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PurposeThis short communication aims to explore and synthesize the main effects of COVID-19 on the labor market in Portugal regarding the dimensions related to job security and unemployment.Design/methodology/approachField research is used to identify and understand the challenges posed by the COVID-19 pandemic to the labor market in Portugal. Data from the National Institute of Statistics of Portugal are analyzed and compared with artifacts published in the field, which allow us to explore the impact of this phenomenon from multiple perspectives.FindingsThe findings indicate that the impact on the labor market is very asymmetric regarding geographical regions, sectors of activity, age groups and the nature of labor ties. The most touristic regions and those with a strong dependence on the exterior are the most affected. Young people and women with unstable employment relationships and in temporary work situations are also particularly vulnerable.Originality/valueThis study focuses on an emerging area with a strong impact of the COVID-19 pandemic on the labor market. This study seeks both to identify challenges in the Portuguese labor market and to discuss measures that should be taken to mitigate their effects, such as reforming the social security model, the role of teleworking or the more balanced development of the territory.

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Complex data management on healthcare institutions makes very hard to identify illegitimate accesses which is a serious issue. We propose to develop a system to detect accesses with suspicious behavior for further investigation. We modeled use cases (UC) and sequence diagrams (SD) showing the data flow between users and systems. The algorithms represented by activity diagrams apply rules based on professionals' routines, use data from an audit trail (AT) and classify accesses as suspicious or normal. The algorithms were evaluated between 23rd and 31st July 2019. The results were analyzed using absolute and relative frequencies and dispersion measures. Access classification was in accordance to rules applied. "Check time of activity" UC had 64, 78% of suspicious classifications, being 55% of activity period shorter and 9, 78% longer than expected, "Check days of activity" presented 2, 27% of suspicious access and "EHR read access" 79%, the highest percentage of suspicious accesses. The results show the first picture of HIS accesses. Deeper analysis to evaluate algorithms sensibility and specificity should be done. Lack of more detailed information about professionals' routines and systems, and low quality of systems logs are some limitations. Although we believe this is an important step in this field.

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This paper develops a novel approach to track power system state evolution based on the maximum correntropy criterion, due to its robustness against non-Gaussian errors. It includes the temporal aspects on the estimation process within a maximum-correntropy-based extended Kalman filter (MCEKF), which is able to deal with both nonlinear supervisory control and data acquisition (SCADA) and phasor measurement unit (PMU) measurement models. By representing the behavior of the state variables with a nonparametric model within the kernel density estimation, it is possible to include abrupt state transitions as part of the process noise with non-Gaussian characteristics. Also, a novel strategy to update the size of Parzen windows in the kernel estimation is proposed to suppress the effects of suspect samples. By properly adjusting the kernel bandwidth, the proposed MCEKF keeps its accuracy during sudden load changes and contingencies, or in the presence of bad data. Simulations with IEEE test systems and the Brazilian interconnected system are carried out. The results show that the method deals with non-Gaussian noises in both the process and measurement, and provides accurate estimates of the system state under normal and abnormal conditions.

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This paper reports on the use of property-based testing for providing feedback to C programming exercises. Test cases are generated automatically from properties specified in a test script; this not only makes it possible to conduct many tests (thus potentially find more mistakes), but also allows simplifying failed tests cases automatically. We present some experimental validation gathered for an introductory C programming course during the fall semester of 2018 that show significant positive correlations between getting feedback during the semester and the student's results in the final exam. We also discuss some limitations regarding feedback for undefined behaviors in the C language. 2012 ACM Subject Classification Social and professional topics ! Student assessment; Software and its engineering ! Software testing and debugging; Software and its engineering ! Domain specific languages.

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