989 resultados para Green Technology
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Dissertação para obtenção do Grau de Doutor em Informática
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Dissertação para obtenção do Grau de Doutor em Química Sustentável
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertation presented to obtain the Ph.D degree in Engineering and Technology Sciences, Biotechnology.
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Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.
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Using a green methodology, 17 different poly(2-oxazolines) were synthesized starting from four different oxazoline monomers. The polymerization reactions were conducted in supercritical carbon dioxide under a cationic ring-opening polymerization (CROP) mechanism using boron trifluoride diethyl etherate as the catalyst. The obtained living polymers were then end-capped with different types of amines, in order to confer them antimicrobial activity. For comparison, four polyoxazolines were end-capped with water, and by their hydrolysis the linear poly(ethyleneimine) (LPEI) was also produced. After functionalization the obtained polymers were isolated, purified and characterized by standard techniques (FT-IR, NMR, MALDI-TOF and GPC). The synthesized poly(2-oxazolines) revealed an unusual intrinsic blue photoluminescence. High concentration of carbonyl groups in the polymer backbone is appointed as a key structural factor for the presence of fluorescence and enlarges polyoxazolines’ potential applications. Microbiological assays were also performed in order to evaluate their antimicrobial profile against gram-positive Staphylococcus aureus NCTC8325-4 and gram-negative Escherichia coli AB1157 strains, two well known and difficult to control pathogens. The minimum inhibitory concentrations (MIC)s and killing rates of three synthesized polymers against both strains were determined. The end-capping with N,N-dimethyldodecylamine of living poly(2- methyl-2-oxazoline) and poly(bisoxazoline) led to materials with higher MIC values but fast killing rates (less than 5 minutes to achieve 100% killing for both bacterial species) than LPEI, a polymer which had a lower MIC value, but took a longer time to kill both E.coli and S.aureus cells. LPEI achieved 100% killing after 45 minutes in contact with E. coli and after 4 hours in contact with S.aureus. Such huge differences in the biocidal behavior of the different polymers can possibly underlie different mechanisms of action. In the future, studies to elucidate the obtained data will be performed to better understand the killing mechanisms of the polymers through the use of microbial cell biology techniques.
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Paper presented at the Colloquium Gerpisa 2013, Paris (http://gerpisa.org/node/2085), Session n°: 19 New kinds of mobility: old and new business models
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This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.
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The demand for costs and time reductions in companies’ processes, in order to increase efficiency, leads companies to seek innovative management paradigms to support their needs for growth and continuous improvement. The Lean paradigm has great relevance in companies’ need for waste reduction, particularly in manufacturing companies. On the other hand the demand of companies for waste reduction has gained a new dimension not only at the material level, but also at the environmental level with the introduction of the Green paradigm. As such, manufacturing companies have been adopting practices that reduce the impact of their activities on the environment. Although nowadays many manufacturing companies already implement waste reduction practices related to Lean and Green paradigms, many of them are unable to understand specifically if their efforts are enough for the application of these practices to be successful or even if their actual performance in implementing Lean or Green practices reflects the self-assessment that they have of themselves. Thus, besides the study of the development of Lean and Green paradigms in recent years, the present dissertation has the important objective of the construction of two indexes (the Lean Index and the Green Index) enabling the measurement of the performance of Portuguese manufacturing companies relating the implementation of Lean and Green practices. The data used to create the Lean and Green indexes where obtained from the implementation of the European Manufacturing Survey 2012 in Portugal. The survey questions related to the implementation of Lean and Green practices are used as variables in the development of the model for the two indexes. For the construction of representative expressions of Lean Index and Green Index it was applied the Factorial Analysis for assigning the variables weights and aggregation.
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With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.
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Os paradigmas de produção lean e green têm sido alvo de inúmeros estudos que realçam o seu impacto positivo no desempenho das empresas. Esta dissertação tem como objetivo analisar o tipo de impacto dos paradigmas de produção lean e green no desempenho de empresas da indústria transformadora em Portugal bem como o nível de utilização das práticas/ferramentas lean e green nas referidas empresas. Para o efeito, foram desenvolvidos dois modelos estruturais, que relacionam as práticas/ferramentas lean e green com o desempenho da empresa, e identificadas duas hipóteses de investigação. O conjunto de práticas/ferramentas lean e green identificadas na revisão da literatura formaram os constructs lean e green, respetivamente. Os constructs desempenho organizacional lean e green foram formados pelo conjunto de indicadores de desempenho associados a cada um dos paradigmas. Para recolha de dados foi implementado o European Manufaturing Survey e obteve-se uma amostra de 62 empresas da indústria transformadora portuguesa. Foram sugeridas algumas metodologias para testar as hipóteses do modelo que não eram possíveis de aplicar neste estudo. Conclui-se que os níveis de utilização das práticas/ferramentas lean e green são relativamente reduzidos.
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Based on the report for the unit “Project IV” of the PhD programme on Technology Assessment under the supervision of Dr.-Ing. Marcel Weil and Prof. Dr. António Brandão Moniz. The report was presented and discussed at the Doctorate Conference on Technologogy Assessment in July 2013 at the University Nova Lisboa, Caparica campus.
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This project attempts to provide an in-depth competitive assessment of the Portuguese indoor location-based analytics market, and to elaborate an entry-pricing strategy for Business Intelligence Positioning System (BIPS) implementation in Portuguese shopping centre stores. The role of industry forces and company’s organizational resources platform to sustain company’s competitive advantage was explored. A customer value-based pricing approach was adopted to assess BIPS value to retailers and maximize Sonae Sierra profitability. The exploratory quantitative research found that there is a market opportunity to explore every store area types with tailored proposals, and to set higher-than-tested membership fees to allow a rapid ROI, concluding there are propitious conditions for Sierra to succeed in BIPS store’s business model in Portugal.