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Proceedings of the 9th Open German-Russian Workshop on Pattern Recognition and Image Understanding
(2015)
The Proceedings of the 9th Open German-Russian Workshop on Pattern Recognition and Image Understanding include publications (extended abstracts), that cover but are not limited to the following topics: - Mathematical Theory of Pattern Recognition, Image and Speech Processing, Analysis, Recognition and Understanding. - Cognitive Technologies, Information Technologies, Automated Systems and Software for Pattern Recognition, Image, Speech and Signal Processing, Analysis and Understanding - Databases, Knowledge Bases, and Linguistic Tools - Special-Purpose Architectures, Software and Hardware Tools - Vision and Sensor Data Interpretation for Robotics - Industrial, Medical, Multimedia and Other Applications - Algorithms, Software, Automated Systems and Information Technologies in Bioinformatics and Medical Informatics. The workshop took place from December 1st-5th, 2014, at the University of Koblenz-Landau in Koblenz, Germany.
A fundamental understanding of attachment of engineered nanoparticles to environmentalrnsurfaces is essential for the prediction of nanoparticle fate and transport in the environment.
The present work investigates the attachment of non-coated silver nanoparticles and citraterncoated silver nanoparticles to different model surfaces and environmental surfaces in thernpresence and absence of humic acid. Batch sorption experiments were used for this investigation.
The objective of this thesis was to investigate how silver nanoparticles interactrnwith surfaces having different chemical functional groups. The effect of presence of HA, on the particle-surface interactions was also investigated. In the absence of humic acid, nanoparticle-surface interactions or attachment was influencedrnby the chemical nature of the interacting surfaces. On the other hand, in the presence ofrnhumic acid, nanoparticle-surface attachment was influenced by the specific surface area of the sorbent surfaces. The sorption of non-coated silver nanoparticles and citrate coatedrnnanoparticles to all the surfaces was nonlinear and best described by Langmuir isotherm, indicating monolayer sorption of nanoparticles on to the surfaces. This can be explained as due to the blocking effect generated by the particle-particle repulsion. In the presence of humic acid, sorption of nanoparticles to the surfaces was linear. When the humic acid was present in the interacting medium, both the nanoparticles and surfaces were getting coated with humic acid and this masks the chemical functionalities of the surfaces. This leads to the change in particle-surface interactions, in the presence of humic acid. For the silver nanoparticle sorption from an unstable suspension, the sorption isotherms did not follow any classical sorption models, suggesting interplay between aggregation and sorption. Citrate coated silver nanoparticles and humic acid coated silver nanoparticles showed arndepression in sorption compared to the sorption of non-coated silver nanoparticles. In therncase of citrate coated silver nanoparticles the decrease in sorption can be explained by thernmore negative zeta potential of citrate coated nanoparticles compared to non-coated ones. For humic acid coated nanoparticles the sorption depression can be due to the steric hindrance caused by the free humic acid molecules which may coat the sorbent surface or due to the competition for sorption sites between the nanoparticle and free humic acid molecules present in the suspension. Thus nanoparticle surface chemistry is an important factor that determines the attachment of nanoparticles towards surfaces and it makes the characterization of nanoparticle surface an essential step in the study of their fate in the environment.
Another aim of this study was to introduce the potential of chemical force microscopy for nanoparticle surface characterization. With the use of this technique, it was possible to distinguish between bare silver nanoparticles, citrate coated silver nanoparticles, and humic acid coated silver nanoparticles. This was possible by measuring the adhesion forces between the nanoparticles and five different AFM probes having different chemical functionalization.
One task of executives and project managers in IT companies or departments is to hire suitable developers and to assign them to suitable problems. In this paper, we propose a new technique that directly leverages previous work experience of developers in a systematic manner. Existing evidence for developer expertise based on the version history of existing projects is analyzed. More specifically, we analyze the commits to a repository in terms of affected API usage. On these grounds, we associate APIs with developers and thus we assess API experience of developers. In transitive closure, we also assess programming domain experience.
For decades a worldwide decline of biological diversity has been reported. Landscapes are influenced by several kinds of anthropogenic disturbances. Agricultural land use, application of fertilizers and pesticides and the removal of corridors simplify and homogenize a landscape whereas others like road constructions lead to fragmentation. Both kinds lead to a constraint of habitats, reduce living environment and gene pool, hinder gene flow and change the functional characteristics of species. Furthermore, it facilitates the introduction of alien species. On the other hand, disturbances of different temporal and spatial dimensions lead to a more diverse landscape because they prevent competitive exclusion and create niches where species are able to coexist.
This study focuses on the complexity of disturbance regimes and its influence on phytodiversity. It differs from other studies that mostly select one or few disturbance types in including all identifiable disturbances. Data were derived from three study sites in the north of Bavaria and are subject to different land-use intensities. Two landscapes underlie agriculture and forestry, of which one is intensively used and the second one rather moderate and small-scaled. The third dataset was collected on an actively used military training area. The first part of the study deals with the influence of disturbance regimes on phytodiversity, first with the focus on military disturbances, afterwards in comparison with the agricultural landscapes. The second part examines the influence of disturbance regimes on red-listed species, the distribution of neophytes and generalist plant species and the homogenization of the landscape. All analyses were conducted on landscape and local scale.
A decisive role was played by the variety of disturbance types, especially in different temporal and spatial dimensions and not by single kinds of disturbances, which significantly was proven in the military training area with its multiple and undirected disturbance regime. Homogeneous disturbance regimes that typically are found in agricultural landscapes led to a reduced species number. On local scale, the abiotic heterogeneity which originated of recent and historical disturbances superimposed the positive effects of disturbance regimes, whereas dry and nutrient-poor sites showed a negative effect. Due to a low tree density and moderate treatment species numbers were significantly higher in forest in the training area than in the two agricultural landscapes.
Numbers of red-listed species were positively correlated to the total number of species in all three sites. However, the military training area showed a significantly higher abundance within the area in comparison to the agricultural landscapes where rare species were mostly found on marginal strips. Furthermore, numbers of neophytes and generalist species were lower and consequently homogenization.
In conclusion, the military training area is an ideal landscape from a nature conservation point of view. The moderately used agricultural area showed high species numbers and agricultural productivity. However, yield is too low to withstand either abandonment or land-use intensification.
In the new epoch of Anthropocene, global freshwater resources are experiencing extensive degradation from a multitude of stressors. Consequently, freshwater ecosystems are threatened by a considerable loss of biodiversity as well as substantial decrease in adequate and secured freshwater supply for human usage, not only on local scales, but also on regional to global scales. Large scale assessments of human and ecological impacts of freshwater degradation enable an integrated freshwater management as well as complement small scale approaches. Geographic information systems (GIS) and spatial statistics (SS) have shown considerable potential in ecological and ecotoxicological research to quantify stressor impacts on humans and ecological entitles, and disentangle the relationships between drivers and ecological entities on large scales through an integrated spatial-ecological approach. However, integration of GIS and SS with ecological and ecotoxicological models are scarce and hence the large scale spatial picture of the extent and magnitude of freshwater stressors as well as their human and ecological impacts is still opaque. This Ph.D. thesis contributes novel GIS and SS tools as well as adapts and advances available spatial models and integrates them with ecological models to enable large scale human and ecological impacts identification from freshwater degradation. The main aim was to identify and quantify the effects of stressors, i.e climate change and trace metals, on the freshwater assemblage structure and trait composition, and human health, respectively, on large scales, i.e. European and Asian freshwater networks. The thesis starts with an introduction to the conceptual framework and objectives (chapter 1). It proceeds with outlining two novel open-source algorithms for quantification of the magnitude and effects of catchment scale stressors (chapter 2). The algorithms, i.e. jointly called ATRIC, automatically select an accumulation threshold for stream network extraction from digital elevation models (DEM) by assuring the highest concordance between DEM-derived and traditionally mapped stream networks. Moreover, they delineate catchments and upstream riparian corridors for given stream sampling points after snapping them to the DEM-derived stream network. ATRIC showed similar or better performance than the available comparable algorithms, and is capable of processing large scale datasets. It enables an integrated and transboundary management of freshwater resources by quantifying the magnitude of effects of catchment scale stressors. Spatially shifting temporal points (SSTP), outlined in chapter 3, estimates pooled within-time series (PTS) variograms by spatializing temporal data points and shifting them. Data were pooled by ensuring consistency of spatial structure and temporal stationarity within a time series, while pooling sufficient number of data points and increasing data density for a reliable variogram estimation. SSTP estimated PTS variograms showed higher precision than the available method. The method enables regional scale stressors quantification by filling spatial data gaps integrating temporal information in data scarce regions. In chapter 4, responses of the assumed climate-associated traits from six grouping features to 35 bioclimatic indices for five insect orders were compared, their potential for changing distribution pattern under future climate change was evaluated and the most influential climatic aspects were identified (chapter 4). Traits of temperature preference grouping feature and the insect order Ephemeroptera exhibited the strongest response to climate as well as the highest potential for changing distribution pattern, while seasonal radiation and moisture were the most influential climatic aspects that may drive a change in insect distribution pattern. The results contribute to the trait based freshwater monitoring and change prediction. In chapter 5, the concentrations of 10 trace metals in the drinking water sources were predicted and were compared with guideline values. In more than 53% of the total area of Pakistan, inhabited by more than 74 million people, the drinking water was predicted to be at risk from multiple trace metal contamination. The results inform freshwater management by identifying potential hot spots. The last chapter (6) synthesizes the results and provides a comprehensive discussion on the four studies and on their relevance for freshwater resources conservation and management.
The intention of this thesis was to characterise the effect of naturally occurring multivalent cations like Calcium and Aluminium on the structure of Soil Organic Matter (SOM) as well as on the sorption behaviour of SOM for heavy metals such as lead.
The first part of this thesis describes the results of experiments in which the Al and Ca cation content was changed for various samples originated from soils and peats of different regions in Germany. The second part focusses on SOM-metal cation precipitates to study rigidity in dependence of the cation content. In the third part the effects of various cation contents in SOM on the binding strength of Pb cations were characterised by using a cation exchange resin as desorption method.
It was found for soil and peat samples as well as precipitates that matrix rigidity was affected by both type and content of cation. The influence of Ca on rigidity was less pronounced than the influence of Al and of Pb used in the precipitation experiments. For each sample one cation content was identified where matrix rigidity was most pronounced. This specific cation content is below the cation saturation as expected by cation exchange capacity. These findings resulted in a model describing the relation between cation type, content and the degree of networking in SOM. For all treated soil and precipitate samples a step transition like glass transition was observed, determined by the step transition temperature T*. It is known from literature that this type of step transition is due to bridges between water molecules and organic functional groups in SOM. In contrast to the glass transition temperature this thermal event is slowly reversing after days or weeks depending on the re-conformation of the water molecules. Therefore, changes of T* with different cation compositions in the samples are explained by the formation of water-molecule-cation bridges between SOM-functional groups. No influence on desorption kinetics of lead for different cation compositions in soil samples was observed. Therefore it can be assumed that the observed changes of matrix rigidity are highly reversible by changing the water status, pH or putting agitation energy by shaking in there.
The publication of freely available and machine-readable information has increased significantly in the last years. Especially the Linked Data initiative has been receiving a lot of attention. Linked Data is based on the Resource Description Framework (RDF) and anybody can simply publish their data in RDF and link it to other datasets. The structure is similar to the World Wide Web where individual HTML documents are connected with links. Linked Data entities are identified by URIs which are dereferenceable to retrieve information describing the entity. Additionally, so called SPARQL endpoints can be used to access the data with an algebraic query language (SPARQL) similar to SQL. By integrating multiple SPARQL endpoints it is possible to create a federation of distributed RDF data sources which acts like one big data store.
In contrast to the federation of classical relational database systems there are some differences for federated RDF data. RDF stores are accessed either via SPARQL endpoints or by resolving URIs. There is no coordination between RDF data sources and machine-readable meta data about a source- data is commonly limited or not available at all. Moreover, there is no common directory which can be used to discover RDF data sources or ask for sources which offer specific data. The federation of distributed and linked RDF data sources has to deal with various challenges. In order to distribute queries automatically, suitable data sources have to be selected based on query details and information that is available about the data sources. Furthermore, the minimization of query execution time requires optimization techniques that take into account the execution cost for query operators and the network communication overhead for contacting individual data sources. In this thesis, solutions for these problems are discussed. Moreover, SPLENDID is presented, a new federation infrastructure for distributed RDF data sources which uses optimization techniques based on statistical information.
Modern agriculture is a dominant land use in Europe, although it has been associated with negative effects on biodiversity in agricultural landscapes. One species-rich insect group in agro-ecosystems is the Lepidoptera (moths and butterflies); however, the populations of a number of Lepidoptera species are currently declining. The aims of this thesis were to assess the amount and structure of field margins in agricultural landscapes, study the effects of realistic field margin input rates of agrochemicals (fertilizer and pesticides) on Lepidoptera, and provide information on moth pollination services.
In general, field margins are common semi-natural habitat elements in agro-ecosystems; however, data on the structure, size, and width of field margins is limited. An assessment in two German agricultural landscapes (4,000 ha each) demonstrated that many of the evaluated field margins were less than 3 m wide (Rhineland‐Palatinate: 85% of margin length; Brandenburg: 45% margin length). In Germany, risk mitigation measures (such as buffer zones) to reduce pesticide inputs to terrestrial non-crop habitats do not have to be established by farmers next to narrow field margins. Thus, narrow field margins receive inputs of agrochemicals, especially via overspray and spray drift. These field margins were used as a development habitat for caterpillars, but the mean abundance of caterpillars was 35 – 60% lower compared with that in meadows. Caterpillars were sensitive to realistic field margin input rates of insecticide (pyrethroid, lambda-cyhalothrin) in a field experiment as well as in laboratory experiments. Moreover, 40% fewer Hadena bicruris eggs were observed on Silene latifolia plants treated with this insecticide compared with control plants, and the flowers of these insecticide-treated plants were less likely to be pollinated by moths. In addition, realistic field margin input rates of herbicides can also affect Lepidoptera. Ranunculus acris L. plants treated with sublethal rates of a sulfonylurea herbicide were used as host plants for Mamestra brassicae L. caterpillars, which resulted in significantly lower caterpillar weights, increased time to pupation, and increased overall development time compared with caterpillars feeding on control plants. These results might have been caused by lower nutritional value of the herbicide-treated plants or increased concentrations of secondary metabolites involved in plant defense. Fertilizer applications slightly increased the caterpillar abundance in the field experiment. However, fertilizers reduce plant diversity in the long term and thus, most likely, also reduce caterpillar diversity.
Moths such as Noctuidae and Sphingidae have been observed to act as pollinators for numerous plant species, including a number of Orchidaceae and Caryophyllaceae. Although in temperate agro-ecosystems moths are less likely to act as the main pollinators for crops, they can pollinate non-crop plants in semi-natural habitats. Currently, the role of moths as pollinators appears to be underestimated, and long-term research focusing on ecosystems is necessary to address temporal fluctuations in their abundance and community composition.
Lepidoptera represent a diverse organism group in agricultural landscapes and fulfill essential ecosystem services, such as pollination. To better protect moths and butterflies, agrochemical inputs to (narrow) field margins habitats should be reduced, for example, via risk mitigation measures and agro-environmental schemes.
101worker is the modular knowledge engineering component of the 101companies project. It has developed maintainability and performance problems due to growing organically, rather than following best software design practices. This thesis lays out these problems, drafts a set of requirements for refactoring the system and then describes and analyzes the resulting implementation. The solution involves collation of scattered and redundant information, setup of unit and functional test suites and incrementalization of the bus architecture of 101worker.
The formulation of the decoding problem for linear block codes as an integer program (IP) with a rather tight linear programming (LP) relaxation has made a central part of channel coding accessible for the theory and methods of mathematical optimization, especially integer programming, polyhedral combinatorics and also algorithmic graph theory, since the important class of turbo codes exhibits an inherent graphical structure. We present several novel models, algorithms and theoretical results for error-correction decoding based on mathematical optimization. Our contribution includes a partly combinatorial LP decoder for turbo codes, a fast branch-and-cut algorithm for maximum-likelihood (ML) decoding of arbitrary binary linear codes, a theoretical analysis of the LP decoder's performance for 3-dimensional turbo codes, compact IP models for various heuristic algorithms as well as ML decoding in combination with higher-order modulation, and, finally, first steps towards an implementation of the LP decoder in specialized hardware. The scientific contributions are presented in the form of seven revised reprints of papers that appeared in peer-reviewed international journals or conference proceedings. They are accompanied by an extensive introductory part that reviews the basics of mathematical optimization, coding theory, and the previous results on LP decoding that we rely on afterwards.