The fast wavelet transform is an important workhorse in signal processing. Wavelets are local in the spatial- or temporal- and the frequency-domain. This property enables frequency domain analysis while preserving som...
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The fast wavelet transform is an important workhorse in signal processing. Wavelets are local in the spatial- or temporal- and the frequency-domain. This property enables frequency domain analysis while preserving some spatiotemporal information. Until recently, wavelets rarely appeared in the machine learning literature. We provide the PyTorch Wavelet Toolbox to make wavelet methods more accessible to the deep learning community. Our PyTorch Wavelet Toolbox is well documented. A pip package is installable with pip install ptwt.
Pipeline transport is an efficient method for transporting fluids in energy supply and other technical applications. While natural gas is the classical example, the transport of hydrogen is becoming more and more impo...
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The data steward, responsible for overseeing data management, plays a pivotal role in evidence-based medicine by ensuring the quality, integrity, and accessibility of data throughout its lifecycle. However, managing m...
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In this paper, the modeling of gas compressors with detailed representation of their calibrated characteristics is considered. A method is developed for transforming the characteristics from the space of calibration d...
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In 2020, around 44% of natural gas in Germany was used in combined heat and power as well as in combined cycle gas turbines plants. As district heating will play an important role in future heating planning, the retro...
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In this paper, a cosmological model is considered, in which dark matter is emitted by T-symmetric quasi-black holes distributed over galaxies. Low energy photons and neutrinos are taken as candidates for dark matter p...
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This paper is a continuation of our recent work on Radial Dark Matter stars (RDM-stars), black holes, coupled with radial flows of dark matter. As a galaxy model, it produces flat rotation curves, approximately valid ...
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In general relativity, there is a class of solutions that currently do not have observed analogues, but on which the theory is shaped, giving an understanding what is fundamentally possible within its framework. Such ...
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This work continues the construction of a recently proposed model of dark matter stars. In this model, dark matter quanta are sterile massless particles that are emitted from the central regions of the galaxy in the r...
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While projects, developments and applications addressing and using artificial intelligence (AI) are rather multifaceted and their number is constantly increasing, the standardisation activities in the field of artific...
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While projects, developments and applications addressing and using artificial intelligence (AI) are rather multifaceted and their number is constantly increasing, the standardisation activities in the field of artificial intelligence are limited, their number is significantly lower and does not increase at the same pace. The European funded project *** aims at supporting European experts' presence in and contributions to international standardisation activities in ICT. The focus of the project is on the 5 priority domains identified by the European Commission (Cloud computing, IoT, Big Data, Cyber Security, 5G) and on Artificial Intelligence while being open for other relevant topics defined in the annual European Rolling Plan for ICT Standardisation. The project has two main outcomes: (i) increased contribution of European experts in international standardisation through support by providing grants for planned contributions of successful applications of experts, and (ii) an online observatory of published standards and ongoing standardisation activities in the areas mentioned before. This observatory (called Standards Watch) is accessible through the project's web site and open for contributions and comments from registered users. As part of the effort for the Standards Watch the projects has prepared a comprehensive analysis of the international standardisation landscape in the AI field, that comprises a description of the ICT standards and ongoing work at international level in the field of AI across the standardisation organisations already active in the field. In this article we will present results of our work where we have analysed the work of the 5 international and European Standards Development Organisations (SDOs) IEEE,1 ISO/IEC,2 ITU-T,3 ETSI4 and CEN-CENELEC5 developing standards in the field of AI. The first 4 bodies have already been active several years in AI standardisation at the time of writing this article. CEN-CENELEC has launched a focu
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