evaluation. New York Springer-Verlag. [Pg.410]

The decomposition-based approach overviewed in Section 10 was first developed in Ettl et al. (2000) for the purpose of performance evaluation and optimization of a large-scale enterprise supply chain. (Refer to Lee and Billington 1986 for an earlier, related work on modeling supply chains.) A related network model, for semiconductor fabrication, appeared in Connors et al. (1996). Also refer to Buzacott and Shanthikumar (1993) for other network models using decomposition-based approximations. [Pg.1692]

During a task network simulation, the model of the crew may indicate they are required to perform several tasks simultaneously. The task network model evaluates total attentional demands for each human resource (e.g., visual, auditory, psychomotor, and cognitive) by combining the attentional demands across aU tasks that are being performed simultaneously. This combination leads to an overall workload demand score for each crewmember. [Pg.2423]

In this chapter we will consider issues pertaining to parallel performance modeling. We first introduce some network performance characteristics for parallel computers that must be considered when modeling parallel performance. We then present several performance measures for parallel programs, and we discuss how to develop a performance model for a parallel algorithm. Finally, we will discuss how to evaluate performance data and illustrate how reported performance data can be potentially misleading. [Pg.71]

When evaluating parallel network performance, it is important to ascertain whether reported bandwidth data refer to unidirectional or bidirectional bandwidths. Most communication networks provide bidirectional communication channels, which are able to transmit messages in both directions... [Pg.72]

Performance of a supply chain distribution network is evaluated through two dimensions. These are the customer needs and the cost of meeting customer needs. Therefore, a trade-olf, between satisfying customer needs and keeping transportation cost minimum, is made in order to decide which distribution network is better. [Pg.6]

In 2003, Dr. Hasna joined the Department of Electrical Engineering at Qatar University as an assistant professor. Currently, he serves as the vice president and chief academic ofScer of Qatar University. His research interests span the general area of digital communication theory and its application to performance evaluation of wireless communication systems over fading channels. His current specific research interests include cooperative communications, ad hoc networks, cognitive radio, and network coding. [Pg.446]

Network analysis can be used to describe the complicated precedence relationships between the activities of a large project. The resulting description can be used to determine a timetable for the activities and to predict a completion date for the project. Examples of network planning methods (or project planning methods) are the Critical Path Methods (CPM) and Performance Evaluation and Review Technique (PERT) (Chryssolouris 2006). [Pg.1000]

Bouissou, M. Pourret, O. 2003. A Bayesian belief network based method for performance evaluation and troubleshooting of multistate systems. International Journal of Reliability, Quality and Safety Engineering, 10(4) 407- 16. [Pg.67]

Rubino, G. (2005). Sensitivity analysis of network reliability using Monte Carlo. Proc. of the 2005 Winter Simulation Conference200IEEE Infocom 2004 Rubino, G. (1998). Network reliability evaluation (Chapter 11) in State-of-the art in performance modeling and simulation. K. Bagchi and J. Walrand, editors,. Gordon and Breach Books. [Pg.1569]

This work aims to provide a tool to assess service availability, given a service demand level, by introducing a performance evaluation model in presence of random failures for next generation core networks. In particular, we focus on those networks based on the IP Multimedia Subsystem (IMS), proposed by Third Generation Partnership Project, as the unified and standard platform to provide traditional and advanced telecommunication services to subscribers. [Pg.1892]

A communication session can be established between two registered UEs if and only if all signalling nodes are available during call set-up procedure. Since all servers involved in the call set-up session are failure-prone, some reliability methodologies are necessary to evaluate the overall IMS-based system availability, which, in line of principle, should be comparable to the PSTN one for voice services. In addition, IMS nodes have typically different performance levels and several failure and repair modes with various effects on the entire signalling network performance. [Pg.1894]

Indices for the Evaluation of Neural Network Performances as Classifier Application to Structural Elucidation in Infrared Spectroscopy. [Pg.139]

M. L. Meistrell and K. A. Spackman, Proceedings of the 13 th Annual Symposium on Computer Applications in Medical Care, Washington, DC, 1989, pp. 295-301. Evaluation of Neural Network Performance by Receiver Operating Characteristic Analysis Examples from the Biotechnology Domain. [Pg.139]

F.P. Rezha, S.Y. Shin, Performance evaluation of ISAlOO.l 1A industrial wireless network, in Proc. lET International Conference on Information and Communications Technologies (lETICT) 2013, April 27-29, 2013, pp. 587-592. [Pg.144]

Choy et al. (2002) use case-based reasoning and neural networks to evaluate and benchmark potential suppliers. Performance of these evaluation methods depends upon data provided by potential suppliers and availability of historical data. The disadvantage of artificial intelligence-based methods is their lack of generality, and subsequently only basic features are usually used. [Pg.101]

Perform network analysis tasks as appropriate to evaluate the impact on network performance of various configuration options—as part of a proposed system expansion or modification... [Pg.503]

Keywords gas distribution networks, non time-homogeneous systems, performance evaluation, Markov regenerative processes, transient stochastic state classes. [Pg.304]

Courtney, T., Gaonkar, S., Keefe, K., Rozier, E., Sanders, W.H. Mobius 2.3 An extensible tool for dependabiUty, security, and performance evaluation of large and complex system models. In lEEE/lFlP Int. Conf on Dependable Systems and Networks (DSN), pp. 353-358 (2009)... [Pg.315]


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See also in sourсe #XX -- [ Pg.109 ]




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