Proposta metodológica para o imageamento digital e modelagem virtual 3d de um bloco de rochas travertinas

In this paper we present the methodological procedures involved in the digital imaging in mesoscale of a block of travertines rock of quaternary age, originating from the city of Acquasanta, located in the Apennines, Italy. This rocky block, called T-Block, was stored in the courtyard of the Laboratório Experimental Petróleo "Kelsen Valente" (LabPetro), of Universidade Estadual de Campinas (UNICAMP), so that from it were performed Scientific studies, mainly for research groups universities and research centers working in brazilian areas of reservoir characterization and 3D digital imaging. The purpose of this work is the development of a Model Solid Digital, from the use of non-invasive techniques of digital 3D imaging of internal and external surfaces of the T-Block. For the imaging of the external surfaces technology has been used LIDAR (Light Detection and Range) and the imaging surface Interior was done using Ground Penetrating Radar (GPR), moreover, profiles were obtained with a Gamma Ray Gamae-spectômetro laptop. The goal of 3D digital imaging involved the identification and parameterization of surface geological and sedimentary facies that could represent heterogeneities depositional mesoscale, based on study of a block rocky with dimensions of approximately 1.60 m x 1.60 m x 2.70 m. The data acquired by means of terrestrial laser scanner made available georeferenced spatial information of the surface of the block (X, Y, Z), and varying the intensity values of the return laser beam and high resolution RGB data (3 mm x 3 mm), total points acquired 28,505,106. This information was used as an aid in the interpretation of radargrams and are ready to be displayed in rooms virtual reality. With the GPR was obtained 15 profiles of 2.3 m and 2 3D grids, each with 24 sections horizontal of 1.3 and 14 m vertical sections of 2.3 m, both the Antenna 900 MHz to about 2600 MHz antenna. Finally, the use of GPR associated with Laser Scanner enabled the identification and 3D mapping of 3 different radarfácies which were correlated with three sedimentary facies as had been defined at the outset. The 6 profiles showed gamma a low amplitude variation in the values of radioactivity. This is likely due to the fact of the sedimentary layers profiled have the same mineralogical composition, being composed by carbonate sediments, with no clay in siliciclastic pellitic layers or other mineral carrier elements radioactive

Mejoras y extensiones en el Front-End de un modelo de predicción de acciones de un estudiante en un laboratorio virtual 3D

Este documento presenta las mejoras y las extensiones introducidas en la herramienta de visualización del modelo predictivo del comportamiento del estudiante o Student Behavior Predictor Viewer (SBPV), implementada en un trabajo anterior. El modelo predictivo del comportamiento del estudiante es parte de un sistema inteligente de tutoría, y se construye a partir de los registros de actividad de los estudiantes en un laboratorio virtual 3D, como el Laboratorio Virtual de Biotecnología Agroforestal, implementado en un trabajo anterior, y cuyos registros de actividad de los estudiantes se han utilizado para validar este trabajo fin de grado. El SBPV es una herramienta para visualizar una representación gráfica 2D del grafo extendido asociado con cualquiera de los clusters del modelo predictivo del estudiante. Además de la visualización del grafo extendido, el SBPV controla la navegación a través del grafo por medio del navegador web. Más concretamente, el SBPV permite al usuario moverse a través del grafo, ampliar o reducir el zoom del gráfico o buscar un determinado estado. Además, el SBPV también permite al usuario modificar el diseño predeterminado del grafo en la pantalla al cambiar la posición de los estados con el ratón. Como parte de este trabajo fin de grado, se han corregido errores existentes en la versión anterior y se han introducido una serie de mejoras en el rendimiento y la usabilidad. En este sentido, se han implementado nuevas funcionalidades, tales como la visualización del modelo de comportamiento de cada estudiante individualmente o la posibilidad de elegir el método de clustering para crear el modelo predictivo del estudiante; así como ha sido necesario rediseñar la interfaz de usuario cambiando el tipo de estructuras gráficas con que se muestran los elementos del modelo y mejorando la visualización del grafo al interaccionar el usuario con él. Todas estas mejoras se explican detenidamente en el presente documento.---ABSTRACT---This document presents the improvements and extensions made to the visualization tool Student Behavior Predictor Viewer (SBPV), implemented in a previous job. The student behavior predictive model is part of an intelligent tutoring system, and is built from the records of students activity in a 3D virtual laboratory, like the “Virtual Laboratory of Agroforestry Biotechnology” implemented in a previous work, and whose records of students activity have been used to validate this final degree work. The SBPV is a tool for visualizing a 2D graphical representation of the extended graph associated with any of the clusters of the student predictive model. Apart from visualizing the extended graph, the SBPV supports the navigation across the graph by means of desktop devices. More precisely, the SBPV allows user to move through the graph, to zoom in/out the graphic or to locate a given state. In addition, the SBPV also allows user to modify the default layout of the graph on the screen by changing the position of the states by means of the mouse. As part of this work, some bugs of the previous version have been fixed and some enhancements have been implemented to improve the performance and the usability. In this sense, we have implemented new features, such as the display of the model behavior of only one student or the possibility of selecting the clustering method to create the student predictive model; as well as it was necessary to redesign the user interface changing the type of graphic structures that show model elements and improving the rendering of the graph when the user interacts with it. All these improvements are explained in detail in the next sections.

3D model reconstruction using neural gas accelerated on GPU

In this work, we propose the use of the neural gas (NG), a neural network that uses an unsupervised Competitive Hebbian Learning (CHL) rule, to develop a reverse engineering process. This is a simple and accurate method to reconstruct objects from point clouds obtained from multiple overlapping views using low-cost sensors. In contrast to other methods that may need several stages that include downsampling, noise filtering and many other tasks, the NG automatically obtains the 3D model of the scanned objects. To demonstrate the validity of our proposal we tested our method with several models and performed a study of the neural network parameterization computing the quality of representation and also comparing results with other neural methods like growing neural gas and Kohonen maps or classical methods like Voxel Grid. We also reconstructed models acquired by low cost sensors that can be used in virtual and augmented reality environments for redesign or manipulation purposes. Since the NG algorithm has a strong computational cost we propose its acceleration. We have redesigned and implemented the NG learning algorithm to fit it onto Graphics Processing Units using CUDA. A speed-up of 180× faster is obtained compared to the sequential CPU version.

Context-aware 3D model generation for biomedical applications

Magdeburg, Univ., Fak. für Informatik, Diss., 2014

Mecano Virtual 3D

L'objectiu principal d'aquest projecte és crear un mecano virtual amb el qual l'usuari pugui manipular peces per a fer un muntatge i que pugui retocar aquest muntatge com vulgui.

Validation of a 3D model for oxygen combustion in a circulating fluidized bed

In this thesis, a model called CFB3D is validated for oxygen combustion in circulating fluidized bed boiler. The first part of the work consists of literature review in which circulating fluidized bed and oxygen combustion technologies are studied. In addition, the modeling of circulating fluidized bed furnaces is discussed and currently available industrial scale three-dimensional furnace models are presented. The main features of CFB3D model are presented along with the theories and equations related to the model parameters used in this work. The second part of this work consists of the actual research and modeling work including measurements, model setup, and modeling results. The objectives of this thesis is to study how well CFB3D model works with oxygen combustion compared to air combustion in circulating fluidized bed boiler and what model parameters need to be adjusted when changing from air to oxygen combustion. The study is performed by modeling two air combustion cases and two oxygen combustion cases with comparable boiler loads. The cases are measured at Ciuden 30 MWth Flexi-Burn demonstration plant in April 2012. The modeled furnace temperatures match with the measurements as well in oxygen combustion cases as in air combustion cases but the modeled gas concentrations differ from the measurements clearly more in oxygen combustion cases. However, the same model parameters are optimal for both air and oxygen combustion cases. When the boiler load is changed, some combustion and heat transfer related model parameters need to be adjusted. To improve the accuracy of modeling results, better flow dynamics model should be developed in the CFB3D model. Additionally, more measurements are needed from the lower furnace to find the best model parameters for each case. The validation work needs to be continued in order to improve the modeling results and model predictability.

Improving sequence-based fold recognition by using 3D model quality assessment

Motivation: The ability of a simple method (MODCHECK) to determine the sequence–structure compatibility of a set of structural models generated by fold recognition is tested in a thorough benchmark analysis. Four Model Quality Assessment Programs (MQAPs) were tested on 188 targets from the latest LiveBench-9 automated structure evaluation experiment. We systematically test and evaluate whether the MQAP methods can successfully detect native-likemodels. Results: We show that compared with the other three methods tested MODCHECK is the most reliable method for consistently performing the best top model selection and for ranking the models. In addition, we show that the choice of model similarity score used to assess a model's similarity to the experimental structure can influence the overall performance of these tools. Although these MQAP methods fail to improve the model selection performance for methods that already incorporate protein three dimension (3D) structural information, an improvement is observed for methods that are purely sequence-based, including the best profile–profile methods. This suggests that even the best sequence-based fold recognition methods can still be improved by taking into account the 3D structural information.

Hausdorff Distance evaluation of orthodontic accessories' streaking artifacts in 3D model superimposition

The aim of this study was to determine whether image artifacts caused by orthodontic metal accessories interfere with the accuracy of 3D CBCT model superimposition. A human dry skull was subjected three times to a CBCT scan: at first without orthodontic brackets (T1), then with stainless steel brackets bonded without (T2) and with orthodontic arch wires (T3) inserted into the brackets' slots. The registration of image surfaces and the superimposition of 3D models were performed. Within-subject surface distances between T1-T2, T1-T3 and T2-T3 were computed and calculated for comparison among the three data sets. The minimum and maximum Hausdorff Distance units (HDu) computed between the corresponding data points of the T1 and T2 CBCT 3D surface images were 0.000000 and 0.049280 HDu, respectively, and the mean distance was 0.002497 HDu. The minimum and maximum Hausdorff Distances between T1 and T3 were 0.000000 and 0.047440 HDu, respectively, with a mean distance of 0.002585 HDu. In the comparison between T2 and T3, the minimum, maximum and mean Hausdorff Distances were 0.000000, 0.025616 and 0.000347 HDu, respectively. In the current study, the image artifacts caused by metal orthodontic accessories did not compromise the accuracy of the 3D model superimposition. Color-coded maps of overlaid structures complemented the computed Hausdorff Distances and demonstrated a precise fusion between the data sets.

Laser scanning microscopy combined with image restoration to analyse a 3D model of the human epithelial airway barrier

A laser scanning microscope collects information from a thin, focal plane and ignores out of focus information. During the past few years it has become the standard imaging method to characterise cellular morphology and structures in static as well as in living samples. Laser scanning microscopy combined with digital image restoration is an excellent tool for analysing the cellular cytoarchitecture, expression of specific proteins and interactions of various cell types, thus defining valid criteria for the optimisation of cell culture models. We have used this tool to establish and evaluate a three dimensional model of the human epithelial airway wall.