Nicht ermittelbar
Refine
Year of publication
Document Type
- Article (111)
- Monograph/Edited Volume (100)
- Part of a Book (75)
- Conference Proceeding (43)
- Other (13)
- Doctoral Thesis (9)
- Review (8)
- Working Paper (8)
- Report (5)
- Postprint (2)
- Preprint (1)
Language
- English (375) (remove)
Keywords
- social media (6)
- artificial intelligence (5)
- coordination (4)
- cyber-physical systems (4)
- digitalization (4)
- machine learning (4)
- maschinelles Lernen (4)
- probabilistic timed systems (4)
- qualitative Analyse (4)
- qualitative analysis (4)
Institute
- Fachgruppe Betriebswirtschaftslehre (65)
- Fachgruppe Politik- & Verwaltungswissenschaft (47)
- Institut für Mathematik (47)
- Hasso-Plattner-Institut für Digital Engineering GmbH (24)
- Institut für Informatik und Computational Science (23)
- Öffentliches Recht (20)
- Institut für Anglistik und Amerikanistik (18)
- Wirtschaftswissenschaften (16)
- Institut für Physik und Astronomie (12)
- Department Musik und Kunst (11)
Molecular modeling calculations using DFT at the B3LYP/6-31G(d,p) level of theory have been performed on diastereomeric complexes formed between chiral carboxylate anions and chiral urea receptors, a combination previously demonstrated to enable enantiodifferentiation by electrochemical sensing. The calculations correctly predicted the stability order of the enantiomers in acetonitrile solution when the distinction between the enantiomers was above the declared threshold reliability value of 1 kcal mol;1 for computations at this level of theory. Thus, the calculations can not only be applied to predict the likely success of undertakings using the analytical method, it can also, provided ;E is sufficient, potentially be used to determine the absolute configuration of chiral analytes with at least the racemate in hand. The previously successful enantiodifferentiations of various amino acids and alcohols using chiral ion mobility spectroscopy (CIMS) with (S)-2-butanol as the chiral selector were also evaluated by DFT calculations. The calculations again correctly predicted the stability order of the enantiomers when the calculated ;E was above the threshold value though cases not providing a value for ;E above the threshold value was problematic for this system. Attempts to address this shortcoming included an expanded conformational evaluation, a broader analytical approach, and an extended basis set.
Developmental expression of a tyramine receptor gene in the brain of the honey bee, Apis mellifera
(2005)
After some seventy years of intensive debates, there is an increasingly strong consensus within the academic and practitioner communities that development is both an objective and a process towards improving the quality of people's lives in various societal dimensions – economic, social, environmental, cultural and political – and about how subjectively satisfied they are with it. Since 2015, the seventeen Sustainable Development Goals (SDGs) of the United Nations (UN) reflect such consensus. The sections behind this argument are based on a review of (i) three key theoretical contributions to development and different phases of development thinking; (ii) global and regional governance arrangements and institutions for development cooperation; (iii) upcoming challenges to development policy and practice stemming from a series of new global challenges; and, (iv) development policy as a long and steady, increasingly global and participatory learning process.
Developing a new paradigm
(2020)
Internet users commonly agree that it is important for them to protect their personal data. However, the same users readily disclose their data when requested by an online service. The dichotomy between privacy attitude and actual behaviour is commonly referred to as the “privacy paradox”. Over twenty years of research were not able to provide one comprehensive explanation for the paradox and seems even further from providing actual means to overcome the paradox. We argue that the privacy paradox is not just an instantiation of the attitude-behaviour gap. Instead, we introduce a new paradigm explaining the paradox as the result of attitude-intention and intentionbehaviour gaps. Historically, motivational goal-setting psychologists addressed the issue of intentionbehaviour gaps in terms of the Rubicon Model of Action Phases and argued that commitment and volitional strength are an essential mechanism that fuel intentions and translate them into action. Thus, in this study we address the privacy paradox from a motivational psychological perspective by developing two interventions on Facebook and assess whether the 287 participants of our online experiment actually change their privacy behaviour. The results demonstrate the presence of an intentionbehaviour gap and the efficacy of our interventions in reducing the privacy paradox.
Defining britishhness from the margins : Peter Weir's gallipoli and hugh hudson's chariots of fire
(2003)
In recent years, computer vision algorithms based on machine learning have seen rapid development. In the past, research mostly focused on solving computer vision problems such as image classification or object detection on images displaying natural scenes. Nowadays other fields such as the field of cultural heritage, where an abundance of data is available, also get into the focus of research. In the line of current research endeavours, we collaborated with the Getty Research Institute which provided us with a challenging dataset, containing images of paintings and drawings. In this technical report, we present the results of the seminar "Deep Learning for Computer Vision". In this seminar, students of the Hasso Plattner Institute evaluated state-of-the-art approaches for image classification, object detection and image recognition on the dataset of the Getty Research Institute. The main challenge when applying modern computer vision methods to the available data is the availability of annotated training data, as the dataset provided by the Getty Research Institute does not contain a sufficient amount of annotated samples for the training of deep neural networks. However, throughout the report we show that it is possible to achieve satisfying to very good results, when using further publicly available datasets, such as the WikiArt dataset, for the training of machine learning models.
Despite the merits of public and social media in private and professional spaces, citizens and professionals are increasingly exposed to cyberabuse, such as cyberbullying and hate speech. Thus, Law Enforcement Agencies (LEA) are deployed in many countries and organisations to enhance the preventive and reactive capabilities against cyberabuse. However, their tasks are getting more complex by the increasing amount and varying quality of information disseminated into public channels. Adopting the perspectives of Crisis Informatics and safety-critical Human-Computer Interaction (HCI) and based on both a narrative literature review and group discussions, this paper first outlines the research agenda of the CYLENCE project, which seeks to design strategies and tools for cross-media reporting, detection, and treatment of cyberbullying and hatespeech in investigative and law enforcement agencies. Second, it identifies and elaborates seven research challenges with regard to the monitoring, analysis and communication of cyberabuse in LEAs, which serve as a starting point for in-depth research within the project.
Observing inconsistent results in prior studies, this paper applies the elaboration likelihood model to investigate the impact of affective and cognitive cues embedded in social media messages on audience engagement during a political event. Leveraging a rich dataset in the context of the 2020 U.S. presidential elections containing more than 3 million tweets, we found the prominence of both cue types. For the overall sample, positivity and sentiment are negatively related to engagement. In contrast, the post-hoc sub-sample analysis of tweets from famous users shows that emotionally charged content is more engaging. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with a vast number of followers. Prosocial orientation (“we-talk”) is consistently associated with more likes, comments, and retweets in the overall sample and sub-samples.
During a crisis event, social media enables two-way communication and many-to-many information broadcasting, browsing others’ posts, publishing own content, and public commenting. These records can deliver valuable insights to approach problematic situations effectively. Our study explores how social media communication can be analyzed to understand the responses to health crises better. Results based on nearly 800 K tweets indicate that the coping and regulation foci framework holds good explanatory power, with four clusters salient in public reactions: 1) “Understanding” (problem-promotion); 2) “Action planning” (problem-prevention); 3) “Hope” (emotion-promotion) and 4) “Reassurance” (emotion-prevention). Second, the inter-temporal analysis shows high volatility of topic proportions and a shift from self-centered to community-centered topics during the course of the event. The insights are beneficial for research on crisis management and practicians who are interested in large-scale monitoring of their audience for well-informed decision-making.
An increasing number of clinicians (i.e., nurses and physicians) suffer from mental health-related issues like depression and burnout. These, in turn, stress communication, collaboration, and decision- making—areas in which Conversational Agents (CAs) have shown to be useful. Thus, in this work, we followed a mixed-method approach and systematically analysed the literature on factors affecting the well-being of clinicians and CAs’ potential to improve said well-being by relieving support in communication, collaboration, and decision-making in hospitals. In this respect, we are guided by Brigham et al. (2018)’s model of factors influencing well-being. Based on an initial number of 840 articles, we further analysed 52 papers in more detail and identified the influences of CAs’ fields of application on external and individual factors affecting clinicians’ well-being. As our second method, we will conduct interviews with clinicians and experts on CAs to verify and extend these influencing factors.
Context-aware, intelligent musical instruments for improving knowledge-intensive business processes
(2022)
With shorter song publication cycles in music industries and a reduced number of physical contact opportunities because of disruptions that may be an obstacle for musicians to cooperate, collaborative time consumption is a highly relevant target factor providing a chance for feedback in contemporary music production processes. This work aims to extend prior research on knowledge transfer velocity by augmenting traditional designs of musical instruments with (I) Digital Twins, (II) Internet of Things and (III) Cyber-Physical System capabilities and consider a new type of musical instrument as a tool to improve knowledge transfers at knowledge-intensive forms of business processes. In a design-science-oriented way, a prototype of a sensitive guitar is constructed as information and cyber-physical system. Findings show that this intelligent SensGuitar increases feedback opportunities. This study establishes the importance of conversion-specific music production processes and novel forms of interactions at guitar playing as drivers of high knowledge transfer velocities in teams and among individuals.
The business problem of having inefficient processes, imprecise process analyses and simulations as well as non-transparent artificial neuronal network models can be overcome by an easy-to-use modeling concept. With the aim of developing a flexible and efficient approach to modeling, simulating and optimizing processes, this paper proposes a flexible Concept of Neuronal Modeling (CoNM). The modeling concept, which is described by the modeling language designed and its mathematical formulation and is connected to a technical substantiation, is based on a collection of novel sub-artifacts. As these have been implemented as a computational model, the set of CoNM tools carries out novel kinds of Neuronal Process Modeling (NPM), Neuronal Process Simulations (NPS) and Neuronal Process Optimizations (NPO). The efficacy of the designed artifacts was demonstrated rigorously by means of six experiments and a simulator of real industrial production processes.
The macrocyclic ring interconversion of four maleonitrile mixed oxadithia crown ethers of variable ring size, mn-12-S2O2, mn-15-S2O3, mn-18-S2O4 and fn-12-S2O2, were studied by 1H and 13C NMR spectroscopy and by molecular modelling. The barriers to ring interconversion were estimated using variable temperature NMR spectroscopy and from the calculated activation energies, together with the spin-lattice relaxation times of the CH2 carbon atoms, conclusions were drawn regarding the intramolecular flexibility of the crown ethers in both the free state as well as the complexed state incorporating either AgI, BiIII, SbIII, PdII or PtII metal cations. Furthermore, both the stoichiometry of the complexes and the coordination sites of the crown ethers to the various cations were also clearly implicated. Molecular modelling was also utilised to ascertain the preferred conformers of the four compounds and their corresponding complexes, the results of which corroborated the experimental NMR results to a high degree.
Conclusion
(2023)
Based on the previous findings in this book, Chapter 18 by Heike Krieger and Andrea Liese discusses the general dynamics of change or metamorphosis in the international legal order. They discern a mixed picture of an international order between metamorphosis—that is, a more fundamental transformation—of international law, norm change, turbulences, and robustness. They explain drivers of change and highlight factors such as national interests during the war on terror, changing long-term foreign policy beliefs, and the rise in populism and autocracy, before discussing the most common strategies the actors involved use. Other relevant factors include changes in the political environment, such as shocks and power shifts or the ambiguous role of fragmentation. Moreover, they identify factors that make legal norms robust, including the vital role of norm defenders and legal and institutional structures as stabilizing elements. Krieger and Liese conclude by cautioning that if the attacks on the international order continue at the current frequency and magnitude, a metamorphosis of international law will likely be unstoppable.