Virtual 3D models of insects for accelerated quarantine control

We learn from the past that invasive species have caused tremendous damage to native species and serious disruption to agricultural industries. It is crucial for us to prevent this in the future. The first step of this process is to identify correctly an invasive species from native ones. Current identification methods, relying on mainly 2D images, can result in low accuracy and be time consuming. Such methods provide little help to a quarantine officer who has time constraints to response when on duty. To deal with this problem, we propose new solutions using 3D virtual models of insects. We explain how working with insects in the 3D domain can be much better than the 2D domain. We also describe how to create true-color 3D models of insects using an image-based 3D reconstruction method. This method is ideal for quarantine control and inspection tasks that involve the verification of a physical specimen against known invasive species. Finally we show that these insect models provide valuable material for other applications such as research, education, arts and entertainment. © 2013 IEEE.

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.

The 3D model of l(IT)eracy and the English curriculum

The field of literacy studies has always been challenged by the changing technologies that humans have used to express, represent and communicate their feelings, ideas, understandings and knowledge. However, while the written word has remained central to literacy processes over a long period, it is generally accepted that there have been significant changes to what constitutes ‘literate’ practice. In particular, the status of the printed word has been challenged by the increasing dominance of the image, along with the multimodal meaning-making systems facilitated by digital media. For example, Gunther Kress and other members of the New London Group have argued that the second half of the twentieth century saw a significant cultural shift from the linguistic to the visual as the dominant semiotic mode. This in turn, they suggest, was accompanied by a cultural shift ‘from page to screen’ as a dominant space of representation (e.g. Cope & Kalantzis, 2000; Kress, 2003; New London Group, 1996). In a similar vein, Bill Green has noted that we have witnessed a shift from the regime of the print apparatus to a regime of the digital electronic apparatus (Lankshear, Snyder and Green, 2000). For these reasons, the field of literacy education has been challenged to find new ways to conceptualise what is meant by ‘literacy’ in the twenty first century and to rethink the conditions under which children might best be taught to be fully literate so that they can operate with agency in today’s world.

Review of 3D model development with application to groundwater studies in New Zealand 1996 – 2011

Three dimensional geological modelling techniques have been applied since 1996 with an aim to characterise the lithological and chronological units of New Zealand’s many diverse aquifers. Models of property-scattered data have also been applied to assess physical properties of aquifers and the distribution of groundwater chemistry, including groundwater age, to inform an understanding of groundwater systems. These models, fundamental to understanding groundwater recharge, flow and discharge have found many uses as outlined in this paper.

Interpretación de información geométrica procedente de diversas fuentes para la reconstrucción virtual del Palacio de los Condestables, Casalarreina (La Rioja)

[ES] Este proyecto se ha realizado a partir de los datos del siguiente proyecto de documentación geométrica, desde donde pueden encontrarse enlaces adicionales a otros documentos relacionados:

An Efficient Correspondence Based Algorithm for 2D and 3D Model Based Recognition

A polynomial time algorithm (pruned correspondence search, PCS) with good average case performance for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image, is presented. Efficient verification algorithms, based on a linear representation of location constraints, are given for the case of affine transformations among vector spaces and for the case of rigid 2D and 3D transformations with scale. Some preliminary experiments suggest that PCS is a practical algorithm. Its similarity to existing correspondence based algorithms means that a number of existing techniques for speedup can be incorporated into PCS to improve its performance.