Content rendering and interaction technologies for digital heritage systems

Existing digital heritage systems accommodate a huge amount of digital repository information; however their content rendering and interaction components generally lack the more interesting functionality that allows better interaction with heritage contents. Many digital heritage libraries are simply collections of 2D images with associated metadata and textual content, i.e. little more than museum catalogues presented online. However, over the last few years, largely as a result of EU framework projects, some 3D representation of digital heritage objects are beginning to appear in a digital library context. In the cultural heritage domain, where researchers and museum visitors like to observe cultural objects as closely as possible and to feel their existence and use in the past, giving the user only 2D images along with textual descriptions significantly limits interaction and hence understanding of their heritage. The availability of powerful content rendering technologies, such as 3D authoring tools to create 3D objects and heritage scenes, grid tools for rendering complex 3D scenes, gaming engines to display 3D interactively, and recent advances in motion capture technologies for embodied immersion, allow the development of unique solutions for enhancing user experience and interaction with digital heritage resources and objects giving a higher level of understanding and greater benefit to the community. This thesis describes DISPLAYS (Digital Library Services for Playing with Shared Heritage Resources), which is a novel conceptual framework where five unique services are proposed for digital content: creation, archival, exposition, presentation and interaction services. These services or tools are designed to allow the heritage community to create, interpret, use and explore digital heritage resources organised as an online exhibition (or virtual museum). This thesis presents innovative solutions for two of these services or tools: content creation where a cost effective render grid is proposed; and an interaction service, where a heritage scenario is presented online using a real-time motion capture and digital puppeteer solution for the user to explore through embodied immersive interaction their digital heritage

Enhancing Data Processing on Clouds with Hadoop/HBase

In the current information age, large amounts of data are being generated and accumulated rapidly in various industrial and scientific domains. This imposes important demands on data processing capabilities that can extract sensible and valuable information from the large amount of data in a timely manner. Hadoop, the open source implementation of Google's data processing framework (MapReduce, Google File System and BigTable), is becoming increasingly popular and being used to solve data processing problems in various application scenarios. However, being originally designed for handling very large data sets that can be divided easily in parts to be processed independently with limited inter-task communication, Hadoop lacks applicability to a wider usage case. As a result, many projects are under way to enhance Hadoop for different application needs, such as data warehouse applications, machine learning and data mining applications, etc. This thesis is one such research effort in this direction. The goal of the thesis research is to design novel tools and techniques to extend and enhance the large-scale data processing capability of Hadoop/HBase on clouds, and to evaluate their effectiveness in performance tests on prototype implementations. Two main research contributions are described. The first contribution is a light-weight computational workflow system called "CloudWF" for Hadoop. The second contribution is a client library called "HBaseSI" supporting transactional snapshot isolation (SI) in HBase, Hadoop's database component. CloudWF addresses the problem of automating the execution of scientific workflows composed of both MapReduce and legacy applications on clouds with Hadoop/HBase. CloudWF is the first computational workflow system built directly using Hadoop/HBase. It uses novel methods in handling workflow directed acyclic graph decomposition, storing and querying dependencies in HBase sparse tables, transparent file staging, and decentralized workflow execution management relying on the MapReduce framework for task scheduling and fault tolerance. HBaseSI addresses the problem of maintaining strong transactional data consistency in HBase tables. This is the first SI mechanism developed for HBase. HBaseSI uses novel methods in handling distributed transactional management autonomously by individual clients. These methods greatly simplify the design of HBaseSI and can be generalized to other column-oriented stores with similar architecture as HBase. As a result of the simplicity in design, HBaseSI adds low overhead to HBase performance and directly inherits many desirable properties of HBase. HBaseSI is non-intrusive to existing HBase installations and user data, and is designed to work with a large cloud in terms of data size and the number of nodes in the cloud

Personalized Interaction with High-Resolution Wall Displays

Fallende Hardwarepreise sowie eine zunehmende Offenheit gegenüber neuartigen Interaktionsmodalitäten haben in den vergangen Jahren den Einsatz von wandgroßen interaktiven Displays möglich gemacht, und in der Folge ist ihre Anwendung, unter anderem in den Bereichen Visualisierung, Bildung, und der Unterstützung von Meetings, erfolgreich demonstriert worden. Aufgrund ihrer Größe sind Wanddisplays für die Interaktion mit mehreren Benutzern prädestiniert. Gleichzeitig kann angenommen werden, dass Zugang zu persönlichen Daten und Einstellungen — mithin personalisierte Interaktion — weiterhin essentieller Bestandteil der meisten Anwendungsfälle sein wird. Aktuelle Benutzerschnittstellen im Desktop- und Mobilbereich steuern Zugriffe über ein initiales Login. Die Annahme, dass es nur einen Benutzer pro Bildschirm gibt, zieht sich durch das gesamte System, und ermöglicht unter anderem den Zugriff auf persönliche Daten und Kommunikation sowie persönliche Einstellungen. Gibt es hingegen mehrere Benutzer an einem großen Bildschirm, müssen hierfür Alternativen gefunden werden. Die daraus folgende Forschungsfrage dieser Dissertation lautet: Wie können wir im Kontext von Mehrbenutzerinteraktion mit wandgroßen Displays personalisierte Schnittstellen zur Verfügung stellen? Die Dissertation befasst sich sowohl mit personalisierter Interaktion in der Nähe (mit Touch als Eingabemodalität) als auch in etwas weiterer Entfernung (unter Nutzung zusätzlicher mobiler Geräte). Grundlage für personalisierte Mehrbenutzerinteraktion sind technische Lösungen für die Zuordnung von Benutzern zu einzelnen Interaktionen. Hierzu werden zwei Alternativen untersucht: In der ersten werden Nutzer via Kamera verfolgt, und in der zweiten werden Mobilgeräte anhand von Ultraschallsignalen geortet. Darauf aufbauend werden Interaktionstechniken vorgestellt, die personalisierte Interaktion unterstützen. Diese nutzen zusätzliche Mobilgeräte, die den Zugriff auf persönliche Daten sowie Interaktion in einigem Abstand von der Displaywand ermöglichen. Einen weiteren Teil der Arbeit bildet die Untersuchung der praktischen Auswirkungen der Ausgabe- und Interaktionsmodalitäten für personalisierte Interaktion. Hierzu wird eine qualitative Studie vorgestellt, die Nutzerverhalten anhand des kooperativen Mehrbenutzerspiels Miners analysiert. Der abschließende Beitrag beschäftigt sich mit dem Analyseprozess selber: Es wird das Analysetoolkit für Wandinteraktionen GIAnT vorgestellt, das Nutzerbewegungen, Interaktionen, und Blickrichtungen visualisiert und dadurch die Untersuchung der Interaktionen stark vereinfacht.An increasing openness for more diverse interaction modalities as well as falling hardware prices have made very large interactive vertical displays more feasible, and consequently, applications in settings such as visualization, education, and meeting support have been demonstrated successfully. Their size makes wall displays inherently usable for multi-user interaction. At the same time, we can assume that access to personal data and settings, and thus personalized interaction, will still be essential in most use-cases. In most current desktop and mobile user interfaces, access is regulated via an initial login and the complete user interface is then personalized to this user: Access to personal data, configurations and communications all assume a single user per screen. In the case of multiple people using one screen, this is not a feasible solution and we must find alternatives. Therefore, this thesis addresses the research question: How can we provide personalized interfaces in the context of multi-user interaction with wall displays? The scope spans personalized interaction both close to the wall (using touch as input modality) and further away (using mobile devices). Technical solutions that identify users at each interaction can replace logins and enable personalized interaction for multiple users at once. This thesis explores two alternative means of user identification: Tracking using RGB+depth-based cameras and leveraging ultrasound positioning of the users' mobile devices. Building on this, techniques that support personalized interaction using personal mobile devices are proposed. In the first contribution on interaction, HyDAP, we examine pointing from the perspective of moving users, and in the second, SleeD, we propose using an arm-worn device to facilitate access to private data and personalized interface elements. Additionally, the work contributes insights on practical implications of personalized interaction at wall displays: We present a qualitative study that analyses interaction using a multi-user cooperative game as application case, finding awareness and occlusion issues. The final contribution is a corresponding analysis toolkit that visualizes users' movements, touch interactions and gaze points when interacting with wall displays and thus allows fine-grained investigation of the interactions

A Survey on Transactional Stream Processing

Transactional stream processing (TSP) strives to create a cohesive model that merges the advantages of both transactional and stream-oriented guarantees. Over the past decade, numerous endeavors have contributed to the evolution of TSP solutions, uncovering similarities and distinctions among them. Despite these advances, a universally accepted standard approach for integrating transactional functionality with stream processing remains to be established. Existing TSP solutions predominantly concentrate on specific application characteristics and involve complex design trade-offs. This survey intends to introduce TSP and present our perspective on its future progression. Our primary goals are twofold: to provide insights into the diverse TSP requirements and methodologies, and to inspire the design and development of groundbreaking TSP systems

A Framework for Delivering Contextually Appropriate Opportunities for Warfighter Practice

Computer-based modeling and simulation has been a training staple in the military domain since the first aircraft simulators were adopted. More recently, virtual environments based on modeling, simulation and serious games, have introduced relatively low-cost, yet high value additions to the learning environment. As these virtual environments have proliferated, many researchers have investigated the relationship between theoretical foundations of learning, learner development and content delivery, and applied their findings in an attempt to bolster learning, yet performance deficiencies continue to exist. This study asserts that performance deficiencies exist in part because of insufficient contextually appropriate opportunities to practice. This work is multi-disciplinary in nature. Its foundation is modeling and simulation engineering; the use of technology to deliver training. Educational psychology and human factors concepts explain the theoretical basis for modeling and simulation as an effective training delivery agent. The study\u27s thesis is that a framework for delivering contextually appropriate opportunities for warfighter practice can be applied to discover whether modeling, simulation and game-based virtual environments have the potential to improve individual performance for learners beyond the Novice Stage (e.g., Competent Stage) of skills acquisition. Furthermore, this conceptually appropriate practice (CAP) framework can be used to assess the potential of low fidelity virtual environments to provide targeted practice and to improve individual performance, not only during training in high-fidelity virtual environments (near transfer) but also in the live environment (far transfer). To evaluate the thesis, this study investigates the relationship of technology and learning science, and features an empirical evaluation of training effectiveness afforded by delivering additional training repetitions using both low-fidelity virtual environment simulator systems and high-fidelity aircraft simulators

Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

Using local and global knowledge in wireless sensor networks

Wireless sensor networks (WSNs) have advanced rapidly in recent years and the volume of raw data received at an endpoint can be huge. We believe that the use of local knowledge, acquired from sources such as the surrounding environment, users and previously sensed data, can improve the efficiency of a WSN and automate the classification of sensed data. We define local knowledge as knowledge about an area that has been gained through experience or experimentation. With this in mind, we have developed a three-tiered architecture for WSNs that uses differing knowledge-processing capabilities at each tier, called the Knowledge-based Hierarchical Architecture for Sensing (KHAS). A novel aligning ontology has been created to support K-HAS, joining widely used, domain-specific ontologies from the sensing and observation domains. We have shown that, as knowledge-processing capabilities are pushed further out into the network, the profit - defined as the value of sensed data - is increased; where the profit is defined as the value of the sensed data received by the end user. Collaborating with Cardiff University School of Biosciences, we have deployed a variation of K-HAS in the Malaysian rainforest to capture images of endangered wildlife, as well as to automate the collection and classification of these images. Technological limitations prevented a complete implementation of K-HAS and an amalgamation of tiers was made to create the Local knowledge Ontology-based Remote-sensing Informatics System (LORIS). A two week deployment in Malaysia suggested that the architecture was viable and that, even using local knowledge at the endpoint of a WSN, improved the efficiency of the network. A simulation was implemented to model K-HAS and this indicated that the network became more efficient as knowledge was pushed further out towards the edge, by allowing nodes to prioritise sensed data based on inferences about its content

Architectural support for ubiquitous access to multimedia content

Tese de doutoramento. Engenharia Electrotécnica e de Computadores (Telecomunicações). Faculdade de Engenharia. Universidade do Porto. 200