Made available in DSpace on 2014-06-12T22:58:05Z (GMT). No. of bitstreams: 2 arquivo1446_1.pdf: 4391997 bytes, checksum: cf2f9970dc31e357b9bdb19b4ffdf45b (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O ambiente costeiro é berçário natural para um grande número de espécies marinhas, principalmente onde ocorrem mangues e recifes, que funcionam como abrigo natural para a desova e início de vida de muitas espécies marinhas. A linha de costa está inserida nesse ambiente, pois representa o limite entre o mar e o continente, no alcance máximo das ondas, onde cessa a ação marinha efetiva. Entretanto, a dinâmica de movimentação das marés torna esse limite uma zona de fronteira de difícil demarcação e monitoramento. Além disso, as alterações geomorfológicas, muitas vezes catalisadas pelas interferências antrópicas, diminuem a capacidade de regeneração natural das praias, dificultando o gerenciamento desse ambiente. Em virtude disso, essa tese desenvolveu alguns experimentos para localizar e monitorar linhas de costa nas praias de Sauaçui e Japaratinga, localizadas no Estado de Alagoas Brasil, aplicando tecnologia de posicionamento dos sistemas GNSS (Global Navigation Satellite System), com base em um indicador de linha de costa com representação matemática, correspondente à máxima altura alcançada pelas marés nos últimos 20 anos, acrescida do run-up, correspondente ao espraio das ondas. O GPS (Global Positioning System), que a partir deste ponto será designado apenas GPS, consiste em um sistema de posicionamento por satélite pertencente ao GNSS e pode gerar posicionamentos no modo dinâmico relativo, com precisão de poucos centímetros e suas técnicas já vem sendo aplicadas em programas de gerenciamento costeiro em várias partes do mundo. Entretanto, as alturas geradas pelo GPS são elipsoidais e representam um problema para o uso desse sistema em aplicações que envolvem altitudes, como é o caso das linhas de costa, que são relacionadas com o nível do mar. A técnica proposta nessa tese gera o modelo de elevação digital da praia, com base em perfis de praia, no mesmo referencial de nível das marés e nele identifica a linha de costa. Para isso, os referenciais verticais de maré e do GPS são correlacionados através de um artifício apropriado que requer o conhecimento das alturas de maré e do GPS em um mesmo local. Os perfis de praia aqui referidos são constituídos de pontos coordenados gerados pelo deslocamento de uma antena GPS em ziguezague ao longo da praia. Essa metodologia mostrou-se adequada para localizar e monitorar linhas de costa com precisão sub-métrica e tem como principal vantagem o fato desse modelo facilitar a visualização do comportamento da linha d´água, sendo apropriado para simular o deslocamento do mar sobre o continente. Os resultados mostram a localização geográfica das linhas de costa das praias objeto desse estudo, expressas no Sistema de Projeção Cartográfica Universal Transverso de Mercator (UTM). O monitoramento da linha de costa provém da comparação do seu traçado, superpondo-se os modelos produzidos em diferentes épocas e indica comportamento sazonal das linhas de costas tanto nas praias de Japaratinga (máximo de 6,0 m), como na praia de Sauaçui (máximo de 8,0 m). Além disso, como o referencial do GPS tem grande estabilidade, ele pode ser usado no monitoramento da estabilidade dos marcos de apoio, cujas coordenadas são suscetíveis de alterações, em havendo subsidências do solo e/ou movimentações de placas da crosta terrestre

Optimizing the loading process of a front loader vehicle is a challenging task. The design space is large and depends on the design of the vehicle, the strategy of the loading process, the nature of the material to load etcetera. Finding an optimal loading strategy, with respect to production and damage on equipment would greatly improve the production and environmental impacts in mining and construction. In this thesis, a method for exploring the design space of a loading strategy is presented. The loading strategy depends on four design variables that controls the shape of the trajectory relative to the shape of the pile. The responses investigated is the production, vehicle damage and work interruptions due to rock spill. Using multi-body dynamic simulations many different strategies can be tested with little cost. The result of these simulations are then used to build surrogate models of the original unknown function. The surrogate models are used to visualize and explore the design space and construct Pareto fronts for the competing responses. The surrogate models were able to predict the production function from the simulations well. The damage and rock spill surrogate models was moderately good in predicting the simulations but still good enough to explore how the design variables affect the response. The produced Pareto fronts makes it easy for the decision maker to compare sets of design variables and choose an optimal design for the loading strategy.

<p>Grain kernel damage during harvesting and handling continues to be a challenge in grain postharvest operations. The damage causes physical and physiological changes to grain, which reduces the grain quality and leads to significant yield loss. During harvesting and handling, grain kernels are subject to complex loading conditions consisting of a combination of impact, shear, and compression forces that can result in mechanical damage. Although there is considerable empirical data focused on kernel damage, there is a lack of generalizable mechanics-based predictive models. Mechanics-based models are desirable since they would be useful for providing guidance on designing and operating grain handling processes to minimize kernel damage and, thus, improve grain quality. The objective of the current study is to develop a mechanics-based model for predicting damage of corn and wheat kernels using the discrete element method (DEM).</p> <p>The first step in DEM modeling is to determine the model input parameter values. This step is critical since the accuracy of the DEM simulations model is greatly affected by these parameters. The input parameters for the model developed in this current study are the physical and mechanical properties of corn and wheat kernels. These properties were determined by either direct measurement or calibration tests and validated with bulk material tests. X-ray micro-CT scanning method was used to acquire the grain kernel particle shape representation. The coefficient of friction (COF) was measured using a reciprocating pin tribometer. The coefficient of restitution (COR) was measured using the calibration method with a box containing multiple bins. The measured model parameter values were used to simulate common bulk material tests, i.e. bulk density and angle of repose. A comparison was made between the simulated results and the experimental measurements. The low percent error between experimental and simulated values indicate the accurate model parameter values estimation.</p> <p>The damage resistance of corn and wheat kernels to compression, friction, and repeated impacts were measured using the universal testing machine, pin-on-disk tribometer, and Wisconsin breakage tester, respectively. Lognormal distribution was used to model the compression test data, and three-parameter Weibull distribution was used to model the single and repeated impact test data. The statistical models were able accurately predict the damage probability based on the loading force or input energy. The wear damage was insignificant for corn-acrylic, corn-steel, and wheat-acrylic wear tests. For wheat-steel wear test, the average work done by the friction force to cause pericarp damage was 3.85 1.50 J. The test results showed that the corn kernels were more susceptible to impact loading, while wheat kernels were more susceptible to compression loading. Both corn and wheat kernels had high resistance to wear damage.</p> <p>The statistical model that predicts the impact damage probability based on impact energy was implemented in DEM. Stein breakage tester was used to validate the developed model. The damage level of the samples was then evaluated and compared with the predicted damage level output by the DEM simulation using the measured input parameters. However, it was found that the DEM simulation prediction error of damage level was high when the input parameters characterized by the Wisconsin breakage tester were used. The parameters were then recalibrated using Stein breakage tester. The model was able to give a good prediction on the damage fraction at different sample size and time levels when the recalibrated parameter values were used.</p>

Digitala ytmodeller (Digital Surface Model – DSM) används ofta i geodetiskt sammanhang. DSM har länge skapats bland annat med hjälp av fotogrammetri där flygbilder har tagits med traditionella flygningar. Intresset tilltar nu för att framställa DSM med hjälp av obemannade flygfarkoster, så kallade UAS (Unmanned Aircraft System). Den största fördelen med UAS är att det går snabbt och enkelt att få den lilla flygfarkosten upp i luften för att ta flygbilder och framställa DSM kostnadseffektivt.Syftet med detta examensarbete var att undersöka vilken höjdosäkerhet som kan uppnås i DSM som framställts genom fotogrammetri med UAS. För att åstadkomma detta har två flygningar gjorts den 25 april 2013 med en Gatewing X100 över ett område i Grillby där cirka 350 flygbilder togs sammanlagt. Efter flygningarna mättes med en totalstation 16 kontrollprofiler in på olika terrängtyper över flygområdet enligt rekommendationer i SIS-TS 21145:2007 ”Statistisk provning av digital terrängmodell”.Från de två flygningarna som gjordes i Grillby framställdes två olika DSM i programvaran AgiSoft Photoscan. DSM importerades därefter till SBG Geo där höjdskillnaderna mellan kontrollprofilerna och DSM beräknades. Medelavvikelsen i höjd varierade mellan -0,112 m och 0,050 m för de olika provytorna. De provytor som systematiskt avvek från DSM var asfaltprofilerna, dessa låg konstant (ca 0,1 m) under DSM. Anledningen tros ligga i bildmatchningen i programvaran AgiSoft Photoscan.De DSM som framställdes i detta examensarbete uppfyllde kraven för klass 4 enligt SIS-TS 21144:2007 vilket innebär att max medelavvikelse i höjd får vara 0,15 m. Det innebär, enligt samma SIS-TS, att framställda DSM är lämpade som projekteringsunderlag för arbetsplan väg och systemhandling järnväg (i jämn terräng). / Digital Surface Models (DSM) is common used for geodetic measurement today. Digital surface models have been created for a long time using photogrammetry where aerial photographs have been taken with traditional flights. The interest to produce DSM using unmanned air vehicles (UAS) has increased lately. The main advantage of a UAS system is that it is quick and easy to get the little aircraft up in the air to take aerial photographs and produce DSM cost-effective.The aim of this thesis was to investigate the height of uncertainty that can be achieved in DSM created by photogrammetry using UAS. To achieve this two flights have been made the 25th of April 2013 with a Gatewing X100. The flights were made over an area in Grillby where approximately 350 aerial photographs in total were taken. After the flights 16 control profiles were measured with a total station on different terrain types over the flight area as recommended by the document SIS-TS 21145:2007 “Statistical testing of Digital Terrain Models”.From the two flights that were made in Grillby, two different DSM was produced in the software AgiSoft Photoscan. The DSM was imported to SBG Geo and height differences between the control profiles and the DSM were calculated. This resulted in height differences which ranged between -0.112 m and 0,050 m in the various sample surfaces. The sample surface that deviated most from the DSM was the asphalt profiles that deviated about -0.1 m. It was considered to be a systematic error, but the source of the systematic error has not been located among the measurements. The error is believed to instead be in the image matching done by AgiSoft Photoscan. The DSM created in this thesis is classified as class 4 in a table from SIS-TS 21144:2007 which means that the max mean difference in height inside the DSM is ±0,15 m. This shows us that the DSM created with photogrammetry using UAS is suited for both as material for planning in railway and road constructions and for visualization of the ground.

The resolution of spatial data has increased over the past decade making them more accurate in depicting landform features. From using a 60m resolution Landsat imagery to resolution close to a meter provided by data from Unmanned Aerial Systems, the number of pixels per area has increased drastically. Topographic features derived from high resolution remote sensing is relevant to measuring agricultural yield. However, conventional algorithms in Geographic Information Systems (GIS) used for processing digital elevation models (DEM) have severe limitations. Typically, 3-by-3 window sizes are used for evaluating the slope, aspect and curvature. Since this window size is very small compared to the resolution of the DEM, they are mostly resampled to a lower resolution to match the size of typical topographic features and decrease processing overheads. This results in low accuracy and limits the predictive ability of any model using such DEM data. In this dissertation, the landform attributes were derived over multiple scales using the concept of sliding window-based aggregation. Using aggregates from previous iteration increases the efficiency from linear to logarithmic thereby addressing scalability issues. The usefulness of DEM-derived topographic features within Random Forest models that predict agricultural yield was examined. The model utilized these derived topographic features and achieved the highest accuracy of 95.31% in predicting Normalized Difference Vegetation Index (NDVI) compared to a 51.89% for window size 3-by-3 in the conventional method. The efficacy of partial dependence plots (PDP) in terms of interpretability was also assessed. This aggregation methodology could serve as a suitable replacement for conventional landform evaluation techniques which mostly rely on reducing the DEM data to a lower resolution prior to data processing. / National Science Foundation (Award OIA-1355466)

Syftet med denna studie är att undersöka två elevgruppers (gymnasieelever åk 1 och 3) användning av pronomina de, dem och dom i skriftlig produktion för att se om användningen har förändrats och om grammatikundervisning har någon påverkan på den. De datainsamlingsmetoder som använts är dokumentation av 36 redan producerade elevtexter samt en semistrukturerad intervju med elevgruppernas svensklärare. Resultatet visar att elevgruppen i årskurs 3 är generellt säkrare i hanteringen av pronomina de och dem, i synnerhet vid funktionen som personligt pronomen i objektsform samt bestämd artikel. Det kan bero på att de fått en gedigen undervisning om pronomina de och dem vid funktionen som subjekts- och objektsform samt genom den respons läraren ger eleverna i deras skivproduktion. Resultatet tyder på att grammatikundervisning har en verkan på denna förändring som skett mellan grupperna och att lärarens roll är avgörande för elevernas hantering och kunskaper kring pronomina de, dem och dom.

Att många inte kan skilja på när de och dem ska användas är en utbredd uppfattning. Trots detta har bruket av dom, enligt en aktuell studie av Lind Palicki och Karlsson (2019), minskat under 2000-talet. Samtidigt kan man notera att en ny form – de för det (de(t)) – har börjat synas allt mer. Syftet med denna studie är därför att undersöka hur bruket av de/dem/dom/det ser ut i sociala medier. Detta realiseras genom en kvantitativ korpusundersökning baserad på material från bloggar, forumen Flashback och FamiljeLiv samt Twitter, som sedan jämförs med Lind Palicki och Karlssons studie av elevtexter (2019). Resultatet visar att skriftspråksnormerna åtföljs till stor del, samtidigt som formvariationen är större i sociala medier. Formen de(t) verkar vara på uppgång och vid osäkerhet använder många dom trots att de tidigare i underlaget brukat de/dem skriftspråksnormenligt. Det talspråkliga sammanhanget främjar formvariation och att göra sig förstådd verkar enligt min analys anses viktigare än att enhetligt följa skriftspråksnormerna, framförallt när skribenten är osäker på vilken form som är skriftspråksnormenlig.

Glaciers in the North Patagonian Ice Fields are temperate glaciers and can be studied to understand the dynamics of climate change. However, the ice field has been neglected in mass balance studies. In this study, multi decadal study of glacial mass balance, glacier retreat and glacial lake expansion in the North Patagonia were studied. Landsat (TM, ETM+ and 8) and ASTER images were used. San Quintin glacier experienced the highest retreat. Demarcation of glacier lakes boundaries indicated an increase in glacial lake area from 13.49 km2 to 65.06 km2 between 1979 and 2013, with an addition of 4 new glacial lakes. Nef glacier recorded the highest mass gain of 9.91 plus or minus 1.96 m.w.e.a.-1 and HPN-4 glacier recorded the highest mass loss of -8.9 plus or minus 1.96 m.w.e.a.-1. However, there is a high uncertainty in the elevation values in the DEM due to the rugged nature of the terrain and presence of the heavy snow cover.

Glaciers are the essential source of fresh water not only to human sustenance, but it is also vital for all lifeforms on earth. Glaciers are also key components in understanding rapid changes in climate. This makes understanding of glacier mass, extent, and overall state essential. In this dissertation, the objective was to analyze the state of snow and ice masses in the mid (California) and low latitude (Chile/Argentina) western American regions using geospatial technology. This study also analyzed the effects of anomalies in snow mass on the regional agricultural practices in California’s Central Valley. In the Southern Andes, the digital elevation models from Shuttle Radar Topographic Mission (SRTM) (the year 2000) were compared with the elevation footprints from the Geoscience Laser Altimeter System (GLAS) campaign for the years 2004 through 2008. Generally, in all sub-regions, the elevation values were lower than the elevation for the year 2000, which demarcates continuous recession of ice mass in the Andean region. Also, this study quantified snow cover extent and mass balance variation in the Sierra Nevada and Mt. Shasta regions in California. To unearth anomalies in snow mass, study used digital elevation models generated from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) between the year 2000 and 2015. A remarkable reduction in snow cover extent of about 80% was observed in the studied watersheds of California. Lastly, the impacts of snow mass anomalies on the total water storage (TWS) and agriculture land cover in the California’s Central Valley were quantified and geo-visualized. The study noticed the change in the land cover area of about 20% (6993 sq.km) due to the alteration of Agriculture land to impervious land covers. Most of the change in the agriculture land cover of about 4402 sq.km occurred in the San Joaquin and Tulare Basins of southern Central Valley region. This dissertation concludes that the increased temperature in the Andes and California has adversely impacted Cryosphere components in the region in the past decade. Besides, it provides valuable insights into the changing state of cryosphere components and highlights impacts of anomalies in TWS on a billion-dollar agricultural industry.

Historical topographic maps are valuable resources for studying past landscapes, but two-dimensional cartographic features are unsuitable for geospatial analysis. They must be extracted and converted into digital formats. This has been accomplished by researchers using sophisticated image processing and pattern recognition techniques, and more recently, artificial intelligence. While these methods are sometimes successful, they require a high level of technical expertise, limiting their accessibility. This research presents a straightforward method practitioners can use to create digital representations of historical topographic data within commercially available Geographic Information Systems (GIS) software. This study uses convolutional neural networks to extract elevation contour lines from a 1940 United States Geological Survey (USGS) topographic map in Sevier County, TN, ultimately producing a Digital Elevation Model (DEM). The topographically derived DEM (TOPO-DEM) is compared to a modern LiDAR-derived DEM to analyze its quality and utility. GIS-capable historians, archaeologists, geographers, and others can use this method in their research and land management practices.