Academic literature on the topic 'Document image interpretation'

Enhancement of document images is an interesting research challenge in the process of character recognition. It is quite significant to have a document with uniform illumination gradient to achieve higher recognition accuracies through a document processing system like Optical Character Recognition (OCR). Complex document images are one of the varied image categories that are difficult to process compared to other types of images. It is the quality of document that decides the precision of a character recognition system. Hence transforming the complex document images to a uniform illumination gradient is foreseen. In the proposed research, ancient document images of UMIACS Tobacco 800 database are considered for removal of marginal noise. The proposed technique carries out the block wise interpretation of document contents to remove the marginal noise that is present usually at the borders of images. Further, Hu moment’s features are computed for the detection of marginal noise in every block. An empirical analysis is carried out for classification of blocks into noisy or non-noisy and the outcomes produced by algorithm are satisfactory and feasible for subsequent analysis.

In this paper, we consider the case of applying convolutional neural networks interpretation methods to ResNet 18 model in order to identify and justify model errors. The model is used in the problem of classifying the orientation of text documents images. First, using interpretation methods, an assumption was made as to why the neural network shows low metrics on data that differs from training images. The alleged reason was the presence of artifacts on the generated training images, caused by the use of an image rotation function. Further, using the Vanilla Gradient, Guided Backpropagation, Integrated Gradients, GradCAM methods and the invented metric, we managed to accurately confirm the hypothesis put forward. The obtained results helped to significantly improve the accuracy of the model.

The study aims to determine whether the images of a teacher in the normative document and the minds of student teachers coincide, as well as to identify the differences. A total of 236 students of the Faculty of Philology and History participated in the associative experiment. The words “ability”, “readiness”, and “possession” are the most common words used in the normative documents of the Russian Federation in the context of higher education. The concept of “teacher” is the main stimulus word in the associative experiment. The results of the associative experiment revealed a group of the most frequent associative words. In addition, based on the quantitative indicators of the associative experiment, nine thematic groups of associative words were formed. A comparative analysis of the indicators of an associative experiment involving students from different countries can make it possible to compare the features of national education systems and show their effect on the formation of a teacher image in the minds of student teachers.

The article proposes a new method for automatic data annotation for solving the problem of document image segmentation using deep object detection neural networks. The format of marked PDF files is considered as the initial data for markup. The peculiarity of this format is that it includes hidden marks that describe the logical and physical structure of the document. To extract them, a tool has been developed that simulates the operation of a stack-based printing machine according to the PDF format specification. For each page of the document, an image and annotation are generated in PASCAL VOC format. The classes and coordinates of the bounding boxes are calculated during the interpretation of the labeled PDF file based on the labels. To test the method, a collection of marked up PDF files was formed from which images of document pages and annotations for three segmentation classes (text, table, figure) were automatically obtained. Based on these data, a neural network of the EfficientDet D2 architecture was trained. The model was tested on manually labeled data from the same domain, which confirmed the effectiveness of using automatically generated data for solving applied problems.

Aim: This study evaluated the influence of the method used for visualization and analysis of cone-beam computed tomography (CBCT) on the diagnosis of endodontic conditions. Materials and methods: Twenty clinical cases containing twelve different endodontic conditions were analyzed by two specialists in dental radiology and one specialist in endodontics. Initially, the evaluators viewed the cases in Portable Document Format (PDF) containing a selection of digital images and, by consensus, described their diagnostic hypotheses for each case. One week later, the evaluators reassessed the cases, this time using multiplanar reconstructions with a Digital Imaging and Communications in Medicine (DICOM) format image viewer. Once more, by consensus, they recorded their diagnostic hypotheses. Results: In 10% of the cases there was a discrepancy between the diagnoses made using preselected digital images in PDFs and by viewing multiplanar reconstructions. The visualization of the PDF images obtained a sensitivity of 0.714, specificity of 0.966, and 90% accuracy. Discussion: In the majority of these cases, endodontic conditions identified using the DICOM image viewer (multiplanar reconstruction) were not detected using the PDFs of preselected images. Conclusion: Although more studies are needed, the authors reiterate that using multiplanar reconstructions should always be preferred to other forms of analysis for CBCT, so that the maximum diagnostic potential of the imaging exam can be achieved.

AbstractDynamic Contrast Enhanced Ultrasound (DCE-US) is an imaging technique that utilizes microbubble contrast agents in diagnostic ultrasound. The EFSUMB guidelines published in 2004, updated in 2008 and 2011 focused on the use of DCE-US, including essential technical requirements, training, investigational procedures and steps, guidance on image interpretation, established and recommended clinical indications and safety considerations. However the quantification of images acquired with ultrasound contrast agents (UCAs) is not discussed in the guidelines. The purpose of this EFSUMB document is to provide some recommendations and descriptions of the quantification of ultrasound images, technical requirements for analysis of time-intensity curves (TICs), methodology for data analysis, and interpretation of the results.

From its early stages, the community of Pattern Recognition and Computer Vision has considered the importance of leveraging the structural information when understanding images. Usually, graphs have been proposed as a suitable model to represent this kind of information due to their flexibility and representational power able to codify both, the components, objects, or entities and their pairwise relationship. Even though graphs have been successfully applied to a huge variety of tasks, as a result of their symbolic and relational nature, graphs have always suffered from some limitations compared to statistical approaches. Indeed, some trivial mathematical operations do not have an equivalence in the graph domain. For instance, in the core of many pattern recognition applications, there is a need to compare two objects. This operation, which is trivial when considering feature vectors defined in ℝn, is not properly defined for graphs. In this thesis, we have investigated the importance of the structural information from two perspectives, the traditional graph-based methods and the new advances on Geometric Deep Learning. On the one hand, we explore the problem of defining a graph representation and how to deal with it on a large scale and noisy scenario. On the other hand, Graph Neural Networks are proposed to first redefine a Graph Edit Distance methodologies as a metric learning problem, and second, to apply them in a real use case scenario for the detection of repetitive patterns which define tables in invoice documents. As experimental framework, we have validated the different methodological contributions in the domain of Document Image Analysis and Recognition.

Vectorization is the most fundamental operation in interpretation of line drawings and document analysis. There are several reasons for converting image vectorization. Vector data is normally created from existing natural source image like photographs,scanned images. Choosing a best vectorization method that suits the needs of the system is very important. In general, good methods must preserve information like line geometry and intersection junction as far as possible. It is also important to analyze the error and find the accuracy of the result with respect to the original data. We have compared Skeletonization by Mathematical Morphology and Voronoi Diagrams with original image for vectorizing images. Root mean squre error is one of the good methods to analysis an error on original Image, Mathematical Morphology and Voronoi Diagrams. Literature about above said methods is also included in this paper.

The mapping of the land use in a tropical wet and dry area (East-Mono, Central Togo) is made using remote sensing data, recorded by the satellite SPOT. The negative, multispectral image data set has been transferred into positives by photographical means and afterwards enhanced using the diazo technique. The combination of the different diazo coloured images resulted in a false colour composite, being the basic document for the visual image interpretation. The image analysis, based upon differences in colour and texture, resulted in a photomorphic unit map. The use of a decision tree including the various image characteristics allowed the conversion of the photomorphic unit map into a land cover map. For this, six main land cover types could be differentiated resulting in 16 different classes of the final map.

"Dragon" is an important design theme and image, to be applied in many design fields, so summing up and interpreting relevant issue of dragon connotation can help better application of dragon image in design. This paper tries to expound dragon iconography, archetype and symbolical meanings in terms of etymology, document research and Jung’s psychology theories. In the light of both objective and subjective meanings this paper regards that the essence of dragon which is mythological being in human subconscious imagination symbolizes and integrates the various great power of nature.

Cette thèse comprend deux axes de recherche. D´abord, un nouveau cadre méthodologique pour évaluer la conformité des données RSO (Radar à Synthèse d’Ouverture) multivariées à haute résolution spatiale est proposé en termes de statistique asymptotique par rapport au modèle produit. Plus précisément, la symétrie sphérique est étudiée en appliquant un test d'hypothèses sur la structure de la matrice de quadri-covariance. Deux jeux de données, simulées et réelles, sont prises en considération pour étudier la performance du test obtenu par l’analyse qualitative et quantitative des résultats. La conclusion la plus importante, en ce qui concerne la méthodologie employée dans l'analyse des données RSO multivariées, est que, selon les différents cas d’usages, une partie considérable de données hétérogènes peut ne pas s’ajuster asymptotiquement au modèle produit. Par conséquent, les algorithmes de classification et/ou détection conventionnels développés sur la base de celui-ci deviennent sub-optimaux. Cette observation met en évidence la nécessité de développer de modèles plus sophistiqués comme l'Analyse en Composantes Indépendantes, ce qui conduit à la deuxième partie de cette thèse qui consiste en l’étude du biais d’estimation des paramètres TSVM (Target Scattering Vector Model) lorsque l’ACP est utilisée. Enfin, les performances de l'algorithme sont également évaluées sous l'hypothèse du bruit gaussien corrélé spatialement. L’évaluation théorique de l'ACI comme un outil de type ICTD (In Coherent Target Decomposition) polarimétrique permet une analyse plus efficace de l’apport d’information fourni. A ce but, deux espaces de représentation sont utilisé, notamment H /alpha et TSVM
This thesis comprises two research axes. First, a new methodological framework to assess the conformity of multivariate high-resolution Synthetic Aperture Radar (SAR) data with respect to the Spherically Invariant Random Vector model in terms of asymptotic statistics is proposed. More precisely, spherical symmetry is investigated by applying statistical hypotheses testing on the structure of the quadricovariance matrix. Both simulated and real data are taken into consideration to investigate the performance of the derived test by a detailed qualitative and quantitative analysis. The most important conclusion drawn, regarding the methodology employed in analysing SAR data, is that, depending on the scenario under study, a considerable portion of high heterogeneous data may not fit the aforementioned model. Therefore, traditional detection and classification algorithms developed based on the latter become sub-optimal when applied in such kind of regions. This assertion highlights for the need of the development of model independent algorithms, like the Independent Component Analysis, what leads to the second part of the thesis. A Monte Carlo approach is performed in order to investigate the bias in estimating the Touzi's Target Scattering Vector Model (TSVM) parameters when ICA is employed using a sliding window approach under different scenarios. Finally, the performance of the algorithm is also evaluated under Gaussian clutter assumption and when spatial correlation is introduced in the model. These theoretical assessment of ICA based ICTD enables a more efficient analysis of the potential new information provided by the ICA based ICTD. Both Touzi TSVM as well as Cloude and Pottier H/alpha feature space are then taken into consideration for that purpose. The combined use of ICA and Touzi TSVM is straightforward, indicating new, but not groundbreaking information, when compared to the Eigenvector approach. Nevertheless, the analysis of the combined use of ICA and Cloude and Pottier H/alpha feature space revealed a potential aspect of the Independent Component Analysis based ICTD, which can not be matched by the Eigenvector approach. ICA does not introduce any unfeasible region in the H/alpha plane, increasing the range of possible natural phenomenons depicted in the aforementioned feature space

Cette thèse propose de définir une génération d’artistes dont la spécificité consiste à collecter, associer et rediffuser des images existantes, sans en transformer le contenu iconique. Pour tenter de cerner les caractéristiques de cette pratique, des entretiens ont été menés avec des artistes français contemporains : Eric Baudelaire, Ludovic Burel, Hervé Coqueret, documentation céline duval, Pierre Leguillon, Mathieu Pernot, Régis Perray et Eric Watier. L’analyse des dispositifs plastiques qu’ils mettent en œuvre fait apparaître deux aspects susceptibles d’identifier la spécificité de leur travail : leur manière d’associer les images entre elles suscite de nouvelles interprétations entraînant leur relecture ; et leur pratique s’inscrit dans une phase transitoire entre l’ère de la reproductibilité technique des images et celle des technologies du numérique. A travers une recherche scientifique pluridisciplinaire, il sera donc question d’étudier leurs processus de création depuis le choix des images jusqu’à la diffusion de leurs projets (I), d’analyser la polysémie des images et les possibilités d’en relire les signes (II) et enfin de comprendre comment s’agence leur position artistique entre deux époques techniquement marquées concernant les images (III). Afin de les démarquer des autres générations réemployant des images, la thèse propose une nouvelle dénomination : les Relecteurs d’images
This thesis proposes to define a generation of artists who are collecting, associating and redistributing pictures without changing or transforming the iconic contents. In order to elaborate their characteristics, several french contemporary artists were interviewed: Eric Baudelaire, Ludovic Burel, Hervé Coqueret, documentation céline duval, Pierre Leguillon, Mathieu Pernot, Régis Perray and Eric Watier. The analysis of the devices implemented by the artists shows two aspects that could identify the specificity of their work: their way of associating the pictures with each other offers new possibilities of interpretation and leads to a second reading of the pictures; and their practice is taking place during the transition between the eras of image reproduction techniques and numerical techniques. Within the scope of a multi-field scientific research, it will be necessary to study the creation processes from the choice of the representation till the distribution of the projects (I), to analyse the polysemy of the images and the possibility of rereading their signs (II), and, finally, to understand how the artistic position is located between two, with respect to pictures, technically distinguished epoches (III). To differentiate this generation of artists from others reusing images, the thesis suggests a new name: the “Rereaders of pictures”

Les travaux de recherche développés dans cette thèse concernent la mise en oeuvre d'un système de vidéo surveillance intelligente en milieu hospitalier. Dans le contexte d'une application en unité de soins intensifs médicale, nous introduisons la notion originale de Boite Noire Médicale et nous proposons un nouveau système de monitoring visuel de Détection Automatique de Situations à risque et d'Alerte (DASA) basé sur un système de vidéosurveillance multi-caméra intelligent. L'objectif étant d'interpréter les flux d'informations visuelles et de détecter en temps réel les situations à risque afin de prévenir l'équipe médicale et ensuite archiver les évènements dans une base de donnée vidéo qui représente la Boite Noire Médicale. Le système d'interprétation est basé sur des algorithmes de reconnaissance de scénarios qui exploitent les Modèles de Markovs Cachés (MMCs). Une extension du modèle MMC standard est proposé afin de gérer la structure hiérarchique interne des scénarios et de contrôler la durée de chaque état du modèle markovien. La contribution majeure de ce travail repose sur l'intégration d'un raisonnement de type évènementiel, pour gérer la décision de reconnaissance en tenant compte des imperfections des informations disponibles. Les techniques de reconnaissance de scénarios proposées ont été testées et évaluées sur une base de séquences vidéo médicales et comparés aux modèles de Markov cachés probabilistiques classiques
This thesis focuses on the study and the implementation of an intelligent visual monitoring system in hospitals. In the context of an application for patient monitoring in mediacal intensive care unit, we introduce an original concept of the Medical Black Box and we propose a new system for visual monitoring of Automatic Detection of risk Situations and Alert (DASA) based on a CCTV system with network smart camera. The aim is to interpret the visual information flow and to detect at real-time risk situations to prevent the mediacl team and then archive the events in a video that is based Medical Black Box data. The interpretation system is based on scenario recognition algorithms that exploit the Hidden Markov Models (HMM). An extension of the classic model of HMM is proposed to handle the internal reporting structure of the scenarios and to control the duration of each state of the Markov model. The main contribution of this work relies on the integration of an evidential reasoning, in order to manage the recognition decision taking into account the imperfections of available information. The proposed scenarios recognition method have been tested and assessed on database of medical video sequences and compared to standard probabilistic Hidden Markov Models

Des del seu inici, la comunitat investigadora sobre reconeixement de patrons i visió per computador ha reconegut la importància d’aprofitar la informació estructural de les imatges. Els grafs s’han seleccionat com el marc adequat per representar aquest tipus d’informació a causa de la seva flexibilitat i poder de representació capaç de codificar, tant els components, objectes i entitats com les seves relacions. Tot i que els grafs s’han aplicat amb èxit a una gran varietat de tasques -com a resultat de la seva naturalesa simbòlica i relacional- sempre han patit d’algunes limitacions comparats amb mètodes estadístics. Això es deu al fet que algunes operacions matemàtiques trivials no tenen una equivalència en el domini dels grafs. Per exemple, en la base de moltes aplicacions de reconeixement de patrons hi ha la necessitat de comparar objectes. No obstant això, aquesta operació trivial no està degudament definida per grafs quan considerem vectors de característiques. Al llarg d’aquesta recerca, el principal domini d’aplicació està basat en el tema de l’Anàlisi i Reconeixement d’Imatges de Documents. Aquest és un subcamp de la Visió per Computador que té com a objectiu compendre imatges de documents. En aquest context, l’estructura -particularment la representació en forma de graf- proporciona una dimensió complementària al contingut de la imatge. En Visió per Computador la primera dificultat que ens trobem recau en construir una representació significativa de grafs capaç de codificar les característiques rellevants d’una imatge donada. Això es deu al fet que és un procés que ha de trobar un equilibri entre la simplicitat de la representació i la flexibilitat, per tal de representar les diferents deformacions que apareixen en cada domini d’aplicació. Hem estudiat aquest tema en l’aplicació de la recerca de paraules, dividint els diferents traços en grafemes –les unitats més petites d’un alfabet manuscrit&-. També, hem investigat diferents metodologies per accelerar el procés de comparació entre grafs perquè la recerca de paraules o, inclús, de forma més general, l’aplicació en la recerca de grafs, pugui incloure grans col·leccions de documents. Aquestes metodologies han estat principalment dues: (a) un sistema d’indexació de grafs combinat amb un sistema de votació en l’àmbit de nodes capaç d’eliminar resultats improbables i (b) usant representacions jeràrquiques de grafs que duen a terme la majoria de les comparacions en una versió reduïda del graf original, mitjançant comparatives entre els nivells més abstractes i els més detallats. A més a més, la representació jeràrquica també ha demostrat obtenir una representació més robusta que el graf original, lidiant amb el soroll i les deformacions de manera elegant. Per tant, proposem explotar aquesta informació en forma de codificació jeràrquica del graf que permeti utilitzar tècniques estadístiques clàssiques. Els nous avenços en aprenentatge profund geomètric han aparegut com una generalització de les metodologies d’aprenentatge profund aplicades a dominis no Euclidians –com grafs i varietats–, i han promogut un gran interès en la comunitat científica per aquests esquemes de representació. Així doncs, proposem una distància de grafs capaç d’obtenir resultats comparables a l’estat de l’art en diferents tasques aprofitant aquests nous desenvolupaments, però considerant les metodologies tradicionals com a base. També hem realitzat una col·laboració industrial amb la finalitat d’extreure informació automàtica de les factures de l’empresa (amb dades anònimes). El resultat ha estat el desenvolupament d’un sistema de detecció de taules en documents administratius. D’aquesta manera les xarxes neuronals basades en grafs han demostrat ser aptes per detectar patrons repetitius, els quals, després d’un procés d’agregació, constitueixen una taula.
La comunidad que investiga el reconocimiento de patrones y la visión por computador ha reconocido la importancia de aprovechar la información estructural de las imágenes. Los grafos se han seleccionado como el marco adecuado para representar este tipo de información a causa de su flexibilidad y poder de representación capaz de codificar los componentes, los objetos, las entidades y sus relaciones. Aunque los grafos se han aplicado con éxito a una gran variedad de tareas –como resultado de su naturaleza simbólica y relacional–, siempre han sufrido algunas limitaciones comparados con los métodos estadísticos. Esto se debe al hecho que algunas operaciones matemáticas triviales no tienen una equivalencia en el dominio de los grafos. Por ejemplo, en la base de la mayoría de aplicaciones de reconocimiento de patrones hay la necesidad de comparar objetos. No obstante, esta operación trivial no está debidamente definida por grafos cuando consideramos vectores de características. Durante la investigación, el principal dominio de aplicación se basa en el Análisis y Reconocimiento de Imágenes de Documentos. Este es un subcampo de la Visión por Computador que tiene como objetivo comprender imágenes de documentos. En este contexto la estructura -particularmente la representación en forma de grafo- proporciona una dimensión complementaria al contenido de la imágen. En Visión por Computador la primera dificultad que nos encontramos se basa en construir una representación significativa de grafos que sea capaz de codificar las características relevantes de una imagen. Esto se debe a que es un proceso que tiene que encontrar un equilibrio entre la simplicidad de la representación y la flexibilidad, para representar las diferentes deformaciones que aparecen en cada dominio de la aplicación. Hemos estudiado este tema en la aplicación de la búsqueda de palabras, dividiendo los diferentes trazos en grafemas –las unidades más pequeñas de un alfabeto manuscrito–. Tambien, hemos investigado diferentes metodologías para acelerar el proceso de comparación entre grafos para que la búsqueda de palabras o, incluso, de forma más general, la aplicación de búsqueda de grafos, pueda incluir grandes colecciones de documentos. Estas metodologías han estado principalmente dos: (a) un sistema de indexación de grafos combinado con un sistema de votación en el ámbito de los nodos capaces de eliminar resultados improbables y (b) usando representaciones jerárquicas de grafos que llevan a término la mayoría de las comparaciones en una versión reducida del grafo original mediante comparativas entre los niveles más abstractos y los más detallados. Asimismo, la representación jerárquica también ha demostrado obtener una representación más robusta que el grafo original, además de lidiar con el ruido y las deformaciones de manera elegante. Así pues, proponemos explotar esta información en forma de codificación jerárquica del grafo que permita utilizar técnicas estadísticas clásicas. Los nuevos avances en el aprendizaje profundo geométrico han aparecido como una generalización de las metodologías de aprendizaje profundo aplicadas a dominios no Euclidianos –como grafos y variedades– y han promovido un gran interés en la comunidad científica por estos esquemas de representación. Proponemos una distancia de grafos capaz de obtener resultados comparables al estado del arte en diferentes tareas aprovechando estos nuevos desarrollos, pero considerando las metodologías tradicionales como base. También hemos realizado una colaboración industrial con la finalidad de extraer información automática de las facturas de la empresa (con datos anónimos). El resultado ha sido el desarrollo de un sistema de detección de tablas en documentos administrativos. Así pues, las redes neuronales basadas en grafos han demostrado ser aptas para detectar patrones repetitivos, los cuales, después de un proceso de agregación, constituyen una tabla.
From its early stages, the community of Pattern Recognition and Computer Vision has considered the importance on leveraging the structural information when understanding images. Usually, graphs have been selected as the adequate framework to represent this kind of information due to their flexibility and representational power able to codify both, the components, objects or entities and their pairwise relationship. Even though graphs have been successfully applied to a huge variety of tasks, as a result of their symbolic and relational nature, graphs have always suffered from some limitations compared to statistical approaches. Indeed, some trivial mathematical operations do not have an equivalence in the graph domain. For instance, in the core of many pattern recognition application, there is the need to compare two objects. This operation, which is trivial when considering feature vectors, is not properly defined for graphs. Along this dissertation the main application domain has been on the topic of Document Image Analysis and Recognition. It is a subfield of Computer Vision aiming at understanding images of documents. In this context, the structure and in particular graph representations, provides a complementary dimension to the raw image contents. In computer vision, the first challenge we face is how to build a meaningful graph representation that is able to encode the relevant characteristics of a given image. This representation should find a trade off between the simplicity of the representation and its flexibility to represent the deformations appearing on each application domain. We applied our proposal to the word spotting application where strokes are divided into graphemes which are the smaller units of a handwritten alphabet. We have investigated different approaches to speed-up the graph comparison in order that word spotting, or more generally, a retrieval application is able to handle large collections of documents. On the one hand, a graph indexing framework combined with a votation scheme at node level is able to quickly prune unlikely results. On the other hand, making use of graph hierarchical representations, we are able to perform a coarse-to-fine matching scheme which performs most of the comparisons in a reduced graph representation. Besides, the hierarchical graph representation demonstrated to be drivers of a more robust scheme than the original graph. This new information is able to deal with noise and deformations in an elegant fashion. Therefore, we propose to exploit this information in a hierarchical graph embedding which allows the use of classical statistical techniques. Recently, the new advances on geometric deep learning, which has emerged as a generalization of deep learning methods to non-Euclidean domains such as graphs and manifolds, has raised again the attention to these representation schemes. Taking advantage of these new developments but considering traditional methodologies as a guideline, we proposed a graph metric learning framework able to obtain state-of-the-art results on different tasks. Finally, the contributions of this thesis have been validated in real industrial use case scenarios. For instance, an industrial collaboration has resulted in the development of a table detection framework in annonymized administrative documents containing sensitive data. In particular, the interest of the company is the automatic information extraction from invoices. In this scenario, graph neural networks have proved to be able to detect repetitive patterns which, after an aggregation process, constitute a table.

Depuis une quinzaine d’années, l’émergence des données de télédétection à Très Haute Résolution Spatiale (THRS) et la démocratisation des Systèmes d’Information Géographique (SIG) aident à répondre aux nouveaux besoins croissants d’informations spatialisées. Le développement de nouvelles méthodes de cartographie offre une opportunité pour comprendre et anticiper les mutations des surfaces terrestres aux grandes échelles, jusqu’ici mal connues. En France, l’emploi de bases de données spatialisées sur l’occupation du sol à grande échelle (BD Ocsol GE) est devenu incontournable dans les opérations courantes de planification et de suivi des territoires. Pourtant, l’acquisition de ce type de bases de données spatialisées est encore un besoin difficile à satisfaire car les demandes portent sur des productions cartographiques sur-mesure, adaptées aux problématiques locales des territoires. Face à cette demande croissante, les prestataires réguliers de ce type de données cherchent à optimiser les procédés de fabrication avec des techniques récentes de traitements d’image. Cependant, la Photo-Interprétation Assistée par Ordinateur (PIAO) reste la méthode privilégiée des prestataires. En raison de sa grande souplesse, elle répond toujours au besoin de cartographie aux grandes échelles, malgré son coût important. La substitution de la PIAO par des méthodes de production entièrement automatisées est rarement envisagée. Toutefois, les développements récents en matière de segmentation d’images peuvent contribuer à l’optimisation de la pratique de la photo-interprétation. Cette thèse présente ainsi une série d’outils (ou modules) qui participent à l’élaboration d’une assistance à la digitalisation pour l’exercice de photo-interprétation d’une BD Ocsol GE. L’assistance se traduit par la réalisation d’un prédécoupage du paysage à partir d’une segmentation menée sur une image THRS. L’originalité des outils présentés est leur intégration dans un contexte de production fortement contraint. La construction des modules est conduite à travers trois prestations cartographiques à grande échelle commandités par des entités publiques. L’apport de ces outils d’automatisation est analysé à travers une analyse comparative entre deux procédures de cartographie : l’une basée sur une démarche de photo-interprétation entièrement manuelle et la seconde basée sur une photo-interprétation assistée en amont par une segmentation numérique. Les gains de productivité apportés par la segmentation sont, évalués à l’aide d’indices quantitatifs et qualitatifs, sur des configurations paysagères différentes. À des degrés divers, il apparaît que quelque soit le type de paysage cartographié, les gains liés à la cartographie assistée sont substantiels. Ces gains sont discutés, à la fois, d’un point de vue technique et d’un point de vue thématique dans une perspective commerciale
Over the last fifteen years, the emergence of remote sensing data at Very High Spatial Resolution (VHRS) and the democratization of Geographic Information Systems (GIS) have helped to meet the new and growing needs for spatial information. The development of new mapping methods offers an opportunity to understand and anticipate land cover change at large scales, still poorly known. In France, spatial databases about land cover and land use at large scale have become an essential part of current planning and monitoring of territories. However, the acquisition of this type of database is still a difficult need to satisfy because the demands concern tailor-made cartographic productions, adapted to the local problems of the territories. Faced with this growing demand, regular service providers of this type of data seek to optimize manufacturing processes with recent image-processing techniques. However, photo interpretation remains the favoured method of providers. Due to its great flexibility, it still meets the need for mapping at large scale, despite its high cost. Using fully automated production methods to substitute for photo interpretation is rarely considered. Nevertheless, recent developments in image segmentation can contribute to the optimization of photo-interpretation practice. This thesis presents a series of tools that participate in the development of digitalization assistance for the photo-interpretation exercise. The assistance results in the realization of a pre-cutting of the landscape from a segmentation carried out on a VHRS image. Tools development is carried out through three large-scale cartographic services, each with different production instructions, and commissioned by public entities. The contribution of these automation tools is analysed through a comparative analysis between two mapping procedures: manual photo interpretation versus digitally assisted segmentation. The productivity gains brought by segmentation are evaluated using quantitative and qualitative indices on different landscape configurations. To varying degrees, it appears that whatever type of landscape is mapped, the gains associated with assisted mapping are substantial. These gains are discussed both technically and thematically from a commercial perspective

Les travaux présentés dans ce mémoire de thèse abordent sous différents angles très intéressants, un sujet vaste et ambitieux : l’interprétation de plans cadastraux couleurs.Dans ce contexte, notre approche se trouve à la confluence de différentes thématiques de recherche telles que le traitement du signal et des images, la reconnaissance de formes, l’intelligence artificielle et l’ingénierie des connaissances. En effet, si ces domaines scientifiques diffèrent dans leurs fondements, ils sont complémentaires et leurs apports respectifs sont indispensables pour la conception d’un système d’interprétation. Le centre du travail est le traitement automatique de documents cadastraux du 19e siècle. La problématique est traitée dans le cadre d'un projet réunissant des historiens, des géomaticiens et des informaticiens. D'une part nous avons considéré le problème sous un angle systémique, s'intéressant à toutes les étapes de la chaîne de traitements mais aussi avec un souci évident de développer des méthodologies applicables dans d'autres contextes. Les documents cadastraux ont été l'objet de nombreuses études mais nous avons su faire preuve d'une originalité certaine, mettant l'accent sur l'interprétation des documents et basant notre étude sur des modèles à base de graphes. Des propositions de traitements appropriés et de méthodologies ont été formulées. Le souci de comblé le gap sémantique entre l’image et l’interprétation a reçu dans le cas des plans cadastraux étudiés une réponse
This thesis tackles the problem of technical document interpretationapplied to ancient and colored cadastral maps. This subject is on the crossroadof different fields like signal or image processing, pattern recognition, artificial intelligence,man-machine interaction and knowledge engineering. Indeed, each of thesedifferent fields can contribute to build a reliable and efficient document interpretationdevice. This thesis points out the necessities and importance of dedicatedservices oriented to historical documents and a related project named ALPAGE.Subsequently, the main focus of this work: Content-Based Map Retrieval within anancient collection of color cadastral maps is introduced

This chapter explores an ancient cultural theme: the links between women and textuality, involving images of female nudity (‘the naked truth’) and of clothing and make up (ornatus). It begins by exploring the mechanics of reading as a homoerotic exchange between a male author and a male reader through the guise of a personified female text, and it documents the evolution of such a theme in the age of Dante, with the flourishing of a rather independent form of female lyric textuality. In creating an embodied text that moves about, speaks, cries out in joy or sorrow, but also writes and reads itself, and, most importantly, opens itself up to the plurality of interpretation, poets promote a very nuanced image of textuality, which defies gender barriers and stereotypes. Eventually such ‘live’ texts, with their fertility, come to challenge the all-male myth of poetic generation and the masculinity of authority.

AbstractAlthough radiogenic isotopes historically have been used in ore genesis studies for age dating and as tracers, here we document the use of regional- and continental-scale Sm–Nd isotope data and derived isotopic maps to assist with metallogenic interpretation, including the identification of metallogenic terranes. For the Sm–Nd system, calculated Nd model ages, which are time independent, are of most value for small-scale isotopic maps. Typically, one- or two-stage depleted mantle model ages (TDM, T2DM) are used to infer age when the isotope characteristics of the rock were in isotopic equilibrium with a modelled (mantle) reservoir. An additional advantage is that Nd model ages provide, with a number of assumptions, an estimate of the approximate age of continental crust in a region. Regional- and continental-scale Nd model age maps, constructed from rocks such as granites, which effectively sample the middle to lower crust, therefore, provide a proxy to constrain the nature of the crust within a region. They are of increasing use in metallogenic analysis, especially when combined with a mineral systems approach, which recognizes that mineral deposits are the result of geological processes, at a scales from the ore shoot to the craton. These maps can be used empirically and/or predictively to identify and target large parts of mineral systems that may be indicative, or form part of, metallogenic terranes. Examples presented here include observed spatial relationships between mineral provinces and isotopic domains; the identification of old and/or thick cratonic blocks; determination of tectonic regimes favorable for mineralization; identification of isotopically juvenile zones that may indicate rifts or primitive arcs; recognition of crustal breaks that define metallogenic terrane boundaries or delineate fluid pathways; and, as baseline maps. Of course, any analysis of Sm–Nd and similar isotopic maps are predicated on integration with geological, geochemical and geophysical information data. In the future, research in this area should focus on the spatial and temporal evolution of the whole lithosphere at the province- to global-scales to more effectively targeting mineral exploration. This must involve integration of radiogenic isotopic data with other data, in particular, geophysical data, which has the advantage of being able to directly image the crust and lithosphere and being of a more continuous nature as compared to invariably incomplete isotopic data sets.

This introductory essay aims at highlighting some aspects concerning the connections between the Ostrogoths and Franks in the Middle Ages. To this end, cases from different contexts and chronologies have been examined: firstly, Giovanni Villani’s chronicle, which conveys a polarized image of the Gothic and Carolingian worlds; and then some testimonies from the ninth century, that use the Ostrogothic model in connection with the present in a more complex and ambivalent manner. The various interpretations of the Gothic world are linked by a tendency to emphasize historical analogies, that leads to an overall and protracted disinterest in the specific forms of Ostrogothic society and in work that most documents it, Cassiodorus’ Variae.

Abstract3D models from passive muted subjects, often used in the books and in preservation design reports as powerful images dense of contents, have nowadays the opportunity to become 'live gears’ leveraging knowledge, interpretation, and management into preservation objectives till to better-informed fruition. To this aim, we need to build up reliable and re-usable 3D Quality models. How to shift from a 3D model toward a 3D quality model?This contribution intends to focus on the parameters defining a 3D Quality model catching the heritage complexity with its components in a holistic methodological and practical vision. A radar chart has been used to manage all the parameters. First of all, Geometry describes a quality model: parameters for data acquisition, on-site surveying, and model processing to obtain 2D-3D Geometry quality are defined. The concept of scale associated with measurable parameters defining the Grade of Accuracy is proposed and applied to the surveying and to the 3D models. 3D models can be considered tools to decode the complexity of cultural heritage made by the different transformations across the centuries, anthropic-natural hazards, climate change threats and events (such as earthquakes, fires, wars). Thus, Geometry is not enough to describe such complexity; it represents the first step. Materials and Construction technologies analysis is the second pillar qualifying a quality model. The connection with the indirect data source (i.e., historical reports and archives documents), is the third pillar to be reconnected to the Geometry and Material analysis in the quality definition. HBIM represents a multidisciplinary environment to convey the information related to geometry and models. Furtherly, several parameters are identified to describe the quality of informative models, as in the case of Object Libraries and Building archeology progressively feeding such models. BIM Level of Developments (phases) and Level of Geometry (contents, not scale!) have been adapted to the HBIM, introducing digitization, surveying, and HBIM modeling into the preservation process. Finally, a quality model is defined by the capability to be re-used circulating Information and Models among the end-users as in the case of informed VR/AR through CDE and XR platforms.

This chapter is about the idea of medical information interchange networks providing signal and possibly image interpretation services. Technically, the issue is similar to Web-accessible services: document conversion, searching the Web, photo development, video on demand, electronic booking of hotels or airline ticketing. Various services use state-of-the-art Internet technology for commerce and entertainment purposes. Unfortunately, medical applications are rarely represented in that form.

We live in the century of technology, where the enormous evolution of data and science has recently favored a strong interest in processing, transmitting, and storing information. If, in the past, only a human mind could extract meaningful information from image data, after decades of dedicated research, scientists have managed to build complex systems that can identify different areas, tables, and texts from scanned documents, all the obtained information being easily accessed and passed by one to another. Books, newspapers, maps, letters, drawings - all types of documents can be scanned and processed in order to become available in a digital format. In the digital world, the storage space is very small compared to physical documents, so these applications will replace millions of old paper volumes with a single memory disk and will be accessible at the same time for anyone using just Internet access and without having a risk of deterioration. Other problems, such as ecological issues, accessibility and flexibility constraints can be solved by the use of document image analysis systems. This article presents the methods and techniques used to process on-paper documents and convert them to electronic ones, starting from pixel level and getting to the level of the entire document. The main purpose of Document Image Analysis Systems is to recognize texts and graphical interpretations from images, extract, format and present their contained information accordingly to the people's needs. We will also try to provide solid ground for practitioners that implement systems from this category to enhance the unsupervised processing features in order to make physical documents easily available to the masses.

On large industrial or nuclear sites there is a requirement to undertake assessments of land quality, from desk studies to detailed field investigations. Data obtained from such investigations provides the baseline from which known or potentially contaminated land can be managed. However, a commonly encountered problem is that this information is often disparate, collected for reasons not related to land quality management, with data from previous ground investigations also exhibiting the following particular problems: • The intent of a previous investigation is often not clear. • There can be much variability in investigation and analytical methods and standards. • The investigation techniques and standards are not documented. • Ground investigation and analytical data does not have adequate quality control in order to make a judgment about its value and applicability. Consequently, a commonly occurring problem is the frequent re-investigation of the same areas of a site for reasons that may not be very different. This is costly and incurs unnecessary risks. In order to resolve this problem, the UK Atomic Energy Authority (UKAEA), in conjunction with ESiT Ltd, has developed and implemented a software application to capture, interrogate and present land quality assessment data for its sites across the UK. The overall assessment of land quality on the sites relies on information that is both varied and disparate in nature. Tools are therefore required to structure and assess this information to enable clear interpretation and management decisions to be made. UKAEA has applied these tools to several areas within its environmental restoration programme including delicensing activities, Safety Cases for contaminated ground, inventories of land liabilities as well as the general monitoring of the environmental conditions on and surrounding the sites. This paper will describe the software application in the context of its function as a land quality management tool. The software application, known as the Information Management and Geographic Evaluation System (IMAGES), has a modular design and facilitates multi-user access. IMAGES interfaces with standard desktop applications to enable straightforward upload or reporting of data. There are also interfaces with industry standard software packages for spatial analysis of data (ArcGIS) and to provide representation of borehole logging data. The modules that make up IMAGES are: • Land & Risk Assessment “Sentencing”; • Document Register; • Photograph/Image register; • Site Investigation; • Excavation & Soil Transfer; • Groundwater Monitoring; • Radiation survey (Health Physics) Monitoring; • Buildings Information; • Geographic Information System (GIS) Data Management. The IMAGES solution is process based, dealing with data acquisition through storage and interpretation to output and has the ability to systematically deal with large volumes of information while ensuring consistency in approach at each stage. It also provides data that is access and revision-controlled and quality assessed. IMAGES also includes a series of standard data capture templates to enable environmental monitoring and site investigation information to be captured directly in the field and automatically logged into the IMAGES relational database structure. Data within the system can be quality assessed and queried using a map-based interface. Information held within IMAGES can also be delivered seamlessly into UKAEA’s Geographic Information System (GIS) for visual assessment and further analysis.

An experimental investigation was conducted on the internal flowfield of a simulated smooth-wall turbine blade cooling passage. The square cross-sectioned passage was manufactured from quartz for optical accessibility. Velocity measurements were taken using Particle Image Velocimetry for both heated and non-heated cases. Thin film resistive heaters on all four exterior walls of the passage allowed heat to be added to the coolant flow without obstructing laser access. Under the same conditions, an infrared detector with associated optics collected wall temperature data for use in calculating local Nusselt number. The test section was operated with radial outward flow and at values of Reynolds number and Rotation number typical of a small turbine blade. The density ratio was 0.27. Velocity data for the non-heated case document the evolution of the coriolis-induced double vortex. The vortex has the effect of disproportionately increasing the leading side boundary layer thickness. Also, the streamwise component of the coriolis acceleration creates a considerably thinned side wall boundary layer. Additionally, these data reveal a highly unsteady, turbulent flowfield in the cooling passage. Velocity data for the heated case show a strongly distorted streamwise profile indicative of a buoyancy effect on the leading side. The coriolis vortex is the mechanism for the accumulation of stagnant flow on the leading side of the passage. Heat transfer data show a maximum factor of two difference in the Nusselt number from trailing side to leading side. A first-order estimate of this heat transfer disparity based on the measured boundary layer edge velocity yields approximately the same factor of two. A momentum integral model was developed for data interpretation which accounts for coriolis and buoyancy effects. Calculated streamwise profiles and secondary flows match the experimental data well. The model, the velocity data, and the heat transfer data combine to strongly suggest the presence of separated flow on the leading wall starting at about five hydraulic diameters from the channel inlet for the conditions studied.

The Witch is a typical stereotype-busting character because its description has changed many times in a long history. This paper is an attempt to understand the visual interpretations and character positioning of the Watch by many creators in different eras, AI is being used to help summarize current stereotypes in witch design, and to propose a way to subvert the Witch stereotype in current popular culture. This study aims to understand the visual interpretations of witches and character positioning by many creators in different eras, and to subvert the stereotype of witches in current popular culture. This study provides material for future research on character design stereotypes, and an attempt is proposed to use artificial intelligence to break the stereotypes in design and is being documented as an experiment in how to subvert current stereotypes from various periods in history. The method begins by using AI to compile stereotypical images of contemporary witches. Then, the two major components of the stereotype, "accessories" and "appearance," are analyzed from historical and social perspectives and attributed to the reasons for the formation and transformation of the Witch image. These past stereotypes are designed using the design approach of "extraction" "retention" and "conversion.", and finally the advantages and disadvantages of this approach are summarized from a practical perspective. Research has shown that it is feasible to use AI to summarize the design elements and use them as clues to trace history. This is especially true for characters such as the Witch, who have undergone many historical transitions. The more changes there are, the more elements can be gathered, and the advantage of this method increases. Stereotypes change over time, and even when the current stereotype has become history, this method is still effective for newly created stereotypes.

Conventional formation evaluation provides fast and accurate estimations of petrophysical properties in conventional formations through conventional well logs and routine core analysis (RCA) data. However, as the complexity of the evaluated formations increases conventional formation evaluation fails to provide accurate estimates of petrophysical properties. This inaccuracy is mainly caused by rapid variation in rock fabric (i.e., spatial distribution of rock components) not properly captured by conventional well logging tools and interpretation methods. Acquisition of high-resolution whole-core computed tomography (CT) scanning images can help to identify rock-fabric-related parameters that can enhance formation evaluation. In a recent publication, we introduced a permeability-based cost function for rock classification, optimization of the number of rock classes, and estimation of permeability. Incorporation of additional petrophysical properties into the proposed cost function can improved the reliability of the detected rock classes and ultimately improve the estimation of class-based petrophysical properties. The objectives of this paper are (a) to introduce a robust optimization method for rock classification and estimation of petrophysical properties, (b), to automatically employ whole-core two-dimensional (2D) CT-scan images and slabbed whole-core photos for enhanced estimates of petrophysical properties, (c) to integrate whole-core CT-scan images and slabbed whole-core photos with well logs and RCA data for automatic rock classification, (d) to derive class-based rock physics models for improved estimates of petrophysical properties. First, we conducted formation evaluation using well logs and RCA data for estimation of petrophysical properties. Then, we derived quantitative features from 2D CT-scan images and slabbed whole-core photos. We employed image-based features, RCA data and CT-scan-based bulk density for optimization of the number rock classes. Optimization of rock classes was accomplished using a physics-based cost function (i.e., a function of petrophysical properties of the rock) that compares class-based estimates of petrophysical properties (e.g., permeability and porosity) with core-measured properties for increasing number of image-based rock classes. The cost function is computed until convergence is achieved. Finally, we used class-based rock physics models for improved estimates of porosity and permeability. We demonstrated the reliability of the proposed method using whole-core CT-scan images and core photos from two siliciclastic depth intervals with measurable variation in rock fabric. We used well logs, RCA data, and CT-scan-based bulk-density. The advantages of using whole-core CT-scan data are two-fold. First, it provides high-resolution quantitative features that capture rapid spatial variation in rock fabric allowing accurate rock classification. Second, the use of CT-scan-based bulk density improved the accuracy of class-based porosity-bulk density models. The optimum number of rock classes was consistent for all the evaluated cost functions. Class-based rock physics models improved the estimates of porosity and permeability values. A unique contribution of the introduced workflow when compared to previously documented image-based rock classification workflows is that it simultaneously improves estimates of both porosity and permeability, and it can capture rock class that might not be identifiable using conventional rock classification techniques.

Historical research report on the external architectural surfaces of the fortress of San LeoThe hinterland of Rimini is characterized by the presence of many castles, but the fortress of San Leo is certainly the most representative because of its position and the different constructive contributions that over time have updated its appearance and military functions. Cited by Dante and Machiavelli for the impervious nature on which it stands, its origin dates back to the early Middle Ages. It was rehashed following the imprint of Francesco di Giorgio Martini in the fifteenth century, restored by Giuseppe Valadier at the end of the eighteenth century and converted to a prison in 1631. A peculiarity that makes the studies on the fortress of San Leo absolutely interesting is the treatment of the external architectural surfaces of which there is ample documentation in the historical archives and of which there are multiple uses in the various areas of the factory; the research aims to offer useful knowledge for the subsequent conservation and restoration project. The theme, completely original, arises from indirect investigations of a documentary and iconographic nature, conducted at the State Archives of Pesaro, Florence, Rome, the Central State Archive and the Vatican Secret Archive, which repeatedly refer in the accounting of works, starting from the seventeenth century, the execution of plasters executed outside the monument. The interpretative tension of the archival documents and the drawings continued by looking for a direct comparison between historical information and materiality of the fortress, in order to identify a correspondence between historical data and constructive reality. It emerges clearly that the external surfaces of many parts of the fortress were treated and finished with plaster since its origins, probably due to the exposure to atmospheric agents; therefore a rethinking of what is reported in the literature is necessary both in terms of interpretative profile of the fortress, and about how its image was perceived over the centuries.

Aim/Purpose: The problem statement in the proposed study focuses on what strategies enterprise information systems specialists need to integrate novel algorithms into an imaging application that had not yet been identified. The aim is to demonstrate that a cross-convolutional neural network can be implemented within the home laboratory – an exploration of a virtual connection for re-search. An analysis of the works provides the basis for future extensibility of the software application for ImageJ2. Background: The study was guided by the research question: What strategies do enterprise information systems specialists need to integrate novel algorithms into an imaging application? This study demonstrates how to bring a lab-tested application online within a home laboratory to further build upon those findings. Methodology: A conceptual analysis was utilized for the artifact’s creation within the umbrella of design science to aid in the data interpretation segment. A conceptual framework was developed to determine relevant subject matter, such as useful software applications and technological enhancements to an image application. A research sample was not used in this study. Contribution: This research contributed to the body of knowledge by using a cross-convolutional neural network to explore novel algorithms as an enterprise information system specialist and set up the imaging application called Im-ageJ2 for development. The study’s setup is documented in a series of steps to demonstrate the how-to set up such a study. Findings: The findings were that it is possible to implement an existing work from within the home laboratory, steps of which are outlined for those to follow. Future work can be extended from the baseline workings. Furthermore, an analysis of the existing code was determined to see if the existing PyTorch code could be developed within Java to act as an extension to ImageJ2 later. By examining the programming code and the cross-convolutional functionality, a determination was made on the best Java mapping. A set of highlights of the processes used are included. Recommendations for Practitioners: The study intersects two differing realms: artificial intelligence and the enterprise information systems network. This study builds upon an AWS system and details the steps to implement an artificial intelligence system on the Amazon Web Service (AWS) platform. The researcher investigated existing soft-ware imaging Java applications and probed the areas of potential extensibility for implementing the artificial intelligence novel algorithms. Recommendations for Researchers: The concept of being able to bring online a turnkey set of computer hard-ware off-the-shelf within the home laboratory may be an unexplored avenue to some researchers. The recommendation is to encourage researchers to see past the constraints that a lack of hardware may bring about for computer science research. The researcher no longer has to be within an office laboratory on campus to access power computers. The doors are open to exploring a whole new world. It explores how to move through the various linkage is-sues with old libraries and new systems. Other avenues this research can enhance are extending the ImageJ libraries as a Java plugin with the novel algorithms such as the cross-convolutional network implemented on the AWS platform. Impact on Society: Expanding the accessibility to the researcher and practitioner field could be profound. No longer is the researcher or practitioner constrained to the office laboratory. This work shows how to move through the issues to invoke the software to produce and investigate existing software. The findings and guidance of this study are profound. Future Research: Future research should focus on implementing the mappings table as deter-mined in previous research. A future design could be pursued from the analysis and implementation of a Java neural network algorithm as a basic implementation. Java can chain elements to begin replicating the algorithm by Xue et al. (2019). The cross-convolutional element should have further analysis to ensure the full replication within Java. A cross-convolutional neural network (CCNN) Java algorithm could be implemented and trial run within the code; this would allow for the leverage of the heavy lifting of the program code to predict image motion. There seemed to be few approaches regarding predicting motion frames of a future image, and such predictions could be a giant leap for the health care world regarding microscopic and x-ray images.

Introduction CConsidering nowadays student's psycho-social profile (traits, interests, values), a natural consequence is to reconsider teacher's competences able to optimally interact in didactic activities with his pupils. Purpose of study In this context, our study is exploring primary and pre-primary teacher's awareness about the purpose and the effects of using informatics technologies in didactic activities. Our study have followed to analyse the hypotheses that there is an obvious discordance between didactic methodologies (and technologies) currently used by teachers in didactic activities and those used during demonstrative lessons performed in order to be evaluated and to obtain first didactic degree. Research methodology In order to fulfil our purpose we have investigated 10 primary and pre-primary teachers (with first didactic degree and at least 10 years didactic experience) and 10 members of the examination committee for the granting first didactic degree (lecturers / professors from universities and schools inspectors). Our methods were observation, individualised interview and opinion questionnaire. Findings and interpretations Our hypothesis has been confirmed: teachers from primary and pre-primary schools (especially those form primary schools) are using in an overwhelming proportion (86%) informatics technologies especially in a demonstrative purpose (during demonstrative lessons performed in order to obtain first didactic degree) and less in current practice. Conclusion This result indicate primary and pre-primary teachers interest for a valued self-image (see the principle of self presentation by E. Goffman, 1959) demonstrated in front of evaluation committee and less for raising the efficiency of didactic activity (and raising pupils' motivation, receptivity, contextual learning etc.). Other results are discussed here. Our study is focused analyse of the primary and pre-primary teachers' motivation for using IT in assisted / demonstrative lessons in order to obtain didactic degree. Using documents' analyze, focus-group and individualised interview we have reached to the conclusion that teachers from primary and pre-primary schools are using in an overwhelming proportion informatics technologies especially in a demonstrative purpose (in order to obtain first didactic degree) and less in current practice. Other results are discussed here.

We provide an updated presentation of the spectacular erosion forms at French River Ontario (Kor et al. 1991) based on new methods of data collection and wider observations. This work includes ~ 10 more detailed study sites, documentation of the range of forms over a larger area, the use of extensive drone image capture and ground surveys, as well as a detailed inventory of forms. Key sites are illustrated using video images. The update extends the conclusions of the Kor paper regarding the significance and scale of subglacial meltwater erosion with some novel findings. We document the importance of plucking (including hydraulic plucking) and, the control of structure on s-forms, which were not highlighted in the Kor study. Apparent cavitation erosion forms are prominent across the study area and provide support for inferred high-velocity meltwater flow. A growing interpretative framework includes discussion of evidence to test a theorized hydraulic sequence of sheet-channel-distributed flow, followed by re-grounding of glacial ice as meltwater flow waned. This hydraulic sequence may also be complementary to observations in thick sediment terrain down flow.

An interpretation of approximately 1700 km of seismic data was completed in 1996. The seismic analysis, together with well information and geological map data, were used to map thirteen seismic horizons in the Cumberland Basin. Ten of the horizons were mapped only in limited areas, whereas three horizons could be mapped regionally. These are: BW (base of the Windsor Group), BP (base of the Boss Point Formation), and PG (base of the Pictou Group). The BW horizon is the deepest regional horizon mapped. The horizon generally dips southerly toward the Cobequid Highlands. It is affected by faults adjacent to the Scotsburn Anticline and the Hastings Uplift; the horizon was not recognized over part of the uplift. On the seismic reflection data, the horizon varies between 500 ms and 3200 ms two-way travel time (approximately 800-7600 metres) and rocks corresponding to this horizon do not outcrop in the basin. The BP and PG horizons can be traced to outcrop on the flanks of the major anticlines. Time structure maps of these horizons mimic the distribution of synclines mapped from outcrop geology. The BP horizon is affected by more faults and is more tightly folded than the PG horizon south of a major fault (Beckwith Fault). North of the Beckwith Fault, both horizons are essentially flat and not deformed. Several geological relationships were documented during this study. A thick (up to 1600 m) clastic unit was recognized in the central portion of the southern margin of the Cumberland Basin. It is interpreted as Windsor Group equivalent. Seismic reflections from within the Falls and Millsville conglomerates were recognized and suggest that these rocks correlate with the Windsor Group. Seismic profiles that cross the southern margin of the Cumberland Basin image parts of the asement complex to the south of the basin (Cobequid Highlands) and show reflection patterns consistent with mountain fronts. The seismic data image the folded and faulted Cobequid Highlands basement complex, which is interpreted as a thrusted structural wedge.

The November 25, 1988, moment magnitude 5.9 (Mw) Saguenay earthquake is one of the largest eastern Canadian earthquakes of the 20th century. It was preceded by a magnitude (MN) 4.7 foreshock and followed by very few aftershocks considering the magnitude of the main shock. The largest aftershock was a magnitude (MN) 4.3 event. This Open File (OF) Report presents a variety of documents (including original and interpreted felt information, images, newspaper clippings, various engineering reports on the damage, mass movements). This OF updates the report of Cajka and Drysdale (1994) with additional material, including descriptions of the foreshock and largest aftershock. Most of the felt report information come from replies of a questionnaire sent to postmasters in more than 2000 localities in Canada and in the United States. Images of the original felt reports from Canada are included. The OF also includes information gathered in damage assessments and newspaper accounts. For each locality, the interpreted information is presented in a digital table. The fields include the name, latitude and longitude of the municipality and the interpreted intensity on the Modified Mercalli Intensity (MMI) scale (most of which are the interpretations of Cajka and Drysdale, 1996). When available or significant, excerpts of the felt reports are added. This OF Report also includes images from contemporary newspapers that describe the impact. In addition, information contained in post-earthquake reports are discussed together with pictures of damage and mass movements. Finally, a GoogleEarth kmz file is added for viewing the felt information reports within a spatial tool.

The Time Of Flight Diffraction (TOFD) Technique is rapidly gaining importance as a reliable NDT technique for weld inspection, capable of both detection and sizing of defects. The acquisition of TOFD inspection data is fast and straightforward; the crucial step in inspection reliability is therefore its interpretation. A reliable interpretation of TOFD images requires considerable training and skill, and in that respect bears resemblance to the interpretation of radiographic images. Therefore a need was recognized to develop a TOFD Image Reference Collection, by analogy with the existing and widely known IIW Collection of Reference Radiographs of Welds in Steel, to assist TOFD operators in analyzing images. The objective to arrive at a reference collection of TOFD Images. The TOFD image collection is a stand-alone document. Revision 0 contains, apart from typical inspection results for most defect types, an extensive introduction describing purpose, scope and instructions for use.