26 resultados para Neighborhood space


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Biofuels for transport are a renewable source of energy that were once heralded as a solution to multiple problems associated with poor urban air quality, the overproduction of agricultural commodities, the energy security of the European Union (EU) and climate change. It was only after the Union had implemented an incentivizing framework of legal and political instruments for the production, trade and consumption of biofuels that the problems of weakening food security, environmental degradation and increasing greenhouse gases through land-use changes began to unfold. In other words, the difference between political aims for why biofuels are promoted and their consequences has grown – which is also recognized by the EU policy-makers. Therefore, the global networks of producing, trading and consuming biofuels may face a complete restructure if the European Commission accomplishes its pursuit to sideline crop-based biofuels after 2020. My aim with this dissertation is not only to trace the manifold evolutions of the instruments used by the Union to govern biofuels but also to reveal how this evolution has influenced the dynamics of biofuel development. Therefore, I study the ways the EU’s legal and political instruments of steering biofuels are coconstitutive with the globalized spaces of biofuel development. My analytical strategy can be outlined through three concepts. I use the term ‘assemblage’ to approach the operations of the loose entity of actors and non-human elements that are the constituents of multi-scalar and -sectorial biofuel development. ‘Topology’ refers to the spatiality of this European biofuel assemblage and its parts whose evolving relations are treated as the active constituents of space, instead of simply being located in space. I apply the concept of ‘nomosphere’ to characterize the framework of policies, laws and other instruments that the EU applies and construes while attempting to govern biofuels. Even though both the materials and methods vary in the independent articles, these three concepts characterize my analytical strategy that allows me to study law, policy and space associated with each other. The results of my examinations underscore the importance of the instruments of governance of the EU constituting and stabilizing the spaces of producing and, on the other hand, how topological ruptures in biofuel development have enforced the need to reform policies. This analysis maps the vast scope of actors that are influenced by the mechanism of EU biofuel governance and, what is more, shows how they are actively engaging in the Union’s institutional policy formulation. By examining the consequences of fast biofuel development that are spatially dislocated from the established spaces of producing, trading and consuming biofuels such as indirect land use changes, I unfold the processes not tackled by the instruments of the EU. Indeed, it is these spatially dislocated processes that have pushed the Commission construing a new type of governing biofuels: transferring the instruments of climate change mitigation to land-use policies. Although efficient in mitigating these dislocated consequences, these instruments have also created peculiar ontological scaffolding for governing biofuels. According to this mode of governance, the spatiality of biofuel development appears to be already determined and the agency that could dampen the negative consequences originating from land-use practices is treated as irrelevant.

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This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

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Almost every problem of design, planning and management in the technical and organizational systems has several conflicting goals or interests. Nowadays, multicriteria decision models represent a rapidly developing area of operation research. While solving practical optimization problems, it is necessary to take into account various kinds of uncertainty due to lack of data, inadequacy of mathematical models to real-time processes, calculation errors, etc. In practice, this uncertainty usually leads to undesirable outcomes where the solutions are very sensitive to any changes in the input parameters. An example is the investment managing. Stability analysis of multicriteria discrete optimization problems investigates how the found solutions behave in response to changes in the initial data (input parameters). This thesis is devoted to the stability analysis in the problem of selecting investment project portfolios, which are optimized by considering different types of risk and efficiency of the investment projects. The stability analysis is carried out in two approaches: qualitative and quantitative. The qualitative approach describes the behavior of solutions in conditions with small perturbations in the initial data. The stability of solutions is defined in terms of existence a neighborhood in the initial data space. Any perturbed problem from this neighborhood has stability with respect to the set of efficient solutions of the initial problem. The other approach in the stability analysis studies quantitative measures such as stability radius. This approach gives information about the limits of perturbations in the input parameters, which do not lead to changes in the set of efficient solutions. In present thesis several results were obtained including attainable bounds for the stability radii of Pareto optimal and lexicographically optimal portfolios of the investment problem with Savage's, Wald's criteria and criteria of extreme optimism. In addition, special classes of the problem when the stability radii are expressed by the formulae were indicated. Investigations were completed using different combinations of Chebyshev's, Manhattan and Hölder's metrics, which allowed monitoring input parameters perturbations differently.

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This guide summarizes useful information about the European Space Agency (ESA), the European space industry, the ECSS standards and product assurance for small and medium enterprises that are aiming to enter the industry. Additionally, the applicability of agile development in space projects is discussed.

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Product assurance is an essential part of product development process if developers want to ensure that final product is safe and reliable. Product assurance can be supported withrisk management and with different failure analysis methods. Product assurance is emphasized in system development process of mission critical systems. The product assurance process in systems of this kind requires extra attention. Inthis thesis, mission critical systems are space systems and the product assurance processof these systems is presented with help of space standards. The product assurance process can be supported with agile development because agile emphasizes transparency of the process and fast response to changes. Even if the development process of space systems is highly standardized and reminds waterfall model, it is still possible to adapt agile development in space systems development. This thesisaims to support the product assurance process of space systems with agile developmentso that the final product would be as safe and reliable as possible. The main purpose of this thesis is to examine how well product assurance is performed in Finnish space organizations and how product assurance tasks and activities can besupported with agile development. The research part of this thesis is performed in survey form.

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Product assurance is an essential part of product development process if developers want to ensure that final product is safe and reliable. Product assurance can be supported with risk management and with different failure analysis methods. Product assurance is emphasized in system development process of mission critical systems. The product assurance process in systems of this kind requires extra attention. In this thesis, mission critical systems are space systems and the product assurance process of these systems is presented with help of space standards. The product assurance process can be supported with agile development because agile emphasizes transparency of the process and fast response to changes. Even if the development process of space systems is highly standardized and reminds waterfall model, it is still possible to adapt agile development in space systems development. This thesis aims to support the product assurance process of space systems with agile development so that the final product would be as safe and reliable as possible. The main purpose of this thesis is to examine how well product assurance is performed in Finnish space organizations and how product assurance tasks and activities can be supported with agile development. The research part of this thesis is performed in survey form.

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Various researches in the field of econophysics has shown that fluid flow have analogous phenomena in financial market behavior, the typical parallelism being delivered between energy in fluids and information on markets. However, the geometry of the manifold on which market dynamics act out their dynamics (corporate space) is not yet known. In this thesis, utilizing a Seven year time series of prices of stocks used to compute S&P500 index on the New York Stock Exchange, we have created local chart to the corporate space with the goal of finding standing waves and other soliton like patterns in the behavior of stock price deviations from the S&P500 index. By first calculating the correlation matrix of normalized stock price deviations from the S&P500 index, we have performed a local singular value decomposition over a set of four different time windows as guides to the nature of patterns that may emerge. I turns out that in almost all cases, each singular vector is essentially determined by relatively small set of companies with big positive or negative weights on that singular vector. Over particular time windows, sometimes these weights are strongly correlated with at least one industrial sector and certain sectors are more prone to fast dynamics whereas others have longer standing waves.

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Health Innovation Village at GE is one of the new communities targeted for startup and growth-oriented companies. It has been established at the premises of a multinational conglomerate that will promote networking and growth of startup companies. The concept combines features from traditional business incubators, accelerators, and coworking spaces. This research compares Health Innovation Village to these concepts regarding its goals, target clients, source of income, organization, facilities, management, and success factors. In addition, a new incubator classification model is introduced. On the other hand, Health Innovation Village is examined from its tenants’ perspective and improvements are suggested. The work was implemented as a qualitative case study by interviewing GE staff with connections to Health Innovation Village as well as startup entrepreneurs and employees’ working there. The most evident features of Health Innovation Village correspond to those of business incubators although it is atypical as a non-profit corporate business incubator. Strong network orientation and connections to venture capitalists are common characteristics of these new types of accelerators. The design of the premises conforms to the principles of coworking spaces, but the services provided to the startup companies are considerably more versatile than the services offered by coworking spaces. The advantages of Health Innovation Village are that there are first-class premises and exceptionally good networking possibilities that other types of incubators or accelerators are not able to offer. A conglomerate can also provide multifaceted special knowledge for young firms. In addition, both GE and the startups gained considerable publicity through their cooperation, indeed a characteristic that benefits both parties. Most of the expectations of the entrepreneurs were exceeded. However, communication and the scope of cooperation remain challenges. Micro companies spend their time developing and marketing their products and acquiring financing. Therefore, communication should be as clear as possible and accessible everywhere. The startups would prefer to cooperate significantly more, but few have the time available to assume the responsibility of leadership. The entrepreneurs also expected to have more possibilities for cooperation with GE. Wider collaboration might be accomplished by curation in the same way as it is used in the well-functioning coworking spaces where curators take care of practicalities and promote cooperation. Communication issues could be alleviated if the community had its own Intranet pages where all information could be concentrated. In particular, a common calendar and a room reservation system could be useful. In addition, it could be beneficial to have a section of the Intranet open for both the GE staff and the startups so that those willing to share their knowledge and those having project offers could use it for advertising.