Nicht ermittelbar
Refine
Year of publication
Document Type
- Article (100)
- Monograph/Edited Volume (96)
- Part of a Book (65)
- Conference Proceeding (32)
- Other (11)
- Doctoral Thesis (9)
- Review (8)
- Working Paper (6)
- Report (3)
- Postprint (2)
Language
- English (332) (remove)
Is part of the Bibliography
- yes (332) (remove)
Keywords
Institute
- Fachgruppe Betriebswirtschaftslehre (53)
- Institut für Mathematik (46)
- Fachgruppe Politik- & Verwaltungswissenschaft (44)
- Institut für Informatik und Computational Science (23)
- Hasso-Plattner-Institut für Digital Engineering GmbH (22)
- Institut für Anglistik und Amerikanistik (18)
- Öffentliches Recht (18)
- Wirtschaftswissenschaften (16)
- Institut für Physik und Astronomie (12)
- Department Psychologie (9)
Introduction
(2023)
Can a metamorphosis of international law be identified while it is still underway? In Chapter 1, the Introduction, Krieger and Liese set the stage for the interdisciplinary assessment of the effects of the current crisis of the international legal order. They offer fundamental common values as a reference point and yardstick to systematically evaluate and analyse normative changes in international law. After explaining the benefits of interdisciplinary exchange and clarifying the basic concepts from the respective disciplinary perspectives, they develop the book’s conceptual framework for assessing and explaining value change in the international legal order. The Introduction also elaborates on the book’s research design and case selection and summarizes the aims and key contributions of each conceptual and empirical chapter.
Virtual reality can have advantages for education and learning. However, it must be adequately designed so that the learner benefits from the technological possibilities. Understanding the underlying effects of the virtual learning environment and the learner’s prior experience with virtual reality or prior knowledge of the content is necessary to design a proper virtual learning environment. This article presents a pre-study testing the design of a virtual learning environment for engineering vocational training courses. In the pre-study, 12 employees of two companies joined the training course in one of the two degrees of immersion (desktop VR and VR HMD). Quantitative results on learning success, cognitive load, usability, and motivation and qualitative learning process data were presented. The qualitative data assessment shows that overall, the employees were satisfied with the learning environment regardless of the level of immersion and that the participants asked for more guidance and structure accompanying the learning process. Further research is needed to test for solid group differences.
Business processes are regularly modified either to capture requirements from the organization’s environment or due to internal optimization and restructuring. Implementing the changes into the individual work routines is aided by change management tools. These tools aim at the acceptance of the process by and empowerment of the process executor. They cover a wide range of general factors and seldom accurately address the changes in task execution and sequence. Furthermore, change is only framed as a learning activity, while most obstacles to change arise from the inability to unlearn or forget behavioural patterns one is acquainted with. Therefore, this paper aims to develop and demonstrate a notation to capture changes in business processes and identify elements that are likely to present obstacles during change. It connects existing research from changes in work routines and psychological insights from unlearning and intentional forgetting to the BPM domain. The results contribute to more transparency in business process models regarding knowledge changes. They provide better means to understand the dynamics and barriers of change processes.
Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level.
Like conventional software projects, projects in model-driven software engineering require adequate management of multiple versions of development artifacts, importantly allowing living with temporary inconsistencies. In the case of model-driven software engineering, employed versioning approaches also have to handle situations where different artifacts, that is, different models, are linked via automatic model transformations.
In this report, we propose a technique for jointly handling the transformation of multiple versions of a source model into corresponding versions of a target model, which enables the use of a more compact representation that may afford improved execution time of both the transformation and further analysis operations. Our approach is based on the well-known formalism of triple graph grammars and a previously introduced encoding of model version histories called multi-version models. In addition to showing the correctness of our approach with respect to the standard semantics of triple graph grammars, we conduct an empirical evaluation that demonstrates the potential benefit regarding execution time performance.
With larger artificial neural networks (ANN) and deeper neural architectures, common methods for training ANN, such as backpropagation, are key to learning success. Their role becomes particularly important when interpreting and controlling structures that evolve through machine learning. This work aims to extend previous research on backpropagation-based methods by presenting a modified, full-gradient version of the backpropagation learning algorithm that preserves (or rather crystallizes) selected neural weights while leaving other weights adaptable (or rather fluid). In a design-science-oriented manner, a prototype of a feedforward ANN is demonstrated and refined using the new learning method. The results show that the so-called crystallizing backpropagation increases the control possibilities of neural structures and interpretation chances, while learning can be carried out as usual. Since neural hierarchies are established because of the algorithm, ANN compartments start to function in terms of cognitive levels. This study shows the importance of dealing with ANN in hierarchies through backpropagation and brings in learning methods as novel ways of interacting with ANN. Practitioners will benefit from this interactive process because they can restrict neural learning to specific architectural components of ANN and can focus further development on specific areas of higher cognitive levels without the risk of destroying valuable ANN structures.
This book brings together a variety of innovative perspectives on the inclusion of gender in the governance of (counter-)terrorism and violent extremism.
Several global governance initiatives launched in recent years have explicitly sought to integrate concern for gender equality and gendered harms into efforts to counter terrorism and violent extremism (CT/CVE). As a result, commitments to gender-sensitivity and gender equality in international and regional CT/CVE initiatives, in national action plans and at the level of civil society programming, ´have become a common aspect of the multilevel governance of terrorism and violent extremism. In light of these developments, there is a need for more systematic analysis of how concerns about gender are being incorporated in the governance of (counter-)terrorism and violent extremism and how it has affected (gendered) practices and power relations in counterterrorism policy-making and implementation.
Ranging from the processes of global and regional integration of gender into the governance of terrorism, via the impact of the shift on government responses to the return of foreign fighters, to state and civil society-led CVE programming and academic discussions, the essays engage with the origins and dynamics behind recent shifts which bring gender to the forefront of the governance of terrorism. This book will be of great value to researchers and scholars interested in gender, governance and terrorism.
The chapters in this book were originally published in Critical Studies on Terrorism.
Introduction
(2023)
Several global governance initiatives launched in recent years have explicitly sought to integrate concern for gender equality and gendered harms into efforts to counter terrorism and violent extremism. As a result, commitments to gender-sensitivity and gender equality in international and regional counterterrorism and countering violent extremism (CT/CVE) initiatives, in national action plans, and at the level of civil society programming, have become a common aspect of the multilevel governance of terrorism and violent extremism. In light of these developments, aspects of our own research have turned in the past years to explore how concerns about gender are being incorporated in the governance of terrorism and violent extremism and how this development has affected (gendered) practices and power relations in CT policymaking and implementation. We were inspired by the growing literature on gender and CT/CVE, and critical scholarship on terrorism and political violence, to bring together a collection of new research addressing these questions.
Atwood (2022) analyzes the effects of the 1963 U.S. measles vaccination on longrun labor market outcomes, using a generalized difference-in-differences approach. We reproduce the results of this paper and perform a battery of robustness checks. Overall, we confirm that the measles vaccination had positive labor market effects. While the negative effect on the likelihood of living in poverty and the positive effect on the probability of being employed are very robust across the different specifications, the headline estimate-the effect on earnings-is more sensitive to the exclusion of certain regions and survey years.
The impact of civilian harm on strategic outcomes in war has been the subject of persistent debate. However, the literature has primarily focused on civilian casualties, thereby overlooking the targeting of civilian infrastructure, which is a recurrent phenomenon during war. This study fills this gap by examining the targeting of healthcare, one of the most indispensable infrastructures during war and peace time. We contend that attacks on medical facilities are distinct from direct violence against civilians. Because they are typically unrelated to military dynamics, the targeting of hospitals is a highly visible form and powerful signal of civilian victimization. To assess its effects, we analyze newly collected data on such attacks by pro-government forces and event data on combat activities in Northwest Syria (2017-2020). Applying a new approach for panel data analysis that combines matching methods with a difference-in-differences estimation, we examine the causal effect of counterinsurgent bombings on subsequent violent events. Distinguishing between regime-initiated and insurgent-initiated combat activities and their associated fatalities, we find that the targeting of hospitals increases insurgent violence. We supplement the quantitative analysis with unique qualitative evidence derived from interviews, which demonstrates that hospital bombings induce rebels to resist more fiercely through two mechanisms: intrinsic motivations and civilian pressure. The results have important implications for the effects of state-led violence and the strength of legal norms that protect noncombatants.