Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelation between variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

Prediction of postprandial blood glucose under intra-patient variability and uncertainty and its use in the design of insulin dosing strategies for type 1 diabetic patients

In this thesis I propose a novel method to estimate the dose and injection-to-meal time for low-risk intensive insulin therapy. This dosage-aid system uses an optimization algorithm to determine the insulin dose and injection-to-meal time that minimizes the risk of postprandial hyper- and hypoglycaemia in type 1 diabetic patients. To this end, the algorithm applies a methodology that quantifies the risk of experiencing different grades of hypo- or hyperglycaemia in the postprandial state induced by insulin therapy according to an individual patient’s parameters. This methodology is based on modal interval analysis (MIA). Applying MIA, the postprandial glucose level is predicted with consideration of intra-patient variability and other sources of uncertainty. A worst-case approach is then used to calculate the risk index. In this way, a safer prediction of possible hyper- and hypoglycaemic episodes induced by the insulin therapy tested can be calculated in terms of these uncertainties.

An exploration of the role of narrative skills in higher-level reading comprehension of teenagers with hearing loss

This Study examines the relationship between scores on adolescents’ self-generated narratives and standardized reading-comprehension scores. This relationship is also compared with the more simple language metrics: vocabulary and syntax.

A study of imitation, comprehension, and production

This paper examines the relationship between imitation, comprehension and speech production in language disordered children, and in identifying whether language-disordered children are "language impaired" or "talking impaired."

Reading comprehension and oral reading fluency of deaf children with cochlear implants

This study investigates whether deaf children with cochlear implants have oral reading fluency scores comparable to reading-age matched hearing peers. It also examines the reading comprehension skills of deaf children with cochlear implants.

On the impact of humidity observations in numerical weather prediction

The impact of humidity observations on forecast skill is explored by producing a series of global forecasts using initial data derived from the ERA-40 reanalyses system, in which all humidity data have been removed during the data assimilation. The new forecasts have been compared with the original ERA-40 analyses and forecasts made from them. Both sets of forecasts show virtually identical prediction skill in the extratropics and the tropics. Differences between the forecasts are small and undergo characteristic amplification rate. There are larger differences in temperature and geopotential in the tropics but the differences are small-scale and unstructured and have no noticeable effect on the skill of the wind forecasts. The results highlight the current very limited impact of the humidity observations, used to produce the initial state, on the forecasts.

The predictability of extratropical storm tracks and the sensitivity of their prediction to the observing system

A new method for assessing forecast skill and predictability that involves the identification and tracking of extratropical cyclones has been developed and implemented to obtain detailed information about the prediction of cyclones that cannot be obtained from more conventional analysis methodologies. The cyclones were identified and tracked along the forecast trajectories, and statistics were generated to determine the rate at which the position and intensity of the forecasted storms diverge from the analyzed tracks as a function of forecast lead time. The results show a higher level of skill in predicting the position of extratropical cyclones than the intensity. They also show that there is potential to improve the skill in predicting the position by 1 - 1.5 days and the intensity by 2 - 3 days, via improvements to the forecast model. Further analysis shows that forecasted storms move at a slower speed than analyzed storms on average and that there is a larger error in the predicted amplitudes of intense storms than the weaker storms. The results also show that some storms can be predicted up to 3 days before they are identified as an 850-hPa vorticity center in the analyses. In general, the results show a higher level of skill in the Northern Hemisphere (NH) than the Southern Hemisphere (SH); however, the rapid growth of NH winter storms is not very well predicted. The impact that observations of different types have on the prediction of the extratropical cyclones has also been explored, using forecasts integrated from analyses that were constructed from reduced observing systems. A terrestrial, satellite, and surface-based system were investigated and the results showed that the predictive skill of the terrestrial system was superior to the satellite system in the NH. Further analysis showed that the satellite system was not very good at predicting the growth of the storms. In the SH the terrestrial system has significantly less skill than the satellite system, highlighting the dominance of satellite observations in this hemisphere. The surface system has very poor predictive skill in both hemispheres.

The prediction of extratropical storm tracks by the ECMWF and NCEP ensemble prediction systems

The prediction of extratropical cyclones by the European Centre for Medium Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) Ensemble Prediction Systems (EPS) has been investigated using an objective feature tracking methodology to identify and track the cyclones along the forecast trajectories. Overall the results show that the ECMWF EPS has a slightly higher level of skill than the NCEP EPS in the northern hemisphere (NH). However in the southern hemisphere (SH), NCEP has higher predictive skill than ECMWF for the intensity of the cyclones. The results from both EPS indicate a higher level of predictive skill for the position of extratropical cyclones than their intensity and show that there is a larger spread in intensity than position. Further analysis shows that the predicted propagation speed of cyclones is generally too slow for the ECMWF EPS and show a slight bias for the intensity of the cyclones to be overpredicted. This is also true for the NCEP EPS in the SH. For the NCEP EPS in the NH the intensity of the cyclones is underpredicted. There is small bias in both the EPS for the cyclones to be displaced towards the poles. For each ensemble forecast of each cyclone, the predictive skill of the ensemble member that best predicts the cyclones position and intensity was computed. The results are very encouraging showing that the predictive skill of the best ensemble member is significantly higher than that of the control forecast in terms of both the position and intensity of the cyclones. The prediction of cyclones before they are identified as 850 hPa vorticity centers in the analysis cycle was also considered. It is shown that an indication of extratropical cyclones can be given by at least 1 ensemble member 7 days before they are identified in the analysis. Further analysis of the ECMWF EPS shows that the ensemble mean has a higher level of skill than the control forecast, particularly for the intensity of the cyclones, 2 from day 3 of the forecast. There is a higher level of skill in the NH than the SH and the spread in the SH is correspondingly larger. The difference between the ensemble mean and spread is very small for the position of the cyclones, but the spread of the ensemble is smaller than the ensemble mean error for the intensity of the cyclones in both hemispheres. Results also show that the ECMWF control forecast has ½ to 1 day more skill than the perturbed members, for both the position and intensity of the cyclones, throughout the forecast.