940 resultados para Complex network. Optimal path. Optimal path cracks


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The energy reform, which is happening all over the world, is caused by the common concern of the future of the humankind in our shared planet. In order to keep the effects of the global warming inside of a certain limit, the use of fossil fuels must be reduced. The marginal costs of the renewable sources, RES are quite high, since they are new technology. In order to induce the implementation of RES to the power grid and lower the marginal costs, subsidies were developed in order to make the use of RES more profitable. From the RES perspective the current market is developed to favor conventional generation, which mainly uses fossil fuels. Intermittent generation, like wind power, is penalized in the electricity market since it is intermittent and thus diffi-cult to control. Therefore, the need of regulation and thus the regulation costs to the producer differ, depending on what kind of generation market participant owns. In this thesis it is studied if there is a way for market participant, who has wind power to use the special characteristics of electricity market Nord Pool and thus reach the gap between conventional generation and the intermittent generation only by placing bids to the market. Thus, an optimal bid is introduced, which purpose is to minimize the regulation costs and thus lower the marginal costs of wind power. In order to make real life simulations in Nord Pool, a wind power forecast model was created. The simulations were done in years 2009 and 2010 by using a real wind power data provided by Hyötytuuli, market data from Nord Pool and wind forecast data provided by Finnish Meteorological Institute. The optimal bid needs probability intervals and therefore the methodology to create probability distributions is introduced in this thesis. In the end of the thesis it is shown that the optimal bidding improves the position of wind power producer in the electricity market.

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This study investigates futures market efficiency and optimal hedge ratio estimation. First, cointegration between spot and futures prices is studied using Johansen method, with two different model specifications. If prices are found cointegrated, restrictions on cointegrating vector and adjustment coefficients are imposed, to account for unbiasedness, weak exogeneity and prediction hypothesis. Second, optimal hedge ratios are estimated using static OLS, and time-varying DVEC and CCC models. In-sample and out-of-sample results for one, two and five period ahead are reported. The futures used in thesis are RTS index, EUR/RUB exchange rate and Brent oil, traded in Futures and options on RTS.(FORTS) For in-sample period, data points were acquired from start of trading of each futures contract, RTS index from August 2005, EUR/RUB exchange rate March 2009 and Brent oil October 2008, lasting till end of May 2011. Out-of-sample period covers start of June 2011, till end of December 2011. Our results indicate that all three asset pairs, spot and futures, are cointegrated. We found RTS index futures to be unbiased predictor of spot price, mixed evidence for exchange rate, and for Brent oil futures unbiasedness was not supported. Weak exogeneity results for all pairs indicated spot price to lead in price discovery process. Prediction hypothesis, unbiasedness and weak exogeneity of futures, was rejected for all asset pairs. Variance reduction results varied between assets, in-sample in range of 40-85 percent and out-of sample in range of 40-96 percent. Differences between models were found small, except for Brent oil in which OLS clearly dominated. Out-of-sample results indicated exceptionally high variance reduction for RTS index, approximately 95 percent.

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The purpose of this thesis is twofold. The first and major part is devoted to sensitivity analysis of various discrete optimization problems while the second part addresses methods applied for calculating measures of solution stability and solving multicriteria discrete optimization problems. Despite numerous approaches to stability analysis of discrete optimization problems two major directions can be single out: quantitative and qualitative. Qualitative sensitivity analysis is conducted for multicriteria discrete optimization problems with minisum, minimax and minimin partial criteria. The main results obtained here are necessary and sufficient conditions for different stability types of optimal solutions (or a set of optimal solutions) of the considered problems. Within the framework of quantitative direction various measures of solution stability are investigated. A formula for a quantitative characteristic called stability radius is obtained for the generalized equilibrium situation invariant to changes of game parameters in the case of the H¨older metric. Quality of the problem solution can also be described in terms of robustness analysis. In this work the concepts of accuracy and robustness tolerances are presented for a strategic game with a finite number of players where initial coefficients (costs) of linear payoff functions are subject to perturbations. Investigation of stability radius also aims to devise methods for its calculation. A new metaheuristic approach is derived for calculation of stability radius of an optimal solution to the shortest path problem. The main advantage of the developed method is that it can be potentially applicable for calculating stability radii of NP-hard problems. The last chapter of the thesis focuses on deriving innovative methods based on interactive optimization approach for solving multicriteria combinatorial optimization problems. The key idea of the proposed approach is to utilize a parameterized achievement scalarizing function for solution calculation and to direct interactive procedure by changing weighting coefficients of this function. In order to illustrate the introduced ideas a decision making process is simulated for three objective median location problem. The concepts, models, and ideas collected and analyzed in this thesis create a good and relevant grounds for developing more complicated and integrated models of postoptimal analysis and solving the most computationally challenging problems related to it.

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The so-called primitive, innate or paraspecific immune system is the phylogenetically older part of the complex immune system. It enables the organism to immediately attack various foreign substances, infectious pathogens, toxins and transformed cells of the organism itself. ,,Paramunity" is defined as an optimal regulated and activated, antigen-nonspecific defence, acquired through continuous active and succesful confrontation with endogenous and exogenous noxes or by means of ,,paramunization" with so called ,,paramunity inducers". Paramunity inducers based on different pox virus species (e.g. Baypamun®, Duphapind®, Conpind) have turned out to be effective and safe when applied with human beings as well as with animals. Pox virus inducers activate phagocytosis and NK-cells in addition to regulation of various cytokines, notably interferon a and g, IL 1, 2, CSF and TNF which comprise the network of the complex paraspecific immune system. The results of experimental work as well as practical use in veterinary medicine have shown that paramunization by pox inducers goes far beyond the common understanding of so-called ,,immuno-therapy". They are ,,bioregulators", because they have 1. a regulatory effect on a disturbed immune system in the sense of an optimal homoeostasis, and 2. simultaneously a regulatory effect between the immune, nervous, circulatory and hormone system. Therefore, the use of paramunization by pox inducers opens a new way of prophylaxis and therapy, not only with regard to infections, but also with regard to different other indications.

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Potilaan hoitamisessa korostuvat mm. triagen tekeminen, potilaan voinnin seuranta ja hoitoa koskevien päätösten tekeminen nopeasti potilaan voinnin mukaan sekä potilaan jatkohoidon turvaaminen. Tämä kaksivaiheinen koulutustutkimus kohdistui päivystyshoitotyön osaamiseen. Tutkimuksen ensimmäisessä vaiheessa määriteltiin päivystyshoitotyön osaaminen ja toisessa vaiheessa arvioitiin valmistuvien sairaanhoitajaopiskelijoiden päivystyshoitotyön osaamista ja osaamiseen yhteydessä olevia tekijöitä. Osaamisen arvioinnin suorittivat opiskelijat itse ja vertailuperustana opiskelijoiden päivystyshoitotyön osaamiselle käytettiin ammatissa toimivien sairaanhoitajien päivystyshoitotyön osaamista. Tutkimuksen tavoitteena oli arvioinnin perusteella määrittää päivystyshoitotyön osaamisen nykytaso ja tehdä tarvittavat ehdotukset päivystyshoitotyön osaamisen kehittämiseen. Tutkimuksen ensimmäisessä vaiheessa (2006–2012) tiedonkeruumenetelminä oli kirjallisuuskatsaus ja asiantuntija-arviointi hyödyntäen delphi-menetelmää. Kirjallisuuskatsauksen perusteella muodostettiin päivystyshoitotyön osaamista kuvaavat pääkategoriat, yläkategoriat ja alakategoriat.Alakategoriat (n=61) annettiin asiantuntijoille (sairaanhoitajat, opettajat, ylihoitajat) arvioitavaksi.Kaksivaiheisen asiantuntija-arvioinnin perusteella muodostui 92 päivystyshoitotyön osaamista kuvaavaa alakategoriaa. Tutkimuksen toisessa vaiheessa (2007–2012) valmistuvien suomalaisten sairaanhoitaja-opiskelijoiden (N=382, n=208, vastausprosentti 55 %) päivystyshoitotyön osaamista arvioitiin tätä tutkimusta varten kehitetyllä mittarilla (Päivystyshoitotyön osaaminen -mittari). Mittari perustui tutkimuksen ensimmäisessä vaiheessa muodostettuun määrittelyyn päivystyshoitotyön osaamisesta. Osaamista mitattiin VAS-janalla (asteikko 0–100) arvon 100 ollessa optimaalinen taso, johon pyrittiin. Sairaanhoitajaopiskelijoiden tavoiteltavaksi osaamisen tasoksi asetettiin 80 olettaen opiskelijoiden osaamisen vielä kehittyvän työkokemuksen myötä. Ammatissa toimivien sairaanhoitajien (N=586, n=280, vastausprosentti 48 %) itsearvioitua osaamista käytettiin vertailuperustana opiskelijoiden osaamiselle. Aineisto analysoitiin tilastollisin menetelmin. Valmistuvien sairaanhoitajaopiskelijoiden itsearvioitu päivystyshoitotyön osaaminen oli alle tavoiteltavan osaamisen tason. Opiskelijoilla oli mielestään eniten eettistä osaamista sekä vuorovaikutus- ja yhteistyöosaamista ja vähiten päätöksenteko-osaamista ja kliinistä osaamista. Myös ammatissa toimivilla sairaanhoitajilla oli mielestään eniten vuorovaikutus- ja yhteistyöosaamista. Vähiten heillä oli ohjausosaamista ja päätöksenteko-osaamista. Sairaanhoitajilla oli tilastollisesti merkitsevästi enemmän päivystyshoitotyön osaamista kuin opiskelijoilla. Opiskelijoiden päivystyshoitotyön osaamista selitti eniten aikaisempi terveysalan tutkinto. Päivystyshoitotyön osaamisen kehittämisehdotukset kohdistuvat ammatillisen peruskoulutuksen ja täydennyskoulutuksen opetuksen sisältöihin ja määrään, opetus- ja opiskelumenetelmiin, osaamisen arviointiin sekä urasuunnitteluun. Jatkotutkimusehdotukset kohdistuvat päivystyshoitotyön osaamisen määrittelyn ja osaamista arvioivan mittarin edelleen kehittämiseen, erilaisten arviointimenetelmien kehittämiseen sekä osaamiseen yhteydessä olevien tekijöiden edelleen tutkimiseen.

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Through advances in technology, System-on-Chip design is moving towards integrating tens to hundreds of intellectual property blocks into a single chip. In such a many-core system, on-chip communication becomes a performance bottleneck for high performance designs. Network-on-Chip (NoC) has emerged as a viable solution for the communication challenges in highly complex chips. The NoC architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication challenges such as wiring complexity, communication latency, and bandwidth. Furthermore, the combined benefits of 3D IC and NoC schemes provide the possibility of designing a high performance system in a limited chip area. The major advantages of 3D NoCs are the considerable reductions in average latency and power consumption. There are several factors degrading the performance of NoCs. In this thesis, we investigate three main performance-limiting factors: network congestion, faults, and the lack of efficient multicast support. We address these issues by the means of routing algorithms. Congestion of data packets may lead to increased network latency and power consumption. Thus, we propose three different approaches for alleviating such congestion in the network. The first approach is based on measuring the congestion information in different regions of the network, distributing the information over the network, and utilizing this information when making a routing decision. The second approach employs a learning method to dynamically find the less congested routes according to the underlying traffic. The third approach is based on a fuzzy-logic technique to perform better routing decisions when traffic information of different routes is available. Faults affect performance significantly, as then packets should take longer paths in order to be routed around the faults, which in turn increases congestion around the faulty regions. We propose four methods to tolerate faults at the link and switch level by using only the shortest paths as long as such path exists. The unique characteristic among these methods is the toleration of faults while also maintaining the performance of NoCs. To the best of our knowledge, these algorithms are the first approaches to bypassing faults prior to reaching them while avoiding unnecessary misrouting of packets. Current implementations of multicast communication result in a significant performance loss for unicast traffic. This is due to the fact that the routing rules of multicast packets limit the adaptivity of unicast packets. We present an approach in which both unicast and multicast packets can be efficiently routed within the network. While suggesting a more efficient multicast support, the proposed approach does not affect the performance of unicast routing at all. In addition, in order to reduce the overall path length of multicast packets, we present several partitioning methods along with their analytical models for latency measurement. This approach is discussed in the context of 3D mesh networks.

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In this Master’s thesis agent-based modeling has been used to analyze maintenance strategy related phenomena. The main research question that has been answered was: what does the agent-based model made for this study tell us about how different maintenance strategy decisions affect profitability of equipment owners and maintenance service providers? Thus, the main outcome of this study is an analysis of how profitability can be increased in industrial maintenance context. To answer that question, first, a literature review of maintenance strategy, agent-based modeling and maintenance modeling and optimization was conducted. This review provided the basis for making the agent-based model. Making the model followed a standard simulation modeling procedure. With the simulation results from the agent-based model the research question was answered. Specifically, the results of the modeling and this study are: (1) optimizing the point in which a machine is maintained increases profitability for the owner of the machine and also the maintainer with certain conditions; (2) time-based pricing of maintenance services leads to a zero-sum game between the parties; (3) value-based pricing of maintenance services leads to a win-win game between the parties, if the owners of the machines share a substantial amount of their value to the maintainers; and (4) error in machine condition measurement is a critical parameter to optimizing maintenance strategy, and there is real systemic value in having more accurate machine condition measurement systems.

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Cyber security is one of the main topics that are discussed around the world today. The threat is real, and it is unlikely to diminish. People, business, governments, and even armed forces are networked in a way or another. Thus, the cyber threat is also facing military networking. On the other hand, the concept of Network Centric Warfare sets high requirements for military tactical data communications and security. A challenging networking environment and cyber threats force us to consider new approaches to build security on the military communication systems. The purpose of this thesis is to develop a cyber security architecture for military networks, and to evaluate the designed architecture. The architecture is described as a technical functionality. As a new approach, the thesis introduces Cognitive Networks (CN) which are a theoretical concept to build more intelligent, dynamic and even secure communication networks. The cognitive networks are capable of observe the networking environment, make decisions for optimal performance and adapt its system parameter according to the decisions. As a result, the thesis presents a five-layer cyber security architecture that consists of security elements controlled by a cognitive process. The proposed architecture includes the infrastructure, services and application layers that are managed and controlled by the cognitive and management layers. The architecture defines the tasks of the security elements at a functional level without introducing any new protocols or algorithms. For evaluating two separated method were used. The first method is based on the SABSA framework that uses a layered approach to analyze overall security of an organization. The second method was a scenario based method in which a risk severity level is calculated. The evaluation results show that the proposed architecture fulfills the security requirements at least at a high level. However, the evaluation of the proposed architecture proved to be very challenging. Thus, the evaluation results must be considered very critically. The thesis proves the cognitive networks are a promising approach, and they provide lots of benefits when designing a cyber security architecture for the tactical military networks. However, many implementation problems exist, and several details must be considered and studied during the future work.

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This paper presents an approach to the solution of moving a robot manipulator with minimum cost along a specified geometric path in the presence of obstacles. The main idea is to express obstacle avoidance in terms of the distances between potentially colliding parts. The optimal traveling time and the minimum mechanical energy of the actuators are considered together to build a multiobjective function. A simple numerical example involving a Cartesian manipulator arm with two-degree-of-freedom is described.

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In recent years the analysis and synthesis of (mechanical) control systems in descriptor form has been established. This general description of dynamical systems is important for many applications in mechanics and mechatronics, in electrical and electronic engineering, and in chemical engineering as well. This contribution deals with linear mechanical descriptor systems and its control design with respect to a quadratic performance criterion. Here, the notion of properness plays an important role whether the standard Riccati approach can be applied as usual or not. Properness and non-properness distinguish between the cases if the descriptor system is exclusively governed by the control input or by its higher-order time-derivatives additionally. In the unusual case of non-proper systems a quite different problem of optimal control design has to be considered. Both cases will be solved completely.

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In this paper, the optimum design of 3R manipulators is formulated and solved by using an algebraic formulation of workspace boundary. A manipulator design can be approached as a problem of optimization, in which the objective functions are the size of the manipulator and workspace volume; and the constrains can be given as a prescribed workspace volume. The numerical solution of the optimization problem is investigated by using two different numerical techniques, namely, sequential quadratic programming and simulated annealing. Numerical examples illustrate a design procedure and show the efficiency of the proposed algorithms.

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This study focuses on the relationship between organizational network competence and the internationalization process of small- and medium sized enterprises (SMEs). Over recent decades, the global business environment has become increasingly conducive to internationalization of small firms. A central facilitating factor in the process has been the emergence of networked business relationships between internationalizing firms. Research on SME internationalization has found that certain types of structures and dynamics of business networks allow SMEs access to the resources they need to enter foreign markets. This consequently means that their internationalization often becomes to depend on the networks they are embedded in. However, research so far has mostly ignored the possibility that the organizational ability to develop and manage business network relationships, network competence, may be a major underlying factor in determining how well SMEs can leverage their network relationships to enter foreign markets and consequently may determine in large part how successful their internationalization process turns out to be. This study aims to respond to those gaps, by empirically examining how the development of network competence in internationalizing SMEs influences the internationalization outcomes that they can expect, and how such network competence is conceptualized and developed. Using a mixed methods approach, survey data collected from 298 Finnish SMEs across five industry sectors is first used to examine how levels of network competence are related to internationalization propensity of SMEs and their subsequent international performance, growth and profitability as internationally operating firms. In order to illustrate in more detail the ways in which network competence is conceptualized and how it develops during the internationalization process of an SME, qualitative data from internationally operating Finnish SMEs are used. Longitudinal interview data of an internationalizing Finnish SME is accompanied by data gathered through a series of semistructured interviews of Finnish and Russian managers involved in mutual business relationship dyads. Structurally, this thesis examines the research issue as an article-based dissertation, consisting of five journal and conference publications. Three of these publications are based on the quantitative data, and the remaining two apply the qualitative interview data. The results find several aspects where network competence has a positive influence on the success of internationalizing SMEs, how it develops and what it entails conceptually in this context. Quantitatively, the level of network competence is found to have a positive relationship to various internationalization outcomes, including the propensity of SMEs to enter foreign markets and on their subsequent international performance, their growth and their profitability. Additionally, the positive relationship is divided between the relationship-specific and cross-relational dimension of network competence, in that the influence of the former is relevant for the propensity to internationalize, while the latter is for the growth and profitability of the already internationalized SMEs. Qualitatively, the results suggest, firstly, that the development process of network competence does not necessarily precede the start of the internationalization process, but may occur through a gradual learning process alongside it. And secondly, the results also imply that the conceptualization of network competence by Finnish managers of internationally operating Finnish SMEs is structurally distinct from that of their culturally distinct partner managers in Russia. This study contributes to the literature on SME internationalization in several ways. Firstly, it introduces operationalized organizational competencies to the literature on internationalization of SMEs, which has so far mainly examined the influence of business networking on the internationalization process without having such an organizational viewpoint. Furthermore, this study provides a multi-level analysis of the determinants of successful SME internationalization, by examining various strategic and performance outcomes across the process. These results also contribute to the literature on organizational strategy of internationalizing SMEs, by clarifying how different dimensions of business networking may be optimal in different phases of the internationalization process. Conceptually, the results of this study contribute to the literature on competence development and SME internationalization, by illustrating how the development process of network competence may occur during internationalization process. Thus, they also contribute to the discussion on how SMEs are able to influence the dynamics and structures of their business networks over time. Finally, this study contributes to the literature on the role of culture in the internationalization process, by implying that the cultural background of the manager of the SME may determine whether business networking and network competence is seen as an organizational-level or an individual level capability. The study also includes some additional contributions to the literature on dynamic capabilities in strategic management, and on that of strategic business networks. These include further clarifying the exact nature and tangibility of dynamic capabilities, and being one of the first studies to introduce constructs from both dynamic capabilities and business network literature to the field of international entrepreneurship. And finally, the study also has some contribution on the two streams of literature, in illustrating how both dyadic and network-level capabilities may be relevant, depending on the current strategic goals and market position of the firm. Keywords: network competence, internationalizatio

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Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.