Abstract
We consider interval-valued time series, that is, series resulting from collecting real intervals as an ordered sequence through time. Since the lower and upper bounds of the observed intervals at each time point are in fact values of the same variable, they are naturally related. We propose modeling interval time series with space-time autoregressive models and, based on the process appropriate for the interval bounds, we derive the model for the intervals' center and radius. A simulation study and an application with data of daily wind speed at different meteorological stations in Ireland illustrate that the proposed approach is appropriate and useful.

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The proliferation of new wireless communication technologies and services led to a boost in the number of different available communication standards and spectrum usage. As the electromagnetic spectrum is a finite resource, concerns about its efficient management became an important aspect. Given this scenario, Cognitive Radio emerged as a solution for future wireless communication devices, by supporting multiple standards and improving spectrum utilization through opportunistic wireless access. The purpose of this research is to study and design a reconfigurable FPGA-based NC-OFDM baseband processor meeting the requirements of next generation Cognitive Radio devices in terms of multi-carrier, multi-standard communications and spectral agility in changing environments. The processor will be the core of a flexible NC-OFDM transceiver for future 5G communications with support for spectrum aggregation and run-time selection of modulation schemes and active sub-carriers. The goal is to achieve higher levels of system adaptability, upgradeability and efficiency, by employing dynamic partial reconfiguration of FPGAs.

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The great incidence of cardiovascular (CV) diseases in the world spurs the search for new solutions to enable an early detection of pathological processes and provides more precise diagnosis based in multi-parameters assessment. The pulse wave velocity (PWV) is considered one of the most important clinical parameters for evaluate the CV risk, vascular adaptation, and therapeutic efficacy. Several studies were dedicated to find the relationship between PWV measurement and pathological status in different diseases, and proved the relevance of this parameter. The commercial devices dedicate to PWV estimation make a regional assessment (measured between two vessels), however a local measurement is more precise evaluation of artery condition, taking into account the differences in the structure of arteries. Moreover, the current devices present some limitations due to the contact nature. Emerging trends in CV monitoring are moving away from more invasive technologies to non-invasive and non-contact solutions. The great challenge is to explore the new instrumental solutions that allow the PWV assessment with fewer approximations for an accurately evaluation and relatively inexpensive techniques in order to be used in the clinical routine. © The Author(s) 2015.

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