Abstract
The use of sensing devices to perform monitoring tasks has continuously evolved in the past decades [...]

Abstract
The American NASA Apollo missions to the lunar surface, between 1969 and 1972 greatly increased the knowledge of the Moon as well as that of our own Earth’s age and origins. Part of the scientific research used geophysical techniques to help define the structure of the Moon, both deep and also regarding the near surface. One such experimentation that was carried out, on both Apollo 14 and Apollo 16, as part of the Apollo Lunar Seismic Experiment Package (ALSEP), was the Active Seismic Experiment (ASE). The ASE comprised of three geophones, planted at approximately 45m apart along a longitudinal line, that recorded signals from small explosive charges deployed at specific distances in between the geophones, The analysis resulted in a set of traveltimes, from source to receiver, that were later interpreted using the intercept time method. Since then the data set results were accepted. The development of traveltime tomographic techniques in the early 1990’s allows for models to have a more realistic appearance with both lateral variations of seismic velocity as well as increasing velocities with a certain gradient in depth. This is opposed to the sharp sudden increases of compressional wave velocity typical of the intercept time method’s assumption. Herein we will present a discussion as well as the results of the reinterpretation of the Apollo 14 and 16 ASE refraction traveltimes using traveltime tomography techniques. © SGEM2019.

Abstract
Os artigos incluídos neste livro, após processo de revisão por pares, são desenvolvimentos de trabalhos apresentados nas JOCLAD 2014-17 e mostram, mais uma vez, a interdisciplinariedade e a diversidade das áreas que integram esta Jornadas.

Abstract
In the food retail sector, maintaining the food quality across the supply chain is of vital importance. The quality of the products is dependent on its storage and transportation conditions and this peculiarity increases the supply chain complexity relatively to other types of retailers. Actually, in this industry there are three types of food supply chains: frozen, chilled and ambient. Moreover, food retailers run different store formats, of different sizes, assortments and sales volume. In this study we research the trade-off between consolidating a range of products in order to perform direct deliveries to the stores versus performing separate delivery routes for products with different transportation requirements. A new consistency dimension is proposed regarding the periodicity that a consolidation strategy is implemented. The aim of this paper is to define a consolidation strategy for the delivery mode planning that allows to smooth the complexity of grocery retail operations. A three-step approach is proposed to tackle a real size problem in a case-study with a major Portuguese grocery retailer. By changing the consolidation strategy with a complete consistent plan the company could reach annual savings of around 4%. © 2019, Springer Nature Switzerland AG.

Abstract
Critical health events represent a relevant cause of mortality in intensive care units of hospitals, and their timely prediction has been gaining increasing attention. This problem is an instance of the more general predictive task of early anomaly detection in time series data. One of the most common approaches to solve this problem is to use standard classification methods. In this paper we propose a novel method that uses a layered learning architecture to solve early anomaly detection problems. One key contribution of our work is the idea of pre-conditional events, which denote arbitrary but computable relaxed versions of the event of interest. We leverage this idea to break the original problem into two layers, which we hypothesize are easier to solve. Focusing on critical health episodes, the results suggest that the proposed approach is advantageous relative to state of the art approaches for early anomaly detection. Although we focus on a particular case study, the proposed method is generalizable to other domains. © Springer Nature Switzerland AG 2019.

Abstract
Global climate change is currently a focus issue because of its impacts on the most diverse natural systems and, consequently, the development of humanity. The electricity sector is a major contributor to climate change because of its long-standing dependence on fossil fuels. However, the energy paradigm is changing, and renewable sources tend to play an increasingly important role in the energy mix in Portugal. Due to the strong relationship between renewable energies and climate-related natural resources, the climate change phenomenon could have considerable effects on the electricity sector. This paper analyzes the effects of climate change on the energy mix in Portugal in the medium / long term (up to 2050). The proposed methodology is based on the simulation of climate scenarios and projections of installed power by type and consumption. The combinations of these conditions are inputted to an energy accounting simulation tool, able to combine all information and provide a characterization of the system state for each case. The most favorable forecasted scenarios indicate that a fully renewable electricity system is achievable in the medium term, in line with the objectives of the European Union, as long as investments in renewable sources continue to be stimulated in the coming years.