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Die Erfindung betrifft ein Verfahren zum Maximieren der von einer analogen Entropiequelle abgeleiteten Entropie, wobei das Verfahren folgende Schritte aufweist:- Bereitstellen von Eingabedaten für die analoge Entropiequelle (2);- Erzeugen von Rückgabewerten durch die analoge Entropiequelle basierend auf den Eingabedaten (3); und- Gruppieren der Rückgabewerte, wobei das Gruppieren der Rückgabewerte ein Anwenden von Versätzen auf Rückgabewerte aufweist (4).
With recent developments in the Ukrainian-Russian conflict, many are discussing about Germany’s dependency on fossil fuel imports in its energy system, and how can the country proceed with reducing that dependency. With its wide-ranging consumption sectors, the electricity sector comes as the perfect choice to start with. Recent reports showed that the German federal government is already intending to have a fully renewable electricity by 2035 while exploiting all possible clean power options. This was published in the federal government’s climate emergency program (Easter Package) in early 2022. The aim of this package is to initiate a rapid transition and decarbonization of the electricity sector. The Easter Package expects an enormous growth of renewable energies to a completely new level, with already at least 80% renewable gross energy consumption, with extensive and broad deployment of different generation technologies on various scales. This paper will discuss this ambitious plan and outline some insights into this huge and rapidly increasing step, and show how much will Germany need in order to achieve this huge milestone towards a fully green supply of the electricity sector. Different scenarios and shares of renewables will be investigated in order to elaborate on preponed climate-neutral goal of the electricity sector by 2035. The results pointed out some promising aspects in achieving a 100% renewable power, with massive investments in both generation and storage technologies.
Following their success in visual recognition tasks, Vision Transformers(ViTs) are being increasingly employed for image restoration. As a few recent works claim that ViTs for image classification also have better robustness properties, we investigate whether the improved adversarial robustness of ViTs extends to image restoration. We consider the recently proposed Restormer model, as well as NAFNet and the "Baseline network" which are both simplified versions of a Restormer. We use Projected Gradient Descent (PGD) and CosPGD for our robustness evaluation. Our experiments are performed on real-world images from the GoPro dataset for image deblurring. Our analysis indicates that contrary to as advocated by ViTs in image classification works, these models are highly susceptible to adversarial attacks. We attempt to find an easy fix and improve their robustness through adversarial training. While this yields a significant increase in robustness for Restormer, results on other networks are less promising. Interestingly, we find that the design choices in NAFNet and Baselines, which were based on iid performance, and not on robust generalization, seem to be at odds with the model robustness.
State-of-the-art models for pixel-wise prediction tasks such as image restoration, image segmentation, or disparity estimation, involve several stages of data resampling, in which the resolution of feature maps is first reduced to aggregate information and then sequentially increased to generate a high-resolution output. Several previous works have investigated the effect of artifacts that are invoked during downsampling and diverse cures have been proposed that facilitate to improve prediction stability and even robustness for image classification. However, equally relevant, artifacts that arise during upsampling have been less discussed. This is significantly relevant as upsampling and downsampling approaches face fundamentally different challenges. While during downsampling, aliases and artifacts can be reduced by blurring feature maps, the emergence of fine details is crucial during upsampling. Blurring is therefore not an option and dedicated operations need to be considered. In this work, we are the first to explore the relevance of context during upsampling by employing convolutional upsampling operations with increasing kernel size while keeping the encoder unchanged. We find that increased kernel sizes can in general improve the prediction stability in tasks such as image restoration or image segmentation, while a block that allows for a combination of small-size kernels for fine details and large-size kernels for artifact removal and increased context yields the best results.
Soiling is an important issue in the renewable energy sector since it can result in significant yield losses, especially in regions with higher pollution or dust levels. To mitigate the impact of soiling on photovoltaic (PV) plants, it is essential to regularly monitor and clean the panels, as well as develop accurate soiling predictions that can affect cleaning strategies and enhance the overall performance of PV power plants. This research focuses on the problem of soiling loss in photovoltaic power plants and the potential to improve the accuracy of soiling predictions. The study examines how soiling can affect the efficiency and productivity of the modules and how to measure and predict soiling using machine learning (ML) algorithms. The research includes analyzing real data from large-scale ground-mounted PV sites and comparing different soiling measurement methods. It was observed that there were some deviations in the real soiling loss values compared to the expected values for some projects in southern Spain, thus, the main goal of this work is to develop machine learning models that could predict the soiling more accurately. The developed models have a low mean square error (MSE), indicating the accuracy and suitability of the models to predict the soiling rates. The study also investigates the impact of different cleaning strategies on the performance of PV power plants and provides a powerful application to predict both the soiling and the number of cleaning cycles.
Femtosecond (fs) time-resolved magneto-optics is applied to investigate laser-excited ultrafast dynamics of one-dimensional nickel gratings on fused silica and silicon substrates for a wide range of periodicities Λ = 400–1500 nm. Multiple surface acoustic modes with frequencies up to a few tens of GHz are generated. Nanoscale acoustic wavelengths Λ/n have been identified as nth-spatial harmonics of Rayleigh surface acoustic wave (SAW) and surface skimming longitudinal wave (SSLW), with acoustic frequencies and lifetimes being in agreement with theoretical calculations. Resonant magnetoelastic excitation of the ferromagnetic resonance (FMR) by SAW’s third spatial harmonic, and, most interestingly fingerprints of the parametric resonance at 1/2 SAW frequency have been observed. Numerical solutions of Landau–Lifshitz–Gilbert (LLG) equation magnetoelastically driven by complex polychromatic acoustic fields quantitatively reproduce all resonances at once. Thus, our results provide a solid experimental and theoretical base for a quantitative understanding of ultrafast fs-laser-driven magnetoacoustics and tailoring the magnetic-grating-based metasurfaces at the nanoscale.
Purpose
Although start-ups have gained increasing scholarly attention, we lack sufficient understanding of their entrepreneurial strategic posture (ESP) in emerging economies. The purpose of this study is to examine the processes of ESP of new technology venture start-ups (NTVs) in an emerging market context.
Design/methodology/approach
In line with grounded theory guidelines and the inductive research traditions, the authors adopted a qualitative approach involving 42 in-depth semi-structured interviews with Ghanaian NTV entrepreneurs to gain a comprehensive analysis at the micro-level on the entrepreneurs' strategic posturing. A systematic procedure for data analysis was adopted.
Findings
From the authors' analysis of Ghanaian NTVs, the authors derived a three-stage model to elucidate the nature and process of ESP Phase 1 spotting and exploiting market opportunities, Phase II identifying initial advantages and Phase III ascertaining and responding to change.
Originality/value
The study contributes to advancing research on ESP by explicating the process through which informal ties and networks are utilised by NTVs and NTVs' founders to overcome extreme resource constraints and information vacuums in contexts of institutional voids. The authors depart from past studies in demonstrating how such ties can be harnessed in spotting and exploiting market opportunities by NTVs. On this basis, the paper makes original contributions to ESP theory and practice.
Social-Media-Content - Auswirkungen auf Fear of Missing Out und den Selbstwert junger Nutzer*innen
(2023)
Social-Media-Marketing ist ein wichtiger Baustein einer erfolgreichen Content-Strategie. Insbesondere jüngere Zielgruppen sind auf Social Media anzutreffen – und das oftmals über viele Stunden täglich. Neben den Vorteilen, die Social Media den Nutzer*innen bietet, gibt es aber auch Schattenseiten. Zwei negative Aspekte, die sogenannte Fear of Missing Out und ein verminderter Selbstwert, wurden im Frühjahr 2022 in einer empirischen Befragung von 1338 Personen zwischen 14 und 30 Jahren untersucht. Daneben wurden auch Daten zum grundsätzlichen Social-Media-Nutzungsverhalten erhoben. Die zentralen Erkenntnisse, die sich aus der Studie ableiten, werden in diesem Kapitel vorgestellt und mit Bezug auf ihre Relevanz für das Content-Marketing hin eingeordnet.
Investigation on Bowtie Antennas Operating at Very Low Frequencies for Ground Penetrating Radar
(2023)
The efficiency of Ground Penetrating Radar (GPR) systems significantly depends on the antenna performance as the signal has to propagate through lossy and inhomogeneous media. GPR antennas should have a low operating frequency for greater penetration depth, high gain and efficiency to increase the receiving power and should be compact and lightweight for ease of GPR surveying. In this paper, two different designs of Bowtie antennas operating at very low frequencies are proposed and analyzed.