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[Context] The continuous inflow of bug reports is a considerable challenge in large development projects. Inspired by contemporary work on mining software repositories, we designed a prototype bug assignment solution based on machine learning in 2011-2016. The prototype evolved into an internal Ericsson product, TRR, in 2017-2018. TRR’s first bug assignment without human intervention happened in A
The X-ray flux provided by X-ray free-electron lasers and storage rings offers new spatiotemporal possibilities to study in-situ and operando dynamics, even using single pulses of such facilities. X-ray Multi-Projection Imaging (XMPI) is a novel technique that enables volumetric information using single pulses of such facilities and avoids centrifugal forces induced by state-of-the-art time-resolv
Auger recombination is a pivotal process for semiconductor nanocrystals (NCs), significantly affecting charge carrier generation and collection in optoelectronic devices. This process depends mainly on the NCs’ electronic structures. In our study, we investigated Auger recombination dynamics in manganese (Mn2+)-doped CsPbI3 NCs using transient absorption (TA) spectroscopy combined with theoretical
Bragg coherent X-ray diffraction imaging (BCDI) has emerged as a powerful technique for strain imaging and morphology reconstruction of nanometre-scale crystals. However, BCDI often suffers from angular distortions that appear during data acquisition, caused by radiation pressure, heating or imperfect scanning stages. This limits the applicability of BCDI, in particular for small crystals and high
Effectively identifying deviations in real-world medical time-series data is a critical endeavor, essential for early surveillance of disease outbreaks. This paper demonstrates the integration of time-series anomaly detection techniques to develop surveillance systems for disease outbreaks. Utilizing data from Sweden's telephone counseling service (1177), we first illustrate the trends in physical
With the dynamic nature of modern software development and operations environments and the increasing complexity of cloud-based software systems, traditional monitoring practices are often insufficient to timely identify and handle unexpected operational failures. To address these challenges, this paper presents the findings from a quantitative industry survey focused on the application of Machine
Oxygen-defective metal oxides like cerium oxides exhibit giant electrostriction and field-induced piezoelectricity due to a dynamic electrosteric interplay between oxygen defects, V O ⋅ ⋅ , and the fluorite lattice. While such mechanisms are generally attributed to oxygen vacancies, recent results also highlight that trapped cationic defects, Ce Ce ′ , i.e. small polarons, can contribute to the el
The double quantum coherence (DQC) signal in nonlinear spectroscopy gives information about the many-body correlation effects not easily available by other methods. The signal is short-lived, consequently, a significant part of it is generated during the pulse overlap. Since the signal is at two times the laser frequency, one may intuitively expect that the pulse overlap-related artifacts are filt
Hur går det till när besluts fattas om huruvida, när och vart ett barn eller en ungdom ska placeras i samhällsvård och vad händer med detta beslutsfattande när ärendetrycket ökar på organisationen? Den brittiske barnavårdsforskaren Nigel Parton (1998), bland andra, har hävdat att när trycket ökar och resurser blir färre inom människobehandlande organisationer som Socialtjänsten, är en vanlig reakt
Non-linear transceivers and non-reciprocity of downlink and uplink channels are two major challenges in the deployment of massive multiple-input-multiple-output (MIMO) systems. We consider an over-the-air (OTA) approach for digital pre-distortion (DPD) and reciprocity calibration to jointly address these issues. In particular, we consider a memory-less non-linearity model for the base station (BS)
Despite extensive research on Quality-of-Services (QoS) analysis of 5G networks, practical applications remain limited. This gap may be attributed to the lack of available tools and the complexity of developing or configuring technical systems to implement theoretical approaches. To address this, we developed an edge control system within a private 5G base station, utilizing Precision Time Protoco
Federated Learning (FL) enables decentralized training of neural networks across multiple hospitals or patients while preserving data privacy. However, FL schemes typically assume data is independent and identically distributed (IID) while healthcare data can be highly heterogeneous. To address this, we propose Interpretable Personalized Federated Learning (IPFL), a novel framework that allows pat
Ferroelectric thin films present a powerful platform for next-generation computing and memory applications. However, domain morphology and dynamics in buried ferroelectric stacks have remained underexplored, despite their importance for real device performance. Here, nanoprobe X-ray diffraction (nano-XRD) is used to image ferroelectric domains inside BiFeO3-based capacitors, revealing local disord
The use of large language models (LLMs) is being explored for a multitude of tasks in software engineering (SE), ranging from code generation to bug report assignment. Although LLMs provide impressive results, they require more time and energy than some other machine learning models. For some tasks, simpler models may be more sustainable than LLMs. In this paper, we construct natural language clas
