14 research outputs found

    Fifth Biennial Report : June 1999 - August 2001

    No full text

    Eight Biennial Report : April 2005 – March 2007

    No full text

    Cross-Layer Cloud Performance Monitoring, Analysis and Recovery

    Get PDF
    The basic idea of Cloud computing is to offer software and hardware resources as services. These services are provided at different layers: Software (Software as a Service: SaaS), Platform (Platform as a Service: PaaS) and Infrastructure (Infrastructure as a Service: IaaS). In such a complex environment, performance issues are quite likely and rather the norm than the exception. Consequently, performance-related problems may frequently occur at all layers. Thus, it is necessary to monitor all Cloud layers and analyze their performance parameters to detect and rectify related problems. This thesis presents a novel cross-layer reactive performance monitoring approach for Cloud computing environments, based on the methodology of Complex Event Processing (CEP). The proposed approach is called CEP4Cloud. It analyzes monitored events to detect performance-related problems and performs actions to fix them. The proposal is based on the use of (1) a novel multi-layer monitoring approach, (2) a new cross-layer analysis approach and (3) a novel recovery approach. The proposed monitoring approach operates at all Cloud layers, while collecting related parameters. It makes use of existing monitoring tools and a new monitoring approach for Cloud services at the SaaS layer. The proposed SaaS monitoring approach is called AOP4CSM. It is based on aspect-oriented programming and monitors quality-of-service parameters of the SaaS layer in a non-invasive manner. AOP4CSM neither modifies the server implementation nor the client implementation. The defined cross-layer analysis approach is called D-CEP4CMA. It is based on the methodology of Complex Event Processing (CEP). Instead of having to manually specify continuous queries on monitored event streams, CEP queries are derived from analyzing the correlations between monitored metrics across multiple Cloud layers. The results of the correlation analysis allow us to reduce the number of monitored parameters and enable us to perform a root cause analysis to identify the causes of performance-related problems. The derived analysis rules are implemented as queries in a CEP engine. D-CEP4CMA is designed to dynamically switch between different centralized and distributed CEP architectures depending on the load/memory of the CEP machine and network traffic conditions in the observed Cloud environment. The proposed recovery approach is based on a novel action manager framework. It applies recovery actions at all Cloud layers. The novel action manager framework assigns a set of repair actions to each performance-related problem and checks the success of the applied action. The results of several experiments illustrate the merits of the reactive performance monitoring approach and its main components (i.e., monitoring, analysis and recovery). First, experimental results show the efficiency of AOP4CSM (very low overhead). Second, obtained results demonstrate the benefits of the analysis approach in terms of precision and recall compared to threshold-based methods. They also show the accuracy of the analysis approach in identifying the causes of performance-related problems. Furthermore, experiments illustrate the efficiency of D-CEP4CMA and its performance in terms of precision and recall compared to centralized and distributed CEP architectures. Moreover, experimental results indicate that the time needed to fix a performance-related problem is reasonably short. They also show that the CPU overhead of using CEP4Cloud is negligible. Finally, experimental results demonstrate the merits of CEP4Cloud in terms of speeding up the repair and reducing the number of triggered alarms compared to baseline methods

    Shape Retrieval Methods for Architectural 3D Models

    Get PDF
    This thesis introduces new methods for content-based retrieval of architecture-related 3D models. We thereby consider two different overall types of architectural 3D models. The first type consists of context objects that are used for detailed design and decoration of 3D building model drafts. This includes e.g. furnishing for interior design or barriers and fences for forming the exterior environment. The second type consists of actual building models. To enable efficient content-based retrieval for both model types that is tailored to the user requirements of the architectural domain, type-specific algorithms must be developed. On the one hand, context objects like furnishing that provide similar functions (e.g. seating furniture) often share a similar shape. Nevertheless they might be considered to belong to different object classes from an architectural point of view (e.g. armchair, elbow chair, swivel chair). The differentiation is due to small geometric details and is sometimes only obvious to an expert from the domain. Building models on the other hand are often distinguished according to the underlying floor- and room plans. Topological floor plan properties for example serve as a starting point for telling apart residential and commercial buildings. The first contribution of this thesis is a new meta descriptor for 3D retrieval that combines different types of local shape descriptors using a supervised learning approach. The approach enables the differentiation of object classes according to small geometric details and at the same time integrates expert knowledge from the field of architecture. We evaluate our approach using a database containing arbitrary 3D models as well as on one that only consists of models from the architectural domain. We then further extend our approach by adding a sophisticated shape descriptor localization strategy. Additionally, we exploit knowledge about the spatial relationship of object components to further enhance the retrieval performance. In the second part of the thesis we introduce attributed room connectivity graphs (RCGs) as a means to characterize a 3D building model according to the structure of its underlying floor plans. We first describe how RCGs are inferred from a given building model and discuss how substructures of this graph can be queried efficiently. We then introduce a new descriptor denoted as Bag-of-Attributed-Subgraphs that transforms attributed graphs into a vector-based representation using subgraph embeddings. We finally evaluate the retrieval performance of this new method on a database consisting of building models with different floor plan types. All methods presented in this thesis are aimed at an as automated as possible workflow for indexing and retrieval such that only minimum human interaction is required. Accordingly, only polygon soups are required as inputs which do not need to be manually repaired or structured. Human effort is only needed for offline groundtruth generation to enable supervised learning and for providing information about the orientation of building models and the unit of measurement used for modeling

    Development of Human Body CAD Models and Related Mesh Processing Algorithms with Applications in Bioelectromagnetics

    Get PDF
    Simulation of the electromagnetic response of the human body relies heavily upon efficient computational CAD models or phantoms. The Visible Human Project (VHP)-Female v. 3.1 - a new platform-independent full-body electromagnetic computational model is revealed. This is a part of a significant international initiative to develop powerful computational models representing the human body. This model’s unique feature is full compatibility both with MATLAB and specialized FEM computational software packages such as ANSYS HFSS/Maxwell 3D and CST MWS. Various mesh processing algorithms such as automatic intersection resolver, Boolean operation on meshes, etc. used for the development of the Visible Human Project (VHP)-Female are presented. The VHP - Female CAD Model is applied to two specific low frequency applications: Transcranial Magnetic Stimulation (TMS) and Transcranial Direct Current Stimulation (tDCS). TMS and tDCS are increasingly used as diagnostic and therapeutic tools for numerous neuropsychiatric disorders. The development of a CAD model based on an existing voxel model of a Japanese pregnant woman is also presented. TMS for treatment of depression is an appealing alternative to drugs which are teratogenic for pregnant women. This CAD model was used to study fetal wellbeing during induced peak currents by TMS in two possible scenarios: (i) pregnant woman as a patient; and (ii) pregnant woman as an operator. An insight into future work and potential areas of research such as a deformable phantom, implants, and RF applications will be presented

    Architectures for ubiquitous 3D on heterogeneous computing platforms

    Get PDF
    Today, a wide scope for 3D graphics applications exists, including domains such as scientific visualization, 3D-enabled web pages, and entertainment. At the same time, the devices and platforms that run and display the applications are more heterogeneous than ever. Display environments range from mobile devices to desktop systems and ultimately to distributed displays that facilitate collaborative interaction. While the capability of the client devices may vary considerably, the visualization experiences running on them should be consistent. The field of application should dictate how and on what devices users access the application, not the technical requirements to realize the 3D output. The goal of this thesis is to examine the diverse challenges involved in providing consistent and scalable visualization experiences to heterogeneous computing platforms and display setups. While we could not address the myriad of possible use cases, we developed a comprehensive set of rendering architectures in the major domains of scientific and medical visualization, web-based 3D applications, and movie virtual production. To provide the required service quality, performance, and scalability for different client devices and displays, our architectures focus on the efficient utilization and combination of the available client, server, and network resources. We present innovative solutions that incorporate methods for hybrid and distributed rendering as well as means to manage data sets and stream rendering results. We establish the browser as a promising platform for accessible and portable visualization services. We collaborated with experts from the medical field and the movie industry to evaluate the usability of our technology in real-world scenarios. The presented architectures achieve a wide coverage of display and rendering setups and at the same time share major components and concepts. Thus, they build a strong foundation for a unified system that supports a variety of use cases.Heutzutage existiert ein großer Anwendungsbereich für 3D-Grafikapplikationen wie wissenschaftliche Visualisierungen, 3D-Inhalte in Webseiten, und Unterhaltungssoftware. Gleichzeitig sind die Geräte und Plattformen, welche die Anwendungen ausführen und anzeigen, heterogener als je zuvor. Anzeigegeräte reichen von mobilen Geräten zu Desktop-Systemen bis hin zu verteilten Bildschirmumgebungen, die eine kollaborative Anwendung begünstigen. Während die Leistungsfähigkeit der Geräte stark schwanken kann, sollten die dort laufenden Visualisierungen konsistent sein. Das Anwendungsfeld sollte bestimmen, wie und auf welchem Gerät Benutzer auf die Anwendung zugreifen, nicht die technischen Voraussetzungen zur Erzeugung der 3D-Grafik. Das Ziel dieser Thesis ist es, die diversen Herausforderungen zu untersuchen, die bei der Bereitstellung von konsistenten und skalierbaren Visualisierungsanwendungen auf heterogenen Plattformen eine Rolle spielen. Während wir nicht die Vielzahl an möglichen Anwendungsfällen abdecken konnten, haben wir eine repräsentative Auswahl an Rendering-Architekturen in den Kernbereichen wissenschaftliche Visualisierung, web-basierte 3D-Anwendungen, und virtuelle Filmproduktion entwickelt. Um die geforderte Qualität, Leistung, und Skalierbarkeit für verschiedene Client-Geräte und -Anzeigen zu gewährleisten, fokussieren sich unsere Architekturen auf die effiziente Nutzung und Kombination der verfügbaren Client-, Server-, und Netzwerkressourcen. Wir präsentieren innovative Lösungen, die hybrides und verteiltes Rendering als auch das Verwalten der Datensätze und Streaming der 3D-Ausgabe umfassen. Wir etablieren den Web-Browser als vielversprechende Plattform für zugängliche und portierbare Visualisierungsdienste. Um die Verwendbarkeit unserer Technologie in realitätsnahen Szenarien zu testen, haben wir mit Experten aus der Medizin und Filmindustrie zusammengearbeitet. Unsere Architekturen erreichen eine umfassende Abdeckung von Anzeige- und Rendering-Szenarien und teilen sich gleichzeitig wesentliche Komponenten und Konzepte. Sie bilden daher eine starke Grundlage für ein einheitliches System, das eine Vielzahl an Anwendungsfällen unterstützt

    The Machine as Art/ The Machine as Artist

    Get PDF
    The articles collected in this volume from the two companion Arts Special Issues, “The Machine as Art (in the 20th Century)” and “The Machine as Artist (in the 21st Century)”, represent a unique scholarly resource: analyses by artists, scientists, and engineers, as well as art historians, covering not only the current (and astounding) rapprochement between art and technology but also the vital post-World War II period that has led up to it; this collection is also distinguished by several of the contributors being prominent individuals within their own fields, or as artists who have actually participated in the still unfolding events with which it is concerne

    The Machine as Art/ The Machine as Artist

    Get PDF

    Constrained camera motion estimation and 3D reconstruction

    Get PDF
    The creation of virtual content from visual data is a tedious task which requires a high amount of skill and expertise. Although the majority of consumers is in possession of multiple imaging devices that would enable them to perform this task in principle, the processing techniques and tools are still intended for the use by trained experts. As more and more capable hardware becomes available, there is a growing need among consumers and professionals alike for new flexible and reliable tools that reduce the amount of time and effort required to create high-quality content. This thesis describes advances of the state of the art in three areas of computer vision: camera motion estimation, probabilistic 3D reconstruction, and template fitting. First, a new camera model geared towards stereoscopic input data is introduced, which is subsequently developed into a generalized framework for constrained camera motion estimation. A probabilistic reconstruction method for 3D line segments is then described, which takes global connectivity constraints into account. Finally, a new framework for symmetry-aware template fitting is presented, which allows the creation of high-quality models from low-quality input 3D scans. Evaluations with a broad range of challenging synthetic and real-world data sets demonstrate that the new constrained camera motion estimation methods provide improved accuracy and flexibility, and that the new constrained 3D reconstruction methods improve the current state of the art.Die Erzeugung virtueller Inhalte aus visuellem Datenmaterial ist langwierig und erfordert viel Geschick und Sachkenntnis. Obwohl der Großteil der Konsumenten mehrere Bildgebungsgeräte besitzt, die es ihm im Prinzip erlauben würden, dies durchzuführen, sind die Techniken und Werkzeuge noch immer für den Einsatz durch ausgebildete Fachleute gedacht. Da immer leistungsfähigere Hardware zur Verfügung steht, gibt es sowohl bei Konsumenten als auch bei Fachleuten eine wachsende Nachfrage nach neuen flexiblen und verlässlichen Werkzeugen, die die Erzeugung von qualitativ hochwertigen Inhalten vereinfachen. In der vorliegenden Arbeit werden Erweiterungen des Stands der Technik in den folgenden drei Bereichen der Bildverarbeitung beschrieben: Kamerabewegungsschätzung, wahrscheinlichkeitstheoretische 3D-Rekonstruktion und Template-Fitting. Zuerst wird ein neues Kameramodell vorgestellt, das für die Verarbeitung von stereoskopischen Eingabedaten ausgelegt ist. Dieses Modell wird in der Folge in eine generalisierte Methode zur Kamerabewegungsschätzung unter Nebenbedingungen erweitert. Anschließend wird ein wahrscheinlichkeitstheoretisches Verfahren zur Rekonstruktion von 3D-Liniensegmenten beschrieben, das globale Verbindungen als Nebenbedingungen berücksichtigt. Schließlich wird eine neue Methode zum Fitting eines Template-Modells präsentiert, bei der die Berücksichtigung der Symmetriestruktur des Templates die Erzeugung von Modellen hoher Qualität aus 3D-Eingabedaten niedriger Qualität erlaubt. Evaluierungen mit einem breiten Spektrum an anspruchsvollen synthetischen und realen Datensätzen zeigen, dass die neuen Methoden zur Kamerabewegungsschätzung unter Nebenbedingungen höhere Genauigkeit und mehr Flexibilität ermöglichen, und dass die neuen Methoden zur 3D-Rekonstruktion unter Nebenbedingungen den Stand der Technik erweitern

    Exploratory search in time-oriented primary data

    Get PDF
    In a variety of research fields, primary data that describes scientific phenomena in an original condition is obtained. Time-oriented primary data, in particular, is an indispensable data type, derived from complex measurements depending on time. Today, time-oriented primary data is collected at rates that exceed the domain experts’ abilities to seek valuable information undiscovered in the data. It is widely accepted that the magnitudes of uninvestigated data will disclose tremendous knowledge in data-driven research, provided that domain experts are able to gain insight into the data. Domain experts involved in data-driven research urgently require analytical capabilities. In scientific practice, predominant activities are the generation and validation of hypotheses. In analytical terms, these activities are often expressed in confirmatory and exploratory data analysis. Ideally, analytical support would combine the strengths of both types of activities. Exploratory search (ES) is a concept that seamlessly includes information-seeking behaviors ranging from search to exploration. ES supports domain experts in both gaining an understanding of huge and potentially unknown data collections and the drill-down to relevant subsets, e.g., to validate hypotheses. As such, ES combines predominant tasks of domain experts applied to data-driven research. For the design of useful and usable ES systems (ESS), data scientists have to incorporate different sources of knowledge and technology. Of particular importance is the state-of-the-art in interactive data visualization and data analysis. Research in these factors is at heart of Information Visualization (IV) and Visual Analytics (VA). Approaches in IV and VA provide meaningful visualization and interaction designs, allowing domain experts to perform the information-seeking process in an effective and efficient way. Today, bestpractice ESS almost exclusively exist for textual data content, e.g., put into practice in digital libraries to facilitate the reuse of digital documents. For time-oriented primary data, ES mainly remains at a theoretical state. Motivation and Problem Statement. This thesis is motivated by two main assumptions. First, we expect that ES will have a tremendous impact on data-driven research for many research fields. In this thesis, we focus on time-oriented primary data, as a complex and important data type for data-driven research. Second, we assume that research conducted to IV and VA will particularly facilitate ES. For time-oriented primary data, however, novel concepts and techniques are required that enhance the design and the application of ESS. In particular, we observe a lack of methodological research in ESS for time-oriented primary data. In addition, the size, the complexity, and the quality of time-oriented primary data hampers the content-based access, as well as the design of visual interfaces for gaining an overview of the data content. Furthermore, the question arises how ESS can incorporate techniques for seeking relations between data content and metadata to foster data-driven research. Overarching challenges for data scientists are to create usable and useful designs, urgently requiring the involvement of the targeted user group and support techniques for choosing meaningful algorithmic models and model parameters. Throughout this thesis, we will resolve these challenges from conceptual, technical, and systemic perspectives. In turn, domain experts can benefit from novel ESS as a powerful analytical support to conduct data-driven research. Concepts for Exploratory Search Systems (Chapter 3). We postulate concepts for the ES in time-oriented primary data. Based on a survey of analysis tasks supported in IV and VA research, we present a comprehensive selection of tasks and techniques relevant for search and exploration activities. The assembly guides data scientists in the choice of meaningful techniques presented in IV and VA. Furthermore, we present a reference workflow for the design and the application of ESS for time-oriented primary data. The workflow divides the data processing and transformation process into four steps, and thus divides the complexity of the design space into manageable parts. In addition, the reference workflow describes how users can be involved in the design. The reference workflow is the framework for the technical contributions of this thesis. Visual-Interactive Preprocessing of Time-Oriented Primary Data (Chapter 4). We present a visual-interactive system that enables users to construct workflows for preprocessing time-oriented primary data. In this way, we introduce a means of providing content-based access. Based on a rich set of preprocessing routines, users can create individual solutions for data cleansing, normalization, segmentation, and other preprocessing tasks. In addition, the system supports the definition of time series descriptors and time series distance measures. Guidance concepts support users in assessing the workflow generalizability, which is important for large data sets. The execution of the workflows transforms time-oriented primary data into feature vectors, which can subsequently be used for downstream search and exploration techniques. We demonstrate the applicability of the system in usage scenarios and case studies. Content-Based Overviews (Chapter 5). We introduce novel guidelines and techniques for the design of contentbased overviews. The three key factors are the creation of meaningful data aggregates, the visual mapping of these aggregates into the visual space, and the view transformation providing layouts of these aggregates in the display space. For each of these steps, we characterize important visualization and interaction design parameters allowing the involvement of users. We introduce guidelines supporting data scientists in choosing meaningful solutions. In addition, we present novel visual-interactive quality assessment techniques enhancing the choice of algorithmic model and model parameters. Finally, we present visual interfaces enabling users to formulate visual queries of the time-oriented data content. In this way, we provide means of combining content-based exploration with content-based search. Relation Seeking Between Data Content and Metadata (Chapter 6). We present novel visual interfaces enabling domain experts to seek relations between data content and metadata. These interfaces can be integrated into ESS to bridge analytical gaps between the data content and attached metadata. In three different approaches, we focus on different types of relations and define algorithmic support to guide users towards most interesting relations. Furthermore, each of the three approaches comprises individual visualization and interaction designs, enabling users to explore both the data and the relations in an efficient and effective way. We demonstrate the applicability of our interfaces with usage scenarios, each conducted together with domain experts. The results confirm that our techniques are beneficial for seeking relations between data content and metadata, particularly for data-centered research. Case Studies - Exploratory Search Systems (Chapter 7). In two case studies, we put our concepts and techniques into practice. We present two ESS constructed in design studies with real users, and real ES tasks, and real timeoriented primary data collections. The web-based VisInfo ESS is a digital library system facilitating the visual access to time-oriented primary data content. A content-based overview enables users to explore large collections of time series measurements and serves as a baseline for content-based queries by example. In addition, VisInfo provides a visual interface for querying time oriented data content by sketch. A result visualization combines different views of the data content and metadata with faceted search functionality. The MotionExplorer ESS supports domain experts in human motion analysis. Two content-based overviews enhance the exploration of large collections of human motion capture data from two perspectives. MotionExplorer provides a search interface, allowing domain experts to query human motion sequences by example. Retrieval results are depicted in a visual-interactive view enabling the exploration of variations of human motions. Field study evaluations performed for both ESS confirm the applicability of the systems in the environment of the involved user groups. The systems yield a significant improvement of both the effectiveness and the efficiency in the day-to-day work of the domain experts. As such, both ESS demonstrate how large collections of time-oriented primary data can be reused to enhance data-centered research. In essence, our contributions cover the entire time series analysis process starting from accessing raw time-oriented primary data, processing and transforming time series data, to visual-interactive analysis of time series. We present visual search interfaces providing content-based access to time-oriented primary data. In a series of novel explorationsupport techniques, we facilitate both gaining an overview of large and complex time-oriented primary data collections and seeking relations between data content and metadata. Throughout this thesis, we introduce VA as a means of designing effective and efficient visual-interactive systems. Our VA techniques empower data scientists to choose appropriate models and model parameters, as well as to involve users in the design. With both principles, we support the design of usable and useful interfaces which can be included into ESS. In this way, our contributions bridge the gap between search systems requiring exploration support and exploratory data analysis systems requiring visual querying capability. In the ESS presented in two case studies, we prove that our techniques and systems support data-driven research in an efficient and effective way
    corecore