33 resultados para Selection negativity

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


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Selostus: Alkionsiirtojalostusohjelma "ASMO", sen tavoitteet ja yhteenveto alkuvalinnan tuloksista

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Tämän diplomityön tavoitteena on kartoittaa suomalaisen sahakonevalmistaja Veisto Oy:n kannalta lähitulevaisuuden merkittävimmät markkina-alueet, joiden sahateollisuuteen tehdään lähivuosina eniten korkean teknologian investointeja. Markkina-alueiden valinnassa sovelletaan sekä numeerisiin tilastoihin että asiantuntijahaastatteluihin pohjautuvia ranking-menetelmiä. Työn ensimmäinen osa käsittelee kansainvälisten teollisten markkinoiden ominaispiirteitä ja niiden analysointia. Pääpaino on kuitenkin screening-menetelmillä, markkina-alueiden vertailumenetelmilläja päätöksenteon työkaluilla. Työn toisessa osassa keskitytään markkina-alueiden screeningiin, analysointiin ja maiden eri ominaisuuksien vertailuun. Päätöksentekomatriiseja hyödyntäen valitaan Veisto Oy:lle kolme tällä hetkellä houkuttelevinta markkina-aluetta, joita ovat Venäjä, USA:n kaakkoisosan Southern Yellow Pine -alue sekä Etelä-Amerikan suurimmat sahaajamaat (Brasilia, Argentiina ja Chile) yhtenä alueena. Valituilla alueilla on Veiston kannalta omat haasteensa: USA:ssa vahvat kotimaiset kilpailijat ja uusien referenssien saaminen, Venäjällä investointien epävarmuus ja markkina-alueen laajuuden tuoma monimuotoisuus sekä Etelä-Amerikassa vahvat ruotsalaiset kilpailijat sekä etenkin Brasilian osalta tuntuvat suojatullit.

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Tutkielmantavoitteena oli luoda ohjeistus toimittajan valinnasta ja suorituskyvyn arvioinnista case - yrityksen, Exel Oyj:n, käyttöön. Ohjeistuksen tarkoituksena oli ollalähtökohtana toimittajan valinta- ja suoristuskyvyn arviointiprosessien kehittämisessä. Tutkielma keskittyy esittelemään toimittajan valintakriteereitä ja toimittajan suorituskyvyn arviointikriteereitä. Kriteerit valittiin ja analysoitiin teorian ja empirian avulla ja kriteereistä tehtiin selkeät listaukset. Näitä listoja käytettiin avuksi pohdittaessa uusia valintakriteereitä ja suorituskyvyn arviointikriteereitä, joita case -yritys voi jatkossa käyttää. Tutkielmassa käytiin läpi myös toimittajan valintaprosessi jaapuvälineitä ja mittareita toimittajan arviointiin liittyen. Empiirisen aineiston keruu toteutettiin haastattelemalla hankintapäällikköä sekä keräämällä tietoavuosikertomuksesta ja yrityksen internet sivuilta. Tutkielman tuloksena saatiinlistauksia kriteereistä, joita yritys voi hyödyntää jatkossa sekä listaukset kriteereistä, jotka valittiin alustavasti yrityksen käyttöön.

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The objective of the dissertation is to increase understanding and knowledge in the field where group decision support system (GDSS) and technology selection research overlap in the strategic sense. The purpose is to develop pragmatic, unique and competent management practices and processes for strategic technology assessment and selection from the whole company's point of view. The combination of the GDSS and technology selection is approached from the points of view of the core competence concept, the lead user -method, and different technology types. In this research the aim is to find out how the GDSS contributes to the technology selection process, what aspects should be considered when selecting technologies to be developed or acquired, and what advantages and restrictions the GDSS has in the selection processes. These research objectives are discussed on the basis of experiences and findings in real life selection meetings. The research has been mainly carried outwith constructive, case study research methods. The study contributes novel ideas to the present knowledge and prior literature on the GDSS and technology selection arena. Academic and pragmatic research has been conducted in four areas: 1) the potential benefits of the group support system with the lead user -method,where the need assessment process is positioned as information gathering for the selection of wireless technology development projects; 2) integrated technology selection and core competencies management processes both in theory and in practice; 3) potential benefits of the group decision support system in the technology selection processes of different technology types; and 4) linkages between technology selection and R&D project selection in innovative product development networks. New type of knowledge and understanding has been created on the practical utilization of the GDSS in technology selection decisions. The study demonstrates that technology selection requires close cooperation between differentdepartments, functions, and strategic business units in order to gather the best knowledge for the decision making. The GDSS is proved to be an effective way to promote communication and co-operation between the selectors. The constructs developed in this study have been tested in many industry fields, for example in information and communication, forest, telecommunication, metal, software, and miscellaneous industries, as well as in non-profit organizations. The pragmatic results in these organizations are some of the most relevant proofs that confirm the scientific contribution of the study, according to the principles of the constructive research approach.

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Tämän tutkielman tavoitteena oli määrittää uuden markkinan valinnan perusteita teolliselle tuotteelle. Tutkielma keskittyi jo tunnettuihin kansainvälisen markkinavalinnan lähestymistapoihin ja pyrki soveltamaan yhtä menetelmää käytäntöön tutkielman empiria osassa case-tutkimuksen avulla. Tutkimusote oli tutkiva, eksploratiivinen ja perustui sekundääri analyysiin. Käytetyt tiedon lähteet olivat suureksi osin sekundäärisiä tuottaen kvalitatiivista tietoa. Kuitenkin haastatteluita suoritettiin myös. Kattava kirjallisuus katsaus tunnetuista teoreettisista lähestymistavoista kansainväliseen markkinavalintaan oli osa tutkielmaa. Kolme tärkeintä lähestymistapaa esiteltiin tarkemmin. Yksi lähestymistavoista, ei-järjestelmällinen, muodosti viitekehyksen tutkielman empiria-osalle. Empiria pyrki soveltamaan yhtä ei-järjestelmällisen lähestymistavan malleista kansainvälisessä paperiteollisuudessa. Tarkoituksena oli tunnistaa kaikkein houkuttelevimmat maat mahdollisille markkinointitoimenpiteille tuotteen yhdellä loppukäyttöalueella. Tutkielmassa päädyttiin käyttämään ilmastollisia olosuhteita, siipikarjan päälukua sekä siipikarjan kasvuprosenttia suodattimina pyrittäessä vähentämään mahdollisten maiden lukumäärää. Tutkielman empiria-osa kärsi selkeästi relevantin tiedon puutteesta. Siten myös tutkielman reliabiliteetti ja validiteetti voidaan jossain määrin kyseenalaistaa.

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Drying is a major step in the manufacturing process in pharmaceutical industries, and the selection of dryer and operating conditions are sometimes a bottleneck. In spite of difficulties, the bottlenecks are taken care of with utmost care due to good manufacturing practices (GMP) and industries' image in the global market. The purpose of this work is to research the use of existing knowledge for the selection of dryer and its operating conditions for drying of pharmaceutical materials with the help of methods like case-based reasoning and decision trees to reduce time and expenditure for research. The work consisted of two major parts as follows: Literature survey on the theories of spray dying, case-based reasoning and decision trees; working part includes data acquisition and testing of the models based on existing and upgraded data. Testing resulted in a combination of two models, case-based reasoning and decision trees, leading to more specific results when compared to conventional methods.

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The main objective of the study was to identify and evaluate criteria for international partner selection in university-university context. This study attempted at promoting better understanding of how universities should proceed in selecting partners for producing joint research publications. Thus, the aim of the study was to gain an understanding of how research collaborations can be developed and how partners can be selected. The choice of a right partner has been identified as a precondition for partnership success. In international research collaborations partnering scientists with different skills and backgrounds bring together complementary knowledge into research projects, which in most cases results in a higher quality output. Therefore, prior to selecting a partner, the set of criteria should be established. This research examined twelve Russian universities with the status of national research university as potential partners for Lappeenranta University of Technology, and selected the most appropriate universities based on established set of criteria. Potential partners’ evaluation was done using secondary sources by tracking partners’ academic success during the period 2005 – 2010. Based on established criteria, the study calculated the partnership index for each university. The results of the research reveal that among twelve examined universities there are four potential partners who have been rather active in publishing scientific articles during 2005 – 2010.

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In this study, feature selection in classification based problems is highlighted. The role of feature selection methods is to select important features by discarding redundant and irrelevant features in the data set, we investigated this case by using fuzzy entropy measures. We developed fuzzy entropy based feature selection method using Yu's similarity and test this using similarity classifier. As the similarity classifier we used Yu's similarity, we tested our similarity on the real world data set which is dermatological data set. By performing feature selection based on fuzzy entropy measures before classification on our data set the empirical results were very promising, the highest classification accuracy of 98.83% was achieved when testing our similarity measure to the data set. The achieved results were then compared with some other results previously obtained using different similarity classifiers, the obtained results show better accuracy than the one achieved before. The used methods helped to reduce the dimensionality of the used data set, to speed up the computation time of a learning algorithm and therefore have simplified the classification task

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In development of human medicines, it is important to predict early and accurately enough the disease and patient population to be treated as well as the effective and safe dose range of the studied medicine. This is pursued by using preclinical research models, clinical pharmacology and early clinical studies with small sample sizes. When successful, this enables effective development of medicines and reduces unnecessary exposure of healthy subjects and patients to ineffectice or harmfull doses of experimental compounds. Toremifene is a selective estrogen receptor modulator (SERM) used for treatment of breast cancer. Its development was initiated in 1980s when selection of treatment indications and doses were based on research in cell and animal models and on noncomparative clinical studies including small number of patients. Since the early development phase, the treatment indication, the patient population and the dose range were confirmed in large comparative clinical studies in patients. Based on the currently available large and long term clinical study data the aim of this study was to investigate how the early phase studies were able to predict the treatment indication, patient population and the dose range of the SERM. As a conclusion and based on the estrogen receptor mediated mechanism of action early studies were able to predict the treatment indication, target patient population and a dose range to be studied in confirmatory clinical studies. However, comparative clinical studies are needed to optimize dose selection of the SERM in treatment of breast cancer.