6 resultados para set based design

em Helda - Digital Repository of University of Helsinki


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Ubiquitous computing is about making computers and computerized artefacts a pervasive part of our everyday lifes, bringing more and more activities into the realm of information. The computationalization, informationalization of everyday activities increases not only our reach, efficiency and capabilities but also the amount and kinds of data gathered about us and our activities. In this thesis, I explore how information systems can be constructed so that they handle this personal data in a reasonable manner. The thesis provides two kinds of results: on one hand, tools and methods for both the construction as well as the evaluation of ubiquitous and mobile systems---on the other hand an evaluation of the privacy aspects of a ubiquitous social awareness system. The work emphasises real-world experiments as the most important way to study privacy. Additionally, the state of current information systems as regards data protection is studied. The tools and methods in this thesis consist of three distinct contributions. An algorithm for locationing in cellular networks is proposed that does not require the location information to be revealed beyond the user's terminal. A prototyping platform for the creation of context-aware ubiquitous applications called ContextPhone is described and released as open source. Finally, a set of methodological findings for the use of smartphones in social scientific field research is reported. A central contribution of this thesis are the pragmatic tools that allow other researchers to carry out experiments. The evaluation of the ubiquitous social awareness application ContextContacts covers both the usage of the system in general as well as an analysis of privacy implications. The usage of the system is analyzed in the light of how users make inferences of others based on real-time contextual cues mediated by the system, based on several long-term field studies. The analysis of privacy implications draws together the social psychological theory of self-presentation and research in privacy for ubiquitous computing, deriving a set of design guidelines for such systems. The main findings from these studies can be summarized as follows: The fact that ubiquitous computing systems gather more data about users can be used to not only study the use of such systems in an effort to create better systems but in general to study phenomena previously unstudied, such as the dynamic change of social networks. Systems that let people create new ways of presenting themselves to others can be fun for the users---but the self-presentation requires several thoughtful design decisions that allow the manipulation of the image mediated by the system. Finally, the growing amount of computational resources available to the users can be used to allow them to use the data themselves, rather than just being passive subjects of data gathering.

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Information visualization is a process of constructing a visual presentation of abstract quantitative data. The characteristics of visual perception enable humans to recognize patterns, trends and anomalies inherent in the data with little effort in a visual display. Such properties of the data are likely to be missed in a purely text-based presentation. Visualizations are therefore widely used in contemporary business decision support systems. Visual user interfaces called dashboards are tools for reporting the status of a company and its business environment to facilitate business intelligence (BI) and performance management activities. In this study, we examine the research on the principles of human visual perception and information visualization as well as the application of visualization in a business decision support system. A review of current BI software products reveals that the visualizations included in them are often quite ineffective in communicating important information. Based on the principles of visual perception and information visualization, we summarize a set of design guidelines for creating effective visual reporting interfaces.

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Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

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This research is connected with an education development project for the four-year-long officer education program at the National Defence University. In this curriculum physics was studied in two alternative course plans namely scientific and general. Observations connected to the later one e.g. student feedback and learning outcome gave indications that action was needed to support the course. The reform work was focused on the production of aligned course related instructional material. The learning material project produced a customized textbook set for the students of the general basic physics course. The research adapts phases that are typical in Design Based Research (DBR). The research analyses the feature requirements for physics textbook aimed at a specific sector and frames supporting instructional material development, and summarizes the experiences gained in the learning material project when the selected frames have been applied. The quality of instructional material is an essential part of qualified teaching. The goal of instructional material customization is to increase the product's customer centric nature and to enhance its function as a support media for the learning process. Textbooks are still one of the core elements in physics teaching. The idea of a textbook will remain but the form and appearance may change according to the prevailing technology. The work deals with substance connected frames (demands of a physics textbook according to the PER-viewpoint, quality thinking in educational material development), frames of university pedagogy and instructional material production processes. A wide knowledge and understanding of different frames are useful in development work, if they are to be utilized to aid inspiration without limiting new reasoning and new kinds of models. Applying customization even in the frame utilization supports creative and situation aware design and diminishes the gap between theory and practice. Generally, physics teachers produce their own supplementary instructional material. Even though customization thinking is not unknown the threshold to produce an entire textbook might be high. Even though the observations here are from the general physics course at the NDU, the research gives tools also for development in other discipline related educational contexts. This research is an example of an instructional material development work together the questions it uncovers, and presents thoughts when textbook customization is rewarding. At the same time, the research aims to further creative customization thinking in instruction and development. Key words: Physics textbook, PER (Physics Education Research), Instructional quality, Customization, Creativity

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The UDP-glucuronosyltransferases (UGTs) are enzymes of the phase II metabolic system. These enzymes catalyze the transfer of α-D-glucuronic acid from UDP-glucuronic acid to aglycones bearing nucleophilic groups affording exclusively their corresponding β-D-glucuronides to render lipophilic endobiotics and xenobiotics more water soluble. This detoxification pathway aids in the urinary and biliary excretion of lipophilic compounds thus preventing their accumulation to harmful levels. The aim of this study was to investigate the effect of stereochemical and steric features of substrates on the glucuronidation catalyzed by UGTs 2B7 and 2B17. Furthermore, this study relates to the design and synthesis of novel, selective inhibitors that display high affinity for the key enzyme involved in drug glucuronidation, UGT2B7. The starting point for the development of inhibitors was to assess the influence of the stereochemistry of substrates on the UGT-catalyzed glucuronidation reaction. A set of 28 enantiomerically pure alcohols was subjected to glucuronidation assays employing the human UGT isoforms 2B7 and 2B17. Both UGT enzymes displayed high stereoselectivity, favoring the glucuronidation of the (R)-enantiomers over their respective mirror-image compounds. The spatial arrangement of the hydroxy group of the substrate determined the rate of the UGT-catalyzed reaction. However, the affinity of the enantiomeric substrates to the enzymes was not significantly influenced by the spatial orientation of the nucleophilic hydroxy group. Based on these results, a rational approach for the design of inhibitors was developed by addressing the stereochemical features of substrate molecules. Further studies showed that the rate of the enzymatic glucuronidation of substrates was also highly dependent on the steric demand in vicinity of the nucleophilic hydroxy group. These findings provided a rational approach to turn high-affinity substrates into true UGT inhibitors by addressing stereochemical and steric features of substrate molecules. The tricyclic sesquiterpenols longifolol and isolongifolol were identified as high-affinity substrates which displayed high selectivity for the UGT isoform 2B7. These compounds served therefore as lead structures for the design of potent and selective inhibitors for UGT2B7. Selective and potent inhibitors were prepared by synthetically modifying the lead compounds longifolol and isolongifolol taking stereochemical and steric features into account. The best inhibitor of UGT2B7, β-phenyllongifolol, displayed an inhibition constant of 0.91 nM.