Dementia disorders are difficult to detect in the early stages of the disease. Therefore, it is of importance to develop new methods in early diagnostics. The Uppsala Dalarna Dementia and Gait Study has established a new method in diagnosing early stages of cognitive impairments. The new method Timed-Up-and-Go (TUG) dual-task, combines a gait test with a verbal task. This thesis analyses nine TUG variables for healthy controls and discusses differences between two age groups, subjects younger than 72 years and subjects 72 years or older. Reliability of the new method is the primary focus point and is assessed using Intraclass Correlation Coefficients (ICC) and Bland-Altman plots. Normative reference values for the continuous variables are estimated with the help of bootstrap confidence intervals for the 2.5 and 97.5 percentiles. The results show that the three variables measuring the time to complete the test have good to excellent reliability, while variables that measure combinations of gait and verbal tasks show poor to moderate reliability. The lower reliability for these variables could be explained by them being ratios or differences of other variables. Differences in reliability can be seen between the age groups, where younger subjects have lower reliability partly due to homogeneity. Results show that the reference values of healthy controls are different for the two age groups.

Accurate and reliable effort estimation is still one of the most challenging processes in software engineering. There have been numbers of attempts to develop cost estimation models. However, the evaluation of model accuracy and reliability of those models have gained interest in the last decade. A model can be finely tuned according to specific data, but the issue remains there is the selection of the most appropriate model. A model predictive accuracy is determined by the difference of the various accuracy measures. The one with minimum relative error is considered to be the best fit. The model predictive accuracy is needed to be statistically significant in order to be the best fit. This practice evolved into model evaluation. Models predictive accuracy indicators need to be statistically tested before taking a decision to use a model for estimation. The aim of this thesis is to statistically evaluate well known effort estimation models according to their predictive accuracy indicators using two new approaches; bootstrap confidence intervals and permutation tests. In this thesis, the significance of the difference between various accuracy indicators were empirically tested on the projects obtained from the International Software Benchmarking Standard Group (ISBSG) data set. We selected projects of Un-Adjusted Function Points (UFP) of quality A. Then, the techniques; Analysis Of Variance ANOVA and regression to form Least Square (LS) set and Estimation by Analogy (EbA) set were used. Step wise ANOVA was used to form parametric model. K-NN algorithm was employed in order to obtain analogue projects for effort estimation use in EbA. It was found that the estimation reliability increased with the pre-processing of the data statistically, moreover the significance of the accuracy indicators were not only tested statistically but also with the help of more complex inferential statistical methods. The decision of selecting non-parametric methodology (EbA) for generating project estimates in not by chance but statistically proved.

En esta tesis, se utilizan t ecnicas matem atico-epidemiol ogicas para modelar el rendimiento acad emico en Espa~na (prestando especial atenci on en el fracaso escolar) para comprender mejor los mecanismos detr as de esta importante cuesti on, as como para predecir c omo evolucionar an los resultados acad emicos en el Bachillerato espa~nol en los pr oximos a~nos. El nivel educativo de Bachillerato en Espa~na est a formado por los dos ultimos cursos antes de acceder a la universidad o al mercado de trabajo y corresponde a los estudiantes de 16 18 a~nos. Este nivel educativo es muy importante para la formaci on de los estudiantes ya que representa un periodo en el que deber an tomar importantes decisiones sobre el futuro acad emico y profesional. En primer lugar, en el Cap tulo 2, se presenta un modelo determinista donde se analiza el rendimiento acad emico asumiendo que la actitud negativa de los alumnos de Bachillerato puede ser debida a su comportamiento aut onomo y la in uencia de compa~neros con malos resultados acad emicos. Luego, en el Cap tulo 3, se mejora el modelo basado en la idea de que no s olo los malos h abitos acad emicos se transmiten socialmente sino tambi en los buenos h abitos de estudio. Adem as, descomponemos los par ametros de transmisi on de h abitos acad emicos con el n de analizar con m as detalle qu e grupos de estudiantes son m as susceptibles a ser in uenciados por compa~neros con buenos o malos h abitos acad emicos. El abandono escolar tambi en han sido incluido en este modelo. El enfoque adoptado permite proporcionar predicciones deterministas y con intervalos de con anza de la evoluci on del rendimiento escolar (incluyendo las tasas de abandono) en Bachillerato en Espa~na en los pr oximos a~nos. Este enfoque, adem as, nos permite modelar el rendimiento acad emico en otros niveles educativos del sistema acad emico espa~nol o de fuera de Espa~na tal y como se muestra en el Cap tulo 4, donde el modelo se aplica satisfactoriamente al sistema acad emico actual de la regi on alemana de Renania del Norte-Westfalia. Para concluir esta tesis, proporcionamos una estimaci on de los costes relacionados con el rendimiento acad emico espa~nol basado en nuestras predicciones. Esta estimaci on representa la inversi on en Bachillerato por parte del Gobierno espa~nol y las familias en los pr oximos a~nos, con especial atenci on en los grupos de estudiantes que no promocionan y abandonan en los diferentes cursos acad emicos. / In this dissertation, we use epidemiologic-mathematical techniques to model the academic performance in Spain (paying special attention on the academic underachievement) to understand better the mechanisms behind this important issue as well as to predict how academic results will evolve in the Spanish Bachillerato over the next few years. The Spanish Bachillerato educational level is made up of the last courses before accessing to the university or to the work market and corresponds to students of 16¿18 years old. This educational level is a milestone in the career training of students because it represents a period to make important decisions about academic and professional future. In a rst step, in the Chapter 2 we will present a deterministic model where academic performance is analyzed assuming the negative attitude of Bachillerato students may be due to their autonomous behavior and the in uence of classmates with bad academic results. Then, in the Chapter 3, the model is improved based on the idea that not only the bad academic habits are socially transmitted but also the good study habits. Besides, we decompose the transmission academic habits into good and bad academic habits, in order to analyze with more detail which group of students are more susceptible to be in uenced by good or bad academic students. The consideration of quantifying the abandon rates is also a new issue dealt with in it. The adopted approach allow to provide both punctual and con dence intervals predictions to the evolution of academic performance (including the abandon rates) in Bachillerato in Spain over the next few years. The adopted approach allows us to model academic performance in academic levels other than Bachillerato and/or beyond the Spanish academic system. This issue is assessed in Chapter 4, where the model is satisfactorily applied to the current academic system of the German region of North Rhine-Westphalia. To conclude this dissertation, we provide an estimation of the cost related to the Spanish academic underachievement based on our predictions. This estimation represents the investment in the Spanish Bachillerato from the Spanish Government and families over the next few years, paying special attention on the groups of students who do not promote and abandon during their corresponding academic year. / Sánchez Sánchez, A. (2013). Modelling the evolution dynamics of the academic performance in high school in Spain. Probabilistic predictions of future trends and their economical consequences [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/32280 / TESIS

This thesis, structured in two parts, addresses a series of problems of relevance in the field of Spatial Geodesy. The first part delves into the application of satellite gravity data to enhance our understanding of water transport dynamics. Here, we present two significant contributions. Both are based on satellite gravity data but stem from different mission concepts with distinct objectives: time-variable gravity monitoring and high-resolution, accurate static geoid modelling. First, the fundamental notions about gravity are introduced and a brief summary is made of the different gravity satellite missions throughout history, with emphasis on the GRACE/GRACE-FO and GOCE missions, whose data are the basis of this work. The first application focuses on estimating water transport and geostrophic circulation in the Southern Ocean by leveraging a GOCE geoid and altimetry data. The Volume Transport across the Antartic Circumpolar Current is analyzed and the resulsts are validated validated using the in-situ data collected during the multiple campaigns in the DP. The second application uses time-variable gravity data from the GRACE and GRACE-FO missions to estimate the water cycle in the Mediterranean and Black Sea system, a critical region for regional climate and global ocean circulation. The analysis delves into the analysis of the different components of the hydrological cycle within this region, including the water flow across the Gibraltar Strait, examining their seasonal variations, climatic patterns, and their connection with the North Atlantic Oscillation Index. The second part of the thesis is more focused on data analysis, with the objective of developing mathematical methods to estimate the cross correlation function between two time series that are both unevenly spaced spaced (the sampling is not uniform over time) and observed at unequal time scales (the set of time points for the first series is not identical to the set of time points of the second series). Such time series are frequently encountered in geodetic surveys, especially when combining data from different sources. The estimation of the the cross correlation function for these time series presents unique challenges and requires the adaptation of traditional analysis methods designed for evenly spaced and synchronized time series. The two main contributions in this context are: (i) the study of the asymptotic properties of the Guassian Kernel estimator, that is the recommended estimator for the cross correlation function when the two time series are observed at unequal time scales; (ii) an extension of the stationary bootstrap that allows to construct bootstrap-based confidence intervals for the cross correlation function for unevenly spaced time series not sampled on identical time points.