On the innovation capacity of technologyrelated knowledge-intensive business services. A case study of the technology and engineering consulting (TEC) sector in Singapore

Even though the research on innovation in services has expanded remarkably especially during the past two decades, there is still a need to increase understanding on the special characteristics of service innovation. In addition to studying innovation in service companies and industries, research has also recently focused more on services in innovation, as especially the significance of so-called knowledge intensive business services (KIBS) for the competitive edge of their clients, othercompanies, regions and even nations has been proved in several previous studies. This study focuses on studying technology-based KIBS firms, and technology andengineering consulting (TEC) sector in particular. These firms have multiple roles in innovation systems, and thus, there is also a need for in-depth studies that increase knowledge about the types and dimensions of service innovations as well as underlying mechanisms and procedures which make the innovations successful. The main aim of this study is to generate new knowledge in the fragmented research field of service innovation management by recognizing the different typesof innovations in TEC services and some of the enablers of and barriers to innovation capacity in the field, especially from the knowledge management perspective. The study also aims to shed light on some of the existing routines and new constructions needed for enhancing service innovation and knowledge processing activities in KIBS companies of the TEC sector. The main samples of data in this research include literature reviews and public data sources, and a qualitative research approach with exploratory case studies conducted with the help of the interviews at technology consulting companies in Singapore in 2006. These complement the qualitative interview data gathered previously in Finland during a larger research project in the years 2004-2005. The data is also supplemented by a survey conducted in Singapore. The respondents for the survey by Tan (2007) were technology consulting companies who operate in the Singapore region. The purpose ofthe quantitative part of the study was to validate and further examine specificaspects such as the influence of knowledge management activities on innovativeness and different types of service innovations, in which the technology consultancies are involved. Singapore is known as a South-east Asian knowledge hub and is thus a significant research area where several multinational knowledge-intensive service firms operate. Typically, the service innovations identified in the studied TEC firms were formed by several dimensions of innovations. In addition to technological aspects, innovations were, for instance, related to new client interfaces and service delivery processes. The main enablers of and barriers to innovation seem to be partly similar in Singaporean firms as compared to the earlier study of Finnish TEC firms. Empirical studies also brought forth the significance of various sources of knowledge and knowledge processing activities as themain driving forces of service innovation in technology-related KIBS firms. A framework was also developed to study the effect of knowledge processing capabilities as well as some moderators on the innovativeness of TEC firms. Especially efficient knowledge acquisition and environmental dynamism seem to influence the innovativeness of TEC firms positively. The results of the study also contributeto the present service innovation literature by focusing more on 'innovation within KIBs' rather than 'innovation through KIBS', which has been the typical viewpoint stressed in the previous literature. Additionally, the study provides several possibilities for further research.

Multi-purpose infrastructure for delivering and supporting mobile context-aware applications

The use of contextual information in mobile devices is receiving increasing attention in mobile and ubiquitous computing research. An important requirement for mobile development today is that devices should be able to interact with the context. In this paper we present a series of contributions regarding previous work on context-awareness. In the first place, we describe a client-server architecture that provides a mechanism for preparing target non context-aware applications in order to be delivered as context-aware applications in a semi-automatic way. Secondly, the framework used in the server to instantiate specific components for context-awareness, the Implicit Plasticity Framework, provides independence from the underlying mobile technology used in client device, as it is shown in the case studies presented. Finally, proposed infrastructure deals with the interaction among different context constraints provided by diverse sensors. All of these contributions are extensions to the infrastructure based on the Dichotomic View of plasticity, which now offers multi-purpose support.

A logic programming framework for possibilistic argumentation: formalization and logical properties

In the last decade defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning. The logic programming paradigm has shown to be particularly useful for developing different argument-based frameworks on the basis of different variants of logic programming which incorporate defeasible rules. Most of such frameworks, however, are unable to deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper presents Possibilistic Logic Programming (P-DeLP), a new logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty. Such features are formalized on the basis of PGL, a possibilistic logic based on G¨odel fuzzy logic. One of the applications of P-DeLP is providing an intelligent agent with non-monotonic, argumentative inference capabilities. In this paper we also provide a better understanding of such capabilities by defining two non-monotonic operators which model the expansion of a given program P by adding new weighed facts associated with argument conclusions and warranted literals, respectively. Different logical properties for the proposed operators are studied

Component Architecture for Context-Aware Applications

Mobiililaitteisiin tehdyt sovellukset ovat nykyään laajassa käytössä. Mobiilisovellukset tarjoavat käyttäjälleen usein tietyn ennalta määritellyn toiminnallisuuden eivätkä ne pysty mukautumaan vaihtelevaan käyttöympäristöönsä. Jos sovellus olisi tietoinen käyttöympäristöstään ja sen muutoksista, se voisi tarjota käyttäjälleen tilanteeseen sopivia ominaisuuksia. Käyttöympäristöstään tietoiset hajautetut sovellukset tarvitsevat kuitenkin huomattavasti perinteisiä sovelluksia monimutkaisemman arkkitehtuurin toimiakseen. Tässä työssä esitellään hajautetuille ja kontekstitietoisille sovelluksille tarkoitettu ohjelmistoarkkitehtuuri. Työ perustuu Oulun yliopiston CAPNET-tutkimusprojektissa kehitettyyn, mobiilisovelluksille tarkoitettuun arkkitehtuuriin. Tämän työn tarkoituksena on tarjota ratkaisuja niihin puutteisiin, jotka tulivat esille CAPNET-arkkitehtuurin kehitys- ja testausvaiheessa. Esimerkiksi arkkitehtuurin komponenttien määrittelyä tulisi tarkentaa ja ne tulisi jakaa horisontaalisiin kerroksiin niiden ominaisuuksien ja alustariippuvuuden mukaisesti. Työssä luodaan katsaus olemassa oleviin teknologioihin jotka tukevat hajautettujen ja kontekstitietoisten järjestelmien kehittämistä. Myös niiden soveltumista CAPNET-arkkitehtuuriin analysoidaan. Työssä esitellään CAPNET-arkkitehtuuri ja ehdotetaan uutta arkkitehtuuria ja komponenttien kerrosjaottelua. Ehdotuksessa arkkitehtuurin komponentit ja järjestelmän rakenne määritellään ja mallinnetaan UML-menetelmällä. Työn tuloksena on arkkitehtuurimäärittely, joka jakaa nykyisen arkkitehtuurin komponentit kerroksiin. Komponenttien rajapinnat on määritelty selkeästi ja tarkasti. Työ tarjoaa myös projektiryhmälle hyvän lähtökohdan uuden arkkitehtuurin suunnittelulle ja toteuttamiselle.

Wireless Network Technologies and Terminals for Mobile Applications

Viimeaikainen langattomien teknologioiden kehitys ja evoluutio johtaa uusiin mahdollisuuksiin business-to-business-teollisuussovellusten laatimisessa. Tämän työn tavoite on tutkia teknisten puitteiden ja perustan sekä teknologisen ennustamisen prosessia innovatiivisten langattomien sovellusten kehitysprosessissa. Työ keskittyy langattomiin teknologioihin - verkkoihin ja päätelaitteisiin. Työssä selvitetään saatavilla olevia ja tulevia langattomia verkkoteknologioita ja mobiilipäätelaitteita, arvioidaan niiden päätyypit, ominaisuudet, rajoitteet ja kehitystrendit, sekä määritellään pääasialliset tekniset ominaisuudet, jotka on huomioitava luotaessa langatonta ratkaisua. Tämä tieto vedetään yhteen jatkokäyttöä varten langattomien sovellusten päätelaitetietokantaan rakentamisen aikana. Työ tarjoaa kuvauksen päätelaitetietokannan suunnittelusta ja rakentamisesta sekä tutkii tietokantaa innovatiivisen esimerkkisovelluksen - Reaaliaikaisen On-Line Asiakaspalvelun - avulla.

Data Collection Agent Framework

Ohjelmistoteollisuudessa pitkiä ja vaikeita kehityssyklejä voidaan helpottaa käyttämällä hyväksi ohjelmistokehyksiä (frameworks). Ohjelmistokehykset edustavat kokoelmaa luokkia, jotka tarjoavat yleisiä ratkaisuja tietyn ongelmakentän tarpeisiin vapauttaen ohjelmistokehittäjät keskittymään sovelluskohtaisiin vaatimuksiin. Hyvin suunniteltujen ohjelmistokehyksien käyttö lisää suunnitteluratkaisujen sekä lähdekoodin uudelleenkäytettävyyttä enemmän kuin mikään muu suunnittelulähestymistapa. Tietyn kohdealueen tietämys voidaan tallentaa ohjelmistokehyksiin, joista puolestaan voidaan erikoistaa viimeisteltyjä ohjelmistotuotteita. Tässä diplomityössä kuvataan ohjelmistoagentteihin (software agents) perustuvaa ohjelmistokehyksen suunnittelua toteutusta. Pääpaino työssä on vaatimusmäärittelyä vastaavan suunnitelman sekä toteutuksen kuvaaminen ohjelmistokehykselle, josta voidaan erikoistaa erilaiseen tiedonkeruuseen kykeneviä ohjelmistoja Internet ympäristöön. Työn kokeellisessa osuudessa esitellään myös esimerkkisovellus, joka perustuu työssä kehitettyyn ohjelmistokehykseen.

Wireless E-Business Applications in ICT Industry

Sähköisen liiketoiminnan sovelluksia on voitu toistaiseksi käyttää useimmissa tapauksissa vain langallisen yhteyden kautta. Uudet langattomat teknologiat, jotka ovat kehittyneet nopeasti muutaman viimeisen vuoden aikana, mahdollistavat näiden sovellusten käytön ajasta ja paikasta riippumatta. Tämän työn tavoitteena oli tutkia langattomien sähköisen liiketoiminnan sovellusten käyttöä ja hyötyjä tieto- ja viestintäteollisuudessa. Työssä keskitytään tutkimaan tätä tietotekniikan evoluutioaskelta yksittäisen yrityksen kannalta: rajoittuen omassa toiminnassa käytettäviin sovelluksiin. Tutkimus luo viitekehyksen mobiilisuuden evoluutioon, uuden tietotekniikan vaikutuksiin ja hyötyihin sekä tarkemmin langattomiin sähköisen liiketoiminnan sovelluksiin. Tätä viitekehystä käytetään analysoitaessa nykyistä käyttöä tutkimuksen kohteena olevissa yrityksissä. Tutkimuksen johtopäätökset niin nykyisestä käytöstä kuin myös tulevasta ovat syntyneet viitekehyksen, nykyisen käytön, sekä tehtyjen haastattelujen pohjalta.

Wireless Applications Evaluation and Development Process: Case -Paper Industry Logistics

Sähköisen liiketoiminnan ja mobiliteetin konvergenssi yhdessä teknologisen innovaation kiihtyvän vauhdin kanssa ovat saaneet aikaan kiinnostusta langattomia liiketoimintaratkaisuja kohtaan. Tämän diplomityön tavoitteena oli tutkia sähköisen liiketoiminnan langattomien sovellusten arviointi- ja kehitysprosessia. Työ keskittyy tarkastelemaan paperiteollisuuden toimitusketjun langatonta seurantaa. Tutkimuksessa esitetään langattoman sähköisen liiketoiminnan määritelmä, kuvaillaan langattomuuden eri sovellusalueita ja sovellusten arviointi- ja kehitysprosessin strategisia sekä teknologisia ulottuvuuksia. Työ luo viitekehyksen, jonka avulla tarkastella langattomien teknologioiden merkitystä logistiikassa. Tutkimuksen merkittävin tulos on prosessimalli sovellusten arvioimiseksi ja kehittämiseksi. Mallilla kehitetty langaton sovellus osoittautui tarkastelussa hyödylliseksi toimitusketjun hallinnassa.

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

Error models in hydrogeology applications

Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.

Defining a framework model to determine total costs of managed desktops using ITIL best practices

In modern day organizations there are an increasing number of IT devices such as computers, mobile phones and printers. These devices can be located and maintained by using specialized IT management applications. Costs related to a single device accumulate from various sources and are normally categorized as direct costs like hardware costs and indirect costs such as labor costs. These costs can be saved in a configuration management database and presented to users using web based development tools such as ASP.NET. The overall costs of IT devices during their lifecycle can be ten times higher than the actual purchase price of the product and ability to define and reduce these costs can save organizations noticeable amount of money. This Master’s Thesis introduces the research field of IT management and defines a custom framework model based on Information Technology Infrastructure Library (ITIL) best practices which is designed to be implemented as part of an existing IT management application for defining and presenting IT costs.

Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.

Diseño e implementación de un framework de presentación

Análisis, diseño e implementación de un framework de presentación para aplicaciones web 'thin client' desarrolladas en la plataforma Java EE.

The Design of a Software Lifecycle Management Framework to a Configuration Management System

Keeping track of software assets and managing software installations in IT environments can be a hard endeavor, especially when the size and diversity of the environment grows. How to install and uninstall software efficiently and cost effectively? Are there too few or too many software licenses purchased? If installed, is the software actually in use? Software Asset Management (SAM) is a process that involves managing and optimizing the purchase, deployment, maintenance, utilization, and disposal of software applications within an organization. This master’s thesis describes a special Software Lifecycle Management Framework to provide solutions to the multitude of challenges within SAM. The main objectives when designing the framework was to provide a set of tools to control the software assets during their entire lifecycle while trying to minimize the costs related to owning and managing them.

RTOS Framework for Real-Time Control System

This thesis is done as a complementary part for the active magnet bearing (AMB) control software development project in Lappeenranta University of Technology. The main focus of the thesis is to examine an idea of a real-time operating system (RTOS) framework that operates in a dedicated digital signal processor (DSP) environment. General use real-time operating systems do not necessarily provide sufficient platform for periodic control algorithm utilisation. In addition, application program interfaces found in real-time operating systems are commonly non-existent or provided as chip-support libraries, thus hindering platform independent software development. Hence, two divergent real-time operating systems and additional periodic extension software with the framework design are examined to find solutions for the research problems. The research is discharged by; tracing the selected real-time operating system, formulating requirements for the system, and designing the real-time operating system framework (OSFW). The OSFW is formed by programming the framework and conjoining the outcome with the RTOS and the periodic extension. The system is tested and functionality of the software is evaluated in theoretical context of the Rate Monotonic Scheduling (RMS) theory. The performance of the OSFW and substance of the approach are discussed in contrast to the research theme. The findings of the thesis demonstrates that the forged real-time operating system framework is a viable groundwork solution for periodic control applications.