Liiketoimintaprosessien uudelleenrakentaminen PK-yrityksessä

Tutkimuksen päätavoite on kehittää pintakäsittelylaitteita valmistavan PK-yrityksen liiketoimintaedellytyksiä suunnittelemalla sille uusi toimintamalli. Sysäyksen kehitysprojektille antoi liiketoiminnan kasvusta johtunut kontrollin pettäminen, mikä aiheutti kannattavuuden kääntymisen negatiiviseksi. Työn keskeisen viitekehyksen muodostavat kolme tekijää; kehitysmenetelmänä liiketoimintaprosessien uudelleenrakentaminen, yritysmuotona projektiliiketoiminta sekä uuden toimintamallin painopisteenä tuotannon ja asennuksen ulkoistaminen. Käytössä olevia liiketoimintaprosesseja analysoitaessa pystyttiin tunnistamaan useita ongelmakohtia yrityksen toiminnassa, joiden pohjalta määriteltiin parannustarpeet ja vaatimukset uusille prosesseille. Yrityksessä oli selkeänä ongelmana yleinen järjestelmällisyyden puute, mikä näkyi määrittelemättöminä liiketoimintaprosesseina ja tästä johtuvina ongelmina yrityksen lähes kaikissa toiminnoissa. Tekninen osaaminen on yrityksessä hyvää, mutta liikkeenjohdollinen puoli kaipaisi kehittämistä. Tyypillisiä ongelmia olivat vaikeasti ennustettavat tuotantoajat ja niistä johtuneet myöhästymiset toimituksissa, valmistusvirheet sekä tuotannon ja asennuksen tehottomuus. Omat vaatimuksensa uusille prosesseille asetti myös siirtyminen ulkoistettuun valmistukseen ja asennukseen. Uusien prosessien myötä keskeisimmät muutokset olivat panostaminen pitkän tähtäimen suunnitteluun, asiakastiedon hallinnan parantaminen, panostaminen alihankkijaverkoston johtamiseen, organisaation sisäisen viestinnän parantaminen ja siirtyminen etätyön mahdollistavaan ”virtuaalitoimistoon”.

Secondary Aural Symptoms in Relation to Cranio-Cervical and General Disorders

The present thesis comprises two study populations. The first study sample (SS1) consisted of 411 adults examined and interviewed at three annual visits. The second study sample (SS2) consisted of 1720 adults who filled in a mailed questionnaire about secondary otalgia, tinnitus and fullness of ears. In the second phase of the SS2, 100 subjects with otalgia were examined and interviewed by specialist in stomatognathic physiology and otorhinolaryngology. In the third phase, 36 subjects participated in a randomized, controlled and blinded trial of effectiveness of occlusal appliance on secondary otalgia, facial pain, headache and treatment need of temporomandibular disorders (TMD). The standardized prevalence of recurrent secondary otalgia was 6%, tinnitus 15% and fullness of ears 8%. Aural symptoms were more frequent among young than old subjects. They were associated with other, simultaneous aural symptoms, TMD pain, head and neck region pain, and visits to a physician. The subjects with aural symptoms more often had tenderness on palpation of masticatory muscles and clinical signs of temporomandibular joint than the subjects without. 85% of the subjects reporting secondary otalgia had cervical spine or temporomandibular disorder or both. In SS1, the final model of secondary otalgia included active need treatment for TMD, elevated level of stress symptoms, and bruxism. In SS2, the final models of aural symptoms included associated aural symptoms, young age, TMD pain, headache and shoulder ache. Stabilization splint more effectively alleviated secondary otalgia and active treatment need for TMD than a palatal control splint. In patients with aural pain, tinnitus or fullness of ears, it is important to first rule out otologic and nasopharyngeal diseases that may cause the symptoms. If no explanation for aural symptoms is found, temporomandibular and cervical spine disorders should be rouled out to minimize unnecessary visits to a physician.

First-mover Advantage

Tämän tutkielman tarkoitus oli tutkia yrityksen markkinoille tai alalle tulon ajoitukseen pohjautuvaa kilpailuetua –erityisesti niin kutsuttua ensimmäisen toimijan etua - eli etua jonka yritys voi saavuttaa tullessaan markkinoille tiettyyn aikaan suhteessa muihin markkinoille tulijoihin. Tutkielma on luonteeltaan kirjallisuuskatsaus. Yleisesti ottaen ei voida sanoa että jokin tietty markkinoille tai alalle tulo strategia –esimerkiksi ensimmäisenä toimiminen – olisi yritykselle aina kannattavaa. On oletettavaa että yrityksen toimintaympäristö, erityisesti toimiala jolla se toimii, määrittää kyseenomaiseen kilpailuetuun liittyvät mahdollisuudet, ja että yrityksen omista lähtökohdista ja toiminnasta riippuu kuinka hyvin se pystyy nämä mahdollisuudet hyödyntämään. Työssä on esitetty ehdotuksia ensimmäisen toimijan edun jatkotutkimusta varten.

Advanced chemometric methods: Applicability on industrial data

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

Some advances in mathematical models for preference relations

Preference relations, and their modeling, have played a crucial role in both social sciences and applied mathematics. A special category of preference relations is represented by cardinal preference relations, which are nothing other than relations which can also take into account the degree of relation. Preference relations play a pivotal role in most of multi criteria decision making methods and in the operational research. This thesis aims at showing some recent advances in their methodology. Actually, there are a number of open issues in this field and the contributions presented in this thesis can be grouped accordingly. The first issue regards the estimation of a weight vector given a preference relation. A new and efficient algorithm for estimating the priority vector of a reciprocal relation, i.e. a special type of preference relation, is going to be presented. The same section contains the proof that twenty methods already proposed in literature lead to unsatisfactory results as they employ a conflicting constraint in their optimization model. The second area of interest concerns consistency evaluation and it is possibly the kernel of the thesis. This thesis contains the proofs that some indices are equivalent and that therefore, some seemingly different formulae, end up leading to the very same result. Moreover, some numerical simulations are presented. The section ends with some consideration of a new method for fairly evaluating consistency. The third matter regards incomplete relations and how to estimate missing comparisons. This section reports a numerical study of the methods already proposed in literature and analyzes their behavior in different situations. The fourth, and last, topic, proposes a way to deal with group decision making by means of connecting preference relations with social network analysis.

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.

Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.