Modeling diagnostic

B. (1995). Monitoring seasonal and interannual variations of gross primary productivity, net primary productivity and net ecosystem productivity using a diagnostic model and remotely-sensed data, Tellus, Ser. B, 47,178-190. 

One of the most innovating contributions of the diagnostic model proposed in these guidelines is that it combines idiographic elements within a standardized multiaxial system, in contrast to the conventional, reductionist opinions that favor only one of these elements. 

The idiographic component of this diagnostic model includes three elements (a) the perspectives of the clinician (b) the perspectives of the patients and their families and (c) the integration of the clinician s perspectives with those of the patient and their family. 

As pointed out earlier, the IGDA utilizes the CIE-10 for the first three axes of its multiaxial formulation. This diagnostic model is structured as follows ... 

M. Ulieru and R. Isermann. Design of a fuzzy-logic based diagnostic model for technical processes. Fuzzy Sets and Systems, 58 249-271, 1993. 

Krasuski JS, Janicak PG. Mixed states current and alternate diagnostic models. Psychiatr Ann 1994 24 7. 

Fortunately, there are already some general practitioners and doctors who take MCS patients very seriously and cooperate in trying to improve their situation, but the majority of medical doctors have not been trained in environmental illnesses and often do not understand MCS very well. When visiting specialists within the mainstream medical establishment, many MCS patients are met with disbelief or the judgment that it s all in your head, since these specialists cannot find a clear explanation for their symptoms using conventional diagnostic models. 

The general property of diagnostic modeling of sea currents consists of the strong dependence of the current field calculated on the water density field used. The differences in the results of different calculation methods (hydro-dynamic models) with the same initial conditions (three-dimensional density fields) are usually observed only in details of the current patterns obtained. 

In contrast to diagnostic modeling, which is aimed at the construction of reliable current fields from the specified density fields, the principal goal of the so-called prognostic modeling lies in the understanding of the mechanisms of formation of the circulation in seas and oceans and their possible reproduction in numerical models. Only if thickness problem is resolved, one can speak about the hydrodynamic current forecasting. 

Koliopoulos, T.C. and Koliopoulou, G. 2007f. A diagnostic model for MSW landfill s operation and the protection of ecosystems with a spatial multiple criteria analysis-Zakynthos Island Greece. In Wessex Institute of Technology Transactions on Ecosystems and Sustainable Development, E. Tiezzi, J.C. Marques, and C.A. Brebbia (eds), pp. 449-62. Jorgensen S.E., UK WIT Press. 

The study was performed employing GC-MS, using bis-trimethylsilyl-trifluor-oacetamide (BSTFA) as derivatization agent during sample preparation. The aim of the study was to compare the metabolic profiles of urine samples from patients with liver cancer (n = 20) and healthy volunteers (n = 20) and, subsequently, to develop a diagnostic model that would include selected metabolites of potential diagnostic significance in HCC [21]. 

As a result of GC-MS analyses, 103 metabolites were determined, of which 66 were successfully identified and 18 were used to create a diagnostic model. Of these 18 metabolites, 5 (suberic acid, glycine, L-tyrosine, L-threonine, and succinic acid) had significantly higher levels in patients with HCC than in healthy volunteers (p < 0.05). Other metabolites (oxalic acid, xylitol, urea, phosphates, propanoic acid, threonine, pimelic acid, butyric acid, trihydroxypentanoic acid, hypoxanthine, arabinofuranose, dipeptide of hydroxyproline, and tetrahydroxypentanoic acid) showed higher levels in healthy volunteers (p < 0.05). In addition, Wu et al. determined the levels of AFP using an ELISA test in serum from the same patients and healthy volunteers as in the metabolomic study of urine samples. An AFP concentration above 20 ng/mL suggests a positive result and the presence of... 

Separate ACTMs driven by meteorological input data from meteo-preproces-sors, measurements or diagnostic models... 

Ono et al. (2001) Diagnostic model of annual cycles of O2, DIG and nitrate below the mixed layer is used to investigate organic matter remineralization. 

FIGURE 4.9 Histograms representing the testing and blinded validation results of (A) sensitivity and (B) specificity of the diagnostic models for MS data acquired on either a Qq-TOF or a PBS-II TOF mass spectrometer. 

Combination of elements of the above methods (hybrid methods). For example, the output of a prognostic model can be combined with observed data as an input to a diagnostic model. 

There are a host of high temperature systems which should now be amenable to this combined diagnostic/modeling approach. It should give kineticists an extra weapon with which to approach complex systems. 

Denison, D. R., Hart, S. L., and Kahn, J. A. (1996), From Chimneys to Cross-Functional Teams Developing and Validating a Diagnostic Model, Academy of Management Journal, Vol. 39, pp. 1005-1023. 

Moreover there are a lot of applications of BNs as support system for the maintenance strategies. An example of preventive maintenance is (Celeux et al. 2006) hut the greater part of the papers investigate the BNs as a diagnostic model for the condition based maintenance. 

Lapide L (2(X)5) Sales and operations planning part HI a diagnostic model. J Bus pOTecasting 24 13-16... 

Fig. 4.8 Basic framework of coupling a behavioural model and a diagnostic model...

Essential advantages of this framework are that ARRs in symbolic form are not required. The diagnostic model is numerically computed by calculating derivatives of its inputs in discrete time. The result is the time evolution of ARR residuals. Finally, in the case of slow real processes, off-line simulation using a behavioural model reveals the effects of parametric faults much faster than a real-time computation of ARRs that uses measured output from the real process. 

If parameters are to be estimated in real-time, only present measured values and past values sampled over a time window of finite length stored in an array are available. Nevertheless, they are inputs into the diagnostic model and solving its equations yields values for the ARR residuals. As a diagnostic bond graph model used for... 

Definition A.9 (Diagnostic model) A set of static or dynamic relations which link specific input variables— the symptoms— to specific output variables—the faults. 

Brown, J. S. and Burton, R. R., Diagnostic Models for Procedural Bugs in Basic Mathematical Skills Cognitive Science, Vol. 2, pp. 155-191,1978. 

---