004 Datenverarbeitung; Informatik
Refine
Has Fulltext
- yes (203)
Year of publication
Document Type
- Journal article (78)
- Doctoral Thesis (75)
- Working Paper (37)
- Conference Proceeding (8)
- Master Thesis (3)
- Report (2)
Language
- English (183)
- German (19)
- Multiple languages (1)
Keywords
- Datennetz (14)
- Leistungsbewertung (13)
- virtual reality (12)
- Robotik (8)
- Mobiler Roboter (7)
- Autonomer Roboter (6)
- Komplexitätstheorie (5)
- Optimierung (5)
- P4 (5)
- Simulation (5)
Institute
- Institut für Informatik (203) (remove)
Schriftenreihe
Sonstige beteiligte Institutionen
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
i
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.
LoRaWAN Network Planning in Smart Environments: Towards Reliability, Scalability, and Cost Reduction
(2022)
The goal in this work is to present a guidance for LoRaWAN planning to improve overall reliability for message transmissions and scalability. At the end, the cost component is discussed. Therefore, a five step approach is presented that helps to plan a LoRaWAN deployment step by step: Based on the device locations, an initial gateway placement is suggested followed by in-depth frequency and channel access planning. After an initial planning phase, updates for channel access and the initial gateway planning is suggested that should also be done periodically during network operation. Since current gateway placement approaches are only studied with random channel access, there is a lot of potential in the cell planning phase. Furthermore, the performance of different channel access approaches is highly related on network load, and thus cell size and sensor density. Last, the influence of different cell planning ideas on expected costs are discussed.
Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.
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.
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.
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.
Data mining has proved its significance in various domains and applications. As an important subfield of the general data mining task, subgroup mining can be used, e.g., for marketing purposes in business domains, or for quality profiling and analysis in medical domains. The goal is to efficiently discover novel, potentially useful and ultimately interesting knowledge. However, in real-world situations these requirements often cannot be fulfilled, e.g., if the applied methods do not scale for large data sets, if too many results are presented to the user, or if many of the discovered patterns are already known to the user. This thesis proposes a combination of several techniques in order to cope with the sketched problems: We discuss automatic methods, including heuristic and exhaustive approaches, and especially present the novel SD-Map algorithm for exhaustive subgroup discovery that is fast and effective. For an interactive approach we describe techniques for subgroup introspection and analysis, and we present advanced visualization methods, e.g., the zoomtable that directly shows the most important parameters of a subgroup and that can be used for optimization and exploration. We also describe various visualizations for subgroup comparison and evaluation in order to support the user during these essential steps. Furthermore, we propose to include possibly available background knowledge that is easy to formalize into the mining process. We can utilize the knowledge in many ways: To focus the search process, to restrict the search space, and ultimately to increase the efficiency of the discovery method. We especially present background knowledge to be applied for filtering the elements of the problem domain, for constructing abstractions, for aggregating values of attributes, and for the post-processing of the discovered set of patterns. Finally, the techniques are combined into a knowledge-intensive process supporting both automatic and interactive methods for subgroup mining. The practical significance of the proposed approach strongly depends on the available tools. We introduce the VIKAMINE system as a highly-integrated environment for knowledge-intensive active subgroup mining. Also, we present an evaluation consisting of two parts: With respect to objective evaluation criteria, i.e., comparing the efficiency and the effectiveness of the subgroup discovery methods, we provide an experimental evaluation using generated data. For that task we present a novel data generator that allows a simple and intuitive specification of the data characteristics. The results of the experimental evaluation indicate that the novel SD-Map method outperforms the other described algorithms using data sets similar to the intended application concerning the efficiency, and also with respect to precision and recall for the heuristic methods. Subjective evaluation criteria include the user acceptance, the benefit of the approach, and the interestingness of the results. We present five case studies utilizing the presented techniques: The approach has been successfully implemented in medical and technical applications using real-world data sets. The method was very well accepted by the users that were able to discover novel, useful, and interesting knowledge.
Knowledge encoding in game mechanics: transfer-oriented knowledge learning in desktop-3D and VR
(2019)
Affine Transformations (ATs) are a complex and abstract learning content. Encoding the AT knowledge in Game Mechanics (GMs) achieves a repetitive knowledge application and audiovisual demonstration. Playing a serious game providing these GMs leads to motivating and effective knowledge learning. Using immersive Virtual Reality (VR) has the potential to even further increase the serious game’s learning outcome and learning quality. This paper compares the effectiveness and efficiency of desktop-3D and VR in respect to the achieved learning outcome. Also, the present study analyzes the effectiveness of an enhanced audiovisual knowledge encoding and the provision of a debriefing system. The results validate the effectiveness of the knowledge encoding in GMs to achieve knowledge learning. The study also indicates that VR is beneficial for the overall learning quality and that an enhanced audiovisual encoding has only a limited effect on the learning outcome.
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 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.
Virtual environments (VEs) can evoke and support emotions, as experienced when playing emotionally arousing games. We theoretically approach the design of fear and joy evoking VEs based on a literature review of empirical studies on virtual and real environments as well as video games’ reviews and content analyses. We define the design space and identify central design elements that evoke specific positive and negative emotions. Based on that, we derive and present guidelines for emotion-inducing VE design with respect to design themes, colors and textures, and lighting configurations. To validate our guidelines in two user studies, we 1) expose participants to 360° videos of VEs designed following the individual guidelines and 2) immerse them in a neutral, positive and negative emotion-inducing VEs combining all respective guidelines in Virtual Reality. The results support our theoretically derived guidelines by revealing significant differences in terms of fear and joy induction.
This paper examines the relationship between time and motion perception in virtual environments. Previous work has shown that the perception of motion can affect the perception of time. We developed a virtual environment that simulates motion in a tunnel and measured its effects on the estimation of the duration of time, the speed at which perceived time passes, and the illusion of self-motion, also known as vection. When large areas of the visual field move in the same direction, vection can occur; observers often perceive this as self-motion rather than motion of the environment. To generate different levels of vection and investigate its effects on time perception, we developed an abstract procedural tunnel generator. The generator can simulate different speeds and densities of tunnel sections (visibly distinguishable sections that form the virtual tunnel), as well as the degree of embodiment of the user avatar (with or without virtual hands). We exposed participants to various tunnel simulations with different durations, speeds, and densities in a remote desktop and a virtual reality (VR) laboratory study. Time passed subjectively faster under high-speed and high-density conditions in both studies. The experience of self-motion was also stronger under high-speed and high-density conditions. Both studies revealed a significant correlation between the perceived passage of time and perceived self-motion. Subjects in the virtual reality study reported a stronger self-motion experience, a faster perceived passage of time, and shorter time estimates than subjects in the desktop study. Our results suggest that a virtual tunnel simulation can manipulate time perception in virtual reality. We will explore these results for the development of virtual reality applications for therapeutic approaches in our future work. This could be particularly useful in treating disorders like depression, autism, and schizophrenia, which are known to be associated with distortions in time perception. For example, the tunnel could be therapeutically applied by resetting patients’ time perceptions by exposing them to the tunnel under different conditions, such as increasing or decreasing perceived time.
The introduction of new types of frequency spectrum in 6G technology facilitates the convergence of conventional mobile communications and radar functions. Thus, the mobile network itself becomes a versatile sensor system. This enables mobile network operators to offer a sensing service in addition to conventional data and telephony services. The potential benefits are expected to accrue to various stakeholders, including individuals, the environment, and society in general. The paper discusses technological development, possible integration, and use cases, as well as future development areas.
The joint 1st Workshop on Evaluations and Measurements in Self-Aware Computing Systems (EMSAC 2019) and Workshop on Self-Aware Computing (SeAC) was held as part of the FAS* conference alliance in conjunction with the 16th IEEE International Conference on Autonomic Computing (ICAC) and the 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO) in Umeå, Sweden on 20 June 2019. The goal of this one-day workshop was to bring together researchers and practitioners from academic environments and from the industry to share their solutions, ideas, visions, and doubts in self-aware computing systems in general and in the evaluation and measurements of such systems in particular. The workshop aimed to enable discussions, partnerships, and collaborations among the participants. This special issue follows the theme of the workshop. It contains extended versions of workshop presentations as well as additional contributions.
This work is composed of three main parts: remote control of mobile systems via Internet, ad-hoc networks of mobile robots, and remote control of mobile robots via 3G telecommunication technologies. The first part gives a detailed state of the art and a discussion of the problems to be solved in order to teleoperate mobile robots via the Internet. The focus of the application to be realized is set on a distributed tele-laboratory with remote experiments on mobile robots which can be accessed world-wide via the Internet. Therefore, analyses of the communication link are used in order to realize a robust system. The developed and implemented architecture of this distributed tele-laboratory allows for a smooth access also with a variable or low link quality. The second part covers the application of ad-hoc networks for mobile robots. The networking of mobile robots via mobile ad-hoc networks is a very promising approach to realize integrated telematic systems without relying on preexisting communication infrastructure. Relevant civilian application scenarios are for example in the area of search and rescue operations where first responders are supported by multi-robot systems. Here, mobile robots, humans, and also existing stationary sensors can be connected very fast and efficient. Therefore, this work investigates and analyses the performance of different ad-hoc routing protocols for IEEE 802.11 based wireless networks in relevant scenarios. The analysis of the different protocols allows for an optimization of the parameter settings in order to use these ad-hoc routing protocols for mobile robot teleoperation. Also guidelines for the realization of such telematics systems are given. Also traffic shaping mechanisms of application layer are presented which allow for a more efficient use of the communication link. An additional application scenario, the integration of a small size helicopter into an IP based ad-hoc network, is presented. The teleoperation of mobile robots via 3G telecommunication technologies is addressed in the third part of this work. The high availability, high mobility, and the high bandwidth provide a very interesting opportunity to realize scenarios for the teleoperation of mobile robots or industrial remote maintenance. This work analyses important parameters of the UMTS communication link and investigates also the characteristics for different data streams. These analyses are used to give guidelines which are necessary for the realization of or industrial remote maintenance or mobile robot teleoperation scenarios. All the results and guidelines for the design of telematic systems in this work were derived from analyses and experiments with real hardware.
In this paper, we bridge the gap between procedural content generation (PCG) and user-generated content (UGC) by proposing and demonstrating an interactive agent-based model of self-assembling ensembles that can be directed though user input. We motivate these efforts by considering the opportunities technology provides to pursue game designs based on according game design frameworks. We present three different use cases of the proposed model that emphasize its potential to (1) self-assemble into predefined 3D graphical assets, (2) define new structures in the context of virtual environments by self-assembling layers on the surfaces of arbitrary 3D objects, and (3) allow novel structures to self-assemble only considering the model’s configuration and no external dependencies. To address the performance restrictions in computer games, we realized the prototypical model implementation by means of an efficient entity component system (ECS). We conclude the paper with an outlook on future steps to further explore novel interactive, dynamic PCG mechanics and to ensure their efficiency.
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.
Modern software is often realized as a modular combination of subsystems for, e. g.,
knowledge management, visualization, verification, or the interaction with users. As
a result, software libraries from possibly different programming languages have to
work together. Even more complex the case is if different programming paradigms
have to be combined. This type of diversification of programming languages and
paradigms in just one software application can only be mastered by mechanisms
for a seamless integration of the involved programming languages. However, the
integration of the common logic programming language Prolog and the popular
object-oriented programming language Java is complicated by various interoperability
problems which stem on the one hand from the paradigmatic gap between the
programming languages, and on the other hand, from the diversity of the available
Prolog systems.
The subject of the thesis is the investigation of novel mechanisms for the integration
of logic programming in Prolog and object–oriented programming in Java. We are
particularly interested in an object–oriented, uniform approach which is not specific
to just one Prolog system. Therefore, we have first identified several important
criteria for the seamless integration of Prolog and Java from the object–oriented
perspective. The main contribution of the thesis is a novel integration framework
called the Connector Architecture for Prolog and Java (CAPJa). The framework is
completely implemented in Java and imposes no modifications to the Java Virtual
Machine or Prolog. CAPJa provides a semi–automated mechanism for the integration
of Prolog predicates into Java. For compact, readable, and object–oriented
queries to Prolog, CAPJa exploits lambda expressions with conditional and relational
operators in Java. The communication between Java and Prolog is based
on a fully automated mapping of Java objects to Prolog terms, and vice versa. In
Java, an extensible system of gateways provides connectivity with various Prolog
system and, moreover, makes any connected Prolog system easily interchangeable,
without major adaption in Java.
Learning is a central component of human life and essential for personal development. Therefore, utilizing new technologies in the learning context and exploring their combined potential are considered essential to support self-directed learning in a digital age. A learning environment can be expanded by various technical and content-related aspects. Gamification in the form of elements from video games offers a potential concept to support the learning process. This can be supplemented by technology-supported learning. While the use of tablets is already widespread in the learning context, the integration of a social robot can provide new perspectives on the learning process. However, simply adding new technologies such as social robots or gamification to existing systems may not automatically result in a better learning environment. In the present study, game elements as well as a social robot were integrated separately and conjointly into a learning environment for basic Spanish skills, with a follow-up on retained knowledge. This allowed us to investigate the respective and combined effects of both expansions on motivation, engagement and learning effect. This approach should provide insights into the integration of both additions in an adult learning context. We found that the additions of game elements and the robot did not significantly improve learning, engagement or motivation. Based on these results and a literature review, we outline relevant factors for meaningful integration of gamification and social robots in learning environments in adult learning.
Global Navigation Satellite System (GNSS) provides accurate positioning data for vehicular navigation in open outdoor environment. In an indoor environment, Light Detection and Ranging (LIDAR) Simultaneous Localization and Mapping (SLAM) establishes a two-dimensional map and provides positioning data. However, LIDAR can only provide relative positioning data and it cannot directly provide the latitude and longitude of the current position. As a consequence, GNSS/Inertial Navigation System (INS) integrated navigation could be employed in outdoors, while the indoors part makes use of INS/LIDAR integrated navigation and the corresponding switching navigation will make the indoor and outdoor positioning consistent. In addition, when the vehicle enters the garage, the GNSS signal will be blurred for a while and then disappeared. Ambiguous GNSS satellite signals will lead to the continuous distortion or overall drift of the positioning trajectory in the indoor condition. Therefore, an INS/LIDAR seamless integrated navigation algorithm and a switching algorithm based on vehicle navigation system are designed. According to the experimental data, the positioning accuracy of the INS/LIDAR navigation algorithm in the simulated environmental experiment is 50% higher than that of the Dead Reckoning (DR) algorithm. Besides, the switching algorithm developed based on the INS/LIDAR integrated navigation algorithm can achieve 80% success rate in navigation mode switching.