882 resultados para the least squares distance method
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ABSTRACT This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q7,10, Q90 and Q95). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall – Pa; total semiannual rainfall of the dry and of the rainy season – Pss and Psc; watershed drainage area – Ad; length of the main river – Lp; total length of the rivers – Lt; and average watershed slope – SL). The results of the principal component analysis pointed out that the variable SL was the least representative for the study, and so it was discarded. The most representative independent variables were Ad and Psc. The best divisions of hydrologically homogeneous regions for the three studied flow characteristics were obtained using the Mahalanobis similarity matrix and the complete linkage clustering method. The cluster analysis enabled the identification of four hydrologically homogeneous regions in the Doce river basin.
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People make up one of the most important resources for a corporation and therefore it has to continuously seek an ever more diverse and international workforce. Inpatriation is another way of utilizing foreign expertise in a corporation. An inpatriate refers to a person that is on an international assignment at the headquarters of a corporation, where they have been sent either from a subsidiary abroad or from a third country outside the corporation. Strengthening the social network of the inpatriate and their family contributes to the adjustment process and furthermore the success of the work assignment. As social networking sites are currently the fastest developing personal networking tools in the world, it is interesting to see how they can help in inpatriate adjustment. The objective of this thesis is to explore the potential of social networking sites (SNS) in inpatriate adjustment. The main objective can be divided into three sub objectives: 1. What is SNS used for during the inpatriate assignment? 2. What are the inpatriates’ motivations to use SNS? 3. Could the three facets of adjustment (work, interaction and general) be gained through SNS? This qualitative study utilizes the theme interview data collection method and the thematic analysis approach for analysing the interview data. From the interviews with five Indian inpatriates in Finland the most mentioned uses of SNS were related to participating (sharing opinions, recommendations and discussing things and connecting to friends, family and colleagues) and consuming (collecting information for work and free time), the least mentioned use of SNS was producing (posting videos, photos and updates). An interesting finding was that the five interviewees did not use SNS for purely entertainment motives at all during their assignment. This thesis found that all three facets of adjustment could potentially be gained through SNS.
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Industrial maintenance can be executed internally, acquired from the original equipment manufacturer or outsourced to a service provider, and this concludes in many different kind of business relationships. To maximize the total value in a maintenance business relationship it is important to know what the partner values. The value of maintenance services can be considered to consist of value elements and the perceived total value for the customer and the service provider is the sum of these value elements. The specific objectives of this thesis are to identify the most important value elements for the maintenance service customer and provider and also to recognize where the value elements differ. The study was executed as a statistical analysis using the survey method. The data has been collected by an online survey sent to 345 maintenance service professionals in Finland. In the survey, four different types of value elements were considered: the customer’s high critical and low critical items and the service provider’s core and support service. The most valued elements by the respondents were reliability, safety at work, environmental safety, and operator knowledge. The least valued elements were asset management factors and access to markets. Statistically significant differences in value elements between service types were also found. As a managerial implication a value gap profile is presented. This Master’s Thesis is part of the MaiSeMa (Industrial Maintenance Services in a Renewing Business Network: Identify, Model and Manage Value) research project where network decision models are created to identify, model and manage the value of maintenance services.
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A model for predicting temperature evolution for automatic controling systems in manufacturing processes requiring the coiling of bars in the transfer table is presented. Although the method is of a general nature, the presentation in this work refers to the manufacturing of steel plates in hot rolling mills. The predicting strategy is based on a mathematical model of the evolution of temperature in a coiling and uncoiling bar and is presented in the form of a parabolic partial differential equation for a shape changing domain. The mathematical model is solved numerically by a space discretization via geometrically adaptive finite elements which accomodate the change in shape of the domain, using a computationally novel treatment of the resulting thermal contact problem due to coiling. Time is discretized according to a Crank-Nicolson scheme. Since the actual physical process takes less time than the time required by the process controlling computer to solve the full mathematical model, a special predictive device was developed, in the form of a set of least squares polynomials, based on the off-line numerical solution of the mathematical model.
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The determination of the intersection curve between Bézier Surfaces may be seen as the composition of two separated problems: determining initial points and tracing the intersection curve from these points. The Bézier Surface is represented by a parametric function (polynomial with two variables) that maps a point in the tridimensional space from the bidimensional parametric space. In this article, it is proposed an algorithm to determine the initial points of the intersection curve of Bézier Surfaces, based on the solution of polynomial systems with the Projected Polyhedral Method, followed by a method for tracing the intersection curves (Marching Method with differential equations). In order to allow the use of the Projected Polyhedral Method, the equations of the system must be represented in terms of the Bernstein basis, and towards this goal it is proposed a robust and reliable algorithm to exactly transform a multivariable polynomial in terms of power basis to a polynomial written in terms of Bernstein basis .
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This paper gives a detailed presentation of the Substitution-Newton-Raphson method, suitable for large sparse non-linear systems. It combines the Successive Substitution method and the Newton-Raphson method in such way as to take the best advantages of both, keeping the convergence features of the Newton-Raphson with the low requirements of memory and time of the Successive Substitution schemes. The large system is solved employing few effective variables, using the greatest possible part of the model equations in substitution fashion to fix the remaining variables, but maintaining the convergence characteristics of the Newton-Raphson. The methodology is exemplified through a simple algebraic system, and applied to a simple thermodynamic, mechanical and heat transfer modeling of a single-stage vapor compression refrigeration system. Three distinct approaches for reproducing the thermodynamic properties of the refrigerant R-134a are compared: the linear interpolation from tabulated data, the use of polynomial fitted curves and the use of functions derived from the Helmholtz free energy.
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Food industry in Finland has a long tradition and the new trends and the future of Finnish food industry is going towards functional and healthy food for the consumers in and outside Finland. Small companies operating in this industry face many difficulties in trying to compete and expand to new markets, that is why these companies are the key of innovation and they have done many breakthroughs in the food industry as well. It is therefore important to understand the internationalization process these companies follow and entry strategies they use, and moreover how they use their limited resources in order to be successful in international markets. This thesis via a case study approach deals with the issue of internationalization of SMEs and Finnish food industry. This study supports earlier theories of internationalization, primarily the Uppsala model and acknowledges internationalization as an incremental process. Meaning that psychic distance is indeed the major barrier of internationalization, and acquisition of international knowledge requires significant amount of time which influences the level of resource-commitment in foreign markets. It follows that due to the risks involved in foreign markets, the least resource-intensive modes of market entry such as direct and indirect exports are generally preferred at the start of internationalization process. As of what explains the non-conventional rapid internationalization process, we conclude that in an internationalized industry and country with established trade flows like Finland, the context in which firms operate may be less significant than the varying level of entrepreneurial skills and confidence present therein.
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This thesis describes work related to the in-depth characterization of the phenolic compounds of silver birch (Betula pendula) inner bark. Phenolic compounds are the most ubiquitous class of plant secondary compounds. The unifying feature of this structurally diverse group is an aromatic ring containing at least one hydroxyl group. Due to the structural diversity, phenolics have various roles in the plant defense against biotic and abiotic stresses. In addition, they can confer several health-promoting properties to humans. Furthermore, the structural diversity of this class of compounds causes challenges for their analysis. The study species in the present work, silver birch, is economically the most important hard wood species in northern Europe. Its inner bark contains a high level of phenolic compounds and it has shown one of the strongest antioxidant activities among 92 Finnish plant materials. The literature review surveys the diversity and organ specific distribution of phenolic compounds in silver birch as well as the proposed ecological functions of phenolic compounds in nature. In addition, the basis for the characterization of phenolics by mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR), and circular dichroism spectroscopy (CD) are reviewed. The objective of the experimental work was to extract, purify, characterize, and quantify the inner bark phenolic compounds. Overall 36 compounds were characterized by MS and ultraviolet spectroscopy (UV). 24 compounds were isolated and their structures confirmed by NMR and CD spectroscopy. Five novel natural compounds were identified. Special emphasis was placed on the establishment of a method for the characterization of proanthocyanidins (PAs). Hydrophilic interaction liquid chromatography (HILIC) was utilized because of its high resolution power and predictable elution order of oligomeric and polymeric PAs according to an increasing degree of polymerization. The combination of HILIC and high-resolution MS detection allowed the identification of procyanidin (PC) polymers up to the degree of polymerization of 22. In addition, a series of oligomeric and polymeric PC monoxylosides were observed for the first time in nature. Season and genotype influenced the quantities of the main inner bark phenolics, yet qualitative differences were not observed. However, manual wounding of the inner bark induced the production of ellagitannins (ETs) in the wounded tissues, i.e. callus. Since ETs were not detected in the intact inner bark, this finding may reflect the capacity of silver birch to exploit ellagitannins in its defense.
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Real option valuation, in particular the fuzzy pay-off method, has proven to be useful in defining risk and visualizing imprecision of investments in various industry applications. This study examines whether the evaluation of risk and profitability for public real estate investments can be improved by using real option methodology. Firstly, the context of real option valuation in the real estate industry is examined. Further, an empirical case study is performed on 30 real estate investments of a Finnish government enterprise in order to determine whether the presently used investment analysis system can be complemented by the pay-off method. Despite challenges in the application of the pay-off method to the case company’s large investment base, real option valuation is found to create additional value and facilitate more robust risk analysis in public real estate applications.
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Large volumes of plasma can be fractionated by the method of Cohn at low cost. However, liquid chromatography is superior in terms of the quality of the product obtained. In order to combine the advantages of each method, we developed an integrated method for the production of human albumin and immunoglobulin G (IgG). The cryoprecipitate was first removed from plasma for the production of factor VIII and the supernatant of the cryoprecipitate was fractionated by the method of Cohn. The first precipitate, containing fractions (F)-I + II + III, was used for the production of IgG by the chromatographic method (see Tanaka K et al. (1998) Brazilian Journal of Medical and Biological Research, 31: 1375-1381). The supernatant of F-I + II + III was submitted to a second precipitation and F-IV was obtained and discarded. Albumin was obtained from the supernatant of the precipitate F-IV by liquid chromatography, ion-exchange on DEAE-Sepharose FF, filtration through Sephacryl S-200 HR and introduction of heat treatment for fatty acid precipitation. Viral inactivation was performed by pasteurization at 60ºC for 10 h. The albumin product obtained by the proposed procedure was more than 99% pure for the 15 lots of albumin produced, with a mean yield of 25.0 ± 0.5 g/l plasma, containing 99.0 to 99.3% monomer, 0.7 to 1.0% dimers, and no polymers. Prekallikrein activator levels were <=5 IU/ml. This product satisfies the requirements of the 1997 Pharmacopée Européenne.
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The purpose of this thesis is to investigate whether different private equity fund characteristics have any influence on the fund performance. Fund characteristics include fund type (venture capital or buyouts), fund size (sizes of funds are divided into six ranges), fund investment industry, fund sequence (first fund or follow-on fund) and investment market (US or EMEA). Fund performance is measured by internal rate of return, and tested by cross-sectional regression analysis with the method of Ordinary Least Squares. The data employs performance and characteristics of 997 private equity funds between 1985 and 2008. Our findings are that fund type has effect on fund performance. The average IRR of venture capital funds is 2.7% less than average IRR of buyout funds. However, We did not find any relationship between fund size and performance, and between fund sequence and performance. Funds based on US market perform better than funds based on EMEA market. The fund performance differs across different industries. The average IRRs of industrial/energy industry, consumer related industry, communications and media industry and medical/health industry are higher than the average IRR of other industries.
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Cement industry significantly associated with high greenhouse gas (GHG) emissions. Considering the environmental impact, particularly global warming potential, it is important to reduce these emissions to air. The aim of the study is to investigate the mitigation possibility of GHG emissions in Ethiopian cement industry. Life cycle assessment (LCA) method used to identify and quantify GHG emissions during one ton of ordinary portland cement (OPC) production. Three mitigation scenarios: alternative fuel use, clinker substitution and thermal energy efficiency were applied on a representative gate-to-gate flow model developed with GaBi 6 software. The results of the study indicate that clinker substitution and alternative fuel use play a great role for GHG emissions mitigation with affordable cost. Applying most energy efficient kiln technology, which in turn reduces the amount of thermal energy use, has the least GHG emissions reduction intensity and high implementation cost comparing to the other scenarios. It was found that the cumulative GHG emissions mitigation potential along with other selected mitigation scenarios can be at least 48.9% per ton of cement production.
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In Brazil, scientific research is carried out mainly at universities, where professors coordinate research projects with the active participation of undergraduate and graduate students. However, there is no formal program for the teaching/learning of the scientific method. The objective of the present study was to evaluate the comprehension of the scientific method by students of health sciences who participate in scientific projects in an academic research laboratory. An observational descriptive cross-sectional study was conducted using Edgar Morin complexity as theoretical reference. In a semi-structured interview, students were asked to solve an abstract logical puzzle - TanGram. The collected data were analyzed using the hermeneutic-dialectic analysis method proposed by Minayo and discussed in terms of the theoretical reference of complexity. The students’ concept of the scientific method is limited to participation in projects, stressing the execution of practical procedures as opposed to scientific thinking. The solving of the TanGram puzzle revealed that the students had difficulties in understanding questions and activities focused on subjects and their processes. Objective answers, even when dealing with personal issues, were also reflected on the students’ opinions about the characteristics of a successful researcher. Students’ difficulties concerning these issues may affect their scientific performance and result in poorly designed experiments. This is a preliminary study that should be extended to other centers of scientific research.
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The aim of this study was to contribute to the current knowledge-based theory by focusing on a research gap that exists in the empirically proven determination of the simultaneous but differentiable effects of intellectual capital (IC) assets and knowledge management (KM) practices on organisational performance (OP). The analysis was built on the past research and theoreticised interactions between the latent constructs specified using the survey-based items that were measured from a sample of Finnish companies for IC and KM and the dependent construct for OP determined using information available from financial databases. Two widely used and commonly recommended measures in the literature on management science, i.e. the return on total assets (ROA) and the return on equity (ROE), were calculated for OP. Thus the investigation of the relationship between IC and KM impacting OP in relation to the hypotheses founded was possible to conduct using objectively derived performance indicators. Using financial OP measures also strengthened the dynamic features of data needed in analysing simultaneous and causal dependences between the modelled constructs specified using structural path models. The estimates were obtained for the parameters of structural path models using a partial least squares-based regression estimator. Results showed that the path dependencies between IC and OP or KM and OP were always insignificant when analysed separate to any other interactions or indirect effects caused by simultaneous modelling and regardless of the OP measure used that was either ROA or ROE. The dependency between the constructs for KM and IC appeared to be very strong and was always significant when modelled simultaneously with other possible interactions between the constructs and using either ROA or ROE to define OP. This study, however, did not find statistically unambiguous evidence for proving the hypothesised causal mediation effects suggesting, for instance, that the effects of KM practices on OP are mediated by the IC assets. Due to the fact that some indication about the fluctuations of causal effects was assessed, it was concluded that further studies are needed for verifying the fundamental and likely hidden causal effects between the constructs of interest. Therefore, it was also recommended that complementary modelling and data processing measures be conducted for elucidating whether the mediation effects occur between IC, KM and OP, the verification of which requires further investigations of measured items and can be build on the findings of this study.
Resumo:
This thesis concerns the analysis of epidemic models. We adopt the Bayesian paradigm and develop suitable Markov Chain Monte Carlo (MCMC) algorithms. This is done by considering an Ebola outbreak in the Democratic Republic of Congo, former Zaïre, 1995 as a case of SEIR epidemic models. We model the Ebola epidemic deterministically using ODEs and stochastically through SDEs to take into account a possible bias in each compartment. Since the model has unknown parameters, we use different methods to estimate them such as least squares, maximum likelihood and MCMC. The motivation behind choosing MCMC over other existing methods in this thesis is that it has the ability to tackle complicated nonlinear problems with large number of parameters. First, in a deterministic Ebola model, we compute the likelihood function by sum of square of residuals method and estimate parameters using the LSQ and MCMC methods. We sample parameters and then use them to calculate the basic reproduction number and to study the disease-free equilibrium. From the sampled chain from the posterior, we test the convergence diagnostic and confirm the viability of the model. The results show that the Ebola model fits the observed onset data with high precision, and all the unknown model parameters are well identified. Second, we convert the ODE model into a SDE Ebola model. We compute the likelihood function using extended Kalman filter (EKF) and estimate parameters again. The motivation of using the SDE formulation here is to consider the impact of modelling errors. Moreover, the EKF approach allows us to formulate a filtered likelihood for the parameters of such a stochastic model. We use the MCMC procedure to attain the posterior distributions of the parameters of the SDE Ebola model drift and diffusion parts. In this thesis, we analyse two cases: (1) the model error covariance matrix of the dynamic noise is close to zero , i.e. only small stochasticity added into the model. The results are then similar to the ones got from deterministic Ebola model, even if methods of computing the likelihood function are different (2) the model error covariance matrix is different from zero, i.e. a considerable stochasticity is introduced into the Ebola model. This accounts for the situation where we would know that the model is not exact. As a results, we obtain parameter posteriors with larger variances. Consequently, the model predictions then show larger uncertainties, in accordance with the assumption of an incomplete model.