Distributed boundary coverage with a team of networked miniature robots using a robust market-based algorithm

We study distributed boundary coverage of known environments using a team of miniature robots. Distributed boundary coverage is an instance of the multi-robot task-allocation problem and has applications in inspection, cleaning, and painting among others. The proposed algorithm is robust to sensor and actuator noise, failure of individual robots, and communication loss. We use a market-based algorithm with known lower bounds on the performance to allocate the environmental objects of interest among the team of robots. The coverage time for systems subject to sensor and actuator noise is significantly shortended by on-line task re-allocation. The complexity and convergence properties of the algorithm are formally analyzed. The system performance is systematically analyzed at two different microscopic modeling levels, using agent-based, discrete-event and module-based, realistic simulators. Finally, results obtained in simulation are validated using a team of Alice miniature robots involved in a distributed inspection case study.     

Adaptive fuzzy-neural-network control for maglev transportation system

A magnetic-levitation (maglev) transportation system including levitation and propulsion control is a subject of considerable scientific interest because of highly nonlinear and unstable behaviors. In this paper, the dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is developed first. Then, a model-based sliding-mode control (SMC) strategy is introduced. In order to alleviate chattering phenomena caused by the inappropriate selection of uncertainty bound, a simple bound estimation algorithm is embedded in the SMC strategy to form an adaptive sliding-mode control (ASMC) scheme. However, this estimation algorithm is always a positive value so that tracking errors introduced by any uncertainty will cause the estimated bound increase even to infinity with time. Therefore, it further designs an adaptive fuzzy-neural-network control (AFNNC) scheme by imitating the SMC strategy for the maglev transportation system. In the model-free AFNNC, online learning algorithms are designed to cope with the problem of chattering phenomena caused by the sign action in SMC design, and to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The outputs of the AFNNC scheme can be directly supplied to the electromagnets and LIM without complicated control transformations for relaxing strict constrains in conventional model-based control methodologies. The effectiveness of the proposed control schemes for the maglev transportation system is verified by numerical simulations, and the superiority of the AFNNC scheme is indicated in comparison with the SMC and ASMC strategies.     

Effective visualization of short routes

In this work we develop a new alternative to conventional maps for visualization of relatively short paths as they are frequently encountered in hotels, resorts or museums. Our approach is based on a warped rendering of a 3D model of the environment such that the visualized path appears to be straight even though it may contain several junctions. This has the advantage that the beholder of the image gains a realistic impression of the surroundings along the way which makes it easy to retrace the route in practice. We give an intuitive method for generation of such images and present results from user studies undertaken to evaluate the benefit of the warped images for orientation in unknown environments.     

Inside the adaptive enterprise: an information technology capabilities perspective on business process agility

Recent innovations in utility computing, web services, and service-oriented architectures, combined with a growing array of IT skills, have improved firms’ ability to be more agile in responding to change. Using the resource-based view of the firm, prior research suggests that IT resources, in isolation, are unlikely to yield superior performance and so as firms try to boost their agility, the question becomes how to configure IT resources to prepare for, or react to, change. In this paper, we posit that managerial IT capabilities based on IT-business partnerships, strategic planning, and ex-post IT project analysis lead to the development of technical IT capabilities associated with a flexible IT infrastructure which in turn drives agility or a firm’s ability to react to change in its products and markets. Using data from matched surveys of IT and business executives in 241 firms, we find that managerial and technical capabilities affect agility. In further testing, we reveal that in a stable setting, technical IT capabilities are more important to agility than managerial IT capabilities, while in a dynamic setting, the opposite is true. Thus, for firms operating in volatile markets, effective models of managerial IT governance are essential for delivering superior agility or adaptiveness.

The aDORe federation architecture: digital repositories at scale

The need to federate repositories emerges in two distinctive scenarios. In one scenario, scalability-related problems in the operation of a repository reach a point beyond which continued service requires parallelization and hence federation of the repository infrastructure. In the other scenario, multiple distributed repositories manage collections of interest to certain communities or applications, and federation is an approach to present a unified perspective across these repositories. The high-level, 3-Tier aDORe federation architecture can be used as a guideline to federate repositories in both cases. This paper describes the architecture, consisting of core interfaces for federated repositories in Tier-1, two shared infrastructure components in Tier-2, and a single-point of access to the federation in Tier-3. The paper also illustrates two large-scale deployments of the aDORe federation architecture: the aDORe Archive repository (over 100,000,000 digital objects) at the Los Alamos National Laboratory and the Ghent University Image Repository federation (multiple terabytes of image files).     

A Secure Grid Medical Data Manager Interfaced to the gLite Middleware

The medical community is producing and manipulating a tremendous volume of digital data for which computerized archiving, processing and analysis is needed. Grid infrastructures are promising for dealing with challenges arising in computerized medicine but the manipulation of medical data on such infrastructures faces both the problem of interconnecting medical information systems to Grid middlewares and of preserving patients’ privacy in a wide and distributed multi-user system. These constraints are often limiting the use of Grids for manipulating sensitive medical data. This paper describes our design of a medical data management system taking advantage of the advanced gLite data management services, developed in the context of the EGEE project, to fulfill the stringent needs of the medical community. It ensures medical data protection through strict data access control, anonymization and encryption. The multi-level access control provides the flexibility needed for implementing complex medical use-cases. Data anonymization prevents the exposure of most sensitive data to unauthorized users, and data encryption guarantees data protection even when it is stored at remote sites. Moreover, the developed prototype provides a Grid storage resource manager (SRM) interface to standard medical DICOM servers thereby enabling transparent access to medical data without interfering with medical practice.     

Food vacuole proteome of the malarial parasite Plasmodium falciparum

The Plasmodium falciparum food vacuole (FV) is a lysosome-like organelle where erythrocyte hemoglobin digestion occurs. It is a favorite target in the development of antimalarials. We have used a tandem mass spectrometry approach to investigate the proteome of an FV-enriched fraction and identified 116 proteins. The electron microscopy analysis and the Western blot data showed that the major component of the fraction was the FV and, as expected, the majority of previously known FV markers were recovered. Of particular interest, several proteins involved in vesicle-mediated trafficking were identified, which are likely to play a key role in FV biogenesis and/or FV protein trafficking. Recovery of parasite surface proteins lends support to the cytostomal pathway of hemoglobin ingestion as a FV trafficking route. We have identified 32 proteins described as hypothetical in the databases. This insight into FV protein content provides new clues towards understanding the biological function of this organelle in P. falciparum.     

Space-time adaptation for patch-based image sequence restoration

We present a novel space-time patch-based method for image sequence restoration. We propose an adaptive statistical estimation framework based on the local analysis of the bias-variance trade-off. At each pixel, the space-time neighborhood is adapted to improve the performance of the proposed patch-based estimator. The proposed method is unsupervised and requires no motion estimation. Nevertheless, it can also be combined with motion estimation to cope with very large displacements due to camera motion. Experiments show that this method is able to drastically improve the quality of highly corrupted image sequences. Quantitative evaluations on standard artificially noise-corrupted image sequences demonstrate that our method outperforms other recent competitive methods. We also report convincing results on real noisy image sequences     

Measuring progress in Premo order-verification

Since verification of computational simulation codes requires significant resources, the ability to measure progress in verification is critical to assess whether resources are being applied appropriately. Additionally, potential users need to know what fraction of the software has been order-verified. In this study, the procedures and progress measures presented by Knupp et al. (Measuring progress order-verification within software development projects. Engineering with Computers, appears in this issue, 2007) are demonstrated on the Premo software, which simulates compressible aerodynamics through and around general geometries. Premo was selected for this demonstration because extensive order-verification tests have been previously performed, yet no systematic effort has been made to assess test-suite completeness or progress. This effort was performed to identify the practical issues encountered when attempting to apply the ideas by Knupp (Measuring progress order-verification within software development projects. Engineering with Computers, appears in this issue, 2007) to existing production-quality software. In this work, a non-specific order-verification exercise is considered, as opposed to an application-specific order-verification exercise, since past and present Premo order-verification efforts have been motivated by the need to verify all of the code, rather than portions relevant for specific applications. Constructing an order-verification test suite that verifies the order of accuracy of all the code capabilities is a major step in measuring progress. A practical approach to test-suite construction is described that helps create a complete test suite through a combination of coarse-grain code coverage, input-keyword inspection, discretization-algorithm documentation, and expert knowledge. Some of the difficulties and issues encountered during the construction of the test suite are described, along with recommendations on how to deal with them. Once the test suite is constructed, the progress measures proposed by Knupp (Measuring progress order-verification within software development projects. Engineering with Computers, appears in this issue, 2007) can be evaluated and used to reconstruct the history of progress in Premo verification over the past several years. Gaps in Premo verification are identified and indicate future directions for making progress. Additionally, a measure of Premo verification fitness is computed for selected applications commonly simulated in the aerospace industry. It is hoped that this demonstration will provide a practical example for other software-development groups in measuring their own verification progress. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed-Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under Contract DE-AC04-94AL85000.

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Modeling expert problem solving in a game of chance: a Yahtzee© case study

Although developments on software agents have led to useful applications in automation of routine tasks such as electronic mail filtering, there is a scarcity of research that empirically evaluates the performance of a software agent versus that of a human reasoner, whose problem-solving capabilities the agent embodies. In the context of a game of a chance, namely Yahtzee©, we identified strategies deployed by expert human reasoners and developed a decision tree for agent development. This paper describes the computer implementation of the Yahtzee game as well as the software agent. It also presents a comparison of the performance of humans versus an automated agent. Results indicate that, in this context, the software agent embodies human expertise at a high level of fidelity.