This thesis work regards free viewpoint TV. The main idea is that users can switch between multiple streams in order to find views of their own choice. The purpose is to provide fast switching between the streams, so that users experience less delay while view switching. In this thesis work we will discuss different video stream switching methods in detail. Then we will discuss issues related to those stream switching methods, including transmission and switching. We shall also discuss different scenarios for fast stream switching in order to make services more interactive by minimizing delays. Stream switching time varies from live to recorded events. Quality of service (QoS) is another factor to consider which can be improved by assigning priorities to the packets. We will discuss simultaneous stream transmission methods which are based on predictions and reduced quality streams for providing fast switching. We will present prediction algorithm for viewpoint prediction, propose system model for fast viewpoint switching and make evaluation of simultaneous stream transmission methods for free viewpoint TV. Finally, we draw our conclusions and propose future work. / Degree project

The demand for measuring the quality aspects and need for higher maintainability and understandability of the models are increasing within the field of software engineering and management. Among these, complex models are of special interest for designers as they are more correlated to the eventual reliability of the system and therefore are considered very important. This study presents a method for measuring the complexity of existing software models in Ericsson seeking to raise the maintainability and understandability of the software engineering project in progress. A literature survey was performed in order to find a list of all potentially useful metrics. Narrowing down the long list of metrics was carried out by interviews with designers at Ericsson. Utilizing statistical data analysis based on interviews results was the next step. Beside, workshops were used for evaluating the reliability of preliminary data analysis and an empirical formula was generated for models’ complexity prediction. Metrics such as “non-self-transitions”, “transitions per states”, and “state depth” are the most important for calculating the models’ complexity score (rank) and for these metrics threshold values were set. Challenges and experiences gained in this study demonstrated the importance of incorporating user generated feedback in the empirical complexity modeling studies

River discharge estimation is the basic hydrological information for most hydrological applications in various socioeconomic planning. Increasing the accuracy of the traditional rating curve in relation to river discharge estimation would be very valuable to hydrological applications. Suggestions have been made that the traditional power function rating curve should be divided into several segments because this is often motivated by the physical characteristics of the river. Each curve is commonly constructed by regression and each requires 3 estimated parameters. However stage-discharge data is often scarce, and this scarcity could lead to overparametrization and deterioration of accuracy. By constructing many unsegmented and segmented rating curves accounting for measurement uncertainty, the models can be validated, it can be determined if segmented rating curves suffers from overparametrization. The results showed that two-segmented rating curves did not yield better fits to data, and nor did it generate larger errors than unsegmented rating curves in extrapolation. Segmentation only reduced errors in low flow interpolation, when there is a clear segmentation.  It could also be concluded that unsegmented rating curves were slightly more robust when extrapolating. The biggest impact on rating curve errors was shown not to be determined by segmentation, but rather much more dependent on the amount of discharge measurement uncertainty or choice of regression method. With a mean discharge uncertainty of ±5 %, the errors from in high flow was 60 % in interpolation and 35 % in extrapolation. For low flows, the interpolation errors were around 95 % end extrapolation error estimation was 250 %. Conclusions could also be made that the relative errors from rating curves increased with lower discharges. Other important regression factors, such as heteroscedasticity, sometimes showed to have substantial impact on rating curve regressions, generally reduced from 59 % occurrence in unsegmented rating curves to 14-15 % in segmented rating curves. / Uppskattning av vattenflöden i vattendrag är den grundläggande informationen för de flesta hydrologiska applikationer vid olika typer av socioekonomisk planering. Att förbättra noggrannheten i avbördningskurvor då vattenflödet uppskattas vid en mätstation skulle vara värdefullt för de flesta tillämpningar där vattenflöden används. Tidigare studier har föreslagit att avbördningskurvor borde delas upp i flera segment, eftersom vattendrag inte sällan har olika segment med olika fysikaliska karaktärer. Varje segment kräver dock att 2-3 regressionsparametrar bestäms, men flödesmätningar vid olika vattennivåer är ofta få, och knappheten kan göra att en utökad modell blir överparametriserad och än mer osäker.   Genom att konstruera många avbördningskurvor, segmenterade och osegmenterade, kan dessa valideras mot valideringsdata och var det möjligt se om segmenterade avbördningskurvor blev överparametriserade. Studien visade att segmenterade avbördningskurvor vid kalibrering, interpolation och extrapolation generellt inte gav bättre prediktion än osegmenterade avbördningskurvor. Vid låga flöden och tydligt motiverade segmenteringar gav segmenterade avbördningskurvor en bättre interpolation, men dock inte vid extrapolation, vilket är en indikation att segmenterade avbördningskurvor var något överparametriserade. Den största inverkan på att minska felen i avbördningskurvor var var att minska mätosäkerheten i flödesmätningarna. Med en genomsnittlig mätosäkerhet i flödesmätningarna på ±5 % kunde osäkerheten kvantifieras till kring 60 % för interpolerade osegmenterade avbördningskurvor vid höga flöden och kring 95 % vid låga flöden. Variansen var dock stor. Osäkerheten från modellvalideringen av extrapolation för osegmenterade avbördningskurvor vid höga flöden kvantifierades till kring 35 % vid höga flöden och kring 250 % vid låga flöden. Resultaten visade att de relativa felen från avbördningskurvor blev större för ju lägre flödet blir.   Heteroskedastitet, som kan generera osäkerheter i avbördningskurvor, visade sig vara vanligare (59 %) i osegmenterade avbördningskurvor jämfört med segmenterade (14-15 %). Även antalet flödesmätningar hade en betydelse för felen i avbördningskurvor. / Avbördningskurva, icke-linjär regression, flöde, flödesmätning, osäkerhet, validering, hydrologi, överparametrisering, vattenstånd

The aim of this thesis is to find out the relationship between the development of the economic situation in Czech regions and potential accessibility of road networks evaluated with mathematical analysis. The intent of the model is to define a relationship between the transport accessibility and economic state in municipalities in 2001, 2011 and to predict for 2021. This evaluation has been reached with the model of potential accessibility. Several methodological problems had to be solved. Model calibration was provided with respect to the reality and changes in economic state in particular geographical regions. After the first step, which was focused on finding out the optimal model for potential accessibility of road networks, the linear regression with prediction of gross added economic value in analysed regions was used. Results showed only minor growth of gross added economic value in core geographical regions in the Czech Republic. In contrary, in peripheral regions dynamic growth of gross economic added value can be expected. This thesis follows the present interest in developing a transportation geography mathematical model, which can help us to understand the road transportation accessibility and its impact on economical development. Key words Potential accessibility, linear regression,...

The aim of this diploma thesis is based on the empirical analysis to identify the relationship between the exchange rate and the interest rates in selected countries and verify the validity of the uncovered interest rate parity. In the first part, the author deals with basic theoretical and exchange rate determinants from a fundamental analysis point of view, which attempts to explain the causality between these two variables. The actual analysis was performed at three levels on monthly time series from 2010 to 2016. Graphical analysis was selected as the first stage of the analysis, also including verification of the validity of the Fisher International Effect. Later, regression and vector autoregressive analysis followed. However, the conclusions of the individual empirical parts show that the exchange rate is determined by many factors, not only by the interest rate differential, as assumed the theory of uncovered interest rate parity. These results are also related to the low quality of the estimated models. Uncovered interest rate parity has been confirmed in very few cases, but none of the monitored currency pairs has been validated at all three levels of empirical analysis at the same time. The work offers valuable insight into the trend appreciation or depreciation of the exchange rates at the positive interest rate differential in the selected period.

Dans un contexte où la consommation de viande bovine est en constante diminution, en partie à cause de sa composition lipidique, il apparaît important pour l'ensemble de la filière de pouvoir communiquer sur l’intérêt nutritionnel de cette viande et plus particulièrement sur sa composition en acides gras (AG). Pour que cette communication soit « efficiente » à tous les niveaux de la filière, il faut disposer de moyens analytiques fiables mais aussi faciles de mise en œuvre et de surcroît peu coûteux. La méthode analytique que nous avons choisi de tester est la spectrométrie proche infrarouge (SPIR) qui présente l’avantage d’être peu coûteuse, peu invasive et qui pourrait ainsi être utilisée à grande échelle et en routine en abattoir. Nous avons montré que la SPIR est performante pour déterminer les teneurs en AG saturés (AGS) et monoinsaturés (AGMI) (R2>0,9). Dans les meilleures conditions pour la prédiction des AGPI (échantillons comportant des teneurs élevées en AGPI et/ou une grande variabilité), les performances de prédiction restent encore insuffisantes (R2 <0,75). Pour pallier cette faiblesse de la SPIR, des équations de prédiction indirectes des AGPI ont été mises en place à partir des teneurs en AGS et AGMI, teneurs correctement déterminées par SPIR, et les informations disponibles en abattoir. Ces équations élaborées par régression linéaire multiple ont permis de prédire correctement les AGPI totaux et les AGPI n-6 (R2 >0,8). Elles restent perfectibles pour la détermination des AGPI n-3 totaux (R2=0,64) mais surtout pour le 18:3 n-3, le 20:5 n-3 et le 22:6 n-3 (R2 <0,55). L’objectif final de ce travail étant d'utiliser les équations en complément des mesures réalisées par SPIR à des fins industrielles afin de déterminer rapidement la composition en AG de la viande bovine, des études complémentaires seront nécessaires pour tester l'ensemble de notre démarche associant SPIR et équations de prédiction. / In a context where the consumption of beef is declining in part because of its lipid composition, an opportunity to revive the beef industry is to communicate with consumers on nutritional quality of beef, especially its fatty acids (FA) composition. To ensure this communication is “efficient” at all levels of the industry, we must have reliable analytical resources but also easy to implement and also inexpensive. The analytical method proposed for determining the beef FA composition is the near-infrared spectroscopy (NIRS) which is inexpensive, minimally invasive and could thus be widely used in routine in slaughterhouse. We showed that NIRS was effective to determine the concentrations of saturated (SFA) and monounsaturated (MUFA) FA (R2> 0.9). Under the best conditions for the prediction of PUFA (samples containing high levels of PUFA and / or with a high variability), PUFA predictions were still not enough (R2 <0.75). So, to overcome this weakness of NIRS, indirect prediction equations of PUFA were performed from the SFA and MUFA contents correctly determined by NIRS and information available in slaughterhouses. These equations, developed by multiple linear regression, were used to correctly predict total and n-6 PUFA (R2> 0.8). These equations are still to be improved for the determination of the total n-3 PUFA (R2 = 0.64) and of the 18:3 n-3, the 20:5 n-3 and the 22:6 n-3 (R2 <0.55). Given that the ultimate aim of this research is to use the equations as a complementary tool in tandem with NIRS measurements to serve industry as a way to rapidly determine the FA content of beef, further studies will be needed to trial and test our novel coupled NIRS–prediction equations approach.

Higher order modes (HOM) are electromagnetic resonant fields. They can be excited by an electron beam entering an accelerating cavity, and constitute a component of the wakefield. This wakefield has the potential to dilute the beam quality and, in the worst case, result in a beam-break-up instability. It is therefore important to ensure that these fields are well suppressed by extracting energy through special couplers. In addition, the effect of the transverse wakefield can be reduced by aligning the beam on the cavity axis. This is due to their strength depending on the transverse offset of the excitation beam. For suitably small offsets the dominant components of the transverse wakefield are dipole modes, with a linear dependence on the transverse offset of the excitation bunch. This fact enables the transverse beam position inside the cavity to be determined by measuring the dipole modes extracted from the couplers, similar to a cavity beam position monitor (BPM), but requires no additional vacuum instrumentation.At the FLASH facility in DESY, 1.3 GHz (known as TESLA) and 3.9 GHz (third harmonic) cavities are installed. Wakefields in 3.9 GHz cavities are significantly larger than in the 1.3 GHz cavities. It is therefore important to mitigate the adverse effects of HOMs to the beam by aligning the beam on the electric axis of the cavities. This alignment requires an accurate beam position diagnostics inside the 3.9 GHz cavities. It is this aspect that is focused on in this thesis. Although the principle of beam diagnostics with HOM has been demonstrated on 1.3 GHz cavities, the realization in 3.9 GHz cavities is considerably more challenging. This is due to the dense HOM spectrum and the relatively strong coupling of most HOMs amongst the four cavities in the third harmonic cryo-module. A comprehensive series of simulations and HOM spectra measurements have been performed in order to study the modal band structure of the 3.9 GHz cavities. The dependencies of various dipole modes on the offset of the excitation beam were subsequently studied using a spectrum analyzer. Various data analysis methods were used: modal identification, direct linear regression, singular value decomposition and k-means clustering. These studies lead to three modal options promising for beam position diagnostics, upon which a set of test electronics has been built. The experiments with these electronics suggest a resolution of 50 micron accuracy in predicting local beam position in the cavity and a global resolution of 20 micron over the complete module. This constitutes the first demonstration of HOM-based beam diagnostics in a third harmonic 3.9 GHz superconducting cavity module. These studies have finalized the design of the online HOM-BPM for 3.9 GHz cavities at FLASH.

The aim of this work was to present the issue of neural network, which is still, despite the fact it exist and has been applied for several years, remains quite unknown for a considerably big part of public and academical environment. The aim of the practical part was to verify via practical application if neural network are truly a better instrument of statistical analysis, than the commonly used ones, especially when the goal is to analyze and describe complex processes and relationships between them. Further aim of the work was to investigate and describe the relationships between the development of trading volumes of Apple shares and the shares of competitive companies regarding the market of smart phones such as Google, HTC, Nokia, Samsung using neural network models. The attainment of these goals was realized through a rather extensive description of neural networks theory as well as the presentation of valuable theoretical tools for avoiding the frequent barriers occurring during the practical implementation. This practical application was realized via software called R, which has widely spread lately due to its availability and a vast range of flexibility, which is provided to users. The value of this work is familiarization and the creation of an integrated knowledge within readers about the issue of neural networks and the deliverance of a proof, that neural networks are indeed a better tool compared to the commonly used ones (ARMA models, linear regression). The author of the work gained a lot of useful knowledge about neural networks, learned how to use them in practice especially in the environment of R software, by which he shifted his proficiency with the current software to a whole new level.

Text in English / Scrum is the most adopted and under-researched Agile methodology. The research conducted on Scrum adoption is mainly qualitative. Therefore, there was a need for a quantitative study to investigate Scrum adoption challenges. The general objective of this study was to investigate the factors that have a significant relationship with Scrum adoption as perceived by Scrum practitioners working within South African organisations. To achieve this objective a narrative review to synthesise the existing challenges was conducted, followed by the use of these challenges in the development of a conceptual framework. After that, a survey questionnaire was used to test and evaluate the developed framework. The research findings indicate that relative advantage, complexity, and sprint management are factors that have a significant linear relationship with Scrum adoption. The findings are generalisable to the population, and the author recommends that organisations review the findings during their adoption phase of Scrum. / Council for Scientific and Industrial Research (CSIR) / University of South Africa (UNISA) / School of Computing / M.Sc. (Computing)

<p>In the field of the construction industry, the research work has been widely focused on identifying key performance indicators and critical success factors without assessing the impact of conflict environment factors. This study focusses on the impact of post-conflict environment factors on local construction organization performance. This research presents a performance prediction model comprising the effect of post-conflict environment factors on construction organization performance. The proposed framework of this study has four stages: identify key performance indicators (KPIs), identify post-conflict environment impacting factors, determine critical success factors (CSFs), and formulate success strategy to improve performance. Analytical hierarchy process (AHP) and multiple linear regression (MLR) techniques are applied to analyze the data.</p> <p>The study finding indicates that there is a significant relationship between the post-conflict condition impacting factors and local construction organization performance, which is insufficiently studied in previous research work. Thus, the developed framework will benefit academic scholars and industry practitioners to analyze and evaluate challenges and opportunities caused by different external environment conditions in the post-conflict construction industry. </p>