41 resultados para Prime rational functions


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Selostus: Sian kasvuominaisuuksien perinnölliset tunnusluvut arvioituna kolmannen asteen polynomifunktion avulla

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Yrityksen sisäisten rajapintojen tunteminen mahdollistaa tiedonvaihdon hallinnan läpi organisaation. Idean muokkaaminen kannattavaksi innovaatioksi edellyttää organisaation eri osien läpi kulkevaa saumatonta prosessiketjua sekä tietovirtaa. Tutkielman tavoitteena oli mallintaa organisaation kahden toiminnallisesti erilaisen osan välinen tiedon vaihto. Tiedon vaihto kuvattiin rajapintana, tietoliittymänä. Kolmiulotteinen organisaatiomalli muodosti tutkimuksen pääteorian. Se kytkettiin yrityksen tuotanto- ja myyntiosiin, kuten myös BestServ-projektin kehittämään uuteen palvelujen kehittämisen prosessiin. Uutta palvelujen kehittämisen prosessia laajennettiin ISO/IEC 15288 standardin kuvaamalla prosessimallilla. Yritysarkkitehtuurikehikoita käytettiin mallintamisen perustana. Tietoliittymä nimenä kuvastaa näkemystä siitä, että tieto [tietämys] on olemukseltaan yksilöiden tai ryhmien välistä. Mallinnusmenetelmät eivät kuitenkaan vielä mahdollista tietoon [tietämykseen] liittyvien kaikkien ominaisuuksien mallintamista. Tietoliittymän malli koostuu kolmesta osasta, joista kaksi esitetään graafisessa muodossa ja yksi taulukkona. Mallia voidaan käyttää itsenäisesti tai osana yritysarkkitehtuuria. Teollisessa palveluliiketoiminnassa sekä tietoliittymän mallinnusmenetelmä että sillä luotu malli voivat auttaa konepajateollisuuden yritystä ymmärtämään yrityksen kehittämistarpeet ja -kohteet, kun se haluaa palvelujen tuottamisella suuremman roolin asiakasyrityksen liiketoiminnassa. Tietoliittymän mallia voidaan käyttää apuna organisaation tietovarannon ja tietämyksen mallintamisessa sekä hallinnassa ja näin pyrkiä yhdistämään ne yrityksen strategiaa palvelevaksi kokonaisuudeksi. Tietoliittymän mallinnus tarjoaa tietojohtamisen kauppatieteelliselle tutkimukselle menetelmällisyyden tutkia innovaatioiden hallintaa sekä organisaation uudistumiskykyä. Kumpikin tutkimusalue tarvitsevat tarkempaa tietoa ja mahdollisuuksia hallita tietovirtoja, tiedon vaihtoa sekä organisaation tietovarannon käyttöä.

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The thesis studies role based access control and its suitability in the enterprise environment. The aim is to research how extensively role based access control can be implemented in the case organization and how it support organization’s business and IT functions. This study points out the enterprise’s needs for access control, factors of access control in the enterprise environment and requirements for implementation and the benefits and challenges it brings along. To find the scope how extensively role based access control can be implemented into the case organization, firstly is examined the actual state of access control. Secondly is defined a rudimentary desired state (how things should be) and thirdly completed it by using the results of the implementation of role based access control application. The study results the role model for case organization unit, and the building blocks and the framework for the organization wide implementation. Ultimate value for organization is delivered by facilitating the normal operations of the organization whilst protecting its information assets.

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Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

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Members of the bacterial genus Streptomyces are well known for their ability to produce an exceptionally wide selection of diverse secondary metabolites. These include natural bioactive chemical compounds which have potential applications in medicine, agriculture and other fields of commerce. The outstanding biosynthetic capacity derives from the characteristic genetic flexibility of Streptomyces secondary metabolism pathways: i) Clustering of the biosynthetic genes in chromosome regions redundant for vital primary functions, and ii) the presence of numerous genetic elements within these regions which facilitate DNA rearrangement and transfer between non-progeny species. Decades of intensive genetic research on the organization and function of the biosynthetic routes has led to a variety of molecular biology applications, which can be used to expand the diversity of compounds synthesized. These include techniques which, for example, allow modification and artificial construction of novel pathways, and enable gene-level detection of silent secondary metabolite clusters. Over the years the research has expanded to cover molecular-level analysis of the enzymes responsible for the individual catalytic reactions. In vitro studies of the enzymes provide a detailed insight into their catalytic functions, mechanisms, substrate specificities, interactions and stereochemical determinants. These are factors that are essential for the thorough understanding and rational design of novel biosynthetic routes. The current study is a part of a more extensive research project (Antibiotic Biosynthetic Enzymes; www.sci.utu.fi/projects/biokemia/abe), which focuses on the post-PKS tailoring enzymes involved in various type II aromatic polyketide biosynthetic pathways in Streptomyces bacteria. The initiative here was to investigate specific catalytic steps in anthracycline and angucycline biosynthesis through in vitro biochemical enzyme characterization and structural enzymology. The objectives were to elucidate detailed mechanisms and enzyme-level interactions which cannot be resolved by in vivo genetic studies alone. The first part of the experimental work concerns the homologous polyketide cyclases SnoaL and AknH. These catalyze the closure of the last carbon ring of the tetracyclic carbon frame common to all anthracycline-type compounds. The second part of the study primarily deals with tailoring enzymes PgaE (and its homolog CabE) and PgaM, which are responsible for a cascade of sequential modification reactions in angucycline biosynthesis. The results complemented earlier in vivo findings and confirmed the enzyme functions in vitro. Importantly, we were able to identify the amino acid -level determinants that influence AknH and SnoaL stereoselectivity and to determine the complex biosynthetic steps of the angucycline oxygenation cascade of PgaE and PgaM. In addition, the findings revealed interesting cases of enzyme-level adaptation, as some of the catalytic mechanisms did not coincide with those described for characterised homologs or enzymes of known function. Specifically, SnoaL and AknH were shown to employ a novel acid-base mechanism for aldol condenzation, whereas the hydroxylation reaction catalysed by PgaM involved unexpected oxygen chemistry. Owing to a gene-level fusion of two ancestral reading frames, PgaM was also shown to adopt an unusual quaternary sturucture, a non-covalent fusion complex of two alternative forms of the protein. Furthermore, the work highlighted some common themes encountered in polyketide biosynthetic pathways such as enzyme substrate specificity and intermediate reactivity. These are discussed in the final chapters of the work.

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The research on language equations has been active during last decades. Compared to the equations on words the equations on languages are much more difficult to solve. Even very simple equations that are easy to solve for words can be very hard for languages. In this thesis we study two of such equations, namely commutation and conjugacy equations. We study these equations on some limited special cases and compare some of these results to the solutions of corresponding equations on words. For both equations we study the maximal solutions, the centralizer and the conjugator. We present a fixed point method that we can use to search these maximal solutions and analyze the reasons why this method is not successful for all languages. We give also several examples to illustrate the behaviour of this method.

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Käytöntukijärjestelmä on ohjelmistokokonaisuus, jota käytetään käyttötoiminnan päätöksenteon tukena useissa verkkoyhtiöissä. Järjestelmä sisältää useita erilaisia sovelluksia, joiden käytön perustana on käytöntukijärjestelmään integroituneiden tietojärjestelmien tietojen hyödyntäminen. Tässä diplomityössä tutkitaan käytöntukijärjestelmän eri toimintoja ja analysoidaan niistä saatavia hyötyjä. Hyötyjen suuruuteen vaikuttaa merkittävästi verkon laajuus, automaatioaste sekä käyttöhenkilökunnan koulutustaso. Lopputuloksena verrataan käytöntukijärjestelmästä saatavaa maksimaalista hyötyä keskeytyskustannuksissa, järjestelmän käyttöönotosta aiheutuviin kustannuksiin. Lisäksi työssä arvioidaan verkkoyhtiön laajuudesta riippuen, onko sen järkevää hankkia käytöntukijärjestelmää ostamalla se itse, palveluntarjoajan kautta tai ei ollenkaan.