Modeling and measuring organizational renewal capability

Globalization and new information technologies mean that organizations have to face world-wide competition in rapidly transforming, unpredictable environments, and thus the ability to constantly generate novel and improved products, services and processes has become quintessential for organizational success. Performance in turbulent environments is, above all, influenced by the organization's capability for renewal. Renewal capability consists of the ability of the organization to replicate, adapt, develop and change its assets, capabilities and strategies. An organization with a high renewal capability can sustain its current success factors while at the same time building new strengths for the future. This capability does not only mean that the organization is able to respond to today's challenges and to keep up with the changes in its environment, but also that it can actas a forerunner by creating innovations, both at the tactical and strategic levels of operation and thereby change the rules of the market. However, even though it is widely agreed that the dynamic capability for continuous learning, development and renewal is a major source of competitive advantage, there is no widely shared view on how organizational renewal capability should be defined, and the field is characterized by a plethora of concepts and definitions. Furthermore,there is a lack of methods for systematically assessing organizational renewal capability. The dissertation aims to bridge these gaps in the existing research by constructing an integrative theoretical framework for organizational renewal capability and by presenting a method for modeling and measuring this capability. The viability of the measurement tool is demonstrated in several contexts, andthe framework is also applied to assess renewal in inter-organizational networks. In this dissertation, organizational renewal capability is examined by drawing on three complimentary theoretical perspectives: knowledge management, strategic management and intellectual capital. The knowledge management perspective considers knowledge as inherently social and activity-based, and focuses on the organizational processes associated with its application and development. Within this framework, organizational renewal capability is understood as the capacity for flexible knowledge integration and creation. The strategic management perspective, on the other hand, approaches knowledge in organizations from the standpoint of its implications for the creation of competitive advantage. In this approach, organizational renewal is framed as the dynamic capability of firms. The intellectual capital perspective is focused on exploring how intangible assets can be measured, reported and communicated. From this vantage point, renewal capability is comprehended as the dynamic dimension of intellectual capital, which consists of the capability to maintain, modify and create knowledge assets. Each of the perspectives significantly contributes to the understanding of organizationalrenewal capability, and the integrative approach presented in this dissertationcontributes to the individual perspectives as well as to the understanding of organizational renewal capability as a whole.

Populating ACT-R's Declarative Memory with Internet Statistics

Decision situations are often characterized by uncertainty: we do not know the values of the different options on all attributes and have to rely on information stored in our memory to decide. Several strategies have been proposed to describe how people make inferences based on knowledge used as cues. The present research shows how declarative memory of ACT-R models could be populated based on internet statistics. This will allow to simulate the performance of decision strategies operating on declarative knowledge based on occurrences and co-occurrences of objects and cues in the environment.

Reusable Bluetooth Networking Component for Symbian Operating System

Tässä diplomityössä käsitellään eri näkökulmia ohjelmistojen uudelleenkäyttöön sekä esitellään perustiedot langattomiin laitteisiin käytettävästä Symbian-käyttöjärjestelmästä ja langattomasta Bluetooth-teknologiasta. Työn käytännön osuudessa suunniteltiin ja toteutettiin uudelleenkäytettävä Bluetooth-ohjelmistokomponentti Symbiankäyttöjärjestelmälle. Ohjelmistojen uudelleenkäytön edut ovat erittäin selkeitä. Uudelleenkäytettävät ohjelmistokomponentit parantavat ohjelmiston laatua ja suorituskykyä. Ohjelmistotuotteiden tuotekehityssykliä voidaan lyhentää merkittävästi ja kehitystyön kokonaiskustannuksia voidaan alentaa tehokkaalla uudelleenkäyttöohjelmalla. Kuitenkin uudelleenkäytöllä on myös esteitä, esimerkkeinä näistä ovat mm. resurssien puute, koulutus sekä uudelleenkäytön vastaiset asenteet. Bluetooth-teknologia on kypsynyt viimeisen kahden vuoden aikana, kun markkinoille on tullut yhä enemmän Bluetooth-laitteita ja niitä käyttäviä sovelluksia. Kehitetty komponentti tarjoaa perustoiminnallisuudet Bluetooth-yhteyksien muodostamiselle ja datan siirtämiselle laitteiden välillä.

Impact of model complexity on cross-temporal transferability in Maxent species distribution models: An assessment using paleobotanical data

Maximum entropy modeling (Maxent) is a widely used algorithm for predicting species distributions across space and time. Properly assessing the uncertainty in such predictions is non-trivial and requires validation with independent datasets. Notably, model complexity (number of model parameters) remains a major concern in relation to overfitting and, hence, transferability of Maxent models. An emerging approach is to validate the cross-temporal transferability of model predictions using paleoecological data. In this study, we assess the effect of model complexity on the performance of Maxent projections across time using two European plant species (Alnus giutinosa (L.) Gaertn. and Corylus avellana L) with an extensive late Quaternary fossil record in Spain as a study case. We fit 110 models with different levels of complexity under present time and tested model performance using AUC (area under the receiver operating characteristic curve) and AlCc (corrected Akaike Information Criterion) through the standard procedure of randomly partitioning current occurrence data. We then compared these results to an independent validation by projecting the models to mid-Holocene (6000 years before present) climatic conditions in Spain to assess their ability to predict fossil pollen presence-absence and abundance. We find that calibrating Maxent models with default settings result in the generation of overly complex models. While model performance increased with model complexity when predicting current distributions, it was higher with intermediate complexity when predicting mid-Holocene distributions. Hence, models of intermediate complexity resulted in the best trade-off to predict species distributions across time. Reliable temporal model transferability is especially relevant for forecasting species distributions under future climate change. Consequently, species-specific model tuning should be used to find the best modeling settings to control for complexity, notably with paleoecological data to independently validate model projections. For cross-temporal projections of species distributions for which paleoecological data is not available, models of intermediate complexity should be selected.

Influence of Equipment Operation and Performance Deterioration on Power Plant Economy.

Pysyäkseen kilpailukykyisenä vapautuneilla sähkömarkkinoilla on voimalaitoksen energiantuotantokustannusten oltava mahdollisimman matalia, tinkimättä kuitenkaan korkeasta käytettävyydestä. Polttoaineen energiasisällön mahdollisimman hyvä hyödyntäminen on ratkaisevan tärkeää voimalaitoksen kannattavuudelle. Polttoainekustannusten osuus on konvektiivisilla laitoksilla yleensä yli puolet koko elinjakson kustannuksista. Kun vielä päästörajat tiukkenevat koko ajan, korostuu polttoaineen korkea hyötykäyttö entisestään. Korkea energiantuotannon luotettavuus ja käytettävyys ovat myös elintärkeitä pyrittäessä kustannusten minimointiin. Tässä työssä on käyty läpi voimalaitoksen kustannuksiin vaikuttavia käsitteitä, kuten hyötysuhdetta, käytettävyyttä, polttoaineen hintoja, ylös- ja alasajoja ja tärkeimpiä häviöitä. Ajostrategiassa ja poikkeamien hallinnassa pyritään hyvään hyötysuhteeseen ja alhaisiin päästöihin joka käyttötilanteessa. Lisäksi on tarkasteltu tiettyjen suureiden, eli höyryn lämpötilan ja paineen, savukaasun hapen pitoisuuden, savukaasun loppulämpötilan, sekä lauhduttimen paineen poikkeamien vaikutusta ohjearvostaan energiantuotantokustannuksiin. Happi / hiilimonoksidi optimoinnissa on otettu huomioon myös pohjatuhkan palamattomat.

Protocol Specific Embedded Operating System

Sulautettujen järjestelmien määrä kuten niiden sisältämä älykkyyskin ovat viime vuosina kasvaneet merkittävästi. Sulautettujen ohjelmistojen yleistymistä ja monipuolistumista on edesauttanut sulautettujen laitteistojen prosessointitehon merkittävä kehittyminen, jonka myötä entistä vaativampien ohjelmistojen totetuttaminen sulautetusti on mahdollistunut. Seuraavana sulautettujen järjestelmien kehitysaskeleena on nähtävissä järjestelmien kommunikointikyvyn paraneminen ja siten uusien ja uudentyyppisten sulautettujen ratkaisujen toteuttaminen. VTT on päättänyt tutkia sulautettujen järjestelmien kommunikointia ja kehittää sulautettun protokolla-alustan. Tutkimuksen perusta on CVOPS protokollajärjestelmä, jota jatkokehittämällä pyritään toteuttamaan sulautettu protokollajärjestelmä, µCVOPS. Tässä diplomityössä esitetään kommunikaation sulautetulle järjestelmälle asettamia vaatimuksia, järjestelmän suunnittelu ja prototyypitys sulautetulla laitteistolla. Prototyypitykseen on käytetty sulautettua DragonBall mikrokontrolleria jonka käyttöjärjestelmänä käytettiin sulautettua Linux:a. Tälle alustalle on tehty CVOPS:sta modifioitu versio, jolla µCVOPS:ia pystytään simuloimaan.

Characterization Method for Comminution Behavior of Limestone and Fuel Ash in a Circulating Fluidized Bed Boiler

Työn tavoite oli kehittää karakterisointimenetelmät kalkkikiven ja polttoaineen tuhkan jauhautumisen ennustamiselle kiertoleijukattilan tulipesässä. Kiintoainekäyttäytymisen karakterisoinnilla ja mallintamisella voidaan tarkentaa tulipesän lämmönsiirron ja tuhkajaon ennustamista. Osittain kokeelliset karakterisointimenetelmät perustuvat kalkkikiven jauhautumiseen laboratoriokokoluokan leijutetussa kvartsiputkireaktorissa ja tuhkan jauhatumiseen rotaatiomyllyssä. Karakterisointimenetelmät ottavat huomioon eri-laiset toimintaolosuhteet kaupallisen kokoluokan kiertoleijukattiloissa. Menetelmät kelpoistettiin kaupallisen kokoluokan kiertoleijukattiloista mitattujen ja fraktioittaisella kiintoainemallilla mallinnettujen taseiden avulla. Kelpoistamistaseiden vähäisyydestä huolimatta karakterisointimenetelmät arvioitiin virhetarkastelujen perusteella järkeviksi. Karakterisointimenetelmien kehittämistä ja tarkentamista tullaan jatkamaan.

Spontaneous Speech and Emotional Response modeling based on One-class classifier oriented to Alzheimer Disease diagnosis

The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.

Financial Modeling to Support Organizational Control

Tutkimus tarkastelee taloudellisia mallintamismahdollisuuksia metsäteollisuuden liiketoimintayksikössä. Tavoitteena on suunnitella ja luoda taloudellinen malli liiketoimintayksikölle, jonka avulla sen tuloksen analysoiminen ja ennustaminen on mahdollista. Tutkimusta tarkastellaan konstruktiivisen tutkimusmenetelmän avulla. Teoreettinen viitekehys tarkastelee olemassa olevan informaation muotoilemista keskittyen tiedon jalostamisen tarpeisiin, päätöksenteon asettamiin vaatimuksiin sekä mallintamiseen. Toiseksi, teoria esittää informaatiolle asetettavia vaatimuksia organisatorisen ohjauksen näkökulmasta.Empiirinen tieto kerätään osallistuvan havainnoinnin avulla hyödyntäen epävirallisia keskusteluja, tietojärjestelmiä ja laskentatoimen dokumentteja. Tulokset osoittavat, että liikevoiton ennustaminen mallin avulla on vaikeaa, koska taustalla vaikuttavien muuttujien määrä on suuri. Tästä johtuen malli täytyykin rakentaa niin, että se tarkastelee liikevoittoa niin yksityiskohtaisella tasolla kuin mahdollista. Testauksessa mallin tarkkuus osoittautui sitä paremmaksi, mitä tarkemmalla tasolla ennustaminen tapahtui. Lisäksi testaus osoitti, että malli on käyttökelpoinen liiketoiminnan ohjauksessa lyhyellä aikavälillä. Näin se luo myös pohjan pitkän aikavälin ennustamiselle.

Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling.

How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model's prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.

System Investigation for Hybrid Electric Vehicle

A hybrid electric vehicle is a fast-growing concept in the field of vehicle industry. Nowadays two global problems make manufactures to develop such systems. These problems are: the growing cost of a fuel and environmental pollution. Also development of controlled electric drive with high control accuracy and reliability allows improving of vehicle drive characteristics. The objective of this Diploma Thesis is to investigate the possibilities of electrical drive application for new principle of parallel hybrid vehicle system. Electric motor calculations, selection of most suitable control system and other calculations are needed. This work is not final work for such topic. Further investigation with more precise calculations, modeling, measurements and cost calculations are needed to answer the question if such system is efficient.

Disseny i implementació d'un clúster high performance computing

Clúster format per una màquina principal HEAD Node més 19 nodes de càlcul de la gama SGI13 Altix14 XE Servers and Clusters, unides en una topologia de màster subordinat, amb un total de 40 processadors Dual Core i aproximadament 160Gb de RAM.

Russian Enterprise Restructuring - the Effect of Privatisation and Market Liberalisation on the Performance of Large Enterprises

The fundamental question in the transitional economies of the former Eastern Europe and Soviet Union has been whether privatisation and market liberalisation have had an effect on the performance of former state-owned enterprises. This study examines the effect of privatisation, capital market discipline, price liberalisation and international price exposure on the restructuring of large Russian enterprises. The performance indicators are sales, profitability, labour productivity and stock market valuations. The results do not show performance differences between state-owned and privatised enterprises. On the other hand, the expansion of the de novo private sector has been strong. New enterprises have significantly higher sales growth, profitability and labour productivity. However, the results indicate a diminishing effect of ownership. The international stock market listing has a significant positive effect on profitability, while the effect of domestic stock market listing is insignificant. The international price exposure has a significant positive increasing effect on profitability and labour productivity. International enterprises have higher profitability only when operating on price liberalised markets, however. The main results of the study are strong evidence on the positive effects of international linkages on the enterprise restructuring and the higher than expected role of new enterprises in the Russian economy.

Fischer-Tropsch Slurry Bubble Column Reactor Modeling

The literature part of the work reviews overall Fischer-Tropsch process, Fischer-Tropsch reactors and catalysts. Fundamentals of Fischer-Tropsch modeling are also presented. The emphasis is on the reactor unit. Comparison of the reactors and the catalysts is carried out to choose the suitable reactor setup for the modeling work. The effects of the operation conditions are also investigated. Slurry bubble column reactor model operating with cobalt catalyst is developed by taking into account the mass transfer of the reacting components (CO and H2) and the consumption of the reactants in the liquid phase. The effect of hydrostatic pressure and the change in total mole flow rate in gas phase are taken into account in calculation of the solubilities. The hydrodynamics, reaction kinetics and product composition are determined according to literature. The cooling system and furthermore the required heat transfer area and number of cooling tubes are also determined. The model is implemented in Matlab software. Commercial scale reactor setup is modeled and the behavior of the model is investigated. The possible inaccuraries are evaluated and the suggestions for the future work are presented. The model is also integrated to Aspen Plus process simulation software, which enables the usage of the model in more extensive Fischer-Tropsch process simulations. Commercial scale reactor of diameter of 7 m and height of 30 m was modeled. The capacity of the reactor was calculated to be about 9 800 barrels/day with CO conversion of 75 %. The behavior of the model was realistic and results were in the right range. The highest uncertainty to model was estimated to be caused by the determination of the kinetic rate.

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal