Multi-utility Learning: Structured-output Learning with Multiple Annotation-specific Loss Functions

Structured-output learning is a challenging problem; particularly so because of the difficulty in obtaining large datasets of fully labelled instances for training. In this paper we try to overcome this difficulty by presenting a multi-utility learning framework for structured prediction that can learn from training instances with different forms of supervision. We propose a unified technique for inferring the loss functions most suitable for quantifying the consistency of solutions with the given weak annotation. We demonstrate the effectiveness of our framework on the challenging semantic image segmentation problem for which a wide variety of annotations can be used. For instance, the popular training datasets for semantic segmentation are composed of images with hard-to-generate full pixel labellings, as well as images with easy-to-obtain weak annotations, such as bounding boxes around objects, or image-level labels that specify which object categories are present in an image. Experimental evaluation shows that the use of annotation-specific loss functions dramatically improves segmentation accuracy compared to the baseline system where only one type of weak annotation is used

Impact of NOM character on copper adsorption by trace ferric hydroxide from iron corrosion in water supply system

The fate of trace concentrations of cupric sulfate (<0.4 mg/L) dosed into chloraminated distribution systems to inhibit nitrification has been shown in this study to be controlled by at least two crucial factors: the character of natural organic matter (NOM) and iron hydroxide corrosion products present at low concentrations (<2 mg/L). This research quantified the removal of Cu(II) ions added into waters containing trace Fe(OH)3 flocs and the effect of NOM of different character on this removal. The dominant dissolved copper species in NOM-containing waters were found to be Cu(II)–NOM complexes. Both intramolecular chelation and intermolecular complexation can occur, with the latter occurring preferentially and resulting in the aggregation of smaller organic molecules to form larger molecules. The presence of ferric hydroxide flocs when Cu(II) ions were added into NOM-containing waters was shown to result in removal of Cu(II) ions, presumably as Cu(II)–NOM complexes. This removal was through adsorption processes obeying Freundlich isotherms, although the presence of larger NOM molecules and heterogeneous copper species (e.g. Cu(OH)2(s) and CuO(s)) appeared to shield smaller Cu(II)–NOM complexes from adsorption to some extent. For the strategy of inhibition of nitrification in distribution systems by the addition of Cu(II) ions, complexation of Cu(II) ions by NOM and adsorption of Cu(II)–NOM complexes by ferric hydroxide flocs released from pipe walls pose significant operational challenges to maintaining the concentration of Cu(II) ions through the distribution system

On the predominant mechanisms active during the high power diode laser modification of the wettability characteristics of an SiO2/Al2O3-based ceramic material

The mechanisms responsible for modifications to the wettability characteristics of a SiO2/Al2O3-based ceramic material in terms of a test liquid set comprising of human blood, human blood plasma, glycerol and 4-octonol after high power diode laser (HPDL) treatment have been elucidated. Changes in the contact angle, , and hence the wettability characteristics of the SiO2/Al2O3-based ceramic were attributed primarily to: modifications to the surface roughness of the ceramic resulting from HPDL interaction which accordingly effected reductions in ; the increase in the surface O2 content of the ceramic after HPDL treatment; since an increase in surface O2 content intrinsically brings about a decrease in , and vice versa and the increase in the polar component of the surface energy, due to the HPDL induced surface melting and resolidification which consequently created a partially vitrified microstructure that was seen to augment the wetting action. However, the degree of influence exerted by each mechanism was found to differ markedly. Isolation of each of these mechanisms permitted the magnitude of their influence to be qualitatively determined. Surface energy, by way of microstructural changes, was found to be by far the most predominant element governing the wetting characteristics of the SiO2/Al2O3-based ceramic. To a much lesser extent, surface O2 content, by way of process gas, was also seen to influence to a changes in the wettability characteristics of the SiO2/Al2O3-based ceramic, whilst surface roughness was found to play a minor role in inducing changes in the wettability characteristics

Contextual Object Detection with a Few Relevant Neighbors

A natural way to improve the detection of objects is to consider the contextual constraints imposed by the detection of additional objects in a given scene. In this work, we exploit the spatial relations between objects in order to improve detection capacity, as well as analyze various properties of the contextual object detection problem. To precisely calculate context-based probabilities of objects, we developed a model that examines the interactions between objects in an exact probabilistic setting, in contrast to previous methods that typically utilize approximations based on pairwise interactions. Such a scheme is facilitated by the realistic assumption that the existence of an object in any given location is influenced by only few informative locations in space. Based on this assumption, we suggest a method for identifying these relevant locations and integrating them into a mostly exact calculation of probability based on their raw detector responses. This scheme is shown to improve detection results and provides unique insights about the process of contextual inference for object detection. We show that it is generally difficult to learn that a particular object reduces the probability of another, and that in cases when the context and detector strongly disagree this learning becomes virtually impossible for the purposes of improving the results of an object detector. Finally, we demonstrate improved detection results through use of our approach as applied to the PASCAL VOC and COCO datasets

Exciton and negative trion dissociation by an external electric field in vertically coupled quantum dots

We study the Stark effect for an exciton confined in a pair of vertically coupled quantum dots. A single-band approximation for the hole and a parabolic lateral confinement potential are adopted which allows for the separation of the lateral center-of-mass motion and consequently for an exact numerical solution of the Schr\"odinger equation. We show that for intermediate tunnel coupling the external electric field leads to the dissociation of the exciton via an avoided crossing of bright and dark exciton energy levels which results in an atypical form of the Stark shift. The electric-field-induced dissociation of the negative trion is studied using the approximation of frozen lateral degrees of freedom. It is shown that in a symmetric system of coupled dots the trion is more stable against dissociation than the exciton. For an asymmetric system of coupled dots the trion dissociation is accompanied by a positive curvature of the recombination energy line as a function of the electric field.Comment: PRB - in prin