15 resultados para Soft switching

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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Työssä esiteltävä laite on osa DC-AC hakkuria, jolla muodostetaan 750 V tasajännitteestä yksivaiheista (230 VRMS, 50 Hz) galvaanisesti erotettua verkkojännitettä. Tasajännite muunnetaan resonanssikonvertterilla korkeataajuiseksi vaihtojännitteeksi, joka johdetaan erotusmuuntajaan. Galvaanisen erotuksen jälkeen korkeataajuisesta vaihtojännitteestä muodostetaan suoraan verkkotaajuista vaihtojännitettä työssä esiteltävällä syklokonvertterilla. Suunnittelussa on pyritty minimoimaan häviöt mahdollisimman tarkkaan, jotta laite olisi kilpailukykyinen ei-galvaanisesti erottavien konverttereiden kanssa. Tämä on toteutettu käyttämällä mahdollisimman vähän komponentteja virran kulkureitillä sekä soveltamalla pehmeää kytkentää kaikissa tilanteissa. Lopuksi esitellään prototyyppi, jonka tarkoitus oli selvittää laitteen toiminta ja ongelmakohdat käytännössä.

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In the era of fast product development and customized product requirements, the concept of product platform has proven its power in practice. The product platform approach has enabledcompanies to increase the speed of product introductions while simultaneously benefit from efficiency and effectiveness in the development and production activities. The product platforms are technological bases, which can be used to develop several derivative products, and hence, the differentiation can be pushed closer to the product introduction. The product platform development has some specific features, which differ somewhat from the product development of single products. The time horizon is longer, since the product platform¿slife cycle is longer than individual product's. The long time-horizon also proposes higher market risks and the use of new technologies increases the technological risks involved. The end-customer interface might be far away, but there is not a lack of needs aimed at the product platforms ¿ in fact, the product platform development is very much balancing between the varying needs set to it by thederivative products. This dissertation concentrated on product platform development from the internal product lines' perspective of a singlecase. Altogether six product platform development factors were identified: 'Strategic and business fit of product platform', 'Project communication and deliverables', 'Cooperation with product platform development', 'Innovativeness of product platform architecture and features', 'Reliability and quality of product platform', and 'Promised schedules and final product platform meeting the needs'. From the six factors, three were found to influence quite strongly the overall satisfaction, namely 'Strategic and business fit of product platform', 'Reliability and quality of product platform', and 'Promised schedules and final product platform meeting the needs'. Hence, these three factors might be the ones a new product platform development unit should concentrate first in order to satisfy their closest customers, the product lines. The 'Project communication and deliverables' and 'Innovativeness of product platform architecture and features' were weaker contributors to the overall satisfaction. Overall, the factors explained quite well the satisfaction of the product lines with product platform development. Along the research, several interesting aspects about the very basic nature of the product platform development were found. The long time horizon of the product platform development caused challenges in the area of strategic fIT - a conflict between the short-term requirements and long term needs. The fact that a product platform was used as basis of several derivative products resulted into varying needs, and hence the match with the needs and the strategies. The opinions, that the releases of the larger product lines were given higher priorities, give an interesting contribution to the strategy theory of powerand politics. The varying needs of the product lines, the strengths of them as well as large number of concurrent releases set requirements to prioritization. Hence, the research showed the complicated nature of the product platform development in the case unIT - the very basic nature of the product platform development might be its strength (gaining efficiency and effectiveness in product development and product launches) but also the biggest challenge (developing products to meet several needs). As a single case study, the results of this research are not directly generalizable to all the product platform development activities. Instead, the research serves best as a starting point for additional research as well as gives some insights about the factors and challengesof one product development unit.

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In metallurgic plants a high quality metal production is always required. Nowadays soft computing applications are more often used for automation of manufacturing process and quality control instead of mechanical techniques. In this thesis an overview of soft computing methods presents. As an example of soft computing application, an effective model of fuzzy expert system for the automotive quality control of steel degassing process was developed. The purpose of this work is to describe the fuzzy relations as quality hypersurfaces by varying number of linguistic variables and fuzzy sets.

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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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Nowadays power drives are the essential part almost of all technological processes. Improvement of efficiency and reduction of losses require development of semiconductor switches. It has a particular meaning for the constantly growing market of renewable sources, especially for wind turbines, which demand more powerful semiconductor devices for control with growth of power. Also at present semiconductor switches are the key component in energy transmission, optimization of generation and network connection. The aim of this thesis is to make a survey of contemporary semiconductor components, showing difference in structures, advantages, disadvantages and most suitable applications. There is topical information about voltage, frequency and current limits of different switches. Study tries to compare dimensions and price of different components. Main manufacturers of semiconductor components are presented with the review of devices produced by them, and a conclusion about their availability was made. IGBT is selected as a main component in this study, because nowadays it is the most attractive component for usage in power drives, especially at the low levels of medium voltage. History of development of IGBT structure, static and dynamic characteristics are considered. Thesis tells about assemblies and connection of components and problems which can appear. One of key questions about semiconductor materials and their future development was considered. For the purpose of comparison strong and weak sides of different switches, calculation of losses of IGBT and its basic competitor – IGCT is presented. This master’s thesis makes an effort to answer the question if there are at present possibilities of accurate selection of switches for electrical drives of different rates of power and looks at future possible ways of development of semiconductor market.

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Connectivity depends on rates of dispersal between communities. For marine soft-sediment communities continued small-scale dispersal as post-larvae and as adults can be equally important in maintaining community composition, as initial recruitment of substrate by pelagic larvae. In this thesis post-larval dispersal strategies of benthic invertebrates, as well as mechanisms by which communities are connected were investigated. Such knowledge on dispersal is scarce, due to the difficulties in actually measuring dispersal directly in nature, and dispersal has not previously been quantified in the Baltic Sea. Different trap-types were used underwater to capture dispersing invertebrates at different sites, while in parallel measuring waves and currents. Local community composition was found to change predictably under varying rates of dispersal and physical connectivity (waves and currents). This response was, however, dependent on dispersal-related traits of taxa. Actively dispersing taxa will be relatively better at maintaining their position, as they are not as dependent on hydrodynamic conditions for dispersal and will be less prone to be passively transported by currents. Taxa also dispersed in relative proportions that were distinctly different from resident community composition and a significant proportion (40 %) of taxa were found to lack a planktonic larval life-stage. Community assembly was re-started in a large-scale manipulative field experiment over one year across several sites, which revealed how patterns of community composition (α-, β- and λ-diversity) change depending on rates of dispersal. Results also demonstrated that in response to small-scale disturbance, initial recruitment was by nearby-dominant species after which other species arrived from successively further away. At later assembly time, the number of coexisting species increased beyond what was expected purely by local niche requirements (species sorting), transferring regional differences in community composition (β-diversity) to the local scale (α-diversity, mass effect). Findings of this thesis complement more theoretical studies in metacommunity ecology by demonstrating that understanding how and when individuals disperse relative to underlying environmental heterogeneity is key to interpreting how patterns of diversity change across different spatial scales. Such information from nature is critical when predicting responses to, for example, different types of disturbances or management actions in conservation.

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Tutkielmassa analysoidaan kolmen internetsivuston uutisartikkeleita kielitieteen näkökulmasta. Tavoitteena on selvittää esiintyykö internetsivustojen BBC, CNN ja Fox News uutisoinnissa politiikkaan liittyviä ennakkoasenteita tai puolueellisuuksia ja miten ne käytännössä näkyvät uutisartikkeleiden kielessä. Kriittiseen diskurssianalyysiin pohjautuen tutkielma esittelee jokaisen uutissivuston taustaan (esimerkiksi rakenteeseen ja rahoitukseen) liittyviä seikkoja sekä mediadiskurssiin ja politiikkaan liittyvät taustatiedot, jolla taataan Norman Fairclough'n kolmivaiheisen menetelmän mahdollisimman perusteellinen toteuttaminen. Uutissivustoja analysoidaan kriittiselle diskurssianalyysille sopivan funktionaalisen kieliopin ja muiden lingvististen välineiden avulla. Koko aineiston (404 artikkelia) otsikot analysoidaan ensin, minkä jälkeen analysoidaan yhdeksän kokonaista artikkelia kolmeen eri aihealueeseen liittyen niin, että jokaiselta internetsivustolta analysoidaan yksi artikkeli jokaista aihetta kohden. Analyysikeinoina käytetään ensisijaisesti systeemis-funktionaalisen kieliopin tekstuaalisen metafunktion välineitä (thematic structure). Myös ideationaalisen metafunktion välineitä (transitivity), referenssiketjuja (referential identity chains) ja leksikaalista analyysia käytetään hyväksi. Lähtökohtaisesti tavoitteena on analysoida uutissivustoja vertailevasti, jolloin analyysin tulokset ovat paremmin havainnoitavissa ja perusteltavissa. Hypoteesi aikaisempien tutkimusten ja yleisen mielikuvan perusteella on, että CNN uutisoi demokraattipuolueelle ja Fox News taas republikaanipuolueelle edulliseen sävyyn. Tutkimustulokset vaihtelivat hypoteesia tukevista ja sen vastaisista tuloksista niihin, jotka eivät olleet tarpeeksi tuettuja kumpaankaan suuntaan. Vahvimmat tulokset ovat kuitenkin hypoteesia tukevia, joten tässä tutkielmassa todetaan, ettei uutisointi ole puolueetonta ainakaan näiden kolmen internetsivuston kohdalla. Lisäksi muutaman aihealueen kohdalla uutisointi on niin toistuvaa tietystä näkökulmasta, että luonnollistumisteorian mukaista aatteiden luonnollistumista saattaa tapahtua. Tutkielmassa käytettyjen menetelmien menestyksen perusteella suositellaan, että tekstuaalisen metafunktion analyysivälineitä käytetään enemmän. Lisäksi suositellaan meta-analyysin harkitsemista, jotta voitaisiin selvittää, mitkä analyysimetodit parhaiten sopivat minkäkinlaisen aineiston analysointiin.

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When modeling machines in their natural working environment collisions become a very important feature in terms of simulation accuracy. By expanding the simulation to include the operation environment, the need for a general collision model that is able to handle a wide variety of cases has become central in the development of simulation environments. With the addition of the operating environment the challenges for the collision modeling method also change. More simultaneous contacts with more objects occur in more complicated situations. This means that the real-time requirement becomes more difficult to meet. Common problems in current collision modeling methods include for example dependency on the geometry shape or mesh density, calculation need increasing exponentially in respect to the number of contacts, the lack of a proper friction model and failures due to certain configurations like closed kinematic loops. All these problems mean that the current modeling methods will fail in certain situations. A method that would not fail in any situation is not very realistic but improvements can be made over the current methods.

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This thesis studies the predictability of market switching and delisting events from OMX First North Nordic multilateral stock exchange by using financial statement information and market information from 2007 to 2012. This study was conducted by using a three stage process. In first stage relevant theoretical framework and initial variable pool were constructed. Then, explanatory analysis of the initial variable pool was done in order to further limit and identify relevant variables. The explanatory analysis was conducted by using self-organizing map methodology. In the third stage, the predictive modeling was carried out with random forests and support vector machine methodologies. It was found that the explanatory analysis was able to identify relevant variables. The results indicate that the market switching and delisting events can be predicted in some extent. The empirical results also support the usability of financial statement and market information in the prediction of market switching and delisting events.

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With a Sales and Operations Planning (S&OP) process, a company aims to manage the demand and supply by planning and forecasting. The studied company uses an integrated S&OP process to improve the company's operations. The aim of this thesis is to develop this business process by finding the best possible way to manage the soft information in S&OP, whilst also understanding the importance and types (assumptions, risks and opportunities) of soft information in S&OP. The soft information in S&OP helps to refine future S&OP planning, taking into account the uncertainties that affect the balance of the long-term demand and supply (typically 12-18 months). The literature review was used to create a framework for soft information management process in S&OP. There were not found a concrete way how to manage soft information in the existing literature. In consequence of the poor literature available the Knowledge Management literature was used as the base for the framework creation, which was seen in the very same type of information management like the soft information management is. The framework created a four-stage process to manage soft information in S&OP that included also the required support systems. First phase is collecting and acquiring soft information in S&OP, which include also categorization. The categorization was the cornerstone to identify different requirements that needs to be taken into consideration when managing soft information in S&OP process. The next phase focus on storing data, which purpose is to ensure the soft information is managed in a common system (support system) in a way that the following phase makes it available to users in S&OP who need by help of sharing and applications process. The last phase target is to use the soft information to understand assumptions and thoughts of users behind the numbers in S&OP plans. With this soft management process the support system will have a key role. The support system, like S&OP tool, ensures that soft information is stored in the right places, kept up-to-date and relevancy. The soft information management process in S&OP strives to improve the relevant soft information documenting behind the S&OP plans into the S&OP support system. The process offers an opportunity to individuals to review, comment and evaluate soft information in S&OP made by their own or others. In the case company it was noticed that without a properly documented and distributed soft information in S&OP it was seen to cause mistrust towards the planning.

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Research has highlighted the adequacy of Markov regime-switching model to address dynamic behavior in long term stock market movements. Employing a purposed Extended regime-switching GARCH(1,1) model, this thesis further investigates the regime dependent nonlinear relationship between changes in oil price and stock market volatility in Saudi Arabia, Norway and Singapore for the period of 2001-2014. Market selection is prioritized to national dependency on oil export or import, which also rationalizes the fitness of implied bivariate volatility model. Among two regimes identified by the mean model, high stock market return-low volatility regime reflects the stable economic growth periods. The other regime characterized by low stock market return-high volatility coincides with episodes of recession and downturn. Moreover, results of volatility model provide the evidence that shocks in stock markets are less persistent during the high volatility regime. While accelerated oil price rises the stock market volatility during recessions, it reduces the stock market risk during normal growth periods in Singapore. In contrast, oil price showed no significant notable impact on stock market volatility of target oil-exporting countries in either of the volatility regime. In light to these results, international investors and policy makers could benefit the risk management in relation to oil price fluctuation.

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Financial time series have a tendency of abruptly changing their behavior and maintain this behavior for several consecutive periods, and commodity futures returns are not an exception. This quality proposes that nonlinear models, as opposed to linear models, can more accurately describe returns and volatility. Markov regime switching models are able to match this behavior and have become a popular way to model financial time series. This study uses Markov regime switching model to describe the behavior of energy futures returns on a commodity level, because studies show that commodity futures are a heterogeneous asset class. The purpose of this thesis is twofold. First, determine how many regimes characterize individual energy commodities’ returns in different return frequencies. Second, study the characteristics of these regimes. We extent the previous studies on the subject in two ways: We allow for the possibility that the number of regimes may exceed two, as well as conduct the research on individual commodities rather than on commodity indices or subgroups of these indices. We use daily, weekly and monthly time series of Brent crude oil, WTI crude oil, natural gas, heating oil and gasoil futures returns over 1994–2014, where available, to carry out the study. We apply the likelihood ratio test to determine the sufficient number of regimes for each commodity and data frequency. Then the time series are modeled with Markov regime switching model to obtain the return distribution characteristics of each regime, as well as the transition probabilities of moving between regimes. The results for the number of regimes suggest that daily energy futures return series consist of three to six regimes, whereas weekly and monthly returns for all energy commodities display only two regimes. When the number of regimes exceeds two, there is a tendency for the time series of energy commodities to form groups of regimes. These groups are usually quite persistent as a whole because probability of a regime switch inside the group is high. However, individual regimes in these groups are not persistent and the process oscillates between these regimes frequently. Regimes that are not part of any group are generally persistent, but show low ergodic probability, i.e. rarely prevail in the market. This study also suggests that energy futures return series characterized with two regimes do not necessarily display persistent bull and bear regimes. In fact, for the majority of time series, bearish regime is considerably less persistent. Rahoituksen aikasarjoilla on taipumus arvaamattomasti muuttaa käyttäytymistään ja jatkaa tätä uutta käyttäytymistä useiden periodien ajan, eivätkä hyödykefutuurien tuotot tee tähän poikkeusta. Tämän ominaisuuden johdosta lineaaristen mallien sijasta epälineaariset mallit pystyvät tarkemmin kuvailemaan esimerkiksi tuottojen jakauman parametreja. Markov regiiminvaihtomallit pystyvät vangitsemaan tämän ominaisuuden ja siksi niistä on tullut suosittuja rahoituksen aikasarjojen mallintamisessa. Tämä tutkimus käyttää Markov regiiminvaihtomallia kuvaamaan yksittäisten energiafutuurien tuottojen käyttäytymistä, sillä tutkimukset osoittavat hyödykefutuurien olevan hyvin heterogeeninen omaisuusluokka. Tutkimuksen tarkoitus on selvittää, kuinka monta regiimiä tarvitaan kuvaamaan energiafutuurien tuottoja eri tuottofrekvensseillä ja mitkä ovat näiden regiimien ominaisuudet. Aiempaa tutkimusta aiheesta laajennetaan määrittämällä regiimien lukumäärä tilastotieteellisen testauksen menetelmin sekä tutkimalla energiafutuureja yksittäin; ei indeksi- tai alaindeksitasolla. Tutkimuksessa käytetään päivä-, viikko- ja kuukausiaikasarjoja Brent-raakaöljyn, WTI-raakaöljyn, maakaasun, lämmitysöljyn ja polttoöljyn tuotoista aikaväliltä 1994–2014, siltä osin kuin aineistoa on saatavilla. Likelihood ratio -testin avulla estimoidaan kaikille aikasarjoille regiimien määrä,jonka jälkeen Markov regiiminvaihtomallia hyödyntäen määritetään yksittäisten regiimientuottojakaumien ominaisuudet sekä regiimien välinen transitiomatriisi. Tulokset regiimien lukumäärän osalta osoittavat, että energiafutuurien päiväkohtaisten tuottojen aikasarjoissa regiimien lukumäärä vaihtelee kolmen ja kuuden välillä. Viikko- ja kuukausituottojen kohdalla kaikkien energiafutuurien prosesseissa regiimien lukumäärä on kaksi. Kun regiimejä on enemmän kuin kaksi, on prosessilla taipumus muodostaa regiimeistä koostuvia ryhmiä. Prosessi pysyy ryhmän sisällä yleensä pitkään, koska todennäköisyys siirtyä ryhmään kuuluvien regiimien välillä on suuri. Yksittäiset regiimit ryhmän sisällä eivät kuitenkaan ole kovin pysyviä. Näin ollen prosessi vaihtelee ryhmän sisäisten regiimien välillä tiuhaan. Regiimit, jotka eivät kuulu ryhmään, ovat yleensä pysyviä, mutta prosessi ajautuu niihin vain harvoin, sillä todennäköisyys siirtyä muista regiimeistä niihin on pieni. Tutkimuksen tulokset osoittavat myös, että prosesseissa, joita ohjaa kaksi regiimiä, nämä regiimit eivät välttämättä ole pysyvät bull- ja bear-markkinatilanteet. Tulokset osoittavat sen sijaan, että bear-markkinatilanne on energiafutuureissa selvästi vähemmän pysyvä.