Global ETD Search

1	Exploring and assessing social research impact : a case study of a research partnership's impacts on policy and practice Morton, Sarah Catherine January 2012 (has links) There is increasing emphasis on the outcomes of research in terms of its impact on wider society. However in the social sciences the ways in which research is taken up and used, discussed, shared and applied in different policy, practice and wider settings is complex. This thesis set out to investigate the ways in which social research was used by various non-academic actors, and to explore what impact it had in order to develop methods for understanding and assessing impact. The research investigated what research impact is, how it occurs, and how it might be assessed. The research was in two phases: firstly, a case study of a research partnership between a research centre and a voluntary organisation; and, secondly, the development and seeking feedback on a framework to assess impact. The care study employed two main approaches: forward-tracking - from research to policy and/or practice - and backward tracking - from policy back to research. Both phases were conducted through a practitioner-research approach, bringing experience of working with the projects involved into the heart of the research model. The study found many ways the research from the partnership had been used in different sectors by different actors. Impacts from the research were harder to identify. In cases where there were clear impacts, the actors involved had adapted research to fit the context for research use in order to create impact. Research users continued to draw on the research for many years after publication, creating further impact as new policy or practice agendas arose. The framework used a 'pathways to impact' model to develop a theory-based approach to assessing impact and to create categories for data collection. The ways in which research might impact on policy and practice are many and cannot be easily predicted. Concepts from complexity theory, particularly a focus on relationships, an understanding of context and the concept of emergence have been useful in framing the picture of impact generated from this research. Any assessment of impact from social research needs to acknowledge that many actors are involved in the process of research being taken up and used, and impact cannot be achieved from the supply side alone. Partnership research, between an academic and voluntary sector organisation, facilitated the use and impact of the research in many ways. The thesis reconceptualises ideas about how research impacts on society, suggesting the concept of 'contribution' is more accurate and useful than attribution. It also adds to the body of empirical work on the processes of impact, and in particular of the role of research partnerships in increasing impact. It suggests that process-based approaches to assessing impact that acknowledge complexity may be fruitful in developing impact assessment methodology. 300.72
2	Machine learning for automatic classification of remotely sensed data Milne, Linda, Computer Science & Engineering, Faculty of Engineering, UNSW January 2008 (has links) As more and more remotely sensed data becomes available it is becoming increasingly harder to analyse it with the more traditional labour intensive, manual methods. The commonly used techniques, that involve expert evaluation, are widely acknowledged as providing inconsistent results, at best. We need more general techniques that can adapt to a given situation and that incorporate the strengths of the traditional methods, human operators and new technologies. The difficulty in interpreting remotely sensed data is that often only a small amount of data is available for classification. It can be noisy, incomplete or contain irrelevant information. Given that the training data may be limited we demonstrate a variety of techniques for highlighting information in the available data and how to select the most relevant information for a given classification task. We show that more consistent results between the training data and an entire image can be obtained, and how misclassification errors can be reduced. Specifically, a new technique for attribute selection in neural networks is demonstrated. Machine learning techniques, in particular, provide us with a means of automating classification using training data from a variety of data sources, including remotely sensed data and expert knowledge. A classification framework is presented in this thesis that can be used with any classifier and any available data. While this was developed in the context of vegetation mapping from remotely sensed data using machine learning classifiers, it is a general technique that can be applied to any domain. The emphasis of the applicability for this framework being domains that have inadequate training data available. contribution analysis ensemble classifiers multi-strategy classification attribute selection feature selection
3	Machine learning for automatic classification of remotely sensed data Milne, Linda, Computer Science & Engineering, Faculty of Engineering, UNSW January 2008 (has links) As more and more remotely sensed data becomes available it is becoming increasingly harder to analyse it with the more traditional labour intensive, manual methods. The commonly used techniques, that involve expert evaluation, are widely acknowledged as providing inconsistent results, at best. We need more general techniques that can adapt to a given situation and that incorporate the strengths of the traditional methods, human operators and new technologies. The difficulty in interpreting remotely sensed data is that often only a small amount of data is available for classification. It can be noisy, incomplete or contain irrelevant information. Given that the training data may be limited we demonstrate a variety of techniques for highlighting information in the available data and how to select the most relevant information for a given classification task. We show that more consistent results between the training data and an entire image can be obtained, and how misclassification errors can be reduced. Specifically, a new technique for attribute selection in neural networks is demonstrated. Machine learning techniques, in particular, provide us with a means of automating classification using training data from a variety of data sources, including remotely sensed data and expert knowledge. A classification framework is presented in this thesis that can be used with any classifier and any available data. While this was developed in the context of vegetation mapping from remotely sensed data using machine learning classifiers, it is a general technique that can be applied to any domain. The emphasis of the applicability for this framework being domains that have inadequate training data available. contribution analysis ensemble classifiers multi-strategy classification attribute selection feature selection
4	The Mississippi timber severance tax: Its economic impacts to forestry and the state economy Nepal, Sakar 12 May 2023 (has links) (PDF) Millions of dollars are collected through Mississippi’s timber severance tax every year which then funds the Forest Resource Development Program (FRDP). This study analyzed their contributions to Mississippi’s economy and found that the total possible contribution was estimated to be $6.0 million in industrial output and 222 full-time and part-time jobs in 2019. However, only about 70 percent of the FRDP funds were expended in that year, and the actual contribution was short by $1.80 million in output and 80 full-time and part-time jobs. This study also examined the impact of the severance tax and FRDP on forest investment, using Multivariate Adaptive Regression Splines (MARS). Results suggest that participation in the program is the most important factor to increase the returns from forest investment and the incentives offered by the program are more important for some landowners than others. Timber severance tax Forest Resource Development Program MARS LEV IMPLAN contribution analysis
5	Análise de caminhos de transferência de energia no projeto de sistemas de controle / Transfer path analysis in the design of active control system Melo, Fábio Xavier de 11 April 2013 (has links) A análise de caminhos de transferência de energia (TPA na sigla em inglês para Transfer Path Analysis) corresponde a um grupo de métodos numérico/experimental para análise e solução de problemas vibro-acústicos de sistemas lineares invariantes no tempo, sendo seu principal campo de aplicação a indústria automotiva. A TPA é uma técnica que identifica as principais fontes de vibração e ruído, e os caminhos estruturais e acústicos pelos quais são transmitidas para determinados locais de interesse. Conhecendo as fontes de ruído e vibração e os caminhos de propagação é possível propor modificações eficientes em minimizar o ruído/vibração nas regiões de interesse, ou atribuir características desejáveis para tais componentes, envolvendo técnicas de controle passivo e ativo. Este trabalho apresenta um estudo numérico e experimental das técnicas de TPA, utilizando métodos diretos e inversos de determinação de forças operacionais. Estes estudos foram realizados em um mockup de um veículo, com o objetivo de determinar o caminho de maior contribuição para o ruído no interior do protótipo, e a partir deste resultado, propor um sistema de controle ativo para minimizar este ruído interno. / The Transfer Path Analysis (TPA) is a group of numerical/experimental tools for the analysis and troubleshooting of noise and vibration problems in linear time invariant vibroacoustic systems, being the automotive sector its major user. TPA consists of a numerical/experimental analysis that allows the identification of the main noise and vibration sources and the structural/acoustic transfer paths to the Target points. Based on the sources and paths, it is possible to propose modifications that efficiently minimize noise and vibration at the target positions. By means of active control it is possible to modify noise and vibration in order to change, rather than minimize noise and vibration, achieving certain design targets. This work presents a numerical and experimental study of TPA techniques, using direct and inverse operational loads determination methods. These studies were performed on a vehicle mockup, in order to determine the path of greatest contribution to the noise inside the prototype, and from this result, propose an active control system to minimize this internal noise. Active structural acoustic control Controle ativo MIMO systems NVH Sistemas MIMO Source path contribution analysis TPA Transfer path analysis Vibro-acoustics Vibro-acústica
6	Análise de caminhos de transferência de energia no projeto de sistemas de controle / Transfer path analysis in the design of active control system Fábio Xavier de Melo 11 April 2013 (has links) A análise de caminhos de transferência de energia (TPA na sigla em inglês para Transfer Path Analysis) corresponde a um grupo de métodos numérico/experimental para análise e solução de problemas vibro-acústicos de sistemas lineares invariantes no tempo, sendo seu principal campo de aplicação a indústria automotiva. A TPA é uma técnica que identifica as principais fontes de vibração e ruído, e os caminhos estruturais e acústicos pelos quais são transmitidas para determinados locais de interesse. Conhecendo as fontes de ruído e vibração e os caminhos de propagação é possível propor modificações eficientes em minimizar o ruído/vibração nas regiões de interesse, ou atribuir características desejáveis para tais componentes, envolvendo técnicas de controle passivo e ativo. Este trabalho apresenta um estudo numérico e experimental das técnicas de TPA, utilizando métodos diretos e inversos de determinação de forças operacionais. Estes estudos foram realizados em um mockup de um veículo, com o objetivo de determinar o caminho de maior contribuição para o ruído no interior do protótipo, e a partir deste resultado, propor um sistema de controle ativo para minimizar este ruído interno. / The Transfer Path Analysis (TPA) is a group of numerical/experimental tools for the analysis and troubleshooting of noise and vibration problems in linear time invariant vibroacoustic systems, being the automotive sector its major user. TPA consists of a numerical/experimental analysis that allows the identification of the main noise and vibration sources and the structural/acoustic transfer paths to the Target points. Based on the sources and paths, it is possible to propose modifications that efficiently minimize noise and vibration at the target positions. By means of active control it is possible to modify noise and vibration in order to change, rather than minimize noise and vibration, achieving certain design targets. This work presents a numerical and experimental study of TPA techniques, using direct and inverse operational loads determination methods. These studies were performed on a vehicle mockup, in order to determine the path of greatest contribution to the noise inside the prototype, and from this result, propose an active control system to minimize this internal noise. Controle ativo NVH Sistemas MIMO TPA Vibro-acústica Active structural acoustic control MIMO systems Source path contribution analysis Transfer path analysis Vibro-acoustics
7	Forschung und forschendes Lernen im Rahmen von Service Learning: am Professionalcenter der Universität zu Köln Kollender-Jonen, Pia, Lönnies, Louisa 19 February 2019 (has links) Der folgende Artikel stellt zwei Untersuchungen und ein Forschendes Lernen-Projekt im Rahmen von Service Learning am ProfessionalCenter der Universität zu Köln vor. Die Untersuchungen hatten die Motivation der teilnehmenden Studierenden sowie die Beweggründe der Projektpartner_ innen zum Gegenstand. Als Beispiel, um den Facettenreichtum und den Nutzen von Service Learning sowohl für Studierende als auch für zivilgesellschaftliche Organisationen zu verdeutlichen, dient die für die Kölner Freiwilligen Agentur durchgeführte Wertbeitragsanalyse der Initiative Lesewelten als Best Practice-Projekt. Abschließend werden weitere umgesetzte Service Learning-Projekte aus diesem Bereich vorgestellt. info:eu-repo/classification/ddc/370 ddc:370
8	Assessing foresight to advance management of complex global problems Berze, Ottilia E. 15 April 2019 (has links) Many people do not like thinking about the future. If they do, over 50% of Canadians think “our way of life” (p. 7) will end within 100 years and over 80% of Canadians think “we need to change our worldview and way of life if we are to create a better future for the world” (Randle & Eckersley, 2015, p. 9). There is a good reason for this. Alarms have sounded over global urgent complex problems with potential for catastrophic consequences such as the development of artificial intelligence, climate change, mass extinction, nuclear war and pandemics (Marien & Halal, 2011). Society is also increasingly fragmenting as imminent crises build on lack of understanding, the sense of incapacity to act, fear, distrust, blame and a lack of hope. This struggle for humanity’s survival is complicated by the turbulent global environment in which institutions continue to follow path-dependent trajectories set forth in a different time and context. Governments at various levels face a problem of “fit” between current structures and processes, that have not progressed sufficiently to meet changing needs of a global society mired in complexity and governance challenges. However, hope exists. Incremental progress on many fronts and a massive amount of efforts and resources are being engaged worldwide. There are emerging fields, lenses and tools that can potentially alleviate complex problems and address this emergency. The purpose of this dissertation is to understand and assess dialogue-based foresight practices being applied towards complex problems in Canada to provide insights into how these practices can assist society to alleviate global urgent complex problems and their impacts, within this backdrop of looming crises. Foresight, alternatively known as future studies or scenario-building, is a forward-looking practice recognized and used globally with over 100 research organizations focused on foresight, widespread usage by firms and over 18 countries involved in foresight activities (Berze, 2014b). Overall literature findings suggest foresight is widely and at least incrementally effective with a number of impacts in various areas (Calof, Miller, & Jackson, 2012; March, Therond, & Leenhardt, 2012; Meissner, Gokhberg, & Sokolov, 2013) but the extent of this effectiveness, the mechanisms involved, and the specific foresight benefits per type of project needs further research and evidence. For instance, limited literature exists on whether foresight can transform complex situations and if so, under what conditions. Thus, opportunities exist for assessing and increasing foresight’s impact. This dissertation is a contextualized, systematic empirical study that taps into transdisciplinary literature and practice, case studies of how foresight has been used to address specific types of complex problems in Canada, as well as surveys and interviews with foresight experts and participants. This dissertation uses a foresight community scan and a comparative case study approach to provide practical and theoretical benefits to foresight and complex problem area stakeholders. The research focuses on studying the broad interactions of foresight and identifying the impacts of dialogue-based foresight projects on people and the outcomes of complex problems. The dissertation concludes that dialogue-based foresight is a valuable and unique practice for ameliorating complex problems and their consequences. Insights are offered towards dialogue-based foresight’s potential contributions within the context of other efforts directed at humanity’s struggle for survival and global complex problems. These insights can then foster the further development and application of dialogue-based foresight on a global scale to alleviate complex problems and their effects. The dissertation outlines recommendations on key next steps to realize these potential contributions. / Graduate foresight dialogue-based complex global problems empirical transdisciplinary crisis comparative cases comparative case study hope practice community Canada projects impact value futures scenario future role wicked problems transformative complexity interviews urgent lens mechanisms assessment well-being strengthening improving concepts types foresight benefits contribution analysis tools approaches mainstream barriers Fore-CAN Georgia Basin Global Energy Landscape Agricultural Adaptation Canadian Payment System 2020 Media Futures systems digital climate change infectious diseases sustainability coping transitioning recommendations multi-perspective dialogue conflict resolution collaboration diversity outcomes invest context contributions efforts innovation cognitive social understanding foresight literacy anticipation futures literacy

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