Space-time Reconstruction of Oceanic Sea States via Variational Stereo Methods

We present a remote sensing observational method for the measurement of the spatio-temporal dynamics of ocean waves. Variational techniques are used to recover a coherent space-time reconstruction of oceanic sea states given stereo video imagery. The stereoscopic reconstruction problem is expressed in a variational optimization framework. There, we design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal regularizers. A nested iterative scheme is devised to numerically solve, via 3-D multigrid methods, the system of partial differential equations resulting from the optimality condition of the energy functional. The output of our method is the coherent, simultaneous estimation of the wave surface height and radiance at multiple snapshots. We demonstrate our algorithm on real data collected off-shore. Statistical and spectral analysis are performed. Comparison with respect to an existing sequential method is analyzed.

A Variational Stereo Method for the Three-Dimensional Reconstruction of Ocean Waves

We develop a novel remote sensing technique for the observation of waves on the ocean surface. Our method infers the 3-D waveform and radiance of oceanic sea states via a variational stereo imagery formulation. In this setting, the shape and radiance of the wave surface are given by minimizers of a composite energy functional that combines a photometric matching term along with regularization terms involving the smoothness of the unknowns. The desired ocean surface shape and radiance are the solution of a system of coupled partial differential equations derived from the optimality conditions of the energy functional. The proposed method is naturally extended to study the spatiotemporal dynamics of ocean waves and applied to three sets of stereo video data. Statistical and spectral analysis are carried out. Our results provide evidence that the observed omnidirectional wavenumber spectrum S(k) decays as k-2.5 is in agreement with Zakharov's theory (1999). Furthermore, the 3-D spectrum of the reconstructed wave surface is exploited to estimate wave dispersion and currents.

A mathematical framework for finite strain elastoplastic consolidation. Part 1: Balance laws, variational formulation, and linearization

A mathematical formulation for finite strain elasto plastic consolidation of fully saturated soil media is presented. Strong and weak forms of the boundary-value problem are derived using both the material and spatial descriptions. The algorithmic treatment of finite strain elastoplasticity for the solid phase is based on multiplicative decomposition and is coupled with the algorithm for fluid flow via the Kirchhoff pore water pressure. Balance laws are written for the soil-water mixture following the motion of the soil matrix alone. It is shown that the motion of the fluid phase only affects the Jacobian of the solid phase motion, and therefore can be characterized completely by the motion of the soil matrix. Furthermore, it is shown from energy balance consideration that the effective, or intergranular, stress is the appropriate measure of stress for describing the constitutive response of the soil skeleton since it absorbs all the strain energy generated in the saturated soil-water mixture. Finally, it is shown that the mathematical model is amenable to consistent linearization, and that explicit expressions for the consistent tangent operators can be derived for use in numerical solutions such as those based on the finite element method.

Space-time ocean wave measurement using variational stereo vision systems

Remote sensing imaging systems for the measurement of oceanic sea states have recently attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting observed waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss the improvement of their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters.

Accuracy estimates based on multifield variational principles

Recent developments to fit the so called Free Formulation into a variational framework have suggested the possibility of introducing a new category of error estimates for finite element computations. Such error estimates are based on differences between certain multifield functionals, which give the same value for the true solution. In the present paper the formulation of some estimates of this kind is introduced for elasticity and plate bending problems, and several examples of their performance are discussed. The observed numerical behavior of the new accuracy measures seems to be acceptable from an engineering point of view. However, further numerical experimentation is still needed to establish practical tolerance levels for real problems.

Joint 4-D variational stereo reconstruction and camera calibration refinement for oceanic sea state measurements

Validating modern oceanographic theories using models produced through stereo computer vision principles has recently emerged. Space-time (4-D) models of the ocean surface may be generated by stacking a series of 3-D reconstructions independently generated for each time instant or, in a more robust manner, by simultaneously processing several snapshots coherently in a true ?4-D reconstruction.? However, the accuracy of these computer-vision-generated models is subject to the estimations of camera parameters, which may be corrupted under the influence of natural factors such as wind and vibrations. Therefore, removing the unpredictable errors of the camera parameters is necessary for an accurate reconstruction. In this paper, we propose a novel algorithm that can jointly perform a 4-D reconstruction as well as correct the camera parameter errors introduced by external factors. The technique is founded upon variational optimization methods to benefit from their numerous advantages: continuity of the estimated surface in space and time, robustness, and accuracy. The performance of the proposed algorithm is tested using synthetic data produced through computer graphics techniques, based on which the errors of the camera parameters arising from natural factors can be simulated.

Explanation of changes in real estate stock market

The aim of this study is to explain the changes in the real estate prices as well as in the real estate stock market prices, using some macro-economic explanatory variables, such as the gross domestic product (GDP), the real interest rate and the unemployment rate. Several regressions have been carried out in order to express some types of incremental and absolute deflated real estate lock market indexes in terms of the macro-economic variables. The analyses are applied to the Swedish economy. The period under study is 1984-1994. Time series on monthly data are used. i.e. the number of data-points is 132. If time leads/lags are introduced in the e regressions, significant improvements in the already high correlations are achieved. The signs of the coefficients for IR, UE and GDP are all what one would expect to see from an economic point of view: those for GDP are all positive, those for both IR and UE are negative. All the regressions have high R2 values. Both markets anticipate change in the unemployment rate by 6 to 9 months, which seems reasonable because such change can be forecast quite reliably. But, on the contrary, there is no reason why they should anticipate by 3-6 months changes in the interest rate that can hardly be reliably forecast so far in advance.

In vitro repair of oxidative DNA damage by human nucleotide excision repair system: Possible explanation for neurodegeneration in Xeroderma pigmentosum patients

Xeroderma pigmentosum (XP) patients fail to remove pyrimidine dimers caused by sunlight and, as a consequence, develop multiple cancers in areas exposed to light. The second most common sign, present in 20–30% of XP patients, is a set of neurological abnormalities caused by neuronal death in the central and peripheral nervous systems. Neural tissue is shielded from sunlight-induced DNA damage, so the cause of neurodegeneration in XP patients remains unexplained. In this study, we show that two major oxidative DNA lesions, 8-oxoguanine and thymine glycol, are excised from DNA in vitro by the same enzyme system responsible for removing pyrimidine dimers and other bulky DNA adducts. Our results suggest that XP neurological disease may be caused by defective repair of lesions that are produced in nerve cells by reactive oxygen species generated as by-products of an active oxidative metabolism.

An empirical explanation of brightness

In this second part of our study on the mechanism of perceived brightness, we explore the effects of manipulating three-dimensional geometry. The additional scenes portrayed here demonstrate that the same luminance profile can elicit different sensations of brightness as a function of how the objects in the scene are arranged in space. This further evidence confirms the implication of the scenes presented in the accompanying paper, namely that sensations of relative brightness—including standard demonstrations of simultaneous brightness contrast—cannot arise by computations of local contrast. The most plausible explanation of the full range of perceptual phenomena we have described is an empirical strategy that links the luminance profile in a visual stimulus with an association (the percept) that represents the profile’s most probable real-world source.

A simple explanation for taxon abundance patterns

For taxonomic levels higher than species, the abundance distributions of the number of subtaxa per taxon tend to approximate power laws but often show strong deviations from such laws. Previously, these deviations were attributed to finite-time effects in a continuous-time branching process at the generic level. Instead, we describe herein a simple discrete branching process that generates the observed distributions and find that the distribution's deviation from power law form is not caused by disequilibration, but rather that it is time independent and determined by the evolutionary properties of the taxa of interest. Our model predicts—with no free parameters—the rank-frequency distribution of the number of families in fossil marine animal orders obtained from the fossil record. We find that near power law distributions are statistically almost inevitable for taxa higher than species. The branching model also sheds light on species-abundance patterns, as well as on links between evolutionary processes, self-organized criticality, and fractals.

Explanation by the double-metal-ion mechanism of catalysis for the differential metal ion effects on the cleavage rates of 5′-oxy and 5′-thio substrates by a hammerhead ribozyme

In a previous examination using natural all-RNA substrates that contained either a 5′-oxy or 5′-thio leaving group at the cleavage site, we demonstrated that (i) the attack by the 2′-oxygen at C17 on the phosphorus atom is the rate-limiting step only for the substrate that contains a 5′-thio group (R11S) and (ii) the departure of the 5′ leaving group is the rate-limiting step for the natural all-RNA substrate (R11O) in both nonenzymatic and hammerhead ribozyme-catalyzed reactions; the energy diagrams for these reactions were provided in our previous publication. In this report we found that the rate of cleavage of R11O by a hammerhead ribozyme was enhanced 14-fold when Mg2+ ions were replaced by Mn2+ ions, whereas the rate of cleavage of R11S was enhanced only 2.2-fold when Mg2+ ions were replaced by Mn2+ ions. This result appears to be exactly the opposite of that predicted from the direct coordination of the metal ion with the leaving 5′-oxygen, because a switch in metal ion specificity was not observed with the 5′-thio substrate. However, our quantitative analyses based on the previously provided energy diagram indicate that this result is in accord with the double-metal-ion mechanism of catalysis.

A wholly empirical explanation of perceived motion

Because the retinal activity generated by a moving object cannot specify which of an infinite number of possible physical displacements underlies the stimulus, its real-world cause is necessarily uncertain. How, then, do observers respond successfully to sequences of images whose provenance is ambiguous? Here we explore the hypothesis that the visual system solves this problem by a probabilistic strategy in which perceived motion is generated entirely according to the relative frequency of occurrence of the physical sources of the stimulus. The merits of this concept were tested by comparing the directions and speeds of moving lines reported by subjects to the values determined by the probability distribution of all the possible physical displacements underlying the stimulus. The velocities reported by observers in a variety of stimulus contexts can be accounted for in this way.

Phrase-based statistical machine translation: explanation of its processes and statistical models and evaluation of the English to Spanish translations produced

Statistical machine translation (SMT) is an approach to Machine Translation (MT) that uses statistical models whose parameter estimation is based on the analysis of existing human translations (contained in bilingual corpora). From a translation student’s standpoint, this dissertation aims to explain how a phrase-based SMT system works, to determine the role of the statistical models it uses in the translation process and to assess the quality of the translations provided that system is trained with in-domain goodquality corpora. To that end, a phrase-based SMT system based on Moses has been trained and subsequently used for the English to Spanish translation of two texts related in topic to the training data. Finally, the quality of this output texts produced by the system has been assessed through a quantitative evaluation carried out with three different automatic evaluation measures and a qualitative evaluation based on the Multidimensional Quality Metrics (MQM).