8 resultados para SIMPLE-algoritmi

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Obstructive sleep apnoea/hypopnoea syndrome (OSAHS) is the periodic reduction or cessation of airflow during sleep. The syndrome is associated whit loud snoring, disrupted sleep and observed apnoeas. Surgery aims to alleviate symptoms of daytime sleepiness, improve quality of life and reduce the signs of sleep apnoea recordered by polysomnography. Surgical intervention for snoring and OSAHS includes several procedures, each designed to increase the patency of the upper airway. Procedures addressing nasal obstruction include septoplasty, turbinectomy, and radiofrequency ablation (RF) of the turbinates. Surgical procedures to reduce soft palate redundancy include uvulopalatopharyngoplasty with or without tonsillectomy, uvulopalatal flap, laser-assisted uvulopalatoplasty, and RF of the soft palate. More significant, however, particularly in cases of severe OSA, is hypopharyngeal or retrolingual obstruction related to an enlarged tongue, or more commonly due to maxillomandibular deficiency. Surgeries in these cases are aimed at reducing the bulk of the tongue base or providing more space for the tongue in the oropharynx so as to limit posterior collapse during sleep. These procedures include tongue-base suspension, genioglossal advancement, hyoid suspension, lingualplasty, and maxillomandibular advancement. We reviewed 269 patients undergoing to osas surgery at the ENT Department of Forlì Hospital in the last decade. Surgery was considered a success if the postoperative apnea/hypopnea index (AHI) was less than 20/h. According to the results, we have developed surgical decisional algorithms with the aims to optimize the success of these procedures by identifying proper candidates for surgery and the most appropriate surgical techniques. Although not without risks and not as predictable as positive airway pressure therapy, surgery remains an important treatment option for patients with obstructive sleep apnea (OSA), particularly for those who have failed or cannot tolerate positive airway pressure therapy. Successful surgery depends on proper patient selection, proper procedure selection, and experience of the surgeon. The intended purpose of medical algorithms is to improve and standardize decisions made in the delivery of medical care, assist in standardizing selection and application of treatment regimens, to reduce potential introduction of errors. Nasal Continuous Positive Airway Pressure (nCPAP) is the recommended therapy for patients with moderate to severe OSAS. Unfortunately this treatment is not accepted by some patient, appears to be poorly tolerated in a not neglible number of subjects, and the compliance may be critical, especially in the long term if correctly evaluated with interview as well with CPAP smart cards analysis. Among the alternative options in Literature, surgery is a long time honoured solution. However until now no clear scientific evidence exists that surgery can be considered a really effective option in OSAHS management. We have design a randomized prospective study comparing MMA and a ventilatory device (Autotitrating Positive Airways Pressure – APAP) in order to understand the real effectiveness of surgery in the management of moderate to severe OSAS. Fifty consecutive previously full informed patients suffering from severe OSAHS were enrolled and randomised into a conservative (APAP) or surgical (MMA) arm. Demographic, biometric, PSG and ESS profiles of the two group were statistically not significantly different. One year after surgery or continuous APAP treatment both groups showed a remarkable improvement of mean AHI and ESS; the degree of improvement was not statistically different. Provided the relatively small sample of studied subjects and the relatively short time of follow up, MMA proved to be in our adult and severe OSAHS patients group a valuable alternative therapeutical tool with a success rate not inferior to APAP.

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Water distribution networks optimization is a challenging problem due to the dimension and the complexity of these systems. Since the last half of the twentieth century this field has been investigated by many authors. Recently, to overcome discrete nature of variables and non linearity of equations, the research has been focused on the development of heuristic algorithms. This algorithms do not require continuity and linearity of the problem functions because they are linked to an external hydraulic simulator that solve equations of mass continuity and of energy conservation of the network. In this work, a NSGA-II (Non-dominating Sorting Genetic Algorithm) has been used. This is a heuristic multi-objective genetic algorithm based on the analogy of evolution in nature. Starting from an initial random set of solutions, called population, it evolves them towards a front of solutions that minimize, separately and contemporaneously, all the objectives. This can be very useful in practical problems where multiple and discordant goals are common. Usually, one of the main drawback of these algorithms is related to time consuming: being a stochastic research, a lot of solutions must be analized before good ones are found. Results of this thesis about the classical optimal design problem shows that is possible to improve results modifying the mathematical definition of objective functions and the survival criterion, inserting good solutions created by a Cellular Automata and using rules created by classifier algorithm (C4.5). This part has been tested using the version of NSGA-II supplied by Centre for Water Systems (University of Exeter, UK) in MATLAB® environment. Even if orientating the research can constrain the algorithm with the risk of not finding the optimal set of solutions, it can greatly improve the results. Subsequently, thanks to CINECA help, a version of NSGA-II has been implemented in C language and parallelized: results about the global parallelization show the speed up, while results about the island parallelization show that communication among islands can improve the optimization. Finally, some tests about the optimization of pump scheduling have been carried out. In this case, good results are found for a small network, while the solutions of a big problem are affected by the lack of constraints on the number of pump switches. Possible future research is about the insertion of further constraints and the evolution guide. In the end, the optimization of water distribution systems is still far from a definitive solution, but the improvement in this field can be very useful in reducing the solutions cost of practical problems, where the high number of variables makes their management very difficult from human point of view.

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Increasingly stringent exhaust emission limits and higher fuel economy are the main drivers of the engine development process. As a consequence, the complexity of the propulsion units and its subsystems increase, due to the extensive use of sensors and actuators needed to obtain a precise control over the combustion phase. Since engine calibration process consumes most of the development time, new tools and methodologies are needed to shorten the development time and increase the performance attainable. Real time combustion analysis, based on the in-cylinder pressure signal, can significantly improve the calibration of the engine control strategies and the development of new algorithms, giving instantaneous feedback on the engine behavior. A complete combustion analysis and diagnosis system has been developed, capable of evaluating the most important indicators about the combustion process, such as indicated mean effective pressure, heat release, mass fraction burned and knock indexes. Such a tool is built on top of a flexible, modular and affordable hardware platform, capable of satisfying the requirements needed for accuracy and precision, but also enabling the use directly on-board the vehicle, due to its small form factor.

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Combustion control is one of the key factors to obtain better performances and lower pollutant emissions for diesel, spark ignition and HCCI engines. An algorithm that allows estimating, as an example, the mean indicated torque for each cylinder, could be easily used in control strategies, in order to carry out cylinders trade-off, control the cycle to cycle variation, or detect misfires. A tool that allows evaluating the 50% of Mass Fraction Burned (MFB50), or the net Cumulative Heat Release (CHRNET), or the ROHR peak value (Rate of Heat Release), could be used to optimize spark advance or to detect knock in gasoline engines and to optimize injection pattern in diesel engines. Modern management systems are based on the control of the mean indicated torque produced by the engine: they need a real or virtual sensor in order to compare the measured value with the target one. Many studies have been performed in order to obtain an accurate and reliable over time torque estimation. The aim of this PhD activity was to develop two different algorithms: the first one is based on the instantaneous engine speed fluctuations measurement. The speed signal is picked up directly from the sensor facing the toothed wheel mounted on the engine for other control purposes. The engine speed fluctuation amplitudes depend on the combustion and on the amount of torque delivered by each cylinder. The second algorithm processes in-cylinder pressure signals in the angular domain. In this case a crankshaft encoder is not necessary, because the angular reference can be obtained using a standard sensor wheel. The results obtained with these two methodologies are compared in order to evaluate which one is suitable for on board applications, depending on the accuracy required.

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Traditional procedures for rainfall-runoff model calibration are generally based on the fit of the individual values of simulated and observed hydrographs. It is used here an alternative option that is carried out by matching, in the optimisation process, a set of statistics of the river flow. Such approach has the additional, significant advantage to allow also a straightforward regional calibration of the model parameters, based on the regionalisation of the selected statistics. The minimisation of the set of objective functions is carried out by using the AMALGAM algorithm, leading to the identification of behavioural parameter sets. The procedure is applied to a set of river basins located in central Italy: the basins are treated alternatively as gauged and ungauged and, as a term of comparison, the results obtained with a traditional time-domain calibration is also presented. The results show that a suitable choice of the statistics to be optimised leads to interesting results in real world case studies as far as the reproduction of the different flow regimes is concerned.

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in the everyday clinical practice. Having this in mind, the choice of a simple setup would not be enough because, even if the setup is quick and simple, the instrumental assessment would still be in addition to the daily routine. The will to overcome this limit has led to the idea of instrumenting already existing and widely used functional tests. In this way the sensor based assessment becomes an integral part of the clinical assessment. Reliable and validated signal processing methods have been successfully implemented in Personal Health Systems based on smartphone technology. At the end of this research project there is evidence that such solution can really and easily used in clinical practice in both supervised and unsupervised settings. Smartphone based solution, together or in place of dedicated wearable sensing units, can truly become a pervasive and low-cost means for providing suitable testing solutions for quantitative movement analysis with a clear clinical value, ultimately providing enhanced balance and mobility support to an aging population.

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Background-Amyloidotic cardiomyopathy (AC) can mimic true left ventricular hypertrophy (LVH), including hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD). We assessed the diagnostic value of combined electrocardiographic/echocardiographic indexes to identify AC among patients with increased echocardiographic LV wall thickness due to either different etiologies of amyloidosis or HCM or HHD. Method-First, we studied 469 consecutive patients: 262 with biopsy/genetically proven AC (with either AL or transthyretin (TTR)-related amyloidosis); 106 with HCM; 101 with HHD. We compared the diagnostic performance of: low QRS voltage, symmetric LVH, low QRS voltage plus interventricular septal thickness >1.98 cm, Sokolow index divided by the cross-sectional area of LV wall, Sokolow index divided by body surface area indexed LV mass (LVMI), Sokolow index divided by LV wall thickness, Sokolow index divided by (LV wall/height^2.7); peripheral QRS score divided by LVMI, Peripheral QRS score divided by LV wall thickness, Peripheral QRS score divided by LV wall thickness indexed to height^2.7, total QRS score divided by LVMI, total QRS score divided by LV wall thickness; total QRS score divided by (LV wall/height^2.7). We tested each criterion, separately in males and females, in the following settings: AC vs. HCM+HHD; AC vs. HCM; AL vs. HCM+HHD; AL vs. HCM; TTR vs. HCM+HHD; TTR vs. HCM. Results-Low QRS voltage showed high specificity but low sensitivity for the identification of AC. All the combined indexes had a higher diagnostic accuracy, being total QRS score divided by LV wall thickness or by LVMI associated with the best performances and the largest areas under the ROC curve. These results were validated in 298 consecutive patients with AC, HCM or HHD. Conclusions-In patients with increased LV wall thickness, a combined ECG/ echocardiogram analysis provides accurate indexes to non-invasively identify AC. Total QRS score divided by LVMI or LV wall thickness offers the best diagnostic performance.