Qual a contribuição das características antropométricas na velocidade de corrida de curta distância ?

v. 19, n. 2, abr./jun. 2016.

Atténuation d'effets non linéaires dans les lasers fibrés de haute puissance opérés en régime continu

Les lasers à fibre de haute puissance sont maintenant la solution privilégiée pour les applications de découpe industrielle. Le développement de lasers pour ces applications n’est pas simple en raison des contraintes qu’imposent les normes industrielles. La fabrication de lasers fibrés de plus en plus puissants est limitée par l’utilisation d’une fibre de gain avec une petite surface de mode propice aux effets non linéaires, d’où l’intérêt de développer de nouvelles techniques permettant l’atténuation de ceux-ci. Les expériences et simulations effectuées dans ce mémoire montrent que les modèles décrivant le lien entre la puissance laser et les effets non linéaires dans le cadre de l’analyse de fibres passives ne peuvent pas être utilisés pour l’analyse des effets non linéaires dans les lasers de haute puissance, des modèles plus généraux doivent donc développés. Il est montré que le choix de l’architecture laser influence les effets non linéaires. En utilisant l’équation de Schrödinger non linéaire généralisée, il a aussi été possible de montrer que pour une architecture en co-propagation, la diffusion Raman influence l’élargissement spectral. Finalement, les expériences et les simulations effectuées montrent qu’augmenter la réflectivité nominale et largeur de bande du réseau légèrement réfléchissant de la cavité permet d’atténuer la diffusion Raman, notamment en réduisant le gain Raman effectif.

Production efficiency in catfish (Clarias gariepinus) Burchell, 1822 in Cross River State , Nigeria

In the study, the production efficiency of catfish in Cross River State was determined. Data was obtained from 120 fish farmers were randomly selected from Cross River Agricultural Zones, using a multistage random sampling technique. Multiple regression analysis model was the main tool of data analysis where different functions were tried. The results indicated that Cobb-Douglass production function had the best fit in explaining the relationship between output of catfish and inputs used, the coefficient of multiple determinant (R2 = 0.61) indicates that sixtyone percent of the variability in output of catfish is explained by the independent variables. The results also indicate that farmers’ educational level positively influence their level of efficiency in catfish production in the study area. The F-value of 16.427 indicates the overall significance of the model at 1 percent level, indicating that there is a significant linear relationship between the independent variables taken together and the yield of catfish produced in Cross River State. The marginal value products of fish pond size (farm size), labour and feed (diet) were N67.50, N 178.13 and N 728.00 respectively, while allocative efficiency for (farm size), labour and feed (diet) were (0.09 over utilized, 2.85 under utilized and 0.99 over utilized), respectively, there existed allocative in-efficiency, there is a high potential for catfish farmers to increase their yields and income. Based on the findings of this study, it is recommended that fish farmers should expand fish farms, improving on production efficiency and adopting new technologies. Regular awareness campaign about new technologies in fish farming should be embarked by extension agents to make fish farmers know the importance of adopting new technologies. KEYWORDS: Production efficiency, Catfish, Cobb-Douglass, Production function, Cross River State

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.

The impact of geometric non-linearities on the fatigue analysis of trailing edge bond lines in wind turbine rotor blades

The accurate prediction of stress histories for the fatigue analysis is of utmost importance for the design process of wind turbine rotor blades. As detailed, transient, and geometrically non-linear three-dimensional finite element analyses are computationally weigh too expensive, it is commonly regarded sufficient to calculate the stresses with a geometrically linear analysis and superimpose different stress states in order to obtain the complete stress histories. In order to quantify the error from geometrically linear simulations for the calculation of stress histories and to verify the practical applicability of the superposition principal in fatigue analyses, this paper studies the influence of geometric non-linearity in the example of a trailing edge bond line, as this subcomponent suffers from high strains in span-wise direction. The blade under consideration is that of the IWES IWT-7.5-164 reference wind turbine. From turbine simulations the highest edgewise loading scenario from the fatigue load cases is used as the reference. A 3D finite element model of the blade is created and the bond line fatigue assessment is performed according to the GL certification guidelines in its 2010 edition, and in comparison to the latest DNV GL standard from end of 2015. The results show a significant difference between the geometrically linear and non-linear stress analyses when the bending moments are approximated via a corresponding external loading, especially in case of the 2010 GL certification guidelines. This finding emphasizes the demand to reconsider the application of the superposition principal in fatigue analyses of modern flexible rotor blades, where geometrical nonlinearities become significant. In addition, a new load application methodology is introduced that reduces the geometrically non-linear behaviour of the blade in the finite element analysis.

Exploring the potential role of allostatic load biomarkers in risk assessment of patients presenting with depressive symptoms

Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.

Modelagem univariada e regressão múltipla na análise da oferta e do preço do boi gordo no mercado brasileiro

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Agronomia e Medicina Veterinária, Programa de Pós-Graduação em Agronegócios, 2016.

Impacto(s) da gestão de recursos humanos na gestão do conhecimento em organizações industriais

Focalizando as dimensões humana e comportamental da gestão do conhecimento, a presente investigação visa uma análise do(s) impacto(s) (facilitador ou inibidor) dos pressupostos da gestão de recursos humanos no grau de aplicação da gestão do conhecimento em organizações industriais. Em particular, explora a(s) dinâmica(s) de influência entre a sofisticação dos pressupostos da formação profissional, da avaliação de desempenho e da gestão de recompensas na aplicação da gestão do conhecimento. Tendo em vista a medição dos constructos centrais do presente estudo, de acordo com a revisão de literatura efectuada, desenvolveram-se acções conducentes à adaptação de um questionário de gestão do conhecimento (GC), à construção, validação e desenvolvimento de três novos questionários (PPFP, PPAD e PPSR) que visaram aceder à percepção dos agentes organizacionais acerca dos pressupostos da gestão de recursos humanos vigentes ou culturalmente característicos do seu contexto laboral. O presente estudo envolveu múltiplas análises aos dados de 1364 questionários individuais auto-administrados e recolhidos em 55 empresas de quatro sub-sectores da cerâmica em Portugal. Para o estudo da relação linear entre um conjunto de variáveis preditoras e uma variável critério optou-se por realizar equações de regressão múltipla hierárquica, considerando-se dois blocos de variáveis. Num primeiro modelo foram introduzidas, apenas, as duas dimensões relativas à formação profissional medidas pelo instrumento PPFP e num segundo modelo aduziram-se as variáveis de avaliação de desempenho e de sistema de recompensas, especificamente, o primeiro factor retido na análise psicométrica dos instrumentos PPAD e PPSR.

Antibiotic Therapy for Very Low BirthWeigh Newborns in NICU

Background: Prolonged empiric antibiotics therapy in neonates results in several adverse consequences including widespread antibiotic resistance, late onset sepsis (LOS), necrotizing enterocolitis (NEC), prolonged hospital course (HC) and increase in mortality rates. Objectives: To assess the risk factors and the outcome of prolonged empiric antibiotic therapy in very low birth weight (VLBW) newborns. Materials and Methods: Prospective study in VLBW neonates admitted to NICU and survived > 2 W, from July 2011 - June 2012. All relevant perinatal and postnatal data including duration of antibiotics therapy (Group I < 2W vs Group II > 2W) and outcome up to the time of discharge or death were documented and compared. Results: Out of 145 newborns included in the study, 62 were in group I, and 83 in Group II. Average duration of antibiotic therapy was 14 days (range 3 - 62 days); duration in Group I and Group II was 102.3 vs 25.510.5 days. Hospital stay was 22.311.5 vs 44.3 14.7 days, respectively. Multiple regression analysis revealed following risk factors as significant for prolonged empiric antibiotic therapy: VLBW especially < 1000 g, (P < 0.001), maternal Illness (P = 0.003), chorioamnionitis (P = 0.048), multiple pregnancy (P = 0.03), non-invasive ventilation (P < 0.001) and mechanical ventilation (P < 0.001). Seventy (48.3%) infants developed LOS; 5 with NEC > stage II, 12 (8.3%) newborns died. Infant mortality alone and with LOS/NEC was higher in group II as compared to group I (P < 0.002 and < 0.001 respectively). Conclusions: Prolonged empiric antibiotic therapy caused increasing rates of LOS, NEC, HC and infant mortality

SVR-GARCH com misturas de kernels gaussianos

Dissertação (mestrado)—Universidade de Brasília, Departamento de Administração, Programa de Pós-graduação em Administração, 2016.

Modelos linear e não linear em análises genéticas para sobrevivência de crias de ovinos da raça Santa Inês.

Resumo: Registros de sobrevivência do nascimento ao desmame de 3846 crias de ovinos da raça Santa Inês foram analisados por modelos de reprodutor linear e não linear (modelo de limiar), para estimar componentes de variância e herdabilidade. Os modelos usados para sobrevivência, analisada como característica da cria, incluíram os efeitos fixos de sexo, da combinação tipo de nascimento-criação da cria e da idade da ovelha ao parto, efeito da covariável peso da cria ao nascer e efeitos aleatórios de reprodutor, da classe rebanho-ano-estação e do resíduo. Componentes de variância para o modelo linear foram estimados pelo método da máxima verossimilhança restrita (REML) e para o modelo não linear por uma aproximação da máxima verossimilhança marginal (MML), pelo programa CMMAT2. O coeficiente de herdabilidade (h2) estimado pelo modelo de limiar foi de 0,29, e pelo modelo linear, 0,14. A correlação de ordem de Spearman entre as capacidades de transmissão dos reprodutores, com base nos dois modelos foi de 0,96. As estimativas de h2 obtidas indicam a possibilidade de se obter, por seleção, ganho genético para sobrevivência. [Linear and nonlinear models in genetic analyses of lamb survival in the Santa Inês hair sheep breed]. Abstract: Records of 3,846 lambs survival from birth to weaning of Santa Inês hair sheep breed, were analyzed by linear and non linear sire models (threshold model) to estimate variance components and heritability (h2). The models that were used to analyze survival, considered in this study as a lamb trait, included the fixed effects of sex of the lamb, combination of type of birth-rearing of lamb, and age of ewe, birth weight of lamb as covariate, and random effects of sire, herd-year-season and residual. Variance components were obtained using restricted maximum likelihood (REML), in linear model and marginal maximum likelihood in threshold model through CMMAT2 program. Estimate of heritability (h2) obtained by threshold model was 0.29 and by linear model was 0.14. Rank correlation of Spearman, between sire solutions based on the two models was 0.96. The obtained estimates in this study indicate that it is possible to acquire genetic gain to survival by selection.

Differences Among Undergraduate and Graduate Nursing Students’ Cultural Competency

This study examined differences in cultural competency levels between undergraduate and graduate nursing students (age, ethnicity, gender, language at home, education level, program standing, program track, diversity encounters, and previous diversity training). Participants were 83% women, aged 20 to 62; 50% Hispanic/Latino; with a Bachelor of Science in Nursing (n = 82) and a Master of Science in Nursing (n = 62). Degrees included high school diplomas, associate/diplomas, bachelors’ degrees in or out of nursing, and medical doctorate degrees from outside the United States. Students spoke English (n = 82) or Spanish (n = 54). The study used a cross-sectional design guided by the three-dimensional cultural competency model. The Cultural Competency Assessment (CCA) tool is composed of two subscales: Cultural Awareness and Sensitivity (CAS) and Culturally Competent Behaviors (CCB). Multiple regressions, Pearson’s correlations, and ANOVAs determined relationships and differences among undergraduate and graduate students. Findings showed significant differences between undergraduate and graduate nursing students in CAS, p <.016. Students of Hispanic/White/European ethnicity scored higher on the CAS, while White/non-Hispanic students scored lower on the CAS, p < .05. One-way ANOVAs revealed cultural competency differences by program standing (grade-point averages), and by program tracks, between Master of Science in Nursing Advanced Registered Nurse Practitioners and both Traditional Bachelor of Science in Nursing and Registered Nurse-Bachelor of Science in Nursing. Univariate analysis revealed that higher cultural competency was associated with having previous diversity training and participation in diversity training as continuing education. After controlling for all predictors, multiple regression analysis found program level, program standing, and diversity training explained a significant amount of variance in overall cultural competency (p = .027; R2 = .18). Continuing education is crucial in achieving students’ cultural competency. Previous diversity training, graduate education, and higher grade-point average were correlated with higher cultural competency levels. However, increased diversity encounters were not associated with higher cultural competency levels.

Essays on employment / education, investment in education and student achievement

Méthodologie: Modèle de régression quantile de variable instrumentale pour données de Panel utilisant la fonction de production partielle

Coastal Forests of Kenya-Ecology, Biodiversity & Conservation

Aims: the broad objective of this study is to investigate the ecological, biodiversity and conservation status of the coastal forests of Kenya fragments. The specific aims of the study are: (1) to investigate current quantitative trends in plant diversity; (2) develop a spatial and standardised vegetation database for the coastal forests Kenya; (3) investigate forest structure, species diversity and composition across the forests; (4) investigate the effect of forest fragment area on plant species diversity; (5) investigate phylogenetic diversity across these coastal remnants (6) assess vulnerability and provide conservation perspectives to concrete policy issues; (7) investigate plant and butterfly diversity correlation. Methods: I performed various analytical methods including species diversity metrics; multiple regression models for species-area relationship and small island effect; non-metric multidimensional scaling; ANOSIM; PERMANOVA; multiplicative beta diversity partitioning; species accumulation curve and species indicator analysis; statistical tests, rarefaction of species richness; phylogenetic diversity metrics of Phylogenetic diversity index, mean pairwise distance, mean nearest taxon distance, and their null-models: and Co-correspondence analysis. Results: developed the first large standardised, spatial and geo-referenced vegetation database for coastal forests of Kenya consisting of 600 plant species, across 25 forest fragments using 158 plots subdivided into 3160 subplots, 18 sacred forests and seven forest reserves; species diversity, composition and forest structure was significantly different across forest sites and between forest reserves and sacred forests, higher beta diversity, species-area relationship explained significant variability of plant diversity, small Island effect was not evident; sacred forests exhibited higher phylogenetic diversity compared to forest reserves; the threatened Red List species contributed higher evolutionary history; a strong correlation between plants and butterfly diversity. Conclusions: This study provides for the first time a standardized and large vegetation data. Results emphasizes need to improve sacred forests protection status and enhance forest connectivity across forest reserves and sacred forests.

Effective procedure for the optimization of the linear controller in an industrial drive for a nonlinear mechanism

Il progetto di tesi è incentrato sull’ottimizzazione del procedimento di taratura dei regolatori lineari degli anelli di controllo di posizione e velocità presenti negli azionamenti usati industrialmente su macchine automatiche, specialmente quando il carico è ad inerzia variabile in dipendenza dalla posizione, dunque non lineare, come ad esempio un quadrilatero articolato. Il lavoro è stato svolto in collaborazione con l’azienda G.D S.p.A. ed il meccanismo di prova è realmente utilizzato nelle macchine automatiche per il packaging di sigarette. L’ottimizzazione si basa sulla simulazione in ambiente Matlab/Simulink dell’intero sistema di controllo, cioè comprensivo del modello Simulink degli anelli di controllo del drive, inclusa la dinamica elettrica del motore, e del modello Simscape del meccanismo, perciò una prima necessaria fase del lavoro è stata la validazione di tali modelli affinché fossero sufficientemente fedeli al comportamento reale. Il secondo passo è stato fornire una prima taratura di tentativo che fungesse da punto di partenza per l’algoritmo di ottimizzazione, abbiamo fatto ciò linearizzando il modello meccanico con l’inerzia minima e utilizzando il metodo delle formule di inversione per determinare i parametri di controllo. Già questa taratura, seppur conservativa, ha portato ad un miglioramento delle performance del sistema rispetto alla taratura empirica comunemente fatta in ambito industriale. Infine, abbiamo lanciato l’algoritmo di ottimizzazione definendo opportunamente la funzione di costo, ed il risultato è stato decisamente positivo, portando ad un miglioramento medio del massimo errore di inseguimento di circa il 25%, ma anche oltre il 30% in alcuni casi.