Directions of Motion Fields are Hardly Ever Ambiguous

International Journal of Computer Vision - If instead of the full motion field, we consider only the direction of the motion field due to a rigid motion, what can we say about the three-dimensional...     

Effect of freeze–dried kefir culture on proteolysis in feta-type and whey-cheeses

The effect of freeze–dried kefir culture on the proteolysis of feta-type and whey-cheese was investigated. All nitrogen fractions increased during ripening. Although no significant differences were observed in total nitrogen (TN), the levels of water-soluble nitrogen (WSN), pH 4.4-soluble nitrogen (SN), 12% trichloroacetic acid-soluble nitrogen (TCA-SN) and phosphotungstic acid-soluble nitrogen (PTA-SN) were significantly higher in cheeses produced by freeze–dried kefir culture during the later stages of ripening. Content of total free amino acids (FAA) was significantly affected by freeze–dried kefir starter culture and it was continuously increased in kefir-cheese while, in rennet-cheese it was increased up to 30 days of ripening and then slightly decreased. On the other hand, FAA content continuously decreased in kefir-whey-cheese whereas it increased in whey-cheese. The cheese samples produced by freeze–dried kefir as starter culture were characterised as high-quality products during the preliminary sensory evaluation and they were accepted by the panel. Overall, the use of freeze–dried kefir suggested acceleration of cheese ripening and resulted in improved sensory characteristics.     

Reliability and economic evaluation of small autonomous power systems containing only renewable energy sources

Evaluation of reliability performance in every power system has to be done within a cost–benefit framework. This approach, however, is a very time consuming task, especially for systems that contain a large number of possible configurations, so simpler techniques referred to the calculation of reliability indices are used. In small autonomous power systems (SAPSs), such an evaluation uses mainly deterministic criteria. This approach, however, cannot be applied in SAPS that contain only renewable energy sources, due to the intermittent nature of the provided energy. In this paper, a complete reliability cost and worth analysis is implemented for these systems, combined with the calculation of some basic probabilistic indices, in order to discover their performance and propose the appropriate of them as a criterion of optimal system configuration. This paper proposes that normalized energy reliability indices as system minutes and energy index of unavailability can be used as adequate criteria of system's optimal performance. This conclusion is validated through a large number of sensitivity analysis studies that are based on different maximum annual loads and different mix of load types.     

Towards treatment planning for the embolization of arteriovenous malformations of the brain: intranidal hemodynamics modeling

This paper presents a patient-derived model for the simulation of the hemodynamics of arteriovenous malformations of the brain (BAVM). This new approach is a step toward the simulation of the outcome of the embolization of the BAVM during treatment planning. More specifically, two aspects of the planning are pursued: simulation of the change of blood flow in the brain vasculature after the blocking of the malformation and simulation of the transport of the embolic liquid. The method we propose is tested on 3 BAVM cases of varying complexity. Twenty two out of 24 main BAVM flow paths have been identified well by simulation.     

Molecular structure of CaO–FeOx–SiO2 glassy slags and resultant inorganic polymer binders

The molecular structures of CaO–FeO_x–SiO₂ slags and their inorganic polymer counterparts were determined using neutron and X‐ray scattering with subsequent pair distribution function (PDF) analysis. The slags were synthesized with approximate molar compositions: 0.17CaO–0.83FeO–SiO₂ and 0.33CaO–0.67FeO–SiO₂ (referred to as low‐Ca and high‐Ca, respectively)_. The PDF data on the slags reasserted the predominantly glassy nature of this iron‐rich industrial byproduct. The dominant metal‐metal correlation was Fe–Si (3.20‐3.25 Å), with smaller contributions from Fe–Ca (3.45‐3.50 Å) and Fe–Fe (2.95‐3.00 Å). After inorganic polymer synthesis, a rise in the amount of Fe³⁺ was observed via the shift of the Fe–O bond length to shorter distances. This shortening of the Fe–O distance in the binder is also evidenced by the apparent rise of the Fe–Fe correlation at 2.95‐3.00 Å, although this feature may also suggest a potential aggregation of FeO_x clusters. In general, the atomic arrangements of the reaction product was shown to be very similar to the precursor structure and the dominance of the Fe–Si correlation suggests the participation of Fe in the silicate network. The binder was shown to be glassy, as no distinct atom‐atom correlations were observed beyond 8 Å.     

Motion segmentation using occlusions

We examine the key role of occlusions in finding independently moving objects instantaneously in a video obtained by a moving camera with a restricted field of view. In this problem, the image motion is caused by the combined effect of camera motion (egomotion), structure (depth), and the independent motion of scene entities. For a camera with a restricted field of view undergoing a small motion between frames, there exists, in general, a set of 3D camera motions compatible with the observed flow field even if only a small amount of noise is present, leading to ambiguous 3D motion estimates. If separable sets of solutions exist, motion-based clustering can detect one category of moving objects. Even if a single inseparable set of solutions is found, we show that occlusion information can be used to find ordinal depth, which is critical in identifying a new class of moving objects. In order to find ordinal depth, occlusions must not only be known, but they must also be filled (grouped) with optical flow from neighboring regions. We present a novel algorithm for filling occlusions and deducing ordinal depth under general circumstances. Finally, we describe another category of moving objects which is detected using cardinal comparisons between structure from motion and structure estimates from another source (e.g., stereo).     

A nonparametric Bayesian approach toward robot learning by demonstration

In the past years, many authors have considered application of machine learning methodologies to effect robot learning by demonstration. Gaussian mixture regression (GMR) is one of the most successful methodologies used for this purpose. A major limitation of GMR models concerns automatic selection of the proper number of model states, i.e., the number of model component densities. Existing methods, including likelihood- or entropy-based criteria, usually tend to yield noisy model size estimates while imposing heavy computational requirements. Recently, Dirichlet process (infinite) mixture models have emerged in the cornerstone of nonparametric Bayesian statistics as promising candidates for clustering applications where the number of clusters is unknown a priori. Under this motivation, to resolve the aforementioned issues of GMR-based methods for robot learning by demonstration, in this paper we introduce a nonparametric Bayesian formulation for the GMR model, the Dirichlet process GMR model. We derive an efficient variational Bayesian inference algorithm for the proposed model, and we experimentally investigate its efficacy as a robot learning by demonstration methodology, considering a number of demanding robot learning by demonstration scenarios.