Chunk-lattices for verb reordering in Arabic–English statistical machine translation

Syntactic disfluencies in Arabic-to-English phrase-based SMT output are often due to incorrect verb reordering in Verb–Subject–Object sentences. As a solution, we propose a chunk-based reordering technique to automatically displace clause-initial verbs in the Arabic side of a word-aligned parallel corpus. This method is used to preprocess the training data, and to collect statistics about verb movements. From this analysis we build specific verb reordering lattices on the test sentences before decoding, and test different lattice-weighting schemes. Finally, we train a feature-rich discriminative model to predict likely verb reorderings for a given Arabic sentence. The model scores are used to prune the reordering lattice, leading to better word reordering at decoding time. The application of our reordering methods to the training and test data results in consistent improvements on the NIST-MT 2009 Arabic–English benchmark, both in terms of BLEU (+1.06%) and of reordering quality (+0.85%) measured with the Kendall Reordering Score.     

Multirobot Localization in Highly Symmetrical Environments

The paper addresses and solves the problem of multirobot collaborative localization in highly symmetrical 2D environments, such as the ones encountered in logistic applications. Because of the environment symmetry, the most common localization algorithms may fail to provide a correct estimate of the position and orientation of the robot, if its initial position is not known, no specific landmark is introduced, and no absolute information (e.g., GPS) is available: the robot can estimate its position with respect to the walls of the corridor, but it could be critical to determine in which corridor it is actually moving. The proposed algorithm is based upon a particle filter cooperative Monte Carlo Localization (MCL) and implements a three-stage procedure for the global localization and the accurate position tracking of each robot of the team. Online simulations and experimental tests, which investigate different situations with respect to the number of robots involved and their initial positions, show how the proposed solution can lead to the global localization of each robot, with a precision sufficient to be used as starting point for the subsequent robot tracking.     

Continuous localization and mapping of a pan–tilt–zoom camera for wide area tracking

Pan–tilt–zoom (PTZ) cameras are well suited for object identification and recognition in far-field scenes. However, the effective use of PTZ cameras is complicated by the fact that a continuous online camera calibration is needed and the absolute pan, tilt and zoom values provided by the camera actuators cannot be used because they are not synchronized with the video stream. So, accurate calibration must be directly extracted from the visual content of the frames. Moreover, the large and abrupt scale changes, the scene background changes due to the camera operation and the need of camera motion compensation make target tracking with these cameras extremely challenging. In this paper, we present a solution that provides continuous online calibration of PTZ cameras which is robust to rapid camera motion, changes of the environment due to varying illumination or moving objects. The approach also scales beyond thousands of scene landmarks extracted with the SURF keypoint detector. The method directly derives the relationship between the position of a target in the ground plane and the corresponding scale and position in the image and allows real-time tracking of multiple targets with high and stable degree of accuracy even at far distances and any zoom level.     

Adaptive Robust Three‐dimensional Trajectory Tracking for Actively Articulated Tracked Vehicles*

A new approach is proposed for an adaptive robust three‐dimensional (3D) trajectory‐tracking controller design. The controller is modeled for actively articulated tracked vehicles (AATVs). These vehicles have active sub‐tracks, called flippers, linked to the ends of the main tracks, to extend the locomotion capabilities in hazardous environments, such as rescue scenarios. The proposed controller adapts the flippers configuration and simultaneously generates the track velocities, to allow the vehicle to autonomously follow a given feasible 3D path. The approach develops both a direct and differential kinematic model of the AATV for traversal task execution correlating the robot body motion to the flippers motion. The benefit of this approach is to allow the controller to flexibly manage all the degrees of freedom of the AATV as well as the steering. The differential kinematic model integrates a differential drive robot model, compensating the slippage between the vehicle tracks and the traversed terrain. The underlying feedback control law dynamically accounts for the kinematic singularities of the mechanical vehicle structure. The designed controller integrates a strategy selector too, which has the role of locally modifying the rail path of the flipper end points. This serves to reduce both the effort of the flipper servo motors and the traction force on the robot body, recognizing when the robot is moving on a horizontal plane surface. Several experiments have been performed, in both virtual and real scenarios, to validate the designed trajectory‐tracking controller, while the AATV negotiates rubble, stairs, and complex terrain surfaces. Results are compared with both the performance of an alternative control strategy and the ability of skilled human operators, manually controlling the actively articulated components of the robot.     

Finite element simulations of laser refractive corneal surgery

We setup a mechanically based finite element model to evaluate the change in the shape of the human cornea induced by ablation of stromal tissue. By considering the deformability of the cornea, the model computes the change of the dioptric power resulting from ablative laser surgery. We use a previously developed 3-D finite element model of the human cornea (Pandolfi and Manganiello in Biomech Model Mechanobiol 5:237–246, 2006). The solid geometry is discretized into finite elements by an automatic procedure which recovers the unloaded configuration. The geometry is defined in parametric form and can be characterized by individual geometrical data when available. A two-fiber reinforced hyperelastic material model, which accounts for the organization of the anisotropic collagen structure, is adopted to describe the stromal tissue. For the simulation of laser refractive surgery of myopic and astigmatic eyes, a geometrical correction of the corneal profile is included into the code. We show two examples of application of the model to the reshaping of a myopic and an astigmatic eye. Numerical results provide the postoperative shape of the cornea, the corrected refractive power, and the distribution of the stress throughout the stromal tissue.     

A fuzzy extension of the XPath query language

Today the current state of the art in querying XML data is represented by XPath and XQuery, both of which rely on Boolean conditions for node selection. Boolean selection is too restrictive when users do not use or even know the data structure precisely, e.g. when queries are written based on a summary rather than on a schema. In this paper we describe a XML querying framework, called FuzzyXPath, based on Fuzzy Set Theory, which relies on fuzzy conditions for the definition of flexible constraints on stored data. A function called “deep-similar” is introduced to replace XPath’s typical “deep-equal” function. The main goal is to provide a degree of similarity between two XML trees, assessing whether they are similar both structure-wise and content-wise. Several query examples are discussed in the field of XML based metadata for e-learning.     

Image‐to‐Geometry Registration: a Mutual Information Method exploiting Illumination‐related Geometric Properties

This work concerns a novel study in the field of image‐to‐geometry registration. Our approach takes inspiration from medical imaging, in particular from multi‐modal image registration. Most of the algorithms developed in this domain, where the images to register come from different sensors (CT, X‐ray, PET), are based on Mutual Information, a statistical measure of non‐linear correlation between two data sources. The main idea is to use mutual information as a similarity measure between the image to be registered and renderings of the model geometry, in order to drive the registration in an iterative optimization framework. We demonstrate that some illumination‐related geometric properties, such as surface normals, ambient occlusion and reflection directions can be used for this purpose. After a comprehensive analysis of such properties we propose a way to combine these sources of information in order to improve the performance of our automatic registration algorithm. The proposed approach can robustly cover a wide range of real cases and can be easily extended.     

Adaptive sampling with automatic stopping for feasible region identification in engineering design

Engineering design is a complex process to find a suitable trade-off among different, and sometimes conflicting, design specifications. In reality, these requirements can be often considered as constraints of the design problem, that can be defined in terms of performance measures or geometrical characteristics of the device under study. In this paper, a new design space exploration methodology is presented for discovering feasible regions in the design space, where the term feasible region indicates the set of all design configurations satisfying all constraints of the design problem. The proposed method is based on Gaussian process metamodels to estimate the feasible region and leverages a information-based adaptive sampling technique to sequentially refine the prediction accuracy, which is applicable for multiple constraints problems. To efficiently stop the adaptive sampling process, a novel framework to estimate the metamodel’s prediction accuracy is proposed. The efficiency, accuracy and robustness of the proposed approach are compared with state-of-art techniques on suitable benchmark problems and practical engineering examples.

     

Enabling fuzzy technologies in high performance networking via an open FPGA-based development platform

Soft computing techniques and particularly fuzzy inference systems are gaining momentum as tools for network traffic modeling, analysis and control. Efficient hardware implementations of these techniques that can achieve real-time operation in high-speed networking equipment as well as other highly time-constrained application fields is however an open problem. We introduce a development platform for fuzzy inference systems with applications to network traffic analysis and control. The platform addresses the current requirements and constraints of high performance networking equipment. For the development process, we set up a methodology and a CAD tool chain that span the entire design process from initial specification in a high-level language to implementation on FPGA devices. An FPGA development board with PCI/PCIe interface is employed to support an open platform that comprises CAD tools as well as IP cores. PCI compatible fuzzy inference modules are implemented as System-on-Programmable-Chip (SoPC). We present satisfactory experimental results from the implementation of fuzzy systems for a number of applications in analysis and control of Internet traffic. These systems are shown to satisfy operational and architectural requirements of current and future high performance routing equipment. The platform proposed allows for the development of prototypes while avoiding large investments and complicated management procedures which constrain the testing and adoption of soft computing techniques in high performance networking.     

Flavonoids from Portuguese heather honey

The flavonoids present in twenty samples of Portuguese heather honey were analysed by reversed-phase HPLC. The flavonoid fraction was purified by a combination of chromatography on Amberlite XAD-2 and Sephadex LH-20 columns. The total amount of flavonoids ranged between 60 and 500 g/100g honey, values which are much smaller than those previously found for Spanish rosemary honey samples (500-2000 g/100 g honey). The main flavonoids present in Portuguese heather honey were the flavanones pinocembrin and pinobanksin and the flavones chrysin and galangin. These analyses showed that all the samples contained a similar flavonoid pattern composed of at least 22 compounds. The most characteristic substances were myricetin, myricetin 3-methyl ether, myricetin 3'-methyl ether and tricetin. These four flavonoids have in common the structural feature of having a trioxygenated ring B (3',4',5'-trioxygenation), this being an attribute not found in the flavonoids detected in any other honey sample of different plant origin analysed so far, suggesting that these substances could probably be used as markers for the botanical origin of heather honey.

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Flavonoide aus portugiesischem Heidehonig

Zusammenfassung Die Flavonoide aus portugiesischem Heidehonig wurden mit der HPLC in reversed-phase-Technik analysiert. Die Fraktionen wurden durch Adsorptionsund Gelchromatographie gereinigt, ihre Gesamtausbeute betrug 60 bis 500 g/100 g Honig. Als Hauptkomponenten wurden Pinocembrin und Pinobanksin (Flavanone) sowie Chrysin und Galangin (Flavone) identifiziert. Alle Proben erhielten ein ähnliches Muster aus mindestens 22 Flavonoiden. Charakteristisch waren Myricitin sowie dessen 3- und 3'-Methylether sowie Tricetin. Derartige Verbindungen wurden bisher in keinem anderen Honig gefunden und eignen sich möglicherweise als Herkunftsnachweis für Heidehonig.