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This paper presents a stabilized scheme that solves the wave propagation problem in a general bianisotropic, stratified medium. The method utilizes the concept of propagators, i.e., the wave propagation operators that map the total tangential electric and magnetic fields from one plane in the slab to another. The scheme transforms the propagator approach into a scattering matrix form, where a spec

We are currently witnessing the second wave of cloud services that go beyond web storefronts and IT systems, aiming for digitalization of industrial systems. Automation and time-sensitive systems are now taking their first steps toward the cloud. The AORTA project aims to facilitate this transition by providing key technology components needed for real-time services running in the cloud. The ambit

Monitoring a microservice system may bring a lot of benefits to development teams such as early detection of run-time errors and various performance anomalies. In this study, we explore deep learning (DL) solutions for detection of anomalous system's behavior based on collected monitoring data that consists of applications' and systems' performance metrics. The study is conducted in a collaboratio

There is a growing interest in industry and academia in machine learning (ML) testing. We believe that industry and academia need to learn together to produce rigorous and relevant knowledge. In this study, we initiate a collaboration between stakeholders from one case company, one research institute, and one university. To establish a common view of the problem domain, we applied an interactive r

In this paper, we propose the first key-recovery side-channel attack on Classic McEliece, a KEM finalist in the NIST Post-quantum Cryptography Standardization Project. Our novel idea is to design an attack algorithm where we submit special ciphertexts to the decryption oracle that correspond to cases of single errors. Decoding of such ciphertexts involves only a single entry in a large secret perm

The Learning with Errors (LWE) problem receives much attention in cryptography, mainly due to its fundamental significance in post-quantum cryptography. Among its solving algorithms, the Blum-Kalai-Wasserman (BKW) algorithm, originally proposed for solving the Learning Parity with Noise (LPN) problem, performs well, especially for certain parameter settings with cryptographic importance. The BKW a

This paper presents simulations of the radar cross section for a marine corner reflector affected by icing as it is illuminated by 3 GHz marine radar. This is compared to the radar cross section for an unaffected reflector, and the consequences for radar range are investigated. To perform the simulations, a finite element-boundary integral hybrid method is used. The simulation code is based on sev

Previous research on A/B testing and continuous experimentation has mostly focused on large-scale settings with company-external customers. However, work efficiency and satisfaction for company coworkers may be highly related to internal tools and their fit-for-use. In this study, we therefore explore A/B testing for online services exclusively used by company co-workers. We A/B tested two version

Automated testing is a safeguard against software regression and provides huge benefits. However, it is yet a challenging subject. Among others, there is a risk that the test cases are too specific, thus making them inefficient. There are many forms of undesirable behaviour that are compatible with a typical program’s specification, that however, harm users. An efficient test should provide most p

Nondestructive testing of composite materials is important in aerospace applications, and mm-wave imaging has been increasingly used for this purpose. Imaging is traditionally performed using Fourier methods, with inverse methods being an alternative. This communication presents a mm-wave imaging method with an inverse approach intended for nondestructive testing of singly curved composite panels

When people are conversing, a key non-verbal aspect of communication is the direction in which the participants are looking, as this may convey where each person’s attention is focused. In a programming context, for instance an integrated development environment (IDE), the interaction design frequentlydirects the programmer’s gaze towards specific locations on-screen. For example, syntax highlight

A coworker teased me a few months ago, describing requirements engineering (RE) as "plumbing,"something he absolutely considered functional, even necessary, but otherwise best not discussed in polite conversation. I responded with a graphically descriptive suggestion of what one might experience with a plumbing failure. I then drew parallels to a situation where a team's excellent execution of the

Large intelligent surfaces (LISs) is an evolution of massive MIMO systems allowing for huge capacity gains. To reduce implementation complexity, it is convenient to implement the LIS using panels that are either activated or deactivated, and associated to terminals according to their propagation characteristics to the panels. The associated spatial resource allocation to maximise the terminals', a

While Weighted Lasso sparse regression has appealing statistical guarantees that would entail a major real-world impact in finance, genomics, and brain imaging applications, it is typically scarcely adopted due to its complex high-dimensional space composed by thousands of hyperparameters. On the other hand, the latest progress with high-dimensional hyperparameter optimization (HD-HPO) methods for

In embedded computing domains, including the automotive industry, complex functionalities are split across multiple tasks that form task chains. These tasks are functionally dependent and communicate partial computations through shared memory slots based on the Logical Execution Time (LET) paradigm. This paper introduces a model that captures the behavior of a producer-consumer pair of tasks in a

Automated fault diagnosis can facilitate diagnostics assistance, speedier troubleshooting, and better-organised logistics. Currently, most AI-based prognostics and health management in the automotive industry ignore textual descriptions of the experienced problems or symptoms. With this study, however, we propose an ML-assisted workflow for automotive fault nowcasting that improves on current indu