Abstract
Data mining and machine learning algorithms can be employed to perform a variety of tasks. However, since most of these problems may depend on environments that change over time, performing classification tasks in dynamic environments has been a challenge in data mining research domain in the last decades. Currently, in the literature, the most common strategies used to detect changes are based on accuracy monitoring, which relies on previous knowledge of the data in order to identify whether or not correct classifications are provided. However, such a feedback can be infeasible in practical problems. In this work, we present a comprehensive overview of current machine learning/data mining approaches proposed to deal with dynamic environments problems. The objective is to highlight the main drawbacks and open issues, as well as future directions and problems worthy of investigation. In addition, we provide the definitions of the main terms used to represent this problem in the literature, such as concept drift and novelty detection. WIREs Data Mining Knowl Discov 2016, 6:156-166. doi: 10.1002/widm.1184 For further resources related to this article, please visit the .

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Abstract
Body skin temperature is a useful parameter for diagnosing diseases and infrared thermography can, be a powerful tool in providing important information to detect body temperature changes in a noninvasive way. The aim of this work was to study the pattern of skin temperature during pregnancy, to establish skin temperature reference values and to find correlations between these and the pregnant population characteristics. Sixty-one healthy pregnant women (mean age 30.6 +/- 5.1 years) in the 8th-40th gestational week with normal pregnancies were examined in 31 regions of interest (ROI). The ROIs were defined all over the body in order to determine the most influenced by factors such as age or body mass index (BMI). The results obtained in this work highlight that in normal pregnant women the skin temperature is symmetrically distributed, with the symmetrical areas differing less than 0.5 degrees C, with a mean value of 0.25 +/- 0.23 degrees C. This study identified a significant negative correlation between the BMI and temperature. Age has been shown to have great influence on the skin temperature, with a significant increase of temperature observed with age. This work explores a novel medical application of infrared thermography and provides a characterization of thermal skin profile in human pregnancy for a large set of ROIs while also evaluating the effects of age and BMI.

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The purpose of this paper is to present the main results of the ongoing analysis of applying dynamic network access tariffs in Portugal. For the 2015-2017 regulatory period, the Portuguese National Regulatory Authority, ERSE, required the three main Portuguese DSOs to submit, until the end of June 2016, plans for the implementation of network dynamic tariff schemes targeting Medium, High and Extra High Voltage customers, as well as the respective cost-benefit analysis. EDP Distribuição, the main Portuguese DSO, is preparing a report regarding the implementation of pilot projects on a sample of these segments of customers, which are due to be on the field during 2017. These pilots should help electrical energy stakeholders understand how the Electric System can benefit from the use of dynamic tariffs focused on networks, allowing for the quantification of benefits in a more accurate way. The level of demand response that results from price signals is a key issue that both the regulator and EDP Distribuição will quantify. Other important issue to assess in this study is the efficiency of cost recovery under a dynamic tariff scheme. In conclusion, this paper will present some results obtained from the cost-benefit analysis regarding the implementation of a Critical Peak Pricing scheme, as well as the key learnings supporting the introduction of dynamic schemes in the future, not only for EHV, HV and MV customers but also eventually extending it to LV ones.

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This research aims to initially address the Digital Mourning concept under the Digital Heritage Management, investigating to what extent we can "Managing the Digital Heritage", namely the content we create on a daily basis on social networks and the Internet.. The ultimate goal is to understand to what extent this issue is important for users and present results showing that items needed to design a system that is accepted and used in practice by users. To assess the need for platforms for the Digital Heritage Management (PGHDs) and what is the desirable content was conducted a questionnaire on the subject. Analyzing the results of this questionnaire it appears that most respondents did not think about the future of your Digital Heritage is not aware about the policies of online services they use. But the evidence is that the higher the technological maturity of most individuals is likely to be future users of this type of platforms. It also notes that the vast majority of users consider necessary technologically developed using PGHDs in the future.

Abstract
Power industry has been deeply restructured in recent decades. Along this period vertically integrated structures evolved to more disaggregated models in which some activities are now provided under competition as generation and retailing while some others are provided under regulated monopolies as network transmission and distribution. Simultaneously, most countries started to encourage the use of renewable sources, namely to cope with environmental issues and to enlarge the energy independency. Having in mind these ideas and given the development of the Iberian Electricity Market and the increase of the installed capacity in units paid by feed-in tariffs, it becomes important to estimate the impact of this feed-in generation in the market prices. This paper describes the approach that was developed to estimate this impact and the implemented software application. This application was then used to evaluate the impact on prices on all trading hours of 2013 of the Portuguese photovoltaic generation, the Portuguese wind generation, all the Portuguese feed-in generation and also all the Iberian feed-in generation.