FRONTIERS IN INVASIVE SPECIES DISTRIBUTION MODELING (iSDM): ASSESSING EFFECTS OF ABSENCE DATA, DISPERSAL CONSTRAINTS, STAGE OF INVASION AND SPATIAL DEPENDENCE

Successful management of biological invasions depends heavily on our ability to predict their geographic ranges and potential habitats. Species distribution modeling (SDM) provides a methodological framework to predict spatial distributions of organisms but the unique aspects of modeling invasive species have been largely ignored in previous applications. Here, three unresolved challenges facing invasive species distribution modeling (iSDM) were examined in an effort to increase prediction accuracy and improve ecological understanding of actual and potential distributions of biological invasions. The effects of absence data and dispersal constraints, stage of invasion, and spatial dependence were assessed, using an extensive collection of field-based data on the invasive forest pathogen Phytophthora ramorum. Spatial analyses were based on a range of statistical techniques (generalized linear models, classification trees, maximum entropy, ecological niche factor analysis, multicriteria evaluation) and four groups of environmental parameters that varied in space and time: atmospheric moisture and temperature, topographic variability, abundance and susceptibility of host vegetation, and dispersal pressure. Results show that incorporating data on species absence and dispersal limitations is crucial not only to avoid overpredictions of the actual invaded range in a specific period of time but also for ecologically meaningful evaluation of iSDMs. When dispersal and colonization cannot be estimated explicitly, e.g. via dispersal kernels of propagule pressure, spatial dependence measured as spatial autocorrelation at multiple scales can serve as an important surrogate for dynamic processes that explain ecological mechanisms of invasion. If the goal is to identify habitats at potential risk of future spread, the stage of invasion should be considered because it represents the degree to which an organism is at equilibrium with its environment and limits the extent to which occurrence observations provide a sample of the species ecological niche. This research provides insight into several key principles of the SDM discipline, with implications for practical management of biological invasions

Entity Linking to Wikipedia : Grounding entity mentions in natural language text using thematic context distance and collective search

This thesis proposes new methods for entity linking in natural language text that assigns entity mentions in unstructured natural language text to the semi-structured encyclopedia Wikipedia. Doing so, entity linking grounds a mention to an encyclopedic entry in Wikipedia and embeds it into this Linked-Open-Data hub. This enables a higher level view on single documents, provides hints for further reading and may be used to add details from other sources. Furthermore, enriching text documents with such links simultaneously resolves the ambiguity of entity names. This ambiguity is an unsolved challenge for many text mining applications: one entity may be designated by a multitude of names and every mention may denote a multitude of entities. Resolving the ambiguity of entity names is thus a crucial step for entity based retrieval, an open problem for most information retrieval and extraction tasks. For instance, search engines relying on heuristic string matches often retrieve irrelevant results as they can not satisfyingly resolve ambiguity. Moreover, there is a huge number of entity mentions that can not be linked to Wikipedia since albeit of its size, Wikipedia has a restricted coverage. Earlier and current work often ignored this and consequently all mentions of uncovered entities. Other approaches handle only entity mentions of specific types or are focussed on English as target language. Apart from such restrictions, no method achieves perfect linking performance. These are the tasks approached in this thesis. We introduce new methods for candidate entity retrieval and candidate entity consolidation, the key components to recall and precision, exploiting both the vast amount of structured and unstructured information stored in Wikipedia. First, we propose a new contextual similarity measure based on latent topic distributions inferred from unstructured natural language text. We show that this thematic distance between mention and candidate entity contexts yields a lower linking error rate than purely word based distances. Being language independent, this method enables high performance entity linking in previously neglected languages such as German and French. This approach is especially suitable, albeit not restricted to link person names, the class of mentions with highest ambiguity. We next propose a new candidate retrieval method to enable successful entity linking also for other entities that are not referenced canonically or exhibit the thematic coherence of persons. We introduce collective search that uses the structured information encoded in Wikipedia’s hyperlink graph to arrive at sets of strongly related candidate entities. This enables us to better handle synonymy, one of the hardest problems in entity linking and not thoroughly treated in previous work. We emphasize on general applicability and evaluate this method on a broad collection of benchmark corpora both in a supervised as well as in an unsupervised setting. We show that candidate enhancement through collective search increases linking performance on nearly all of these corpora and that our method is the most stable compared to other state-of-the-art approaches. Presenting the first unification of diverse performance measures, we also make a step forward to the comparability of entity linking methods. In conclusion, we provide state-of-the-art entity linking methods for nearly all of the current use cases. When it comes to fine-tuning, we note that entity linking has subjective aspects and adaptions may be necessary depending on the task at hand

Two and three dimensional segmentation of multimodal imagery

The role of segmentation in the realms of image understanding/analysis, computer vision, pattern recognition, remote sensing and medical imaging in recent years has been significantly augmented due to accelerated scientific advances made in the acquisition of image data. This low-level analysis protocol is critical to numerous applications, with the primary goal of expediting and improving the effectiveness of subsequent high-level operations by providing a condensed and pertinent representation of image information. In this research, we propose a novel unsupervised segmentation framework for facilitating meaningful segregation of 2-D/3-D image data across multiple modalities (color, remote-sensing and biomedical imaging) into non-overlapping partitions using several spatial-spectral attributes. Initially, our framework exploits the information obtained from detecting edges inherent in the data. To this effect, by using a vector gradient detection technique, pixels without edges are grouped and individually labeled to partition some initial portion of the input image content. Pixels that contain higher gradient densities are included by the dynamic generation of segments as the algorithm progresses to generate an initial region map. Subsequently, texture modeling is performed and the obtained gradient, texture and intensity information along with the aforementioned initial partition map are used to perform a multivariate refinement procedure, to fuse groups with similar characteristics yielding the final output segmentation. Experimental results obtained in comparison to published/state-of the-art segmentation techniques for color as well as multi/hyperspectral imagery, demonstrate the advantages of the proposed method. Furthermore, for the purpose of achieving improved computational efficiency we propose an extension of the aforestated methodology in a multi-resolution framework, demonstrated on color images. Finally, this research also encompasses a 3-D extension of the aforementioned algorithm demonstrated on medical (Magnetic Resonance Imaging / Computed Tomography) volumes

Untangling hotel industry’s inefficiency: An SFA approach applied to a renowned Portuguese hotel chain

The present paper explores the technical efficiency of four hotels from Teixeira Duarte Group - a renowned Portuguese hotel chain. An efficiency ranking is established from these four hotel units located in Portugal using Stochastic Frontier Analysis. This methodology allows to discriminate between measurement error and systematic inefficiencies in the estimation process enabling to investigate the main inefficiency causes. Several suggestions concerning efficiency improvement are undertaken for each hotel studied.info:eu-repo/semantics/publishedVersio

Semantic radical consistency and character transparency effects in Chinese: an ERP study

BACKGROUND: This event-related potential (ERP) study aims to investigate the representation and temporal dynamics of Chinese orthography-to-semantics mappings by simultaneously manipulating character transparency and semantic radical consistency. Character components, referred to as radicals, make up the building blocks used dur...postprin

The neurobiological basis of inter-individual variability in visual perception

Visual perception is the conscious experience that is unique to each individual. However, conventional neuroscience studies tend to focus on the commonality in visual perception across different individuals and fail to address the key properties of any conscious experience - its individuality and subjectivity. In my thesis, I investigated the neurobiological basis of perceptual variability across healthy human adults, through a combined approach of psychophysics, in-vivo MR imaging, in-vitro histological imaging, and computational modeling. I found that perception of local and global visual features, as assessed respectively from visual discrimination of local feature details and visual illusion induced by global feature contexts, exhibits a ten-fold inter-individual variability that correlates with the morphology of primary visual cortex. Specifically, an increase in the surface area of primary visual cortex is associated with a shift in the scope of visual feature perception from global-context-oriented to local-detail-oriented, where individuals with smaller visual cortical surface area experience stronger visual illusion and individuals with larger visual cortical surface area perform more accurate visual discrimination. Intriguingly, an increase in the thickness of primary visual cortex has the opposite impact, where visual discrimination is less accurate at visual field locations corresponding to thicker parts of primary visual cortex. The functional impact that visual cortical anatomy exerts on visual feature perception is recapitulated in visual neural selectivity. I found that in individuals with larger surface area of primary visual cortex, visual cortical neurons exhibit higher selectivity and respond to a smaller, localised visual field range. By contrast, at thicker parts of primary visual cortex, visual cortical neurons exhibit lower selectivity and respond to a larger, globalised visual field range. The opposite functional impacts exhibited by the two morphological dimensions, the surface area and the thickness, of primary visual cortex can nonetheless be unified under the framework of intracortical scaling. I found that the scaling of intracortical connectivity with visual cortical morphology shifts the scope of both visual feature perception and visual neural selectivity between global- and local-oriented. Together these findings revealed that the individuality in visual feature perception arises neurobiologically from the variability in visual cortical morphology, through the mediation of intracortical connectivity and visual neural selectivity

Communities at a Crossroads. Material semiotics for online sociability in the fade of cyberculture

How to conceptualize online sociability in the 21st century? To answer this question, Communities at a Crossroads looks back at the mid-2000s. With the burst of the creative-entrepreneur alliance, the territorialization of the internet and the commercialization of interpersonal ties, that period constituted a turning point for digital communitarian cultures. Many of the techno-libertarian culture\u2019s utopias underpinning the ideas for online sociability faced systematic counter evidence. This change in paradigm has still consequences today. Avoiding both empty invocations of community and swift conclusions of doom, Annalisa Pelizza investigates the theories of actions that have underpinned the development of techno-social digital assemblages after the \u2018golden age\u2019 of online communities. Communities at a Crossroads draws upon the analysis of Ars Electronica\u2019s Digital Communities archive, which is the largest of its kind worldwide, and in doing so presents a multi-faceted picture of internet sociability between the two centuries. Privileging an anti-essentialist, performative approach over sociological understandings of online communities, Communities at a Crossroads proposes a radical epistemological turn. It argues that in order to conceptualize contemporary online sociability, we need first to abandon the techno-libertarian communalist rhetoric. Then, it is necessary to move beyond the foundational distinction between Gemeinschaft and Gesellschaft, and adopt a material semiotic approach. In the end, we might have to relinquish the effort to define online or digital communities and engage in more meaningful mapping exercises

Spatial and Temporal Variation of Reef Fish Assemblages in the Galapagos Archipelago: The Influence of Biogeography, Management and ENSO

I investigated the spatial and temporal distribution of Galapagos fish assemblages using diversity, abundance, and length data from baited remote underwater stereo-video systems. I generated information describing the ecology and status of finfish populations in relation to key natural and anthropogenic pressures. This information has local and global implications, including highlighting the unique values of the Galapagos archipelago for biogeography research. I suggest possible management actions to improve the status of local fish populations

Characterising and modeling the co-evolution of transportation networks and territories

The identification of structuring effects of transportation infrastructure on territorial dynamics remains an open research problem. This issue is one of the aspects of approaches on complexity of territorial dynamics, within which territories and networks would be co-evolving. The aim of this thesis is to challenge this view on interactions between networks and territories, both at the conceptual and empirical level, by integrating them in simulation models of territorial systems.Comment: Doctoral dissertation (2017), Universit\'e Paris 7 Denis Diderot. Translated from French. Several papers compose this PhD thesis; overlap with: arXiv:{1605.08888, 1608.00840, 1608.05266, 1612.08504, 1706.07467, 1706.09244, 1708.06743, 1709.08684, 1712.00805, 1803.11457, 1804.09416, 1804.09430, 1805.05195, 1808.07282, 1809.00861, 1811.04270, 1812.01473, 1812.06008, 1908.02034, 2012.13367, 2102.13501, 2106.11996

Human mobility: Models and applications

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordRecent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.US Army Research Offic