Solar images are one of the most important sources of available information on the current state and behaviour of the sun, and the PICARD satellite is one of several ground and space-based observatories dedicated to the collection of that data. The PICARD satellite hosts the Solar Diameter Imager and Surface Mapper (SODISM), a telescope aimed at continuously monitoring the Sun. It has generated a huge cache of images and other data that can be analysed and interpreted to improve the monitoring of features, such as sunspots and the prediction and diagnosis of solar activity. In proportion to the available raw material, the little-published analysis of SODISM data has provided the impetus for this study, specifically a novel method of contributing to the development of a system to enhance, detect and segment sunspots using new hybrid methods. This research aims to yield an improved understanding of SODISM data by providing novel methods to tabulate a sunspot and filling factor (FF) catalogue, which will be useful for future forecasting activities. The developed technologies and the findings achieved in this research will work as a corner stone to enhance the accuracy of sunspot segmentation; create efficient filling factor catalogue systems, and enhance our understanding of SODISM image enhancement. The results achieved can be summarised as follows: i) Novel enhancement method for SODISM images. ii) New efficient methods to segment dark regions and detect sunspots. iii) Novel catalogue for filling factor including the number, size and sunspot location. v) Novel statistical method to summarise FFs catalogue. Image processing and partitioning techniques are used in this work; these methods have been applied to remove noise and detect sunspots and will provide more information such as sunspot numbers, size and filling factor. The performance of the model is compared to the fillers extracted from other satellites, such as SOHO. Also, the results were compared with the NOAA catalogue and achieved a precision of 98%. Performance measurement is also introduced and applied to verify results and evaluate proposal methods. Algorithms, implementation, results and future work have been explained in this thesis.

No description available.

In this modern rather interconnected era, an organization’s top priority is to protect itself from major security breaches occurring frequently within a communicational environment. But, it seems, as if they quite fail in doing so. Every week there are new headlines relating to information being forged, funds being stolen and corrupt usage of credit card and so on. Personal computers are turned into “zombie machines” by hackers to steal confidential and financial information from sources without disclosing hacker’s true identity. These identity thieves rob private data and ruin the very purpose of privacy. The purpose of this project is to identify suspicious user activity by analyzing a log file which then later can help an investigation agency like FBI to track and monitor anonymous user(s) who seek for weaknesses to attack vulnerable parts of a system to have access of it. The project also emphasizes the potential damage that a malicious activity could have on the system. This project uses Hadoop framework to search and store log files for logging activities and then performs a ‘Map Reduce’ programming code to finally compute and analyze the results.

Spectral reflectance of the Earth surface, obtained from the satellite images, should be independent from the external influences and should reflect the surface properties, specifically the proportion of the radiance reflected from the object. It was proved in this paper that the time series of the 63 images from the Landsat 5 satellite were visibly influenced by the external factors even in the case of the images already atmospherically corrected. These external factors were age of the image and WRS-2 position from which the image was obtained. Age of the image was documented with the steady decrease of the spectral reflectance values of the invariant features, especially in the visible part of the electromagnetic spectrum, caused by the sensor degradation. The influence of the WRS-2 position was documented especially in the infrared bands. The western parts of the images are lighter (have higher values of the surface reflectance) than the eastern parts. That may cause the difference between values when monitoring one spot in two overlapping WRS-2 positions. The method originally used for the relative radiometric normalization IR-MAD was here applied to normalize the surface reflectance data, and resulted in the fact that these influences did not show up any more. In order to extend the time...

Made available in DSpace on 2016-12-12T20:22:53Z (GMT). No. of bitstreams: 1 Wilcilene Maria K Schratzenstaller.pdf: 1929821 bytes, checksum: 3ec3776f9e1f9931f0836220596c52a8 (MD5) Previous issue date: 2015-09-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In order to attend demands faster and at lower cost, small and medium enterprises (SME) are joined in virtual organizations breeding environments (VBEs) where they can share resources to work collaboratively. The work in these environments is facilitated by using of serviceoriented architectures (SOA) and enterprise service buses (ESBs). Although SOA and ESBs help the process of systems integration, it still remaining a complex task due to the heterogeneity of existing data. To solve this problem ESBs could be improved with a semantic support to mediate differences between the data provided by SME. But, how to add semantic support to ESBs to facilitate data mapping for SMEs to integrate them into the VBEs? This work proposes the creation of an ontology and a method that adds semantics to the data in order to solve semantic incompatibilities. To validate the proposal, metrics were applied to evaluate the ontology according to its coverage of searched terms, the wealth of knowledge represented and the level detail. Besides that, tests were performed on the developed semantic mapper prototype. / Com intuito de atenderem demandas de forma mais rápida e com menor custo, pequenas e médias empresas (PME) se unem em ambientes de criação de organizações virtuais (ACVs) onde compartilham recursos para atuarem de forma colaborativa. O trabalho nestes ambientes é facilitado pelo uso de arquiteturas orientadas a serviços. Mais especificamente, com o uso de barramentos de serviços empresariais (ESBs). ESBs possibilitam que os sistemas das PME envolvidas sejam integrados e mensagens sejam trocadas. A tarefa de integrar os sistemas é complexa devido à heterogeneidade de dados existente. Para resolver este problema, os ESBs poderiam ser munidos de um suporte semântico que mediasse as divergências existentes entre os dados fornecidos pelas PME. Mas, como adicionar suporte semântico aos ESBs para facilitar a identificação dos dados das PME a fim de integrá-las ao ACV? Este trabalho propõe a criação de uma ontologia e um método que adiciona semântica aos dados no intuito de resolver as incompatibilidades semânticas. Para validar a proposta foram aplicadas métricas que avaliam a cobertura dos termos buscados, a riqueza de representação do conhecimento e o detalhamento de nível da ontologia, bem como foram realizados testes no protótipo de mapeador semântico desenvolvido.

Biomass burning in southern Africa has brought significant challenges to the research society as a fundamental driver of climate and land cover changes. Burned area mapping approaches have been developed that generate large-scale low and moderate resolution products made with different satellite data. This consequently afford the remote sensing community a unique opportunity to support their potential applications in e.g., examining the impact of fire on natural resources, estimating the quantities of burned biomass and gas emissions. Generally, the satellite-derived burned area products produced with dissimilar algorithms provide mapped burned areas at different levels of accuracy, as the environmental and remote sensing factors vary both spatially and temporally. This study focused on the inter-comparison and accuracy evaluation of the 500-meter Moderate Resolution Imaging Spetroradiomter (MODIS) burned area product (MCD45A1) and the Backup MODIS burned area product (hereafter BMBAP) across the main-fire prone South African biomes using reference data independently-derived from multi-temporal 30-meter Landsat 5 Thematic Mapper (TM) imagery distributed over six validation sites. The accuracy of the products was quantified using confusion matrices, linear regression and subpixel burned area measures. The results revealed that the highest burned area mapping accuracies were reported in the fynbos and grassland biomes by the MCD45A1 product, following the BMBAP product across the pine forest and savanna biomes, respectively. Further, the MCD45A1 product presented higher subpixel detection probabilities for the burned area fractions <= 50% than the BMBAP product, which appeared more reliable in detecting burned area fractions > 50% of a MODIS pixel. Finally the results demonstrated that the probability of identifying a burned area within a MODIS pixel is directly related to the proportion of the MODIS pixel burned and thus, highlights the relevance of fractional burned area during classification accuracy assessment of lower resolution remotely-sensed products using data with higher spatial resolution. / Dissertation (MSc)--University of Pretoria, 2011. / Geography, Geoinformatics and Meteorology / unrestricted

With the help of new technology it has become much easier to apply for a job. Reaching out to a larger audience also results in a lot of more applications to consider when hiring for a new position. This has resulted in that many big companies uses statistical learning methods as a tool in the first step of the recruiting process. Smaller companies that do not have access to the same amount of historical and big data sets do not have the same opportunities to digitalise their recruitment process. Using topological data analysis, this thesis explore how clustering methods can be used on smaller data sets in the early stages of the recruitment process. It also studies how the level of abstraction in data representation affects the results. The methods seem to perform well on higher level job announcements but struggles on basic level positions. It also shows that the representation of candidates and jobs has a huge impact on the results. / Ny teknologi har förenklat processen för att söka arbete. Detta har resulterat i att företag får tusentals ansökningar som de måste ta hänsyn till. För att förenkla och påskynda rekryteringsprocessen har många stora företag börjat använda sig av maskininlärningsmetoder. Mindre företag, till exempel start-ups, har inte samma möjligheter för att digitalisera deras rekrytering. De har oftast inte tillgång till stora mängder historisk ansökningsdata. Den här uppsatsen undersöker därför med hjälp av topologisk dataanalys hur klustermetoder kan användas i rekrytering på mindre datauppsättningar. Den analyserar också hur abstraktionsnivån på datan påverkar resultaten. Metoderna visar sig fungera bra för jobbpositioner av högre nivå men har problem med jobb på en lägre nivå. Det visar sig också att valet av representation av kandidater och jobb har en stor inverkan på resultaten.

yes / PICARD is a space-based observatory hosting the Solar Diameter Imager and Surface Mapper (SODISM) telescope, which has continuously observed the Sun from July 2010 and up to March 2014. In order to study the fine structure of the solar surface, it is helpful to apply techniques that enhance the images so as to improve the visibility of solar features such as sunspots or faculae. The objective of this work is to develop an innovative technique to enhance the quality of the SODISM images in the five wavelengths monitored by the telescope at 215.0 nm, 393.37 nm, 535.7 nm, 607.1 nm and 782.2 nm. An enhancement technique using interpolation of the high-frequency sub-bands obtained by Discrete Wavelet Transforms (DWT) and the input image is applied to the SODISM images. The input images are decomposed by the DWT as well as Stationary Wavelet Transform (SWT) into four separate sub-bands in horizontal and vertical directions namely, low-low (LL), low-high (LH), high-low (HL) and high–high (HH) frequencies. The DWT high frequency sub-bands are interpolated by a factor 2. The estimated high frequency sub-bands (edges) are enhanced by introducing an intermediate stage using a stationary Wavelet Transform (SWT), and then all these sub-bands and input image are combined and interpolated with half of the interpolation factor α/2, used to interpolate the high-frequency sub-bands, in order to reach the required size for IDWT processing. Quantitative and visual results show the superiority of the proposed technique over a bicubic image resolution enhancement technique. In addition, filling factors for sunspots are calculated from SODISM images and results are presented in this work.

No description available.

The objective of this work is to design and implement an Object-relational framework for PHP. This framework will be able to map objects to traditional relational database tables. In this work, an appropriate solution of  metadata specification is presented. These metadata describe how an object can be store in a relational database. The framework itself is able to store, load and query any object data in relational database. This object-relational framework has been designed for simple portability among various database systems.