904 resultados para Multi-sector models


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In the power market, electricity prices play an important role at the economic level. The behavior of a price trend usually known as a structural break may change over time in terms of its mean value, its volatility, or it may change for a period of time before reverting back to its original behavior or switching to another style of behavior, and the latter is typically termed a regime shift or regime switch. Our task in this thesis is to develop an electricity price time series model that captures fat tailed distributions which can explain this behavior and analyze it for better understanding. For NordPool data used, the obtained Markov Regime-Switching model operates on two regimes: regular and non-regular. Three criteria have been considered price difference criterion, capacity/flow difference criterion and spikes in Finland criterion. The suitability of GARCH modeling to simulate multi-regime modeling is also studied.

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This thesis studies cash and short term investments to net assets ratio of Finnish industrial companies during financial crisis, and how different firm specific and macro economical variables affect cash and short term investments. The data consists of quarter level interim reports. Regression analysis was used to find out the effects of different variables. Regression models were formed based on previous studies on cash holdings. It was found that firms studied held more cash during financial crisis than before it. Cash and short-term investments acted as substitute of net working capital. Leverage had a positive and significant relationship to cash and short term investment ratio. It was also found out that firms have a target cash and short term investments ratio.

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The purpose of this dissertation is to examine the dynamics of the socio-technical system in the field of ageing. The study stems from the notion that the ageing of the population as a powerful megatrend has wide societal effects, and is not just a matter for the social and health sector. The central topic in the study is change: not only the age structures and structures of society are changing, but also at the same time there is constant development, for instance, in technologies, infrastructures and cultural perceptions. The changing concept of innovation has widened the understanding of innovations related to ageing from medical and assistive technological innovations to service and social innovations, as well as systemic innovations at different levels, which means the intertwined and co-evolutionary change in technologies, structures, services and thinking models. By the same token, the perceptions of older people and old age are becoming more multi-faceted: old age is no longer equated to illnesses and decline, but visions of active ageing and a third age have emerged, which are framed by choices, opportunities, resources and consumption in later life. The research task in this study is to open up the processes and mechanisms of change in the field of ageing, which are studied as a complex, multi-level and interrelated socio-technical system. The question is about co-effective elements consisting of macro-level landscape changes, the existing socio-technical regime (the rule system, practices and structures) and bottom-up niche-innovations. Societal transitions do not account for the things inside the regime alone, or for the long-term changes in the landscape, nor for the radical innovations, but for the interplay between all these levels. The research problem is studied through five research articles, which offer micro-level case studies to macro-level phenomenon. Each of the articles focus on different aspects related to ageing and change, and utilise various datasets. The framework of this study leans on the studies of socio-technical systems and multi-level perspective on transitions mainly developed by Frank Geels. Essential factors in transition from one socio-technological regime to another are the co-evolutionary processes between landscape changes, regime level and experimental niches. Landscape level changes, like the ageing of the population, destabilise the regime in the forms of coming pressures. This destabilization offers windows for opportunity to niche-innovations outside or at fringe of the regime, which, through their breakthrough, accelerate the transition process. However, the change is not easy because of various kinds of lock-ins and inertia, which tend to maintain the stability of the regime. In this dissertation, a constructionist approach of society is applied leaning mainly to the ideas of Anthony Giddens’ theory of structuration, with the dual nature of structures. The change is taking place in the interplay between actors and structures: structures shape people’s practices, but at the same time these practices constitute and reproduce social systems. Technology and other material aspects, as part of socio-technical systems, and the use of them, also take part in the structuration process. The findings of the study point out that co-evolutionary and co-effective relationships between economic, cultural, technological and institutional fields, as well as relationships between landscape changes, changes in the local and regime-level practices and rule systems, are a very complex and multi-level dynamic socio-technical phenomenon. At the landscape level of ageing, which creates the pressures and triggers to the regime change, there are three remarkable megatrends: demographic change, changes in the global economy and the development of technologies. These exert pressures to the socio-technical regime, which as a rule system is experiencing changes in the form of new markets and consumer habits, new ways of perceiving ageing, new models of organising the health care and other services and as new ways of considering innovation and innovativeness. There are also inner dynamics in the relationships between these aspects within the regime. These are interrelated and coconstructed: the prevailing perceptions of ageing and innovation, for instance, reflect the ageing policies, innovation policies, societal structures, organising models, technology and scientific discussion, and vice versa. Technology is part of the inner dynamics of the sociotechnological regime. Physical properties of the artefacts set limitations and opportunities with regard to their functions and uses. The use of and discussion about technology, contributes producing and reproducing the perceptions of old age. For societal transition, micro-level changes are also needed, in form of niche-innovations, for instance new services, organisational models or new technologies, Regimes, as stabilitystriven systems, tend to generate incremental innovations, but radically new innovations are generated in experimental niches protected from ‘normal’ market selection. The windows of opportunity for radical novelties may be opened if the circumstances are favourable for instance by tensions in the socio-technical regime affected by landscape level changes. This dissertation indicates that a change is taking place, firstly, in the dynamic interactionbetween levels, as a result of purposive action and governance to some extent. Breaking the inertia and using the window of opportunity for change and innovation offered by dynamics between levels, presupposes the actors’ special capabilities and actions such as dynamic capabilities and distance management. Secondly, the change is taking place the socio-technological negotiations inside the regime: interaction between technological and social, which is embodied in the use of technology. The use of technology includes small-level contextual scripts that also participate in forming broader societal scripts (for instance defining old age at the society level), which in their turn affect the formation of policies for innovation and ageing. Thirdly, the change is taking place by the means of active formation of the multi-actor innovation networks, where the role of distance management is crucial to facilitate the communication between actors coming from different backgrounds as well as to help the niches born outside the regime to utilise the window of opportunity offered by regime destabilisation. This dissertation has both theoretical and practical contributions. This study participates in the discussion of action-oriented view on transition by opening up of the socio-technological, coevolutionary processes of the multi-faceted phenomenon of ageing, which has lacked systematic analyses. The focus of this study, however, is not on the large-scale coordination and governance, but rather on opening up the incremental elements and structuration processes, which contribute to the transition little by little, and which can be affected to. This increases the practical importance of this dissertation, by highlighting the importance of very tiny, everyday elements in the change processes in the long run.

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Preference relations, and their modeling, have played a crucial role in both social sciences and applied mathematics. A special category of preference relations is represented by cardinal preference relations, which are nothing other than relations which can also take into account the degree of relation. Preference relations play a pivotal role in most of multi criteria decision making methods and in the operational research. This thesis aims at showing some recent advances in their methodology. Actually, there are a number of open issues in this field and the contributions presented in this thesis can be grouped accordingly. The first issue regards the estimation of a weight vector given a preference relation. A new and efficient algorithm for estimating the priority vector of a reciprocal relation, i.e. a special type of preference relation, is going to be presented. The same section contains the proof that twenty methods already proposed in literature lead to unsatisfactory results as they employ a conflicting constraint in their optimization model. The second area of interest concerns consistency evaluation and it is possibly the kernel of the thesis. This thesis contains the proofs that some indices are equivalent and that therefore, some seemingly different formulae, end up leading to the very same result. Moreover, some numerical simulations are presented. The section ends with some consideration of a new method for fairly evaluating consistency. The third matter regards incomplete relations and how to estimate missing comparisons. This section reports a numerical study of the methods already proposed in literature and analyzes their behavior in different situations. The fourth, and last, topic, proposes a way to deal with group decision making by means of connecting preference relations with social network analysis.

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Academic research on services and innovations on services has significantly grown during recent years. So far research concerning management of knowledge intensive work on service development activities is very limited. The objective of this study was to examine knowledge integration practices that support service innovation development and to the best of knowledge such studies have not been previously published in academic literature. In the theoretical part of the study a review of state‐of‐the‐art literature was conducted, research gap was indicated and a framework for analysis was built. In the empirical part an explorative comparative multi‐case study was carried out in KIBS sector. Four companies were selected and four service development projects were inspected. The service development activities and knowledge integration practices were identified. The cases were carefully compared and results formed. The empirical results indicated that service innovation development is partly linear and partly incremental flow of activities where knowledge integration practices have important role supporting the planning and execution of tasks. Knowledge integration practices supporting planning and workshops are close interaction, interpretation, project planning and sequencing of work tasks. The identified knowledge integration practices supporting building service solution were careful role and competence management, routines and common knowledge. The main implication is that to manage knowledge intensive service innovation development a firm should carefully develop and choose relevant knowledge integration practices to support the service development activities.

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The objective of this thesis was to examine the potential of multi-axis solutions in packaging machines produced in Europe. The definition of a multi-axis solution in this study is a construction that uses a common DC bus power supply for different amplifiers running the axes and the intelligence is centralized into one unit. The cost structure of a packaging machine was gained from an automation research, which divided the machines according to automation categories. The automation categories were then further divided into different sub-components by evaluating the ratio of multi-axis solutions compared to other automation components in packaging machines. A global motion control study was used for further information. With the help of the ratio, an estimation of the potential of multi-axis solutions in each country and packaging machine sector was completed. In addition to the research, a specific questionnaire was sent to five companies to gain information about the present situation and possible trends in packaging machinery. The greatest potential markets are in Germany and Italy, which are also the largest producers of packaging machinery in Europe. The greatest growth in the next few years will be seen in Turkey where the annual growth rate equals the general machinery production rate in Asia. The greatest market potential of the Nordic countries is found in Sweden in 35th position on the list. According to the interviews, motion control products in packaging machines will retain their current power levels, as well as the number of axes in the future. Integrated machine safety features together with a universal programming language are the desired attributes of the future. Unlike generally in industry, the energy saving objectives are and will remain insignificant in the packaging industry.

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Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

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Nanotubes are one of the most perspective materials in modern nanotechologies. It makes present investigation very actual. In this work magnetic properties of multi-walled nanotubes on polystyrene substrate are investigated by using quantum magnetometer SQUID. Main purpose was to obtain magnetic field and temperature dependences of magnetization and to compare them to existing theoretical models of magnetism in carbon-bases structures. During data analysis a mathematical algorithm for obtained data filtration was developed because measurement with quantum magnetometer assume big missives of number data, which contain accidental errors. Nature of errors is drift of SQUID signal, errors of different parts of measurement station. Nanotube samples on polystyrene substrate were studied with help of atomic force microscope. On the surface traces of nanotube were found contours, which were oriented in horizontal plane. This feature was caused by rolling method for samples. Detailed comparison of obtained dependences with information of other researches on this topic allows to obtain some conclusions about nature of magnetism in the samples. It emphasizes importance and actuality of this scientific work.

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The freezing times of fruit pulp models packed and conditioned in multi-layered boxes were evaluated under conditions similar to those employed commercially. Estimating the freezing time is a difficult practice due to the presence of significant voids in the boxes, whose influence may be analyzed by means of various methods. In this study, a procedure for estimating freezing time by using the models described in the literature was compared with experimental measurements by collecting time/temperature data. The following results show that the airflow through packages is a significant parameter for freezing time estimation. When the presence of preferential channels was considered, the predicted freezing time in the models could be 10% lower than the experimental values, depending on the method. The isotherms traced as a function of the location of the samples inside the boxes showed the displacement of the thermal center in relation to the geometric center of the product.

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Crystal properties, product quality and particle size are determined by the operating conditions in the crystallization process. Thus, in order to obtain desired end-products, the crystallization process should be effectively controlled based on reliable kinetic information, which can be provided by powerful analytical tools such as Raman spectrometry and thermal analysis. The present research work studied various crystallization processes such as reactive crystallization, precipitation with anti-solvent and evaporation crystallization. The goal of the work was to understand more comprehensively the fundamentals, phenomena and utilizations of crystallization, and establish proper methods to control particle size distribution, especially for three phase gas-liquid-solid crystallization systems. As a part of the solid-liquid equilibrium studies in this work, prediction of KCl solubility in a MgCl2-KCl-H2O system was studied theoretically. Additionally, a solubility prediction model by Pitzer thermodynamic model was investigated based on solubility measurements of potassium dihydrogen phosphate with the presence of non-electronic organic substances in aqueous solutions. The prediction model helps to extend literature data and offers an easy and economical way to choose solvent for anti-solvent precipitation. Using experimental and modern analytical methods, precipitation kinetics and mass transfer in reactive crystallization of magnesium carbonate hydrates with magnesium hydroxide slurry and CO2 gas were systematically investigated. The obtained results gave deeper insight into gas-liquid-solid interactions and the mechanisms of this heterogeneous crystallization process. The research approach developed can provide theoretical guidance and act as a useful reference to promote development of gas-liquid reactive crystallization. Gas-liquid mass transfer of absorption in the presence of solid particles in a stirred tank was investigated in order to gain understanding of how different-sized particles interact with gas bubbles. Based on obtained volumetric mass transfer coefficient values, it was found that the influence of the presence of small particles on gas-liquid mass transfer cannot be ignored since there are interactions between bubbles and particles. Raman spectrometry was successfully applied for liquid and solids analysis in semi-batch anti-solvent precipitation and evaporation crystallization. Real-time information such as supersaturation, formation of precipitates and identification of crystal polymorphs could be obtained by Raman spectrometry. The solubility prediction models, monitoring methods for precipitation and empirical model for absorption developed in this study together with the methodologies used gives valuable information for aspects of industrial crystallization. Furthermore, Raman analysis was seen to be a potential controlling method for various crystallization processes.

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This thesis addresses the coolability of porous debris beds in the context of severe accident management of nuclear power reactors. In a hypothetical severe accident at a Nordic-type boiling water reactor, the lower drywell of the containment is flooded, for the purpose of cooling the core melt discharged from the reactor pressure vessel in a water pool. The melt is fragmented and solidified in the pool, ultimately forming a porous debris bed that generates decay heat. The properties of the bed determine the limiting value for the heat flux that can be removed from the debris to the surrounding water without the risk of re-melting. The coolability of porous debris beds has been investigated experimentally by measuring the dryout power in electrically heated test beds that have different geometries. The geometries represent the debris bed shapes that may form in an accident scenario. The focus is especially on heap-like, realistic geometries which facilitate the multi-dimensional infiltration (flooding) of coolant into the bed. Spherical and irregular particles have been used to simulate the debris. The experiments have been modeled using 2D and 3D simulation codes applicable to fluid flow and heat transfer in porous media. Based on the experimental and simulation results, an interpretation of the dryout behavior in complex debris bed geometries is presented, and the validity of the codes and models for dryout predictions is evaluated. According to the experimental and simulation results, the coolability of the debris bed depends on both the flooding mode and the height of the bed. In the experiments, it was found that multi-dimensional flooding increases the dryout heat flux and coolability in a heap-shaped debris bed by 47–58% compared to the dryout heat flux of a classical, top-flooded bed of the same height. However, heap-like beds are higher than flat, top-flooded beds, which results in the formation of larger steam flux at the top of the bed. This counteracts the effect of the multi-dimensional flooding. Based on the measured dryout heat fluxes, the maximum height of a heap-like bed can only be about 1.5 times the height of a top-flooded, cylindrical bed in order to preserve the direct benefit from the multi-dimensional flooding. In addition, studies were conducted to evaluate the hydrodynamically representative effective particle diameter, which is applied in simulation models to describe debris beds that consist of irregular particles with considerable size variation. The results suggest that the effective diameter is small, closest to the mean diameter based on the number or length of particles.

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Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.

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In the scope of the current thesis we review and analyse networks that are formed by nodes with several attributes. We suppose that different layers of communities are embedded in such networks, besides each of the layers is connected with nodes' attributes. For example, examine one of a variety of online social networks: an user participates in a plurality of different groups/communities – schoolfellows, colleagues, clients, etc. We introduce a detection algorithm for the above-mentioned communities. Normally the result of the detection is the community supplemented just by the most dominant attribute, disregarding others. We propose an algorithm that bypasses dominant communities and detects communities which are formed by other nodes' attributes. We also review formation models of the attributed networks and present a Human Communication Network (HCN) model. We introduce a High School Texting Network (HSTN) and examine our methods for that network.

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This article studies mobility patterns of German workers in light of a model of sector-specific human capital. Furthermore, I employ and describe little-used data on continuous on-the-job training occurring after apprenticeships. Results are presented describing the incidence and duration of continuous training. Continuous training is quite common, despite the high incidence of apprenticeships which precedes this part of a worker's career. Most previous studies have only distinguished between firm-specific and general human capital, usually concluding that training was general. Inconsistent with those conclusions, I show that German men are more likely to find a job within the same sector if they have received continuous training in that sector. These results are similar to those obtained for young U.S. workers, and suggest that sector-specific capital is an important feature of very different labor markets. In addition, they suggest that the observed effect of training on mobility is sensible to the state of the business cycle, indicating a more complex interaction between supply and demand that most theoretical models allow for.

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Using data from the National Longitudinal Survey of Youth (NLSY), we re-examine the effect of formal on-the-job training on mobility patterns of young American workers. By employing parametric duration models, we evaluate the economic impact of training on productive time with an employer. Confirming previous studies, we find a positive and statistically significant impact of formal on-the-job training on tenure with the employer providing the training. However, the expected net duration of the time spent in the training program is generally not significantly increased. We proceed to document and analyze intra-sectoral and cross-sectoral mobility patterns in order to infer whether training provides firm-specific, industry-specific, or general human capital. The econometric analysis rejects a sequential model of job separation in favor of a competing risks specification. We find significant evidence for the industry-specificity of training. The probability of sectoral mobility upon job separation decreases with training received in the current industry, whether with the last employer or previous employers, and employment attachment increases with on-the-job training. These results are robust to a number of variations on the base model.