1,230 research outputs found

    Ambiguity of Underwater Color Measurement and Color-based Habitat Classification

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    The paper discusses ambiguities in recording color underwater. Routinely collected RGB imagery can be used for classification and recognition utilizing the proposed probabilistic approach. The device for collection of spectral signatures, necessary for this approach is described

    Probabilistic Reconstruction of Color for Species’ Classification Underwater

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    Color is probably the most informative cue for object recognition and classification in natural scenes. Difference in shades can indicate to the biologist the potential for diversity of species or stress on the habitats. However, severe color distortions may occur in underwater imagery due to wavelength-dependent attenuation of light. Affordable tri-chromatic sensors are used to record the ambient light condition and color correct the imagery, but results show that this approach works reliably only under highly controllable conditions. This paper proposes an approach that combines hyperspectral data collected for the object of interest, hardware properties of the imaging sensor, and exterior conditions (optical properties of water and illumination) with tri-chromatic underwater imagery. Due to ambiguity of color reconstruction underwater, demonstrated in the paper, a probabilistic approach is used for classification that allows the identification of the object of interest from other objects

    Usage of Videomosaic for Computer Aided Analysis of North Sea Hard Bottom Underwater Video for Baseline Study of Offshore Windmill Park

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    Windmill park on the open North Sea coast at Hävsul area in Norway is one of the first in the world to be build on such extreme high-energy coast. To determine possible environmental impact of this project, baseline study was performed in 2010-2011. Two areas, impacted (area where windmill park is planned to be build) and reference were chosen. For hard bottoms work class ROV was used to take underwater video, as no traditional sampling methods are suitable for such environment and depths. The system was equipped with powerful (400 Watt) xenon lights, USBL navigation and HDTV color camera. For video analysis videomosaicing approach was used. Combining overlapping frames into a single picture allows include in the analysis all visual information, and avoid over counting due to the possible presence of the same feature in the number of differnt frames. Bottom fauna and flora in the area include highly heterogenic small patches of various red algae, encrusting algae and encrusting animals. For lesser depths kelp “forests” are common, some megabenthos species are also present. Due to extreme patchiness of the bottom views, it is difficult to process them manually. To overcome this problem computer aided analysis method was developed. Computer aided videomosaics analysis method used for this study is based on color differences of different bottom features. After manually creating training color pallets for different features, it is possible to process large amount of visual data obtaining repeatable and reliable quantitative estimations on the coverage. Additional benefits of videomosaickning are extended abilities to manipulate visual data, what allows more accurate manual estimation of certain features, such as counts of mega benthos species individuals. Although initial study was successful and color based features extraction approach proved to be robust and accurate, it can’t reliably separate certain features (for example, different red algae species). Additional researches on implementing textures and shapes based analysis are needed

    Natural discretizations for the divergence, gradient, and curl on logically rectangular grids

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    AbstractThis is the first in series of papers creating a discrete analog of vector analysis on logically rectangular, nonorthogonal, nonsmooth grids. We introduce notations for 2-D logically rectangular grids, describe both cell-valued and nodal discretizations for scalar functions, and construct the natural discretizations of vector fields, using the vector components normal and tangential to the cell boundaries. We then define natural discrete analogs of the divergence, gradient, and curl operators based on coordinate invariant definitions and interpret these formulas in terms of curvilinear coordinates, such as length of elements of coordinate lines, areas of elements of coordinate surfaces, and elementary volumes.We introduce the discrete volume integral of scalar functions, the discrete surface integral, and a discrete analog of the line integral and prove discrete versions of the main theorems relating these objects. These theorems include the following: the discrete analog of relationship div A→ = 0 if and only if A→ = curl B→; curl A→ = 0 if and only if A→ = grad ϕ; if A→ = grad ϕ, then the line integral does not depend on path; and if the line integral of a vector function is equal to zero for any closed path, then this vector is the gradient of a scalar function.Last, we define the discrete operators DIV, GRAD, and CURL in terms of primitive differencing operators (based on forward and backward differences) and primitive metric operators (related to multiplications of discrete functions by length of edges, areas of surfaces, and volumes of 3-D cells). These formulations elucidate the structure of the discrete operators and are useful when investigating the relationships between operators and their adjoints

    A proof of a Shilnikov theorem for C^1-smooth dynamical systems

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    Dynamical systems with a homoclinic loop to a saddle equilibrium state are considered. Andronov and Leontovich have shown (see [1939], [1959]) that a generic bifurcation of a two-dimensional C1-smooth dynamical system with a homoclinic loop leads to appearance of a unique periodic orbit. This result holds true in the multi-dimensional setting if some additional conditions are satisfied, which was proved by Shilnikov [1962, 1963, 1968] for the case of dynamical systems of sufficiently high smoothness. In the present paper we reprove the Shilnikov theorem for dynamical systems in C1

    Filling Gaps in Earthworm Digital Diversity in Northern Eurasia from Russian-language Literature

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    Data availability for certain groups of organisms (ecosystem engineers, invasive or protected species, etc.) is important for monitoring and making predictions in changing environments. One of the most promising directions for research on the impact of changes is species distribution modelling. Such technologies are highly dependent on occurrence data of high quality (Van Eupen et al. 2021). Earthworms (order Crassiclitellata) are a key group of organisms (Lavelle 2014), but their distribution around the globe is underrepresented in digital resources. Dozens of earthworm species, both widespread and endemic, inhabit the territory of Northern Eurasia (Perel 1979), but extremely poor data on them is available through global biodiversity repositories (Cameron 2018). There are two main obstacles to data mobilisation. Firstly, studies of the diversity of earthworms in Northen Eurasia have a long history (since the end of the nineteenth century) and were conducted by several generations of Soviet and Russian researchers. Most of the collected data have been published in "grey literature", now stored only in a few libraries. Until recently, most of these remained largely undigitised, and some are probably irretrievably lost. The second problem is the difference in the taxonomic checklists used by Soviet and European researchers. Not all species and synonyms are included in the GBIF (Global Biodiversity Information Facility) Backbone Taxonomy. As a result, existing earthworm species distribution models (Phillips 2019) potentially miss a significant amount of data and may underestimate biodiversity, and predict distributions inaccurately. To fill this gap, we collected occurrence data from the Russian language literature (published by Soviet and Russian researchers) and digitised species checklists, keeping the original scientific names.To find relevant literature, we conducted a keyword search for "earthworms" and "Lumbricidae" through the Russian national scientific online library eLibrary and screened reference lists from the monographs of leading Soviet and Russian soil zoologist Tamara Perel (Vsevolodova-Perel 1997, Perel 1979). As a result, about 1,000 references were collected, of which 330 papers had titles indicating the potential to contain data on earthworm occurrences. Among these, 219 were found as PDF files or printed papers. For dataset compilation, 159 papers were used; the others had no exact location data or duplicated data contained in other papers. Most of the sources were peer-reviewed articles (Table 1). A reference list is available through Zenodo (Ivanova et al. 2023).The earliest publication we could find dates back to 1899, by Wilhelm Michaelsen. The most recent publication is 2023. About a third of the sources were written by systematists Iosif Malevich and Tamara Perel. Occurrence data were extracted and structured according to the Darwin Core standard (Wieczorek et al. 2012). During the data digitisation process, we tried to include as much primary information as possible. Only one tenth of the literature occurrences contained the geographic coordinates of locations provided by the authors. The remaining occurrences were manually georeferenced using the point-radius method (Wieczorek et al. 2010).The resulting occurrence dataset Earthworm occurrences from Russian-language literature (Shashkov et al. 2023) was published through the Global Biodiversity Information Facility portal. It contains 5304 occurrences of 117 species from 27 countries (Fig. 1).To improve the GBIF Backbone Taxonomy, we digitised two catalogues of earthworm species published for the USSR (Perel 1979) and Russian Federation (Vsevolodova-Perel 1997) by Tamara Perel. Based on these monographs, three checklist datasets were published through GBIF (Shashkov 2023b, 124 records; Shashkov 2023c, 87 records; Shashkov 2023a, 95 records). Now we work towards including these names in the GBIF Backbone so that all species names can be matched and recorded exactly as mentioned in papers published by Soviet and Russian researchers
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