This study investigates on the planimetric (x, y) positional accuracy of the National Shoreline (NSL) data, produced in collaboration between the Swedish mapping agency Lantmäteriet and the Swedish Maritime Administration (SMA). Due to the compound nature of shorelines, such data is afflicted by substantial positional uncertainties. In contrast, the positional accuracy requirements of NSL data are high. An apparent problem is that Lantmäteriet do not measure the positional accuracy of NSL in accordance to the NSL data product specification. In addition, currently, there is little understanding of the latent positional changes of shorelines affected by the component of time, in direct influence of the accuracy of NSL. Therefore, in accordance to the two specific aims of this study, first, an accuracy assessment technique is applied so that to measure the positional accuracy of NSL. Second, positional time changes of NSL are analysed. This study provides with an overview of potential problems and future prospects of NSL, which can be used by Lantmäteriet to improve the quality assurance of the data. Two line-based NSL data sets within the NSL classified regions of Sweden are selected. Positional uncertainties of the selected NSL areas are investigated using two distinctive methodologies. First, an accuracy assessment method is applied and accuracy metrics by the root-means-square error (RMSE) are derived. The accuracy metrics are checked toward specification and standard accuracy tolerances. Results of the assessment by the calculated RMSE metrics in comparison to tolerances indicate on an approved accuracy of tested data. Second, positional changes of NSL data are measured using a proposed space-time analysis technique. The results of the analysis reveal significant discrepancies between the two areas investigated, indicating that one of the test areas are influenced by much greater positional changes over time. The accuracy assessment method used in this study has a number of apparent constraints. One manifested restriction is the potential presence of bias in the derived accuracy metrics. In mind of current restrictions, the method to be preferred in assessment of the positional accuracy of NSL is a visual inspection towards aerial photographs. In regard of the result of the space-time analysis, one important conclusion can be made. Time-dependent positional discrepancies between the two areas investigated, indicate that Swedish coastlines are affected by divergent degrees of positional changes over time. Therefore, Lantmäteriet should consider updating NSL data at different time phases dependent on the prevailing regional changes so that to assure the currently specified positional accuracy of the entire data structure of NSL.

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Bakgrund: Skelettscintigrafi är en nuklearmedicinsk undersökning. Undersökningen är den mest använda nukleardiagnostiska metoden och den genomförs ofta som en helkroppsundersökning. För att undersökningen ska kunna erhålla sin diagnostiska kvalitet, samt följa strålsäkerhetsmyndighetens rekommendationer behövs det mer kännedom till hur optimeringen ska följa as low as reasonably achievable (ALARA). Studiens syfte var att optimera patientstråldos samt att undersöka hur injicerad aktivitet kan anpassas efter patientens specifika parametrar. Metod: Studiegruppen bestod av 85 patienter som genomgick skelettscintigrafier vid Central sjukhuset i Karlstad, från perioden februari-april 2020. Resultat: Visade att både ålder och vikt är patientspecifika variabler som borde tas till betraktning vid bestämning av injicerad strålningsdos. Konklusionen: För att optimera undersökningen för varje patient bör injicerad aktivitet anpassas efter både kroppsvikt och ålder. Fler studier där andra parametrar undersöks måste genomföras. / Background: Bone scintigraphy is a nuclear medicine procedure. It is the most used nuclear diagnostic method and provides the opportunity to perform a full-body examination. For the method to retain its diagnostic quality, and to follow the recommendations of the Radiation Safety Authority, more knowledge is required on how the optimization should follow as low as reasonably achievable (ALARA). The purpose of the study was to optimize patient radiation dose and to investigate how the injected activity can be adapted to patient-specific parameters. Method: The study group consisted of 85 patients who underwent bone scintigraphy at the Central Hospital in Karlstad, from the period February-April 2020. Result: Showed that age and weight are patient-specific variables that should be considered when determining injected radiation dose. Conclusion: To optimize the examination for each patient, injected activity should be adjusted according to the patient’s body weight and age. More studies in where other parameters are investigated must be carried out.

Este trabalho tem por objetivo comparar os seguintes métodos de compressão de imagens de impressão digital: transformada discreta do cosseno (DCT), transformada de wavelets de Haar, transformada de wavelets de Daubechies e transformada de wavelets de quantização escalar (WSQ). O propósito da comparação é identificar o método que resulta numa menor perda de dados, para a maior taxa de compressão possível. São utilizadas as seguintes métricas para avaliação da qualidade da imagem para os métodos: erro quadrático médio (ERMS), a relação sinal e ruído (SNR) e a relação sinal ruído de pico (PSNR). Para as métricas utilizadas a DCT apresentou os melhores resultados, seguida pela WSQ. No entanto, o melhor tempo de compressão e a melhor qualidade das imagens recuperadas avaliadas pelo software GrFinger 4.2, foram obtidos com a técnica WSQ. / This research aims to compare the following fingerprint image compression methods: the discrete cosseno transform (DCT), Haar wavelet transform, Daubechies wavelets transform and wavelet scalar quantization (WSQ). The main interest is to find out the technique with the smallest distortion and higher compression ratio. Image quality is measured using peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR) and root mean square (ERMS). Image quality using these metrics showed best results for the DCT followed by WSQ, although the WSQ had the best compression time and presented the best quality when evaluated by the GrFinger 4.2 software.

Este trabalho tem por objetivo comparar os seguintes métodos de compressão de imagens de impressão digital: transformada discreta do cosseno (DCT), transformada de wavelets de Haar, transformada de wavelets de Daubechies e transformada de wavelets de quantização escalar (WSQ). O propósito da comparação é identificar o método que resulta numa menor perda de dados, para a maior taxa de compressão possível. São utilizadas as seguintes métricas para avaliação da qualidade da imagem para os métodos: erro quadrático médio (ERMS), a relação sinal e ruído (SNR) e a relação sinal ruído de pico (PSNR). Para as métricas utilizadas a DCT apresentou os melhores resultados, seguida pela WSQ. No entanto, o melhor tempo de compressão e a melhor qualidade das imagens recuperadas avaliadas pelo software GrFinger 4.2, foram obtidos com a técnica WSQ. / This research aims to compare the following fingerprint image compression methods: the discrete cosseno transform (DCT), Haar wavelet transform, Daubechies wavelets transform and wavelet scalar quantization (WSQ). The main interest is to find out the technique with the smallest distortion and higher compression ratio. Image quality is measured using peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR) and root mean square (ERMS). Image quality using these metrics showed best results for the DCT followed by WSQ, although the WSQ had the best compression time and presented the best quality when evaluated by the GrFinger 4.2 software.

It is important for a retail company to forecast its sale in correct and accurate way to be ableto plan and evaluate sales and commercial strategies. Various forecasting techniques areavailable for this purpose. Two popular modelling techniques are Predictive Modelling andEconometric Modelling. The models created by these techniques are used to minimize thedifference between the real and the predicted values. There are several different errormetrics that can be used to measure and describe the difference. Each metric focuses ondifferent properties in the forecasts and it is hence important which metrics that is used whena model is created. Most traditional techniques use the sum of squared error which havegood mathematical properties but is not always optimal for forecasting purposes. This thesisfocuses on optimization of three widely used error metrics MAPE, WMAPE and RMSE.Especially the metrics protection against overfitting, which occurs when a predictive modelcatches noise and irregularities in the data, that is not part of the sought relationship, isevaluated in this thesis.Genetic Programming, a general optimization technique based on Darwin’s theories ofevolution. In this study genetic programming is used to optimize predictive models based oneach metrics. The sales data of five products of ICA (a Swedish retail company) has beenused to observe the effects of the optimized error metrics when creating predictive models.This study shows that all three metrics are quite poorly protected against overfitting even ifWMAPE and MAPE are slightly better protected than MAPE. However WMAPE is the mostpromising metric to use for optimization of predictive models. When evaluated against allthree metrics, models optimized based on WMAPE have the best overall result. The results oftraining and test data shows that the results hold in spite of overfitted models. / Program: Magisterutbildning i informatik

Unmanned aerial vehicle (UAV) technology was used to determine tidal extent in Kimages Creek, a restored tidal wetland located in Charles City County, Virginia. A Sensefly eBee Real-Time Kinematic UAV equipped with the Sensor Optimized for Drone Applications (SODA) camera (20-megapixel RGB sensor) was flown during a single high and low tide event in Summer 2017. Collectively, over 1,300 images were captured and processed using Pix4D. Horizontal and vertical accuracy of models created using ground control points (GCP) ranged from 0.176 m to 0.363 m. The high tide elevation model was subtracted from the low tide using the ArcMap 10.5.1 raster calculator. The positive difference was displayed to show the portion of high tide that was above the low tide. These results show that UAVs offer numerous spatial and temporal advantages, but further research is needed to determine the best method of GCP placement in areas of similar forest structure.

This thesis presents how to estimate the length of a power cable using the MaximumLikelihood Estimate (MLE) technique by using Matlab. The model of the power cableis evaluated in the time domain with additive white Gaussian noise. The statistics havebeen used to evaluate the performance of the estimator, by repeating the experiment fora large number of samples where the random additive noise is generated for each sample.The estimated sample variance is compared to the theoretical Cramer Raw lower Bound(CRLB) for unbiased estimators. At the end of thesis, numerical results are presentedthat show when the resulting sample variance is close to the CRLB, and hence that theperformance of the estimator will be more accurate.

Vaizdo kontūrų nustatymo metodų tyrimui buvo pasirinktas 100 įvairaus turinio paveikslų su įvairiu elementų dydžiu ir skaičiumi. Tyrimui buvo pasirinkti 8 populiariausi vaizdo kontūrų nustatymo metodai: Canny, Sobel, Prewitt, Roberts, Zerocross, Laplacian, LoG, Marr-Hildreth. Atliekant tyrimus visiems paveikslams, naudojant visus 8 metodus, buvo subjektyviai parinkta optimaliausia slenkstinė reikšmė. Gavus visų 100 įvairių paveikslų geriausias slenkstines reikšmes su visais 8 metodais, buvo nustatytos slenkstinių reikšmių kitimo ribos kiekvienam kontūro išskyrimo metodui. Kiekvienam paveikslui buvo pritaikyta vidutiniškai 10 slenkstinių reikšmių ir kiekvienam paveikslui buvo suskaičiuotas vidutinis kvadratinis nuokrypis (RMSE, Root Mean Square Error) su geriausiu pasirinktu kontūru. / One hundred various pictures with different size and number of elements were chosen for the method research of image outline evaluation. All these pictures were converted into grayscale pictures. Most of edge detection methods (filters) required to be blurred to reduce noise. Eight the most popular methods were chosen to evaluate the image outline: Canny, Sobel, Prewitt, Roberts, Zerocross, Laplacian, LoG, Marr-Hildreth. A Root Mean Square Error (RMSE) was computed for each edge picture with the best-chosen outline.

The multimedia revolution has made a strong impact on our society. The explosive growth of the Internet, the access to this digital information generates new opportunities and challenges. The ease of editing and duplication in digital domain created the concern of copyright protection for content providers. Various schemes to embed secondary data in the digital media are investigated to preserve copyright and to discourage unauthorized duplication: where digital watermarking is a viable solution. This thesis proposes a novel invisible watermarking scheme: a discrete cosine transform (DCT) domain based watermark embedding and blind extraction algorithm for copyright protection of the color images. Testing of the proposed watermarking scheme's robustness and security via different benchmarks proves its resilience to digital attacks. The detectors response, PSNR and RMSE results show that our algorithm has a better security performance than most of the existing algorithms.