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The emerging 5G networks promises more throughput, faster, and more reliable services, but as the network complexity and dynamics increases, it becomes more difficult to troubleshoot the systems. Vendors are spending a lot of time and effort on early anomaly detection in their development cycle and majority of the time is spent on manually analyzing system logs. While main research in anomaly detection uses performance metrics, anomaly detection using functional behaviour is still lacking in depth analysis. In this paper we show how a boosted ensemble of Long Short Term Memory classifiers can detect anomalies in the 5G Radio Access Network system logs. Acquiring system logs from a live 5G network is difficult due to confidentiality issues, live network disturbance, and problems to repeat scenarios. Therefore, we perform our evaluation on logs from a 5G test bed that simulate realistic traffic in a city. Our ensemble learns the functional behaviour of an application by training on logs from normal execution time. It can then detect deviations from normal behaviour and also be retrained on false positive cases found during validation. Anomaly detection in RAN shows that our ensemble called BoostLog, outperforms a single LSTM classifier and further testing on HDFS logs confirms that BoostLog also can be used in other domains. Instead of using domain experts to manually analyse system logs, BoostLog can be used by less experienced trouble shooters to automatically detect anomalies faster and more reliable.

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Naegleria fowleri causes the usually fatal disease primary amebic meningoencephalitis (PAM), typically in people who have been swimming in warm, untreated freshwater. Recently, some cases in the United States were associated with exposure to treated drinking water. In 2013, a case of PAM was reported for the first time in association with the exposure to water from a US treated drinking water system colonized with culturable N. fowleri. This system and another were found to have multiple areas with undetectable disinfectant residual levels. In response, the water distribution systems were temporarily converted from chloramine disinfection to chlorine to inactivate N. fowleri and reduced biofilm in the distribution systems. Once >1.0 mg/L free chlorine residual was attained in all systems for 60 days, water testing was performed; N. fowleri was not detected in water samples after the chlorine conversion. This investigation highlights the importance of maintaining adequate residual disinfectant levels in drinking water distribution systems. Water distribution system managers should be knowledgeable about the ecology of their systems, understand potential water quality changes when water temperatures increase, and work to eliminate areas in which biofilm growth may be problematic and affect water quality.

A method is proposed for HCF-analysis that is suitable for use in early design stages of turbomachinery blades. Quantitative measures of the risk for later encountering HCF life limiting vibrations are the goal for the development. The novelty of the system is the unique and rational way all design data are processed resulting in a mode risk priority listing. The method makes extensive use of FE calculated modal analyses and simple assumptions on the modal force and damping. The modal force is taken proportional to the tangential force on the blade over the operating range. This choice is made because the tangential force is known early on from the compressor performance map, and gives a reasonable scaling with the operating point. Crossings occurring at low speed get a lower force than at high speed. The system damping used is a constant critical damping ratio. Using a modal force and damping along with the FE model forced response amplitude can be directly computed at resonance crossings inside operating envelope. The modal force calculated this way can be compared to the force amplitude needed to reach the fatigue limit in a Haigh diagram. Using the Haigh diagram this way allows modes with localized high stresses, so-called hot spots, to be highlighted. Taking the ratio of the forces gives a ranking value that can be used to compare risk. Details of the technique along with example applications to compressor blades are presented in the paper. It is found that many mode crossings can be excluded as low risk this way and that a rational way of prioritizing is achieved.