Building Dynamic Data Centers for Fast Delivery of New Data and Data Updates

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Comparison of five popular normalization methods using a spike-in proteomics data set

Mass spectrometry (MS)-based proteomics has seen significant technical advances during the past two decades and mass spectrometry has become a central tool in many biosciences. Despite the popularity of MS-based methods, the handling of the systematic non-biological variation in the data remains a common problem. This biasing variation can result from several sources ranging from sample handling to differences caused by the instrumentation. Normalization is the procedure which aims to account for this biasing variation and make samples comparable. Many normalization methods commonly used in proteomics have been adapted from the DNA-microarray world. Studies comparing normalization methods with proteomics data sets using some variability measures exist. However, a more thorough comparison looking at the quantitative and qualitative differences of the performance of the different normalization methods and at their ability in preserving the true differential expression signal of proteins, is lacking. In this thesis, several popular and widely used normalization methods (the Linear regression normalization, Local regression normalization, Variance stabilizing normalization, Quantile-normalization, Median central tendency normalization and also variants of some of the forementioned methods), representing different strategies in normalization are being compared and evaluated with a benchmark spike-in proteomics data set. The normalization methods are evaluated in several ways. The performance of the normalization methods is evaluated qualitatively and quantitatively on a global scale and in pairwise comparisons of sample groups. In addition, it is investigated, whether performing the normalization globally on the whole data or pairwise for the comparison pairs examined, affects the performance of the normalization method in normalizing the data and preserving the true differential expression signal. In this thesis, both major and minor differences in the performance of the different normalization methods were found. Also, the way in which the normalization was performed (global normalization of the whole data or pairwise normalization of the comparison pair) affected the performance of some of the methods in pairwise comparisons. Differences among variants of the same methods were also observed.

Fiber flows in global paper and pulp industry. A panel data approach.

The purpose of this thesis is to study factors that explain the bilateral fiber trade flows. This is done by analyzing bilateral trade flows during 1990-2006. It will be studied also, whether there are differences between fiber types. This thesis uses a gravity model approach to study the trade flows. Gravity model is mostly used to study the aggregate data between trading countries. In this thesis the gravity model is applied to single fibers. This model is then applied to panel data set. Results from the regression show clearly that there are benefits in studying different fibers in separate. The effects differ considerably from each other. Furthermore, this thesis speaks for the existence of Linder’s effect in certain fiber types.

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Collectiveness within startup teams – Leading the way to initiating and managing collective pursuit of opportunities in organizational contexts

While traditional entrepreneurship literature addresses the pursuit of entrepreneurial opportunities to a solo entrepreneur, scholars increasingly agree that new ventures are often founded and operated by entrepreneurial teams as collective efforts especially in hightechnology industries. Researchers also suggest that team ventures are more likely to survive and succeed than ventures founded by the individual entrepreneur although specific challenges might relate to multiple individuals being involved in joint entrepreneurial action. In addition to new ventures, entrepreneurial teams are seen central for organizing work in established organizations since the teams are able to create major product and service innovations that drive organizational success. Acknowledgement of the entrepreneurial teams in various organizational contexts has challenged the notion on the individual entrepreneur. However, considering that entrepreneurial teams represent a collective-level phenomenon that bases on interactions between organizational members, entrepreneurial teams may not have been studied as indepth as could be expected from the point of view of the team-level, rather than the individual or the individuals in the team. Many entrepreneurial team studies adopt the individualized view of entrepreneurship and examine the team members’ aggregate characteristics or the role of a lead entrepreneur. The previous understandings might not offer a comprehensive and indepth enough understanding of collectiveness within entrepreneurial teams and team venture performance that often relates to the team-level issues in particular. In addition, as the collective-level of entrepreneurial teams has been approached in various ways in the existing literatures, the phenomenon has been difficult to understand in research and practice. Hence, there is a need to understand entrepreneurial teams at the collective-level through a systematic and comprehensive perspective. This study takes part in the discussions on entrepreneurial teams. The overall objective of this study is to offer a description and understanding of collectiveness within entrepreneurial teams beyond individual(s). The research questions of the study are: 1) what collectiveness within entrepreneurial teams stands for, what constitutes the basic elements of it, and who are included in it, 2) why, how, and when collectiveness emerges or reinforces within entrepreneurial teams, and 3) why collectiveness within entrepreneurial teams matters and how it could be developed or supported. In order to answer the above questions, this study bases on three approaches, two set of empirical data, two analysis techniques, and conceptual study. The first data set consists of 12 qualitative semi-structured interviews with business school students who are seen as prospective entrepreneurs. The data is approached through a social constructionist perspective and analyzed through discourse analysis. The second data set bases on a qualitative multiplecase study approach that aims at theory elaboration. The main data consists of 14 individual and four group semi-structured thematic interviews with members of core entrepreneurial teams of four team startups in high-technology industries. The secondary data includes publicly available documents. This data set is approached through a critical realist perspective and analyzed through systematic thematic analysis. The study is completed through a conceptual study that aims at building a theoretical model of collective-level entrepreneurship drawing from existing literatures on organizational theory and social-psychology. The theoretical work applies a positivist perspective. This study consists of two parts. The first part includes an overview that introduces the research background, knowledge gaps and objectives, research strategy, and key concepts. It also outlines the existing knowledge of entrepreneurial team literature, presents and justifies the choices of paradigms and methods, summarizes the publications, and synthesizes the findings through answering the above mentioned research questions. The second part consists of five publications that address independent research questions but all enable to answer the research questions set for this study as a whole. The findings of this study suggest a map of relevant concepts and their relationships that help grasp collectiveness within entrepreneurial teams. The analyses conducted in the publications suggest that collectiveness within entrepreneurial teams stands for cognitive and affective structures in-between team members including elements of collective entity, collective idea of business, collective effort, collective attitudes and motivations, and collective feelings. Collectiveness within entrepreneurial teams also stands for specific joint entrepreneurial action components in which the structures are constructed. The action components reflect equality and democracy, and open and direct communication in particular. Collectiveness emerges because it is a powerful tool for overcoming individualized barriers to entrepreneurship and due to collectively oriented desire for, collective value orientation to, demand for, and encouragement to team entrepreneurship. Collectiveness emerges and reinforces in processes of joint creation and realization of entrepreneurial opportunities including joint analysis and planning of the opportunities and strategies, decision-making and realization of the opportunities, and evaluation, feedback, and sanctions of entrepreneurial action. Collectiveness matters because it is relevant for potential future entrepreneurs and because it affects the ways collective ventures are initiated and managed. Collectiveness also matters because it is a versatile, dynamic, and malleable phenomenon and the ideas of it can be applied across organizational contexts that require team work in discovering or creating and realizing new opportunities. This study further discusses how the findings add to the existing knowledge of entrepreneurial team literature and how the ideas can be applied in educational, managerial, and policy contexts.

Patient-perceived health-related quality of life during recovery after total hip arthroplasty – a 6-month follow-up study

Potilaiden käsitys terveyteen liittyvästä elämänlaadusta lonkan tekonivelleikkauksen jälkeisenä toipumisaikana – kuuden kuukauden seurantatutkimus Tässä kaksivaiheisessa seurantatutkimuksessa tarkasteltiin potilaiden käsitystä terveyteen liittyvästä elämänlaadusta lonkan tekonivelleikkauksen jälkeisenä toipumisaikana. Tutkimuksen ensimmäisessä vaiheessa tarkoituksena oli sekä kuvailla potilaiden kokemuksia potilaana olosta, saamastaan hoidosta ja terveyspalveluorganisaatiosta että analysoida aikaisempien tutkimusten perusteella leikkauksen tuloksia potilaan kannalta. Toisessa vaiheessa tarkoituksena oli arvioida potilaiden kokemaa elämänlaatua leikkauksen jälkeen, ja sitä vaikuttivatko primaaritulokset (fyysinen toimintakyky, kipu, ahdistus) tai taloudelliset seuraukset (potilaiden itsensämaksamat kustannukset, palvelujen käyttö) terveyteen liittyvään elämänlaatuun. Tutkimuksen tavoitteena oli löytää mahdolliset kriittiset ajankohdat tai tekijät, jotka saattavat hidastaa toipumista ja siten huonontaa potilaiden elämänlaatua. Tätä tietoa voidaan käyttää hoitotyössä kun suunnitellaan sopivaa hoitoa ja tukea toipumisajalle. Tutkimuksen ensimmäisessä vaiheessa primaarileikkaukseen tulevat potilaat (n = 17) kuvailivat teemahaastatteluissa kokemuksiaan kahdesti leikkauksen jälkeen. Haastatteluaineisto analysoitiin induktiivisella sisällönanalyysilla. Lisäksi 17 tutkimusartikkelista analysoitiin deduktiivisella sisällönanalyysilla leikkauksen tuloksia potilaalle, tuloksiin vaikuttavia tekijöitä ja käytetyt tutkimusmetodit. Toisessa vaiheessa primaari- tai revisioleikkaukseen tulevat potilaat (n = 100) arvioivat leikkauksen tuloksia kuuden kuukauden ajan leikkauksen jälkeen: terveyteen liittyvää elämänlaatua, primaarituloksia ja taloudellisia seurauksia. Aineisto kerättiin erilaisilla mittareilla: Sickness Impact Profile, Finnish Version, Stait-Trait Anxiety Inventory, ja Numeric Rating Scale. Lisäksi käytettiin tätä tutkimusta varten tehtyjä kyselylomakkeita: Fyysinen toimintakyky-mittari, Palvelujen käyttö-mittari ja Kustannusmittari. Tutkimuksen toiseen vaiheen tulokset analysoitiin tilastollisilla menetelmillä. Potilaiden terveyteen liittyvä elämänlaatu parani ja kipu lievittyi leikkauksen jälkeen ja fyysinen toimintakyky lisääntyi toipumisaikana. Positiivisista muutoksista huolimatta potilaat kokivat ahdistusta samassa määrin kuin ennen leikkaustakin. Palvelujen käyttö vaihteli toipumisajan kuluessa ja potilaiden maksamissa kustannuksissa oli suuria vaihteluita. Fyysisen toimintakyvyn lisääntyminen ja kivun lieveneminen paransivat terveyteen liittyvää elämänlaatua. Sen sijaan huonompi elämänlaatu toipumisaikana oli yhteydessä suurempaan palvelujen käyttöön, kun taas kustannuksilla ei ollut yhteyttä elämänlaatuun. Potilaiden ominaispiirteet tulisi ottaa enemmän huomioon suunniteltaessa sopivaa leikkauksenjälkeistä hoitoa ja tukea. Potilaat tarvitsevat yksilöllisiä ohjeita, sillä monet taustatekijät (esim. ikä, sukupuoli, preoperatiivinen kipu, siviilisääty, ja leikkaustyyppi) vaikuttavat toipumiseen.

Fuzzy Principal Components Analysis

Due to the large number of characteristics, there is a need to extract the most relevant characteristicsfrom the input data, so that the amount of information lost in this way is minimal, and the classification realized with the projected data set is relevant with respect to the original data. In order to achieve this feature extraction, different statistical techniques, as well as the principal components analysis (PCA) may be used. This thesis describes an extension of principal components analysis (PCA) allowing the extraction ofa finite number of relevant features from high-dimensional fuzzy data and noisy data. PCA finds linear combinations of the original measurement variables that describe the significant variation in the data. The comparisonof the two proposed methods was produced by using postoperative patient data. Experiment results demonstrate the ability of using the proposed two methods in complex data. Fuzzy PCA was used in the classificationproblem. The classification was applied by using the similarity classifier algorithm where total similarity measures weights are optimized with differential evolution algorithm. This thesis presents the comparison of the classification results based on the obtained data from the fuzzy PCA.

Yrityksen sijaintipaikkapäätökseen vaikuttavat tekijät ja alueiden kilpailukyky Suomessa

Tämän diplomityön tavoite on luoda viitekehys kahdesta työn pääteorioista, jotka ovat: "liiketoiminnan ulkoiset menestystekijät" ja "alueiden kilpailukyky". Kummatkin teoriat sisältävät tekijöitä, joilla on vaikutusta yrityksen sijaintipaikkapäätökseen. Viitekehyksen pohjalta tarkastellaan kahta tutkimusaluetta: Landen seutua ja Kuuma-aluetta. Työn tuloksena syntyy kuva kummastakin tutkimusalueesta ja analyysi viitekehyksestä. Työn ensimmäisessä osassa käydään läpi aihealueen tutkimuksen taustaa ja mitä ongelmia tutkimuksissa on tullut esille. Senjälkeen esitellään kaikki liiketoiminnan ulkoiset menestystekijät. Alueiden kilpailukyvyn teoriaosuus täydentää viitekehyksen tekijät. Työn jälkimmäinen empiirinen osa perustuu lähdemateriaaliin, joka on kerätty haastatteluista, lehtiartikkeleista ja seminaareista koskien tutkimusalueita. Tutkimustuloksista selviää, että kummatkin tutkimusalueet ovat erilaisia ja niillä on omat avainklusterinsa ja menestyvät toimialansa. Viitekehys luotiin melko onnistuneesti. Lopulta selvisi, että se sopii hyvin aihealueen tutkimuksen laajentamiseen, mutta heikosti yksittäisenyrityksen sijaintipaikkapäätökseen.

Covariance Matrix Estimation and Mean-Variance Optimization in application to International Diversification

Tutkimus keskittyy kansainväliseen hajauttamiseen suomalaisen sijoittajan näkökulmasta. Tutkimuksen toinen tavoite on selvittää tehostavatko uudet kovarianssimatriisiestimaattorit minimivarianssiportfolion optimointiprosessia. Tavallisen otoskovarianssimatriisin lisäksi optimoinnissa käytetään kahta kutistusestimaattoria ja joustavaa monimuuttuja-GARCH(1,1)-mallia. Tutkimusaineisto koostuu Dow Jonesin toimialaindekseistä ja OMX-H:n portfolioindeksistä. Kansainvälinen hajautusstrategia on toteutettu käyttäen toimialalähestymistapaa ja portfoliota optimoidaan käyttäen kahtatoista komponenttia. Tutkimusaieisto kattaa vuodet 1996-2005 eli 120 kuukausittaista havaintoa. Muodostettujen portfolioiden suorituskykyä mitataan Sharpen indeksillä. Tutkimustulosten mukaan kansainvälisesti hajautettujen investointien ja kotimaisen portfolion riskikorjattujen tuottojen välillä ei ole tilastollisesti merkitsevää eroa. Myöskään uusien kovarianssimatriisiestimaattoreiden käytöstä ei synnytilastollisesti merkitsevää lisäarvoa verrattuna otoskovarianssimatrisiin perustuvaan portfolion optimointiin.

The effect of information and communication technology on global paper consumption

The objective of this thesis is to find out how information and communication technology affects the global consumption of printing and writing papers. Another objective is to find out, whether there are differences between paper grades in these effects. The empirical analysis is conducted by linear regression analysis using three sets of country-level panel data from 1990-2006. Data set of newsprint contains 95 countries, data set of uncoated woodfree paper 61 countries and data set of coated mechanical paper 42 countries. The material is based on paper consumption data of RISI’s Industry Statistics Database and on the information and communication technology data of GMID-database. Results indicate that number of Internet users has statistically significant negative effect on the consumption of newsprint and on the consumption of coated mechanical paper and number of mobile telephone users has positive effect on the consumptions of these papers. Results also indicate that information and communication technologies have only small effect on consumption of uncoated woodfree paper or no significant effect at all, but these results are more uncertain to some extent.

External Location Factors of Foreign Direct Investment in Russia – Finnish Perspective

Tämän diplomityön tavoitteena on selvittää, mitä alueellisia tekijöitä suomalaiset yritykset ottavat huomioon valitessaan sopivaa sijaintia suoralle investoinnille Venäjän sisällä. Muutamia yrityksen sisäisiä tekijöitä käytetään taustamuuttujina selittämään sijaintitekijöiden painotuksissa havaittavia eroja erilaisten yritysten välillä. Venäjän alueita vertaillaan lopuksi painotusten valossa. Työn ensimmäisessä osassa keskitytään suorien ulkomaisten investointien teoreettiseen taustaan. Aiempia tutkimuksia käydään läpi, jotta tekijät, joilla on havaittu olevan vaikutusta investointien sijoittumiseen maan sisällä, saadaan kartoitettua. Työn jälkimmäinen osa perustuu yrityskyselyn avulla kerättyyn empiiriseen aineistoon. Aineiston avulla selvitetään mitä tekijöitä suomalaisyritykset huomioivat sijaintipäätöstä tehdessään. Tulosten valossa on ilmeistä, että alueen markkinapotentiaali on suomalaisyrityksissä tärkein huomioitava tekijä investoinnin sijainnista päätettäessä. Myös infrastruktuuri ja kustannushyödyt vaikuttavat päätökseen. Erityyppisten yritysten painotukset ovat hyvin samanlaisia. Moskova ja Pietari vastaavat Venäjän alueista parhaiten suomalaisyritysten investoinnin sijainnille asettamia kriteerejä.

Analysis of outliers in electricity spot prices with exampleof New England and New Zealand markets

Electricity spot prices have always been a demanding data set for time series analysis, mostly because of the non-storability of electricity. This feature, making electric power unlike the other commodities, causes outstanding price spikes. Moreover, the last several years in financial world seem to show that ’spiky’ behaviour of time series is no longer an exception, but rather a regular phenomenon. The purpose of this paper is to seek patterns and relations within electricity price outliers and verify how they affect the overall statistics of the data. For the study techniques like classical Box-Jenkins approach, series DFT smoothing and GARCH models are used. The results obtained for two geographically different price series show that patterns in outliers’ occurrence are not straightforward. Additionally, there seems to be no rule that would predict the appearance of a spike from volatility, while the reverse effect is quite prominent. It is concluded that spikes cannot be predicted based only on the price series; probably some geographical and meteorological variables need to be included in modeling.

Factors Affecting Consumer’s Illicit Purchase of Copyrighted Digital Work

Peer-to-Peer (P2P) technology has revolutionized file exchange activities besides enhancing processing power distribution. As such, this technology which is nowadays made freely available to all internet users also imposes a threat as it enables the illegal distribution of copyrighted digital work. P2P technology continuously evolves in a greater pace than copyright legislation, leading to compatibility gaps between the applicability of copyright law and the illicit file sharing and downloading. Such issues give high incentives to consumers to practise piracy using P2P systems with a low perception of risk towards prosecution, leading to substantial losses for copyright owners. This study focuses on developing insights for content owners on consumer behaviour towards piracy in Finland, where quantitative analyses are assessed using a data set based on a survey conducted by the Helsinki Institute for IT. The research approach investigates the significance of three fundamental areas in relation to evaluate consumer behaviour as: environmental-related factors, innovation-related factors and consumer-related. each of these are integrates concepts derived in previous theoretical models such as the technology acceptance model, theory of reasoned action, theory of planned behaviour, the issue-risk-judgement model and the Hunt & Vitell’s model.