Modeling Longevity Risk using Extreme Value Theory: An Empirical Investigation using Portuguese and Spanish Population Data

Extreme value theory (EVT) provides a framework to formalize the study of behaviour in the tails of a distribution. In this paper we use EVT to model the statistical behaviour of mortality rates over a given high threshold age and to estimate the significance of rare longevity risk in a given population. We adopt a piecewise approach in estimating the optimal threshold age using an iterative algorithm of maximum likelihood estimation.that statistically determines the cut-off between the central (Gompertz) part of the distribution and the upper tail modelled using the generalized Pareto distribution. The model is empirically tested using the most recent period mortality data for the total, male and female populations of Portugal and Spain. We use some classical results from EVT to estimate the evolution of the theoretical maximum life span over time and to derive confidence intervals for the central estimates. We then use time series methods to forecast the highest attained age. We observe a good fit of the model in all populations and subperiods analysed and on the whole life span considered. We estimate an increase in the theoretical maximum life span over time for all populations, more significant in the male subpopulations

Computing the Component-Labeling and the Adjacency Tree of a Binary Digital Image in Near Logarithmic-Time

Connected component labeling (CCL) of binary images is one of the fundamental operations in real time applications. The adjacency tree (AdjT) of the connected components offers a region-based representation where each node represents a region which is surrounded by another region of the opposite color. In this paper, a fully parallel algorithm for computing the CCL and AdjT of a binary digital image is described and implemented, without the need of using any geometric information. The time complexity order for an image of m × n pixels under the assumption that a processing element exists for each pixel is near O(log(m+ n)). Results for a multicore processor show a very good scalability until the so-called memory bandwidth bottleneck is reached. The inherent parallelism of our approach points to the direction that even better results will be obtained in other less classical computing architectures.Ministerio de Economía y Competitividad MTM2016-81030-PMinisterio de Economía y Competitividad TEC2012-37868-C04-0

A collaborative filtering method for music recommendation

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsThe present dissertation focuses on proposing and describing a collaborative filtering approach for Music Recommender Systems. Music Recommender Systems, which are part of a broader class of Recommender Systems, refer to the task of automatically filtering data to predict the songs that are more likely to match a particular profile. So far, academic researchers have proposed a variety of machine learning approaches for determining which tracks to recommend to users. The most sophisticated among them consist, often, on complex learning techniques which can also require considerable computational resources. However, recent research studies proved that more simplistic approaches based on nearest neighbors could lead to good results, often at much lower computational costs, representing a viable alternative solution to the Music Recommender System problem. Throughout this thesis, we conduct offline experiments on a freely-available collection of listening histories from real users, each one containing several different music tracks. We extract a subset of 10 000 songs to assess the performance of the proposed system, comparing it with a Popularity-based model approach. Furthermore, we provide a conceptual overview of the recommendation problem, describing the state-of-the-art methods, and presenting its current challenges. Finally, the last section is dedicated to summarizing the essential conclusions and presenting possible future improvements

Specifying, Analyzing, Integrating Mobile Apps and Location Sensors as part of Cyber-Physical Systems in the Classroom Environment

Cyber-Physical Systems (CPS) are characterized as complex systems usually networked, composed of several heterogeneous components that make the connection between events in the physical environment with computation. We can observe that this kind of systems is increasingly used in different areas such as automotive facilities, construction (civil engineering), health care and energy industry, providing a service or activity which depends on the interaction with users and the physical environment in which they are installed. Nowadays, in the educational context, the process of control and monitor of evaluation activities is conducted in a non-automated way by lecturers. This control is performed before, during and after the beginning of the evaluation activity, and include logistical processes such as classroom reservation, distribution of students per classroom, attendance record or fraud control. However, in an environment involving a large number of students, the execution of these tasks becomes difficult to perform efficiently and safely, requiring innovative techniques or assistance tools. In this work, the creation/design of a cyber-physical system through a modeling approach is proposed, aiming to help teachers to control and monitor evaluation activities. Based on a systematic literature study, we claim that there are no studies presenting the modeling of cyber-physical systems in an educational context, enhancing the interest of the proposed case study. In this document, we show how we used a framework named ModelicaML to model this system during the design phase. Also, this framework will offer a simulation component to simulate the behavior of the prescribed system. On the side of the hardware architecture, for the purpose of identifying the valid seats for the specific students inclass during the examination period, an indoor location system will be used, allowing to blueprint the physical layout of the room and globally manage the activity workflow. We finish this work by showing with empirical studies the gains of our solution when compared to the traditional method

Simplification Techniques for Maps in Simplicial Topology

This paper offers an algorithmic solution to the problem of obtaining "economical" formulae for some maps in Simplicial Topology, having, in principle, a high computational cost in their evaluation. In particular, maps of this kind are used for defining cohomology operations at the cochain level. As an example, we obtain explicit combinatorial descriptions of Steenrod k-th powers exclusively in terms of face operators