Capturing Weak Signals for Foresight Building

Tulevaisuuden hahmottamisen merkitys heikkojen signaalien avulla on korostunut viime vuosien aikana merkittävästi,koska yrityksen liiketoimintaympäristössä tapahtuvia muutoksia on ollut yhä vaikeampaa ennustaa historian perusteella. Liiketoimintaympäristössä monien muutoksien merkkejä on ollut nähtävissä, mutta niitä on ollut vaikea havaita. Heikkoja signaaleja tunnistamalla ja keräämällä sekä reagoimalla tilanteeseen riittävän ajoissa, on mahdollista saavuttaa ylivoimaista kilpailuetua. Kirjallisuustutkimus keskittyy heikkojen signaalien tunnistamisen haasteisiin liiketoimintaympäristöstä, signaalien ja informaation kehittymiseen sekä informaation hallintaan organisaatiossa. Kiinnostus näihin perustuu tarpeeseen määritellä heikkojen signaalien tunnistamiseen vaadittava prosessi, jonka avulla heikot signaalit voidaan huomioida M-real Oyj:n päätöksenteossa. Kirjallisuustutkimus osoittaa selvästi sen, että heikkoja signaaleita on olemassa ja niitä pystytään tunnistamaan liiketoimintaympäristöstä. Signaaleja voidaan rikastuttaa yrityksessä olevalla tietämyksellä ja hyödyntää edelleen päätöksenteossa. Vertailtaessa sekä kirjallisuustutkimusta että empiiristä tutkimusta tuli ilmi selkeästi tiedon moninaisuus; määrä,laatu ja tiedonsaannin oikea-aikaisuus päätöksenteossa. Tutkimuksen aikana kehittyi prosessimalli tiedon suodattamiselle, luokittelulle ja heikkojen signaalien tunnistamiselle. Työn edetessä prosessimalli kehittyi osaksi tässä työssä kehitettyä kokonaisuutta 'Weak Signal Capturing' -työkalua. Monistamalla työkalua voidaan kerätä heikkoja signaaleja eri M-realin liiketoiminnan osa-alueilta. Tietoja systemaattisesti kokoamalla voidaan kartoittaa tulevaisuutta koko M-realille.

Voir le monde à travers les lunettes du métacontraste: un modèle mathématique inspiré de la psychologie sociale

La théorie de l'autocatégorisation est une théorie de psychologie sociale qui porte sur la relation entre l'individu et le groupe. Elle explique le comportement de groupe par la conception de soi et des autres en tant que membres de catégories sociales, et par l'attribution aux individus des caractéristiques prototypiques de ces catégories. Il s'agit donc d'une théorie de l'individu qui est censée expliquer des phénomènes collectifs. Les situations dans lesquelles un grand nombre d'individus interagissent de manière non triviale génèrent typiquement des comportements collectifs complexes qui sont difficiles à prévoir sur la base des comportements individuels. La simulation informatique de tels systèmes est un moyen fiable d'explorer de manière systématique la dynamique du comportement collectif en fonction des spécifications individuelles. Dans cette thèse, nous présentons un modèle formel d'une partie de la théorie de l'autocatégorisation appelée principe du métacontraste. À partir de la distribution d'un ensemble d'individus sur une ou plusieurs dimensions comparatives, le modèle génère les catégories et les prototypes associés. Nous montrons que le modèle se comporte de manière cohérente par rapport à la théorie et est capable de répliquer des données expérimentales concernant divers phénomènes de groupe, dont par exemple la polarisation. De plus, il permet de décrire systématiquement les prédictions de la théorie dont il dérive, notamment dans des situations nouvelles. Au niveau collectif, plusieurs dynamiques peuvent être observées, dont la convergence vers le consensus, vers une fragmentation ou vers l'émergence d'attitudes extrêmes. Nous étudions également l'effet du réseau social sur la dynamique et montrons qu'à l'exception de la vitesse de convergence, qui augmente lorsque les distances moyennes du réseau diminuent, les types de convergences dépendent peu du réseau choisi. Nous constatons d'autre part que les individus qui se situent à la frontière des groupes (dans le réseau social ou spatialement) ont une influence déterminante sur l'issue de la dynamique. Le modèle peut par ailleurs être utilisé comme un algorithme de classification automatique. Il identifie des prototypes autour desquels sont construits des groupes. Les prototypes sont positionnés de sorte à accentuer les caractéristiques typiques des groupes, et ne sont pas forcément centraux. Enfin, si l'on considère l'ensemble des pixels d'une image comme des individus dans un espace de couleur tridimensionnel, le modèle fournit un filtre qui permet d'atténuer du bruit, d'aider à la détection d'objets et de simuler des biais de perception comme l'induction chromatique. Abstract Self-categorization theory is a social psychology theory dealing with the relation between the individual and the group. It explains group behaviour through self- and others' conception as members of social categories, and through the attribution of the proto-typical categories' characteristics to the individuals. Hence, it is a theory of the individual that intends to explain collective phenomena. Situations involving a large number of non-trivially interacting individuals typically generate complex collective behaviours, which are difficult to anticipate on the basis of individual behaviour. Computer simulation of such systems is a reliable way of systematically exploring the dynamics of the collective behaviour depending on individual specifications. In this thesis, we present a formal model of a part of self-categorization theory named metacontrast principle. Given the distribution of a set of individuals on one or several comparison dimensions, the model generates categories and their associated prototypes. We show that the model behaves coherently with respect to the theory and is able to replicate experimental data concerning various group phenomena, for example polarization. Moreover, it allows to systematically describe the predictions of the theory from which it is derived, specially in unencountered situations. At the collective level, several dynamics can be observed, among which convergence towards consensus, towards frag-mentation or towards the emergence of extreme attitudes. We also study the effect of the social network on the dynamics and show that, except for the convergence speed which raises as the mean distances on the network decrease, the observed convergence types do not depend much on the chosen network. We further note that individuals located at the border of the groups (whether in the social network or spatially) have a decisive influence on the dynamics' issue. In addition, the model can be used as an automatic classification algorithm. It identifies prototypes around which groups are built. Prototypes are positioned such as to accentuate groups' typical characteristics and are not necessarily central. Finally, if we consider the set of pixels of an image as individuals in a three-dimensional color space, the model provides a filter that allows to lessen noise, to help detecting objects and to simulate perception biases such as chromatic induction.

Supervised localimage feature detection

This thesis is about detection of local image features. The research topic belongs to the wider area of object detection, which is a machine vision and pattern recognition problem where an object must be detected (located) in an image. State-of-the-art object detection methods often divide the problem into separate interest point detection and local image description steps, but in this thesis a different technique is used, leading to higher quality image features which enable more precise localization. Instead of using interest point detection the landmark positions are marked manually. Therefore, the quality of the image features is not limited by the interest point detection phase and the learning of image features is simplified. The approach combines both interest point detection and local description into one phase for detection. Computational efficiency of the descriptor is therefore important, leaving out many of the commonly used descriptors as unsuitably heavy. Multiresolution Gabor features has been the main descriptor in this thesis and improving their efficiency is a significant part. Actual image features are formed from descriptors by using a classifierwhich can then recognize similar looking patches in new images. The main classifier is based on Gaussian mixture models. Classifiers are used in one-class classifier configuration where there are only positive training samples without explicit background class. The local image feature detection method has been tested with two freely available face detection databases and a proprietary license plate database. The localization performance was very good in these experiments. Other applications applying the same under-lying techniques are also presented, including object categorization and fault detection.

Competencia de trabajo en equipo: definición y categorización

La competencia de trabajo en equipo se impone a la individualización laboral. El cambio de estructura y proceso de las organizaciones de la sociedad actual ha generado un gran impacto en la nueva manera de trabajar. Las tareas han aumentado su dificultad, haciendo que su resolución individual sea imposible. Es por este motivo, que las organizaciones del trabajo reclaman, hoy más que nunca, la competencia transversal de trabajo en equipo. Este constructo (Competencia de Trabajo en Equipo) recientemente nuevo en las organizaciones ofrece definiciones y modelos de categorización subyacentes que necesitan hacerse oír en el panorama sociolaboral. En esta revisión de la literatura se analizan los 4 modelos más representativos de la competencia de trabajo en equipo, a través de los cuales se propone una definición de la competencia y una posible estructura de la categorización de la misma.

Perusterveydenhuollon ja erikoissairaanhoidon käytön seuranta ja ennakointi kuntanäkökulmasta

Follow-up of utilisation and prediction of primary health care and hospital care from the municipality point of view. Planning, follow-up, and evaluation of primary health care within municipality entail comprehensive information about factors that influence health. In addition to populationbased research, various statistical data and registries serve as sources of information. The present study examined utilisation of primary health care and hospital care with the existing databases, registries, and categorization of Diagnosis Related Groups (DRGs) from the municipality (purchaser) point of view. Research involving the cases of Paimio, Sauvo, and Turku as examples of municipalities pointed out that, even in the small municipalities, it is possible to assess and predict health services to be offered to the inhabitants by following databases and registries. Health-related databases and registries include a plenty of possible uses that have not adequately been employed at the level of municipality. Descriptive futures research and community analysis formed the framework of the study. Descriptive futures research may be used to establish predictions based on past developmental traditions, and quantitative time trend analyses may be employed to make estimations about future events. Community analysis will assist in making conclusions about population- based health care needs, in assessing the functionality or effectiveness of the health care system, and in appropriately targeting limited resources. The aim of the present study was to describe the health service profile so that the arrangements and planning of health services as well as the contract negotiations of hospital care become easier within municipalities. Another aim was to assess the application of Hilmo (registry for posting hospital care periods), Aitta and Sotka (statistical databases) for the purposes of resource planning in the procurement of hospital care. A third aim was to evaluate how the system of the DRGs adapts in the prediction of retaining health services within short (1-year), intermediate (5-year) and long range (10-15-year) intervals. The findings indicated that the follow-up of primary health care utilisation combined with follow-up of hospital care utilisation allows municipalities to plan and predict health services when databases are applied. Information about the past contacts with the databases has indicated that the health care culture and incidence of disease change rather slowly in the area of investigation. For the purposes of health care research, it is recommended that methods of application used in making predictions about health care utilisation need to be further developed

Intelligent Internet Data Searching

In this thesis author approaches the problem of automated text classification, which is one of basic tasks for building Intelligent Internet Search Agent. The work discusses various approaches to solving sub-problems of automated text classification, such as feature extraction and machine learning on text sources. Author also describes her own multiword approach to feature extraction and pres-ents the results of testing this approach using linear discriminant analysis based classifier, and classifier combining unsupervised learning for etalon extraction with supervised learning using common backpropagation algorithm for multilevel perceptron.

The REporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) Statement: Methods for Arriving at Consensus and Developing Reporting Guidelines.

OBJECTIVE: Routinely collected health data, collected for administrative and clinical purposes, without specific a priori research questions, are increasingly used for observational, comparative effectiveness, health services research, and clinical trials. The rapid evolution and availability of routinely collected data for research has brought to light specific issues not addressed by existing reporting guidelines. The aim of the present project was to determine the priorities of stakeholders in order to guide the development of the REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. METHODS: Two modified electronic Delphi surveys were sent to stakeholders. The first determined themes deemed important to include in the RECORD statement, and was analyzed using qualitative methods. The second determined quantitative prioritization of the themes based on categorization of manuscript headings. The surveys were followed by a meeting of RECORD working committee, and re-engagement with stakeholders via an online commentary period. RESULTS: The qualitative survey (76 responses of 123 surveys sent) generated 10 overarching themes and 13 themes derived from existing STROBE categories. Highest-rated overall items for inclusion were: Disease/exposure identification algorithms; Characteristics of the population included in databases; and Characteristics of the data. In the quantitative survey (71 responses of 135 sent), the importance assigned to each of the compiled themes varied depending on the manuscript section to which they were assigned. Following the working committee meeting, online ranking by stakeholders provided feedback and resulted in revision of the final checklist. CONCLUSIONS: The RECORD statement incorporated the suggestions provided by a large, diverse group of stakeholders to create a reporting checklist specific to observational research using routinely collected health data. Our findings point to unique aspects of studies conducted with routinely collected health data and the perceived need for better reporting of methodological issues.

ACACIA: an agent-based program for simulating behavior to reach long-term goals

We present ACACIA, an agent-based program implemented in Java StarLogo 2.0 that simulates a two-dimensional microworld populated by agents, obstacles and goals. Our program simulates how agents can reach long-term goals by following sensorial-motor couplings (SMCs) that control how the agents interact with their environment and other agents through a process of local categorization. Thus, while acting in accordance with this set of SMCs, the agents reach their goals through the emergence of global behaviors. This agent-based simulation program would allow us to understand some psychological processes such as planning behavior from the point of view that the complexity of these processes is the result of agent-environment interaction.

Web Client for Smart Messaging Exchange

TeliaSoneran älykkään viestintäjärjestelmän kehitysluonnoksella (SME) pilotoidaan prototyyppipalveluita, joiden avulla asiakkaat voivat välittää viestejä matkapuhelimilla sekä tietokoneilla. SME:n peruspalveluita voidaan käyttää SIP-standardin mukaisilla asiakasohjelmilla sekä SME:n omilla WAP- ja WWW-käyttöliittymillä. Käyttäjät voivat nähdä toistensa tilatiedon, muuttaa omaa tilatietoaan sekä lähettää SIP-pikaviestejä, sähköpostiviestejä ja tekstiviestejä. Käyttäjät voivat myös ylläpitää listaa yhteyshenkilöistään, vastaanottaa pikaviestejä ja selata vastaanotettuja viestejä. Diplomityössä käsitellään yleisesti SME-järjestelmän rakennetta ja paneudutaan tutkimaan työssä toteutetun SME:n WWW-asiakasohjelman toteutusta. Diplomityössä käydään läpi projektiin liittyviä standardeja, suosituksia, toteustekniikoita sekä palveluita. Lisäksi tarkastellaan työssä hyödynnettyjä ohjelmointirajapintoja, nykyisiä älypuhelimia sekä niiden Internet-selaimia, jotka rajoittavat WWW-asiakaspalvelun toteutuksessa käytettyjä toteutustekniikkavaihtoehtoja. Lopuksi esitellään toteutettujen ohjelmistojen sisäistä rakennetta ja toimintaa.

Cost allocation of corporate IT-services

Cost allocation is an inescapable problem in nearly every organization and in nearly every facet of accounting. Within large corporations there are several different types of units, like profit-making business units and non-profit service units. In order to evaluate the performance of the business units and to fund the operations of service units, the expenses of service production need to be allocated to the business units benefiting from the services.The objective of this thesis was to find good and fair allocating factors for the costs of corporate wide IT services. In order to reach this objective, the cost allocation process was studied in general and an overview of cost structure was established. All possible cost driver candidates were mapped and their good and bad properties were weighed. The cost allocation problem was handled separately according to organizational division of corporate IT department: infrastructure, administrative systems, sales system and e-business. The emphasis was on two largest cost groups: infrastructure costs and sales system costs. As a result of the study an allocation model is presented. It contains categorization of the costs, selected cost drivers and cost distributions for the current year.

Voimalaitoskattilan pyörivän regeneratiivisen ilman esilämmittimen suorituskyky ja mitoitus

Diplomityön tarkoituksena oli kehittää laskentaohjelma pyörivälle regeneratiiviselle lämmönsiirtimelle. Työ tehtiin Foster Wheeler Energia Oy:n Varkauden toimipisteessä. Työn ensimmäisessä osuudessa tutkittiin kirjallisuuden avulla regeneraattoreihin liittyvää teoriaa. Tämä osuus sisältää regeneratiivisen lämmönsiirron perusteita, regeneraattoreiden luokittelua, sektorijakoja, vuotoja, lämpöpintojen geometriaa ja likaantumista. Soveltavassa osassa tehtiin laskentaohjelma, jonka avulla voidaan laskea pyörivän regeneraattorin mitoitus- ja suorituskykylaskuja. Lisäksi ohjelman avulla voidaan laskea regeneraattorin lämpötilaprofiili.

The Dynamic Customer Portfolio Method in Customer Relationship Management

Tutkielman tavoitteena on määritellä keskeiset ja sopivat asiakasportfoliomallit ja asiakasmatriisit asiakassuhteen määrittämiseen. Tutkimus keskittyy asiakassuhteen arvottamiseen ja avainasiakkaiden määrittämiseen kohdeyrityksessä. Keskeisimmät ja sopivimmat asiakasportfliomallit huomioidaan asiakkaiden arvioinnissa. Tutkielman teoriaosassa esitellään tunnetuimmat ja käytetyimmät asiakasportfoliomallit ja matriisit alan kirjallisuuden perusteella. Tämän lisäksi asiakasportfoliomalleihin yhdistetään näkökulmia suhdemarkkinoinnin, asiakkuuksien johtamisen ja tuoteportfolioiden teorioista. Keskeisimmät kirjallisuuden lähteet ovat johtamisen ja markkinoinnin alalta. Tutkielman empiriaosassa esitellään kohdeyritys ja sen tämän hetkinen asiakassuhteiden johtamiskäytäntö. Lisäksi tehdään parannusehdotuksia kohdeyrityksen nykyiseen asiakassuhteiden arvottamismenetelmään jotta asiakassuhteiden arvon laskeminen vastaisi mahdollisimman hyvin kohdeyrityksen nykyisiä tarpeita. Asiakassuhteen arvon määrittämiseksi käytetään myös fokusryhmähaastattelua. Avainasiakkaat määritellään ja tilannetta havainnollistetaan sijoittamalla avainasiakkaat asiakasportfolioon.

MRO-tuotteiden hankintaprosessin tehostaminen toimittajayhteistyön avulla

Tutkimuksen tavoitteena oli selvittää MRO-tuotteiden hankinnassa käytettäviä liiketoimintasuhdemuotoja sekä huomioitavia asioita siirryttäessä kohti yhteistyötä toimittajan kanssa. Tutkimus toteutettiin kvalitatiivisena case-tutkimuksena, jossa aineiston kokoaminen pohjautui haastatteluihin, sisäisiin dokumentaatioihin sekä osallistuvaan havainnointiin. Analysointi tapahtui teoreettisen tuoteluokittelun pohjalta sekä luokitteluryhmien tarkastelulla käytännössä. Tutkimuksen keskeisimpänä tuloksena on havainto yhteistyösuhteiden käytön lisääntymisestä vakiotuotteiden hankinnassa. Tämä johtuu pyrkimyksestä suorittaa ko. tuotteiden hankinta mahdollisimman vähin resurssein, jolloin hankintojen huomio voidaan keskittää kriittisempiin tuotteisiin. MRO-tuotteissa käytettäviä yleisimpiä liiketoimintasuhteita ovat kilpailutus sekä vuosi- ja puitesopimukset. Ylläpitosopimukset ja kumppanuus-suhteet ovat mahdollisia, kun tuotteiden strateginen merkitys nousee merkittäväksi ja osapuolten välillä vallitsee korkea luottamus.

From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.

Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra-categorical auditory discrimination for untrained items follows the temporal hierarchy and transpires in a late stage of semantic processing. On the other hand, correct categorization of individually trained stimuli occurs earlier, during a period contemporaneous with human vs. animal vocalization discrimination, and involves a parallel semantic pathway requiring expertise.

Facing Structural Disadvantage: The Role of Ingroup Connectedness

This thesis focuses on the social-psychological factors that help coping with structural disadvantage, and specifically on the role of cohesive ingroups and the sense of connectedness and efficacy they entail in this process. It aims to complement existing group-based models of coping that are grounded in a categorization perspective to groups and consequently focus exclusively on the large-scale categories made salient in intergroup contexts of comparisons. The dissertation accomplishes this aim through a reconsideration of between-persons relational interdependence as a sufficient and independent antecedent of a sense of groupness, and the benefits that a sense of group connectedness in one's direct environment, regardless of the categorical or relational basis of groupness, might have in the everyday struggles of disadvantaged group members. The three empirical papers aim to validate this approach, outlined in the first theoretical introduction, by testing derived hypotheses. They are based on data collected with youth populations (15-30) from three institutions in French-speaking Switzerland within the context of a larger project on youth transitions. Methods of data collection are paper-pencil questionnaires and in-depth interviews with a selected sub-sample of participants. The key argument of the first paper is that members of socially disadvantaged categories face higher barriers to their life project and that a general sense of connectedness, either based on categorical identities or other proximal groups and relations, mitigates the feeling of powerlessness associated with this experience. The second paper develops and tests a model that defines individual needs satisfaction as antecedent of self-group bonds and the efficacy beliefs derived from these intragroup bonds as the mechanism underlining the role of ingroups in coping. The third paper highlights the complexities that might be associated with the construction of a sense of groupness directly from intergroup comparisons and categorization-based disadvantage, and points out a more subtle understanding of the processes underling the emergence of groupness out of the situation of structural disadvantage. Overall, the findings confirm the central role of ingroups in coping with structural disadvantage and the importance of an understanding of groupness and its role that goes beyond the dominant focus on intergroup contexts and categorization processes.