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Diese Arbeit präsentiert eine Methode zur zuverlässigen Personendetektion für die Absicherung des Arbeitsbereichs von Industrierobotern. Hierzu wird ein im Nahinfrarotbereich (NIR) arbeitendes aktives Kamerasystem eingesetzt, das durch erweiterte und robuste Hauterkennungseigenschaften besonders dazu geeignet ist, zwischen verschiedensten Materialoberflächen und menschlicher Haut zu unterscheiden. So soll zum einen die Erkennungsleistung gegenüber handelsüblichen, im visuellen Bereich arbeitenden RGB-Kamerasystemen gesteigert werden und gleichzeitig eine „intelligente“ Form des Mutings realisiert werden. Die im Rahmen des Projekts „Sichere Personendetektion im Arbeitsbereich von Industrierobotern durch ein aktives NIR-Kamerasystem (SPAI)“ entwickelte und hier vorgestellte Methode erreicht in einer ersten Variante eine pixelweise Personenerkennungsrate von ca. 98,16%.
Mobile Datenkommunikation basiert üblicherweise auf der drahtlosen Anbindung eines Endgerätes an eine Basisstation, die ihrerseits an eine feste Infrastruktur angebunden ist. In vielen Szenarien sind diese Voraussetzungen jedoch nicht gegeben. Beispiele hierfür sind Katastrophen wie Hochwasser, Erdbeben oder Flugzeugabstürze in dünn besiedelten Regionen. Einen Lösungsansatz für sich daraus ergebende Anforderungen bieten dynamisch aufgebaute Ad-Hoc Netze mit einer satellitengestützten Anbindung an eine Festnetz-Infrastruktur. In solchen Netzen stellen die mobilen Terminals die benötigte lokale Infrastruktur selbst dynamisch her. Ziel der hier vorgestellten Arbeiten ist es, die Zuverlässigkeit und Dienstqualität der verwendeten Technologien zu untersuchen und durch geeignete Mechanismen so anzupassen, dass die Anforderungen typischer Applikationen möglichst erfüllt werden. Zur Demonstration wurde ein Prototyp aufgebaut, der unter anderem die Anwendungen "Voice over IP" (VoIP), "Datenbankzugriff im Intranet" und "Internetzugang" (WWW) untersucht.
Zuverlässige Ad-Hoc Kommunikation mobiler Endgeräte mit satellitengestützter Internet-Anbindung
(2005)
Mobile Datenkommunikation basiert üblicherweise auf der drahtlosen Anbindung eines Endgerätes an eine Basisstation, die ihrerseits an eine feste Infrastruktur angebunden ist. In vielen Szenarien sind diese Voraussetzungen jedoch nicht gegeben. Beispiele hierfür sind Hochwasser, Erdbeben oder Flugzeugabstürze in dünn besiedelten Regionen. Einen Lösungsansatz für sich daraus ergebende Anforderungen bieten dynamisch aufgebaute Ad-Hoc Netze mit einer satellitengestützten Anbindung an eine Festnetz-Infrastruktur. In solchen Netzen stellen die mobilen Terminals die benötigte lokale Infrastruktur selbst dynamisch her. Ziel der hier vorgestellten Arbeiten ist es, die Zuverlässigkeit und Dienstqualität der verwendeten Technologien zu untersuchen und durch geeignete Mechanismen so anzupassen, dass die Anforderungen typischer Applikationen möglichst erfüllt werden. Zur Demonstration wurde ein Prototyp aufgebaut, der unter anderem die Anwendungen "Voice over IP" (VoIP), "Datenbankzugriff im Intranet" und Internetzugang (WWW) untersucht.
Studienverläufe von Studenten weichen nicht selten vom offiziell geplanten Curriculum ab. Für eine den Studienerfolg verbessernde Planung und Weiterentwicklung von Studiengängen und Curricula fehlen den Verantwortlichen häufig Erkenntnisse über tatsächliche sowie typischerweise erfolgreiche und weniger erfolgreiche Studienverlaufsmuster. Process-Mining-Techniken können helfen, mehr Transparenz bei der Auswertung von Studienverläufen zu schaffen und so die Erkennung typischer Studienverlaufsmuster, die Überprüfung der Übereinstimmung der konkreten Studienverläufe mit dem vorgegebenen Curriculum sowie eine zielgerechte Verbesserung des Curriculums zu unterstützen.
Gegen unveröffentlichte – nur wenigen Personen bekannte – Sicherheitslücken (Less-than-Zero-Day Vulnerabilities) und diese ausnutzende Angriffsprogramme (Exploits) können IT-Systeme nicht geschützt werden. In der Vergangenheit wurden Sicherheitslücken meist dem Hersteller gemeldet; dieser stellte (allerdings nicht in allen Fällen) eine Fehlerkorrektur zur Verfügung. In jüngerer Zeit werden Sicherheitslücken systematisch (Tool-gestützt) gesucht und an Behörden, Unternehmen und an die organisierte Kriminalität verkauft – und nicht oder nicht sofort dem Hersteller gemeldet. Durch Ausnutzung dieser unveröffentlichten Sicherheitslücken ist Wirtschaftsspionage und Computersabotage (auch der Steuerungsrechner des Internet) unerkannt möglich [GI 2007]. Praktizierte Anwendungen sind – u.a. auch als Titan Rain – dokumentiert [BfDI 2007, Keizer 2006, NSTAC 2007, Pohl 2007, Rath 2007].
Zentrale Archivierung und verteilte Kommunikation digitaler Bilddaten in der Pneumokoniosevorsorge
(2010)
Pneumokoniose-Vorsorgeuntersuchungen erfordern die Befundung einer Röntgenthoraxaufnahme nach ILO-Staublungenklassifikation. Inzwischen werden die benötigten Aufnahmen bereits in großem Umfang digital angefertigt und kommuniziert. Hierdurch entstehen neue Anforderungen an verwendete Technik und Workflow-Mechanismen, um einen effizienten Ablauf von Untersuchung, Befundung und Dokumentation zu gewährleisten.
Along with the success of the digitally revived stereoscopic cinema, other events beyond 3D movies become attractive for movie theater operators, i.e. interactive 3D games. In this paper, we present a case that explores possible challenges and solutions for interactive 3D games to be played by a movie theater audience. We analyze the setting and showcase current issues related to lighting and interaction. Our second focus is to provide gameplay mechanics that make special use of stereoscopy, especially depth-based game design. Based on these results, we present YouDash3D, a game prototype that explores public stereoscopic gameplay in a reduced kiosk setup. It features live 3D HD video stream of a professional stereo camera rig rendered in a real-time game scene. We use the effect to place the stereoscopic effigies of players into the digital game. The game showcases how stereoscopic vision can provide for a novel depth-based game mechanic. Projected trigger zones and distributed clusters of the audience video allow for easy adaptation to larger audiences and 3D movie theater gaming.
YAWL (Yet Another Workflow Language) is an open source Business Process Management System, first released in 2003. YAWL grew out of a university research environment to become a unique system that has been deployed worldwide as a laboratory environment for research in Business Process Management and as a productive system in other scientific domains.
YAWL User Group
(2012)
YAWL Symposium 2013. Proceedings of the First YAWL Symposium, Sankt Augustin, Germany, June 7, 2013
(2013)
In this paper, we present XPERSim, a 3D simulator built on top of open source components that enables users to quickly and easily construct an accurate and photo-realistic simulation for robots of arbitrary morphology and their environments. While many existing robot simulators provide a good dynamics simulation, they often lack the high quality visualization that is now possible with general-purpose hardware. XPERSim achieves such visualization by using the Object-Oriented Graphics Rendering Engine 3D (Ogre) engine to render the simulation whose dynamics are calculated using the Open Dynamics Engine (ODE). Through XPERSim’s integration into a component-based software integration framework used for robotic learning by experimentation, XPERSIF, and the use of the scene-oriented nature of the Ogre engine, the simulation is distributed to numerous users that include researchers and robotic components, thus enabling simultaneous, quasi-realtime observation of the multiple-camera simulations.
XPERSIF: a software integration framework & architecture for robotic learning by experimentation
(2008)
The integration of independently-developed applications into an efficient system, particularly in a distributed setting, is the core issue addressed in this work. Cooperation between researchers across various field boundaries in order to solve complex problems has become commonplace. Due to the multidisciplinary nature of such efforts, individual applications are developed independent of the integration process. The integration of individual applications into a fully-functioning architecture is a complex and multifaceted task. This thesis extends a component-based architecture, previously developed by the authors, to allow the integration of various software applications which are deployed in a distributed setting. The test bed for the framework is the EU project XPERO, the goal of which is robot learning by experimentation. The task at hand is the integration of the required applications, such as planning of experiments, perception of parametrized features, robot motion control and knowledge-based learning, into a coherent cognitive architecture. This allows a mobile robot to use the methods involved in experimentation in order to learn about its environment. To meet the challenge of developing this architecture within a distributed, heterogeneous environment, the authors specified, defined, developed, implemented and tested a component-based architecture called XPERSIF. The architecture comprises loosely-coupled, autonomous components that offer services through their well-defined interfaces and form a service-oriented architecture. The Ice middleware is used in the communication layer. Its deployment facilitates the necessary refactoring of concepts. One fully specified and detailed use case is the successful integration of the XPERSim simulator which constitutes one of the kernel components of XPERO.The results of this work demonstrate that the proposed architecture is robust and flexible, and can be successfully scaled to allow the complete integration of the necessary applications, thus enabling robot learning by experimentation. The design supports composability, thus allowing components to be grouped together in order to provide an aggregate service. Distributed simulation enabled real time tele-observation of the simulated experiment. Results show that incorporating the XPERSim simulator has substantially enhanced the speed of research and the information flow within the cognitive learning loop.
XML Signature Wrapping (XSW) has been a relevant threat to web services for 15 years until today. Using the Personal Health Record (PHR), which is currently under development in Germany, we investigate a current SOAP-based web services system as a case study. In doing so, we highlight several deficiencies in defending against XSW. Using this real-world contemporary example as motivation, we introduce a guideline for more secure XML signature processing that provides practitioners with easier access to the effective countermeasures identified in the current state of research.
In this contribution, we describe the activities and promotion programs installed at the Bonn-Rhein-Sieg University as an institution and at the Department of Computer Science respectively for increasing the total number of computer science students and in particular the female rate. We report about our experiences in addressing gender aspects in education and try to evaluate the outcome of our programs with respect to our equal rights for women strategy. We propose a closer look at mental self-theories enabled by E-portfolios to address also gender issues in Computer Science. Moreover, reasons are identified and discussed which may be responsible for the reduced interest in particular of female young adults to choose a computer science study program.
Risk-based authentication (RBA) aims to strengthen password-based authentication rather than replacing it. RBA does this by monitoring and recording additional features during the login process. If feature values at login time differ significantly from those observed before, RBA requests an additional proof of identification. Although RBA is recommended in the NIST digital identity guidelines, it has so far been used almost exclusively by major online services. This is partly due to a lack of open knowledge and implementations that would allow any service provider to roll out RBA protection to its users. To close this gap, we provide a first in-depth analysis of RBA characteristics in a practical deployment. We observed N=780 users with 247 unique features on a real-world online service for over 1.8 years. Based on our collected data set, we provide (i) a behavior analysis of two RBA implementations that were apparently used by major online services in the wild, (ii) a benchmark of the features to extract a subset that is most suitable for RBA use, (iii) a new feature that has not been used in RBA before, and (iv) factors which have a significant effect on RBA performance. Our results show that RBA needs to be carefully tailored to each online service, as even small configuration adjustments can greatly impact RBA's security and usability properties. We provide insights on the selection of features, their weightings, and the risk classification in order to benefit from RBA after a minimum number of login attempts.
Risk-based authentication (RBA) aims to strengthen password-based authentication rather than replacing it. RBA does this by monitoring and recording additional features during the login process. If feature values at login time differ significantly from those observed before, RBA requests an additional proof of identification. Although RBA is recommended in the NIST digital identity guidelines, it has so far been used almost exclusively by major online services. This is partly due to a lack of open knowledge and implementations that would allow any service provider to roll out RBA protection to its users.
To close this gap, we provide a first in-depth analysis of RBA characteristics in a practical deployment. We observed N=780 users with 247 unique features on a real-world online service for over 1.8 years. Based on our collected data set, we provide (i) a behavior analysis of two RBA implementations that were apparently used by major online services in the wild, (ii) a benchmark of the features to extract a subset that is most suitable for RBA use, (iii) a new feature that has not been used in RBA before, and (iv) factors which have a significant effect on RBA performance. Our results show that RBA needs to be carefully tailored to each online service, as even small configuration adjustments can greatly impact RBA's security and usability properties. We provide insights on the selection of features, their weightings, and the risk classification in order to benefit from RBA after a minimum number of login attempts.
Application systems are often advertised with features, and features are used heavily for requirements man- agement. However, often software manufacturers only have incomplete information about the features of their software. The information is distributed over different sources, such as requirements documents, issue trackers, user manuals, and code. In this paper, we research the occurrence of feature information in open source software engineering data. We report on a case study with three open source systems. We analyze what information about features can be found in issue trackers and user documentation. Furthermore, we study the abstraction levels on which the features are described, how feature information is related, and we discuss the possibility to discover such information semi-automatically. To mirror the diversity of software development contexts, we choose open source systems, which are quite different, e.g., in the rigor of issue tracker usage. The results differ accordingly. One main result is that the user documentation did not provide more accurate information than the issue tracker compared to a provided feature list. The results also give hints on how the management of feature relevant information can be supported.
Web-based Editor for YAWL
(2013)
This paper presents a web-based editor that offers YAWL editing capabilities and comprehensive support for the XML format of YAWL. The open-source project Signavio Core Components is extended with a graphical user interface (GUI) for parts of the YAWL Language, and an import-/export component that converts between YAWL and the internal format of Signavio Core Components. This conversion, between the web-based editor and the offcial YAWL Editor, is lossless so both tools may be used together. Compared to the offcial YAWL Editor, the web-based editor is missing some features, but could still facilitate the usage of the YAWL system in use cases that are not supported by a desktop application.
Vorrichtung zur Authentifikation einer Person anhand mindestens eines biometrischen Parameters
(2008)
Die Vorrichtung zur Authentifikation einer Person anhand mindestens eines biometrischen Parameters, insbesondere anhand eines Fingerabdrucks, ist versehen mit einem Biometrie-Detektor (20) zur Detektion eines biometrischen Parameters, einem Haut-Detektor (24) zur berührungslosen Erkennung lebender menschlicher Haut innerhalb eines Erfassungsbereichs. Der Haut-Detektor (24) weist mindestens eine Gruppe aus mindestens einer Strahlungseinheit (26, 28) und mindestens einer Empfangseinheit (30) auf. Die mindestens eine Strahlungseinheit (26, 28) gibt in Richtung auf den Erfassungsbereich Strahlung bei mindestens zwei unterschiedlichen Wellenlängen im Wellenlängenbereich zwischen 400 nm und 1500 nm ab, wobei mindestens eine der Wellenlängen (26, 28) im Wellenlängenbereich von 900 nm bis 1500 nm liegt und die mindestens eine Empfangseinheit (30) aus dem Erfassungsbereich reflektierte Strahlung empfängt. Ferner ist die Vorrichtung versehen mit einer mit dem Biometer-Detektor (20) und dem Haut-Detektor (24) verbundenen Signalauswerteeinheit (22) zur Auswertung der Intensität der von der Empfangseinheit (30) empfangenen reflektierten Strahlungen der Strahlungseinheit (26, 28). In der Signalauswerteeinheit (22) ist anhand der Intensitäten der von der Empfangseinheit (30) empfangenen reflektierten Strahlungen der Strahlungseinheit (26, 28) bei den zwei unterschiedlichen Wellenlängen ermittelbar, ob der Haut-Detektor lebende menschliche Haut erkennt.
In diesem Beitrag wird der interaktive Volumenrenderer Volt für die NVIDIA CUDA Architektur vorgestellt. Die Beschleunigung wird durch das Ausnutzen der technischen Eigenschaften des CUDA Device, durch die Partitionierung des Algorithmus und durch die asynchrone Ausführung des CUDA Kernels erreicht. Parallelität wird auf dem Host, auf dem Device und zwischen Host und Device genutzt. Es wird dargestellt, wie die Berechnungen durch den gezielten Einsatz der Ressourcen effizient durchgeführt werden. Die Ergebnisse werden zurückkopiert, so dass der Kernel nicht auf dem zur Anzeige bestimmten Device ausgeführt werden muss. Synchronisation der CUDA Threads ist nicht notwendig.
The development of mobile robotic systems is a demanding task regarding its complexity, required resources and skills in multiple fields such as software development, artificial intelligence, mechanical design, electrical engineering, signal processing, sensor technology or control theory. This holds true particularly for soccer playing robots, where additional aspects like high dynamics, cooperation and high physical stress have to be dealt with. In robot competitions such as RoboCup, additional skills in the domains of team, project and knowledge management are of importance.
Nowadays Field Programmable Gate Arrays (FPGA) are used in many fields of research, e.g. to create prototypes of hardware or in applications where hardware functionality has to be changed more frequently. Boolean circuits, which can be implemented by FPGAs are the compiled result of hardware description languages such as Verilog or VHDL. Odin II is a tool, which supports developers in the research of FPGA based applications and FPGA architecture exploration by providing a framework for compilation and verification. In combination with the tools ABC, T-VPACK and VPR, Odin II is part of a CAD flow, which compiles Verilog source code that targets specific hardware resources. This paper describes the development of a graphical user interface as part of Odin II. The goal is to visualize the results of these tools in order to explore the changing structure during the compilation and optimization processes, which can be helpful to research new FPGA architectures and improve the workflow.
In this contribution a machine vision inspection system is presented which is designed as a length measuring sensor. It is developed to be applied to a range of heat shrink tubes, varying in length, diameter and color. The challenges of this task were the precision and accuracy demands as well as the real-time applicability of the entire approach since it should be realized in regular industrial line production. In production, heat shrink tubes are cut to specific sizes from a continuous tube. A multi-measurement strategy has been developed, which measures each individual tube segment several times with sub pixel accuracy while being in the visual field. The developed approach allows for a contact-free and fully automatic control of 100% of produced heat shrink tubes according to the given requirements with a measuring precision of 0.1mm. Depending on the color, length and diameter of the tubes considered, a true positive rate of 99.99% to 100% has been reached at a true negative rate of > 99.7.
"Visual Computing" (VC) fasst als hochgradig aktuelles Forschungsgebiet verschiedene Bereiche der Informatik zusammen, denen gemeinsam ist, dass sie sich mit der Erzeugung und Auswertung visueller Signale befassen. Im Fachbereich Informatik der FH Bonn-Rhein-Sieg nimmt dieser Aspekt eine zentrale Rolle in Lehre und Forschung innerhalb des Studienschwerpunktes Medieninformatik ein. Drei wesentliche Bereiche des VC werden besonders in diversen Lehreinheiten und verschiedenen Projekten vermittelt: Computergrafik, Bildverarbeitung und Hypermedia-Anwendungen. Die Aktivitäten in diesen drei Bereichen fließen zusammen im Kontext immersiver virtueller Visualisierungsumgebungen.
Dieser Tagungsband enthält die Beiträge zum 12. Workshop zum Thema Virtuelle und Erweiterte Realität der Fachgruppe VR/AR der Gesellschaft für Informatik e.V. Der Workshop dient zum Informations- und Ideenaustausch deutschsprachigen WissenschaftlerInnen, zusätzlich bietet der Workshop den idealen Rahmen aktuelle Ergebnisse und Vorhaben aus Forschung und Entwicklung einem fachkundigen Publikum zur Diskussion zu stellen. Insbesondere wollen wir auch jungen Nachwuchswissenschaftlern die Möglichkeit geben, ihre Arbeiten zu präsentieren.
Dies ist der Tagungsband zum elften aus einer Reihe erfolgreicher Workshops zum Thema Virtuelle und Erweiterte Realität, die von der Fachgruppe VR/AR der Gesellschaft für Informatik e.V. ins Leben gerufen wurde. Als etablierte Plattform für den Informations- und Ideenaustausch der deutschsprachigen VR/AR-Szene bietet der Workshop den idealen Rahmen, aktuelle Ergebnisse und Vorhaben aus Forschung und Entwicklung im Kreise eines fachkundigen Publikums zur Diskussion zu stellen. Insbesondere wollen wir auch jungen Nachwuchswissenschaftlern die Möglichkeit geben, ihre Arbeiten zu präsentieren.
Virtuelle Umgebungen
(2000)
Background: Virtual reality combined with spherical treadmills is used across species for studying neural circuits underlying navigation.
New Method: We developed an optical flow-based method for tracking treadmil ball motion in real-time using a single high-resolution camera.
Results: Tracking accuracy and timing were determined using calibration data. Ball tracking was performed at 500 Hz and integrated with an open source game engine for virtual reality projection. The projection was updated at 120 Hz with a latency with respect to ball motion of 30 ± 8 ms.
Comparison: with Existing Method(s) Optical flow based tracking of treadmill motion is typically achieved using optical mice. The camera-based optical flow tracking system developed here is based on off-the-shelf components and offers control over the image acquisition and processing parameters. This results in flexibility with respect to tracking conditions – such as ball surface texture, lighting conditions, or ball size – as well as camera alignment and calibration.
Conclusions: A fast system for rotational ball motion tracking suitable for virtual reality animal behavior across different scales was developed and characterized.
While humans can effortlessly pick a view from multiple streams, automatically choosing the best view is a challenge. Choosing the best view from multi-camera streams poses a problem regarding which objective metrics should be considered. Existing works on view selection lack consensus about which metrics should be considered to select the best view. The literature on view selection describes diverse possible metrics. And strategies such as information-theoretic, instructional design, or aesthetics-motivated fail to incorporate all approaches. In this work, we postulate a strategy incorporating information-theoretic and instructional design-based objective metrics to select the best view from a set of views. Traditionally, information-theoretic measures have been used to find the goodness of a view, such as in 3D rendering. We adapted a similar measure known as the viewpoint entropy for real-world 2D images. Additionally, we incorporated similarity penalization to get a more accurate measure of the entropy of a view, which is one of the metrics for the best view selection. Since the choice of the best view is domain-dependent, we chose demonstration-based training scenarios as our use case. The limitation of our chosen scenarios is that they do not include collaborative training and solely feature a single trainer. To incorporate instructional design considerations, we included the trainer’s body pose, face, face when instructing, and hands visibility as metrics. To incorporate domain knowledge we included predetermined regions’ visibility as another metric. All of those metrics are taken into account to produce a parameterized view recommendation approach for demonstration-based training. An online study using recorded multi-camera video streams from a simulation environment was used to validate those metrics. Furthermore, the responses from the online study were used to optimize the view recommendation performance with a normalized discounted cumulative gain (NDCG) value of 0.912, which shows good performance with respect to matching user choices.
Risk-based authentication (RBA) is an adaptive security measure to strengthen password-based authentication against account takeover attacks. Our study on 65 participants shows that users find RBA more usable than two-factor authentication equivalents and more secure than password-only authentication. We identify pitfalls and provide guidelines for putting RBA into practice.
Vection underwater
(2022)
Execution monitoring is essential for robots to detect and respond to failures. Since it is impossible to enumerate all failures for a given task, we learn from successful executions of the task to detect visual anomalies during runtime. Our method learns to predict the motions that occur during the nominal execution of a task, including camera and robot body motion. A probabilistic U-Net architecture is used to learn to predict optical flow, and the robot's kinematics and 3D model are used to model camera and body motion. The errors between the observed and predicted motion are used to calculate an anomaly score. We evaluate our method on a dataset of a robot placing a book on a shelf, which includes anomalies such as falling books, camera occlusions, and robot disturbances. We find that modeling camera and body motion, in addition to the learning-based optical flow prediction, results in an improvement of the area under the receiver operating characteristic curve from 0.752 to 0.804, and the area under the precision-recall curve from 0.467 to 0.549.
Using Visual and Auditory Cues to Locate Out-of-View Objects in Head-Mounted Augmented Reality
(2021)
In interactive graphics it is often necessary to introduce large changes in the image in response to updated information about the state of the system. Updating the local state immediately would lead to a sudden transient change in the image, which could be perceptually disruptive. However, introducing the correction gradually using smoothing operations increases latency and degrades precision. It would be beneficial to be able to introduce graphic updates immediately if they were not perceptible. In the paper the use of saccade-contingent updates is exploited to hide graphic updates during the period of visual suppression that accompanies a rapid, or saccadic, eye movement. Sensitivity to many visual stimuli is known to be reduced during a change in fixation compared to when the eye is still. For example, motion of a small object is harder to detect during a rapid eye movement (saccade) than during a fixation. To evaluate if these findings generalize to large scene changes in a virtual environment, gaze behavior in a 180 degree hemispherical display was recorded and analyzed. This data was used to develop a saccade detection algorithm adapted to virtual environments. The detectability of trans-saccadic scene changes was evaluated using images of high resolution real world scenes. The images were translated by 0.4, 0.8 or 1.2 degrees of visual angle during horizontal saccades. The scene updates were rarely noticeable for saccades with a duration greater than 58 ms. The detection rate for the smallest translation was just 6.25%. Qualitatively, even when trans-saccadic scene changes were detectible, they were much less disturbing than equivalent changes in the absence of a saccade.
Despite perfect functioning of its internal components, a robot can be unsuccessful in performing its tasks because of unforeseen situations. These situations occur when the behavior of the objects in the robot’s environment deviates from its expected values. For robots, such deviations are exhibited in the form of unknown external faults which prohibit them from performing their tasks successfully. In this work we propose to use naive physics knowledge to reason about such faults in the robotics domain. We propose an approach that uses naive physics concepts to find information about the situations which result in a detected unknown fault. The naive physics knowledge is represented by the physical properties of objects which are formalized in a logical framework. The proposed approach applies a qualitative version of physical laws to these properties for reasoning about the detected fault. By interpreting the reasoning results the robot finds the information about the situations which can cause the fault. We apply the proposed approach to the scenarios in which a robot performs manipulation tasks of picking and placing objects. Results of this application show that naive physics holds great promise for reasoning about unknown ex- ternal faults in robotics.
Improving the study entry supports students in a decisive phase of their university education. Implementing improvements is a change process and can only be successful if the relevant stakeholders are addressed and convinced. In the described Teaching Quality Pact project evaluation data is used as a mean to discuss in the university the situation of the study programs. As these discussions were based on empirical data rather than on opinion, it was possible to achieve an open discussion about measures that are implemented. The open discussion is maintained during the project when results of the measures taken are analyzed.
In this paper, a set of micro-benchmarks is proposed to determine basic performance parameters of single-node mainstream hardware architectures for High Performance Computing. Performance parameters of recent processors, including those of accelerators, are determined. The investigated systems are Intel server processor architectures as well as the two accelerator lines Intel Xeon Phi and Nvidia graphic processors. Results show similarities for some parameters between all architectures, but significant differences for others.
Efficient and comprehensive assessment of students knowledge is an imperative task in any learning process. Short answer grading is one of the most successful methods in assessing the knowledge of students. Many supervised learning and deep learning approaches have been used to automate the task of short answer grading in the past. We investigate why assistive grading with active learning would be the next logical step in this task as there is no absolute ground truth answer for any question and the task is very subjective in nature. We present a fast and easy method to harness the power of active learning and natural language processing in assisting the task of grading short answer questions. A webbased GUI is designed and implemented to incorporate an interactive short answer grading system. The experiments show that active learning saves the time and effort of graders in assessment and reaches the performance of supervised learning with less amount of graded answers for training.
Risikobasierte Authentifizierung (RBA) ist ein adaptiver Ansatz zur Stärkung der Passwortauthentifizierung. Er überwacht eine Reihe von Merkmalen, die sich auf das Loginverhalten während der Passworteingabe beziehen. Wenn sich die beobachteten Merkmalswerte signifikant von denen früherer Logins unterscheiden, fordert RBA zusätzliche Identitätsnachweise an. Regierungsbehörden und ein Erlass des US-Präsidenten empfehlen RBA, um Onlineaccounts vor Angriffen mit gestohlenen Passwörtern zu schützen. Trotz dieser Tatsachen litt RBA unter einem Mangel an offenem Wissen. Es gab nur wenige bis keine Untersuchungen über die Usability, Sicherheit und Privatsphäre von RBA. Das Verständnis dieser Aspekte ist jedoch wichtig für eine breite Akzeptanz.
Diese Arbeit soll ein umfassendes Verständnis von RBA mit einer Reihe von Studien vermitteln. Die Ergebnisse ermöglichen es, datenschutzfreundliche RBA-Lösungen zu schaffen, die die Authentifizierung stärken bei gleichzeitig hoher Menschenakzeptanz.
The study of locomotion in virtual environments is a diverse and rewarding research area. Yet, creating effective and intuitive locomotion techniques is challenging, especially when users cannot move around freely. While using handheld input devices for navigation may often be good enough, it does not match our natural experience of motion in the real world. Frequently, there are strong arguments for supporting body-centered self-motion cues as they may improve orientation and spatial judgments, and reduce motion sickness. Yet, how these cues can be introduced while the user is not moving around physically is not well understood. Actuated solutions such as motion platforms can be an option, but they are expensive and difficult to maintain. Alternatively, within this article we focus on the effect of upper-body tilt while users are seated, as previous work has indicated positive effects on self-motion perception. We report on two studies that investigated the effects of static and dynamic upper body leaning on perceived distances traveled and self-motion perception (vection). Static leaning (i.e., keeping a constant forward torso inclination) had a positive effect on self-motion, while dynamic torso leaning showed mixed results. We discuss these results and identify further steps necessary to design improved embodied locomotion control techniques that do not require actuated motion platforms.
Die Wahrnehmung des perzeptionellen Aufrecht (perceptual upright, PU) variiert in Abhängigkeit der Gewichtung verschiedener gravitationsbezogener und körperbasierter Merkmale zwischen Kontexten und aufgrund individueller Unterschiede. Ziel des Vorhabens war es, systematisch zu untersuchen, welche Zusammenhänge zwischen visuellen und gravitationsbedingten Merkmalen bestehen. Das Vorhaben baute auf vorangegangen Untersuchungen auf, deren Ergebnisse indizieren, dass eine Gravitation von ca. 0,15g notwendig ist, um effiziente Selbstorientierungsinformationen bereit zu stellen (Herpers et. al, 2015; Harris et. al, 2014).
In dem hier beschriebenen Vorhaben wurden nun gezielt künstliche Gravitationsbedingungen berücksichtigt, um die Gravitationsschwelle, ab der ein wahrnehmbarer Einfluss beobachtbar ist, genauer zu quantifizieren bzw. die oben genannte Hypothese zu bestätigen. Es konnte gezeigt werden, dass die zentripetale Kraft, die auf einer rotierenden Zentrifuge entlang der Längsachse des Körpers wirkt, genauso efektiv wie Stehen mit normaler Schwerkraft ist, um das Gefühl des perzeptionellen Aufrechts auszulösen. Die erzielten Daten deuten zudem darauf hin, dass ein Gravitationsfeld von mindestens 0,15 g notwendig ist, um eine efektive Orientierungsinformation für die Wahrnehmung von Aufrecht zu liefern. Dies entspricht in etwa der Gravitationskraft von 0,17 g, die auf dem Mond besteht. Für eine lineare Beschleunigung des Körpers liegt der vestibulare Schwellenwert bei etwa 0,1 m/s2 und somit liegt der Wert für die Situation auf dem Mond von 1,6 m/s2 deutlich über diesem Schwellenwert.
Zur Erreichung des Sachziels Vertraulichkeit werden Daten (Dokumente, Dateien, E-Mails etc.) bei der Speicherung und Übertragung in lokalen Netzen, Intranets und im Internet häufig vom Endanwender verschlüsselt. Die dazu benutzten Schlüssel müssen bei Bedarf für den Endanwender genauso verfügbar sein wie für das Unternehmen bei Nicht-Verfügbarkeit des Endanwenders. Unternehmensinterne Schlüssel-Archive speichern die benutzten Schlüssel oder speichern die Adressen benutzter Schlüssel oder stellen auf andere Weise die benutzten Schlüssel auf Anforderung Berechtigten wieder bereit. Schlüssel-Archive sind aus der auf dem Escrowed Encryption Standard (EES) basierenden Clipper-Initiative der Vereinigten Staaten entstanden und werden dort als Key Recovery Center bezeichnet.
Unexpected Situations in Service Robot Environment: Classification and Reasoning Using Naive Physics
(2014)
Understanding the Internet of Things: A Conceptualisation of Business-to-Thing (B2T) Interactions
(2015)
TSEM: Temporally-Weighted Spatiotemporal Explainable Neural Network for Multivariate Time Series
(2023)
TSEM: Temporally Weighted Spatiotemporal Explainable Neural Network for Multivariate Time Series
(2022)
Deep learning has become a one-size-fits-all solution for technical and business domains thanks to its flexibility and adaptability. It is implemented using opaque models, which unfortunately undermines the outcome trustworthiness. In order to have a better understanding of the behavior of a system, particularly one driven by time series, a look inside a deep learning model so-called posthoc eXplainable Artificial Intelligence (XAI) approaches, is important. There are two major types of XAI for time series data, namely model-agnostic and model-specific. Model-specific approach is considered in this work. While other approaches employ either Class Activation Mapping (CAM) or Attention Mechanism, we merge the two strategies into a single system, simply called the Temporally Weighted Spatiotemporal Explainable Neural Network for Multivariate Time Series (TSEM). TSEM combines the capabilities of RNN and CNN models in such a way that RNN hidden units are employed as attention weights for the CNN feature maps temporal axis. The result shows that TSEM outperforms XCM. It is similar to STAM in terms of accuracy, while also satisfying a number of interpretability criteria, including causality, fidelity, and spatiotemporality.
Trusted EPC Administration
(2009)
RFID-Transponder dienen der Identifizierung von Produkten, der Zuordnung von Produkten zu Personen, der Fälschungssicherheit und weiteren Anwendungsgebieten. Durch RFID-Transponder sollen Technologien wie z.B. der Barcode (teilweise) abgelöst werden. Einige Unternehmen sehen eine Koexistenz zwischen den Technologien, da die alte Technologie zur Zeit noch kostengünstiger ist. Einige Branchen, wie z.B. Produktion, Logistik und Handel, können von der Technologie profitieren. Die RFID-Transponder bringen gegenüber alten Technologien viele Vorteile. RFID ermöglicht die Verarbeitung eines größeren Datenvolumens, es ist kein direkter Sichtkontakt zum Lese-/Schreibgerät erforderlich und mehrere Transponder können gleichzeitig ausgewertet werden. Business-to-Business (B2B) Anwender erhoffen sich einen effizienteren und transparenteren Beschaffungsprozess, welcher im Rahmen des Supply-Chain-Managements Vorteile bringen kann. Diese Arbeit legt ihren Schwerpunkt auf die Echtzeitüberwachung während des gesamten Produktlebenszyklus. Zur weltweit eindeutigen Identifikation von Objekten werden dazu in RFID-Transpondern item-level Identifikationsnummern wie der EPC (Electronic Product Code) verwendet.
The non-filarial and non-communicable disease podoconiosis affects around 4 million people and is characterized by severe leg lymphedema accompanied with painful intermittent acute inflammatory episodes, called acute dermatolymphangioadenitis (ADLA) attacks. Risk factors have been associated with the disease but the mechanisms of pathophysiology remain uncertain. Lymphedema can lead to skin lesions, which can serve as entry points for bacteria that may cause ADLA attacks leading to progression of the lymphedema. However, the microbiome of the skin of affected legs from podoconiosis individuals remains unclear. Thus, we analysed the skin microbiome of podoconiosis legs using next generation sequencing. We revealed a positive correlation between increasing lymphedema severity and non-commensal anaerobic bacteria, especially Anaerococcus provencensis, as well as a negative correlation with the presence of Corynebacterium, a constituent of normal skin flora. Disease symptoms were generally linked to higher microbial diversity and richness, which deviated from the normal composition of the skin. These findings show an association of distinct bacterial taxa with lymphedema stages, highlighting the important role of bacteria for the pathogenesis of podoconiosis and might enable a selection of better treatment regimens to manage ADLA attacks and disease progression.
It is challenging to provide users with a haptic weight sensation of virtual objects in VR since current consumer VR controllers and software-based approaches such as pseudo-haptics cannot render appropriate haptic stimuli. To overcome these limitations, we developed a haptic VR controller named Triggermuscle that adjusts its trigger resistance according to the weight of a virtual object. Therefore, users need to adapt their index finger force to grab objects of different virtual weights. Dynamic and continuous adjustment is enabled by a spring mechanism inside the casing of an HTC Vive controller. In two user studies, we explored the effect on weight perception and found large differences between participants for sensing change in trigger resistance and thus for discriminating virtual weights. The variations were easily distinguished and associated with weight by some participants while others did not notice them at all. We discuss possible limitations, confounding factors, how to overcome them in future research and the pros and cons of this novel technology.
Airborne and spaceborne platforms are the primary data sources for large-scale forest mapping, but visual interpretation for individual species determination is labor-intensive. Hence, various studies focusing on forests have investigated the benefits of multiple sensors for automated tree species classification. However, transferable deep learning approaches for large-scale applications are still lacking. This gap motivated us to create a novel dataset for tree species classification in central Europe based on multi-sensor data from aerial, Sentinel-1 and Sentinel-2 imagery. In this paper, we introduce the TreeSatAI Benchmark Archive, which contains labels of 20 European tree species (i.e., 15 tree genera) derived from forest administration data of the federal state of Lower Saxony, Germany. We propose models and guidelines for the application of the latest machine learning techniques for the task of tree species classification with multi-label data. Finally, we provide various benchmark experiments showcasing the information which can be derived from the different sensors including artificial neural networks and tree-based machine learning methods. We found that residual neural networks (ResNet) perform sufficiently well with weighted precision scores up to 79 % only by using the RGB bands of aerial imagery. This result indicates that the spatial content present within the 0.2 m resolution data is very informative for tree species classification. With the incorporation of Sentinel-1 and Sentinel-2 imagery, performance improved marginally. However, the sole use of Sentinel-2 still allows for weighted precision scores of up to 74 % using either multi-layer perceptron (MLP) or Light Gradient Boosting Machine (LightGBM) models. Since the dataset is derived from real-world reference data, it contains high class imbalances. We found that this dataset attribute negatively affects the models' performances for many of the underrepresented classes (i.e., scarce tree species). However, the class-wise precision of the best-performing late fusion model still reached values ranging from 54 % (Acer) to 88 % (Pinus). Based on our results, we conclude that deep learning techniques using aerial imagery could considerably support forestry administration in the provision of large-scale tree species maps at a very high resolution to plan for challenges driven by global environmental change. The original dataset used in this paper is shared via Zenodo (https://doi.org/10.5281/zenodo.6598390, Schulz et al., 2022). For citation of the dataset, we refer to this article.
Analyzing training performance in sport is usually based on standardized test protocols and needs laboratory equipment, e.g., for measuring blood lactate concentration or other physiological body parameters. Avoiding special equipment and standardized test protocols, we show that it is possible to reach a quality of performance simulation comparable to the results of laboratory studies using training models with nothing but training data. For this purpose, we introduce a fitting concept for a performance model that takes the peculiarities of using training data for the task of performance diagnostics into account. With a specific way of data preprocessing, accuracy of laboratory studies can be achieved for about 50% of the tested subjects, while lower correlation of the other 50% can be explained.
Updating a shared data structure in a parallel program is usually done with some sort of high-level synchronization operation to ensure correctness and consistency. However, underlying synchronization instructions in a processor architecture are costly and rather limited in their scalability on larger multi-core/multi-processors systems. In this paper, we examine work queue operations where such costly atomic update operations are replaced with non-atomic modifiers (simple read+write). In this approach, we trade the exact amount of work with atomic operations against doing more and redundant work but without atomic operations and without violating the correctness of the algorithm. We show results for the application of this idea to the concrete scenario of parallel Breadth First Search (BFS) algorithms for undirected graphs on two large NUMA shared memory system with up to 64 cores.
Tracelets and Specifications
(2017)
In the accompanying paper [1] the authors study a model of concurrent programs in terms of events and a dependence relation, i.e., a set of arrows, between them. There also two simplifying interface models are presented; they abstract in different ways from the intricate network of internal points and arrows of program components. This report supplements [1] by presenting full proofs for the properties of the interface models, in particular, that both models exhibit homomorphic behaviour w.r.t. sequential and concurrent composition. [1] B. Möller, C.A.R. Hoare, M.E. Müller, G. Struth: A discrete geometric model of concurrent program execution. In H. Zhu, J. Bowen: Proc. UTP 16. LNCS 10134. Springer 2017, 1-25
In this paper we present the steps towards a well-designed concept of a 5VR6 system for school experiments in scientific domains like physics, biology and chemistry. The steps include the analysis of system requirements in general, the analysis of school experiments and the analysis of input and output devices demands. Based on the results of these steps we show a taxonomy of school experiments and provide a comparison between several currently available devices which can be used for building such a system. We also compare the advantages and shortcomings of 5VR6 and 5AR6 systems in general to show why, in our opinion, 5VR6 systems are better suited for school-use.
People have dreamed of machines, which would free them from unpleasant, dull, dirty and dangerous tasks and work for them as servants, for centuries if not millennia. Service robots seem to finally let these dreams come true. But where are all these robots that eventually serve us all day long, day for day? A few service robots have entered the market: domestic and professional cleaning robots, lawnmowers, milking robots, or entertainment robots. Some of these robots look more like toys or gadgets rather than real robots. But where is the rest? This is a question, which is asked not only by customers, but also by service providers, care organizations, politicians, and funding agencies. The answer is not very satisfying. Today’s service robots have their problems operating in everyday environments. This is by far more challenging than operating an industrial robot behind a fence. There is a comprehensive list of technical and scientific problems, which still need to be solved. To advance the state of the art in service robotics towards robots, which are capable of operating in an everyday environment, was the major objective of the DESIRE project (Deutsche Service Robotik Initiative – Germany Service Robotics Initiative) funded by the German Ministry of Education and Research (BMBF) under grant no. 01IME01A. This book offers a sample of the results achieved in DESIRE.