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Deep learning enables enormous progress in many computer vision-related tasks. Artificial Intel- ligence (AI) steadily yields new state-of-the-art results in the field of detection and classification. Thereby AI performance equals or exceeds human performance. Those achievements impacted many domains, including medical applications.
One particular field of medical applications is gastroenterology. In gastroenterology, machine learning algorithms are used to assist examiners during interventions. One of the most critical concerns for gastroenterologists is the development of Colorectal Cancer (CRC), which is one of the leading causes of cancer-related deaths worldwide. Detecting polyps in screening colonoscopies is the essential procedure to prevent CRC. Thereby, the gastroenterologist uses an endoscope to screen the whole colon to find polyps during a colonoscopy. Polyps are mucosal growths that can vary in severity.
This thesis supports gastroenterologists in their examinations with automated detection and clas- sification systems for polyps. The main contribution is a real-time polyp detection system. This system is ready to be installed in any gastroenterology practice worldwide using open-source soft- ware. The system achieves state-of-the-art detection results and is currently evaluated in a clinical trial in four different centers in Germany.
The thesis presents two additional key contributions: One is a polyp detection system with ex- tended vision tested in an animal trial. Polyps often hide behind folds or in uninvestigated areas. Therefore, the polyp detection system with extended vision uses an endoscope assisted by two additional cameras to see behind those folds. If a polyp is detected, the endoscopist receives a vi- sual signal. While the detection system handles the additional two camera inputs, the endoscopist focuses on the main camera as usual.
The second one are two polyp classification models, one for the classification based on shape (Paris) and the other on surface and texture (NBI International Colorectal Endoscopic (NICE) classification). Both classifications help the endoscopist with the treatment of and the decisions about the detected polyp.
The key algorithms of the thesis achieve state-of-the-art performance. Outstandingly, the polyp detection system tested on a highly demanding video data set shows an F1 score of 90.25 % while working in real-time. The results exceed all real-time systems in the literature. Furthermore, the first preliminary results of the clinical trial of the polyp detection system suggest a high Adenoma Detection Rate (ADR). In the preliminary study, all polyps were detected by the polyp detection system, and the system achieved a high usability score of 96.3 (max 100). The Paris classification model achieved an F1 score of 89.35 % which is state-of-the-art. The NICE classification model achieved an F1 score of 81.13 %.
Furthermore, a large data set for polyp detection and classification was created during this thesis. Therefore a fast and robust annotation system called Fast Colonoscopy Annotation Tool (FastCAT) was developed. The system simplifies the annotation process for gastroenterologists. Thereby the
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gastroenterologists only annotate key parts of the endoscopic video. Afterward, those video parts are pre-labeled by a polyp detection AI to speed up the process. After the AI has pre-labeled the frames, non-experts correct and finish the annotation. This annotation process is fast and ensures high quality. FastCAT reduces the overall workload of the gastroenterologist on average by a factor of 20 compared to an open-source state-of-art annotation tool.
The ubiquity of mobile devices fosters the combined use of ecological momentary assessments (EMA) and mobile crowdsensing (MCS) in the field of healthcare. This combination not only allows researchers to collect ecologically valid data, but also to use smartphone sensors to capture the context in which these data are collected. The TrackYourTinnitus (TYT) platform uses EMA to track users' individual subjective tinnitus perception and MCS to capture an objective environmental sound level while the EMA questionnaire is filled in. However, the sound level data cannot be used directly among the different smartphones used by TYT users, since uncalibrated raw values are stored. This work describes an approach towards making these values comparable. In the described setting, the evaluation of sensor measurements from different smartphone users becomes increasingly prevalent. Therefore, the shown approach can be also considered as a more general solution as it not only shows how it helped to interpret TYT sound level data, but may also stimulate other researchers, especially those who need to interpret sensor data in a similar setting. Altogether, the approach will show that measuring sound levels with mobile devices is possible in healthcare scenarios, but there are many challenges to ensuring that the measured values are interpretable.
Smart sensors and smartphones are becoming increasingly prevalent. Both can be used to gather environmental data (e.g., noise). Importantly, these devices can be connected to each other as well as to the Internet to collect large amounts of sensor data, which leads to many new opportunities. In particular, mobile crowdsensing techniques can be used to capture phenomena of common interest. Especially valuable insights can be gained if the collected data are additionally related to the time and place of the measurements. However, many technical solutions still use monolithic backends that are not capable of processing crowdsensing data in a flexible, efficient, and scalable manner. In this work, an architectural design was conceived with the goal to manage geospatial data in challenging crowdsensing healthcare scenarios. It will be shown how the proposed approach can be used to provide users with an interactive map of environmental noise, allowing tinnitus patients and other health-conscious people to avoid locations with harmful sound levels. Technically, the shown approach combines cloud-native applications with Big Data and stream processing concepts. In general, the presented architectural design shall serve as a foundation to implement practical and scalable crowdsensing platforms for various healthcare scenarios beyond the addressed use case.
This technical report introduces the Descartes Modeling Language (DML), a new architecture-level modeling language for modeling Quality-of-Service (QoS) and resource management related aspects of modern dynamic IT systems, infrastructures and services. DML is designed to serve as a basis for self-aware resource management during operation ensuring that system QoS requirements are continuously satisfied while infrastructure resources are utilized as efficiently as possible.
Complexity and Partitions
(2001)
Computational complexity theory usually investigates the complexity of sets, i.e., the complexity of partitions into two parts. But often it is more appropriate to represent natural problems by partitions into more than two parts. A particularly interesting class of such problems consists of classification problems for relations. For instance, a binary relation R typically defines a partitioning of the set of all pairs (x,y) into four parts, classifiable according to the cases where R(x,y) and R(y,x) hold, only R(x,y) or only R(y,x) holds or even neither R(x,y) nor R(y,x) is true. By means of concrete classification problems such as Graph Embedding or Entailment (for propositional logic), this thesis systematically develops tools, in shape of the boolean hierarchy of NP-partitions and its refinements, for the qualitative analysis of the complexity of partitions generated by NP-relations. The Boolean hierarchy of NP-partitions is introduced as a generalization of the well-known and well-studied Boolean hierarchy (of sets) over NP. Whereas the latter hierarchy has a very simple structure, the situation is much more complicated for the case of partitions into at least three parts. To get an idea of this hierarchy, alternative descriptions of the partition classes are given in terms of finite, labeled lattices. Based on these characterizations the Embedding Conjecture is established providing the complete information on the structure of the hierarchy. This conjecture is supported by several results. A natural extension of the Boolean hierarchy of NP-partitions emerges from the lattice-characterization of its classes by considering partition classes generated by finite, labeled posets. It turns out that all significant ideas translate from the case of lattices. The induced refined Boolean hierarchy of NP-partitions enables us more accuratly capturing the complexity of certain relations (such as Graph Embedding) and a description of projectively closed partition classes.
Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research
(2021)
Creation and exchange of knowledge depends on collaboration. Recent work has suggested that the emergence of collaboration frequently relies on geographic proximity. However, being co-located tends to be associated with other dimensions of proximity, such as social ties or a shared organizational environment. To account for such factors, multiple dimensions of proximity have been proposed, including cognitive, institutional, organizational, social and geographical proximity. Since they strongly interrelate, disentangling these dimensions and their respective impact on collaboration is challenging. To address this issue, we propose various methods for measuring different dimensions of proximity. We then present an approach to compare and rank them with respect to the extent to which they indicate co-publications and co-inventions. We adapt the HypTrails approach, which was originally developed to explain human navigation, to co-author and co-inventor graphs. We evaluate this approach on a subset of the German research community, specifically academic authors and inventors active in research on artificial intelligence (AI). We find that social proximity and cognitive proximity are more important for the emergence of collaboration than geographic proximity.
Aktivitätsbasierte Verhaltensmodellierung und ihre Unterstützung bei Multiagentensimulationen
(2000)
Durch Zusammenführung traditioneller Methoden zur individuenbasierten Simulation und dem Konzept der Multiagentensysteme steht mit der Multiagentensimulation eine Methodik zur Verfügung, die es ermöglicht, sowohl technisch als auch konzeptionell eine neue Ebene an Detaillierung bei Modellbildung und Simulation zu erreichen. Ein Modell beruht dabei auf dem Konzept einer Gesellschaft: Es besteht aus einer Menge interagierender, aber in ihren Entscheidungen autonomen Einheiten, den Agenten. Diese ändern durch ihre Aktionen ihre Umwelt und reagieren ebenso auf die für sie wahrnehmbaren Änderungen in der Umwelt. Durch die Simulation jedes Agenten zusammen mit der Umwelt, in der er "lebt", wird die Dynamik im Gesamtsystem beobachtbar. In der vorliegenden Dissertation wurde ein Repräsentationsschema für Multiagentensimulationen entwickelt werden, das es Fachexperten, wie zum Beispiel Biologen, ermöglicht, selbständig ohne traditionelles Programmieren Multiagentenmodelle zu implementieren und mit diesen Experimente durchzuführen. Dieses deklarative Schema beruht auf zwei Basiskonzepten: Der Körper eines Agenten besteht aus Zustandsvariablen. Das Verhalten des Agenten kann mit Regeln beschrieben werden. Ausgehend davon werden verschiedene Strukturierungsansätze behandelt. Das wichtigste Konzept ist das der "Aktivität", einer Art "Verhaltenszustand": Während der Agent in einer Aktivität A verweilt, führt er die zugehörigen Aktionen aus und dies solange, bis eine Regel feuert, die diese Aktivität beendet und eine neue Aktivität auswählt. Durch Indizierung dieser Regeln bei den zugehörigen Aktivitäten und Einführung von abstrakten Aktivitäten entsteht ein Schema für eine vielfältig strukturierbare Verhaltensbeschreibung. Zu diesem Schema wurde ein Interpreter entwickelt, der ein derartig repräsentiertes Modell ausführt und so Simulationsexperimente mit dem Multiagentenmodell erlaubt. Auf dieser Basis wurde die Modellierungs- und Experimentierumgebung SeSAm ("Shell für Simulierte Agentensysteme") entwickelt. Sie verwendet vorhandene Konzepte aus dem visuellen Programmieren. Mit dieser Umgebung wurden Anwendungsmodelle aus verschiedenen Domänen realisiert: Neben abstrakten Spielbeispielen waren dies vor allem Fragestellungen zu sozialen Insekten, z.B. zum Verhalten von Ameisen, Bienen oder der Interaktion zwischen Bienenvölkern und Milbenpopulationen.
Die Realisierung einer koordinierten und effektiven Fortbewegung für einen mobilen Roboter in natürlichen, sich kontinuierlich verändernden Umgebungen unter sich ebenso bewegenden Hindernissen ist eine komplexe Aufgabe, die die Lösung einer Reihe von Unterproblemen voraussetzt. Die vorliegende Arbeit beschäftigt sich sowohl mit den Themen der Wahrnehmung und Fortbewegung in veränderlichen Umgebungen, als auch mit Methoden zur Analyse der Hindernisbewegungen in Zusammenhang mit der Roboterbewegung selbst. Die Wahrnehmung wird in erster Linie anhand von Laserscannern betrachtet, und ein entsprechendes Verfahren zur Hindernisdetektion und -verfolung wird vorgestellt. Dabei werden Verfahren der globalen Netzwerkoptimierung eingesetzt, um Korrespondenzen zwischen Objekten aus den Einzelbildern herzustellen, was sich positiv auf die Robustheit gegenüber Störungen durch sporadische kleine Objekte auswirkt. Die Navigation basiert auf einer Adaption des sog. "Velocity Obstacle" Ansatzes auf die vorhandene Fahrzeugkinematik, und eine kooperative Bewegungskoordination (Roboter begleitet Mensch) wird durch eine geeignete Auswahlregel für kollisionsfreie Geschwindigkeiten realisiert. Anschließend werden verschiedene Distanzmaße eingeführt, anhand derer sich etwa der Pfad des Roboters mit dem Pfad seiner Begleitperson vergleichen lässt. Weiter wird eine Klassifizierung von Situationen vorgenommen, in die der Roboter potentiell involviert sein kann, und nach einer Übersicht über existierende Ansätze zur automatischen Intentionserkennung wird ein praktikabler Ansatz zur Erkennung gezielter Behinderungen eines mobilen Roboters vorgestellt. Die Arbeit schließt mit einem neuen Ansatz der Bewegungsplanung in dynamischen Umgebungen, der auf rekursiven Modellen des Roboters von seinem Gegenüber basiert, d.h. der Roboter berechnet zunächst, wie er sich in der Situation des (intelligenten, beweglichen) Hindernisses fortbewegen würde, und bezieht dies in die Entscheidung über die eigene Fortbewegung mit ein. Je nach Rekursionstiefe entstehen hierdurch Verhaltensweisen unterschiedlichen Charakters für den Roboter.
A bipartite graph G=(U,V,E) is convex if the vertices in V can be linearly ordered such that for each vertex u∈U, the neighbors of u are consecutive in the ordering of V. An induced matching H of G is a matching for which no edge of E connects endpoints of two different edges of H. We show that in a convex bipartite graph with n vertices and m weighted edges, an induced matching of maximum total weight can be computed in O(n+m) time. An unweighted convex bipartite graph has a representation of size O(n) that records for each vertex u∈U the first and last neighbor in the ordering of V. Given such a compact representation, we compute an induced matching of maximum cardinality in O(n) time. In convex bipartite graphs, maximum-cardinality induced matchings are dual to minimum chain covers. A chain cover is a covering of the edge set by chain subgraphs, that is, subgraphs that do not contain induced matchings of more than one edge. Given a compact representation, we compute a representation of a minimum chain cover in O(n) time. If no compact representation is given, the cover can be computed in O(n+m) time. All of our algorithms achieve optimal linear running time for the respective problem and model, and they improve and generalize the previous results in several ways: The best algorithms for the unweighted problem versions had a running time of O(n\(^{2}\)) (Brandstädt et al. in Theor. Comput. Sci. 381(1–3):260–265, 2007. https://doi.org/10.1016/j.tcs.2007.04.006). The weighted case has not been considered before.
Today’s Internet architecture was not designed from scratch but was driven by new services that emerged during its development. Hence, it is often described as patchwork where additional patches are applied in case new services require modifications to the existing architecture. This process however is rather slow and hinders the development of innovative network services with certain architecture or network requirements. Currently discussed technologies like Software-Defined Networking (SDN) or Network Virtualization (NV) are seen as key enabling technologies to overcome this rigid best effort legacy of the Internet. Both technologies offer the possibility to create virtual networks that accommodate the specific needs of certain services. These logical networks are operated on top of a physical substrate and facilitate flexible network resource allocation as physical resources can be added and removed depending on the current network and load situation. In addition, the clear separation and isolation of networks foster the development of application-aware networks that fulfill the special requirements of emerging applications. A prominent use case that benefits from these extended capabilities of the network is denoted with service component mobility. Services hosted on Virtual Machines (VMs) follow their consuming mobile endpoints, so that access latency as well as consumed network resources are reduced. Especially for applications like video streaming, which consume a large fraction of the available resources, is this an important means to relieve the resource constraints and eventually provide better service quality. Service and endpoint mobility both allow an adaptation of the used paths between an offered service, i.e., video streaming and the consuming users in case the service quality drops due to network problems. To make evidence-based adaptations in case of quality drops, a scalable monitoring component is required that is able to monitor the service quality for video streaming applications with reliable accuracy. This monograph details challenges that arise when deploying a certain service, i.e., video streaming, in a future virtualized network architecture and discusses possible solutions. In particular, this work evaluates the performance of mechanisms enabling service mobility and presents an optimized architecture for service mobility. Concerning endpoint mobility, improvements are developed that reduce the latency between endpoints and consumed services and ensure connectivity regardless of the used mobile access network. In the last part, a network-based video quality monitoring solution is developed and its accuracy is evaluated.
The focus of this work lies on the communication issues of Medium Access Control (MAC) and routing protocols in the context of WSNs. The communication challenges in these networks mainly result from high node density, low bandwidth, low energy constraints and the hardware limitations in terms of memory, computational power and sensing capabilities of low-power transceivers. For this reason, the structure of WSNs is always kept as simple as possible to minimize the impact of communication issues. Thus, the majority of WSNs apply a simple one hop star topology since multi-hop communication has high demands on the routing protocol since it increases the bandwidth requirements of the network. Moreover, medium access becomes a challenging problem due to the fact that low-power transceivers are very limited in their sensing capabilities. The first contribution is represented by the Backoff Preamble-based MAC Protocol with Sequential Contention Resolution (BPS-MAC) which is designed to overcome the limitations of low-power transceivers. Two communication issues, namely the Clear Channel Assessment (CCA) delay and the turnaround time, are directly addressed by the protocol. The CCA delay represents the period of time which is required by the transceiver to detect a busy radio channel while the turnaround time specifies the period of time which is required to switch between receive and transmit mode. Standard Carrier Sense Multiple Access (CSMA) protocols do not achieve high performance in terms of packet loss if the traffic is highly correlated due to the fact that the transceiver is not able to sense the medium during the switching phase. Therefore, a node may start to transmit data while another node is already transmitting since it has sensed an idle medium right before it started to switch its transceiver from receive to transmit mode. The BPS-MAC protocol uses a new sequential preamble-based medium access strategy which can be adapted to the hardware capabilities of the transceivers. The protocol achieves a very low packet loss rate even in wireless networks with high node density and event-driven traffic without the need of synchronization. This makes the protocol attractive to applications such as structural health monitoring, where event suppression is not an option. Moreover, acknowledgments or complex retransmission strategies become almost unnecessary since the sequential preamble-based contention resolution mechanism minimizes the collision probability. However, packets can still be lost as a consequence of interference or other issues which affect signal propagation. The second contribution consists of a new routing protocol which is able to quickly detect topology changes without generating a large amount of overhead. The key characteristics of the Statistic-Based Routing (SBR) protocol are high end-to-end reliability (in fixed and mobile networks), load balancing capabilities, a smooth continuous routing metric, quick adaptation to changing network conditions, low processing and memory requirements, low overhead, support of unidirectional links and simplicity. The protocol can establish routes in a hybrid or a proactive mode and uses an adaptive continuous routing metric which makes it very flexible in terms of scalability while maintaining stable routes. The hybrid mode is optimized for low-power WSNs since routes are only established on demand. The difference of the hybrid mode to reactive routing strategies is that routing messages are periodically transmitted to maintain already established routes. However, the protocol stops the transmission of routing messages if no data packets are transmitted for a certain time period in order to minimize the routing overhead and the energy consumption. The proactive mode is designed for high data rate networks which have less energy constraints. In this mode, the protocol periodically transmits routing messages to establish routes in a proactive way even in the absence of data traffic. Thus, nodes in the network can immediately transmit data since the route to the destination is already established in advance. In addition, a new delay-based routing message forwarding strategy is introduced. The forwarding strategy is part of SBR but can also be applied to many routing protocols in order to modify the established topology. The strategy can be used, e.g. in mobile networks, to decrease the packet loss by deferring routing messages with respect to the neighbor change rate. Thus, nodes with a stable neighborhood forward messages faster than nodes within a fast changing neighborhood. As a result, routes are established through nodes with correlated movement which results in fewer topology changes due to higher link durations.
The Internet of Things (IoT) enables a variety of smart applications, including smart home, smart manufacturing, and smart city. By enhancing Business Process Management Systems with IoT capabilities, the execution and monitoring of business processes can be significantly improved. Providing a holistic support for modeling, executing and monitoring IoT-driven processes, however, constitutes a challenge. Existing process modeling and process execution languages, such as BPMN 2.0, are unable to fully meet the IoT characteristics (e.g., asynchronicity and parallelism) of IoT-driven processes. In this article, we present BPMNE4IoT—A holistic framework for modeling, executing and monitoring IoT-driven processes. We introduce various artifacts and events based on the BPMN 2.0 metamodel that allow realizing the desired IoT awareness of business processes. The framework is evaluated along two real-world scenarios from two different domains. Moreover, we present a user study for comparing BPMNE4IoT and BPMN 2.0. In particular, this study has confirmed that the BPMNE4IoT framework facilitates the support of IoT-driven processes.
Graphs are a frequently used tool to model relationships among entities. A graph is a binary relation between objects, that is, it consists of a set of objects (vertices) and a set of pairs of objects (edges).
Networks are common examples of modeling data as a graph. For example, relationships between persons in a social network, or network links between computers in a telecommunication network can be represented by a graph.
The clearest way to illustrate the modeled data is to visualize the graphs. The field of Graph Drawing deals with the problem of finding algorithms to automatically generate graph visualizations. The task is to find a "good" drawing, which can be measured by different criteria such as number of crossings between edges or the used area. In this thesis, we study Angular Schematization in Graph Drawing. By this, we mean drawings
with large angles (for example, between the edges at common vertices or at crossing points).
The thesis consists of three parts. First, we deal with the placement of boxes. Boxes are axis-parallel rectangles that can, for example, contain text.
They can be placed on a map to label important sites, or can be used to describe semantic relationships between words in a word network. In the second part of the thesis, we consider graph drawings visually guide the
viewer. These drawings generally induce large angles between edges that meet at a vertex. Furthermore, the edges are drawn crossing-free and in a way that
makes them easy to follow for the human eye. The third and final part is devoted to crossings with large angles. In drawings with crossings, it is important to have large angles between edges at their crossing point, preferably right angles.
This article introduces the Off-The-Shelf Stylus (OTSS), a framework for 2D interaction (in 3D) as well as for handwriting and sketching with digital pen, ink, and paper on physically aligned virtual surfaces in Virtual, Augmented, and Mixed Reality (VR, AR, MR: XR for short). OTSS supports self-made XR styluses based on consumer-grade six-degrees-of-freedom XR controllers and commercially available styluses. The framework provides separate modules for three basic but vital features: 1) The stylus module provides stylus construction and calibration features. 2) The surface module provides surface calibration and visual feedback features for virtual-physical 2D surface alignment using our so-called 3ViSuAl procedure, and surface interaction features. 3) The evaluation suite provides a comprehensive test bed combining technical measurements for precision, accuracy, and latency with extensive usability evaluations including handwriting and sketching tasks based on established visuomotor, graphomotor, and handwriting research. The framework’s development is accompanied by an extensive open source reference implementation targeting the Unity game engine using an Oculus Rift S headset and Oculus Touch controllers. The development compares three low-cost and low-tech options to equip controllers with a tip and includes a web browser-based surface providing support for interacting, handwriting, and sketching. The evaluation of the reference implementation based on the OTSS framework identified an average stylus precision of 0.98 mm (SD = 0.54 mm) and an average surface accuracy of 0.60 mm (SD = 0.32 mm) in a seated VR environment. The time for displaying the stylus movement as digital ink on the web browser surface in VR was 79.40 ms on average (SD = 23.26 ms), including the physical controller’s motion-to-photon latency visualized by its virtual representation (M = 42.57 ms, SD = 15.70 ms). The usability evaluation (N = 10) revealed a low task load, high usability, and high user experience. Participants successfully reproduced given shapes and created legible handwriting, indicating that the OTSS and it’s reference implementation is ready for everyday use. We provide source code access to our implementation, including stylus and surface calibration and surface interaction features, making it easy to reuse, extend, adapt and/or replicate previous results (https://go.uniwue.de/hci-otss).
An important but very time consuming part of the research process is literature review. An already large and nevertheless growing ground set of publications as well as a steadily increasing publication rate continue to worsen the situation. Consequently, automating this task as far as possible is desirable. Experimental results of systems are key-insights of high importance during literature review and usually represented in form of tables. Our pipeline KIETA exploits these tables to contribute to the endeavor of automation by extracting them and their contained knowledge from scientific publications. The pipeline is split into multiple steps to guarantee modularity as well as analyzability, and agnosticim regarding the specific scientific domain up until the knowledge extraction step, which is based upon an ontology. Additionally, a dataset of corresponding articles has been manually annotated with information regarding table and knowledge extraction. Experiments show promising results that signal the possibility of an automated system, while also indicating limits of extracting knowledge from tables without any context.
In der Arbeit wird ein neues Konzept für Fahrsimulator-Datenbasen vorgestellt. Der Anwender entwirft eine auf seine Fragestellung zugeschnittene Datenbasis mithilfe einer einfachen Skriptsprache. Das Straßennetzwerk wird auf einer topologischen Ebene repäsentiert. In jedem Simulationsschritt wird hieraus im Sichtbarkeitsbereich des Fahrers die geometrische Repäsentation berechnet. Die für den Fahrer unsichtbaren Teile des Straßenetzwerks können während der Simulation verändert werden. Diese Veränderungen können von der Route des Fahrers oder von den in der Simulation erhobenen Messerten abhängen. Zudem kann der Anwender das Straßennetzwerk interaktiv verändern. Das vorgestellte Konzept bietet zahlreiche Möglichkeiten zur Erzeugung reproduzierbarer Szenarien für Experimente in Fahrsimulatoren.
Background: Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed.
Results: (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones).
Conclusions: Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior.
Nowadays, robotics plays an important role in increasing fields of application. There exist many environments or situations where mobile robots instead of human beings are used, since the tasks are too hazardous, uncomfortable, repetitive, or costly for humans to perform. The autonomy and the mobility of the robot are often essential for a good solution of these problems. Thus, such a robot should at least be able to answer the question "Where am I?". This thesis investigates the problem of self-localizing a robot in an indoor environment using range measurements. That is, a robot equipped with a range sensor wakes up inside a building and has to determine its position using only its sensor data and a map of its environment. We examine this problem from an idealizing point of view (reducing it into a pure geometric one) and further investigate a method of Guibas, Motwani, and Raghavan from the field of computational geometry to solving it. Here, so-called visibility skeletons, which can be seen as coarsened representations of visibility polygons, play a decisive role. In the major part of this thesis we analyze the structures and the occurring complexities in the framework of this scheme. It turns out that the main source of complication are so-called overlapping embeddings of skeletons into the map polygon, for which we derive some restrictive visibility constraints. Based on these results we are able to improve one of the occurring complexity bounds in the sense that we can formulate it with respect to the number of reflex vertices instead of the total number of map vertices. This also affects the worst-case bound on the preprocessing complexity of the method. The second part of this thesis compares the previous idealizing assumptions with the properties of real-world environments and discusses the occurring problems. In order to circumvent these problems, we use the concept of distance functions, which model the resemblance between the sensor data and the map, and appropriately adapt the above method to the needs of realistic scenarios. In particular, we introduce a distance function, namely the polar coordinate metric, which seems to be well suited to the localization problem. Finally, we present the RoLoPro software where most of the discussed algorithms are implemented (including the polar coordinate metric).
For machine manufacturing companies, besides the production of high quality and reliable machines, requirements have emerged to maintain machine-related aspects through digital services. The development of such services in the field of the Industrial Internet of Things (IIoT) is dealing with solutions such as effective condition monitoring and predictive maintenance. However, appropriate data sources are needed on which digital services can be technically based. As many powerful and cheap sensors have been introduced over the last years, their integration into complex machines is promising for developing digital services for various scenarios. It is apparent that for components handling recorded data of these sensors they must usually deal with large amounts of data. In particular, the labeling of raw sensor data must be furthered by a technical solution. To deal with these data handling challenges in a generic way, a sensor processing pipeline (SPP) was developed, which provides effective methods to capture, process, store, and visualize raw sensor data based on a processing chain. Based on the example of a machine manufacturing company, the SPP approach is presented in this work. For the company involved, the approach has revealed promising results.
Ambalytics: a scalable and distributed system architecture concept for bibliometric network analyses
(2021)
A deep understanding about a field of research is valuable for academic researchers. In addition to technical knowledge, this includes knowledge about subareas, open research questions, and social communities (networks) of individuals and organizations within a given field. With bibliometric analyses, researchers can acquire quantitatively valuable knowledge about a research area by using bibliographic information on academic publications provided by bibliographic data providers. Bibliometric analyses include the calculation of bibliometric networks to describe affiliations or similarities of bibliometric entities (e.g., authors) and group them into clusters representing subareas or communities. Calculating and visualizing bibliometric networks is a nontrivial and time-consuming data science task that requires highly skilled individuals. In addition to domain knowledge, researchers must often provide statistical knowledge and programming skills or use software tools having limited functionality and usability. In this paper, we present the ambalytics bibliometric platform, which reduces the complexity of bibliometric network analysis and the visualization of results. It accompanies users through the process of bibliometric analysis and eliminates the need for individuals to have programming skills and statistical knowledge, while preserving advanced functionality, such as algorithm parameterization, for experts. As a proof-of-concept, and as an example of bibliometric analyses outcomes, the calculation of research fronts networks based on a hybrid similarity approach is shown. Being designed to scale, ambalytics makes use of distributed systems concepts and technologies. It is based on the microservice architecture concept and uses the Kubernetes framework for orchestration. This paper presents the initial building block of a comprehensive bibliometric analysis platform called ambalytics, which aims at a high usability for users as well as scalability.
Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i) in embryonic Danio rerio 4 and 8 days past fertilization (dpf) and (ii) to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ) wild-type and its septin mutant (unc-59(e261)). We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261) on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement). This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter). Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles) and specificity (true vesicles) as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual annotation. Both automatic and semi-automatic modes are explained including a tutorial.
In the present day, unmanned aerial vehicles become seemingly more popular every year, but, without regulation of the increasing number of these vehicles, the air space could become chaotic and uncontrollable. In this work, a framework is proposed to combine self-aware computing with multirotor formations to address this problem. The self-awareness is envisioned to improve the dynamic behavior of multirotors. The formation scheme that is implemented is called platooning, which arranges vehicles in a string behind the lead vehicle and is proposed to bring order into chaotic air space. Since multirotors define a general category of unmanned aerial vehicles, the focus of this thesis are quadcopters, platforms with four rotors. A modification for the LRA-M self-awareness loop is proposed and named Platooning Awareness. The implemented framework is able to offer two flight modes that enable waypoint following and the self-awareness module to find a path through scenarios, where obstacles are present on the way, onto a goal position. The evaluation of this work shows that the proposed framework is able to use self-awareness to learn about its environment, avoid obstacles, and can successfully move a platoon of drones through multiple scenarios.
Das Potenzial der Wissensentdeckung in Daten wird häufig nicht ausgenutzt, was hauptsächlich auf Barrieren zwischen dem Entwicklerteam und dem Endnutzer des Data-Mining zurückzuführen ist. In dieser Arbeit wird ein transparenter Ansatz zum Beschreiben und Erklären von Daten für Entscheidungsträger vorgestellt. In Entscheidungsträger-zentrierten Aufgaben werden die Projektanforderungen definiert und die Ergebnisse zu einer Geschichte zusammengestellt. Eine Anforderung besteht dabei aus einem tabellarischen Bericht und ggf. Mustern in seinem Inhalt, jeweils verständlich für einen Entscheidungsträger. Die technischen Aufgaben bestehen aus einer Datenprüfung, der Integration der Daten in einem Data-Warehouse sowie dem Generieren von Berichten und dem Entdecken von Mustern wie in den Anforderungen beschrieben. Mehrere Data-Mining-Projekte können durch Wissensmanagement sowie eine geeignete Infrastruktur voneinander profitieren. Der Ansatz wurde in zwei Projekten unter Verwendung von ausschließlich Open-Source-Software angewendet.
With the introduction of OpenFlow by the Stanford University in 2008, a process began in the area of network research, which questions the predominant approach of fully distributed network control. OpenFlow is a communication protocol that allows the externalization of the network control plane from the network devices, such as a router, and to realize it as a logically-centralized entity in software. For this concept, the term "Software Defined Networking" (SDN) was coined during scientific discourse.
For the network operators, this concept has several advantages. The two most important can be summarized under the points cost savings and flexibility. Firstly, it is possible through the uniform interface for network hardware ("Southbound API"), as implemented by OpenFlow, to combine devices and software from different manufacturers, which increases the innovation and price pressure on them. Secondly, the realization of the network control plane as a freely programmable software with open interfaces ("Northbound API") provides the opportunity to adapt it to the individual circumstances of the operator's network and to exchange information with the applications it serves. This allows the network to be more flexible and to react more quickly to changing circumstances as well as transport the traffic more effectively and tailored to the user’s "Quality of Experience" (QoE).
The approach of a separate network control layer for packet-based networks is not new and has already been proposed several times in the past. Therefore, the SDN approach has raised many questions about its feasibility in terms of efficiency and applicability. These questions are caused to some extent by the fact that there is no generally accepted definition of the SDN concept to date. It is therefore a part of this thesis to derive such a definition. In addition, several of the open issues are investigated. This Investigations follow the three aspects: Performance Evaluation of Software Defined Networking, applications on the SDN control layer, and the usability of SDN Northbound-API for creation application-awareness in network operation.
Performance Evaluation of Software Defined Networking: The question of the efficiency of an SDN-based system was from the beginning one of the most important. In this thesis, experimental measurements of the performance of OpenFlow-enabled switch hardware and control software were conducted for the purpose of answering this question. The results of these measurements were used as input parameters for establishing an analytical model of the reactive SDN approach. Through the model it could be determined that the performance of the software control layer, often called "Controller", is crucial for the overall performance of the system, but that the approach is generally viable. Based on this finding a software for analyzing the performance of SDN controllers was developed. This software allows the emulation of the forwarding layer of an SDN network towards the control software and can thus determine its performance in different situations and configurations. The measurements with this software showed that there are quite significant differences in the behavior of different control software implementations. Among other things it has been shown that some show different characteristics for various switches, in particular in terms of message processing speed. Under certain circumstances this can lead to network failures.
Applications on the SDN control layer: The core piece of software defined networking are the intelligent network applications that operate on the control layer. However, their development is still in its infancy and little is known about the technical possibilities and their limitations. Therefore, the relationship between an SDN-based and classical implementation of a network function is investigated in this thesis. This function is the monitoring of network links and the traffic they carry. A typical approach for this task has been built based on Wiretapping and specialized measurement hardware and compared with an implementation based on OpenFlow switches and a special SDN control application. The results of the comparison show that the SDN version can compete in terms of measurement accuracy for bandwidth and delay estimation with the traditional measurement set-up. However, a compromise has to be found for measurements below the millisecond range.
Another question regarding the SDN control applications is whether and how well they can solve existing problems in networks. Two programs have been developed based on SDN in this thesis to solve two typical network issues. Firstly, the tool "IPOM", which enables considerably more flexibility in the study of effects of network structures for a researcher, who is confined to a fixed physical test network topology.
The second software provides an interface between the Cloud Orchestration Software "OpenNebula" and an OpenFlow controller. The purpose of this software was to investigate experimentally whether a pre-notification of the network of an impending relocation of a virtual service in a data center is sufficient to ensure the continuous operation of that service. This was demonstrated on the example of a video service.
Usability of the SDN Northbound API for creating application-awareness in network operation: Currently, the fact that the network and the applications that run on it are developed and operated separately leads to problems in network operation. SDN offers with the Northbound-API an open interface that enables the exchange between information of both worlds during operation. One aim of this thesis was to investigate whether this interface can be exploited so that the QoE experienced by the user can be maintained on high level. For this purpose, the QoE influence factors were determined on a challenging application by means of a subjective survey study. The application is cloud gaming, in which the calculation of video game environments takes place in the cloud and is transported via video over the network to the user. It was shown that apart from the most important factor influencing QoS, i.e., packet loss on the downlink, also the type of game type and its speed play a role. This demonstrates that in addition to QoS the application state is important and should be communicated to the network. Since an implementation of such a state conscious SDN for the example of Cloud Gaming was not possible due to its proprietary implementation, in this thesis the application “YouTube video streaming” was chosen as an alternative. For this application, status information is retrievable via the "Yomo" tool and can be used for network control. It was shown that an SDN-based implementation of an application-aware network has distinct advantages over traditional network management methods and the user quality can be obtained in spite of disturbances.
Future mobile communication networks, such as 5G and beyond, can benefit from Virtualized Network Functions (VNFs) when deployed on cloud infrastructures to achieve elasticity and scalability. However, new challenges arise as to managing states of Network Functions (NFs). Especially control plane VNFs, which are mainly found in cellular core networks like the 5G Core (5GC), received little attention since the shift towards virtualizing NFs. Most existing solutions for these core networks are often complex, intrusive, and are seldom compliant with the standard. With the emergence of 5G campus networks, UEs will be mainly machine-type devices. These devices communicate more deterministically, bringing new opportunities for elaborated state management. This work presents an emulation environment to perform rigorous measurements on state access patterns. The emulation comes with a fully parameterized Markov model for the UE to examine a wide variety of different devices. These measurements can then be used as a solid base for designing an efficient, simple, and standard conform state management solution that brings us further towards stateless core networks.
No abstract available
Die Dissertation befaßt sich mit der Entwicklung einer multimedialen, datenbankgestützten Lehr- und Lernplattform. Die entwickelten Module ermöglichen und erweitern nicht nur die Möglichkeit des Selbststudiums für den Studenten sondern erleichtern auch die Arbeit der Dozenten. Außerdem wird auch die Zusammenarbeit und der Austausch von Lernobjekten zwischen verschiedenen Institutionen ermöglicht. In der Lehr- und Lernplattform können verschiedene Lernobjekt-Typen verwaltet werden. Exemplarisch wurden die Typen Bilder, 3D-Animationen, Vorlesungen, Lerntexte, Fallbeispiele und Quizelemente integriert. Die Lehr- und Lernplattform besteht aus drei Bausteinen: 1. In der Lernobjekt-Datenbank werden alle Lernobjekt-Typen und Lernobjekte verwaltet. 2. Autorenwerkzeuge dienen zur Erstellung von Lernobjekten. 3. In der Lernplattform werden die Lernobjekte den Studenten zum (Selbst-)Lernen präsentiert. Neben den Vorteilen, die der Einsatz von E-Learning im allgemeinen bietet, wie die flexible Lernorganisation oder die Nutzung von Lerninhalten unabhängig von Ort und Zeit, zeichnet sich die entwickelte Lehr- und Lernplattform besonders durch folgende Punkte aus: Generierung von Lerninhalten höherer Qualität durch multizentrische Expertenbündelung und Arbeitsteilung, Erweiterbarkeit auf andere, neue Lernobjekt-Typen, Verwaltbarkeit, Konsistenz, Flexibilität, geringer Verwaltungsaufwand, Navigationsmöglichkeiten für den Studenten, Personalisierbarkeit und Konformität zu internationalen Standards. Sowohl bei der Modellierung als auch bei der Umsetzung wurde darauf geachtet, möglichst gut die Anforderungen der Dermatologie bei gleichzeitiger Erweiterbarkeit auf andere, ähnliche Szenarien zu erfüllen. Besonders einfach sollte die Anpassung der Plattform für andere bildorientierte Disziplinen sein.
Two studies are reported that investigate how readily accessible and applicable ten force-dynamic categories are to novices in describing short episodes of human-technology interaction (Study 1) and that establish a measure of inter-coder reliability when re-classifying these episodes into force-dynamic categories (Study 2). The results of the first study show that people can easily and confidently relate their experiences with technology to the definitions of force-dynamic events (e.g. “The driver released the handbrake” as an example of restraint removal). The results of the second study show moderate agreement between four expert coders across all ten force-dynamic categories (Cohen’s kappa = .59) when re-classifying these episodes. Agreement values for single force-dynamic categories ranged between ‘fair’ and ‘almost perfect’, i.e. between kappa = .30 and .95. Agreement with the originally intended classifications of study 1 was higher than the pure inter-coder reliabilities. Single coders achieved an average kappa of .71, indicating substantial agreement. Using more than one coder increased kappas to almost perfect: up to .87 for four coders. A qualitative analysis of the predicted versus the observed number of category confusions revealed that about half of the category disagreement could be predicted from strong overlaps in the definitions of force-dynamic categories. From the quantitative and qualitative results, guidelines are derived to aid the better training of coders in order to increase inter-coder reliability.
For formative evaluations of user experience (UX) a variety of methods have been developed over the years. However, most techniques require the users to interact with the study as a secondary task. This active involvement in the evaluation is not inclusive of all users and potentially biases the experience currently being studied. Yet there is a lack of methods for situations in which the user has no spare cognitive resources. This condition occurs when 1) users' cognitive abilities are impaired (e.g., people with dementia) or 2) users are confronted with very demanding tasks (e.g., air traffic controllers). In this work we focus on emotions as a key component of UX and propose the new structured observation method Proxemo for formative UX evaluations. Proxemo allows qualified observers to document users' emotions by proxy in real time and then directly link them to triggers. Technically this is achieved by synchronising the timestamps of emotions documented by observers with a video recording of the interaction.
In order to facilitate the documentation of observed emotions in highly diverse contexts we conceptualise and implement two separate versions of a documentation aid named Proxemo App. For formative UX evaluations of technology-supported reminiscence sessions with people with dementia, we create a smartwatch app to discreetly document emotions from the categories anger, general alertness, pleasure, wistfulness and pride. For formative UX evaluations of prototypical user interfaces with air traffic controllers we create a smartphone app to efficiently document emotions from the categories anger, boredom, surprise, stress and pride. Descriptive case studies in both application domains indicate the feasibility and utility of the method Proxemo and the appropriateness of the respectively adapted design of the Proxemo App.
The third part of this work is a series of meta-evaluation studies to determine quality criteria of Proxemo. We evaluate Proxemo regarding its reliability, validity, thoroughness and effectiveness, and compare Proxemo's efficiency and the observers' experience to documentation with pen and paper. Proxemo is reliable, as well as more efficient, thorough and effective than handwritten notes and provides a better UX to observers. Proxemo compares well with existing methods where benchmarks are available.
With Proxemo we contribute a validated structured observation method that has shown to meet requirements formative UX evaluations in the extreme contexts of users with cognitive impairments or high task demands. Proxemo is agnostic regarding researchers' theoretical approaches and unites reductionist and holistic perspectives within one method.
Future work should explore the applicability of Proxemo for further domains and extend the list of audited quality criteria to include, for instance, downstream utility. With respect to basic research we strive to better understand the sources leading observers to empathic judgments and propose reminisce and older adults as model environment for investigating mixed emotions.
In future telecommunication systems, we observe an increasing diversity of access networks. The separation of transport services and applications or services leads to multi-network services, i.e., a future service has to work transparently to the underlying network infrastructure. Multi-network services with edge-based intelligence, like P2P file sharing or the Skype VoIP service, impose new traffic control paradigms on the future Internet. Such services adapt the amount of consumed bandwidth to reach different goals. A selfish behavior tries to keep the QoE of a single user above a certain level. Skype, for instance, repeats voice samples depending on the perceived end-to-end loss. From the viewpoint of a single user, the replication of voice data overcomes the degradation caused by packet loss and enables to maintain a certain QoE. The cost for this achievement is a higher amount of consumed bandwidth. However, if the packet loss is caused by congestion in the network, this additionally required bandwidth even worsens the network situation. Altruistic behavior, on the other side, would reduce the bandwidth consumption in such a way that the pressure on the network is released and thus the overall network performance is improved. In this monograph, we analyzed the impact of the overlay, P2P, and QoE paradigms in future Internet applications and the interactions from the observing user behavior. The shift of intelligence toward the edge is accompanied by a change in the emerging user behavior and traffic profile, as well as a change from multi-service networks to multi-networks services. In addition, edge-based intelligence may lead to a higher dynamics in the network topology, since the applications are often controlled by an overlay network, which can rapidly change in size and structure as new nodes can leave or join the overlay network in an entirely distributed manner. As a result, we found that the performance evaluation of such services provides new challenges, since novel key performance factors have to be first identified, like pollution of P2P systems, and appropriate models of the emerging user behavior are required, e.g. taking into account user impatience. As common denominator of the presented studies in this work, we focus on a user-centric view when evaluating the performance of future Internet applications. For a subscriber of a certain application or service, the perceived quality expressed as QoE will be the major criterion of the user's satisfaction with the network and service providers. We selected three different case studies and characterized the application's performance from the end user's point of view. Those are (1) cooperation in mobile P2P file sharing networks, (2) modeling of online TV recording services, and (3) QoE of edge-based VoIP applications. The user-centric approach facilitates the development of new mechanisms to overcome problems arising from the changing user behavior. An example is the proposed CycPriM cooperation strategy, which copes with selfish user behavior in mobile P2P file sharing system. An adequate mechanism has also been shown to be efficient in a heterogeneous B3G network with mobile users conducting vertical handovers between different wireless access technologies. The consideration of the user behavior and the user perceived quality guides to an appropriate modeling of future Internet applications. In the case of the online TV recording service, this enables the comparison between different technical realizations of the system, e.g. using server clusters or P2P technology, to properly dimension the installed network elements and to assess the costs for service providers. Technologies like P2P help to overcome phenomena like flash crowds and improve scalability compared to server clusters, which may get overloaded in such situations. Nevertheless, P2P technology invokes additional challenges and different user behavior to that seen in traditional client/server systems. Beside the willingness to share files and the churn of users, peers may be malicious and offer fake contents to disturb the data dissemination. Finally, the understanding and the quantification of QoE with respect to QoS degradations permits designing sophisticated edge-based applications. To this end, we identified and formulated the IQX hypothesis as an exponential interdependency between QoE and QoS parameters, which we validated for different examples. The appropriate modeling of the emerging user behavior taking into account the user's perceived quality and its interactions with the overlay and P2P paradigm will finally help to design future Internet applications.
3D point clouds are a de facto standard for 3D documentation and modelling. The advances in laser scanning technology broadens the usability and access to 3D measurement systems. 3D point clouds are used in many disciplines such as robotics, 3D modelling, archeology and surveying. Scanners are able to acquire up to a million of points per second to represent the environment with a dense point cloud. This represents the captured environment with a very high degree of detail. The combination of laser scanning technology with photography adds color information to the point clouds. Thus the environment is represented more realistically. Full 3D models of environments, without any occlusion, require multiple scans. Merging point clouds is a challenging process. This thesis presents methods for point cloud registration based on the panorama images generated from the scans. Image representation of point clouds introduces 2D image processing methods to 3D point clouds. Several projection methods for the generation of panorama maps of point clouds are presented in this thesis. Additionally, methods for point cloud reduction and compression based on the panorama maps are proposed. Due to the large amounts of data generated from the 3D measurement systems these methods are necessary to improve the point cloud processing, transmission and archiving. This thesis introduces point cloud processing methods as a novel framework for the digitisation of archeological excavations. The framework replaces the conventional documentation methods for excavation sites. It employs point clouds for the generation of the digital documentation of an excavation with the help of an archeologist on-site. The 3D point cloud is used not only for data representation but also for analysis and knowledge generation. Finally, this thesis presents an autonomous indoor mobile mapping system. The mapping system focuses on the sensor placement planning method. Capturing a complete environment requires several scans. The sensor placement planning method solves for the minimum required scans to digitise large environments. Combining this method with a navigation system on a mobile robot platform enables it to acquire data fully autonomously. This thesis introduces a novel hole detection method for point clouds to detect obscured parts of a captured environment. The sensor placement planning method selects the next scan position with the most coverage of the obscured environment. This reduces the required number of scans. The navigation system on the robot platform consist of path planning, path following and obstacle avoidance. This guarantees the safe navigation of the mobile robot platform between the scan positions. The sensor placement planning method is designed as a stand alone process that could be used with a mobile robot platform for autonomous mapping of an environment or as an assistant tool for the surveyor on scanning projects.
Scalability is often mentioned in literature, but a stringent definition is missing. In particular, there is no general scalability assessment which clearly indicates whether a system scales or not or whether a system scales better than another. The key contribution of this article is the definition of a scalability index (SI) which quantifies if a system scales in comparison to another system, a hypothetical system, e.g., linear system, or the theoretically optimal system. The suggested SI generalizes different metrics from literature, which are specialized cases of our SI. The primary target of our scalability framework is, however, benchmarking of two systems, which does not require any reference system. The SI is demonstrated and evaluated for different use cases, that are (1) the performance of an IoT load balancer depending on the system load, (2) the availability of a communication system depending on the size and structure of the network, (3) scalability comparison of different location selection mechanisms in fog computing with respect to delays and energy consumption; (4) comparison of time-sensitive networking (TSN) mechanisms in terms of efficiency and utilization. Finally, we discuss how to use and how not to use the SI and give recommendations and guidelines in practice. To the best of our knowledge, this is the first work which provides a general SI for the comparison and benchmarking of systems, which is the primary target of our scalability analysis.
This thesis deals with the management and analysis of source code, which is represented in XML. Using the elementary methods of the XML repository, the XML source code representation is accessed, changed, updated, and saved. We reason about the source code, refactor source code and we visualize dependency graphs for call analysis. The visualized dependencies between files, modules, or packages are used to structure the source code in order to get a system, which is easily to comprehend, to modify and to complete. Sophisticated methods have been developed to slice the source code in order to obtain a working package of a large system, containing only a specific functionality. The basic methods, on which the visualizations and analyses are built on can be changed like changing a plug-in. The visualization methods can be reused in order to handle arbitrary source code representations, e.g., JAML, PHPML, PROLOGML. Dependencies of other context can be visualized, too, e.g., ER diagrams, or website references. The tool SCAV supports source code visualization and analyzing methods.
Within the healthcare environment, mobile health (mHealth) applications (apps) are becoming more and more important. The number of new mHealth apps has risen steadily in the last years. Especially the COVID-19 pandemic has led to an enormous amount of app releases. In most countries, mHealth applications have to be compliant with several regulatory aspects to be declared a “medical app”. However, the latest applicable medical device regulation (MDR) does not provide more details on the requirements for mHealth applications. When developing a medical app, it is essential that all contributors in an interdisciplinary team — especially software engineers — are aware of the specific regulatory requirements beforehand. The development process, however, should not be stalled due to integration of the MDR. Therefore, a developing framework that includes these aspects is required to facilitate a reliable and quick development process. The paper at hand introduces the creation of such a framework on the basis of the Corona Health and Corona Check apps. The relevant regulatory guidelines are listed and summarized as a guidance for medical app developments during the pandemic and beyond. In particular, the important stages and challenges faced that emerged during the entire development process are highlighted.
Routing is one of the most important issues in any communication network. It defines on which path packets are transmitted from the source of a connection to the destination. It allows to control the distribution of flows between different locations in the network and thereby is a means to influence the load distribution or to reach certain constraints imposed by particular applications. As failures in communication networks appear regularly and cannot be completely avoided, routing is required to be resilient against such outages, i.e., routing still has to be able to forward packets on backup paths even if primary paths are not working any more.
Throughout the years, various routing technologies have been introduced that are very different in their control structure, in their way of working, and in their ability to handle certain failure cases. Each of the different routing approaches opens up their own specific questions regarding configuration, optimization, and inclusion of resilience issues. This monograph investigates, with the example of three particular routing technologies, some concrete issues regarding the analysis and optimization of resilience. It thereby contributes to a better general, technology-independent understanding of these approaches and of their diverse potential for the use in future network architectures.
The first considered routing type, is decentralized intra-domain routing based on administrative IP link costs and the shortest path principle. Typical examples are common today's intra-domain routing protocols OSPF and IS-IS. This type of routing includes automatic restoration abilities in case of failures what makes it in general very robust even in the case of severe network outages including several failed components. Furthermore, special IP-Fast Reroute mechanisms allow for a faster reaction on outages. For routing based on link costs, traffic engineering, e.g. the optimization of the maximum relative link load in the network, can be done indirectly by changing the administrative link costs to adequate values.
The second considered routing type, MPLS-based routing, is based on the a priori configuration of primary and backup paths, so-called Label Switched Paths. The routing layout of MPLS paths offers more freedom compared to IP-based routing as it is not restricted by any shortest path constraints but any paths can be setup. However, this in general involves a higher configuration effort.
Finally, in the third considered routing type, typically centralized routing using a Software Defined Networking (SDN) architecture, simple switches only forward packets according to routing decisions made by centralized controller units. SDN-based routing layouts offer the same freedom as for explicit paths configured using MPLS. In case of a failure, new rules can be setup by the controllers to continue the routing in the reduced topology. However, new resilience issues arise caused by the centralized architecture. If controllers are not reachable anymore, the forwarding rules in the single nodes cannot be adapted anymore. This might render a rerouting in case of connection problems in severe failure scenarios infeasible.
Innovative Software kann die Position eines Unternehmens im Wettbewerb sichern. Die Einführung innovativer Software ist aber alles andere als einfach. Denn obgleich die technischen Aspekte offensichtlicher sind, dominieren organisationale Aspekte. Zu viele Softwareprojekte schlagen fehl, da die Einführung nicht gelingt, trotz Erfüllung technischer Anforderungen. Vor diesem Hintergrund ist das Forschungsziel der Masterarbeit, Risiken und Erfolgsfaktoren für die Einführung innovativer Software in Unternehmen zu finden, eine Strategie zu formulieren und dabei die Bedeutung von Schlüsselpersonen zu bestimmen.
Crowdsensing offers a cost-effective way to collect large amounts of environmental sensor data; however, the spatial distribution of crowdsensing sensors can hardly be influenced, as the participants carry the sensors, and, additionally, the quality of the crowdsensed data can vary significantly. Hybrid systems that use mobile users in conjunction with fixed sensors might help to overcome these limitations, as such systems allow assessing the quality of the submitted crowdsensed data and provide sensor values where no crowdsensing data are typically available. In this work, we first used a simulation study to analyze a simple crowdsensing system concerning the detection performance of spatial events to highlight the potential and limitations of a pure crowdsourcing system. The results indicate that even if only a small share of inhabitants participate in crowdsensing, events that have locations correlated with the population density can be easily and quickly detected using such a system. On the contrary, events with uniformly randomly distributed locations are much harder to detect using a simple crowdsensing-based approach. A second evaluation shows that hybrid systems improve the detection probability and time. Finally, we illustrate how to compute the minimum number of fixed sensors for the given detection time thresholds in our exemplary scenario.
This work focuses on coordination methods and the control of motion in groups of nonholonomic wheeled mobile robots, in particular of the car-like type. These kind of vehicles are particularly restricted in their mobility. In the main part of this work the two problems of formation motion coordination and of rendezvous in distributed multi-vehicle systems are considered. We introduce several enhancements to an existing motion planning approach for formations of nonholonomic mobile robots. Compared to the original method, the extended approach is able to handle time-varying reference speeds as well as adjustments of the formation's shape during reference trajectory segments with continuously differentiable curvature. Additionally, undesired discontinuities in the speed and steering profiles of the vehicles are avoided. Further, the scenario of snow shoveling on an airfield by utilizing multiple formations of autonomous snowplows is discussed. We propose solutions to the subproblems of motion planning for the formations and tracking control for the individual vehicles. While all situations that might occur have been tested in a simulation environment, we also verified the developed tracking controller in real robot hardware experiments. The task of the rendezvous problem in groups of car-like robots is to drive all vehicles to a common position by means of decentralized control laws. Typically there exists no direct interaction link between all of the vehicles. In this work we present decentralized rendezvous control laws for vehicles with free and with bounded steering. The convergence properties of the approaches are analyzed by utilizing Lyapunov based techniques. Furthermore, they are evaluated within various simulation experiments, while the bounded steering case is also verified within laboratory hardware experiments. Finally we introduce a modification to the bounded steering system that increases the convergence speed at the expense of a higher traveled distance of the vehicles.
Cooperative, connected and automated mobility (CCAM) systems depend on a reliable communication to provide their service and more crucially to ensure the safety of users. One way to ensure the reliability of a data transmission is to use multiple transmission technologies in combination with redundant flows. In this paper, we describe a system requiring multipath communication in the context of CCAM. To this end, we introduce a data plane-based scheduler that uses replication and integration modules to provide redundant and transparent multipath communication. We provide an analytical model for the full replication module of the system and give an overview of how and where the data-plane scheduler components can be realized.
Cooperative, connected and automated mobility (CCAM) systems depend on a reliable communication to provide their service and more crucially to ensure the safety of users. One way to ensure the reliability of a data transmission is to use multiple transmission technologies in combination with redundant flows. In this paper, we describe a system requiring multipath communication in the context of CCAM. To this end, we introduce a data plane-based scheduler that uses replication and integration modules to provide redundant and transparent multipath communication. We provide an analytical model for the full replication module of the system and give an overview of how and where the data-plane scheduler components can be realized.
Radiation therapy today, on account of improvements in treatment procedures over the last 60 years, allows precise treatment of static tumors inside the human body. However, irradiation of moving tumors is still a challenging task as moving tumors often leave the treatment beam and the radiation dose delivered to the tumor reduces simultaneously increasing that on healthy tissue. This research work aims to push the frontiers of radiation therapy in order to enable precise treatment of moving tumors with focus on research and development of a unique real-time system enabling active motion compensation through robotic means to compensate tumor motion. During treatment, patients lie on a treatment couch which is normally used for static position corrections of patient set-up errors prior to radiation treatment. The treatment couch used, called HexaPOD, is a parallel manipulator with six degrees of freedom which can precisely position heavy loads inside a small region. Despite the HexaPOD not initially built with dynamics in mind, it is used in this work for sustained motion compensation by moving patients such that tumors stay precisely located at the center of the treatment beam during the complete course of treatment. In order to realize real-time tumor motion compensation by means of the HexaPOD, several challanges need to be addressed. Real-time aspects are covered by the adoption of a hard real-time operation system in combination with measurement and estimation of latencies of all physical quantities in the compensation system such as tumor or breathing position measurements. Accurate timing information is respected consistently in the whole system and all software-induced latencies are adaptively compensated for. This requires knowledge of future tumor positions from predictors. Several predictors for breathing and tumor motion predictions are proposed and evaluated in terms of a variety of different performance metrics. Extensions to prediction algorithms are introduced fusing both breathing and tumor position information to allow for predictions without the need of an explicit correlation model. Predictions determine the future motion path of the HexaPOD in order to compensate for tumor motion. Several control schemes are developed to enable reference tracking for the HexaPOD. Based on linear and non-linear dynamic modelling of the HexaPOD with system identification methods, a first controller is derived in the form of a model predictive controller. A second controller is proposed based on an assumption of the working principle of the HexaPOD's internal controller. Finally, a third controller is derived as combination of the first and second one. For each of these controllers, comparative results with real hardware experiments and humans in the loop as well as choices of free parameters are presented and discussed. Apart from precise tracking, emphasis is placed on patient comfort which is of crucial importance for acceptance of the system. It is demonstrated that smooth trajectories can be realized by the controllers to guarantee that patients feel comfortable while their tumor motion is compensated at sub-millimeter accuracies. Overall errors of the system are analyzed by relating them to tracking and prediction errors. By exploiting the properties of different predictors, it is shown that the startup time until tracking is reached can be reduced to only a few seconds, even in the case of an initially at-rest HexaPOD and with no initial knowledge of tumor motion. This makes the system especially suitable for the relatively short-fractionated treatment sessions for lung tumors. The tumor motion compensation system has been developed solely based on standard clinical hardware, found in most treatment rooms. With a simple and flexible design, existing treatment can be updated in a cost-efficient way to introduce motion compensation capabilities. Simultaneously, the system does not impose any constraints on state-of-the-art treatment types such as intensity modulated radiotherapy or volumetric modulated arc therapy. Supporting different compensation modes, the system can be applied to any moving tumor whether its motion is predictable (lung tumors) or unpredictable (prostate tumors). By integration of adequate tumor position determination methods, the system can be easily extended to other tumors as well.
Verteilte dynamische Systeme unter lokalen und globalen Gesichtspunkten zu optimieren ist eine schwierige Aufgabe. Zwar sind grundsätzliche Auswirkungen einzelner Maßnahmen häufig bekannt, durch widerstrebende Ziele, Wechselwirkungen zwischen Prozessen und Nebenwirkungen von Maßnahmen ist ein analytisches Vorgehen bei der Optimierung nicht möglich. Besonders schwierig wird es, wenn lokale Einheiten einerseits ihre Ziele und Autonomie behalten sollen, aber durch zentrale Vorgaben bzw. Anreize so gesteuert werden sollen, dass ein übergeordnetes Ziel erreicht wird. Ein praktisches Beispiel dieses allgemeinen Optimierungsproblems findet sich im Gesundheitswesen. Das Management von modernen Kliniken ist stets mit dem Problem konfrontiert, die Qualität der Pflege zu gewährleisten und gleichzeitig kosteneffizient zu arbeiten. Hier gilt es unter gegeben Rahmenbedingungen und bei Respektierung der Autonomie der Funktionseinheiten, Optimierungsmaßnahmen zu finden und durchzuführen. Vorhandene Werkzeuge zur Simulation und Modellierung bieten für diese Aufgabe keine ausreichend guten Vorgehensmodelle und Modellierungsmechanismen. Die agentenbasierte Simulation ermöglicht die Abbildung solcher Systeme und die Durchführung von Simulationsexperimenten zur Bewertung einzelner Maßnahmen. Es werden Lösungswege und Werkzeuge vorgestellt und evaluiert, die den Benutzer bei der Formalisierung des Wissens und der Modellierung solch komplexer Szenarien unterstützen und ein systematisches Vorgehen zur Optimierung ermöglichen.
CLIP knows image aesthetics
(2022)
Most Image Aesthetic Assessment (IAA) methods use a pretrained ImageNet classification model as a base to fine-tune. We hypothesize that content classification is not an optimal pretraining task for IAA, since the task discourages the extraction of features that are useful for IAA, e.g., composition, lighting, or style. On the other hand, we argue that the Contrastive Language-Image Pretraining (CLIP) model is a better base for IAA models, since it has been trained using natural language supervision. Due to the rich nature of language, CLIP needs to learn a broad range of image features that correlate with sentences describing the image content, composition, environments, and even subjective feelings about the image. While it has been shown that CLIP extracts features useful for content classification tasks, its suitability for tasks that require the extraction of style-based features like IAA has not yet been shown. We test our hypothesis by conducting a three-step study, investigating the usefulness of features extracted by CLIP compared to features obtained from the last layer of a comparable ImageNet classification model. In each step, we get more computationally expensive. First, we engineer natural language prompts that let CLIP assess an image's aesthetic without adjusting any weights in the model. To overcome the challenge that CLIP's prompting only is applicable to classification tasks, we propose a simple but effective strategy to convert multiple prompts to a continuous scalar as required when predicting an image's mean aesthetic score. Second, we train a linear regression on the AVA dataset using image features obtained by CLIP's image encoder. The resulting model outperforms a linear regression trained on features from an ImageNet classification model. It also shows competitive performance with fully fine-tuned networks based on ImageNet, while only training a single layer. Finally, by fine-tuning CLIP's image encoder on the AVA dataset, we show that CLIP only needs a fraction of training epochs to converge, while also performing better than a fine-tuned ImageNet model. Overall, our experiments suggest that CLIP is better suited as a base model for IAA methods than ImageNet pretrained networks.
While developing modern applications, it is necessary to ensure an efficient and performant communication between different applications. In current environments, a middleware software is used, which supports the publish/subscribe communication pattern. Using this communication pattern, a publisher sends information encapsulated in messages to the middleware. A subscriber registers its interests at the middleware. The monograph describes three different steps to determine the performance of such a system. In a first step, the message throughput performance of a publish/subscribe in different scenarios is measured using a Java Message Service (JMS) based implementation. In the second step the maximum achievable message throughput is described by adapted models depending on the filter complexity and the replication grade. Using the model, the performance characteristics of a specific system in a given scenario can be determined. These numbers are used for the queuing model described in the third part of the thesis, which supports the dimensioning of a system in realistic scenarios. Additionally, we introduce a method to approximate an M/G/1 system numerically in an efficient way, which can be used for real time analysis to predict the expected performance in a certain scenario. Finally, the analytical model is used to investigate different possibilities to ensure the scalability of the maximum achievable message throughput of the overall system.
This study provides a systematic literature review of research (2001–2020) in the field of teaching and learning a foreign language and intercultural learning using immersive technologies. Based on 2507 sources, 54 articles were selected according to a predefined selection criteria. The review is aimed at providing information about which immersive interventions are being used for foreign language learning and teaching and where potential research gaps exist. The papers were analyzed and coded according to the following categories: (1) investigation form and education level, (2) degree of immersion, and technology used, (3) predictors, and (4) criterions. The review identified key research findings relating the use of immersive technologies for learning and teaching a foreign language and intercultural learning at cognitive, affective, and conative levels. The findings revealed research gaps in the area of teachers as a target group, and virtual reality (VR) as a fully immersive intervention form. Furthermore, the studies reviewed rarely examined behavior, and implicit measurements related to inter- and trans-cultural learning and teaching. Inter- and transcultural learning and teaching especially is an underrepresented investigation subject. Finally, concrete suggestions for future research are given. The systematic review contributes to the challenge of interdisciplinary cooperation between pedagogy, foreign language didactics, and Human-Computer Interaction to achieve innovative teaching-learning formats and a successful digital transformation.
Visual stimuli are frequently used to improve memory, language learning or perception, and understanding of metacognitive processes. However, in virtual reality (VR), there are few systematically and empirically derived databases. This paper proposes the first collection of virtual objects based on empirical evaluation for inter-and transcultural encounters between English- and German-speaking learners. We used explicit and implicit measurement methods to identify cultural associations and the degree of stereotypical perception for each virtual stimuli (n = 293) through two online studies, including native German and English-speaking participants. The analysis resulted in a final well-describable database of 128 objects (called InteractionSuitcase). In future applications, the objects can be used as a great interaction or conversation asset and behavioral measurement tool in social VR applications, especially in the field of foreign language education. For example, encounters can use the objects to describe their culture, or teachers can intuitively assess stereotyped attitudes of the encounters.
Wireless communication is nothing new. The first data transmissions based on electromagnetic waves have been successfully performed at the end of the 19th century. However, it took almost another century until the technology was ripe for mass market. The first mobile communication systems based on the transmission of digital data were introduced in the late 1980s. Within just a couple of years they have caused a revolution in the way people communicate. The number of cellular phones started to outnumber the fixed telephone lines in many countries and is still rising. New technologies in 3G systems, such as UMTS, allow higher data rates and support various kinds of multimedia services. Nevertheless, the end of the road in wireless communication is far from being reached. In the near future, the Internet and cellular phone systems are expected to be integrated to a new form of wireless system. Bandwidth requirements for a rich set of wireless services, e.g.\ video telephony, video streaming, online gaming, will be easily met. The transmission of voice data will just be another IP based service. On the other hand, building such a system is by far not an easy task. The problems in the development of the UMTS system showed the high complexity of wireless systems with support for bandwidth-hungry, IP-based services. But the technological challenges are just one difficulty. Telecommunication systems are planned on a world-wide basis, such that standard bodies, governments, institutions, hardware vendors, and service providers have to find agreements and compromises on a number of different topics. In this work, we provide the reader with a discussion of many of the topics involved in the planning of a Wireless LAN system that is capable of being integrated into the 4th generation mobile networks (4G) that is being discussed nowadays. Therefore, it has to be able to cope with interactive voice and video traffic while still offering high data rates for best effort traffic. Let us assume a scenario where a huge office complex is completely covered with Wireless LAN access points. Different antenna systems are applied in order to reduce the number of access points that are needed on the one hand, while optimizing the coverage on the other. No additional infrastructure is implemented. Our goal is to evaluate whether the Wireless LAN technology is capable of dealing with the various demands of such a scenario. First, each single access point has to be capable of supporting best-effort and Quality of Service (QoS) demanding applications simultaneously. The IT infrastructure in our scenario consists solely of Wireless LAN, such that it has to allow users surfing the Web, while others are involved in voice calls or video conferences. Then, there is the problem of overlapping cells. Users attached to one access point produce interference for others. However, the QoS support has to be maintained, which is not an easy task. Finally, there are nomadic users, which roam from one Wireless LAN cell to another even during a voice call. There are mechanisms in the standard that allow for mobility, but their capabilities for QoS support are yet to be studied. This shows the large number of unresolved issues when it comes to Wireless LAN in the context of 4G networks. In this work we want to tackle some of the problems.
Web caches often use a Time-to-live (TTL) limit to validate data consistency with web servers. We study the impact of TTL constraints on the hit ratio of basic strategies in caches of fixed size. We derive analytical results and confirm their accuracy in comparison to simulations. We propose a score-based caching method with awareness of the current TTL per data for improving the hit ratio close to the upper bound.
At the center of the Internet’s protocol stack stands the Internet Protocol (IP) as a common denominator that enables all communication. To make routing efficient, resilient, and scalable, several aspects must be considered. Care must be taken that traffic is well balanced to make efficient use of the existing network resources, both in failure free operation and in failure scenarios.
Finding the optimal routing in a network is an NP-complete problem. Therefore, routing optimization is usually performed using heuristics. This dissertation shows that a routing optimized with one objective function is often not good when looking at other objective functions. It can even be worse than unoptimized routing with respect to that objective function. After looking at failure-free routing and traffic distribution in different failure scenarios, the analysis is extended to include the loop-free alternate (LFA) IP fast reroute mechanism. Different application scenarios of LFAs are examined and a special focus is set on the fact that LFAs usually cannot protect all traffic in a network even against single link failures. Thus, the routing optimization for LFAs is targeted on both link utilization and failure coverage. Finally, the pre-congestion notification mechanism PCN for network admission control and overload protection is analyzed and optimized. Different design options for implementing the protocol are compared, before algorithms are developed for the calculation and optimization of protocol parameters and PCN-based routing.
The second part of the thesis tackles a routing problem that can only be resolved on a global scale. The scalability of the Internet is at risk since a major and intensifying growth of the interdomain routing tables has been observed. Several protocols and architectures are analyzed that can be used to make interdomain routing more scalable. The most promising approach is the locator/identifier (Loc/ID) split architecture which separates routing from host identification. This way, changes in connectivity, mobility of end hosts, or traffic-engineering activities are hidden from the routing in the core of the Internet and the routing tables can be kept much smaller. All of the currently proposed Loc/ID split approaches have their downsides. In particular, the fact that most architectures use the ID for routing outside the Internet’s core is a poor design, which inhibits many of the possible features of a new routing architecture. To better understand the problems and to provide a solution for a scalable routing design that implements a true Loc/ID split, the new GLI-Split protocol is developed in this thesis, which provides separation of global and local routing and uses an ID that is independent from any routing decisions.
Besides GLI-Split, several other new routing architectures implementing Loc/ID split have been proposed for the Internet. Most of them assume that a mapping system is queried for EID-to-RLOC mappings by an intermediate node at the border of an edge network. When the mapping system is queried by an intermediate node, packets are already on their way towards their destination, and therefore, the mapping system must be fast, scalable, secure, resilient, and should be able to relay packets without locators to nodes that can forward them to the correct destination. The dissertation develops a classification for all proposed mapping system architectures and shows their similarities and differences. Finally, the fast two-level mapping system FIRMS is developed. It includes security and resilience features as well as a relay service for initial packets of a flow when intermediate nodes encounter a cache miss for the EID-to-RLOC mapping.
Measurements of physiological parameters provide an objective, often non-intrusive, and (at least semi-)automatic evaluation and utilization of user behavior. In addition, specific hardware devices of Virtual Reality (VR) often ship with built-in sensors, i.e. eye-tracking and movements sensors. Hence, the combination of physiological measurements and VR applications seems promising. Several approaches have investigated the applicability and benefits of this combination for various fields of applications. However, the range of possible application fields, coupled with potentially useful and beneficial physiological parameters, types of sensor, target variables and factors, and analysis approaches and techniques is manifold. This article provides a systematic overview and an extensive state-of-the-art review of the usage of physiological measurements in VR. We identified 1,119 works that make use of physiological measurements in VR. Within these, we identified 32 approaches that focus on the classification of characteristics of experience, common in VR applications. The first part of this review categorizes the 1,119 works by field of application, i.e. therapy, training, entertainment, and communication and interaction, as well as by the specific target factors and variables measured by the physiological parameters. An additional category summarizes general VR approaches applicable to all specific fields of application since they target typical VR qualities. In the second part of this review, we analyze the target factors and variables regarding the respective methods used for an automatic analysis and, potentially, classification. For example, we highlight which measurement setups have been proven to be sensitive enough to distinguish different levels of arousal, valence, anxiety, stress, or cognitive workload in the virtual realm. This work may prove useful for all researchers wanting to use physiological data in VR and who want to have a good overview of prior approaches taken, their benefits and potential drawbacks.
After the recent emergence of SARS-CoV-2 infection, unanswered questions remain related to its evolutionary history, path of transmission or divergence and role of recombination. There is emerging evidence on amino acid substitutions occurring in key residues of the receptor-binding domain of the spike glycoprotein in coronavirus isolates from bat and pangolins. In this article, we summarize our current knowledge on the origin of SARS-CoV-2. We also analyze the host ACE2-interacting residues of the receptor-binding domain of spike glycoprotein in SARS-CoV-2 isolates from bats, and compare it to pangolin SARS-CoV-2 isolates collected from Guangdong province (GD Pangolin-CoV) and Guangxi autonomous regions (GX Pangolin-CoV) of South China. Based on our comparative analysis, we support the view that the Guangdong Pangolins are the intermediate hosts that adapted the SARS-CoV-2 and represented a significant evolutionary link in the path of transmission of SARS-CoV-2 virus. We also discuss the role of intermediate hosts in the origin of Omicron.
In network research, reproducibility of experiments is not always easy to achieve. Infrastructures are cumbersome to set up or are not available due to vendor-specific devices. Emulators try to overcome those issues to a given extent and are available in different service models. Unfortunately, the usability of emulators requires time-consuming efforts and a deep understanding of their functionality. At first, we analyze to which extent currently available open-source emulators support network configurations and how user-friendly they are. With these insights, we describe, how an ease-to-use emulator is implemented and may run as a Network Emulator as a Service (NEaaS). Therefore, virtualization plays a major role in order to deploy a NEaaS based on Kathará.
Packets sent over a network can either get lost or reach their destination. Protocols like TCP try to solve this problem by resending the lost packets. However, retransmissions consume a lot of time and are cumbersome for the transmission of critical data. Multipath solutions are quite common to address this reliability issue and are available on almost every layer of the ISO/OSI model. We propose a solution based on a P4 network to duplicate packets in order to send them to their destination via multiple routes. The last network hop ensures that only a single copy of the traffic is further forwarded to its destination by adopting a concept similar to Bloom filters. Besides, if fast delivery is requested we provide a P4 prototype, which randomly forwards the packets over different transmission paths. For reproducibility, we implement our approach in a container-based network emulation system called Kathará.
Failure prediction is an important aspect of self-aware computing systems. Therefore, a multitude of different approaches has been proposed in the literature over the past few years. In this work, we propose a taxonomy for organizing works focusing on the prediction of Service Level Objective (SLO) failures. Our taxonomy classifies related work along the dimensions of the prediction target (e.g., anomaly detection, performance prediction, or failure prediction), the time horizon (e.g., detection or prediction, online or offline application), and the applied modeling type (e.g., time series forecasting, machine learning, or queueing theory). The classification is derived based on a systematic mapping of relevant papers in the area. Additionally, we give an overview of different techniques in each sub-group and address remaining challenges in order to guide future research.
Understanding the Performance of Different Packet Reception and Timestamping Methods in Linux
(2023)
This document briefly presents some renowned packet reception techniques for network packets in Linux systems. Further, it compares their performance when measuring packet timestamps with respect to throughput and accuracy. Both software and hardware timestamps are compared, and various parameters are examined, including frame size, link speed, network interface card, and CPU load. The results indicate that hardware timestamping offers significantly better accuracy with no downsides, and that packet reception techniques that avoid system calls offer superior measurement throughput.
This document presents a networking latency measurement setup that focuses on affordability and universal applicability, and can provide sub-microsecond accuracy. It explains the prerequisites, hardware choices, and considerations to respect during measurement. In addition, it discusses the necessity for exhaustive latency measurements when dealing with high availability and low latency requirements. Preliminary results show that the accuracy is within ±0.02 μs when used with the Intel I350-T2 network adapter.
Knowledge about ransomware is important for protecting sensitive data and for participating in public debates about suitable regulation regarding its security. However, as of now, this topic has received little to no attention in most school curricula. As such, it is desirable to analyze what citizens can learn about this topic outside of formal education, e.g., from news articles. This analysis is both relevant to analyzing the public discourse about ransomware, as well as to identify what aspects of this topic should be included in the limited time available for this topic in formal education. Thus, this paper was motivated both by educational and media research. The central goal is to explore how the media reports on this topic and, additionally, to identify potential misconceptions that could stem from this reporting. To do so, we conducted an exploratory case study into the reporting of 109 media articles regarding a high-impact ransomware event: the shutdown of the Colonial Pipeline (located in the east of the USA). We analyzed how the articles introduced central terminology, what details were provided, what details were not, and what (mis-)conceptions readers might receive from them. Our results show that an introduction of the terminology and technical concepts of security is insufficient for a complete understanding of the incident. Most importantly, the articles may lead to four misconceptions about ransomware that are likely to lead to misleading conclusions about the responsibility for the incident and possible political and technical options to prevent such attacks in the future.
In this paper, we present a virtual audience simulation system for Virtual Reality (VR). The system implements an audience perception model controlling the nonverbal behaviors of virtual spectators, such as facial expressions or postures. Groups of virtual spectators are animated by a set of nonverbal behavior rules representing a particular audience attitude (e.g., indifferent or enthusiastic). Each rule specifies a nonverbal behavior category: posture, head movement, facial expression and gaze direction as well as three parameters: type, frequency and proportion. In a first user-study, we asked participants to pretend to be a speaker in VR and then create sets of nonverbal behaviour parameters to simulate different attitudes. Participants manipulated the nonverbal behaviours of single virtual spectator to match a specific levels of engagement and opinion toward them. In a second user-study, we used these parameters to design different types of virtual audiences with our nonverbal behavior rules and evaluated their perceptions. Our results demonstrate our system’s ability to create virtual audiences with three types of different perceived attitudes: indifferent, critical, enthusiastic. The analysis of the results also lead to a set of recommendations and guidelines regarding attitudes and expressions for future design of audiences for VR therapy and training applications.
This article presents a novel method for controlling a virtual audience system (VAS) in Virtual Reality (VR) application, called STAGE, which has been originally designed for supervised public speaking training in university seminars dedicated to the preparation and delivery of scientific talks. We are interested in creating pedagogical narratives: narratives encompass affective phenomenon and rather than organizing events changing the course of a training scenario, pedagogical plans using our system focus on organizing the affects it arouses for the trainees. Efficiently controlling a virtual audience towards a specific training objective while evaluating the speaker’s performance presents a challenge for a seminar instructor: the high level of cognitive and physical demands required to be able to control the virtual audience, whilst evaluating speaker’s performance, adjusting and allowing it to quickly react to the user’s behaviors and interactions. It is indeed a critical limitation of a number of existing systems that they rely on a Wizard of Oz approach, where the tutor drives the audience in reaction to the user’s performance. We address this problem by integrating with a VAS a high-level control component for tutors, which allows using predefined audience behavior rules, defining custom ones, as well as intervening during run-time for finer control of the unfolding of the pedagogical plan. At its core, this component offers a tool to program, select, modify and monitor interactive training narratives using a high-level representation. The STAGE offers the following features: i) a high-level API to program pedagogical narratives focusing on a specific public speaking situation and training objectives, ii) an interactive visualization interface iii) computation and visualization of user metrics, iv) a semi-autonomous virtual audience composed of virtual spectators with automatic reactions to the speaker and surrounding spectators while following the pedagogical plan V) and the possibility for the instructor to embody a virtual spectator to ask questions or guide the speaker from within the Virtual Environment. We present here the design, and implementation of the tutoring system and its integration in STAGE, and discuss its reception by end-users.
Starfree regular languages can be build up from alphabet letters by using only Boolean operations and concatenation. The complexity of these languages can be measured with the so-called dot-depth. This measure leads to concatenation hierarchies like the dot-depth hierarchy (DDH) and the closely related Straubing-Thérien hierarchy (STH). The question whether the single levels of these hierarchies are decidable is still open and is known as the dot-depth problem. In this thesis we prove/reprove the decidability of some lower levels of both hierarchies. More precisely, we characterize these levels in terms of patterns in finite automata (subgraphs in the transition graph) that are not allowed. Therefore, such characterizations are called forbidden-pattern characterizations. The main results of the thesis are as follows: forbidden-pattern characterization for level 3/2 of the DDH (this implies the decidability of this level) decidability of the Boolean hierarchy over level 1/2 of the DDH definition of decidable hierarchies having close relations to the DDH and STH Moreover, we prove/reprove the decidability of the levels 1/2 and 3/2 of both hierarchies in terms of forbidden-pattern characterizations. We show the decidability of the Boolean hierarchies over level 1/2 of the DDH and over level 1/2 of the STH. A technique which uses word extensions plays the central role in the proofs of these results. With this technique it is possible to treat the levels 1/2 and 3/2 of both hierarchies in a uniform way. Furthermore, it can be used to prove the decidability of the mentioned Boolean hierarchies. Among other things we provide a combinatorial tool that allows to partition words of arbitrary length into factors of bounded length such that every second factor u leads to a loop with label u in a given finite automaton.
In this doctoral thesis we cover the performance evaluation of next generation data plane architectures, comprised of complex software as well as programmable hardware components that allow fine granular configuration. In the scope of the thesis we propose mechanisms to monitor the performance of singular components and model key performance indicators of software based packet processing solutions. We present novel approaches towards network abstraction that allow the integration of heterogeneous data plane technologies into a singular network while maintaining total transparency between control and data plane. Finally, we investigate a full, complex system consisting of multiple software-based solutions and perform a detailed performance analysis. We employ simulative approaches to investigate overload control mechanisms that allow efficient operation under adversary conditions. The contributions of this work build the foundation for future research in the areas of network softwarization and network function virtualization.
Die Erkennung handschriftlicher Artefakte wie Unterstreichungen in Buchdrucken ermöglicht Rückschlüsse auf das Rezeptionsverhalten und die Provenienzgeschichte und wird auch für eine OCR benötigt. Dabei soll zwischen handschriftlichen Unterstreichungen und waagerechten Linien im Druck (z. B. Trennlinien usw.) unterschieden werden, da letztere nicht ausgezeichnet werden sollen. Im Beitrag wird ein Ansatz basierend auf einem auf Unterstreichungen trainierten Neuronalen Netz gemäß der U-Net Architektur vorgestellt, dessen Ergebnisse in einem zweiten Schritt mit heuristischen Regeln nachbearbeitet werden. Die Evaluationen zeigen, dass Unterstreichungen sehr gut erkannt werden, wenn bei der Binarisierung der Scans nicht zu viele Pixel der Unterstreichung wegen geringem Kontrast verloren gehen. Zukünftig sollen die Worte oberhalb der Unterstreichung mit OCR transkribiert werden und auch andere Artefakte wie handschriftliche Notizen in alten Drucken erkannt werden.
In scientific research, the independent reproduction of experiments is the source of trust. Detailed documentation is required to enable experiment reproduction. Reproducibility awards were created to honor the increased documentation effort. In this work, we propose a novel approach toward reproducible research—a structured experimental workflow that allows the creation of reproducible experiments without requiring additional efforts of the researcher. Moreover, we present our own testbed and toolchain, namely, plain orchestrating service (pos), which enables the creation of such experimental workflows. The experiment is documented by our proposed, fully scripted experiment structure. In addition, pos provides scripts enabling the automation of the bundling and release of all experimental artifacts. We provide an interactive environment where pos experiments can be executed and reproduced, available at https://gallenmu.github.io/single-server-experiment.
The present paper compares the effect of different waypoint parameters on the flight performance of a special autonomous indoor UAV (unmanned aerial vehicle) fusing ultrasonic, inertial, pressure and optical sensors for 3D positioning and controlling. The investigated parameters are the acceptance threshold for reaching a waypoint as well as the maximal waypoint step size or block size. The effect of these parameters on the flight time and accuracy of the flight path is investigated. Therefore the paper addresses how the acceptance threshold and step size influence the speed and accuracy of the autonomous flight and thus influence the performance of the presented autonomous quadrocopter under real indoor navigation circumstances.
Furthermore the paper demonstrates a drawback of the standard potential field method for navigation of such autonomous quadrocopters and points to an improvement.
A procedure to control all six DOF (degrees of freedom) of a UAV (unmanned aerial vehicle) without an external reference system and to enable fully autonomous flight is presented here. For 2D positioning the principle of optical flow is used. Together with the output of height estimation, fusing ultrasonic, infrared and inertial and pressure sensor data, the 3D position of the UAV can be computed, controlled and steered. All data processing is done on the UAV. An external computer with a pathway planning interface is for commanding purposes only. The presented system is part of the AQopterI8 project, which aims to develop an autonomous flying quadrocopter for indoor application. The focus of this paper is 2D positioning using an optical flow sensor. As a result of the performed evaluation, it can be concluded that for position hold, the standard deviation of the position error is 10cm and after landing the position error is about 30cm.
This paper presents a novel concept to extend state-of-the-art buffer monitoring with additional measures to estimate service-curves. The online algorithm for service-curve estimation replaces the state-of-the-art timestamp logging, as we expect it to overcome the main disadvantages of generating a huge amount of data and using a lot of CPU resources to store the data to a file during operation. We prove the accuracy of the online-algorithm offline with timestamp data and compare the derived bounds to the measured delay and backlog. We also do a proof-of- concept of the online-algorithm, implement it in LabVIEW and compare its performance to the timestamp logging by CPU load and data-size of the log-file. However, the implementation is still work-in-progress.
How to Model and Predict the Scalability of a Hardware-In-The-Loop Test Bench for Data Re-Injection?
(2023)
This paper describes a novel application of an empirical network calculus model based on measurements of a hardware-in-the-loop (HIL) test system. The aim is to predict the performance of a HIL test bench for open-loop re-injection in the context of scalability. HIL test benches are distributed computer systems including software, hardware, and networking devices. They are used to validate complex technical systems, but have not yet been system under study themselves. Our approach is to use measurements from the HIL system to create an empirical model for arrival and service curves. We predict the performance and design the previously unknown parameters of the HIL simulator with network calculus (NC), namely the buffer sizes and the minimum needed pre-buffer time for the playback buffer. We furthermore show, that it is possible to estimate the CPU load from arrival and service-curves based on the utilization theorem, and hence estimate the scalability of the HIL system in the context of the number of sensor streams.
Knowledge-based systems (KBS) face an ever-increasing interest in various disciplines and contexts. Yet, the former aim to construct the ’perfect intelligent software’ continuously shifts to user-centered, participative solutions. Such systems enable users to contribute their personal knowledge to the problem solving process for increased efficiency and an ameliorated user experience. More precisely, we define non-functional key requirements of participative KBS as: Transparency (encompassing KBS status mediation), configurability (user adaptability, degree of user control/exploration), quality of the KB and UI, and evolvability (enabling the KBS to grow mature with their users). Many of those requirements depend on the respective target users, thus calling for a more user-centered development. Often, also highly expertise domains are targeted — inducing highly complex KBs — which requires a more careful and considerate UI/interaction design. Still, current KBS engineering (KBSE) approaches mostly focus on knowledge acquisition (KA) This often leads to non-optimal, little reusable, and non/little evaluated KBS front-end solutions.
In this thesis we propose a more encompassing KBSE approach. Due to the strong mutual influences between KB and UI, we suggest a novel form of intertwined UI and KB development. We base the approach on three core components for encompassing KBSE:
(1) Extensible prototyping, a tailored form of evolutionary prototyping; this builds on mature UI prototypes and offers two extension steps for the anytime creation of core KBS prototypes (KB + core UI) and fully productive KBS (core KBS prototype + common framing functionality). (2) KBS UI patterns, that define reusable solutions for the core KBS UI/interaction; we provide a basic collection of such patterns in this work. (3) Suitable usability instruments for the assessment of the KBS artifacts. Therewith, we do not strive for ’yet another’ self-contained KBS engineering methodology. Rather, we motivate to extend existing approaches by the proposed key components. We demonstrate this based on an agile KBSE model.
For practical support, we introduce the tailored KBSE tool ProKEt. ProKEt offers a basic selection of KBS core UI patterns and corresponding configuration options out of the box; their further adaption/extension is possible on various levels of expertise. For practical usability support, ProKEt offers facilities for quantitative and qualitative data collection. ProKEt explicitly fosters the suggested, intertwined development of UI and KB. For seamlessly integrating KA activities, it provides extension points for two selected external KA tools: For KnowOF, a standard office based KA environment. And for KnowWE, a semantic wiki for collaborative KA. Therewith, ProKEt offers powerful support for encompassing, user-centered KBSE.
Finally, based on the approach and the tool, we also developed a novel KBS type: Clarification KBS as a mashup of consultation and justification KBS modules. Those denote a specifically suitable realization for participative KBS in highly expertise contexts and consequently require a specific design. In this thesis, apart from more common UI solutions, we particularly also introduce KBS UI patterns especially tailored towards Clarification KBS.
Given points in the plane, connect them using minimum ink. Though the task seems simple, it turns out to be very time consuming. In fact, scientists believe that computers cannot efficiently solve it. So, do we have to resign? This book examines such NP-hard network-design problems, from connectivity problems in graphs to polygonal drawing problems on the plane. First, we observe why it is so hard to optimally solve these problems. Then, we go over to attack them anyway. We develop fast algorithms that find approximate solutions that are very close to the optimal ones. Hence, connecting points with slightly more ink is not hard.
The three-dimensional cuneiform script is one of the oldest known writing systems and a central object of research in Ancient Near Eastern Studies and Hittitology. An important step towards the understanding of the cuneiform script is the provision of opportunities and tools for joint analysis. This paper presents an approach that contributes to this challenge: a collaborative compatible web-based scientific exploration and analysis of 3D scanned cuneiform fragments. The WebGL -based concept incorporates methods for compressed web-based content delivery of large 3D datasets and high quality visualization. To maximize accessibility and to promote acceptance of 3D techniques in the field of Hittitology, the introduced concept is integrated into the Hethitologie-Portal Mainz, an established leading online research resource in the field of Hittitology, which until now exclusively included 2D content. The paper shows that increasing the availability of 3D scanned archaeological data through a web-based interface can provide significant scientific value while at the same time finding a trade-off between copyright induced restrictions and scientific usability.
Digitization and transcription of historic documents offer new research opportunities for humanists and are the topics of many edition projects. However, manual work is still required for the main phases of layout recognition and the subsequent optical character recognition (OCR) of early printed documents. This paper describes and evaluates how deep learning approaches recognize text lines and can be extended to layout recognition using background knowledge. The evaluation was performed on five corpora of early prints from the 15th and 16th Centuries, representing a variety of layout features. While the main text with standard layouts could be recognized in the correct reading order with a precision and recall of up to 99.9%, also complex layouts were recognized at a rate as high as 90% by using background knowledge, the full potential of which was revealed if many pages of the same source were transcribed.
In many cases, problems, data, or information can be modeled as graphs. Graphs can be used as a tool for modeling in any case where connections between distinguishable objects occur. Any graph consists of a set of objects, called vertices, and a set of connections, called edges, such that any edge connects a pair of vertices. For example, a social network can be modeled by a graph by
transforming the users of the network into vertices and friendship relations between users into edges. Also physical networks like computer networks or transportation networks, for example, the metro network of a city, can be seen as graphs.
For making graphs and, thereby, the data that is modeled, well-understandable for users, we need a visualization. Graph drawing deals with algorithms for visualizing graphs. In this thesis, especially the use of crossings and curves is investigated for graph drawing problems under additional constraints. The constraints that occur in the problems investigated in this thesis especially restrict the positions of (a part of) the vertices; this is done either as a hard constraint or as an optimization criterion.
No abstract available
In der vorliegenden Arbeit wird das Problem der Kalibrierung Agenten-basierter Simulationen (ABS) behandelt, also das Problem, die Parameterwerte eines Agenten-basierten Simulationsmodells so einzustellen, dass valides Simulationsverhalten erreicht wird. Das Kalibrierungsproblem für Simulationen an sich ist nicht neu und ist im Rahmen klassischer Simulationsparadigmen, wie z.B. der Makro-Simulation, fester Bestandteil der Forschung. Im Vergleich zu den dort betrachteten Kalibrierungsproblemen zeichnet sich das Kalibrierungsproblem für ABS jedoch durch eine Reihe zusätzlicher Herausforderungen aus, welche die direkte Anwendung existierender Kalibrierungsverfahren in begrenzter Zeit erschweren, bzw. nicht mehr sinnvoll zulassen. Die Lösung dieser Probleme steht im Zentrum dieser Dissertation: Das Ziel besteht darin, den Nutzer bei der Kalibrierung von ABS auf der Basis von unzureichenden, potentiell fehlerhaften Daten und Wissen zu unterstützen. Dabei sollen drei Hauptprobleme gelöst werden: 1)Vereinfachung der Kalibrierung großer Agenten-Parametermengen auf der Mikro- Ebene in Agenten-basierten Simulationen durch Ausnutzung der spezifischen Struktur von ABS (nämlich dem Aufbau aus einer Menge von Agentenmodellen). 2)Kalibrierung Agenten-basierter Simulationen, so dass auf allen relevanten Beobachtungsebenen valides Simulationsverhalten erzeugt wird (mindestens Mikro und Makro-Ebene). Als erschwerende Randbedingung muss die Kalibrierung unter der Voraussetzung einer Makro-Mikro-Wissenslücke durchgeführt werden. 3)Kalibrierung Agenten-basierter Simulationen auf der Mikro-Ebene unter der Voraussetzung, dass zur Kalibrierung einzelner Agentenmodelle nicht ausreichend und potentiell verfälschte Daten zur Verhaltensvalidierung zur Verfügung stehen. Hierzu wird in dieser Arbeit das sogenannte Makro-Mikro-Verfahren zur Kalibrierung von Agenten-basierten Simulationen entwickelt. Das Verfahren besteht aus einem Basisverfahren, das im Verlauf der Arbeit um verschiedene Zusatzverfahren erweitert wird. Das Makro-Mikro-Verfahren und seine Erweiterungen sollen dazu dienen, die Modellkalibrierung trotz stark verrauschter Daten und eingeschränktem Wissen über die Wirkungszusammenhänge im Originalsystem geeignet zu ermöglichen und dabei den Kalibrierungsprozess zu beschleunigen: 1) Makro-Mikro-Kalibrierungsverfahren: Das in dieser Arbeit entwickelte Makro- Mikro-Verfahren unterstützt den Nutzer durch eine kombinierte Kalibrierung auf der Mikro- und der Makro-Beobachtungsebene, die gegebenenfalls durch Zwischenebenen erweitert werden kann. Der Grundgedanke des Verfahrens besteht darin, das Kalibrierungsproblem in eines auf aggregierter Verhaltensebene und eines auf der Ebene des Mikro-Agentenverhaltens aufzuteilen. Auf der Makro-Ebene wird nach validen idealen aggregierten Verhaltensmodellen (IVM) der Agenten gesucht. Auf der Mikro-Ebene wird versucht die individuellen Modelle der Agenten auf Basis des erwünschten Gesamtverhaltens und der ermittelten IVM so zu kalibrieren, das insgesamt Simulationsverhalten entsteht, das sowohl auf Mikro- als auch auf Makro-Ebene valide ist. 2) Erweiterung 1: Robuste Kalibrierung: Um den Umgang mit potentiell verrauschten Validierungskriterien (d.h. mit verrauschten Daten über ein Originalsystem, auf denen die Validierungskriterien der Simulation beruhen) und Modellteilen während der Kalibrierung von ABS zu ermöglichen, wird eine robuste Kalibrierungstechnik zur Anwendung im Makro-Mikro-Verfahren entwickelt. 3) Erweiterung 2: Kalibrierung mit Heterogenitätssuche: Als zweite Erweiterung des Makro-Mikro-Verfahrens wird ein Verfahren entwickelt, das das Problem des unklaren Detaillierungsgrades von ABS auf der Ebene der Parameterwerte adressiert. Prinzipiell kann zwar jeder Agent unterschiedliche Parameterwerte verwenden, obwohl eine geringere Heterogenität zur Erzeugung validen Verhaltens ausreichend wäre. Die entwickelte Erweiterung versucht, während der Kalibrierung, eine geeignete Heterogenitätsausprägung für die Parameterwerte der Agenten zu ermitteln. Unter einer Heterogenitätsausprägung wird dabei eine Einteilung der simulierten Agenten in Gruppen mit jeweils gleichen Parameterwerten verstanden. Die Heterogenitätssuche dient dazu, einen Kompromiss zu finden zwischen der Notwendigkeit, sehr große Parametersuchräume durchsuchen zu müssen und gleichzeitig den Suchraum so klein wie möglich halten zu wollen.
Though several previous studies reported the in vitro and in vivo antioxidant effect of kinetin (Kn), details on its action in cisplatin-induced toxicity are still scarce. In this study we evaluated, for the first time, the effects of kinetin in cisplatin (cp)- induced liver and lymphocyte toxicity in rats. Wistar male albino rats were divided into nine groups: (i) the control (C), (ii) groups 2,3 and 4, which received 0.25, 0.5 and 1 mg/kg kinetin for 10 days; (iii) the cisplatin (cp) group, which received a single intraperitoneal injection of CP (7.0 mg/kg); and (iv) groups 6, 7, 8 and 9, which received, for 10 days, 0.25, 0.5 and 1 mg/kg kinetin or 200 mg/kg vitamin C, respectively, and Cp on the fourth day. CP-injected rats showed a significant impairment in biochemical, oxidative stress and inflammatory parameters in hepatic tissue and lymphocytes. PCR showed a profound increase in caspase-3, and a significant decline in AKT gene expression. Intriguingly, Kn treatment restored the biochemical, redox status and inflammatory parameters. Hepatic AKT and caspase-3 expression as well as CD95 levels in lymphocytes were also restored. In conclusion, Kn mitigated oxidative imbalance, inflammation and apoptosis in CP-induced liver and lymphocyte toxicity; therefore, it can be considered as a promising therapy.
Natural walking in virtual reality games is constrained by the physical boundaries defined by the size of the player’s tracking space. Impossible spaces, a redirected walking technique, enlarge the virtual environment by creating overlapping architecture and letting multiple locations occupy the same physical space. Within certain thresholds, this is subtle to the player. In this paper, we present our approach to implement such impossible spaces and describe how we handled challenges like objects with simulated physics or precomputed global illumination.
Time-to-Live (TTL) caches decouple the occupancy of objects in cache through object-specific validity timers. Stateof- the art techniques provide exact methods for the calculation of object-specific hit probabilities given entire cache hierarchies with random inter-cache network delays. The system hit probability is a provider-centric metric as it relates to the origin offload, i.e., the decrease in the number of requests that are served by the content origin server. In this paper we consider a user-centric metric, i.e., the response time, which is shown to be structurally different from the system hit probability. Equipped with the state-of-theart exact modeling technique using Markov-arrival processes we derive expressions for the expected object response time and pave a way for its optimization under network delays.
In the last years, visual methods have been introduced in industrial software production and teaching of software engineering. In particular, the international standardization of a graphical software engineering language, the Unified Modeling Language (UML) was a reason for this tendency. Unfortunately, various problems exist in concrete realizations of tools, e.g. due to a missing compliance to the standard. One problem is the automatic layout, which is required for a consistent automatic software design. The thesis derives reasons and criteria for an automatic layout method, which produces drawings of UML class diagrams according to the UML specification and issues of human computer interaction, e.g. readability. A unique set of aesthetic criteria is combined from four different disciplines involved in this topic. Based on these aethetic rules, a hierarchical layout algorithm is developed, analyzed, measured by specialized measuring techniques and compared to related work. Then, the realization of the algorithm as a Java framework is given as an architectural description. Finally, adaptions to anticipated future changes of the UML, improvements of the framework and example drawings of the implementation are given.
Mindfulness is considered an important factor of an individual's subjective well-being. Consequently, Human-Computer Interaction (HCI) has investigated approaches that strengthen mindfulness, i.e., by inventing multimedia technologies to support mindfulness meditation. These approaches often use smartphones, tablets, or consumer-grade desktop systems to allow everyday usage in users' private lives or in the scope of organized therapies. Virtual, Augmented, and Mixed Reality (VR, AR, MR; in short: XR) significantly extend the design space for such approaches. XR covers a wide range of potential sensory stimulation, perceptive and cognitive manipulations, content presentation, interaction, and agency. These facilities are linked to typical XR-specific perceptions that are conceptually closely related to mindfulness research, such as (virtual) presence and (virtual) embodiment. However, a successful exploitation of XR that strengthens mindfulness requires a systematic analysis of the potential interrelation and influencing mechanisms between XR technology, its properties, factors, and phenomena and existing models and theories of the construct of mindfulness. This article reports such a systematic analysis of XR-related research from HCI and life sciences to determine the extent to which existing research frameworks on HCI and mindfulness can be applied to XR technologies, the potential of XR technologies to support mindfulness, and open research gaps. Fifty papers of ACM Digital Library and National Institutes of Health's National Library of Medicine (PubMed) with and without empirical efficacy evaluation were included in our analysis. The results reveal that at the current time, empirical research on XR-based mindfulness support mainly focuses on therapy and therapeutic outcomes. Furthermore, most of the currently investigated XR-supported mindfulness interactions are limited to vocally guided meditations within nature-inspired virtual environments. While an analysis of empirical research on those systems did not reveal differences in mindfulness compared to non-mediated mindfulness practices, various design proposals illustrate that XR has the potential to provide interactive and body-based innovations for mindfulness practice. We propose a structured approach for future work to specify and further explore the potential of XR as mindfulness-support. The resulting framework provides design guidelines for XR-based mindfulness support based on the elements and psychological mechanisms of XR interactions.
Service orchestration requires enormous attention and is a struggle nowadays. Of course, virtualization provides a base level of abstraction for services to be deployable on a lot of infrastructures. With container virtualization, the trend to migrate applications to a micro-services level in order to be executable in Fog and Edge Computing environments increases manageability and maintenance efforts rapidly. Similarly, network virtualization adds effort to calibrate IP flows for Software-Defined Networks and eventually route it by means of Network Function Virtualization. Nevertheless, there are concepts like MAPE-K to support micro-service distribution in next-generation cloud and network environments. We want to explore, how a service distribution can be improved by adopting machine learning concepts for infrastructure or service changes. Therefore, we show how federated machine learning is integrated into a cloud-to-fog-continuum without burdening single nodes.
Dynamic point cloud compression based on projections, surface reconstruction and video compression
(2021)
In this paper we will present a new dynamic point cloud compression based on different projection types and bit depth, combined with the surface reconstruction algorithm and video compression for obtained geometry and texture maps. Texture maps have been compressed after creating Voronoi diagrams. Used video compression is specific for geometry (FFV1) and texture (H.265/HEVC). Decompressed point clouds are reconstructed using a Poisson surface reconstruction algorithm. Comparison with the original point clouds was performed using point-to-point and point-to-plane measures. Comprehensive experiments show better performance for some projection maps: cylindrical, Miller and Mercator projections.
To jointly provide different services/technologies, like IP and Ethernet or IP and SDH/SONET, in a single network, equipment of multiple technologies needs to be deployed to the sites/Points of Presence (PoP) and interconnected with each other. Therein, a technology may provide transport functionality to other technologies and increase the number of available resources by using multiplexing techniques. By providing its own switching functionality, each technology creates connections in a logical layer which leads to the notion of multi-layer networks. The design of such networks comprises the deployment and interconnection of components to suit to given traffic demands. To prevent traffic loss due to failures of networking equipment, protection mechanisms need to be established. In multi-layer networks, protection usually can be applied in any of the considered layers. In turn, the hierarchical structure of multi-layer networks also bears shared risk groups (SRG). To achieve a cost-optimal resilient network, an appropriate combination of multiplexing techniques, technologies, and their interconnections needs to be found. Thus, network design is a combinatorial problem with a large parameter and solution space. After the design stage, the resources of a multi-layer network can be provided to traffic demands. Especially, dynamic capacity provisioning requires interaction of sites and layers, as well as accurate retrieval of constraint information. In recent years, generalized multiprotocol label switching (GMPLS) and path computation elements (PCE) have emerged as possible approaches for these challenges. Like the design, the provisioning of multi-layer networks comprises a variety of optimization parameters, like blocking probability, resilience, and energy efficiency. In this work, we introduce several efficient heuristics to approach the considered optimization problems. We perform capital expenditure (CAPEX)-aware design of multi-layer networks from scratch, based on IST NOBEL phase 2 project's cost and equipment data. We comprise traffic and resilience requirements in different and multiple layers as well as different network architectures. On top of the designed networks, we consider the dynamic provisioning of multi-layer traffic based on the GMPLS and PCE architecture. We evaluate different PCE deployments, information retrieval strategies, and re-optimization. Finally, we show how information about provisioning utilization can be used to provide a feedback for network design.
Mapping and localization of mobile robots in an unknown environment are essential for most high-level operations like autonomous navigation or exploration. This paper presents a novel approach for combining estimated trajectories, namely curvefusion. The robot used in the experiments is equipped with a horizontally mounted 2D profiler, a constantly spinning 3D laser scanner and a GPS module. The proposed algorithm first combines trajectories from different sensors to optimize poses of the planar three degrees of freedom (DoF) trajectory, which is then fed into continuous-time simultaneous localization and mapping (SLAM) to further improve the trajectory. While state-of-the-art multi-sensor fusion methods mainly focus on probabilistic methods, our approach instead adopts a deformation-based method to optimize poses. To this end, a similarity metric for curved shapes is introduced into the robotics community to fuse the estimated trajectories. Additionally, a shape-based point correspondence estimation method is applied to the multi-sensor time calibration. Experiments show that the proposed fusion method can achieve relatively better accuracy, even if the error of the trajectory before fusion is large, which demonstrates that our method can still maintain a certain degree of accuracy in an environment where typical pose estimation methods have poor performance. In addition, the proposed time-calibration method also achieves high accuracy in estimating point correspondences.
This work deals with teams in teleoperation scenarios, where one human team partner (supervisor) guides and controls multiple remote entities (either robotic or human) and coordinates their tasks. Such a team needs an appropriate infrastructure for sharing information and commands. The robots need to have a level of autonomy, which matches the assigned task. The humans in the team have to be provided with autonomous support, e.g. for information integration. Design and capabilities of the human-robot interfaces will strongly influence the performance of the team as well as the subjective feeling of the human team partners. Here, it is important to elaborate the information demand as well as how information is presented. Such human-robot systems need to allow the supervisor to gain an understanding of what is going on in the remote environment (situation awareness) by providing the necessary information. This includes achieving fast assessment of the robot´s or remote human´s state. Processing, integration and organization of data as well as suitable autonomous functions support decision making and task allocation and help to decrease the workload in this multi-entity teleoperation task. Interaction between humans and robots is improved by a common world model and a responsive system and robots. The remote human profits from a simplified user interface providing exactly the information needed for the actual task at hand. The topic of this thesis is the investigation of such teleoperation interfaces in human-robot teams, especially for high-risk, time-critical, and dangerous tasks. The aim is to provide a suitable human-robot team structure as well as analyze the demands on the user interfaces. On one side, it will be looked on the theoretical background (model, interactions, and information demand). On the other side, real implementations for system, robots, and user interfaces are presented and evaluated as testbeds for the claimed requirements. Rescue operations, more precisely fire-fighting, was chosen as an exemplary application scenario for this work. The challenges in such scenarios are high (highly dynamic environments, high risk, time criticality etc.) and it can be expected that results can be transferred to other applications, which have less strict requirements. The present work contributes to the introduction of human-robot teams in task-oriented scenarios, such as working in high risk domains, e.g. fire-fighting. It covers the theoretical background of the required system, the analysis of related human factors concepts, as well as discussions on implementation. An emphasis is placed on user interfaces, their design, requirements and user testing, as well as on the used techniques (three-dimensional sensor data representation, mixed reality, and user interface design guidelines). Further, the potential integration of 3D sensor data as well as the visualization on stereo visualization systems is introduced.
The correct behavior of spacecraft components is the foundation of unhindered mission operation. However, no technical system is free of wear and degradation. A malfunction of one single component might significantly alter the behavior of the whole spacecraft and may even lead to a complete mission failure. Therefore, abnormal component behavior must be detected early in order to be able to perform counter measures. A dedicated fault detection system can be employed, as opposed to classical health monitoring, performed by human operators, to decrease the response time to a malfunction. In this paper, we present a generic model-based diagnosis system, which detects faults by analyzing the spacecraft’s housekeeping data. The observed behavior of the spacecraft components, given by the housekeeping data is compared to their expected behavior, obtained through simulation. Each discrepancy between the observed and the expected behavior of a component generates a so-called symptom. Given the symptoms, the diagnoses are derived by computing sets of components whose malfunction might cause the observed discrepancies. We demonstrate the applicability of the diagnosis system by using modified housekeeping data of the qualification model of an actual spacecraft and outline the advantages and drawbacks of our approach.
This paper gives an overview of our recent activities in the field of satellite communication networks, including an introduction to geostationary satellite systems and Low Earth Orbit megaconstellations. To mitigate the high latencies of geostationary satellite networks, TCP-splitting Performance Enhancing Proxies are deployed. However, these cannot be applied in the case of encrypted transport headers as it is the case for VPNs or QUIC. We summarize performance evaluation results from multiple measurement campaigns. In a recently concluded project, multipath communication was used to combine the advantages of very heterogeneous communication paths: low data rate, low latency (e.g., DSL light) and high data rate, high latency (e.g., geostationary satellite).
Immersive virtual environments provide users with the opportunity to escape from the real world, but scripted dialogues can disrupt the presence within the world the user is trying to escape within. Both Non-Playable Character (NPC) to Player and NPC to NPC dialogue can be non-natural and the reliance on responding with pre-defined dialogue does not always meet the players emotional expectations or provide responses appropriate to the given context or world states. This paper investigates the application of Artificial Intelligence (AI) and Natural Language Processing to generate dynamic human-like responses within a themed virtual world. Each thematic has been analysed against humangenerated responses for the same seed and demonstrates invariance of rating across a range of model sizes, but shows an effect of theme and the size of the corpus used for fine-tuning the context for the game world.
The rating of perceived exertion (RPE) is a subjective load marker and may assist in individualizing training prescription, particularly by adjusting running intensity. Unfortunately, RPE has shortcomings (e.g., underreporting) and cannot be monitored continuously and automatically throughout a training sessions. In this pilot study, we aimed to predict two classes of RPE (≤15 “Somewhat hard to hard” on Borg’s 6–20 scale vs. RPE >15 in runners by analyzing data recorded by a commercially-available smartwatch with machine learning algorithms. Twelve trained and untrained runners performed long-continuous runs at a constant self-selected pace to volitional exhaustion. Untrained runners reported their RPE each kilometer, whereas trained runners reported every five kilometers. The kinetics of heart rate, step cadence, and running velocity were recorded continuously ( 1 Hz ) with a commercially-available smartwatch (Polar V800). We trained different machine learning algorithms to estimate the two classes of RPE based on the time series sensor data derived from the smartwatch. Predictions were analyzed in different settings: accuracy overall and per runner type; i.e., accuracy for trained and untrained runners independently. We achieved top accuracies of 84.8 % for the whole dataset, 81.8 % for the trained runners, and 86.1 % for the untrained runners. We predict two classes of RPE with high accuracy using machine learning and smartwatch data. This approach might aid in individualizing training prescriptions.
Die Entwicklung eines wissensbasierten Systems, speziell eines Diagnosesystems, ist eine Teildisziplin der künstlichen Intelligenz und angewandten Informatik. Im Laufe der Forschung auf diesem Gebiet wurden verschiedene Lösungsansätze mit unterschiedlichem Erfolg bei der Anwendung in der Kraftfahrzeugdiagnose entwickelt. Diagnosesysteme in Vertragswerkstätten, das heißt in Fahrzeughersteller gebundenen Werkstätten, wenden hauptsächlich die fallbasierte Diagnostik an. Zum einen hält sich hier die Fahrzeugvielfalt in Grenzen und zum anderen besteht eine Meldepflicht bei neuen, nicht im System vorhandenen Fällen. Die freien Werkstätten verfügen nicht über eine solche Datenbank. Somit ist der fallbasierte Ansatz schwer umsetzbar. In freien Werkstätten - Fahrzeughersteller unabhängigen Werkstätten - basiert die Fehlersuche hauptsächlich auf Fehlerbäumen. Wegen der wachsenden Fahrzeugkomplexität, welche wesentlich durch die stark zunehmende Anzahl der durch mechatronische Systeme realisierten Funktionen bedingt ist, und der steigenden Typenvielfalt ist die geführte Fehlersuche in freien Werkstätten nicht immer zielführend. Um die Unterstützung des Personals von freien Werkstätten bei der zukünftigen Fehlersuche zu gewährleisten, werden neue Generationen von herstellerunabhängigen Diagnosetools benötigt, die die Probleme der Variantenvielfalt und Komplexität lösen. In der vorliegenden Arbeit wird ein Lösungsansatz vorgestellt, der einen qualitativen, modellbasierten Diagnoseansatz mit einem auf heuristischem Diagnosewissen basierenden Ansatz vereint. Neben der Grundlage zur Wissenserhebung werden in dieser Arbeit die theoretische Grundlage zur Beherrschung der Variantenvielfalt sowie die Tests für die erstellten Diagnosemodelle behandelt. Die Diagnose ist symptombasiert und die Inferenzmechanismen zur Verarbeitung des Diagnosewissens sind eine Kombination aus Propagierung der abweichenden physikalischen Größen im Modell und der Auswertung des heuristischen Wissens. Des Weiteren werden in dieser Arbeit verschiedene Aspekte der Realisierung der entwickelten theoretischen Grundlagen dargestellt, zum Beispiel: Systemarchitektur, Wissenserhebungsprozess, Ablauf des Diagnosevorgangs in den Werkstätten. Die Evaluierung der entwickelten Lösung bei der Wissenserhebung in Form von Modellerstellungen und Modellierungsworkshops sowie Feldtests dient nicht nur zur Bestätigung des entwickelten Ansatzes, sondern auch zur Ideenfindung für die Integration der entwickelten Tools in die existierende IT-Infrastruktur.
Cosmology often uses intricate formulas and mathematics to derive new theories and concepts. We do something different in this paper: We look at biological processes and derive from these heuristics so that the revised cosmology agrees with astronomical observations but does also agree with standard biological observations. We show that we then have to replace any type of singularity at the start of the universe by a condensation nucleus and that the very early period of the universe usually assumed to be inflation has to be replaced by a period of rapid crystal growth as in Weiss magnetization domains.
Impressively, these minor modifications agree well with astronomical observations including removing the strong inflation perturbations which were never observed in the recent BICEP2 experiments. Furthermore, looking at biological principles suggests that such a new theory with a condensation nucleus at start and a first rapid phase of magnetization-like growth of the ordered, physical laws obeying lattice we live in is in fact the only convincing theory of the early phases of our universe that also is compatible with current observations.
We show in detail in the following that such a process of crystal creation, breaking of new crystal seeds and ultimate evaporation of the present crystal readily leads over several generations to an evolution and selection of better, more stable and more self-organizing crystals. Moreover, this explains the “fine-tuning” question why our universe is fine-tuned to favor life: Our Universe is so self-organizing to have enough offspring and the detailed physics involved is at the same time highly favorable for all self-organizing processes including life.
This biological theory contrasts with current standard inflation cosmologies. The latter do not perform well in explaining any phenomena of sophisticated structure creation or self-organization. As proteins can only thermodynamically fold by increasing the entropy in the solution around them we suggest for cosmology a condensation nucleus for a universe can form only in a “chaotic ocean” of string-soup or quantum foam if the entropy outside of the nucleus rapidly increases. We derive an interaction potential for 1 to n-dimensional strings or quantum-foams and show that they allow only 1D, 2D, 4D or octonion interactions. The latter is the richest structure and agrees to the E8 symmetry fundamental to particle physics and also compatible with the ten dimensional string theory E8 which is part of the M-theory. Interestingly, any other interactions of other dimensionality can be ruled out using Hurwitz compositional theorem. Crystallization explains also extremely well why we have only one macroscopic reality and where the worldlines of alternative trajectories exist: They are in other planes of the crystal and for energy reasons they crystallize mostly at the same time, yielding a beautiful and stable crystal. This explains decoherence and allows to determine the size of Planck´s quantum h (very small as separation of crystal layers by energy is extremely strong).
Ultimate dissolution of real crystals suggests an explanation for dark energy agreeing with estimates for the “big rip”. The halo distribution of dark matter favoring galaxy formation is readily explained by a crystal seed starting with unit cells made of normal and dark matter.
That we have only matter and not antimatter can be explained as there may be right handed mattercrystals and left-handed antimatter crystals. Similarly, real crystals are never perfect and we argue that exactly such irregularities allow formation of galaxies, clusters and superclusters. Finally, heuristics from genetics suggest to look for a systems perspective to derive correct vacuum and Higgs Boson energies.
The phase space for the standard model of the basic four forces for n quanta includes all possible ensemble combinations of their quantum states m, a total of n**m states. Neighbor states reach according to transition possibilities (S-matrix) with emergent time from entropic ensemble gradients.
We replace the “big bang” by a condensation event (interacting qubits become decoherent) and inflation by a crystallization event – the crystal unit cell guarantees same symmetries everywhere. Interacting qubits solidify and form a rapidly growing domain where the n**m states become separated ensemble states, rising long-range forces stop ultimately further growth. After that very early events, standard cosmology with the hot fireball model takes over. Our theory agrees well with lack of inflation traces in cosmic background measurements, large-scale structure of voids and filaments, supercluster formation, galaxy formation, dominance of matter and life-friendliness.
We prove qubit interactions to be 1,2,4 or 8 dimensional (agrees with E8 symmetry of our universe). Repulsive forces at ultrashort distances result from quantization, long-range forces limit crystal growth. Crystals come and go in the qubit ocean. This selects for the ability to lay seeds for new crystals, for self-organization and life-friendliness.
We give energy estimates for free qubits vs bound qubits, misplacements in the qubit crystal and entropy increase during qubit decoherence / crystal formation. Scalar fields for color interaction and gravity derive from the permeating qubit-interaction field. Hence, vacuum energy gets low only inside the qubit crystal. Condensed mathematics may advantageously model free / bound qubits in phase space.
Conversational agents and smart speakers have grown in popularity offering a variety of options for use, which are available through intuitive speech operation. In contrast to the standard dyad of a single user and a device, voice-controlled operations can be observed by further attendees resulting in new, more social usage scenarios. Referring to the concept of ‘media equation’ and to research on the idea of ‘computers as social actors,’ which describes the potential of technology to trigger emotional reactions in users, this paper asks for the capacity of smart speakers to elicit empathy in observers of interactions. In a 2 × 2 online experiment, 140 participants watched a video of a man talking to an Amazon Echo either rudely or neutrally (factor 1), addressing it as ‘Alexa’ or ‘Computer’ (factor 2). Controlling for participants’ trait empathy, the rude treatment results in participants’ significantly higher ratings of empathy with the device, compared to the neutral treatment. The form of address had no significant effect. Results were independent of the participants’ gender and usage experience indicating a rather universal effect, which confirms the basic idea of the media equation. Implications for users, developers and researchers were discussed in the light of (future) omnipresent voice-based technology interaction scenarios.
Since ancient times aging has also been regarded as a disease, and humankind has always strived to extend the natural lifespan. Analyzing the genes involved in aging and disease allows for finding important indicators and biological markers for pathologies and possible therapeutic targets. An example of the use of omics technologies is the research regarding aging and the rare and fatal premature aging syndrome progeria (Hutchinson-Gilford progeria syndrome, HGPS). In our study, we focused on the in silico analysis of differentially expressed genes (DEGs) in progeria and aging, using a publicly available RNA-Seq dataset (GEO dataset GSE113957) and a variety of bioinformatics tools. Despite the GSE113957 RNA-Seq dataset being well-known and frequently analyzed, the RNA-Seq data shared by Fleischer et al. is far from exhausted and reusing and repurposing the data still reveals new insights. By analyzing the literature citing the use of the dataset and subsequently conducting a comparative analysis comparing the RNA-Seq data analyses of different subsets of the dataset (healthy children, nonagenarians and progeria patients), we identified several genes involved in both natural aging and progeria (KRT8, KRT18, ACKR4, CCL2, UCP2, ADAMTS15, ACTN4P1, WNT16, IGFBP2). Further analyzing these genes and the pathways involved indicated their possible roles in aging, suggesting the need for further in vitro and in vivo research. In this paper, we (1) compare “normal aging” (nonagenarians vs. healthy children) and progeria (HGPS patients vs. healthy children), (2) enlist genes possibly involved in both the natural aging process and progeria, including the first mention of IGFBP2 in progeria, (3) predict miRNAs and interactomes for WNT16 (hsa-mir-181a-5p), UCP2 (hsa-mir-26a-5p and hsa-mir-124-3p), and IGFBP2 (hsa-mir-124-3p, hsa-mir-126-3p, and hsa-mir-27b-3p), (4) demonstrate the compatibility of well-established R packages for RNA-Seq analysis for researchers interested but not yet familiar with this kind of analysis, and (5) present comparative proteomics analyses to show an association between our RNA-Seq data analyses and corresponding changes in protein expression.
We use algebraic closures and structures which are derived from these in complexity theory. We classify problems with Boolean circuits and Boolean constraints according to their complexity. We transfer algebraic structures to structural complexity. We use the generation problem to classify important complexity classes.
Small satellites contribute significantly in the rapidly evolving innovation in space engineering, in particular in distributed space systems for global Earth observation and communication services. Significant mass reduction by miniaturization, increased utilization of commercial high-tech components, and in particular standardization are the key drivers for modern miniature space technology.
This thesis addresses key fields in research and development on miniature satellite technology regarding efficiency, flexibility, and robustness. Here, these challenges are addressed by the University of Wuerzburg’s advanced pico-satellite bus, realizing a generic modular satellite architecture and standardized interfaces for all subsystems. The modular platform ensures reusability, scalability, and increased testability due to its flexible subsystem interface which allows efficient and compact integration of the entire satellite in a plug-and-play manner.
Beside systematic design for testability, a high degree of operational robustness is achieved by the consequent implementation of redundancy of crucial subsystems. This is combined with efficient fault detection, isolation and recovery mechanisms. Thus, the UWE-3 platform, and in particular the on-board data handling system and the electrical power system, offers one of the most efficient pico-satellite architectures launched in recent years and provides a solid basis for future extensions.
The in-orbit performance results of the pico-satellite UWE-3 are presented and summarize successful operations since its launch in 2013. Several software extensions and adaptations have been uploaded to UWE-3 increasing its capabilities. Thus, a very flexible platform for in-orbit software experiments and for evaluations of innovative concepts was provided and tested.
Background: Because most human stroke victims are elderly, studies of experimental stroke in the aged rather than the young rat model may be optimal for identifying clinically relevant cellular responses, as well for pinpointing beneficial interventions.
Methodology/Principal Findings: We employed the Affymetrix platform to analyze the whole-gene transcriptome following temporary ligation of the middle cerebral artery in aged and young rats. The correspondence, heat map, and dendrogram analyses independently suggest a differential, age-group-specific behaviour of major gene clusters after stroke. Overall, the pattern of gene expression strongly suggests that the response of the aged rat brain is qualitatively rather than quantitatively different from the young, i.e. the total number of regulated genes is comparable in the two age groups, but the aged rats had great difficulty in mounting a timely response to stroke. Our study indicates that four genes related to neuropathic syndrome, stress, anxiety disorders and depression (Acvr1c, Cort, Htr2b and Pnoc) may have impaired response to stroke in aged rats. New therapeutic options in aged rats may also include Calcrl, Cyp11b1, Prcp, Cebpa, Cfd, Gpnmb, Fcgr2b, Fcgr3a, Tnfrsf26, Adam 17 and Mmp14. An unexpected target is the enzyme 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 1 in aged rats, a key enzyme in the cholesterol synthesis pathway. Post-stroke axonal growth was compromised in both age groups.
Conclusion/Significance: We suggest that a multi-stage, multimodal treatment in aged animals may be more likely to produce positive results. Such a therapeutic approach should be focused on tissue restoration but should also address other aspects of patient post-stroke therapy such as neuropathic syndrome, stress, anxiety disorders, depression, neurotransmission and blood pressure.
Historical maps are fascinating documents and a valuable source of information for scientists of various disciplines. Many of these maps are available as scanned bitmap images, but in order to make them searchable in useful ways, a structured representation of the contained information is desirable.
This book deals with the extraction of spatial information from historical maps. This cannot be expected to be solved fully automatically (since it involves difficult semantics), but is also too tedious to be done manually at scale.
The methodology used in this book combines the strengths of both computers and humans: it describes efficient algorithms to largely automate information extraction tasks and pairs these algorithms with smart user interactions to handle what is not understood by the algorithm. The effectiveness of this approach is shown for various kinds of spatial documents from the 16th to the early 20th century.