A generic framework for context-sensitive analysis of modular programs

Context-sensitive analysis provides information which is potentially more accurate than that provided by context-free analysis. Such information can then be applied in order to validate/debug the program and/or to specialize the program obtaining important improvements. Unfortunately, context-sensitive analysis of modular programs poses important theoretical and practical problems. One solution, used in several proposals, is to resort to context-free analysis. Other proposals do address context-sensitive analysis, but are only applicable when the description domain used satisfies rather restrictive properties. In this paper, we argüe that a general framework for context-sensitive analysis of modular programs, Le., one that allows using all the domains which have proved useful in practice in the non-modular setting, is indeed feasible and very useful. Driven by our experience in the design and implementation of analysis and specialization techniques in the context of CiaoPP, the Ciao system preprocessor, in this paper we discuss a number of design goals for context-sensitive analysis of modular programs as well as the problems which arise in trying to meet these goals. We also provide a high-level description of a framework for analysis of modular programs which does substantially meet these objectives. This framework is generic in that it can be instantiated in different ways in order to adapt to different contexts. Finally, the behavior of the different instantiations w.r.t. the design goals that motivate our work is also discussed

Fast Fight Detection

Action recognition has become a hot topic within computer vision. However, the action recognition community has focused mainly on relatively simple actions like clapping, walking, jogging, etc. The detection of specific events with direct practical use such as fights or in general aggressive behavior has been comparatively less studied. Such capability may be extremely useful in some video surveillance scenarios like prisons, psychiatric centers or even embedded in camera phones. As a consequence, there is growing interest in developing violence detection algorithms. Recent work considered the well-known Bag-of-Words framework for the specific problem of fight detection. Under this framework, spatio-temporal features are extracted from the video sequences and used for classification. Despite encouraging results in which high accuracy rates were achieved, the computational cost of extracting such features is prohibitive for practical applications. This work proposes a novel method to detect violence sequences. Features extracted from motion blobs are used to discriminate fight and non-fight sequences. Although the method is outperformed in accuracy by state of the art, it has a significantly faster computation time thus making it amenable for real-time applications

Topological Quintessence

A global monopole (or other topological defect) formed during a recent phase transition with core size comparable to the present Hubble scale, could induce the observed accelerating expansion of the universe. In such a model, topological considerations trap the scalar field close to a local maximum of its potential in a cosmologically large region of space. We perform detailed numerical simulations of such an inhomogeneous dark energy system (topological quintessence) minimally coupled to gravity, in a flat background of initially homogeneous matter. We find that when the energy density of the field in the monopole core starts dominating the background density, the spacetime in the core starts to accelerate its expansion in accordance to a \Lambda CDM model with an effective inhomogeneous spherical dark energy density parameter \Omega_\Lambda(r). The matter density profile is found to respond to the global monopole profile via an anti-correlation (matter underdensity in the monopole core). Away from the monopole core, the spacetime is effectively Einstein-deSitter (\Omega_\Lambda(r_{out}) -> 0) while at the center \Omega_\Lambda(r ~ 0) is maximum. We fit the numerically obtained expansion rate at the monopole core to the Union2 data and show that the quality of fit is almost identical to that of \Lambda CDM. Finally, we discuss potential observational signatures of this class of inhomogeneous dark energy models.Comment: Accepted in Phys. Rev. D (to appear). Added observational bounds on parameters. 10 pages (two column revtex), 6 figures. The Mathematica files used to produce the figures of this study may be downloaded from http://leandros.physics.uoi.gr/topquin

The influence of coronal EUV irradiance on the emission in the He I 10830 A and D3 multiplets

Two of the most attractive spectral windows for spectropolarimetric investigations of the physical properties of the plasma structures in the solar chromosphere and corona are the ones provided by the spectral lines of the He I 10830 A and 5876 A (or D3) multiplets, whose polarization signals are sensitive to the Hanle and Zeeman effects. However, in order to be able to carry out reliable diagnostics, it is crucial to have a good physical understanding of the sensitivity of the observed spectral line radiation to the various competing driving mechanisms. Here we report a series of off-the-limb non-LTE calculations of the He I D3 and 10830 A emission profiles, focusing our investigation on their sensitivity to the EUV coronal irradiation and the model atmosphere used in the calculations. We show in particular that the intensity ratio of the blue to the red components in the emission profiles of the He I 10830 A multiplet turns out to be a good candidate as a diagnostic tool for the coronal irradiance. Measurements of this observable as a function of the distance to the limb and its confrontation with radiative transfer modeling might give us valuable information on the physical properties of the solar atmosphere and on the amount of EUV radiation at relevant wavelengths penetrating the chromosphere from above.Comment: 19 pages, 11 figures (pre-print format). Accepted for publication in Ap