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1021 research outputs found
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Charging scheduling of hybrid energy storage systems for EV charging stations
No full textThe growing demand for electric vehicles (EV) in the last decade and the most recent European Commission regulation to only allow EV on the road from 2035 involved the necessity to design a cost-effective and sustainable EV charging station (CS). A crucial challenge for charging stations arises from matching fluctuating power supplies and meeting peak load demand. The overall objective of this paper is to optimize the charging scheduling of a hybrid energy storage system (HESS) for EV charging stations while maximizing PV power usage and reducing grid energy costs.
This goal is achieved by forecasting the PV power and the load demand using different deep learning (DL) algorithms such as the recurrent neural network (RNN) and long short-term memory (LSTM). Then, the predicted data are adopted to design a scheduling algorithm that determines the optimal charging time slots for the HESS. The findings demonstrate the efficiency of the proposed approach, showcasing a root-mean-square error (RMSE) of 5.78% for real-time PV power forecasting and 9.70%
for real-time load demand forecasting. Moreover, the proposed scheduling algorithm reduces the total grid energy cost by 12.13%
Dimension-independent spectral gap of polar slice sampling
No full textPolar slice sampling, a Markov chain construction for approximate sampling, performs, under suitable assumptions on the target and initial distribution, provably independent of the state space dimension. We extend the aforementioned result of Roberts and Rosenthal (Stoch Model 18(2):257–280, 2002) by developing a theory which identifies conditions, in terms of a generalized level set function, that imply an explicit lower bound on the spectral gap even in a general slice sampling context. Verifying the identified conditions for polar slice sampling yields a lower bound of 1/2 on the spectral gap for arbitrary dimension if the target density is rotationally invariant, log-concave along rays emanating from the origin and sufficiently smooth. The general theoretical result is potentially applicable beyond the polar slice sampling framework
Automated test generation for SCRATCH programs
No full textThe importance of programming education has led to dedicated educational program-
ming environments, where users visually arrange block-based programming constructs that typically control graphical, interactive game-like programs. The SCRATCH programming environment is particularly popular, with more than 90 million registered users at the time of this writing. While the block-based nature of S CRATCH helps learners by preventing syntactical mistakes, there nevertheless remains a need to provide feedback and support in order to implement desired functionality. To support individual learning and classroom settings, this feedback and support should ideally be provided in an automated fashion, which requires tests to enable dynamic program analysis. In prior work we introduced W HISKER , a framework that enables automated testing of S CRATCH programs. However, creating these automated tests for S CRATCH programs is challenging. In this paper, we therefore investigate how to automatically generate W HISKER tests. Generating tests for S CRATCH raises important challenges: First, game-like programs are typically randomised, leading to flaky tests. Second, S CRATCH programs usually consist of animations and interactions with long delays, inhibiting the application of classical test generation approaches. Thus, the new application domain raises the question of which test generation technique is best suited
to produce high coverage tests capable of detecting faulty behaviour. We investigate these questions using an extension of the W HISKER test framework for automated test generation. Evaluation on common programming exercises, a random sample of 1000 S CRATCH user programs, and the 1000 most popular S CRATCH programs demonstrates that our approach enables W HISKER to reliably accelerate test executions, and even though many SCRATCH programs are small and easy to cover, there are many unique challenges for which advanced search-based test generation using many-objective algorithms is needed in order to achieve high coverage
Growth of log-analytic functions
No full textWe show that unary log-analytic functions are polynomially bounded. In the higher dimensional case, globally a log-analytic function can have exponential growth. We show that a log-analytic function is polynomially bounded on a definable set which contains the germ of every ray at infinity
Datenbankherstellerrecht und Datenbankforschung
No full textIn diesem Übersichtsartikel stellen wir das Datenbankherstellerrecht vor. Hierbei handelt es sich nicht, wie man aus dem
Blickwinkel eines juristischen Laien und Mitglied der Datenbankforschungsgemeinde meinen könnte, um die Rechte bei der Entwicklung einer Datenbankmanagementsoftware, sondern um die Rechte des Herstellers einer Datenbankinstanz. Auch Forschende oder Forschungsinstitutionen werden beim Forschungsdatenmanagement zu Datenbankherstellern, ins-
besondere wenn sie Forschungsartefakte verfügbar machen. Somit gewinnt die zugrundeliegende EU-Richtlinie aus den 1990er-Jahren an neuer Brisanz.
Unser Beitrag gibt einen systematischen Überblick über den rechtlichen Schutz der einzelnen Komponenten einer Datenbankanwendung. Insbesondere stellen wir das Datenbankherstellerrecht und praktische Anwendungsfälle vor, sowie anknüpfende Forschungsfragen
On nation, homeland, and democracy: Toward a novel three-factor measurement model for nationalism and patriotism. Evidence from two representative studies
No full textThis article calls for revisiting the predominant yet flawed nationalism-patriotism dichotomy, which has to date remained unchallenged. It advocates for a more nuanced triad: nationalism, exclusively referring to the nation; patriotism, revolving around the homeland; and democratic patriotism, with democracy as its object of attachment. This novel conceptual approach explicitly theorizes these three objects of attachment, which have hitherto rarely been considered. In so doing, the article synthesizes the field's predominant research traditions that have not been fully recognized as diverging nor been simultaneously investigated. By responding to calls for more theoretically robust measures, it not only makes a theoretical but also an empirical contribution to the field. Drawing on data from a representative sample (N = 1875) in Germany in 2022, the study introduces a three-factor measurement model of nationalism, patriotism, and democratic patriotism. Taking into account both the antecedents of the triad and its impact on outgroup hostility, the measures are further validated. To establish its applicability in non-German contexts, the model is additionally supported using data from a representative sample (N = 1164) in Denmark in 2022
Mutual desecuritization as a model of détente? Foreign policy change in the US-Cuban dyad
No full textIn foreign policy dyads characterized by enmity, mutual desecuritization can serve as a crucial asset for détente. But how does “the way out of the emergency mode” function, considering mutual securitizations over decades? Embarking from theoretical insights provided by second generation scholars on securitization and desecuritization studies, the authors generate a theory-based model of détente for dyads. This analytical tool contributes to the study of the dissolution of historically grown, mutual (re-)securitization processes in interstate relations. By clarifying the impact and functioning of the four desecuritizing modes (replacement, silencing, change through stabilization, and rearticulation), our model allows us to trace dynamics of change and assess the sustainability of détente. Especially mutual desecuritization as rearticulation has the potential to substantially change the self-other relation with effects on the social structure of a foreign policy dyad. The heuristic case study of US-Cuban relations serves as a prime example of a complex dyad of enmity which became a subject of change due to the Obama–Castro diplomacy in 2014. The study on US-Cuban foreign policy issues before and after 2014 helps to sharpen our understanding of dynamic securitization and desecuritization processes. The overall analysis demonstrates that the modes of desecuritization during the Obama–Castro diplomacy lifted the process of détente to a new and unprecedented level
Performance analysis of large language models in the domain of legal argument mining
No full textGenerative pre-trained transformers (GPT) have recently demonstrated excellent performance in various natural language tasks. The development of ChatGPT and the recently released GPT-4 model has shown competence in solving complex and higher-order reasoning tasks without further training or fine-tuning. However, the applicability and strength of these models in classifying legal texts in the context of argument mining are yet to be realized and have not been tested thoroughly. In this study, we investigate the effectiveness of GPT-like models, specifically GPT-3.5 and GPT-4, for argument mining via prompting. We closely study the model's performance considering diverse prompt formulation and example selection in the prompt via semantic search using state-of-the-art embedding models from OpenAI and sentence transformers. We primarily concentrate on the argument component classification task on the legal corpus from the European Court of Human Rights. To address these models' inherent non-deterministic nature and make our result statistically sound, we conducted 5-fold cross-validation on the test set. Our experiments demonstrate, quite surprisingly, that relatively small domain-specific models outperform GPT 3.5 and GPT-4 in the F1-score for premise and conclusion classes, with 1.9% and 12% improvements, respectively. We hypothesize that the performance drop indirectly reflects the complexity of the structure in the dataset, which we verify through prompt and data analysis. Nevertheless, our results demonstrate a noteworthy variation in the performance of GPT models based on prompt formulation. We observe comparable performance between the two embedding models, with a slight improvement in the local model's ability for prompt selection. This suggests that local models are as semantically rich as the embeddings from the OpenAI model. Our results indicate that the structure of prompts significantly impacts the performance of GPT models and should be considered when designing them
Three Essays on Brand Management in the Business-to-Business Context: Brand Identity, Brand Culture, and Brand Essence
No full textThis dissertation examines the overarching research question of how the suppliers’ brand management in the form of brand identity, brand culture, and brand essence influences buyer-seller relationships in three independent essays.
In Essay 1, I address the structure, capabilities, and outcomes of brand identity from a supplier perspective. Through qualitative interviews with suppliers, I examine how widespread the concept of brand identity is in practice and what exactly practitioners understand by it. Going further, I look at what capabilities and conditions are necessary for brand identity to be successful and what outcomes suppliers hope to achieve. Using an Information-Display-Matrix (IDM) test and a sample of Master of Business Administration (MBA) students, I examine the relevance of brand functions in more detail.
In Essay 2, I use a dyadic dataset with matched buyer-seller dyads to examine the causes and effects of perceptual congruence and incongruence of brand culture strength on the buyer-seller relationship, while considering relationship-specific investments and interaction mechanisms as moderating effects. I show that congruence and incongruence have different effects on customer loyalty and price sensitivity and that these are strongly context-dependent.
In Essay 3, I deal with brand essence strength interactions and their effects on the buyer-seller relationship. I use a dyadic dataset with matched buyer-seller dyads to show how brand essence strength influences customer loyalty and customer profitability, and how it interacts with key customer attitudes and other important buyer-seller relationship closeness indicators.
This dissertation makes a significant contribution to the literature on brand identity, brand culture, and brand essence in buyer-seller relationships. Furthermore, my dissertation offers practical implications for managers at B2B suppliers who (re)shape their brand management with a focus on the inner parts of the brand
Qualität von Prozessmodellen - Entwicklung eines Ordnungsrahmens zur Analyse, Klassifikation und Bestimmung der Qualitätsanforderungen an Prozessmodelle
No full textDie vorliegende Dissertation behandelt die Qualität von Prozessmodellen.
Vor diesem Hintergrund haben Experteninterviews mit Forschungs- und Praxispartnern zur Entwicklung und Evaluierung eines Ordnungsrahmens zur Qualitätsbestimmung von Prozessmodellen beigetragen.
Die Ergebnisse zeigen, dass unter anderem die Einsatzzwecke der Prozessmodelle sowie die mit den Prozessmodellen in Berührung kommenden Personengruppen differenziert betrachtet werden müssen, um Auswirkungen auf die Prozessmodellqualität untersuchen zu können