A system for beach video-monitoring: Beachkeeper plus

A suitable knowledge of coastal systems, of their morphodynamic characteristics and their response to storm events and man-made structures is essential for littoral conservation and management. Nowadays webcams represent a useful device to obtain information from beaches. Video-monitoring techniques are generally site specific and softwares working with any image acquisition system are rare. Therefore, this work aims at submitting theory and applications of an experimental video monitoring software: Beachkeeper plus, a freeware non-profit software, can be employed and redistributed without modifications. A license file is provided inside software package and in the user guide. Beachkeeper plus is based on Matlab ® and it can be used for the analysis of images and photos coming from any kind of acquisition system (webcams, digital cameras or images downloaded from internet), without any a-priori information or laboratory study of the acquisition system itself. Therefore, it could become a useful tool for beach planning. Through a simple guided interface, images can be analyzed by performing georeferentiation, rectification, averaging and variance. This software was initially operated in Pietra Ligure (Italy), using images from a tourist webcam, and in Mar del Plata (Argentina) using images from a digital camera. In both cases the reliability in different geomorphologic and morphodynamic conditions was confirmed by the good quality of obtained images after georeferentiation, rectification and averaging. © 2012 Elsevier Ltd.Fil: Brignone, Massimo. University of Genoa; ItaliaFil: Schiaffino, Chiara F.. University of Genoa; ItaliaFil: Isla, Federico Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Ferrari, Marco. University of Genoa; Itali

Nearshore hydrodynamics and morphology derived from video imagery

Tese de doutoramento, Geologia (Geodinâmica Externa), Universidade de Lisboa, Faculdade de Ciências, 2018The coastal zone is the dynamic interface between the land and the ocean. Natural processes, including wave action, flooding and coastal erosion, often endanger human occupation and the use of the littoral. It is therefore essential to improve our understanding of the physical processes occurring at the coast, particularly those related with coastal morphodynamics. Due to the complexity of the coastal environment, littoral studies should be as comprehensive as possible, covering both hydrodynamic forcing and morphological response. However, conventional in-situ survey methods involve the use of instrumentation which, due to the logistical commitments, do not provide the required time-space scales. Remote sensing methods emerge in this context as an interesting alternative solution to yield simultaneous high temporal frequency and high spatial resolution observations of the nearshore processes. Among others, shore-based video remote sensing systems have been proved, over the last three decades, as a cost-efficient and high-quality tool to support coastal scientists and managers. Video monitoring installations offer excellent spatio-temporal resolutions, in combination with cost-efficient long-term data acquisition. This dissertation aims to present new conceptual models and video imagery tools to assess nearshore morphodynamics. This objective was accomplished through the development of a set of efficient computational tools to extract synoptic hydrodynamic and morphology information from video images. Data used in this work were acquired at five different study sites located worldwide. At three sites, video data were collected from dedicated video systems installed for scientific purpose. Two more additional video data sets were derived from the acquisition of online-streaming surfcams, which are camera infrastructures installed at the coast to provide remote visual information of sea state to surf users. A stand-alone set of algorithm was built to process and to geo-reference the acquired video sequence using already existing software. In addition, the automated processing is set to produce special images, namely Timex Variance and Timestack. A first video-based technique exploited the pixel intensity variation of Timestack images to characterize nearshore hydrodynamics. The standard deviation of pixel intensity was successfully related to the spatial distribution of wave transformation domains. Therefore, shoaling, surf and swash zones could be clearly identified in the nearshore profile covered by the image. This technique provides a new tool to study the nearshore dynamics, as the extent of wave domains can be related with distinctive morphodynamic behaviour. The method can be also directly applied to Variance images, hence it offers the possibility of extending such studies to the alongshore dimension. A second methodology developed in the scope of the present work exploited the use of pixel intensity average of Timestack images to estimate wave breaking height. Breakpoint locations and pixel intensity profiles were used to define the cross-shore breaking pattern length visible on a time-averaged image, here defined as the parameter. A first approach coupled to the available bathymetry to solve a simple conceptual model for finding breaker height. Wave breaking height estimates yield a Normalized Root Mean Square Error (NRMSE) of 14% when compared to numerical model results, for offshore wave heights ranging from 1.6 m to 3.5 m. A second approach proposed the relationship /24 to replace water depth parameter on the simplest wave height calculation formula, which multiplies water depth by the breaker index. The technique can be directly applied on Timex, therefore images from four different sites were used to test its validity, obtaining an NRMSE of about 22% for a wide range of wave heights. A third methodology aimed to investigate the possibility of combining two shorebased remote sensing techniques, 2D terrestrial LiDAR and video imagery to perform detailed beach intertidal topography. 2D LiDAR provided precise shoreline elevation along a cross-shore beach transect, while shoreline contour was detected on Timex images in the alongshore dimension. The dataset from both instruments were complemented to perform 3D beach intertidal topography mapping with a Root Mean Square Error (RMSE) of approximately 0.12 m. Finally, a method to assess nearshore bathymetry was developed. The method is based on a depth inversion technique, where wave celerity was estimated using wave trajectories visible on Timestacks. The procedure differentiates the waves in the shoaling and breaking zones and then estimates local depth from shallow or intermediate water equations. In the test case, bathymetry was mapped till a depth of 11 m with relative short time observations (5 hours), registering a RMSE of about 0.46 m when compared to ground truth data. The techniques herein developed allow to extract from video images some of the key drivers of nearshore morphodynamics, such as wave breaking height and wave period, as well as the main morphological features, namely subtidal bathymetry and intertidal beach topography. The combination of the methodologies presented in this thesis provides a comprehensive coverage of nearshore processes, enabling a synoptic representation of hydrodynamics and morphology. These methodologies may foster the implementation of new video-based operational systems and support the quasi-real time determination of coastal indicators and early warning systems for coastal hazards.Fundação para a Ciência e a Tecnologia (FCT), SFRH/BD/52558/201

Eesti keele üldvaldkonna tekstide laia kattuvusega automaatne sündmusanalüüs

Seoses tekstide suuremahulise digitaliseerimisega ning digitaalse tekstiloome järjest laiema levikuga on tohutul hulgal loomuliku keele tekste muutunud ja muutumas masinloetavaks. Masinloetavus omab potentsiaali muuta tekstimassiivid inimeste jaoks lihtsamini hallatavaks, nt lubada rakendusi nagu automaatne sisukokkuvõtete tegemine ja tekstide põhjal küsimustele vastamine, ent paraku ei ulatu praegused automaatanalüüsi võimalused tekstide sisu tegeliku mõistmiseni. Oletatakse, tekstide sisu mõistvale automaatanalüüsile viib meid lähemale sündmusanalüüs – kuna paljud tekstid on narratiivse ülesehitusega, tõlgendatavad kui „sündmuste kirjeldused”, peaks tekstidest sündmuste eraldamine ja formaalsel kujul esitamine pakkuma alust mitmete „teksti mõistmist” nõudvate keeletehnoloogia rakenduste loomisel. Käesolevas väitekirjas uuritakse, kuivõrd saab eestikeelsete tekstide sündmusanalüüsi käsitleda kui avatud sündmuste hulka ja üldvaldkonna tekste hõlmavat automaatse lingvistilise analüüsi ülesannet. Probleemile lähenetakse eesti keele automaatanalüüsi kontekstis uudsest, sündmuste ajasemantikale keskenduvast perspektiivist. Töös kohandatakse eesti keelele TimeML märgendusraamistik ja luuakse raamistikule toetuv automaatne ajaväljendite tuvastaja ning ajasemantilise märgendusega (sündmusviidete, ajaväljendite ning ajaseoste märgendusega) tekstikorpus; analüüsitakse korpuse põhjal inimmärgendajate kooskõla sündmusviidete ja ajaseoste määramisel ning lõpuks uuritakse võimalusi ajasemantika-keskse sündmusanalüüsi laiendamiseks geneeriliseks sündmusanalüüsiks sündmust väljendavate keelendite samaviitelisuse lahendamise näitel. Töö pakub suuniseid tekstide ajasemantika ja sündmusstruktuuri märgenduse edasiarendamiseks tulevikus ning töös loodud keeleressurssid võimaldavad nii konkreetsete lõpp-rakenduste (nt automaatne ajaküsimustele vastamine) katsetamist kui ka automaatsete märgendustööriistade edasiarendamist.  Due to massive scale digitalisation processes and a switch from traditional means of written communication to digital written communication, vast amounts of human language texts are becoming machine-readable. Machine-readability holds a potential for easing human effort on searching and organising large text collections, allowing applications such as automatic text summarisation and question answering. However, current tools for automatic text analysis do not reach for text understanding required for making these applications generic. It is hypothesised that automatic analysis of events in texts leads us closer to the goal, as many texts can be interpreted as stories/narratives that are decomposable into events. This thesis explores event analysis as broad-coverage and general domain automatic language analysis problem in Estonian, and provides an investigation starting from time-oriented event analysis and tending towards generic event analysis. We adapt TimeML framework to Estonian, and create an automatic temporal expression tagger and a news corpus manually annotated for temporal semantics (event mentions, temporal expressions, and temporal relations) for the language; we analyse consistency of human annotation of event mentions and temporal relations, and, finally, provide a preliminary study on event coreference resolution in Estonian news. The current work also makes suggestions on how future research can improve Estonian event and temporal semantic annotation, and the language resources developed in this work will allow future experimentation with end-user applications (such as automatic answering of temporal questions) as well as provide a basis for developing automatic semantic analysis tools

Temporal disambiguation of relative temporal expressions in clinical texts using temporally fine-tuned contextual word embeddings.

Temporal reasoning is the ability to extract and assimilate temporal information to reconstruct a series of events such that they can be reasoned over to answer questions involving time. Temporal reasoning in the clinical domain is challenging due to specialized medical terms and nomenclature, shorthand notation, fragmented text, a variety of writing styles used by different medical units, redundancy of information that has to be reconciled, and an increased number of temporal references as compared to general domain texts. Work in the area of clinical temporal reasoning has progressed, but the current state-of-the-art still has a ways to go before practical application in the clinical setting will be possible. Much of the current work in this field is focused on direct and explicit temporal expressions and identifying temporal relations. However, there is little work focused on relative temporal expressions, which can be difficult to normalize, but are vital to ordering events on a timeline. This work introduces a new temporal expression recognition and normalization tool, Chrono, that normalizes temporal expressions into both SCATE and TimeML schemes. Chrono advances clinical timeline extraction as it is capable of identifying more vague and relative temporal expressions than the current state-of-the-art and utilizes contextualized word embeddings from fine-tuned BERT models to disambiguate temporal types, which achieves state-of-the-art performance on relative temporal expressions. In addition, this work shows that fine-tuning BERT models on temporal tasks modifies the contextualized embeddings so that they achieve improved performance in classical SVM and CNN classifiers. Finally, this works provides a new tool for linking temporal expressions to events or other entities by introducing a novel method to identify which tokens an entire temporal expression is paying the most attention to by summarizing the attention weight matrices output by BERT models

Extracting Temporal and Causal Relations between Events

Structured information resulting from temporal information processing is crucial for a variety of natural language processing tasks, for instance to generate timeline summarization of events from news documents, or to answer temporal/causal-related questions about some events. In this thesis we present a framework for an integrated temporal and causal relation extraction system. We first develop a robust extraction component for each type of relations, i.e. temporal order and causality. We then combine the two extraction components into an integrated relation extraction system, CATENA---CAusal and Temporal relation Extraction from NAtural language texts---, by utilizing the presumption about event precedence in causality, that causing events must happened BEFORE resulting events. Several resources and techniques to improve our relation extraction systems are also discussed, including word embeddings and training data expansion. Finally, we report our adaptation efforts of temporal information processing for languages other than English, namely Italian and Indonesian.Comment: PhD Thesi

Integration of temporal and semantic components into the Geographic Information. Part II: Methodology

The overall objective of this research project is to enrich geographic data with temporal and semantic components in order to significantly improve spatio-temporal analysis of geographic phenomena. To achieve this goal, we intend to establish and incorporate three new layers (structures) into the core of the Geographic Information by using mark-up languages as well as defining a set of methods and tools for enriching the system to make it able to retrieve and exploit such layers (semantic-temporal, geosemantic, and incremental spatio-temporal). Besides these layers, we also propose a set of models (temporal and spatial) and two semantic engines that make the most of the enriched geographic data. The roots of the project and its definition have been previously presented in Siabato & Manso-Callejo 2011. In this new position paper, we extend such work by delineating clearly the methodology and the foundations on which we will base to define the main components of this research: the spatial model, the temporal model, the semantic layers, and the semantic engines. By putting together the former paper and this new work we try to present a comprehensive description of the whole process, from pinpointing the basic problem to describing and assessing the solution. In this new article we just mention the methods and the background to describe how we intend to define the components and integrate them into the GI

Rip currents in Mediterranean environment: a case study along eastern Ligurian coast

openThis thesis proposes a study on the rip currents development within a Mediterranean embayed beach. The rip (or cross-shore) currents are among the most investigated phenomena in the eld of coastal research, and their fame is due to their environmental and socio-economic implications. The coastal areas are considered as transition environments, where hydrosphere, lithosphere, biosphere, atmosphere and (often) anthroposphere meet. The rip currents are a crucial component of the coastal hydro-morphodynamic processes (hydrosphere and lithosphere) (Short, 1999; Castelle et al., 2016), play a role in larval recruitment processes (biosphere) (Shanks et al., 2010), and they are also well known as risks source for beachgoers (anthroposphere) (Short and Hogan, 1994; Austin et al., 2012). However, the rip currents role along the Mediterranean coasts is often neglected, and most of the literature concerns the rip currents in oceanic environments. The aim of this research is a detailed description of the rip currents behaviour along a Mediterranean embayed beach, also considering the possible sea-level rise implications. The study area was identied within Levanto bay, along the eastern Ligurian coast (NW Italy). The research activity has been conducted through an integrated application of several investigation methodologies, in order to obtain the best possible results in therm of phenomena description. The rip currents individuation is performed through a coastal video-monitoring system installed on the Levanto beach, and the collected data were processed through a dedicated software for coastal video-monitoring (Brignone et al., 2012). Several eld surveys were performed to obtain a full description of the geomorphological boundary conditions (topo-bathymetric surveys and sedimentological sampling). The rip currents description and evaluation were executed through the application of the XBeach model (Roelvink et al., 2009), which is a well-known tool for coastal modelling. Moreover, the modelling approach allowed the evaluation of the possible rip currents response under dierent sea-level rise scenarios (local sea-level projections to 2100) (Kopp et al., 2014). The obtained results show a detailed description of the rip currents phenomena, showing their essential role in the local coastal dynamics. The proposed research approach has proved to be reliable for the rip currents investigation in the Mediterranean environment, and it can be applied along any stretch of coast of the Mediterranean Sea. Moreover, the modelling results showed a signicant relation between sea-level rise and rip currents behaviour. The results of this study highlight the role of the rip currents in the Mediterranean environment and represent a rm basis for the rip currents investigation along the Mediterranean coasts.openXXXI CICLO - SCIENZE E TECNOLOGIE PER L'AMBIENTE E IL TERRITORIO (STAT) - Scienze della terraCarpi, Luc