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Taming the Randomness: Towards Label-Preserving Cropping in Contrastive Learning
No full textContrastive learning (CL) approaches have gained great recognition as a very successful subset of self-supervised learning (SSL) methods. SSL enables learning from unlabeled data, a crucial step in the advancement of deep learning, particularly in computer vision (CV), given the plethora of unlabeled image data. CL works by comparing different random augmentations (e.g., different crops) of the same image, thus achieving self-labeling. Nevertheless, randomly augmenting images and especially random cropping can result in an image that is semantically very distant from the original and therefore leads to false labeling, hence undermining the efficacy of the methods. In this research, two novel parameterized cropping methods are introduced that increase the robustness of self-labeling and consequently increase the efficacy. The results show that the use of these methods significantly improves the accuracy of the model by between 2.7\% and 12.4\% on the downstream task of classifying CIFAR-10, depending on the crop size compared to that of the non-parameterized random cropping method
Dataset Supporting Farmers' Motivational Structures for Biodiversity in Nature-Protected Areas: A Qualitative Focus Group Study
No full textThis dataset supports the dissertation "Balancing Biodiversity and Economic Viability: Farmers' Motivation and Challenges in Nature-Protected Areas".The study explores the potential transfer of farmers' motivations to adopt biodiversity-friendly practices to Maslow's Hierachy of Needs. This investigation employs a multifacetd approach, including qualitative focus group interviews with farmers operating within nature-protected areas and a structured content anaylsis guided by Mayring's methodology.Data collection and Implementation:The focus group interviews were conducted in April 2022 by the policy research institue "dimap", commissioned within the framework of the dissertaion project. The study design and focus group guiede were developed by the author in close collaboration with dimap. While dimap moderated, recorded and transcribed the interviews, the coding and analysis were carried out by the author using ATLAS.ti
The Sciences and the Humanities: Two Cultures? A Module for an International and Interdisciplinary Core Curriculum
No full textThis curriculum is one of the outcomes of the research project „Public Humanities and Pedagogy in the Global South“, funded by the Government of India (SPARC project no. 1871). The project brought together an international and interdisciplinary team, with meetings in Germany (2024) and India (2025). As part of our collaboration, we designed a new course tailored for STEM students at BITS-Pilani, Goa Campus. Each contributor brought unique disciplinary perspectives to the course and taught sessions to a diverse group of students during the spring semester of 2025. The course evolved into an intercultural learning space and provided a platform not only to examine the classic „two cultures“ divide—between the natural and engineering sciences on the one hand and humanities and social sciences on the other—but also to engage with the cultural and national diversity of our team. More broadly, we reflected on Indian-German research collaboration, the role that the humanities in technically-oriented institutions of higher learning (such as German Technical Universities), and the dynamics and challenges of international academic collaboration.We are convinced that the long-standing debate on the „two cultures“ remains a productive starting point for students, educators and researchers interested in critically examining their roles and positions within their institutions, academic communities, and the global system of science and higher education. The topics and ideas presented here build on the course developed for BITS-Pilani and is intended not as a fixed program, but as a flexible toolkit. It is designed for educators seeking to create and adapt similar courses—particularly in alternative institutional and international contexts. The idea of publishing such “core curricula” as open educational resources emerged in connection with another project: the Rhine Ruhr Center for Science Communication Research (RRC), funded by the Volkswagen Foundation (2021-2026). A central insight of our work is that teaching—especially in interdisciplinary settings—should be recognized as a vital form of science communication. Here, students are not seen as passive recipients of knowledge, but as active intermediaries who bridge the different lifeworlds of the university, their communities, personal networks, and their future professions
Sensor-monitored impact sensitivity investigations on HMTD of different aging stages with accompanying PTR-TOF measurements of the substances
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Key Parameters for Performance and Resilience Modeling of 3D Time-of-Flight Cameras Under Consideration of Signal-to-Noise Ratio and Phase Noise Wiggling
No full textBecause of their resilience, Time-of-Flight (ToF) cameras are now essential components in scientific and industrial settings. This paper outlines the essential factors for modeling 3D ToF cameras, with specific emphasis on analyzing the phenomenon known as “wiggling”. Through our investigation, we demonstrate that wiggling not only causes systematic errors in distance measurements, but also introduces periodic fluctuations in statistical measurement uncertainty, which compounds the dependence on the signal-to-noise ratio (SNR). Armed with this knowledge, we developed a new 3D camera model, which we then made computationally tractable. To illustrate and evaluate the model, we compared measurement data with simulated data of the same scene. This allowed us to individually demonstrate various effects on the signal-to-noise ratio, reflectivity, and distance
Prüfungsordnung für den Bachelor-Studiengang „Informatik“, den Bachelor-Studiengang „Cyber Security & Privacy“, den Bachelor-Studiengang „Wirtschaftsinformatik“, den Bachelor-Studiengang „Informatik kooperativ“, den Master-Studiengang „Informatik“, den Master-Studiengang „Cyber Security & Privacy“, den Master-Studiengang „Autonomous Systems“ und den Master-Studiengang „Game Technologies“ am Campus Sankt Augustin der Hochschule Bonn-Rhein-Sieg vom 28.11.2024
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