856 resultados para backward mapping


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Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

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Rob Kitchin, geógrafo muy activo y prolífico, mantiene una intensa actividad editorial, puesto que dirige colecciones de temas geográficos y forma parte de los comités asesores de varias revistas internacionales de primera línea, entre ellas, Social and Cultural Geography, que se publica bimensualmente desde el año 2000 y de la que es director. Precisamente, en esta revista dedicada a temas relacionados con la geografía cultural y social se halla el origen de este libro, uno de cuyos propósitos iniciales fue desafiar la hegemonía anglosajona que domina el panorama geográfico internacional.

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Webben är en enorm källa för information. Innehållet på webbsidorna är en synlig typ av information, men webben innehåller även information av en annan typ, en mera gömd typ i form av sambanden och nätverken som hyperlänkarna skapar mellan webbsajterna och –sidorna som de kopplar ihop. Forskningsområdet webometri ämnar, bland annat, att skapa ny kunskap ur denna gömda information som finns inbyggt i hyperlänkarna samt att skapa förståelse för hurudana fenomen och förhållanden utanför webben kan finnas representerade i hyperlänkarna. Målet med denna forskning var att öka förståelse för användningen av hyperlänkar på webben och speciellt kommunernas användning av hyperlänkar. Denna forskning undersökte hur kommunerna i Egentliga Finland skapade och mottog hyperlänkar samt hurudana nätverk formades av dessa hyperlänkar. Forskningen kartlade nätverk av direkta länkar mellan kommunerna och av samlänkar till och från kommunerna och undersökte ifall dessa nätverk kunde användas för att undersöka geopolitiska förhållanden och samarbete mellan kommunerna i Egentliga Finland. De övergripande forskningsfrågorna som har besvarats i denna forskning är: 1) Från ett webometriskt perspektiv, hur använder kommunerna i Egentliga Finland webben? 2) Kan hyperlänkar (direkta länkar och samlänkar) användas för att kartlägga geopolitiska förhållanden och samarbete mellan kommuner? 3) Vilka är de viktigaste motiveringarna för att skapa länkar mellan, till och från kommunernas webbsajter? Denna forskning kom till ovanligt tydliga resultat för en webometrisk forskning, både när det gäller upptäckta geografiska faktorer som påverkar hyperlänkningarna och de klassificerade motivationerna för att skapa länkarna. Resultaten visade att de direkta hyperlänkarna mellan kommunerna kan användas för att kartlägga geopolitiska förhållanden och samarbete mellan kommunerna för att de direkta länkarna var motiverade av officiella orsaker och de var klart påverkade av distansen mellan kommunerna och av de ekonomiska regionerna. Samlänkningarna in till kommunerna visade sig fungera som ett mått för geografisk likhet mellan kommunerna, medan samlänkningarna ut från kommunerna visade potential för att kunna användas till för att kartlägga kommunernas gemensamma intressen. Forskningen kontribuerade även till utvecklandet av forskningsområdet webometri. En del av de viktigaste kontributionerna av denna forskning var utvecklandet av nya metoder för webometrisk forskning samt att öka kunskap om hur existerande metoder från nätverksanalys kan användas effektivt för webometrisk forskning. Resultaten från denna forskning och de utvecklade metoderna kan användas för snabba kartläggningar av diverse förhållanden mellan olika organisationer och företag genom att använda information gratis tillgängligt på webben.

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The present work aimed to characterize and identify QTLs for wood quality and growth traits in E. grandis x E. urophylla hybrids. For this purpose a RAPD linkage map was developed for the hybrids (LOD=3 and r=0.40) containing 52 markers and 12 linkage groups. Traits related to wood quality and growth were evaluated in the QTL analyses. QTL analyses were performed using chi-square tests, single-marker, interval mapping and composite interval mapping analyses. All approaches led to the identification of similar QTLs associated with wood density, cellulose pulp yield and percentage of extractives, which were detected and confirmed by both the interval mapping and composite interval mapping methodologies. Some QTLs regions were confirmed only by the composite interval mapping methodology: percentage of soluble lignin, percentage of insoluble lignin, CBH and total height. Overlapping QTLs regions were detected, and these, can be the result of major genes involved in the regulation and control of the growth traits by epistatic interactions. In order to evaluate the effect of early selection using RAPD molecular data, molecular markers adjacent to QTLs were used genotype selection. The analysis of selection differential values suggests that for all the traits the phenotypic selection at seven years should generate larger genetic gains than early selection assisted by molecular markers and the combination of the strategies should elevate the selection efficiency.

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This paper aims to assess the effectiveness of ASTER imagery to support the mapping of Pittosporum undulatum, an invasive woody species, in Pico da Vara Natural Reserve (S. Miguel Island, Archipelago of the Azores, Portugal). This assessment was done by applying K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Maximum Likelihood (MLC) pixel-based supervised classifications to 4 different geographic and remote sensing datasets constituted by the Visible, Near-Infrared (VNIR) and Short Wave Infrared (SWIR) of the ASTER sensor and by digital cartography associated to orography (altitude and "distance to water streams") of which the spatial distribution of Pittosporum undulatum directly depends. Overall, most performed classifications showed a strong agreement and high accuracy. At targeted species level, the two higher classification accuracies were obtained when applying MLC and KNN to the VNIR bands coupled with auxiliary geographic information use. Results improved significantly by including ecology and occurrence information of species (altitude and distance to water streams) in the classification scheme. These results show that the use of ASTER sensor VNIR spectral bands, when coupled to relevant ancillary GIS data, can constitute an effective and low cost approach for the evaluation and continuous assessment of Pittosporum undulatum woodland propagation and distribution within Protected Areas of the Azores Islands.

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The search for low subjectivity area estimates has increased the use of remote sensing for agricultural monitoring and crop yield prediction, leading to more flexibility in data acquisition and lower costs comparing to traditional methods such as census and surveys. Low spatial resolution satellite images with higher frequency in image acquisition have shown to be adequate for cropland mapping and monitoring in large areas. The main goal of this study was to map the Summer crops in the State of Paraná, Brazil, using 10-day composition of NDVI SPOT Vegetation data for 2005/2006, 2006/2007 and 2007/2008 cropping seasons. For this, a supervised digital classification method with Parallelepiped algorithm in multitemporal RGB image composites was used, in order to generate masks of Summer cultures for each 10-day composition. Accuracy assessment was performed using Kappa index, overall accuracy and Willmott's concordance index, resulting in good levels of accuracy. This methodology allowed the accomplishment, with free and low resolution data, of the mapping of Summer cultures at State level.

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The objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of the following classes: crops, bare soil/stubble, forests and urban area. The PCA technique applied to irrigation water quality data explained 53.27% of the variation in water quality among the sampled points. Nitrate, thermotolerant coliforms, temperature, electrical conductivity and bicarbonate were the parameters that best explained the spatial variation of water quality.

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Coffee production was closely linked to the economic development of Brazil and, even today, coffee is an important product of the national agriculture. The State of Minas Gerais currently accounts for 52% of the whole coffee area in Brazil. Remote sensing data can provide information for monitoring and mapping of coffee crops, faster and cheaper than conventional methods. In this context, the objective of this study was to assess the effectiveness of coffee crop mapping in Monte Santo de Minas municipality, Minas Gerais State, Brazil, from fraction images derived from MODIS data, in both dry and rainy seasons. The Spectral Linear Mixing Model was used to derive fraction images of soil, coffee, and water/shade. These fraction images served as input data for the supervised automatic classification using the SVM - Support Vector Machine approach. The best results concerning Overall Accuracy and Kappa Index were obtained in the classification of the dry season, with 67% and 0.41, respectively.

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Tämän pro gradu -tutkielman aiheena on kääntäminen ja viestintä vieraalla kielellä Suomen ulkoasiainministeriön rahoittamissa kansalaisjärjestöjen kehitysyhteistyöhankkeissa. Tutkielman on tarkoitus kartoittaa kyseisten kehitysyhteistyöhankkeiden kääntämiseen ja vieraskieliseen viestintään liittyviä tarpeita ja -käytäntöjä. Aihetta ei ole tutkittu laajasti muutoin, joten empiirinen osuus on erityisen merkittävässä roolissa. Tutkielman alussa esitellään ulkoasiainministeriön laatimia suomalaisten kansalaisjärjestöjen kehitysyhteistyöhankkeiden ehtoja ja ohjeita, jotka ovat kyseiselle tutkimukselle olennaisia. Tutkielman teoreettinen osuus koostuu lähinnä metodologisesta pohdinnasta, koska aiempaa tutkimustietoa on vähän. Tutkimusmetodien analysointia on painotettu myös siksi, että empiirisellä osuudella on niin suuri merkitys. Tutkielman empiirinen aineisto on yhtäältä peräisin tutkijan havainnoista, jotka saatiin omia varhaisempia hankehallinnointikokemuksia hyödyntäen sekä osallistuvan havainnoinnin menetelmää käyttäen kahden opiskelijajärjestön kehitysyhteistyöhankkeista vuosien 2009 ja 2012 välisenä aikana. Toisaalta aineisto on kerätty kyselytutkimuksen vastauksista. Kysely lähetettiin 35 suomalaiselle kansalaisjärjestölle, joiden kehitysyhteistyöhankkeita Suomen ulkoasiainministeriö rahoittaa. Järjestöt valittiin satunnaisotannalla. Empiirisen aineiston analyysistä ilmeni muun muassa, että tutkijan alkuperäinen hypoteesi kehitysyhteistyöhön liittyvien tekstien kääntämisen yleisyydestä pitää osittain paikkansa, vaikka tekstejä käännettiinkin kansalaisjärjestöissä vähemmän kuin tutkija odotti. Tutkimusaineisto ei ole kuitenkaan tarpeeksi laaja, jotta tuloksia voitaisiin yleistää, sillä kansalaisjärjestöt, niiden hankkeet, käännöstarpeet ja asiantuntemus osoittautuivat odotetusti hyvin erilaisiksi. Tulokset sisältävät asiaa myös esimerkiksi järjestöissä kääntävien ja vieraalla kielellä viestivien taustoista. Jatkotutkimukset ovat kuitenkin tarpeen, ja mahdollisia tutkimusaiheita on runsaasti.

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The ongoing global financial crisis has demonstrated the importance of a systemwide, or macroprudential, approach to safeguarding financial stability. An essential part of macroprudential oversight concerns the tasks of early identification and assessment of risks and vulnerabilities that eventually may lead to a systemic financial crisis. Thriving tools are crucial as they allow early policy actions to decrease or prevent further build-up of risks or to otherwise enhance the shock absorption capacity of the financial system. In the literature, three types of systemic risk can be identified: i ) build-up of widespread imbalances, ii ) exogenous aggregate shocks, and iii ) contagion. Accordingly, the systemic risks are matched by three categories of analytical methods for decision support: i ) early-warning, ii ) macro stress-testing, and iii ) contagion models. Stimulated by the prolonged global financial crisis, today's toolbox of analytical methods includes a wide range of innovative solutions to the two tasks of risk identification and risk assessment. Yet, the literature lacks a focus on the task of risk communication. This thesis discusses macroprudential oversight from the viewpoint of all three tasks: Within analytical tools for risk identification and risk assessment, the focus concerns a tight integration of means for risk communication. Data and dimension reduction methods, and their combinations, hold promise for representing multivariate data structures in easily understandable formats. The overall task of this thesis is to represent high-dimensional data concerning financial entities on lowdimensional displays. The low-dimensional representations have two subtasks: i ) to function as a display for individual data concerning entities and their time series, and ii ) to use the display as a basis to which additional information can be linked. The final nuance of the task is, however, set by the needs of the domain, data and methods. The following ve questions comprise subsequent steps addressed in the process of this thesis: 1. What are the needs for macroprudential oversight? 2. What form do macroprudential data take? 3. Which data and dimension reduction methods hold most promise for the task? 4. How should the methods be extended and enhanced for the task? 5. How should the methods and their extensions be applied to the task? Based upon the Self-Organizing Map (SOM), this thesis not only creates the Self-Organizing Financial Stability Map (SOFSM), but also lays out a general framework for mapping the state of financial stability. This thesis also introduces three extensions to the standard SOM for enhancing the visualization and extraction of information: i ) fuzzifications, ii ) transition probabilities, and iii ) network analysis. Thus, the SOFSM functions as a display for risk identification, on top of which risk assessments can be illustrated. In addition, this thesis puts forward the Self-Organizing Time Map (SOTM) to provide means for visual dynamic clustering, which in the context of macroprudential oversight concerns the identification of cross-sectional changes in risks and vulnerabilities over time. Rather than automated analysis, the aim of visual means for identifying and assessing risks is to support disciplined and structured judgmental analysis based upon policymakers' experience and domain intelligence, as well as external risk communication.

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A thymidine kinase (tk)-deleted bovine herpesvirus 5 (BoHV-5tkΔ) was previously shown to establish latent infection and reactivate - even poorly - in a sheep model (Cadore et al. 2013). As TK-negative alphaherpesviruses are unlike to reactivate in neural tissue, this study investigated the sites of latency and reactivation by this recombinant in lambs. For this, groups of lambs were inoculated intranasally with the parental BoHV-5 strain (SV-507/99) or with the recombinant BoHV-5tkΔ. During latent infection (40 days post-inoculation, pi), the distribution of recombinant virus DNA in neural and non-neural tissues was similar to that of the parental virus. Parental and recombinant virus DNA was consistently detected by PCR in trigeminal ganglia (TGs); frequently in palatine and pharyngeal tonsils and, less frequently in the retropharyngeal lymph nodes. In addition, latent DNA of both viruses was detected in several areas of the brain. After dexamethasone (Dx) administration (day 40pi), the recombinant virus was barely detected in nasal secretions contrasting with marked shedding of the parental virus. In tissues of lambs euthanized at day 3 post-Dx treatment (pDx), reverse-transcription-PCR (RT-PCR) for a late viral mRNA (glycoprotein D gene) demonstrated reactivation of parental virus in neural (TGs) and lymphoid tissues (tonsils, lymph node). In contrast, recombinant virus mRNA was detected only in lymphoid tissues. These results demonstrate that BoHV-5 and the recombinant BoHV-5tkΔ do establish latent infection in neural and non-neural sites. Reactivation of the recombinant BoHV-5tkΔ, however, appeared to occur only in non-neural sites. In anyway, the ability of a tk-deleted strain to reactivate latent infection deserves attention in the context of vaccine safety.

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In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.