Parameter identification in time series models

Time series analysis can be categorized into three different approaches: classical, Box-Jenkins, and State space. Classical approach makes a basement for the analysis and Box-Jenkins approach is an improvement of the classical approach and deals with stationary time series. State space approach allows time variant factors and covers up a broader area of time series analysis. This thesis focuses on parameter identifiablity of different parameter estimation methods such as LSQ, Yule-Walker, MLE which are used in the above time series analysis approaches. Also the Kalman filter method and smoothing techniques are integrated with the state space approach and MLE method to estimate parameters allowing them to change over time. Parameter estimation is carried out by repeating estimation and integrating with MCMC and inspect how well different estimation methods can identify the optimal model parameters. Identification is performed in probabilistic and general senses and compare the results in order to study and represent identifiability more informative way.

Automatic image-based identification of Saimaa ringed seals

The Saimaa ringed seal is one of the most endangered seals in the world. It is a symbol of Lake Saimaa and a lot of effort have been applied to save it. Traditional methods of seal monitoring include capturing the animals and installing sensors on their bodies. These invasive methods for identifying can be painful and affect the behavior of the animals. Automatic identification of seals using computer vision provides a more humane method for the monitoring. This Master's thesis focuses on automatic image-based identification of the Saimaa ringed seals. This consists of detection and segmentation of a seal in an image, analysis of its ring patterns, and identification of the detected seal based on the features of the ring patterns. The proposed algorithm is evaluated with a dataset of 131 individual seals. Based on the experiments with 363 images, 81\% of the images were successfully segmented automatically. Furthermore, a new approach for interactive identification of Saimaa ringed seals is proposed. The results of this research are a starting point for future research in the topic of seal photo-identification.

Identification of characteristics for successful university-company partnership development

The importance of university-company collaboration has increased during the last decades. The drivers for that are, on the one hand, changes in business logic of companies and on the other hand the decreased state funding of universities. Many companies emphasize joint research with universities as an enabling input to their development processes, which aim at creating new innovations, products and wealth. These factors have changed universities’ operations and they have adopted several practices of dynamic business organizations, such as strategic planning, monitoring and controlling methods of internal processes etc. The objective of this thesis is to combine different characteristics of successful university-company partnership and its development. The development process starts with identifying potential partners in the university’s interest group, which requires understanding the role of different partners in the innovation system. Next, in order to find a common development basis, matching the policy and strategy between partners is needed. The third phase is to combine the academic and industrial objectives of a joint project, which is a typical form of university-company collaboration. The optimum is a win-win situation where both partners, universities and companies, can get addedvalue. For the companies added value typically means access to new research results before their competitors. For the universities added value offers a possibility to carry on high level scientific work. The research output in the form of published scientific articles is evaluated by the international science community. Because the university-company partnership is often executed by joint projects, the different forms of this kind of projects is discussed in this study. The most challenging form of collaboration is a semi-open project model, which is not based on bilateral activities between universities and companies but on a consortium of several universities, research institutes and companies. The universities and companies are core actors in the innovation system. Thus the discussion of their roles and relations to public operators like publicly funded financiers is important. In the Finnish innovation system there are at least the following doers executing strategies and policies: EU, Academy of Finland and TEKES. In addition to these, Strategic Centres for Science, Technology and Innovation which are owned jointly by companies, universities and research organizations have a very important role in their fields of business. They transfer research results into commercial actions to generate wealth. The thesis comprises two parts. The first part consists of an overview of the study including introduction, literature review, research design, synthesis of findings and conclusions. The second part introduces four original research publications.

Competence foresight: linking the identification of HR competences and competence management alignment with business strategy

The objective of this study was to increase understanding of the link between the identification of required HR competences and competence management alignment with business strategy in a Finnish, global company employing over 8,000 people and about 100 HR professionals. This aim was approached by analyzing the data collected in focus group interviews using a grounded theory method and in parallel reviewing the literature of strategic human resource management, competence-based strategic management, strategy and foresight. The literature on competence management in different contexts dismisses in-depth discussions on the foresight process and individuals are often forgotten in strategic frameworks. However, corporate foresight helps in the detection of emerging opportunities for innovations and in the implementation of strategy. The empirical findings indicate a lack of strategic leadership and an alignment with HR and business. Accordingly, the most important HR competence areas identified were the need for increasing business understanding and enabling change. As a result, the study provided a holistic model for competence foresight, which introduces HR professionals as strategic change agents in the role of organizational futurists at the heart of the company: facilitating competence foresight and competence development on individual as well as organizational levels, resulting in an agile organization with increased business understanding, sensitive sensors and adaptive actions to enable change.

The role of brand identification in alumni support to their alma mater

Universities around the world are facing global competition and challenges to finance their main functions - research and education. This study focused on the role of graduates, alumni, in the success of a university. The purpose of this study was to examine the role of brand identification in alumni willingness to support their alma mater. The research concentrated on finding out what is the relationship between brand identification and it’s antecedents (prestige, satisfaction, interpretation of brand) to alumni willingness to promote university, participate in university activities and support financially by donating money to university’s research. The research method was quantitative and the data was collected via online survey from 569 alumni of a Finnish university. The findings suggest that there is a strong relationship between brand identification and alumni support. The stronger brand identification is, the more willing alumni were to promote university, participate in university activities and support financially. Based on the research, it is beneficial for universities to invest in brand development in order to get alumni to act as ambassadors of the university after their graduation.

Determining vehicle drivetrain dynamics using system identification

Target of this book is to propose an approach for modelling drivetrain dynamics in order to design further a vibration control system of a hybrid bus. In this thesis two approaches are examined and compared. First model is obtained by theoretical means: drivetrain is represented as a system of rotating masses, which motion is described with differential equations. Second model is obtained using system identification method: mathematical description of the dynamic behavior of a system is formed based on measured input (torque) and output (speed) data. Then two models are compared and an optimal approach is suggested.

Detection, Identification and Molecular Variation of Human Enteroviruses

Picornaviruses are the most common human viruses and the identification of the picornaviruses is nowadays based on molecular techniques, for example, reverse transcriptase polymerase chain reaction (RT-PCR). One aim of this thesis was to improve the identification of picornaviruses, especially rhino- and enteroviruses, with a real-time assay format and, also, to improve the differentiation of the viruses with genus-specific locked nucleic acid (LNA) probes. Another aim was to identify and study the causative agent of the enterovirus epidemics that appeared in Finland during seasons 2008-2010. In this thesis, the first version of picornavirus qRT-PCR with a melting curve analysis was used in a study of rhinovirus transmission within families with a rhinovirus positive index child where rhinovirus infection was monitored in all family members. In conclusion, rhinoviruses spread effectively within families causing mostly symptomatic infections in children and asymptomatic infections in adults. To improve the differentiation between rhino- and enterovirus the picornavirus qRT-PCR was modified with LNA-incorporated probes. The LNA probes were validated with picornavirus prototypes and different clinical specimen types. The LNA probe-based picornavirus qRT-PCR was able to differentiate all rhino- and enteroviruses correctly, which makes it suitable for diagnostic use. Moreover, in this thesis enterovirus outbreaks were studied with a well-observed method to create a strain-specific qRT-PCR from the typing region VP1 protein. In a hand-foot-and-mouth-disease (HFMD) outbreak in 2008, the causative agent was identified as CV-A6 and when the molecular evolution of the new HFMD CV-A6 strain was studied it was found that CV-A6 was the emerging agent for HFMD and onychomadesis. Furthermore, unusual E-30 meningitis epidemics that apeared during seasons 2009 and 2010 were studied with strain-specific qRT-PCR. The E-30 affected mostly adolescents and was probably spread in sports teams.

Active Magnetic Bearing System Identification Methods and Rotor Model Updating

Active magnetic bearing is a type of bearing which uses magnetic field to levitate the rotor. These bearings require continuous control of the currents in electromagnets and data from position of the rotor and the measured current from electromagnets. Because of this different identification methods can be implemented with no additional hardware. In this thesis the focus was to implement and test identification methods for active magnetic bearing system and to update the rotor model. Magnetic center calibration is a method used to locate the magnetic center of the rotor. Rotor model identification is an identification method used to identify the rotor model. Rotor model update is a method used to update the rotor model based on identification data. These methods were implemented and tested with a real machine where rotor was levitated with active magnetic bearings and the functionality of the methods was ensured. Methods were developed with further extension in mind and also with the possibility to apply them for different machines with ease.

Wood species identification by visual characterization of fibers

Kandidaatintyö tehtiin osana PulpVision-tutkimusprojektia, jonka tarkoituksena on kehittää kuvapohjaisia laskenta- ja luokittelumetodeja sellun laaduntarkkailuun paperin valmistuksessa. Tämän tutkimusprojektin osana on aiemmin kehitetty metodi, jolla etsittiin kaarevia rakenteita kuvista, ja tätä metodia hyödynnettiin kuitujen etsintään kuvista. Tätä metodia käytettiin lähtökohtana kandidaatintyölle. Työn tarkoituksena oli tutkia, voidaanko erilaisista kuitukuvista laskettujen piirteiden avulla tunnistaa kuvassa olevien kuitujen laji. Näissä kuitukuvissa oli kuituja neljästä eri puulajista ja yhdestä kasvista. Nämä lajit olivat akasia, koivu, mänty, eukalyptus ja vehnä. Jokaisesta lajista valittiin 100 kuitukuvaa ja nämä kuvat jaettiin kahteen ryhmään, joista ensimmäistä käytettiin opetusryhmänä ja toista testausryhmänä. Opetusryhmän avulla jokaiselle kuitulajille laskettiin näitä kuvaavia piirteitä, joiden avulla pyrittiin tunnistamaan testausryhmän kuvissa olevat kuitulajit. Nämä kuvat oli tuottanut CEMIS-Oulu (Center for Measurement and Information Systems), joka on mittaustekniikkaan keskittynyt yksikkö Oulun yliopistossa. Yksittäiselle opetusryhmän kuitukuvalle laskettiin keskiarvot ja keskihajonnat kolmesta eri piirteestä, jotka olivat pituus, leveys ja kaarevuus. Lisäksi laskettiin, kuinka monta kuitua kuvasta löydettiin. Näiden piirteiden eri yhdistelmien avulla testattiin tunnistamisen tarkkuutta käyttämällä k:n lähimmän naapurin menetelmää ja Naiivi Bayes -luokitinta testausryhmän kuville. Testeistä saatiin lupaavia tuloksia muun muassa pituuden ja leveyden keskiarvoja käytettäessä saavutettiin jopa noin 98 %:n tarkkuus molemmilla algoritmeilla. Tunnistuksessa kuitujen keskimäärinen pituus vaikutti olevan kuitukuvia parhaiten kuvaava piirre. Käytettyjen algoritmien välillä ei ollut suurta vaihtelua tarkkuudessa. Testeissä saatujen tulosten perusteella voidaan todeta, että kuitukuvien tunnistaminen on mahdollista. Testien perusteella kuitukuvista tarvitsee laskea vain kaksi piirrettä, joilla kuidut voidaan tunnistaa tarkasti. Käytetyt lajittelualgoritmit olivat hyvin yksinkertaisia, mutta ne toimivat testeissä hyvin.

Identification and validation of novel prostate cancer biomarkers

Prostate cancer (PCa) has emerged as the most commonly diagnosed lethal cancer in European men. PCa is a heterogeneous cancer that in the majority of the cases is slow growing: consequently, these patients would not need any medical treatment. Currently, the measurement of prostate-specific antigen (PSA) from blood by immunoassay followed by digital rectal examination and a pathological examination of prostate tissue biopsies are the most widely used methods in the diagnosis of PCa. These methods suffer from a lack of sensitivity and specificity that may cause either missed cancers or overtreatment as a consequence of over-diagnosis. Therefore, more reliable biomarkers are needed for a better discrimination between indolent and potentially aggressive cancers. The aim of this thesis was the identification and validation of novel biomarkers for PCa. The mRNA expression level of 14 genes including AMACR, AR, PCA3, SPINK1, TMPRSS2-ERG, KLK3, ACSM1, CACNA1D, DLX1, LMNB1, PLA2G7, RHOU, SPON2, and TDRD1 was measured by a truly quantitative reverse transcription PCR in different prostate tissue samples from men with and without PCa. For the last eight genes the function of the genes in PCa progression was studied by a specific siRNA knockdown in PC-3 and VCaP cells. The results from radical prostatectomy and cystoprostatectomy samples showed statistically significant overexpression for all the target genes, except for KLK3 in men with PCa compared with men without PCa. Statistically significant difference was also observed in low versus high Gleason grade tumors (for PLA2G7), PSA relapse versus no relapse (for SPON2), and low versus high TNM stages (for CACNA1D and DLX1). Functional studies and siRNA silencing results revealed a cytotoxicity effect for the knock-down of DLX1, PLA2G7, and RHOU, and altered tumor cell invasion for PLA2G7, RHOU, ACSM1, and CACNA1D knock-down in 3D conditions. In addition, effects on tumor cell motility were observed after silencing PLA2G7 and RHOU in 2D monolayer cultures. Altogether, these findings indicate the possibility of utilizing these new markers as diagnostic and prognostic markers, and they may also represent therapeutic targets for PCa.