5 resultados para Design theory

em Helda - Digital Repository of University of Helsinki


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The aim of the thesis was to compare the correspondence of the outcome a computer assisted program appearance compared to the original image. The aspect of the study was directed to embroidery with household machines. The study was made from the usability point of view with Brother's PE-design 6.0 embroidery design programs two automatic techniques; multicoloured fragment design and multicoloured stitch surface design. The study's subject is very current because of the fast development of machine embroidery. The theory is based on history of household sewing machines, embroidery sewing machines, stitch types in household sewing machines, embroidery design programs as well as PE-design 6.0 embroidery design program's six automatic techniques. Additionally designing of embroidery designs were included: original image, digitizing, punching, applicable sewing threads as well as the connection between embroidery designs and materials used on embroidery. Correspondences of sewn appearances were examined with sewing experimental methods. 18 research samples of five original image were sewn with both techniques. Experiments were divided into four testing stages in design program. Every testing stage was followed by experimental sewing with Brother Super Galaxie 3100D embroidery machine. Experiments were reported into process files and forms made for the techniques. Research samples were analysed on images syntactic bases with sensory perception assessment. Original images and correspondence of the embroidery appearances were analysed with a form made of it. The form was divided into colour and shape assessment in five stage-similarity-scale. Based on this correspondence analysis it can be said that with both automatic techniques the best correspondence of colour and shape was achieved by changing the standard settings and using the makers own thread chart and edited original image. According to the testing made it is impossible to inform where the image editing possibilities of the images are sufficient or does the optimum correspondence need a separate program. When aiming at correspondence between appearances of two images the computer is unable to trace by itself the appearance of the original image. Processing a computer program assisted embroidery image human perception and personal decision making are unavoidable.

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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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Governance has been one of the most popular buzzwords in recent political science. As with any term shared by numerous fields of research, as well as everyday language, governance is encumbered by a jungle of definitions and applications. This work elaborates on the concept of network governance. Network governance refers to complex policy-making situations, where a variety of public and private actors collaborate in order to produce and define policy. Governance is processes of autonomous, self-organizing networks of organizations exchanging information and deliberating. Network governance is a theoretical concept that corresponds to an empirical phenomenon. Often, this phenomenon is used to descirbe a historical development: governance is often used to describe changes in political processes of Western societies since the 1980s. In this work, empirical governance networks are used as an organizing framework, and the concepts of autonomy, self-organization and network structure are developed as tools for empirical analysis of any complex decision-making process. This work develops this framework and explores the governance networks in the case of environmental policy-making in the City of Helsinki, Finland. The crafting of a local ecological sustainability programme required support and knowledge from all sectors of administration, a number of entrepreneurs and companies and the inhabitants of Helsinki. The policy process relied explicitly on networking, with public and private actors collaborating to design policy instruments. Communication between individual organizations led to the development of network structures and patterns. This research analyses these patterns and their effects on policy choice, by applying the methods of social network analysis. A variety of social network analysis methods are used to uncover different features of the networked process. Links between individual network positions, network subgroup structures and macro-level network patterns are compared to the types of organizations involved and final policy instruments chosen. By using governance concepts to depict a policy process, the work aims to assess whether they contribute to models of policy-making. The conclusion is that the governance literature sheds light on events that would otherwise go unnoticed, or whose conceptualization would remain atheoretical. The framework of network governance should be in the toolkit of the policy analyst.

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This paper addresses several questions in the compensation literature by examining stock option compensation practices of Finnish firms. First, the results indicate that principal-agent theory succeeds quite well in predicting the use of stock options. Proxies for monitoring costs, growth opportunities, ownership structure, and risk are found to determine the use of incentives consistent with theory. Furthermore, the paper examines whether determinants of stock options targeted to top management differ from determinants of broad-based stock option plans. Some evidence is found that factors driving these two types of incentives differ. Second, the results reveal that systematic risk significantly increases the likelihood that firms adopt stock option plans, whereas total firm risk and unsystematic risk do not seem to affect this decision. Third, the results show that growth opportunities are related to time-dimensional contracting frequency, consistent with the argument that incentive levels deviate more rapidly from optimum in firms with high growth opportunities. Finally, the results suggest that vesting schedules are decreasing in financial leverage, and that contract maturity is decreasing in firm focus. In addition, both vesting schedules and contract maturity tend to be longer in firms involving state ownership.