90 research outputs found
Fitting Spanish electricity market supply curves using bid data
No full textThe present study analyzes the supply behavior of Spain’s major electricity
generators—Axpo Iberia, Iberdrola Energ´ıa, Acciona Green Energy, and Endesa
Generaci´on—over the year 2023. Utilizing hourly bid data, polynomial curves were
fitted to capture the diverse bidding strategies employed by these generators, since
polynomial fitting provides a wider view of the market, moving beyond traditional
concentration indexes and offering a comprehensive empirical analysis of generator
behavior. By analyzing the generators’ supply curves, the study reveals a relationship between the technology mix and bidding behavior, suggesting that market
power and strategic actions can lead to inefficiencies and higher prices for consumers.
Renewable-heavy generators exhibit consistent polynomial fits, reflecting stable bidding patterns due to their reliance on renewable technologies. In contrast, generators
with varies technology mixes, display variable polynomial fits across different hours,
indicating more complex and potentially strategic bidding behaviors. This work
contributes to a deeper understanding of the supply-side dynamics in liberalized
electricity markets, with implications for market regulation and policy
Depth Light Field Training (DeLFT): NeRF as a rendering primitive
No full textNeural radiance fields (NeRF) based solutions for novel view synthesis can achieve state of the art results. Recent work proposes models that take less time to render, need less training data or take up less space. However, few papers explore the use of NeRFs in classic rendering scenarios such as rasterization, which could contribute to wider adoption. Our paper tackles the issue of shadow generation and proposes a deep residual MLP network with fast evaluation times, that generates view-dependent shadow maps. The network distills the knowledge of an existing NeRF model and achieves the speedup through the use of neural light fields, by only doing one network forward per ray.CSE3000 Research ProjectComputer Science and Engineerin
Machine-Learning for Optimal Fitness Function Selection in Automated Testing
No full textThe perpetual desire for more qualitative software has been an excellent incentive for software engineers to create automated tools to ease and improve the process of software testing. EvoSuite is an example of a state-of-the-art tool that synthesises test cases automatically. It uses a genetic algorithm to produce test cases based on given search targets. Previous studies have analysed the performance of single or combinations of targets but have not yet explored the differences between various combinations. In this research, we compare the Weak Mutation + Branch setting to Branch and the Default (combination of eight separate targets) of EvoSuite. We aim to provide insightful information about their differences in branch coverage and mutation scores. Moreover, we discuss machine-learning models that can predict which combination has the highest score (i.e., branch coverage, mutation score) based on characteristics of the tested classes, such as the number of lines of code. Our results highlight that the Weak Mutation + Branch combination outperforms Branch for the mutation score metric and Default for the branch coverage metric. They also show that Weak Mutation + Branch is outperformed by the branch criterion for Branch Coverage and by the Default combination for mutation score. Our findings also cover the performance of the models, having concluded that the Random Forest and Decision Tree classifiers produce the best results and are feasible options for predicting the best combinations from the ones analysed. Finally, static code metrics such as 'wmc', 'loc', and 'mathOperationsOty' often appear as relevant features for our models. We visualise how they influence the most suitable combination of criteria through our Decision Trees.CSE3000 Research ProjectComputer Science and Engineerin
A possible slow-slip-event in the Vrancea seismic active region of Romania
No full textIn the last 300 years the window of time for two consecutive large and destructive intermediate-depth earthquakes in Vrancea (Romania) was between 36 and 102 years. An explanation for the larger window of time might be a release of stress produced by a slow-slip-event (SSE). In a vertical sinking slab slightly attached from the Earth’s crust both large earthquakes and SSE are expected to generate a downward movement in the vertical displacements of GPS data. The building-up of stress in the asperity preventing a steady aseismic sinking was expected to be transmitted upwards to faults in the crust and recorded based on a magnetotelluric phase splitting effect. A large stress build-up has been suggested around a fault in the years 2012–2013, but no large earthquake was recorded. We supposed a large SSE in the year 2013–2014 with a duration of 13 months released the accumulated stress. GPS stations in the epicentral region of Vrancea seismic active region supported our suggestion by showing a downward displacement of vertical data obtained for the year 2014. However, the vertical displacements are small and other possible causes than SSE need to be taken into account.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Astrodynamics & Space Mission
Review of ”Brand-urile în era Web 2.0. Conținutul generat de consumatori” [Web 2.0 Brands. User-generated Content] by Rodica Săvulescu, Bucharest: Tritonic, 2016, 252 pages
No full textThe web 2.0 era has shifted brand ownership from communication specialists towards consumers. This is the main idea on which Rodica Săvulescu builds her argumentation in her recently published book, Web 2.0 Brands. User-generated content (2016). The emergence of new technologies blurs the lines between content producers and consumers. In this book, the author addresses the topic of democratization of content in relation with brand communication
INFLUENCE OF THE SIZE OF METHYLENE SPACERS ON THE THERMAL BEHAVIOR OF SEVERAL ALIPHATIC-AROMATIC POLYESTERS
No full textPolyesters have a wide range of technical applications and therefore their processing is of the utmost importance. Since polyesters are usually processed by melting, their thermal stability is an extremely important characteristic for the exact determination of the operational parameters. The thermal analysis was carried out using a MOM-Budapest derivatograph at the 10 C/min heating speed, aluminum oxide the reference material, and the air conditions were static. The study lead to conclusions on the thermal stability and degradation mechanism depending on the number of methylene groups in the spacer. Thermal stability is supported by the increase in the number of methylene groups in the spacer. The degradation mechanism is complex through successive reactions. The spacer size influences the nature of the micromolecules formed by spacer fragmenting and by the number of carbon atoms, respectively
Recent Advances in Molecularly Imprinted Polymers and Emerging Polymeric Technologies for Hazardous Compounds
No full textAddressing hazards from dangerous pollutants requires specialized techniques and risk-control strategies, including detection, neutralization and disposal of contaminants. Smart polymers, designed for specific contaminants, provide powerful solutions for hazardous compound challenges. Their remarkable performance capabilities and potential applications present exciting opportunities for further exploration and development in this field. This editorial aims to provide a comprehensive overview of smart materials with unique features and emerging polymeric technologies that are being developed for isolation, screening, removal, and decontamination of hazardous compounds (e.g., heavy metals, pharmaceutically active contaminants, hormones, endocrine-disrupting chemicals, pathogens, and energetic materials). It highlights recent advancements in synthesis methods, characterization, and the applications of molecularly imprinted polymers (MIPs), along with alternative smart polymeric platforms including hydrogels, ion-imprinted composites, screen-printed electrodes, nanoparticles, and nanofibers. MIPs offer highly selective recognition properties, reusability, long-term stability, and low production costs. Various MIP types, including particles and films, are used in applications like sensing/diagnostic devices for hazardous chemicals, biochemicals, pharmaceuticals, and environmental safety
The Insecticides Effectiveness on Tanymecus Dilaticollis Attack on Maize at NARDI Fundulea
No full textAbstractIn this paper, authors collective present effect of two pesticides applied on maize seeds (Olt variety), Gaucho 600 FS (8.0 l/tonne) and Nuprid 600 FS (8.0 l/tona) and two insecticides applied in vegetation, Calypso 480 SC (90 ml/ha) and Decis Mega (150 ml/ha) against maize leaf weevil attack, at NARDI Fundulea. Also, it performed productivity elements and seeds yields and chemical compozition on Laboratory of Yields Quality of Plant Science Department, Bucharest Faculty of Agriculture. The higher insecticides effectiveness fluctuated between 4.56 when it was applied Nuprid 600 FS and 8.33 when it was applied Calypso 480 SC.The largest attack was recorded to control plots where there is no treatment was applied. The density of plants ranged between 116 and 118 plants/plot, respectively over 65% of saved plants by treatment on seeds with both insecticides. In case of spraying insecticides in vegetation, their effect were insignificant, 31 plants/plot density and 17% saved plants in case of Calypso 480 SC and 16.75 plants/plots density and 9.31% saved plants in case of Decis Mega. The largest yields was of 7,778 kg/ha at insecticides variant with the best effectiveness and density of 65,690 plants/ha. Insecticides showed no influence on chemical composition of seeds at harvesting. But due to high temperatures and drought, the maize seeds accumulated: 12.31% protein; 70.18% starch; 5.05% oil; 1.46% ash; 5.24% fibre
Serverless is More: From PaaS to Present Cloud Computing
No full textIn the late-1950s, leasing time on an IBM 704 cost hundreds of dollars per minute. Today, cloud computing, that is, using IT as a service, on-demand and pay-per-use, is a widely used computing paradigm that offers large economies of scale. Born from a need to make platform as a service (PaaS) more accessible, fine-grained, and affordable, serverless computing has garnered interest from both industry and academia. This article aims to give an understanding of these early days of serverless computing: what it is, where it comes from, what is the current status of serverless technology, and what are its main obstacles and opportunities.Accepted author manuscriptData-Intensive System
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