Abstract
A Community of Practice (CoP) allows practitioners of a clearly defined domain to share knowledge, experience, and best practices. It provides a social context for practitioners, often distributed across multiple organizations, and emerged over the last few decades as a fundamental mechanism for knowledge sharing, management, and generation within organizations. Best practices, innovations, and solutions to shared problems first emerge within CoPs. These are, and must be perceived as, an investment in organizations' future and competitiveness. Establishing a CoP is a straightforward process, the most challenging factor being the recruitment of members to attain critical mass. The challenge is to maintain the CoP active, with members contributing with high quality, innovative content. Increasing a CoP's medium / long-term survival probabilities requires careful planning to avoid incurring in some well-known pitfalls. This paper proposes and discusses a set of nine guidelines for establishing and maintaining a community of practice within the context of Electronic Governance (EGOV) and Government Chief Information Officers (GCIO). This research was motivated by the initiative of the government of a developing country. Results are based on a review of the relevant literature, together with the detailed analysis of interviews to members or coordinators of large communities of practice. This analysis was further validated against the opinions of public servants directly involved on EGOV-GCIO-related functions during two focus groups meetings. © 2018 Association for Computing Machinery.

Abstract
Many real-world phenomena exhibit both relational structure and uncertainty. Probabilistic Inductive Logic Programming (PILP) uses Inductive Logic Programming (ILP) extended with probabilistic facts to produce meaningful and interpretable models for real-world phenomena. This merge between First Order Logic (FOL) theories and uncertainty makes PILP a very adequate tool for knowledge representation and extraction. However, this flexibility is coupled with a problem (inherited from ILP) of exponential search space growth and so, often, only a subset of all possible models is explored due to limited resources. Furthermore, the probabilistic evaluation of FOL theories, coming from the underlying probabilistic logic language and its solver, is also computationally demanding. This work introduces a prediction-based pruning strategy, which can reduce the search space based on the probabilistic evaluation of models, and a safe pruning criterion, which guarantees that the optimal model is not pruned away, as well as two alternative more aggressive criteria that do not provide this guarantee. Experiments performed using three benchmarks from different areas show that prediction pruning is effective in (i) maintaining predictive accuracy for all criteria and experimental settings; (ii) reducing the execution time when using some of the more aggressive criteria, compared to using no pruning; and (iii) selecting better candidate models in limited resource settings, also when compared to using no pruning. © Joana Côrte-Real, Anton Dries, Inês Dutra, and Ricardo Rocha; licensed under Creative Commons License CC-BY

Abstract
Cloud software continues to expand globally, highly motivated by how widespread the Internet is and the possibilities it unlocks with cloud computing. Still, cloud development has some intrinsic properties to it, making it complex to unexperienced developers. This research is capturing those intricacies in the form of a pattern language that gathers ten patterns for engineering software for the cloud. This paper elaborates on that research by contributing with two new patterns: Automated Recovery, which checks if a container is working properly, automatically recovering it in case of failure and Scheduler, which periodically executes actions within the infrastructure. The described patterns are useful for anyone designing software for the cloud, either to bootstrap or to validate their design decisions with the end goal of enabling them to create better software for the cloud.

Abstract
Customer relationship management is critical for organizations. The public institutions, in particular the municipalities, are not an exception to this fact. However, these institutions have a number of peculiarities, as such their systems must be appropriate to their specific reality. In this article are presented the fundamental concepts of CRM (Customer Relationship Management) and CzRM (Citizen Relationship Management), discussing the distinctive characteristics of municipalities regarding other organizations.

Abstract
This paper describes the design of an electromagnetic interference (EMI) filter for the high-frequency link matrix converter (HFLMC). The proposed method aims to systematize the design process for pre-compliance with CISPR 11 Class B standard in the frequency range 150 kHz to 30 MHz. This approach can be extended to other current source converters which allows time-savings during the project of the filter. Conducted emissions are estimated through extended simulation and take into account the effect of the measurement apparatus. Differential-mode (DM) and common-mode (CM) filtering stages are projected separately and then integrated in a synergistic way in a single PCB to reduce volume and weight. A prototype of the filter was constructed and tested in the laboratory. Experimental results with the characterization of the insertion losses following the CISPR 17 standard are provided. The attenuation capability of the filter was demonstrated in the final part of the paper.

Abstract
Cloud software continues to expand globally, highly motivated by how widespread the Internet is and the possibilities it unlocks with cloud computing. Still, cloud development has some intrinsic properties to it, making it complex to unexperienced developers. This research is capturing those intricacies in the form of a pattern language, gathering ten patterns for engineering software for the cloud. This paper elaborates on that research by contributing with two new patterns: External Monitoring, which continuously monitors the system as a black box, validating its status and Failure Injection, which continuously verifies system reliability by injecting failures into the cloud environment and confirming that the system recovers from it. The described patterns are useful for anyone designing software for the cloud, either to bootstrap or to validate their design decisions with the end goal of enabling them to create better software for the cloud.