Importance of Reservoir Tributaries to Spawning of Migratory Fish in the Upper Paraná River

Regulation of rivers by dams transforms previously lotic reaches above the dam into lentic ones and limits or prevents longitudinal connectivity, which impairs access to suitable habitats for the reproduction of many migratory fish species. Frequently, unregulated tributaries can provide important habitat heterogeneity to a regulated river and may mitigate the influence of impoundments on the mainstem river. We evaluated the importance of tributaries to spawning of migratory fish species over three spawning seasons, by comparing several abiotic conditions and larval fish distributions in four rivers that are tributaries to an impounded reach of the Upper Paraná River, Brazil. Our study confirmed reproduction of at least 8 long‐distance migrators, likely nine, out of a total of 19 occurring in the Upper Paraná River. Total larval densities and percentage species composition differed among tributaries, but the differences were not consistent among spawning seasons and unexpectedly were not strongly related to annual differences in temperature and hydrology. We hypothesize that under present conditions, densities of larvae of migratory species may be better related to efficiency of fish passage facilities than to temperature and hydrology. Our study indicates that adult fish are finding suitable habitat for spawning in tributaries, fish eggs are developing into larvae, and larvae are finding suitable rearing space in lagoons adjacent to the tributaries. Our findings also suggest the need for establishment of protected areas in unregulated and lightly regulated tributaries to preserve essential spawning and nursery habitats. Copyright © 2014 John Wiley & Sons, Ltd.     

Assessment of crowdsourcing and gamification loss in user-assisted object segmentation

There has been a growing interest in applying human computation – particularly crowdsourcing techniques – to assist in the solution of multimedia, image processing, and computer vision problems which are still too difficult to solve using fully automatic algorithms, and yet relatively easy for humans. In this paper we focus on a specific problem – object segmentation within color images – and compare different solutions which combine color image segmentation algorithms with human efforts, either in the form of an explicit interactive segmentation task or through an implicit collection of valuable human traces with a game. We use Click’n’Cut, a friendly, web-based, interactive segmentation tool that allows segmentation tasks to be assigned to many users, and Ask’nSeek, a game with a purpose designed for object detection and segmentation. The two main contributions of this paper are: (i) We use the results of Click’n’Cut campaigns with different groups of users to examine and quantify the crowdsourcing loss incurred when an interactive segmentation task is assigned to paid crowd-workers, comparing their results to the ones obtained when computer vision experts are asked to perform the same tasks. (ii) Since interactive segmentation tasks are inherently tedious and prone to fatigue, we compare the quality of the results obtained with Click’n’Cut with the ones obtained using a (fun, interactive, and potentially less tedious) game designed for the same purpose. We call this contribution the assessment of the gamification loss, since it refers to how much quality of segmentation results may be lost when we switch to a game-based approach to the same task. We demonstrate that the crowdsourcing loss is significant when using all the data points from workers, but decreases substantially (and becomes comparable to the quality of expert users performing similar tasks) after performing a modest amount of data analysis and filtering out of users whose data are clearly not useful. We also show that – on the other hand – the gamification loss is significantly more severe: the quality of the results drops roughly by half when switching from a focused (yet tedious) task to a more fun and relaxed game environment.     

Privacy Preserving Geo-Linkage in the Big Urban Data Era

Big data technologies and a range of Government open data initiatives provide the basis for discovering new insights into cities; how they are planned, how they managed and the day-to-day challenges they face in health, transport and changing population profiles. The Australian Urban Research Infrastructure Network (AURIN – www.aurin.org.au) project is one example of such a big data initiative that is currently running across Australia. AURIN provides a single gateway providing online (live) programmatic access to over 2000 data sets from over 70 major and typically definitive data-driven organizations across federal and State government, across industry and across academia. However whilst open (public) data is useful to bring data-driven intelligence to cities, more often than not, it is the data that is not-publicly accessible that is essential to understand city challenges and needs. Such sensitive (unit-level) data has unique requirements on access and usage to meet the privacy and confidentiality demands of the associated organizations. In this paper we highlight a novel geo-privacy supporting solution implemented as part of the AURIN project that provides seamless and secure access to individual (unit-level) data from the Department of Health in Victoria. We illustrate this solution across a range of typical city challenges in localized contexts around Melbourne. We show how unit level data can be combined with other data in a privacy-protecting manner. Unlike other secure data access and usage solutions that have been developed/deployed, the AURIN solution allows any researcher to access and use the data in a manner that meets all of the associated privacy and confidentiality concerns, without obliging them to obtain ethical approval or any other hurdles that are normally put in place on access to and use of sensitive data. This provides a paradigm shift in secure access to sensitive data with geospatial content.     

Augmented reality system to assist inexperienced pool players

Computational Visual Media - Pool and billiards are amongst a family of games played on a table with six pockets along the rails. This paper presents an augmented reality tool designed to assist...     

The MAC method

In this article recent advances in the Marker and Cell (MAC) method will be reviewed. The MAC technique dates back to the early 1960s at the Los Alamos Laboratories and this article starts with a historical review, and then a brief discussion of related techniques. Improvements since the early days of MAC (and the Simplified MAC - SMAC) include automatic time-stepping, the use of the conjugate gradient method to solve the Poisson equation for the corrected velocity potential, greater efficiency through stripping out the virtual particles (markers) other than those near the free surface, and more accurate approximations of the free surface boundary conditions, the addition of bounded high accuracy upwinding for the convected terms (thereby being able to solve higher Reynolds number flows), and a (dynamics) flow visualization facility. More recently, effective techniques for surface and interfacial flows and, in particular, for accurately tracking the associated surface(s)/interface(s) including moving contact angles have been developed. This article will concentrate principally on a three-dimensional version of the SMAC method. It will eschew both code verification and model validation; instead it will emphasize the applications that the MAC method can solve, from multiphase flows to rheology.     

LEGClust- a clustering algorithm based on layered entropic subgraphs.

Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity measures are distance measures. The derived proximity matrices can be used to build graphs, which provide the basic structure for some clustering methods. We present here a new proximity matrix based on an entropic measure and also a clustering algorithm (LEGClust) that builds layers of subgraphs based on this matrix, and uses them and a hierarchical agglomerative clustering technique to form the clusters. Our approach capitalizes on both a graph structure and a hierarchical construction. Moreover, by using entropy as a proximity measure we are able, with no assumption about the cluster shapes, to capture the local structure of the data, forcing the clustering method to reflect this structure. We present several experiments on artificial and real data sets that provide evidence on the superior performance of this new algorithm when compared with competing ones.     

Dynamic flow‐based particle splitting in smoothed particle hydrodynamics

In this work, a dynamic procedure for local particle refinement to be used in smoothed particle hydrodynamics (SPH) is presented. The algorithm is able to consistently produce successive levels of particle splitting in accordance to a flow‐based criterion. It has been applied together with accurate and robust formulations for variable spatial resolution in the framework of a semi‐implicit, truly incompressible scheme for SPH. Different test cases have been considered to assess the capabilities and advantages of the proposed procedure, namely, the laminar flow around circular and square obstacles in a plane channel for various regimes. Such flow cases entail the simulation of attached and separated shear layers, recirculating flow, vortex shedding and surface discontinuities. The results obtained for two levels of particle splitting have demonstrated that significant improvements may be obtained with respect to uniform particle spacing solutions in a variety of situations, thus presenting an excellent trade‐off between accuracy and computational cost. Copyright © 2015 John Wiley & Sons, Ltd.     

Preconcentration and Voltammetric Determination of Mercury(II) at a Chemically Modified Glassy Carbon Electrode

In this work, the organic compound 2-mercaptobenzimidazole was covalently bound on the surface of a glassy carbon rod, via silanization, yielding a material capable of selectively complexing Hg(2+) ions. This material was applied as an electrode for voltammetric determination of mercury(II) following its nonelectrolytic preconcentration. After exchanging the medium, the voltammetric measurements were carried out by anodic stripping in the differential pulse mode (pulse amplitude, 50 mV; scan rate, 1.25 mV s(-)(1)) using 10(-)(2) mol L(-)(1) NaSCN solution as supporting electrolyte. An anodic stripping peak was obtained at 0.06 V (vs SCE) by scanning the potential from -0.3 to +0.3 V. After a 5 min preconcentration period in a pH 4.0 Hg(2+) solution, this electrode shows increasing voltammetric response in the range 0.1-2.2 μg mL(-)(1), with a relative standard deviation of 5% and a practical detection limit of 0.1 μg mL(-)(1) (5.0 × 10(-)(7) mol dm(-)(3)). Compared with the conventional stripping approach, this chemically modified glassy carbon electrode procedure presented good discrimination against interference from Cu(II) in up to 10-fold molar excess.     

Post-processing and visualization techniques in 2D boundary element analysis

Most post-processors for boundary element (BE) analysis use an auxiliary domain mesh to display domain results, working against the profitable modelling process of a pure boundary discretization. This paper introduces a novel visualization technique which preserves the basic properties of the boundary element methods. The proposed algorithm does not require any domain discretization and is based on the direct and automatic identification of isolines. Another critical aspect of the visualization of domain results in BE analysis is the effort required to evaluate results in interior points. In order to tackle this issue, the present article also provides a comparison between the performance of two different BE formulations (conventional and hybrid). In addition, this paper presents an overview of the most common post-processing and visualization techniques in BE analysis, such as the classical algorithms of scan line and the interpolation over a domain discretization. The results presented herein show that the proposed algorithm offers a very high performance compared with other visualization procedures.