Small networks of polarized splicing processors are universal

In this paper, we consider the computational power of a new variant of networks of splicing processors in which each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined (negative, neutral, positive), the polarization of data is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that networks of polarized splicing processors (NPSP) of size 2 are computationally complete, which immediately settles the question of designing computationally complete NPSPs of minimal size. With two more nodes we can simulate every nondeterministic Turing machine without increasing the time complexity. Particularly, we prove that NPSP of size 4 can accept all languages in NP in polynomial time. Furthermore, another computational model that is universal, namely the 2-tag system, can be simulated by NPSP of size 3 preserving the time complexity. All these results can be obtained with NPSPs with valuations in the set \(\{-1,0,1\}\) as well. We finally show that Turing machines can simulate a variant of NPSPs and discuss the time complexity of this simulation.     

SnapPaste: an interactive technique for easy mesh composition

Editing and manipulation of existing 3D geometric objects are a means to extend their repertoire and promote their availability. Traditionally, tools to compose or manipulate objects defined by 3D meshes are in the realm of artists and experts. In this paper, we introduce a simple and effective user interface for easy composition of 3D mesh-parts for non-professionals. Our technique borrows from the cut-and-paste paradigm where a user can cut parts out of existing objects and paste them onto others to create new designs. To assist the user attach objects to each other in a quick and simple manner, many applications in computer graphics support the notion of “snapping”. Similarly, our tool allows the user to loosely drag one mesh part onto another with an overlap, and lets the system snap them together in a graceful manner. Snapping is accomplished using our Soft-ICP algorithm which replaces the global transformation in the ICP algorithm with a set of point-wise locally supported transformations. The technique enhances registration with a set of rigid to elastic transformations that account for simultaneous global positioning and local blending of the objects. For completeness of our framework, we present an additional simple mesh-cutting tool, adapting the graph-cut algorithm to meshes.     

Energy Levels of “Hydrogen Atom” in Discrete Time Dynamics

We analyze dynamical consequences of a conjecture that there exists a fundamental (indivisible) quant of time. In particular we study the problem of discrete energy levels of hydrogen atom. We are able to reconstruct potential which in discrete time formalism leads to energy levels of unperturbed hydrogen atom. We also consider linear energy levels of quantum harmonic oscillator and show how they are produced in the discrete time formalism. More generally, we show that in discrete time formalism finite motion in central potential leads to discrete energy spectrum, the property which is common for quantum mechanical theory. Thus deterministic (but discrete time!) dynamics is compatible with discrete energy levels.     

Morphological hat-transform scale spaces and their use in pattern classification

In this paper we present a multi-scale method based on mathematical morphology which can successfully be used in pattern classification tasks. A connected operator similar to the morphological hat-transform is defined, and two scale-space representations are built. The most important features are extracted from the scale spaces by unsupervised cluster analysis, and the resulting pattern vectors provide the input of a decision tree classifier. We report classification results obtained using contour features, texture features, and a combination of these. The method has been tested on two large sets, a database of diatom images and a set of images from the Brodatz texture database. For the diatom images, the method is applied twice, once on the curvature of the outline (contour), and once on the grey-scale image itself.     

SMOS first data analysis for sea surface salinity determination

Soil Moisture and Ocean Salinity (SMOS), launched on 2 November 2009, is the first satellite mission addressing sea surface salinity (SSS) measurement from space. Its unique payload is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), a new two-dimensional interferometer designed by the European Space Agency (ESA) and operating at the L-band frequency. This article presents a summary of SSS retrieval from SMOS observations and shows initial results obtained one year after launch. These results are encouraging, but also indicate that further improvements at various data processing levels are needed and hence are currently under investigation.     

Synergistic verification and validation of systems and software engineering models

In this paper, we present a unified approach for the verification and validation of software and systems engineering design models expressed in UML 2.0 and SysML 1.0. The approach is based on three well-established techniques, namely formal analysis, programme analysis and software engineering (SwE) techniques. More precisely, our contribution consists of the synergistic combination of model checking, static analysis and SwE metrics that enables the automatic and efficient assessment of design models from static and dynamic perspectives. Additionally, we present the design and implementation of an automated computer-aided assessing framework integrating the proposed approach. Moreover, we discuss the related technical details and the underlying synergism. Finally, we illustrate the proposed approach by assessing a design case study that is composed of state machine and sequence diagrams.     

Application of a new algorithm using Doppler information to retrieve complex wind fields over the Black Sea from ENVISAT SAR images

Several algorithms have been proposed to retrieve near-surface wind fields from C-band synthetic aperture radar (SAR) images acquired over the ocean. They mainly differ in the way they retrieve the wind direction. Conventionally, the wind direction is taken from atmospheric models or is extracted from the linear features sometimes visible in SAR images. Recently, a new wind retrieval algorithm has been proposed, which also includes the Doppler shift induced by motions of the sea surface. In this article, we apply three wind retrieval algorithms, including the one using Doppler information, to three complex wind events encountered over the Black Sea and compare the SAR-derived wind fields with model wind fields calculated using the high-resolution weather research and forecasting (WRF) model. It is shown that the new algorithm is very efficient in resolving the 180° ambiguity in the wind direction, which is often a problem in the streak-based wind retrieval algorithms. However, the Doppler-based algorithm only yields good results for wind directions that have a significant component in the look direction of the SAR antenna. Furthermore, it is dependent on good separation of the contributions to the Doppler shift induced by surface currents and wind-related effects (wind drift and wind-sea components of the ocean wave spectrum). We conclude that an optimum wind retrieval algorithm should consist of a combination of the algorithms based on linear features and Doppler information.     

Robustness and coordination in voltage control of large-scale power systems

In this paper it is shown how the robustness and the coordination of the voltage regulation actions for the transmission grid can be improved. Simpler approaches which ensure higher robustness and performances can be used if the control objectives are pursued at two hierarchical levels of different nature. Also, this is a way to coordinate means of control of different nature with a sufficient time and methodological separation in order to avoid negative mutual influence. At the first level, called the static level, optimal reachable set-points are computed for the second control level, called the dynamic level. The static level can be combined with the shunt reactive power compensation. The system non-linearities are taken into account at the static level while the dynamic level is a linear robust predictive control which takes into account the presence of asynchronous transmission delays. The predictive control strategy is based on the separation property; the output delays are handled using an original steady-state Kalman predictor of order equal to the length of the state of the system without delays. The robustness is improved at the dynamic level against uncertain delays, parametric uncertainties (like, e.g., moderate topological errors and load variations not taken into account in the control model) and unmodelled dynamics. The two-level organisation of the control allows, on one hand, to take into account the important evolutions of the system (like, e.g., large and known topological and load changes) and, on the other hand, a coherent hybrid reactive power control: the switched control of the grid shunt compensation for the reactive power is done at the static level while the reactive power injection provided by the generators is continuously handled at the dynamic level. This is a theoretical analysis of how concepts of automatic control and voltage regulation of power systems can be combined. To be applied as a control scheme, the results presented here should be adapted to a specific context (particularities of the power system and of the organisation of the power industry). They can be used, eventually in conjunction with other improvements, to existing horizontally-organised interconnections (in which all generators of a controlled region can be easily managed since owned by the same utility) or to face specific requirements of moving to the open access in the electric power industry like, e.g., tolerating simplified models in order to cover larger regions, taking into account the interaction between regions, recalibrating set-points, assisting human operator when necessary or facilitating implementation of mechanisms for the management of the reactive power based on price signals.     

3D Motion Completion in Crowded Scenes

Crowded motions refer to multiple objects moving around and interacting such as crowds, pedestrians and etc. We capture crowded scenes using a depth scanner at video frame rates. Thus, our input is a set of depth frames which sample the scene over time. Processing such data is challenging as it is highly unorganized, with large spatio‐temporal holes due to many occlusions. As no correspondence is given, locally tracking 3D points across frames is hard due to noise and missing regions. Furthermore global segmentation and motion completion in presence of large occlusions is ambiguous and hard to predict. Our algorithm utilizes Gestalt principles of common fate and good continuity to compute motion tracking and completion respectively. Our technique does not assume any pre‐given markers or motion template priors. Our key‐idea is to reduce the motion completion problem to a 1D curve fitting and matching problem which can be solved efficiently using a global optimization scheme. We demonstrate our segmentation and completion method on a variety of synthetic and real world crowded scanned scenes.