As colonized peoples Native Americans have had a complicated relationship to the United States. They have faced the question of whether they should demand tribal independence or embrace American citizenship. During the early 1970s, when radical ethnic and political movements occupied center stage in the United States, and in 1992, when the 500 year anniversary of Columbus discovery of America was celebrated, the issue of Indian American identification was actualized. The various possible ways in which Native Americans could identify in relation to the United States made their identification often seem contradictory. The same group and even the same individual could  identify as both part of and apart from the United States. Likewise, the same event could trigger different identifications in relation to the United States. How can this be explained? In this thesis I offer an explanation of Indian American identification that combines the perspectives of world view and historical context. Native Americans have related to two different world views, a Western world view which imagines a world made up of states, and a "traditional" Indian world view which imagines a world made up of peoples placed on their lands by the Creator. Different ways of understanding the world impacted how Native Americans understood "America," as USA or Indian ancestral homelands. Different world views provided different images of Native American relationship to the United States. These images could be put forward or be actualized in different contexts. The historical context influenced which images were most commonly chosen. During the 1970s, given the period's generally revolutionary discourse, more separatist images were prominent. In 1992, when a government-to-government relationship between tribal and federal governments was firmly established, Indians chose a more inclusive relationship to the Untied States.

This thesis presents transformation as the key principle of production, as well as reception of a literary text. As far as production is concerned, the thesis takes off from the passing nature of any moment, any element of reality, and it perceives a literary text as a way to save and conserve that element. It is obvious that should the given element of the physical reality - perishable in its true character - survive in a text, it needs to undergo a change, a transformation: what needs to change in order for it to survive? By analyzing authors who discuss this nature of the text in their works, the thesis comes to understanding the production of a text as a discovery of such an environment within the text, which would allow the element of reality to be conserved. As far as reception is concerned, the thesis studies the influence a literary text has on our experience of reality. The problem is not only tackled as a perception of the world via a certain literary work, which was for example the case with the literary characters of Don Quixote or Madame Bovary, but the thesis tries to describe the deep transformation of our perception of reality caused by a poetic outlook on elements of the real world.

The purpose of this study is to examine how the internationalization process in small firms impacts their resource base renewal. The relationships between organizational learning, dynamic capabilities, operational capabilities and resources are empirically examined to determine the impact of internationalization on changes to the firm’s resource base. The empirical analysis follows a multiple case study research methodology and is based on in depth case studies of four internationalized professional service firms in Ontario. Cases include born-global and born-again global firms, exemplifying both location-based and knowledge-based services. The study finds evidence supporting the relationships between internationalization, organizational learning and planned change via dynamic capabilities, as well as internationalization, organizational learning and ad hoc problem solving. Findings also suggest that the firms’ repetitive use of ad hoc problem solving when faced with similar situations leads to the creation of dynamic capabilities. This research adds to the existing body of literature on services, international entrepreneurship and strategy by responding to a call for empirical examination of organizational learning within the RBV and DC constructs. Furthermore, it also applies a novel theoretical framework with which to examine the impact of small firm internationalization and their strategic renewal. By doing so, this thesis extends the RBV and DC perspectives to small service firms. Findings demonstrate a need to further continue this research path to gain greater understanding of the change processes that occur during the evolution of the firm’s resource base, as pertains to small knowledge-intensive service firms.

With the proliferation of social networks, people are likely to share their opinions about news, social events and products on the Web. There is an increasing interest in understanding users’ attitude or sentiment from the large repository of opinion-rich data on the Web. This can benefit many commercial and political applications. Primarily, the researchers concentrated on the documents such as users’ comments on the purchased products. Recent works show that visual appearance also conveys rich human affection that can be predicted. While great efforts have been devoted on the single media, either text or image, little attempts are paid for the joint analysis of multi-view data which is becoming a prevalent form in the social media. For example, paired with the posted textual messages on Twitter, users are likely to upload images and videos which may carry their affective states. One common obstacle is the lack of sufficient manually annotated instances for model learning and performance evaluation. To prompt the researches on this problem, we introduce a multi-view sentiment analysis dataset (MVSA) including a set of manually annotated image-text pairs collected from Twitter. The dataset can be utilized as a valuable benchmark for both single-view and multi-view sentiment analysis. In this thesis, we further conduct a comprehensive study on computational analysis of sentiment from the multi-view data. The state-of-the-art approaches on single view (image or text) or multi view (image and text) data are introduced, and compared through extensive experiments conducted on our constructed dataset and other public datasets. More importantly, the effectiveness of the correlation between different views is also studied using the widely used fusion strategies and advanced multi-view feature extraction methods.

This thesis presents a usability evaluation of a non conventional way to visualize virtual objects in Augmented Reality (AR). The virtual objects consists of a window that can be placed on a real surface and then opened to view a virtual room containing some virtual objects. This concept was applied to a smartphone application created and designed to evaluate the usability of the concept. The usability was evaluated with user testing methods designed to gather information about the interaction and the perception of handheld Augmented Reality (HAR) applications. The usefulness of the concept was also evaluated by designing the application to be intended for entertainment and then evaluating the users interest for such an application. Design guidelines and design patterns created for HAR applications was followed when designing the application. The results of this project has shown that the concept is easy to both comprehend and interact with. This applies to users with previous smartphone experience but not much experience with AR. The results has also shown that smartphone users find an interest in using an application of this type. An application designed for entertainment and with the described concept. The purpose of evaluating this concept has been to verify its usefulness to promote its use in AR applications. This would create a variety in the visualization of virtual objects in AR. It would also open up for new opportunities in the use of AR.

This thesis deals with the Microsoft's self-service business intelligence tools and it's used for eCommerce. The main goal of this work is to analyze and design metrics and applications for effective management of eCommerce using PowerPivot and Power View. Metrics are based on balanced scorecard approach and applications are based on MBI reference model. This thesis is supposed to help eCommerce managers and administrators to implement a custom self-service business intelligence solution.

This thesis addresses current topic of self-service business intelligence solutions. The main goal is to create a dimensional model and pilot applications for retail used for Management of Business Informatics (MBI). In order to achieve it is main goal there are four steps, to be taken. During fulfilling of these steps minor and practical goals are achieved as well. Minor goal focuses on comparison of the advantages and disadvantages of current business intel-ligence approaches. Practical goal is to create reports and dashboards for Management of Business Informatics (MBI). The first step is to introduce the issue of classic and self-service BI concluded by comparison of both variants. The second step is the definition of retail and identification of potential indicators. The third step is the introduction of Mi-crosoft´s self-service BI technologies and tools. The fourth step is to create applications for retail in MBI using tools PowerPivot and Power View. The main contribution of this work is to create reports and dashboards that are able to support processes of general retail mod-el. Reports and dashboards will serve as pilot applications for MBI. Another contribution is to acquaint readers with the possibilities of tools PowerPivot and Power View.

The theme of my thesis The operational and financial leasing of cars (accounting and tax view) is the evaluation of the advantages of these two forms of financing. Firstly there are basic terms and types of leasing after that the situation on Czech leasing trade is evaluated. Subsequently the accounting and tax view on operational and financial leasing is processed. Theoretical knowledge is applied to practical case study, there is evaluated the most optimal form of financing a car.

The present work proposes methods to calculate street-level exposures to solar radiation. The methods comprise a combination of different software algorithms, online databases and real-time standard measurements of solar radiation. Firstly, the use of the free access image database “Google Street View” to reconstruct urban geometries is illustrated. Google Street View represents an enormous source of information readily available for its general use in the field of urban atmospheric studies. With the aid of existing software packages, it was possible to reconstruct urban geometries as projected fisheye images of the canyon upper-hemispheric view, and to model total-shortwave solar irradiance within an urban canyon. The models allowed the calculation of relative street-canyon irradiance as a fraction of that received under a full-sky view, depending on the visibility of the solar disc and the reduced sky view factor. The combined use of the ideal models with real-time data allows for the calculation of street-canyon irradiance under any cloud conditions. Validation of these techniques was obtained by comparing the calculations against in situ measurements of irradiance from a local street canyon. The existing software, however, does not allow the calculation of spectral irradiance, required for inferring, for example, the biological effects of solar radiation. The use of spectral radiative transfer software was explored to provide spectral irradiance, but commonly available models do not include the effects of horizon obstructions. The approach presented here followed the same general guidelines used to calculate total-shortwave irradiance. The spectral models required a spectral partitioning of global irradiance into direct and diffuse components, allowing the independent analysis of horizon obstruction effects on these components at each wavelength. To partition global irradiance, two equations were developed for the calculation of the diffuse-to-global irradiance ratio (DGR) under cloudless conditions: one based on simplified radiative transfer theory, and an empirical fit for local conditions. Afterwards, the effects of horizon obstructions were evaluated in combination with real-time measurements of unobstructed global spectral irradiance. A set of simulated obstructions were used to validate the models. Finally, it was observed that neglecting the anisotropic distribution of the diffuse component of solar radiation in these simple models could produce large uncertainties in some situations. A practical solution for including the anisotropy of diffuse radiation was proposed, requiring images from an unobstructed digital sky camera. The combination of tools described here will allow calculation of total and spectral global irradiance upon a flat horizontal surface whatever the local field of view. This is possible at any geographical location were the urban geometries can be described, either by manually obtaining digital photographs, or through the Google Street View database, and where there is a reasonably local standard measurement of radiation.

Wear debris found in gear lubricating oil provides extremely valuable information on the nature and severity of gear faults as well as remaining gear life. The conventional off-line process of taking samples of oil for testing of wear debris is a hindrance because it is laborious, expensive, delays information collection, and is expert oriented. In view of these limitations, the development of automating wear debris particle analysis using various approaches has been ongoing for years. However, existing online technology does not encourage widespread use of wear debris analysis (WDA) in the industry. High costs coupled with expert and labour requirements have led users to use other types of condition-based maintenance, such as vibration. There is a need to develop a WDA technique that is relatively cheap, online, requires little expertise to handle, and provides more information for maintenance decision-making. This PhD thesis proposes a WDA technique which uses image processing and three-dimensional image reconstruction to diagnose the health of machinery. Its emphasis is on using the thickness and volume of the particles generated over time to predict the onset of gearbox failure, so that maintenance action can be taken before gears reach catastrophic failure.