Impact of log parsing on deep learning-based anomaly detection.

Software systems log massive amounts of data, recording important runtime information. Such logs are used, for example, for log-based anomaly detection, which aims to automatically detect abnormal behaviors of the system under analysis by processing the information recorded in its logs. Many log-based anomaly detection techniques based on deep learning models include a pre-processing step called log parsing.

PRINS: scalable model inference for component-based system logs.

Behavioral software models play a key role in many software engineering tasks; unfortunately, these models either are not available during software development or, if available, quickly become outdated as implementations evolve. Model inference techniques have been proposed as a viable solution to extract finite state models from execution logs. However, existing techniques do not scale well when processing very large logs that can be commonly found in practice.

Aqueous solution/metal interfaces investigated in operando by photoelectron spectroscopy.

We describe a new in operando approach for the investigation of heterogeneous processes at solid/liquid interfaces with elemental and chemical specificity which combines the preparation of thin liquid films using the meniscus method with standing wave ambient pressure X-ray photoelectron spectroscopy [Nemšák et al., Nat. Commun.

Commissioning and quality assurance of an integrated system for patient positioning and setup verification in particle therapy.

In an increasing number of clinical indications, radiotherapy with accelerated particles shows relevant advantages when compared with high energy X-ray irradiation. However, due to the finite range of ions, particle therapy can be severely compromised by setup errors and geometric uncertainties. The purpose of this work is to describe the commissioning and the design of the quality assurance procedures for patient positioning and setup verification systems at the Italian National Center for Oncological Hadrontherapy (CNAO).