Filtern
Erscheinungsjahr
Dokumenttyp
- Konferenzveröffentlichung (351) (entfernen)
Sprache
- Englisch (216)
- Deutsch (133)
- Französisch (1)
- Rumänisch (1)
Schlagworte
- Bionik (9)
- Akkreditierung (3)
- Gespenstschrecken (3)
- Haftorgan (3)
- Strukturoptimierung (3)
- adhesion (3)
- stick insects (3)
- Competency-Oriented Exams (2)
- E-Learning (2)
- Field measurement (2)
- Human-Robot Interaction (2)
- Leichtbau (2)
- Solar modules (2)
- Sportsoziologie (2)
- Sportökonomie (2)
- Tetraplegie (2)
- Virtuelle Hochschule (2)
- 360° Panorama (1)
- AEM-Electrolysis (1)
- API 1130 (1)
- Abusive Supervision (1)
- Air handling unit (1)
- Akademischer Grad (1)
- Alltagsunterstützende Assistenzlösung (1)
- Alternative Geschäftsmodelle (1)
- Arbeitsbelastung (1)
- Artificial Intelligence (1)
- Assisted living technologies (1)
- Assistive robotics (1)
- Augmented Reality (1)
- Automatisierung, Journalismus, Literaturüberblick (1)
- Automatisierungstechnik (1)
- Autonomous Agents (1)
- Bachelor-Studiengang (1)
- Bachelorstudiengang (1)
- Bachelorstudium (1)
- Belgien (1)
- Berufsbefähigung (1)
- Bildverarbeitung (1)
- Biomimetics (1)
- Bologna-Prozess (1)
- Building Information Modeling (1)
- Burnout (1)
- CFD Simulation (1)
- COIL (1)
- CPM (1)
- Climate change (1)
- Constructive Alignment (1)
- Continuous Assessment (1)
- Continuous Queries (1)
- Crowdfunding (1)
- Current Pulses (1)
- Curriculanormwert (1)
- Daseinsvorsorge (1)
- Datalog (1)
- Datenjournalismus (1)
- Deductive Databases (1)
- Deutschland (1)
- Deutschland / Technische Regeln für brennbare Flüssigkeiten (1)
- Digitalisierung (1)
- Distributed Software Development (1)
- Elastizitätsmodul (1)
- Electrodeposition (1)
- Elektrolyseure (1)
- Energieeffizienz (1)
- Erneuerbare Energien (1)
- Erweiterte Realität <Informatik> (1)
- Exams with Third-Party Applications (1)
- Fehlererkennung (1)
- Fehlerortung (1)
- Flat-Channel (1)
- Flipped Classroom (1)
- Formative Assessment (1)
- Future capacity needs (1)
- Gehirn & Computer (1)
- Gentrifizierung (1)
- Großveranstaltung (1)
- High Reynold Numer (1)
- Hochschulbildung (1)
- Human-centered computing (1)
- Hydraulic compression, Carbon Nano Fibers, PEM Fuel Cells, Catalyst utilization (1)
- Hygiene (1)
- Incremental Evaluation (1)
- Informatik (1)
- Informatikstudium (1)
- Ingenieurstudium (1)
- Interactive Voting Systems (1)
- Interaktion (1)
- Intercultural Collaboration (1)
- Internationalisierung (1)
- Journalismus (1)
- Journalistenausbildung (1)
- Juristenausbildung (1)
- KMU (1)
- Kalman filter (1)
- Klimatechnik (1)
- Klimawandel (1)
- Klimaänderung (1)
- Kohlenstoff-Nanoröhre (1)
- Kreditpunktesystem (1)
- Künstliche Intelligenz (1)
- Launcher (1)
- Leak detection (1)
- Leckerkennung (1)
- Leckortung (1)
- Lecksuchgerät (1)
- Lecküberwachung (1)
- Leistungsreserve (1)
- Machine Learning (1)
- Maschinenintelligenz (1)
- Master-Studiengang (1)
- Masterstudiengang (1)
- Masterstudium (1)
- Mastery Experience (1)
- Mathematikstudium (1)
- Maus (1)
- Membran-Elektroden-Einheit (1)
- Mensch-Roboter (1)
- Menschheitsentwicklung (1)
- Mikrofotografie (1)
- Mixed Reality (1)
- Modularisierung (1)
- Multi-Agent System (1)
- Nachhaltigkeitsreporting (1)
- Naturwissenschaftliches Studium (1)
- NeRF (1)
- Ni-Mo alloy Catalyst (1)
- Online Programming Exams (1)
- Online Supervision (1)
- Online-Studium (1)
- PEM Electrolysis, Hydrogen, Hydraulic Compression, High Pressure (1)
- PEM fuel cells; electrode preparation; carbon nanofibers; in-situ performance test (1)
- Peer Assessment (1)
- Peer Instruction (1)
- People with disabilities (1)
- Performance prediction (1)
- Physics-Informed Deep Learning (1)
- Polymer-Elektrolytmembran-Brennstoffzelle (1)
- Project-based Learning (1)
- Qualifikationsrahmen (1)
- RLT-Geräte (1)
- Raumluftströmung (1)
- Rechtssprache (1)
- Regeln der Technik (1)
- Rescue Robotics (1)
- Robot assistive drinking (1)
- Robot assistive eating (1)
- Robotik (1)
- Selbstoptimierung (1)
- Sensortechnik (1)
- Sinusoidal (1)
- Skalierung (1)
- Small UAVs (1)
- Smart Grid (1)
- Social Learning (1)
- Standortfaktor (1)
- Standortpolitik (1)
- Student Activation (1)
- Studierbarkeit (1)
- Supercomputer (1)
- TRFL (1)
- Temperature coefficients (1)
- Testsystem (1)
- Thermal Stress (1)
- Transformative Teaching (1)
- Update Propagation (1)
- Urban heat island (1)
- Visual Monocular SLAM (1)
- Wasserstoffenergietechnik (1)
- Weiterbildung (1)
- Wirtschaftsjurist (1)
- Workload (1)
- Wärmepumpen, VDI 4645, Jahresarbeitszahl, Wärmewende, Bewertungstool (1)
- Young´s modulus (1)
- Zustandsmaschine (1)
- biomimicry (1)
- bionik robotik ameisen (1)
- consent banner (1)
- cookie banner (1)
- cookies (1)
- human-centered design (1)
- hybrid sensor system (1)
- leak locating (1)
- leak monitoring (1)
- participatory design (1)
- privacy (1)
- risk management (1)
- sensor fusion (1)
- state machine (1)
- user acceptance (1)
- web measurement (1)
- Ähnlichkeitstheorie (1)
- Übersetzung (1)
Institut
- Institut für Internetsicherheit (69)
- Westfälisches Institut für Gesundheit (63)
- Informatik und Kommunikation (45)
- Westfälisches Energieinstitut (38)
- Maschinenbau Bocholt (29)
- Wirtschaft und Informationstechnik Bocholt (26)
- Elektrotechnik und angewandte Naturwissenschaften (22)
- Wirtschaftsrecht (8)
- Institut für biologische und chemische Informatik (6)
- Institut für Innovationsforschung und -management (5)
Steps Towards an Open All-in-one Rich-Client Environment for Particle-Based Mesoscopic Simulation
(2018)
Web advertisements are the primary financial source for many online services, but also for cybercriminals. Successful ad campaigns rely on good online profiles of their potential customers. The financial potentials of displaying ads have led to the rise of malware that injects or replaces ads on websites, in particular, so-called adware. This development leads to always further optimized and customized advertising. For these customization's, various tracking methods are used. However, only sparse work has gone into privacy issues emerging from adware. In this paper, we investigate the tracking capabilities and related privacy implications of adware and potentially unwanted programs (PUPs). Therefore, we developed a framework that allows us to analyze any network communication of the Firefox browser on the application level to circumvent encryption like TLS. We use this to dynamically analyze the communication streams of over 16,000 adware or potentially unwanted programs samples that tamper with the users' browser session. Our results indicate that roughly 37% of the requests issued by the analyzed samples contain private information and are accordingly able to track users. Additionally, we analyze which tracking techniques and services are used.
In der modernen Informationsgesellschaft nehmen Online-Transaktionen einen wichtigen Teil unseres täglichen Lebens ein. In dieser Arbeit stellen wir ein nutzerzentriertes Protokoll vor, dass es Nutzern erlaubt vertrauenswürdige und sichere Transkationen durchzuführen selbst wenn sie ein nicht vertrau-enswürdiges oder mit Schadsoftware infiziertes Gerät nutzen. Das Protokoll nutzt einen CAPTCHA-artigen Ansatz, der verhindert, dass ein Angreifer eine Transaktion verändert ohne, dass Server oder Client dies bemerken. Dazu stellen wir dem Nutzer eine Aufgabe die kontextsensitive Informationen der Transaktion enthält. Die Aufgabe wird so gestellt, dass sie einfach von Menschen lösbar ist aber nur schwer automatisiert gelöst werden kann. Zur Evaluation des Systems haben wir eine Nutzerstudie (n=30) durchgeführt und berechnet mit welcher Wahrscheinlichkeit ein Angreifer erfolgreich die richtige Antwort auf die Frage erraten kann. Wir zeigen, dass ein Großteil der Transaktionen (> 94%) geschützt werden kann während das System selbst nutzbar bleibt.
In diesem Artikel wird ein Alert-System für das Online-Banking vorgestellt, welches das Schutzniveau im Kontext von Social-Engineering-Angriffen sowohl clientseitig als auch serverseitig erhöhen soll. Hierfür wird durch das Alert-System ein kontinuierliches Lagebild über die aktuelle Gefahrenlage beim Online-Banking erstellt. Bei konkretem Bedarf wird der Nutzer punktuell vor aktuellen Betrugsmaschen gewarnt und zielgerichtet über Schutzvorkehrungen und Handlungsempfehlungen informiert. Für die Berechnung der aktuellen Gefahrenlage wurden unterschiedliche off-the-shelf-Algorithmen des Maschinellen Lernens verwendet und miteinander verglichen. Die Effektivität des Alert-Systems wurde anhand von echten Betrugsfällen evaluiert, die bei einer Bankengruppe in Deutschland aufgetreten sind. Zusätzlich wurde die Usability des Systems in einer Nutzerstudie mit 50 Teilnehmern untersucht. Die ersten Ergebnisse zeigen, dass die verwendeten Verfahren dazu geeignet sind, die Gefahrenlage im Online-Banking zu beurteilen und dass ein solches Alert-System auf hohe Akzeptanz bei Nutzern stößt.
Renewable and sustainable energy production by many small and distributed producers is revolutionizing the energy landscape as we know it. Consumers produce energy, making them to prosumers in the smart grid. The interaction between prosumers and other entities in the grid and the optimal utilization of new smart grid components (electric cars, freezers, solar panels, etc.) are crucial for the success of the smart grid. The Power Trading Agent Competition is an open simulation platform that allows researchers to conduct low risk studies in this new energy market. In this work we present Maxon16, an autonomous energy broker and champion of the 2016's Power Trading Agent Competition. We present the strategies the broker used in the final round and evaluate the effectiveness of the strategies by analyzing the tournament's results.
This technical report is about the architecture and integration of commercial UAVs in Search and Rescue missions. We describe a framework that consists of heterogeneous UAVs, a UAV task planner, a bridge to the UAVs, an intelligent image hub, and a 3D point cloud generator. A first version of the framework was developed and tested in several training missions in the EU project TRADR.
This technical report is about the mission and the experience gained during the reconnaissance of an industrial hall with hazardous substances after a major fire in Berlin. During this operation, only UAVs and cameras were used to obtain information about the site and the building. First, a geo-referenced 3D model of the building was created in order to plan the entry into the hall. Subsequently, the UAVs were used to fly in the heavily damaged interior and take pictures from inside of the hall. A 360° camera mounted under the UAV was used to collect images of the surrounding area especially from sections that were difficult to fly into. Since the collected data set contained similar images as well as blurred images, it was cleaned from non-optimal images using visual SLAM, bundle adjustment and blur detection so that a 3D model and overviews could be calculated. It was shown that the emergency services were not able to extract the necessary information from the 3D model. Therefore, an interactive panorama viewer with links to other 360° images was implemented where the links to the other images depends on the semi dense point cloud and located camera positions of the visual SLAM algorithm so that the emergency forces could view the surroundings.
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.
This technical report is about the architecture and integration of very small commercial UAVs (< 40 cm diagonal) in indoor Search and Rescue missions. One UAV is manually controlled by only one single human operator delivering live video streams and image series for later 3D scene modelling and inspection. In order to assist the operator who has to simultaneously observe the environment and navigate through it we use multiple deep neural networks to provide guided autonomy, automatic object detection and classification and local 3D scene modelling. Our methods help to reduce the cognitive load of the operator. We describe a framework for quick integration of new methods from the field of Deep Learning, enabling for rapid evaluation in real scenarios, including the interaction of methods.
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.