36 resultados para Technological development and diffusion

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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The Kenyan forestry and sawmilling industry have been subject to a changing environment since 1999 when the industrial forest plantations were closed down. This has lowered raw material supply and it has affected and reduced the sawmill operations and the viability of the sawmill enterprises. The capacity of the 276 registered sawmills is not sufficient to fulfill sawn timber demand in Kenya. This is because of the technological degradation and lack of a qualified labor force, which were caused because of non-existent sawmilling education and further training in Kenya. Lack of competent sawmill workers has led to low raw material recovery, under utilization of resources and loss of employment. The objective of the work was to suggest models, methods and approaches for the competence and capacity development of the Kenyan sawmilling industry, sawmills and their workers. A nationwide field survey, interviews, questionnaire and literature review was used for data collection to find out the sawmills’ competence development areas and to suggest models and methods for their capacity building. The sampling frame included 22 sawmills that represented 72,5% of all the registered sawmills in Kenya. The results confirmed that the sawmills’ technological level was backwards, productivity low, raw material recovery unacceptable and workers’ professional education low. The future challenges will be how to establish the sawmills’ capacity building and workers’ competence development. Sawmilling industry development requires various actions through new development models and approaches. Activities should be started for technological development and workers’ competence development. This requires re-starting of vocational training in sawmilling and the establishment of more effective co-operation between the sawmills and their stakeholder groups. In competence development the Enterprise Competence Management Model of Nurminen (2007) can be used, whereas the best training model and approach would be a practically oriented learning at work model in which the short courses, technical assistance and extension services would be the key functions.

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Our goal is to get better understanding of different kind of dependencies behind the high-level capability areas. The models are suitable for investigating present state capabilities or future developments of capabilities in the context of technology forecasting. Three levels are necessary for a model describing effects of technologies on military capabilities. These levels are capability areas, systems and technologies. The contribution of this paper is to present one possible model for interdependencies between technologies. Modelling interdependencies between technologies is the last building block in constructing a quantitative model for technological forecasting including necessary levels of abstraction. This study supplements our previous research and as a result we present a model for the whole process of capability modelling. As in our earlier studies, capability is defined as the probability of a successful task or operation or proper functioning of a system. In order to obtain numerical data to demonstrate our model, we conducted a questionnaire to a group of defence technology researchers where interdependencies between seven representative technologies were inquired. Because of a small number of participants in questionnaires and general uncertainties concerning subjective evaluations, only rough conclusions can be made from the numerical results

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The purpose of the study is: (1) to describe how nursing students' experienced their clinical learning environment and the supervision given by staff nurses working in hospital settings; and (2) to develop and test an evaluation scale of Clinical Learning Environment and Supervision (CLES). The study has been carried out in different phases. The pilot study (n=163) explored the association between the characteristics of a ward and its evaluation as a learning environment by students. The second version of research instrument (which was developed by the results of this pilot study) were tested by an expert panel (n=9 nurse teachers) and test-retest group formed by student nurses (n=38). After this evaluative phase, the CLES was formed as the basic research instrument for this study and it was tested with the Finnish main sample (n=416). In this phase, a concurrent validity instrument (Dunn & Burnett 1995) was used to confirm the validation process of CLES. The international comparative study was made by comparing the Finnish main sample with a British sample (n=142). The international comparative study was necessary for two reasons. In the instrument developing process, there is a need to test the new instrument in some other nursing culture. Other reason for comparative international study is the reflecting the impact of open employment markets in the European Union (EU) on the need to evaluate and to integrate EU health care educational systems. The results showed that the individualised supervision system is the most used supervision model and the supervisory relationship with personal mentor is the most meaningful single element of supervision evaluated by nursing students. The ward atmosphere and the management style of ward manager are the most important environmental factors of the clinical ward. The study integrates two theoretical elements - learning environment and supervision - in developing a preliminary theoretical model. The comparative international study showed that, Finnish students were more satisfied and evaluated their clinical placements and supervision with higher scores than students in the United Kingdom (UK). The difference between groups was statistical highly significant (p= 0.000). In the UK, clinical placements were longer but students met their nurse teachers less frequently than students in Finland. Arrangements for supervision were similar. This research process has produced the evaluation scale (CLES), which can be used in research and quality assessments of clinical learning environment and supervision in Finland and in the UK. CLES consists of 27 items and it is sub-divided into five sub-dimensions. Cronbach's alpha coefficient varied from high 0.94 to marginal 0.73. CLES is a compact evaluation scale and user-friendliness makes it suitable for continuing evaluation.

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Tuotekehityksestä ja sen johtamisesta on tullut erittäin tärkeä osa tietoliikenneteollisuutta. Jatkuva teknologinen kehitys ja lyhentyneet tuotteiden elinkaaret ovat saaneet yritykset panostamaan tuotekehitysprosesseihin ja johtamiseen. Erityisesti nopeatempoiset ja lyhytkestoiset projektit onkin koettu ongelmallisiksi. Diplomityön tavoitteena oli tutkia teoriassa uusien tuotteiden tuotekehitystä, tuotekehitysprosesseja sekä projektijohtamista. Käytännön osuudessa oli tavoitteena kehittää kokeellinen tuotekehitysmalli nopeatempoisten ja lyhytkestoisten tuotekehitysprojektien tarpeisiin muuttuvissa ja epävarmoissa olosuhteissa. Tavoitteena oli myös käyttää ja analysoida kehitettyä kokeellista tuotekehitysmallia lyhytkestoisen tuotekehitysprojektin yhteydessä. Työn tuloksena saatiin ohjelmistotuote vaadituilla ominaisuuksilla vaaditussa ajassa ja todettiin projektissa käytetyn kokeellisen tuotekehitysmallin osoittautuneen toimivaksi. Jatkotutkimuksia tarvitaan selvittämään mallin sopivuutta ja sen kehityskohteita erilaisten tuotekehitysprojektien kohdalla.

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Main purpose of this thesis is to introduce a new lossless compression algorithm for multispectral images. Proposed algorithm is based on reducing the band ordering problem to the problem of finding a minimum spanning tree in a weighted directed graph, where set of the graph vertices corresponds to multispectral image bands and the arcs’ weights have been computed using a newly invented adaptive linear prediction model. The adaptive prediction model is an extended unification of 2–and 4–neighbour pixel context linear prediction schemes. The algorithm provides individual prediction of each image band using the optimal prediction scheme, defined by the adaptive prediction model and the optimal predicting band suggested by minimum spanning tree. Its efficiency has been compared with respect to the best lossless compression algorithms for multispectral images. Three recently invented algorithms have been considered. Numerical results produced by these algorithms allow concluding that adaptive prediction based algorithm is the best one for lossless compression of multispectral images. Real multispectral data captured from an airplane have been used for the testing.

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The developing energy markets and rising energy system costs have sparked the need to find new forms of energy production and increase the self-sufficiency of energy production. One alternative is gasification, whose principles have been known for decades, but it is only recently when the technology has become a true alternative. However, in order to meet the requirements of modern energy production methods, it is necessary to study the phenomenon thoroughly. In order to understand the gasification process better and optimize it from the viewpoint of ecology and energy efficiency, it is necessary to develop effective and reliable modeling tools for gasifiers. The main aims of this work have been to understand gasification as a process and furthermore to develop an existing three-dimensional circulating fluidized bed modeling tool for modeling of gasification. The model is applied to two gasification processes of 12 and 50 MWth. The results of modeling and measurements have been compared and subsequently reviewed. The work was done in co-operation with Lappeenranta University of Technology and Foster Wheeler Energia Oy.

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More and more innovations currently being commercialized exhibit network effects, in other words, the value of using the product increases as more and more people use the same or compatible products. Although this phenomenon has been the subject of much theoretical debate in economics, marketing researchers have been slow to respond to the growing importance of network effects in new product success. Despite an increase in interest in recent years, there is no comprehensive view on the phenomenon and, therefore, there is currently incomplete understanding of the dimensions it incorporates. Furthermore, there is wide dispersion in operationalization, in other words, the measurement of network effects, and currently available approaches have various shortcomings that limit their applicability, especially in marketing research. Consequently, little is known today about how these products fare on the marketplace and how they should be introduced in order to maximize their chances of success. Hence, the motivation for this study was driven by the need to increase our knowledge and understanding of the nature of network effects as a phenomenon, and of their role in the commercial success of new products. This thesis consists of two parts. The first part comprises a theoretical overview of the relevant literature, and presents the conclusions of the entire study. The second part comprises five complementary, empirical research publications. Quantitative research methods and two sets of quantitative data are utilized. The results of the study suggest that there is a need to update both the conceptualization and the operationalization of the phenomenon of network effects. Furthermore, there is a need for an augmented view on customers’ perceived value in the context of network effects, given that the nature of value composition has major implications for the viability of such products in the marketplace. The role of network effects in new product performance is not as straightforward as suggested in the existing theoretical literature. The overwhelming result of this study is that network effects do not directly influence product success, but rather enhance or suppress the influence of product introduction strategies. The major contribution of this study is in conceptualizing the phenomenon of network effects more comprehensively than has been attempted thus far. The study gives an augmented view of the nature of customer value in network markets, which helps in explaining why some products thrive on these markets whereas others never catch on. Second, the study discusses shortcomings in prior literature in the way it has operationalized network effects, suggesting that these limitations can be overcome in the research design. Third, the study provides some much-needed empirical evidence on how network effects, product introduction strategies, and new product performance are associated. In general terms, this thesis adds to our knowledge of how firms can successfully leverage network effects in product commercialization in order to improve market performance.

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The Repair of segmental defects in load-bearing long bones is a challenging task because of the diversity of the load affecting the area; axial, bending, shearing and torsional forces all come together to test the stability/integrity of the bone. The natural biomechanical requirements for bone restorative materials include strength to withstand heavy loads, and adaptivity to conform into a biological environment without disturbing or damaging it. Fiber-reinforced composite (FRC) materials have shown promise, as metals and ceramics have been too rigid, and polymers alone are lacking in strength which is needed for restoration. The versatility of the fiber-reinforced composites also allows tailoring of the composite to meet the multitude of bone properties in the skeleton. The attachment and incorporation of a bone substitute to bone has been advanced by different surface modification methods. Most often this is achieved by the creation of surface texture, which allows bone growth, onto the substitute, creating a mechanical interlocking. Another method is to alter the chemical properties of the surface to create bonding with the bone – for example with a hydroxyapatite (HA) or a bioactive glass (BG) coating. A novel fiber-reinforced composite implant material with a porous surface was developed for bone substitution purposes in load-bearing applications. The material’s biomechanical properties were tailored with unidirectional fiber reinforcement to match the strength of cortical bone. To advance bone growth onto the material, an optimal surface porosity was created by a dissolution process, and an addition of bioactive glass to the material was explored. The effects of dissolution and orientation of the fiber reinforcement were also evaluated for bone-bonding purposes. The Biological response to the implant material was evaluated in a cell culture study to assure the safety of the materials combined. To test the material’s properties in a clinical setting, an animal model was used. A critical-size bone defect in a rabbit’s tibia was used to test the material in a load-bearing application, with short- and long-term follow-up, and a histological evaluation of the incorporation to the host bone. The biomechanical results of the study showed that the material is durable and the tailoring of the properties can be reproduced reliably. The Biological response - ex vivo - to the created surface structure favours the attachment and growth of bone cells, with the additional benefit of bioactive glass appearing on the surface. No toxic reactions to possible agents leaching from the material could be detected in the cell culture study when compared to a nontoxic control material. The mechanical interlocking was enhanced - as expected - with the porosity, whereas the reinforcing fibers protruding from the surface of the implant gave additional strength when tested in a bone-bonding model. Animal experiments verified that the material is capable of withstanding load-bearing conditions in prolonged use without breaking of the material or creating stress shielding effects to the host bone. A Histological examination verified the enhanced incorporation to host bone with an abundance of bone growth onto and over the material. This was achieved with minimal tissue reactions to a foreign body. An FRC implant with surface porosity displays potential in the field of reconstructive surgery, especially regarding large bone defects with high demands on strength and shape retention in load-bearing areas or flat bones such as facial / cranial bones. The benefits of modifying the strength of the material and adjusting the surface properties with fiber reinforcement and bone-bonding additives to meet the requirements of different bone qualities are still to be fully discovered.