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Der Apple ][ war einer der drei ersten kompletten Computersysteme auf dem Markt. Von April 1977 an wurde er rund 16 Jahre lang mehrere Millionen mal verkauft. Entwickelt wurde dieser 8 Bit Homecomputer von Steve Wozniak und Steve Jobs. Sie ebneten damit den Weg für den Macintosh und das heute gut bekannte Unternehmen Apple.
Diese Arbeit beschreibt die Implementierung eines Softwareemulators für das komplette Apple ][ Computersystem auf nur einem Atmel AVR Microcontroller. Die größte Herausforderung besteht darin, dass der Microcontroller nur eine geringfügig höhere Taktrate als die zu emulierende Hardware hat. Dies erfordert eine effiziente Emulation der CPU und Speicherverwaltung, die nachfolgend zusammen mit der Laufzeitumgebung für die Emulation vorgestellt wird. Weiterhin wird die Umsetzung des Emulators mit Display und Tastatur in Hardware naher erläutert.
Mit dieser Arbeit wird die erfolgreiche Entwicklung eines portablen Apple ][ Emulators, von der Software über die Hardware bis hin zu einem Prototypen, vorgestellt.
Field margins are often the only remaining habitats of various wild plant species in agricultural landscapes. However, due to their proximity to agricultural fields, the vegetation of field margins can be affected by agrochemicals applied to the crop fields. The aim of this thesis was to investigate the individual and combined effects of herbicide, insecticide and fertilizer inputs on the plant community of a field margin. Therefore, a 3-year field experiment with a randomized block design including seven treatments (H: herbicide, I: insecticide, F: fertilizer, H+I, F+I, F+H and F+H+I) and one control was conducted on a low-production meadow. Each treatment was replicated 8 times in 8 m x 8 m plots with a distance of 2 m between each plot. The fertilizer rates (25 % of the field rate) and pesticide rates (30 % of the field rate) used for the plot applications were consistent with realistic average input rates (overspray + drift) in the first meter of a field margin directly adjacent to a wheat field.
The study revealed that fertilizer and herbicide misplacements in field margins are major factors that affect the natural plant communities of these habitats. In total, 20 of the 26 abundant species on the study site were significantly affected by the fertilizer and herbicide treatment. The fertilizer promoted plants with high nutrient uptake and decreased the frequencies of small species. The herbicide caused a nearly complete disappearance of three species directly after the first application, whereas sublethal effects (e.g., phytotoxic effects and reduced seed productions of up to 100 %) were observed for the other affected species. However, if field margins are exposed to repeated agrochemical applications over several years, then such sublethal effects (particularly reproduction effects) also reduce the population size of plant species significantly, as observed in this study.
Significant herbicide-fertilizer interaction effects were also detected and could not be extrapolated from individual effects. The fertilizer and herbicide effects became stronger over time, leading to shifts in plant community compositions after three years and to a 15 % lower species diversity than in the control. The insecticide significantly affected the frequencies of two plant species (1 positively and 1 negatively). The results of the experiment suggest that a continuous annual agrochemical application on the study site would cause further plant community shifts and would likely lead to the disappearance of certain affected plants. A clear trend of increasing grass dominance at the expense of flowering herbs was detected. This finding corresponds well with monitoring data from field margins near the study site.
Although herbicide risk assessment aims to protect non-target plants in off-field habitats from adverse effects, reproduction effects and combined effects are currently not considered. Furthermore, no regulations for fertilizer applications next to field margins exist and thus, fertilizer misplacements in field margins are likely to occur and to interact with herbicide effects.
Adaptations of the current risk assessment, a development of risk mitigation measures (e.g., in-field buffers) for the application of herbicides and fertilizers, and general management measures for field margins are needed to restore and conserve plant diversity in field margins in agricultural landscapes.
This study explored the question whether greenhouse gas mitigation projects in Namibia could be initiated through local economic development programmes. In particular, research was done on whether the Clean Development Mechanism (CDM) of the Kyoto Protocol could play an essential role in the promotion of such mitigation projects.
In a first step supporting and inhibiting factors (potential for mitigation projects, business and investment climate, institutions, etc.) were discussed, which have a negative or positive influence on mitigation projects. In a second step the mind-set of climate and energy experts as well as of local economic development experts and practitioners was analysed with regard to the research questions. To this end, 229 questionnaires, 28 interviews and the output of a focus group discussion with 20 participants were evaluated. Additionally, the author conducted a real life case study to investigate the practicability of initiating greenhouse gas mitigation projects through local economic development efforts. Parallel to the development of an economic development strategy in the Namibian region of Otjozondjupa, the potential for greenhouse gas mitigation projects was explored. Based on the outcome of this investigation project ideas were developed and their potential socio-economic impact was evaluated. Promising projects were then included into the development strategy.
Due to various factors such as the complexity of CDM, low greenhouse gas emissions in Namibia, the low price of emission rights and insufficient financial means it is unlikely that CDM projects can be initiated through local economic development initiatives in Namibia. However, many stakeholders consider the idea of interlinking mitigation projects and local economic development initiatives favourably as long as such projects support the broader objectives of those initiatives. This research has shown that locally initiated mitigation projects do not contribute much to employment or income generation at the local level in Namibia. Thus, national strategic objectives should be considered, such as improving access to electricity to all strata of society or becoming less dependent on electricity imports. This requires, however, that local economic development strategies also cover the energy sector, that local governments are willing and capacitated to initiate mitigation projects, that national and local public institutions work together more closely, that national and local economic framework conditions are improved so as to attract private investments, and that the experiences and interests of the relevant stakeholders are considered throughout the project development process.
Diffusion imaging captures the movement of water molecules in tissue by applying varying gradient fields in a magnetic resonance imaging (MRI)-based setting. It poses a crucial contribution to in vivo examinations of neuronal connections: The local diffusion profile enables inference of the position and orientation of fiber pathways. Diffusion imaging is a significant technique for fundamental neuroscience, in which pathways connecting cortical activation zones are examined, and for neurosurgical planning, where fiber reconstructions are considered as intervention related risk structures.
Diffusion tensor imaging (DTI) is currently applied in clinical environments in order to model the MRI signal due to its fast acquisition and reconstruction time. However, the inability of DTI to model complex intra-voxel diffusion distributions gave rise to an advanced reconstruction scheme which is known as high angular resolution diffusion imaging (HARDI). HARDI received increasing interest in neuroscience due to its potential to provide a more accurate view of pathway configurations in the human brain.
In order to fully exploit the advantages of HARDI over DTI, advanced fiber reconstructions and visualizations are required. This work presents novel approaches contributing to current research in the field of diffusion image processing and visualization. Diffusion classification, tractography, and visualizations approaches were designed to enable a meaningful exploration of neuronal connections as well as their constitution. Furthermore, an interactive neurosurgical planning tool with consideration of neuronal pathways was developed.
The research results in this work provide an enhanced and task-related insight into neuronal connections for neuroscientists as well as neurosurgeons and contribute to the implementation of HARDI in clinical environments.
The aim of this paper is to identify and understand the risks and issues companies are experiencing from the business use of social media and to develop a framework for describing and categorising those social media risks. The goal is to contribute to the evolving theorisation of social media risk and to provide a foundation for the further development of social media risk management strategies and processes. The study findings identify thirty risk types organised into five categories (technical, human, content, compliance and reputational). A risk-chain is used to illustrate the complex interrelated, multi-stakeholder nature of these risks and directions for future work are identified.
The way information is presented to users in online community platforms has an influence on the way the users create new information. This is the case, for instance, in question-answering fora, crowdsourcing platforms or other social computation settings. To better understand the effects of presentation policies on user activity, we introduce a generative model of user behaviour in this paper. Running simulations based on this user behaviour we demonstrate the ability of the model to evoke macro phenomena comparable to the ones observed on real world data.
Modeling and publishing Linked Open Data (LOD) involves the choice of which vocabulary to use. This choice is far from trivial and poses a challenge to a Linked Data engineer. It covers the search for appropriate vocabulary terms, making decisions regarding the number of vocabularies to consider in the design process, as well as the way of selecting and combining vocabularies. Until today, there is no study that investigates the different strategies of reusing vocabularies for LOD modeling and publishing. In this paper, we present the results of a survey with 79 participants that examines the most preferred vocabulary reuse strategies of LOD modeling. Participants of our survey are LOD publishers and practitioners. Their task was to assess different vocabulary reuse strategies and explain their ranking decision. We found significant differences between the modeling strategies that range from reusing popular vocabularies, minimizing the number of vocabularies, and staying within one domain vocabulary. A very interesting insight is that the popularity in the meaning of how frequent a vocabulary is used in a data source is more important than how often individual classes and properties arernused in the LOD cloud. Overall, the results of this survey help in understanding the strategies how data engineers reuse vocabularies, and theyrnmay also be used to develop future vocabulary engineering tools.
Next word prediction is the task of suggesting the most probable word a user will type next. Current approaches are based on the empirical analysis of corpora (large text files) resulting in probability distributions over the different sequences that occur in the corpus. The resulting language models are then used for predicting the most likely next word. State-of-the-art language models are based on n-grams and use smoothing algorithms like modified Kneser-Ney smoothing in order to reduce the data sparsity by adjusting the probability distribution of unseen sequences. Previous research has shown that building word pairs with different distances by inserting wildcard words into the sequences can result in better predictions by further reducing data sparsity. The aim of this thesis is to formalize this novel approach and implement it by also including modified Kneser-Ney smoothing.
The availability of digital cameras and the possibility to take photos at no cost lead to an increasing amount of digital photos online and on private computers. The pure amount of data makes approaches that support users in the administration of the photo necessary. As the automatic understanding of photo content is still an unsolved task, metadata is needed for supporting administrative tasks like search or photo work such as the generation of photo books. Meta-information textually describes the depicted scene or consists of information on how good or interesting a photo is.
In this thesis, an approach for creating meta-information without additional effort for the user is investigated. Eye tracking data is used to measure the human visual attention. This attention is analyzed with the objective of information creation in the form of metadata. The gaze paths of users working with photos are recorded, for example, while they are searching for photos or while they are just viewing photo collections.
Eye tracking hardware is developing fast within the last years. Because of falling prices for sensor hardware such as cameras and more competition on the eye tracker market, the prices are falling, and the usability is increasing. It can be assumed that eye tracking technology can soon be used in everyday devices such as laptops or mobile phones. The exploitation of data, recorded in the background while the user is performing daily tasks with photos, has great potential to generate information without additional effort for the users.
The first part of this work deals with the labeling of image region by means of gaze data for describing the depicted scenes in detail. Labeling takes place by assigning object names to specific photo regions. In total, three experiments were conducted for investigating the quality of these assignments in different contexts. In the first experiment, users decided whether a given object can be seen on a photo by pressing a button. In the second study, participants searched for specific photos in an image search application. In the third experiment, gaze data was collected from users playing a game with the task to classify photos regarding given categories. The results of the experiments showed that gaze-based region labeling outperforms baseline approaches in various contexts. In the second part, most important photos in a collection of photos are identified by means of visual attention for the creation of individual photo selections. Users freely viewed photos of a collection without any specific instruction on what to fixate, while their gaze paths were recorded. By comparing gaze-based and baseline photo selections to manually created selections, the worth of eye tracking data in the identification of important photos is shown. In the analysis of the data, the characteristics of gaze data has to be considered, for example, inaccurate and ambiguous data. The aggregation of gaze data, collected from several users, is one suggested approach for dealing with this kind of data.
The results of the performed experiments show the value of gaze data as source of information. It allows to benefit from human abilities where algorithms still have problems to perform satisfyingly.
Mathematical Modelling of GIS Tailored GUI Design with the Application of Spatial Fuzzy Logic
(2014)
This PhD thesis is situated within the framework of the Research-Group Learning and Neurosciences (ReGLaN)-Health and Logistics project. The goal of this project is the optimisation of health service delivery in the rural areas of South Africa. Cooperation takes place between ReGLaN-Health and Logistics and the South African Council for Scientific and Industrial Research (CSIR) Meraka Institute, with Prof Dr Dr Marlien Herselman of Pretoria, South Africa, as the central contact person. This thesis deals with the mathematical modelling of Geographic Information System (GIS)-tailoredrnGraphical User Interface (GUI) design with the application of spatial fuzzy logic. This thesis considers the mathematical visualisation of risk and resource maps for epidemiological issues using GIS and adaptive GUI design for an Open Source (OS) application for digital devices. The intention ofrnthis thesis is to provide spatial decision support tailored to different user groups. In order for the GUI elements to be evaluated and initialised, empirical teaching-learning-research on dealing with geomedia and GUI elements was conducted.