TY - CHAP A1 - Seidl, Tobias A1 - Bennemann, Michael T1 - Image Stitching of Microscopic Images T2 - Konferenz: "Society for Experimental Biology (SEB)", 3.-7. Juli 2016 in Brighton (England) N2 - Method to stich many microscopic images to gain one image with a very high resolution. KW - Bildverarbeitung KW - Maus KW - Mikrofotografie Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1010-opus4-5076 ER - TY - JOUR A1 - Unger, Sebastian A1 - Robens, Sibylle A1 - Anderle, Laura A1 - Ostermann, Thomas T1 - Digital Drawing Tools for Assessing Mental Health Conditions – A Scoping Review JF - German Medical Data Sciences 2024 - Health - Thinking, Researching and Acting Together ; Proceedings of the 69th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) 2024 in Dresden, Germany Studies in Health Technology and Informatics, Bd. 317 N2 - Introduction: Drawing tasks are an elementary component of psychological assessment in the evaluation of mental health. With the rise of digitalization not only in psychology but healthcare in general, digital drawing tools (dDTs) have also been developed for this purpose. This scoping review aims at summarizing the state of the art of dDTs available to assess mental health conditions in people above preschool age. Methods: PubMed, PsycInfo, PsycArticles, CINAHL, and Psychology and Behavioral Sciences Collection were searched for dDTs from 2000 onwards. The focus was on dDTs, which not only evaluate the final drawing, but also process data. Results: After applying the search and selection strategy, a total of 37 articles, comprising unique dDTs, remained for data extraction. Around 75 % of these articles were published after 2014 and most of them target adults (86.5 %). In addition, dDTs were mainly used in two areas: tremor detection and assessment of cognitive states, utilizing, for example, the Spiral Drawing Test and the Clock Drawing Test. Conclusion: Early detection of mental diseases is an increasingly important field in healthcare. Through the integration of digital and art based solutions, this area could expand into an interdisciplinary science. This review shows that the first steps in this direction have already been taken and that the possibilities for further research, e.g., on the optimized application of dDTs, are still open. KW - Review KW - Software Tools KW - Drawing KW - Painting KW - Mental Health Y1 - 2024 U6 - https://doi.org/10.3233/SHTI240864 SP - 251 EP - 259 ER - TY - CHAP A1 - Surmann, Hartmut A1 - Digakis, Niklas A1 - Kremer, Jan-Niklas A1 - Meine, Julien A1 - Schulte, Max A1 - Voigt, Niklas T1 - Redefining Recon: Bridging Gaps with UAVs, 360° Cameras, and Neural Radiance Fields N2 - In the realm of digital situational awareness during disaster situations, accurate digital representations, like 3D models, play an indispensable role. To ensure the safety of rescue teams, robotic platforms are often deployed to generate these models. In this paper, we introduce an innovative approach that synergizes the capabilities of compact Unmaned Arial Vehicles (UAVs), smaller than 30 cm, equipped with 360° cameras and the advances of Neural Radiance Fields (NeRFs). A NeRF, a specialized neural network, can deduce a 3D representation of any scene using 2D images and then synthesize it from various angles upon request. This method is especially tailored for urban environments which have experienced significant destruction, where the structural integrity of buildings is compromised to the point of barring entry—commonly observed post-earthquakes and after severe fires. We have tested our approach through recent post-fire scenario, underlining the efficacy of NeRFs even in challenging outdoor environments characterized by water, snow, varying light conditions, and reflective surfaces. KW - Small UAVs KW - 360° Panorama KW - Visual Monocular SLAM KW - Rescue Robotics KW - NeRF Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1010-opus4-44603 SP - 1 EP - 6 ER - TY - VIDEO A1 - Meine, Julien A1 - Voigt, Niklas A1 - Kremer, Jan-Niklas A1 - Digakis, Niklas A1 - Schulte, Max A1 - Surmann, Hartmut T1 - Nerf(acto) for 3D modeling of the DRZ outside testing area N2 - The video shows a very high resolution 3D point cloud !!! of the outdoor area of the German Rescue Robotics Center. For the recording, a 25-second POI flight was performed with a Mavic 3. From the 4K video footage captured during this flight, 77 images were cropped and localized within 4 minutes using colmap and processed using Neural Radiance Fields (NeRF). The nerfacto model of Nerfstudio was trained on an Nvidia RTX 4090 for 8 minutes. In summary, a top 3D model is available to task forces after about 13 minutes. The calculation is performed locally on site by the RobLW of the DRZ. The video shown here shows a free camera path rendered at 60 hz (Full HD). Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1010-opus4-43156 ER - TY - CHAP A1 - Surmann, Hartmut A1 - Leinweber, Artur A1 - Senkowski, Gerhard A1 - Meine, Julien A1 - Slomma, Dominik T1 - UAVs and Neural Networks for search and rescue missions N2 - In this paper, we present a method for detecting objects of interest, including cars, humans, and fire, in aerial images captured by unmanned aerial vehicles (UAVs) usually during vegetation fires. To achieve this, we use artificial neural networks and create a dataset for supervised learning. We accomplish the assisted labeling of the dataset through the implementation of an object detection pipeline that combines classic image processing techniques with pretrained neural networks. In addition, we develop a data augmentation pipeline to augment the dataset with utomatically labeled images. Finally, we evaluate the performance of different neural networks. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1010-opus4-44617 SP - 1 EP - 8 ER - TY - CHAP A1 - Meyer, Manfred ED - Carmo, Mafalda T1 - Challenges – Towards Continuous Peer Assessment in Undergraduate Programming Classes T2 - Education and New Developments 2023, Vol. 1 N2 - This paper presents a pragmatic approach for stepwise introduction of peer assessment elements in undergraduate programming classes, discusses some lessons learned so far and directions for further work. Students are invited to challenge their peers with their own programming exercises to be submitted through Moodle and evaluated by other students according to a predefined rubric and supervised by teaching assistants. Preliminary results show an increased activation and motivation of students leading to a better performance in the final programming exams. KW - Continuous Assessment KW - Peer Assessment KW - Formative Assessment KW - Competency-Oriented Exams Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1010-opus4-45124 SN - 978-989-35106-3-6 SN - 2184-044X SN - 2184-1489 SP - 134 EP - 138 PB - inScience Press CY - Lissabon ER - TY - RPRT A1 - Drosten, Klaus A1 - Bals, Christian T1 - BeanMaker - a Tool for Automatic Generation of Persistent Enterprise JavaBeans N2 - An EJB container can host three types of beans: Session beans to model business processes, entity beans to represent business objects and message-driven beans to provide for asynchronous method calls. This paper addresses entity beans and their mapping to persistent storage, especially relational and object-relational databases. A tool named BeanMaker is presented which can do object mapping either automatically by metadata analysis of a database schema or manually based on intrinsic real world semantics supplied by the user. BeanMaker is a running prototype system with an intuitive GUI interface. This paper looks what's behind the scenes and focuses on design issues and concepts of code generation. KW - Enterprise JavaBeans KW - Codegenerierung KW - Persistenz KW - Enterprise JavaBeans KW - Object-relational Mapping Y1 - 2004 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1010-opus4-115 ER - TY - CHAP A1 - Meyer, Manfred T1 - The Many Ways to Student Activation: Lessons Learned from 25 Years of Teaching Undergraduate Programming Classes T2 - Proceedings of the 16th Annual International Conference of Education, Research and Innovation, November 13th - 15th, 2023, Seville, Spain N2 - This paper reveals various approaches undertaken over more than two decades of teaching undergraduate programming classes at different Higher Education Institutions, in order to improve student activation and participation in class and consequently teaching and learning effectiveness. While new technologies and the ubiquity of smartphones and internet access has brought new tools to the classroom and opened new didactic approaches, lessons learned from this personal long-term study show that neither technology itself nor any single new and often hyped didactic approach ensured sustained improvement of student activation. Rather it needs an integrated yet open approach towards a participative learning space supported but not created by new tools, technology and innovative teaching methods. KW - Student Activation KW - Interactive Voting Systems KW - Flipped Classroom KW - Peer Instruction KW - Social Learning Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1010-opus4-45141 SN - 978-84-09-55942-8 SN - 2340-1095 SP - 9281 EP - 9290 PB - IATED Academy CY - Valencia ER - TY - JOUR A1 - Pulst, Edda A1 - Hagwood, John A1 - Kieback, Antoinette A1 - Niemeier, Joachim T1 - Analysis of future development opportunities for OIS (Office Information Systems) methods and tools. JF - Decision Support Systems. DSS ; the international journal Y1 - 1992 SN - 1873-5797 SN - 0167-9236 VL - 1992 IS - 8 SP - 197 EP - 209 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Springer, Raphael A1 - Schmitz, Alexander A1 - Leinweber, Artur A1 - Urban, Tobias A1 - Dietrich, Christian J. T1 - Padding Matters - Exploring Function Detection in PE Files: Data/Toolset T2 - CODASPY '25: Proceedings of the Fifteenth ACM Conference on Data and Application Security and Privacy, June 4-6 2025, Pittsburgh PA USA N2 - Function detection is a well-known problem in binary analysis. While prior work has focused on Linux/ELF, Windows/PE binaries have only partially been considered. This paper introduces FuncPEval, a dataset for Windows x86 and x64 PE files, featuring Chromium and the Conti ransomware, along with ground truth data for 1,092,820 function starts. Utilizing FuncPEval, we evaluate five heuristics-based (Ghidra, IDA, Nucleus, rev.ng, SMDA) and three machine-learning-based (DeepDi, RNN, XDA) function start detection tools. Among these, IDA achieves the highest F1-score (98.44%) for Chromium x64, while DeepDi closely follows (97%) but stands out as the fastest. Towards explainability, we examine the impact of padding between functions on the detection results, finding all tested tools, except rev.ng, are susceptible to randomized padding. The randomized padding significantly diminishes the effectiveness of the RNN, XDA, and Nucleus. Among the learning-based tools, DeepDi exhibits the least sensitivity, while Nucleus is the most adversely affected among the non-learning-based tools. KW - Binary Code Analysis KW - Function Detection KW - Malware Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1010-opus4-48386 SN - 979-8-4007-1476-4 VL - 2025 SP - 179 EP - 184 PB - Association for Computing Machinery (ACM) CY - New York ER -