The “Always Best Packet Switching” architecture for SIP-based mobile multimedia services

This paper presents a distributed architecture for the provision of seamless and responsive mobile multimedia services. This architecture allows its user applications to use concurrently all the wireless network interface cards (NICs) a mobile terminal is equipped with. In particular, as mobile multimedia services are usually implemented using the UDP protocol, our architecture enables the transmission of each UDP datagram through the “most suitable” (e.g. most responsive, least loaded) NIC among those available at the time a datagram is transmitted. We term this operating mode of our architecture Always Best Packet Switching (ABPS). ABPS enables the use of policies for load balancing and recovery purposes. In essence, the architecture we propose consists of the following two principal components: (i) a fixed proxy server, which acts as a relay for the mobile node and enables communications from/to this node regardless of possible firewalls and NAT systems, and (ii) a proxy client running in the mobile node responsible for maintaining a multi-path tunnel, constructed out of all the node's NICs, with the above mentioned fixed proxy server. We show how the architecture supports multimedia applications based on the SIP and RTP/RTCP protocols, and avoids the typical delays introduced by the two way message/response handshake of the SIP signaling protocol. Experimental results originated from the implementation of a VoIP application on top of the architecture we propose show the effectiveness of our approach.     

ROMANSEVAL: Results for Italian by SENSE

The paper describes SENSE, a word sense disambiguation system thatmakes use of different types of cues to infer the most likelysense of a word given its context. Architecture and functioning ofthe system are briefly illustrated. Results are given for theROMANSEVAL Italian test corpus of verbs.     

Oxidation of proteins: Basic principles and perspectives for blood proteomics

Protein oxidation mechanisms result in a wide array of modifications, from backbone cleavage or protein crosslinking to more subtle modifications such as side chain oxidations. Protein oxidation occurs as part of normal regulatory processes, as a defence mechanism against oxidative stress, or as a deleterious processes when antioxidant defences are overcome. Because blood is continually exposed to reactive oxygen and nitrogen species, blood proteomics should inherently adopt redox proteomic strategies. In this review, we recall the biochemical basis of protein oxidation, review the proteomic methodologies applied to analyse redox modifications, and highlight some physiological and in vitro responses to oxidative stress of various blood components.     

FERM3D: A finite element R-matrix electron molecule scattering code

FERM3D is a three-dimensional finite element program, for the elastic scattering of a low energy electron from a general polyatomic molecule, which is converted to a potential scattering problem. The code is based on tricubic polynomials in spherical coordinates. The electron-molecule interaction is treated as a sum of three terms: electrostatic, exchange, and polarization. The electrostatic term can be extracted directly from ab initio codes (GAUSSIAN 98 in the work described here), while the exchange term is approximated using a local density functional. A local polarization potential based on density functional theory [C. Lee, W. Yang, R.G. Parr, Phys. Rev. B 37 (1988) 785] describes the long range attraction to the molecular target induced by the scattering electron. Photoionization calculations are also possible and illustrated in the present work. The generality and simplicity of the approach is important in extending electron-scattering calculations to more complex targets than it is possible with other methods.

Program summary

Title of program:FERM3DCatalogue identifier:ADYL_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYL_v1_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputer for which the program is designed and others on which it has been tested:Intel Xeon, AMD Opteron 64 bit, Compaq AlphaOperating systems or monitors under which the program has been tested:HP Tru64 Unix v5.1, Red Hat Linux Enterprise 3Programming language used:Fortran 90Memory required to execute with typical data:900 MB (neutral CO₂), 2.3 GB (ionic CO₂), 1.4 GB (benzene)No. of bits in a word:32No. of processors used:1Has the code been vectorized?:NoNo. of lines in distributed program, including test data, etc.:58 383No. of bytes in distributed program, including test data, etc.:561 653Distribution format:tar.gzip fileCPC Program library subprograms used:ADDA, ACDPNature of physical problem:Scattering of an electron from a complex polyatomic molecular target.Method of solution:Solution of a partial differential equation using a finite element basis, and direct sparse linear solvers.Restrictions on the complexity of the problem:Memory constraints.Typical running time:2 hours.Unusual features of the program:

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very extensive use of memory,

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requires installation of Lapack, Blas, a direct sparse solver library (SuperLU, freely available, or Pardiso, which requires a license, but is free of charge for academic use), and optionally the Cernlib and Arpack libraries, freely available,

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requires input from quantum chemistry programs (Gaussian, Molpro or PC Gamess).

     

Classification and recognition of dynamical models: the role of phase, independent components, kernels and optimal transport

We address the problem of performing decision tasks, and in particular classification and recognition, in the space of dynamical models in order to compare time series of data. Motivated by the application of recognition of human motion in image sequences, we consider a class of models that include linear dynamics, both stable and marginally stable (periodic), both minimum and non-minimum phase, driven by non-Gaussian processes. This requires extending existing learning and system identification algorithms to handle periodic modes and nonminimum phase behavior, while taking into account higher-order statistics of the data. Once a model is identified, we define a kernel-based cord distance between models that includes their dynamics, their initial conditions as well as input distribution. This is made possible by a novel kernel defined between two arbitrary (non-Gaussian) distributions, which is computed by efficiently solving an optimal transport problem. We validate our choice of models, inference algorithm, and distance on the tasks of human motion synthesis (sample paths of the learned models), and recognition (nearest-neighbor classification in the computed distance). However, our work can be applied more broadly where one needs to compare historical data while taking into account periodic trends, non-minimum phase behavior, and non-Gaussian input distributions.     

A variational approach to problems in calibration of multiple cameras

This paper addresses the problem of calibrating camera parameters using variational methods. One problem addressed is the severe lens distortion in low-cost cameras. For many computer vision algorithms aiming at reconstructing reliable representations of 3D scenes, the camera distortion effects will lead to inaccurate 3D reconstructions and geometrical measurements if not accounted for. A second problem is the color calibration problem caused by variations in camera responses that result in different color measurements and affects the algorithms that depend on these measurements. We also address the extrinsic camera calibration that estimates relative poses and orientations of multiple cameras in the system and the intrinsic camera calibration that estimates focal lengths and the skew parameters of the cameras. To address these calibration problems, we present multiview stereo techniques based on variational methods that utilize partial and ordinary differential equations. Our approach can also be considered as a coordinated refinement of camera calibration parameters. To reduce computational complexity of such algorithms, we utilize prior knowledge on the calibration object, making a piecewise smooth surface assumption, and evolve the pose, orientation, and scale parameters of such a 3D model object without requiring a 2D feature extraction from camera views. We derive the evolution equations for the distortion coefficients, the color calibration parameters, the extrinsic and intrinsic parameters of the cameras, and present experimental results.     

The multimod application framework: a rapid application development tool for computer aided medicine

This paper describes a new application framework (OpenMAF) for rapid development of multimodal applications in computer-aided medicine. MAF applications are multimodal in data, in representation, and in interaction. The framework supports almost any type of biomedical data, including DICOM datasets, motion-capture recordings, or data from computer simulations (e.g. finite element modeling). The interactive visualization approach (multimodal display) helps the user interpret complex datasets, providing multiple representations of the same data. In addition, the framework allows multimodal interaction by supporting the simultaneous use of different input-output devices like 3D trackers, stereoscopic displays, haptics hardware and speech recognition/synthesis systems. The Framework has been designed to run smoothly even on limited power computers, but it can take advantage of all hardware capabilities. The Framework is based on a collection of portable libraries and it can be compiled on any platform that supports OpenGL, including Windows, MacOS X and any flavor of Unix/linux.     

Spectral Duality for Finitely Generated Nilpotent Minimum Algebras, with Applications

We establish a categorical duality for the finitely generatedLindenbaum-Tarski algebras of propositional nilpotent minimumlogic. The latter's conjunction is semantically interpretedby a left-continuous (but not continuous) triangular norm; implicationis obtained through residuation. Our duality allows one to transferto nilpotent minimum logic several known results about inutitionisticlogic with the prelinearity axiom (also called Gödel-Dummettlogic), mutatis mutandis. We give several such applications.     

Algorithmic and architectural design for real-time and power-efficient Retinex image/video processing

This paper presents novel algorithmic and architectural solutions for real-time and power-efficient enhancement of images and video sequences. A programmable class of Retinex-like filters, based on the separation of the illumination and reflectance components, is proposed. The dynamic range of the input image is controlled by applying a suitable non-linear function to the illumination, while the details are enhanced by processing the reflectance. An innovative spatially recursive rational filter is used to estimate the illumination. Moreover, to improve the visual quality results of two-branch Retinex operators when applied to videos, a novel three-branch technique is proposed which exploits both spatial and temporal filtering. Real-time implementation is obtained by designing an Application Specific Instruction-set Processor (ASIP). Optimizations are addressed at algorithmic and architectural levels. The former involves arithmetic accuracy definition and linearization of non-linear operators; the latter includes customized instruction set, dedicated memory structure, adapted pipeline, bypasses, custom address generator, and special looping structures. The ASIP is synthesized in standard-cells CMOS technology and its performances are compared to known Digital signal processor (DSP) implementations of real-time Retinex filters. As a result of the comparison, the proposed algorithmic/architectural design outperforms state-of-art Retinex-like operators achieving the best trade-off between power consumption, flexibility, and visual quality.