Prediction-based methods for teleoperation across delayed networks

The remote nature of telepresence scenarios can be seen as a strongpoint and also as a weakness. Although it enables the remote control of robots in dangerous or inaccessible environments, it necessarily involves some kind of communication mechanism for the transmission of control signals. This communication mechanism necessarily involves adverse network effects such as delay. Three mechanisms aimed at improving the effects of network delay are presented in this paper: (1) Motion prediction to partially compensate for network delays, (2) force prediction to learn a local force model, thereby reducing dependency on delayed force signals, and (3) haptic data compression to reduce the required bandwidth of high frequency data. The utilized motion prediction scheme was shown to improve operator performance, but had no influence on operator immersion. The force prediction provided haptic feedback through synchronous forces from the local model, thereby stabilizing the control loop. The developed haptic data compression scheme reduced the number of packets sent across the network by 90%, while improving the quality of the haptic feedback.     

Dynamic Multiple Swarms in Multiobjective Particle Swarm Optimization

A multiple-swarm multiobjective particle swarm optimization (PSO) algorithm, named dynamic multiple swarms in multiobjective PSO, is proposed in which the number of swarms is adaptively adjusted throughout the search process via the proposed dynamic swarm strategy. The strategy allocates an appropriate number of swarms as required to support convergence and diversity criteria among the swarms. Additional novel designs include a PSO updating mechanism to better manage the communication within a swarm and among swarms and an objective space compression and expansion strategy to progressively exploit the objective space during the search process. Comparative study shows that the performance of the proposed algorithm is competitive in comparison to the selected algorithms on standard benchmark problems. In particular, when dealing with test problems with multiple local Pareto fronts, the proposed algorithm is much less computationally demanding. Sensitivity analysis indicates that the proposed algorithm is insensitive to most of the user-specified design parameters.     

Rectification of legibility distance in a driving simulator

Visual differences lead to differences in the legibility distances of traffic signs between driving simulators and real road environments. To ensure that the legibility distance in a simulator is similar to that in the real world, this study proposes a theoretical equation for predicting legibility distance and a simple algorithm for determining the magnifying power of a traffic sign for a display system in a simulator. Experiments of traffic sign recognition using a simulator were conducted under quasi-static and dynamic driving conditions. On-road tests were also carried out under quasi-static and dynamic driving conditions. Thirty healthy and non-disabled volunteers were recruited. The experimental results showed that the proposed theoretical equation for predicting legibility distance and the simple algorithm for determining the magnifying power of traffic signs reduced the difference in legibility distances between the simulator and real road environment under quasi-static and dynamic driving conditions.     

Engineering analysis of biological variables: an example of blood pressure over 1 day

Almost all variables in biology are nonstationarily stochastic. For these variables, the conventional tools leave us a feeling that some valuable information is thrown away and that a complex phenomenon is presented imprecisely. Here, we apply recent advances initially made in the study of ocean waves to study the blood pressure waves in the lung. We note first that, in a long wave train, the handling of the local mean is of predominant importance. It is shown that a signal can be described by a sum of a series of intrinsic mode functions, each of which has zero local mean at all times. The process of deriving this series is called the "empirical mode decomposition method." Conventionally, Fourier analysis represents the data by sine and cosine functions, but no instantaneous frequency can be defined. In the new way, the data are represented by intrinsic mode functions, to which Hilbert transform can be used. Titchmarsh [Titchmarsh, E. C. (1948) Introduction to the Theory of Fourier Integrals (Oxford Univ. Press, Oxford)] has shown that a signal and i times its Hilbert transform together define a complex variable. From that complex variable, the instantaneous frequency, instantaneous amplitude, Hilbert spectrum, and marginal Hilbert spectrum have been defined. In addition, the Gumbel extreme-value statistics are applied. We present all of these features of the blood pressure records here for the reader to see how they look. In the future, we have to learn how these features change with disease or interventions.     

Wetting of Rough Walls

Quenched geometric disorder of a wall delimiting a spectator phase can have dramatic effects on the nature of critical wetting transitions. We consider self-affine walls in 2D with roughness exponent _W. Transfer matrix results for directed interfacial models with short-range interactions suggest that wetting turns first-order as soon as _W exceeds ₀, the anisotropy index of interface fluctuations in the bulk. Discontinuous interface depinning is best identified by a peculiar two-peak structure in the statistical distributions of wall–interface contacts obtained by sampling over disorder. On the other hand, for _W<₀ wetting remains continuous, most plausibly in the same universality class as with flat walls. This occurs both with ordered (₀ = 1/2) and with bond-disordered (₀ = 2/3) bulk. A precise location of the thresholds at _W = ₀ can be argued on the basis of an analysis of different terms in the interfacial free energy. This analysis elucidates the peculiar role played by the intrinsic interfacial roughness and suggests extensions of the results to 3D and to long-range substrate forces.     

Costimulatory molecule-deficient dendritic cell progenitors (MHC class II+, CD80dim, CD86-) prolong cardiac allograft survival in nonimmunosuppressed recipients

We have shown previously that granulocyte-macrophage colony-stimulating factor-stimulated mouse bone marrow-derived MHC class II+ dendritic cell (DC) progenitors that are deficient in cell surface expression of the costimulatory molecules B7-1 (CD80) and B7-2 (CD86) can induce alloantigen-specific T-cell anergy in vitro. To test the in vivo relevance of these findings, 2 x 10(6) B10 (H2b) mouse bone marrow-derived DC progenitors (NLDC 145+, MHC class II+, B7-1dim, B7-2-/dim) that induced T-cell hyporesponsiveness in vitro were injected systemically into normal C3H (H2k) recipients. Seven days later, the mice received heterotopic heart transplants from B10 donors. No immunosuppressive treatment was given. Median graft survival time was prolonged significantly from 9.5 to 22 days. Median graft survival time was also increased, although to a lesser extent (16.5 days), in mice that received third-party (BALB/c; H2d) DC progenitors. Ex vivo analysis of host T-cell responses to donor and third-party alloantigens 7 days after the injection of DC progenitors (the time of heart transplant) revealed minimal anti-donor mixed leukocyte reaction and cytotoxic T lymphocyte reactivity. These responses were reduced substantially compared with those of spleen cells from animals pretreated with "mature" granulocyte-macrophage colony-stimulating factor + interleukin-4-stimulated DC (MHC class IIbright, B7-1+, B7-2bright), many of which rejected their heart grafts in an accelerated fashion. Among the injected donor MHC class II+ DC progenitors that migrated to recipient secondary lymphoid tissue were cells that appeared to have up-regulated cell surface B7-1 and B7-2 molecule expression. This observation may explain, at least in part, the temporary or unstable nature of the hyporesponsiveness induced by the DC progenitors in nonimmunosuppressed recipients.     

Trust Management and Admission Control for Host-Based Collaborative Intrusion Detection

The accuracy of detecting an intrusion within a network of intrusion detection systems (IDSes) depends on the efficiency of collaboration between member IDSes. The security itself within this network is an additional concern that needs to be addressed. In this paper, we present a trust-based framework for secure and effective collaboration within an intrusion detection network (IDN). In particular, we design a trust model that allows each IDS to evaluate the trustworthiness of other IDSes based on its personal experience. We also propose an admission control algorithm for the IDS to manage the acquaintances it approaches for advice about intrusions. We discuss the effectiveness of our approach in protecting the IDN against common attacks. Additionally, experimental results demonstrate that our system yields significant improvement in detecting intrusions. The trust model further improves the robustness of the collaborative system against malicious attacks. The experimental results also support that our admission control algorithm is effective and fair, and creates incentives for collaboration.     

Performance modeling,real-time dispatching and simulation of wafer fabrication systems using timed extended object-oriented Petri nets

Semiconductor wafer fabrication system (SWFS) is the most complex and capital-intensive phase in the entire semiconductor manufacturing cycle. With characteristics of re-entrant processing routes, equipment uncertainty, product diversity and improving technologies, great challenges are presented in SWFS’s modeling, scheduling and simulation. To implement efficient production control, this paper provides a timed extended object-oriented Petri nets (TEOPNs) approach to performance modeling, real-timed dispatching and simulation of SWFSs. The TEOPNs models are constructed in a hierarchy to accord with the real-world SWFS’s organization, and a new type of signal place is added into the TEOPNs to respond the dynamic states of all processing facilities. A novel autonomy and coordination-based real-time dispatching mechanism (A&C-RDM) is developed in this paper, which executes under the support of the TEOPNs-based hybrid real-time dispatching control system (HRDCS). Owning to the ability of gathering dynamic real-time information of all production facilities and WIP products, the HRDCS can make adaptive dispatching decisions according to the local and global real-time processing status. Two sets of key elements of real-time dispatching, i.e. the state thresholds and dispatching rules, are defined in the HRDCS so that the A&C-RDM can integrate different types of dispatching rules. A set of simulation experiments prove the efficiency of the proposed modeling and dispatching algorithm. In summary, the proposed TEOPNs, HRDCS and A&C-RDM form the cornerstones of a real-time dispatching simulation prototype of SWFS, and the work described in this paper carries out an advanced integrated “modeling–dispatching–simulation” methodology.     

Qualitative Scene Interpretation Using Planar Surfaces

Our aim is to provide an autonomous vehicle moving into an indoor environment with a visual system to perform a qualitative 3D structure reconstruction of the surrounding environment by recovering the different planar surfaces present in the observed scene.The method is based on qualitative detection of planar surfaces by using projective invariant constraints without the use of depth estimates. The goal is achieved by analyzing two images acquired by observing the scene from two different points of view. The method can be applied to both stereo images and motion images.Our method recovers planar surfaces by clustering high variance interest points whose cross ratio measurements are preserved in two different perspective projections. Once interest points are extracted from each image, the clustering process requires to grouping corresponding points by preserving the cross ratio measurements.We solve the twofold problem of finding corresponding points and grouping the coplanar ones through a global optimization approach based on matching of high relational graphs and clustering on the corresponding association graph through a relaxation labeling algorithm.Through our experimental tests, we found the method to be very fast to converge to a solution, showing how higher order interactions, instead to giving rise to a more complex problem, help to speed-up the optimization process and to reach at same time good results.