Reseptikeskuksen lääkekohtaisen tiedon laadun kartoitus toiminnallisesta näkökulmasta

Diplomityössä kartoitetaan tiedon laatuun vaikuttavia tekijöitä kirjallisuuden pohjalta sekä tutkitaan empiirisesti sähköisen reseptin tietosisällön laatua toiminnallisuuden näkökulmasta tarkasteltuna. Tutkimuksen tavoitteena on tuottaa esiselvitys Reseptikeskuksen tietosisällön toiminnallisesta laadusta käytettäväksi lähtötietona tiedon laadun arviointiin ja seurantaan. Tutkimuksen empiirinen osuus toteutettiin kvantitatiivisena tutkimuksena analysoimalla Reseptikeskuksen tietosisällöstä poimittua n. 600 potilaan otosta. Tutkitussa tietosisällössä havaittiin joitain poikkeamia tietosisältöä koskeviin määrityksiin verrattuna, mutta merkittäviä eroja terveydenhuollon eri toimijaryhmien apteekeissa, julkisella ja yksityisellä sektorilla kirjaamien reseptien tietosisällön laadussa ei havaittu. Tiedon kontekstisidonnaisuus on keskeinen tekijä tiedon toiminnallisen laadun määrittämisessä, arvioinnissa ja kehittämisessä. Toiminnan kannalta merkityksellinen tieto rakentuu dataan liitettyjen merkitysten, tiedon käyttäjien kokemusten sekä teknisen ja sosiaalisen käyttöympäristön muodostamana kokonaisuutena. Tiedon laadun parantaminen on jatkuva prosessi, jota tulee ylläpitää arvioimalla ja kehittämällä käytettäviä laatumittareita ja analysointimalleja. Reseptikeskuksen tietosisällön laatua voidaan edelleen kehittää ja nyt tehdyn esikartoituksen pohjalta voidaan jatkossa seurata tietosisällön laadun kehittymistä uusien tutkimusten avulla

R&D Performance Analysis: Case Studies on the Challenges and Promotion of the Evaluation and Measurement of R&D

Due to the intense international competition, demanding, and sophisticated customers, and diverse transforming technological change, organizations need to renew their products and services by allocating resources on research and development (R&D). Managing R&D is complex, but vital for many organizations to survive in the dynamic, turbulent environment. Thus, the increased interest among decision-makers towards finding the right performance measures for R&D is understandable. The measures or evaluation methods of R&D performance can be utilized for multiple purposes; for strategic control, for justifying the existence of R&D, for providing information and improving activities, as well as for the purposes of motivating and benchmarking. The earlier research in the field of R&D performance analysis has generally focused on either the activities and considerable factors and dimensions - e.g. strategic perspectives, purposes of measurement, levels of analysis, types of R&D or phases of R&D process - prior to the selection of R&Dperformance measures, or on proposed principles or actual implementation of theselection or design processes of R&D performance measures or measurement systems. This study aims at integrating the consideration of essential factors anddimensions of R&D performance analysis to developed selection processes of R&D measures, which have been applied in real-world organizations. The earlier models for corporate performance measurement that can be found in the literature, are to some extent adaptable also to the development of measurement systemsand selecting the measures in R&D activities. However, it is necessary to emphasize the special aspects related to the measurement of R&D performance in a way that make the development of new approaches for especially R&D performance measure selection necessary: First, the special characteristics of R&D - such as the long time lag between the inputs and outcomes, as well as the overall complexity and difficult coordination of activities - influence the R&D performance analysis problems, such as the need for more systematic, objective, balanced and multi-dimensional approaches for R&D measure selection, as well as the incompatibility of R&D measurement systems to other corporate measurement systems and vice versa. Secondly, the above-mentioned characteristics and challenges bring forth the significance of the influencing factors and dimensions that need to be recognized in order to derive the selection criteria for measures and choose the right R&D metrics, which is the most crucial step in the measurement system development process. The main purpose of this study is to support the management and control of the research and development activities of organizations by increasing the understanding of R&D performance analysis, clarifying the main factors related to the selection of R&D measures and by providing novel types of approaches and methods for systematizing the whole strategy- and business-based selection and development process of R&D indicators.The final aim of the research is to support the management in their decision making of R&D with suitable, systematically chosen measures or evaluation methods of R&D performance. Thus, the emphasis in most sub-areas of the present research has been on the promotion of the selection and development process of R&D indicators with the help of the different tools and decision support systems, i.e. the research has normative features through providing guidelines by novel types of approaches. The gathering of data and conducting case studies in metal and electronic industry companies, in the information and communications technology (ICT) sector, and in non-profit organizations helped us to formulate a comprehensive picture of the main challenges of R&D performance analysis in different organizations, which is essential, as recognition of the most importantproblem areas is a very crucial element in the constructive research approach utilized in this study. Multiple practical benefits regarding the defined problemareas could be found in the various constructed approaches presented in this dissertation: 1) the selection of R&D measures became more systematic when compared to the empirical analysis, as it was common that there were no systematic approaches utilized in the studied organizations earlier; 2) the evaluation methods or measures of R&D chosen with the help of the developed approaches can be more directly utilized in the decision-making, because of the thorough consideration of the purpose of measurement, as well as other dimensions of measurement; 3) more balance to the set of R&D measures was desired and gained throughthe holistic approaches to the selection processes; and 4) more objectivity wasgained through organizing the selection processes, as the earlier systems were considered subjective in many organizations. Scientifically, this dissertation aims to make a contribution to the present body of knowledge of R&D performance analysis by facilitating dealing with the versatility and challenges of R&D performance analysis, as well as the factors and dimensions influencing the selection of R&D performance measures, and by integrating these aspects to the developed novel types of approaches, methods and tools in the selection processes of R&D measures, applied in real-world organizations. In the whole research, facilitation of dealing with the versatility and challenges in R&D performance analysis, as well as the factors and dimensions influencing the R&D performance measure selection are strongly integrated with the constructed approaches. Thus, the research meets the above-mentioned purposes and objectives of the dissertation from the scientific as well as from the practical point of view.

Spectral Analysis of Buffers in Communication Systems

Muokatun matriisi-geometrian tekniikan kehitys yleimmäksi jonoksi on esitelty tässä työssä. Jonotus systeemi koostuu useista jonoista joilla on rajatut kapasiteetit. Tässä työssä on myös tutkittu PH-tyypin jakautumista kun ne jaetaan. Rakenne joka vastaa lopullista Markovin ketjua jossa on itsenäisiä matriiseja joilla on QBD rakenne. Myös eräitä rajallisia olotiloja on käsitelty tässä työssä. Sen esitteleminen matriisi-geometrisessä muodossa, muokkaamalla matriisi-geometristä ratkaisua on tämän opinnäytetyön tulos.

Investigation and data adaptive analysis of CARS spectra

In this diploma work advantages of coherent anti-Stokes Raman scattering spectrometry (CARS) and various methods of the quantitative analysis of substance structure with its help are considered. The basic methods and concepts of the adaptive analysis are adduced. On the basis of these methods the algorithm of automatic measurement of a scattering strip size of a target component in CARS spectrum is developed. The algorithm uses known full spectrum of target substance and compares it with a CARS spectrum. The form of a differential spectrum is used as a feedback to control the accuracy of matching. To exclude the influence of a background in CARS spectra the differential spectrum is analysed by means of its second derivative. The algorithm is checked up on the simulated simple spectra and on the spectra of organic compounds received experimentally.

Finnair’s “New Silk Road” in the New Millennium: An Analysis of the Construction of Asia and of the Company

During the past century, an increasingly diverse world provided us with opportunities for intercultural communication; especially the growth of commerce at all levels from domestic to international has made the combination of the theories of intercultural communication and international business necessary. As one of the main beneficiaries in international business in recent years, companies in airline industries have developed their international market. For instance, Finnair has developed its Asian strategy which responds to the increasing market demand for flights from Europe to Asia in the new millennium. Therefore, the company manages marketing communication in a global environment and becomes a suitable case for studying the theories of intercultural communication in the context of international marketing. Finnair implemented a large number of international advertisements to promote its Asian routes, where Asia has been constructed as a number of exotic destinations. Meanwhile, the company itself as a provider of these destinations has also been constructed contrastively. Thus, this thesis aims at research how Finnair constructs Asia and the company itself in the new millennium, and how these constructions compare with the theories of intercultural communication. This research applied the theories of international marketing, intercultural communication and culture. In order to analyze the collected corpora as Finnair’s international advertisements and its annual reports in the new millennium, the methods of content analysis and discourse analysis have been used in this research. As a result, Finnair has purposefully applied the essentialist approach to intercultural communication and constructed Asia as an exotic “Other” due to the company’s market orientation. Meanwhile, Finnair has also constructed the company itself two identities based on the same approach: as an international airline provider between Europe and Asia, as well as a part of Finnish society. The combination of intercultural communication and international marketing theories, together with the combination of the methods of content analysis and discourse analysis ensure the originality of this paper.

Economic Geographical Analysis of The Finnish Paper Industry

The purpose of this academic economic geographical dissertation is to study and describe how competitiveness in the Finnish paper industry has developed during 2001–2008. During these years, the Finnish paper industry has faced economically challenging times. This dissertation attempts to fill the existing gap between theoretical and empirical discussions concerning economic geographical issues in the paper industry. The main research questions are: How have the supply chain costs and margins developed during 2001–2008? How do sales prices, transportation, and fixed and variable costs correlate with gross margins in a spatial context? The research object for this case study is a typical large Finnish paper mill that exports over 90 % of its production. The economic longitudinal research data were obtained from the case mill’s controlled economic system and, correlation (R2) analysis was used as the main research method. The time series data cover monthly economic and manufacturing observations from the mill from 2001 to 2008. The study reveals the development of prices, costs and transportation in the case mill, and it shows how economic variables correlate with the paper mills’ gross margins in various markets in Europe. The research methods of economic geography offer perspectives that pay attention to the spatial (market) heterogeneity. This type of research has been quite scarce in the research tradition of Finnish economic geography and supply chain management. This case study gives new insight into the research tradition of Finnish economic geography and supply chain management and its applications. As a concrete empirical result, this dissertation states that the competitive advantages of the Finnish paper industry were significantly weakened during 2001–2008 by low paper prices, costly manufacturing and expensive transportation. Statistical analysis expose that, in several important markets, transport costs lower gross margins as much as decreasing paper prices, which was a new finding. Paper companies should continuously pay attention to lowering manufacturing and transporting costs to achieve more profitable economic performance. The location of a mill being far from markets clearly has an economic impact on paper manufacturing, as paper demand is decreasing and oversupply is pressuring paper prices down. Therefore, market and economic forecasting in the paper industry is advantageous at the country and product levels while simultaneously taking into account the economic geographically specific dimensions.

MCMC Analysis for Optimization of Stochastic Models

In any decision making under uncertainties, the goal is mostly to minimize the expected cost. The minimization of cost under uncertainties is usually done by optimization. For simple models, the optimization can easily be done using deterministic methods.However, many models practically contain some complex and varying parameters that can not easily be taken into account using usual deterministic methods of optimization. Thus, it is very important to look for other methods that can be used to get insight into such models. MCMC method is one of the practical methods that can be used for optimization of stochastic models under uncertainty. This method is based on simulation that provides a general methodology which can be applied in nonlinear and non-Gaussian state models. MCMC method is very important for practical applications because it is a uni ed estimation procedure which simultaneously estimates both parameters and state variables. MCMC computes the distribution of the state variables and parameters of the given data measurements. MCMC method is faster in terms of computing time when compared to other optimization methods. This thesis discusses the use of Markov chain Monte Carlo (MCMC) methods for optimization of Stochastic models under uncertainties .The thesis begins with a short discussion about Bayesian Inference, MCMC and Stochastic optimization methods. Then an example is given of how MCMC can be applied for maximizing production at a minimum cost in a chemical reaction process. It is observed that this method performs better in optimizing the given cost function with a very high certainty.

Bayesian analysis of SEIR epidemic models

This thesis concerns the analysis of epidemic models. We adopt the Bayesian paradigm and develop suitable Markov Chain Monte Carlo (MCMC) algorithms. This is done by considering an Ebola outbreak in the Democratic Republic of Congo, former Zaïre, 1995 as a case of SEIR epidemic models. We model the Ebola epidemic deterministically using ODEs and stochastically through SDEs to take into account a possible bias in each compartment. Since the model has unknown parameters, we use different methods to estimate them such as least squares, maximum likelihood and MCMC. The motivation behind choosing MCMC over other existing methods in this thesis is that it has the ability to tackle complicated nonlinear problems with large number of parameters. First, in a deterministic Ebola model, we compute the likelihood function by sum of square of residuals method and estimate parameters using the LSQ and MCMC methods. We sample parameters and then use them to calculate the basic reproduction number and to study the disease-free equilibrium. From the sampled chain from the posterior, we test the convergence diagnostic and confirm the viability of the model. The results show that the Ebola model fits the observed onset data with high precision, and all the unknown model parameters are well identified. Second, we convert the ODE model into a SDE Ebola model. We compute the likelihood function using extended Kalman filter (EKF) and estimate parameters again. The motivation of using the SDE formulation here is to consider the impact of modelling errors. Moreover, the EKF approach allows us to formulate a filtered likelihood for the parameters of such a stochastic model. We use the MCMC procedure to attain the posterior distributions of the parameters of the SDE Ebola model drift and diffusion parts. In this thesis, we analyse two cases: (1) the model error covariance matrix of the dynamic noise is close to zero , i.e. only small stochasticity added into the model. The results are then similar to the ones got from deterministic Ebola model, even if methods of computing the likelihood function are different (2) the model error covariance matrix is different from zero, i.e. a considerable stochasticity is introduced into the Ebola model. This accounts for the situation where we would know that the model is not exact. As a results, we obtain parameter posteriors with larger variances. Consequently, the model predictions then show larger uncertainties, in accordance with the assumption of an incomplete model.

The Competitive Analysis of Selected Biorefineries in Finland

Biorefineries is a perspective field of study that covers many opportunities of a successful business unit with respect to sustainability. The thesis focuses on the following key objective: identification of a competitive biorefineries production process in small and medium segments of the chemical and forest industries in Finland. The scope of the research relates to the selected biorefineries operations in Finland and the use of hemicellulose, as a raw material. The identification of the types of biorefineries and the important technical and process characteristics opens the advantage in the company’s competitive analysis. The study concentrates on the practical approach to the scientific methods of the market and companies research with the help of Quality Function Deployment and House of Quality tool. The thesis’s findings provide mindset version of the expert’s House of Quality application, identification of crucial biorefineries technical and design characteristics’ correlation and their effect on the competitive behavior of a company. The theoretical background helps to build the picture of the problematic issues within the field and provides scientific possible solutions. The analysis of the biorefineries’ market and companies operations bring the practical-oriented aptitude of the research. The results of the research can be used for the following investigations in a field and may be applied as a company’s management analytic and strategic application.