A geometrical nonlinear eccentric 3D-beam element with arbitrary cross-sections

In this paper a finite element formulation of eccentric space curved beams with arbitrary cross-sections is derived. Based on a Timoshenko beam kinematic, the strain measures are derived by exploitation of the Green-Lagrangean strain tensor. Thus, the formulation is conformed with existing nonlinear shell theories. Finite rotations are described by orthogonal transformations of the basis systems from the initial to the current configuration. Since for arbitrary cross-sections the centroid and shear center do not coincide, torsion bending coupling occurs in the linear as well as in the finite deformation case. The linearization of the boundary value formulation leads to a symmetric bilinear form for conservative loads. The resulting finite element model is characterized by 6 degrees of freedom at the nodes and therefore is fully compatible with existing shell elements. Since the reference curve lies arbitrarily to the line of centroids, the element can be used to model eccentric stiffener of shells with arbitrary cross-sections.     

Multi-Level Parallelism for the Cardiac Bidomain Equations

Cardiovascular diseases are associated with high mortality rates in the globe. The development of new drugs, new medical equipment and non-invasive techniques for the heart demand multidisciplinary efforts towards the characterization of cardiac anatomy and function from the molecular to the organ level. Computational modeling has demonstrated to be a useful tool for the investigation and comprehension of the complex biophysical processes that underlie cardiac function. The set of Bidomain equations is currently one of the most complete mathematical models for simulating the electrical activity in cardiac tissue. Unfortunately, large scale simulations, such as those resulting from the discretization of an entire heart, remain a computational challenge. In order to reduce simulation execution times, parallel implementations have traditionally exploited data parallelism via numerical schemes based on domain-decomposition. However, it has been verified that the parallel efficiency of these implementations severely degrades as the number of processors increases. In this work we propose and implement a new parallel algorithm for the solution of cardiac models. By relaxing the coherence of the execution, a new level of parallelism could be identified and exploited: pipelining. A synchronous parallel algorithm that uses both pipelining and data decomposition techniques was implemented and used the MPI library for communication. Numerical tests were performed in two different cluster configurations. Our preliminary results indicated that the proposed algorithm is able to increase the parallel efficiency up to 20% on an 8-core cluster. On a 32-core cluster the multi-level algorithm was 1.7 times faster than the traditional domain decomposition algorithm. In addition, the numerical precision was kept under control (relative errors under 6%) when the relaxed coherence execution was adopted.     

Making Augmented Reality Practical on Mobile Phones, Part 1

Since 2003, the authors have been developing three generations of a software framework for handheld augmented reality (AR), targeting mobile phones. This article is the first part of a discussion on the experiences and design decisions that resulted in the current software framework, Studierstube ES (Embedded System). The authors describe the restrictions of the mobile phone platform and a software architecture that allows fast development of mobile phone AR applications.     

Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000

The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) has been identified as one of several key satellite-derived biophysical datasets. With multiple global FAPAR datasets now available and a lack of in-situ measurements and comparison studies in the far north, this study attempts to provide the reader with an indication of the performance of four global FAPAR datasets (MODIS, CYCLOPES, JRC and GLOBCARBON) over Northern Eurasia in the year 2000 via comparison. Within the year 2000 growing season, both the MODIS and CYCLOPES datasets recorded on average similar but substantially higher values than the JRC and GLOBCARBON datasets. Among three of the four datasets, a high level of agreement in deciduous broadleaf forests and croplands was observed. Largest disagreement occurred among needleleaf forests and grassland/shrubland. Potential reasons for discrepancies among the datasets include different retrieval methods, use of LAI and land cover, snow effects and others. Findings from this study and other published results suggest that overall, JRC best captures FAPAR over northern Eurasia in the year 2000. However, when considering individual landcover types, any one or more of the four products may be suitable. There exists a real need for more in-situ measurements in this region — the lack of such measurements makes evaluation extremely difficult. It appears that areas north of 60° urgently require further investigation.     

Detecting unknown coal fires: synergy of automated coal fire risk area delineation and improved thermal anomaly extraction

This paper presents two complementing algorithms for remote sensing based coal fire research and the results derived thereof. Both are applicable on Landsat, ASTER and MODIS data. The first algorithm automatically delineates coal fire risk areas from multispectral satellite data. The second automatically extracts local coal fire related thermal anomalies from thermal data. The presented methods aim at the automated, unbiased retrieval of coal fire related information. The delineation of coal fire risk areas is based on land cover extraction through a knowledge based spectral test sequence. This sequence has been proven to extract coal fire risk areas not only in time series of the investigated study areas in China, but also in transfer regions of India and Australia. The algorithm for the extraction of thermal anomalies is based on a moving window approach analysing sub‐window histograms. It allows the extraction of thermally anomalous pixels with regard to their surrounding background and therefore supports the extraction of very subtle, local thermal anomalies of different temperature. It thus shows clear advantages to anomaly extraction via simple thresholding techniques. Since the thermal algorithm also does extract thermal anomalies, which are not related to coal fires, the derived risk areas can help to eliminate false alarms. Overall, 50% of anomalies derived from night‐time data can be rejected, while even 80% of all anomalies extracted from daytime data are likely to be false alarms. However, detection rates are very good. Over 80% of existing coal fires in our first study area were extracted correctly and all fires (100%) in study area two were extracted from Landsat data. In MODIS data extraction depends on coal fire types and reaches 80% of all fires in our study area with hot coal fires of large spatial extent, while in another region with smaller and ‘colder’ coal fires only the hottest ones (below 20%) can be extracted correctly. The success of the synergetic application of the two methods has been proven through our detection of so far unknown coal fires in Landsat 7 ETM+ remote sensing data. This is the first time in coal fire research that unknown coal fires were detected in satellite remote sensing data exclusively and were validated later subsequently during in situ field checks.     

Perci: Pervasive Service Interaction with the Internet of Things

The advancement of ubiquitous computing technologies has greatly improved the availability of digital resources in the real world. Here, the authors investigate mobile interaction with tagged, everyday objects and associated information that's based on the Internet of Things and its technologies. Their framework for integrating Web services and mobile interaction with physical objects relies on information typing to increase interoperability. Two prototypes for mobile interaction with smart posters build upon this framework to realize multi-tag interaction with physical user interfaces. The authors' evaluation identifies usability issues regarding the design of physical mobile interactions, interfaces, and applications.     

A Linear Time Algorithm for the Arc Disjoint Menger Problem in Planar Directed Graphs

Given a graph G=(V,E) and two vertices s,t ∈ V , s\neq t , the Menger problem is to find a maximum number of disjoint paths connecting s and t . Depending on whether the input graph is directed or not, and what kind of disjointness criterion is demanded, this general formulation is specialized to the directed or undirected vertex, and the edge or arc disjoint Menger problem, respectively. For planar graphs the edge disjoint Menger problem has been solved to optimality [W2], while the fastest algorithm for the arc disjoint version is Weihe's general maximum flow algorithm for planar networks [W1], which has running time \bf O (|V| log |V|) . Here we present a linear time, i.e., asymptotically optimal, algorithm for the arc disjoint version in planar directed graphs. Received August 1997; revised January 1999.     

Selection of knowledge acquisition techniques based upon the problem domain characteristics of production and operations management expert systems

The application of expert systems to various problem domains in business has grown steadily since their introduction. Regardless of the chosen method of development, the most commonly cited problems in developing these systems are the unavailability of both the experts and knowledge engineers and difficulties with the process of acquiring knowledge from domain experts. Within the field of artificial intelligence, this has been called the 'knowledge acquisition' problem and has been identified as the greatest bottleneck in the expert system development process. Simply stated, the problem is how to acquire the specific knowledge for a well-defined problem domain efficiently from one or more experts and represent it in the appropriate computer format. Given the 'paradox of expertise', the experts have often proceduralized their knowledge to the point that they have difficulty in explaining exactly what they know and how they know it. However, empirical research in the field of expert systems reveals that certain knowledge acquisition techniques are significantly more efficient than others in helping to extract certain types of knowledge within specific problem domains. In this paper we present a mapping between these empirical studies and a generic taxonomy of expert system problem domains. In so doing, certain knowledge acquisition techniques can be prescribed based on the problem domain characteristics. With the production and operations management (P/OM) field as the pilot area for the current study, we first examine the range of problem domains and suggest a mapping of P/OM tasks to a generic taxonomy of problem domains. We then describe the most prominent knowledge acquisition techniques. Based on the examination of the existing empirical knowledge acquisition research, we present how the empirical work can be used to provide guidance to developers of expert systems in the field of P/OM.     

Virtual Reality Interfaces for Visualization and Control of Remote Vehicles

The Autonomy and Robotics Area (ARA) at NASA Ames Research Center has investigated the use of various types of Virtual Reality-based operator interfaces to remotely control complex robotic mechanisms. In this paper, we describe the major accomplishments and technology applications of the ARA in this area, and highlight the advantages and issues related to this technology.     

Work Practices Surrounding PACS: The Politics of Space in Hospitals

This paper uses a case study of collaborative work practices within the radiology department of a hospital, for examining the usefulness of spatial approaches to collaboration. It takes a socio-political perspective on understanding the shaping effects of spatial arrangements on work practices, and seeks to identify some of the key CSCW issues that can be addressed in spatial terms. We analyse the spatial settings or layers (physical, digital and auditory) within which work takes place, and the qualities of connections between them, examining in how far they support (professional) boundaries or help maintain a sense of context. Guiding themes are the relationships between space and the visibility of work, and how to accommodate social world needs through spatial arrangements.