External Location Factors of Foreign Direct Investment in Russia – Finnish Perspective

Tämän diplomityön tavoitteena on selvittää, mitä alueellisia tekijöitä suomalaiset yritykset ottavat huomioon valitessaan sopivaa sijaintia suoralle investoinnille Venäjän sisällä. Muutamia yrityksen sisäisiä tekijöitä käytetään taustamuuttujina selittämään sijaintitekijöiden painotuksissa havaittavia eroja erilaisten yritysten välillä. Venäjän alueita vertaillaan lopuksi painotusten valossa. Työn ensimmäisessä osassa keskitytään suorien ulkomaisten investointien teoreettiseen taustaan. Aiempia tutkimuksia käydään läpi, jotta tekijät, joilla on havaittu olevan vaikutusta investointien sijoittumiseen maan sisällä, saadaan kartoitettua. Työn jälkimmäinen osa perustuu yrityskyselyn avulla kerättyyn empiiriseen aineistoon. Aineiston avulla selvitetään mitä tekijöitä suomalaisyritykset huomioivat sijaintipäätöstä tehdessään. Tulosten valossa on ilmeistä, että alueen markkinapotentiaali on suomalaisyrityksissä tärkein huomioitava tekijä investoinnin sijainnista päätettäessä. Myös infrastruktuuri ja kustannushyödyt vaikuttavat päätökseen. Erityyppisten yritysten painotukset ovat hyvin samanlaisia. Moskova ja Pietari vastaavat Venäjän alueista parhaiten suomalaisyritysten investoinnin sijainnille asettamia kriteerejä.

Optimizing Mobile Java Location-Based Services in Symbian OS

This thesis evaluates methods for obtaining high performance in applications running on the mobile Java platform. Based on the evaluated methods, an optimization was done to a Java extension API running on top the Symbian operating system. The API provides location-based services for mobile Java applications. As a part of this thesis, the JNI implementation in Symbian OS was also benchmarked. A benchmarking tool was implemented in the analysis phase in order to implement extensive performance test set. Based on the benchmark results, it was noted that the landmarks implementation of the API was performing very slowly with large amounts of data. The existing implementation proved to be very inconvenient for optimization because the early implementers did not take performance and design issues into consideration. A completely new architecture was implemented for the API in order to provide scalable landmark initialization and data extraction by using lazy initialization methods. Additionally, runtime memory consumption was also an important part of the optimization. The improvement proved to be very efficient based on the measurements after the optimization. Most of the common API use cases performed extremely well compared to the old implementation. Performance optimization is an important quality attribute of any piece of software especially in embedded mobile devices. Typically, projects get into trouble with performance because there are no clear performance targets and knowledge how to achieve them. Well-known guidelines and performance models help to achieve good overall performance in Java applications and programming interfaces.

Tuotetiedon soveltaminen varastotiedon hallinnan parantamisessa

Inventory data management is defined as an accurate creation and maintenance of item master data, inventory location data and inventory balances per an inventory location. The accuracy of inventory data is dependent of many elements of the product data management like the management of changes during a component’s life-cycle and the accuracy of product configuration in enterprise resource planning systems. Cycle-counting is counting of inventory balances per an inventory location and comparing them to the system data on a daily basis. The Cycle-counting process is a way to measure the accuracy of the inventory data in a company. Through well managed cycle-counting process a company gets a lot of information of their inventory data accuracy. General inaccuracy of the inventory data can’t be fixed through only assigning resources to the cycle-counting but the change requires disciplined following of the defined processes from all parties involved in updating inventory data through a component’s life-cycle. The Processes affecting inventory data are mapped and the appropriate metrics are defined in order to achieve better manageability of the inventory data. The Life-cycles of a single component and of a product are used in evaluation of the processes.

Role of human hydroxysteroid (17beta) dehydrogenase type 1 (HSD17B1) in steroid-dependent diseases in females –novel indications for HSD17B1 inhibitors. Phenotypic analysis of transgenic mice overexpressing human HSD17B1.

Hormone-dependent diseases, e.g. cancers, rank high in mortality in the modern world, and thus, there is an urgent need for new drugs to treat these diseases. Although the diseases are clearly hormone-dependent, changes in circulating hormone concentrations do not explain all the pathological processes observed in the diseased tissues. A more inclusive explanation is provided by intracrinology – a regulation of hormone concentrations at the target tissue level. This is mediated by the expression of a pattern of steroid-activating and -inactivating enzymes in steroid target tissues, thus enabling a concentration gradient between the blood circulation and the tissue. Hydroxysteroid (17beta) dehydrogenases (HSD17Bs) form a family of enzymes that catalyze the conversion between low active 17-ketosteroids and highly active 17beta-hydroxysteroids. HSD17B1 converts low active estrogen (E1) to highly active estradiol (E2) with high catalytic efficiency, and altered HSD17B1 expression has been associated with several hormone-dependent diseases, including breast cancer, endometriosis, endometrial hyperplasia and cancer, and ovarian epithelial cancer. Because of its putative role in E2 biosynthesis in ovaries and peripheral target tissues, HSD17B1 is considered to be a promising drug target for estrogen-dependent diseases. A few studies have indicated that the enzyme also has androgenic activity, but they have been ignored. In the present study, transgenic mice overexpressing human HSD17B1 (HSD17B1TG mice) were used to study the effects of the enzyme in vivo. Firstly, the substrate specificity of human HSD17B1 was determined in vivo. The results indicated that human HSD17B1 has significant androgenic activity in female mice in vivo, which resulted in increased fetal testosterone concentration and female disorder of sexual development appearing as masculinized phenotype (increased anogenital distance, lack of nipples, lack of vaginal opening, combination of vagina with urethra, enlarged Wolffian duct remnants in the mesovarium and enlarged female prostate). Fetal androgen exposure has been linked to polycystic ovary syndrome (PCOS) and metabolic syndrome during adulthood in experimental animals and humans, but the genes involved in PCOS are largely unknown. A putative mechanism to accumulate androgens during fetal life by HSD17B1 overexpression was shown in the present study. Furthermore, as a result of prenatal androgen exposure locally in the ovaries, HSD17B1TG females developed ovarian benign serous cystadenomas in adulthood. These benign lesions are precursors of low-grade ovarian serous tumors. Ovarian cancer ranks fifth in mortality of all female cancers in Finland, and most of the ovarian cancers arise from the surface epithelium. The formation of the lesions was prevented by prenatal antiandrogen treatment and by transplanting wild type (WT) ovaries prepubertally into HSD17B1TG females. The results obtained in our non-clinical TG mouse model, together with a literature analysis, suggest that HSD17B1 has a role in ovarian epithelial carcinogenesis, and especially in the development of serous tumors. The role of androgens in ovarian carcinogenesis is considered controversial, but the present study provides further evidence for the androgen hypothesis. Moreover, it directly links HSD17B1-induced prenatal androgen exposure to ovarian epithelial carcinogenesis in mice. As expected, significant estrogenic activity was also detected for human HSD17B1. HSD17B1TG mice had enhanced peripheral conversion of E1 to E2 in a variety of target tissues, including the uterus. Furthermore, this activity was significantly decreased by treatments with specific HSD17B1 inhibitors. As a result, several estrogen-dependent disorders were found in HSD17B1TG females. Here we report that HSD17B1TG mice invariably developed endometrial hyperplasia and failed to ovulate in adulthood. As in humans, endometrial hyperplasia in HSD17B1TG females was reversible upon ovulation induction, triggering a rise in circulating progesterone levels, and in response to exogenous progestins. Remarkably, treatment with a HSD17B1 inhibitor failed to restore ovulation, yet completely reversed the hyperplastic morphology of epithelial cells in the glandular compartment. We also demonstrate that HSD17B1 is expressed in normal human endometrium, hyperplasia, and cancer. Collectively, our non-clinical data and literature analysis suggest that HSD17B1 inhibition could be one of several possible approaches to decrease endometrial estrogen production in endometrial hyperplasia and cancer. HSD17B1 expression has been found in bones of humans and rats. The non-clinical data in the present study suggest that human HSD17B1 is likely to have an important role in the regulation of bone formation, strength and length during reproductive years in female mice. Bone density in HSD17B1TG females was highly increased in femurs, but in lesser amounts also in tibias. Especially the tibia growth plate, but not other regions of bone, was susceptible to respond to HSD17B1 inhibition by increasing bone length, whereas the inhibitors did not affect bone density. Therefore, HSD17B1 inhibitors could be safer than aromatase inhibitors in regard to bone in the treatment of breast cancer and endometriosis. Furthermore, diseases related to improper growth, are a promising new indication for HSD17B1 inhibitors.

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.

Determining the location for a mobile device by utilization of local resources of the environment

The subject being analyzed of this Master’s Thesis is a development of a service that is used to define a current location of a mobile device. The service utilized data that is obtained from own GPS receiver in some possible cases and as well data from mobile devices which can be afforded for the current environment for acquisition of more precise position of the device. The computation environment is based on context of a mobile device. The service is implemented as an application for communicator series Nokia N8XX. The Master’s Thesis presents theoretical concept of the method and its practical implementation, architecture of the application, requirements and describes a process of its functionality. Also users’ work with application is presented and recommendations for possible future improvements are made.

Creating carbon footprint calculating tool for plastic packaging products

The environmental challenges of plastic packaging industry have increased remarkably along with climate change debate. The interest to study carbon footprints of packaging has increased in packaging industry to find out the real climate change impacts of packaging. In this thesis the greenhouse gas discharges of plastic packaging during their life cycle is examined. The carbon footprint is calculated for food packaging manufactured from plastic laminate. The structure of the laminate is low density polyethylene (PE-LD) and oriented polypropylene (OPP), which have been joined together with laminating adhesive. The purpose is to find out the possibilities to create a carbon footprint calculating tool for plastic packaging and its usability in a plastic packaging manufacturing company. As a carbon footprint calculating method PAS 2050 standard has been used. In the calculations direct and indirect greenhouse gas discharges as well as avoided discharges are considered. Avoided discharges are born for example in packaging waste utilization as energy. The results of the calculations have been used to create a simple calculating tool to be used for similar laminate structures. Although the utilization of the calculating tool is limited to one manufacturing plant because the primary activity data is dependent of geographical location and for example the discharges of used energy in the plant. The results give an approximation of the climate change potential caused by the laminate. It is although noticed that calculations do not include all environmental impacts of plastic packaging´s life cycle.

Strategic outsourcing of R&D: The location-specific advantages of India to the pharmaceutical industry

Companies are increasingly under pressure to be more efficient both in terms of costs and overall performance and thus, they seek new ways to develop their products and innovate. For pharmaceutical industry it can take several decades to launch a new drug to the markets. Since pharmaceutical industry is one of the most research-intensive industries, is outsourcing one way to enhance the R&D processes of such companies. It is said that outsourcing to offshore locations is vastly more challenging and complicated than any other exporting activity or inter-company relationship that has evoked a lot of discussion. By outsourcing strategically, companies must also thoroughly focus on transaction costs and core competences. Today, the suppliers are looked for beyond national boundaries and furthermore, the location of the outsourcing activity must also be thoroughly considered. Consequently, the purpose of this study is to analyze what is known of strategic outsourcing of pharmaceutical R&D to India. In order to meet the purpose of the study, this study tries to answer three sub-questions set to it: first, what is strategic outsourcing, second, why pharmaceutical companies utilize strategic outsourcing of R&D and last, why pharmaceutical companies select India as the location for outsourcing their R&D. The study is a qualitative study. The purpose of the study was approached by a literature review with systematic elements and sub-questions were analyzed through different relevant theories, such as theory of transaction costs, core competences and location advantages. Applicable academic journal articles were comprehensively included in the study. The data was collected from electronic journal article databases using key words and almost only peer-reviewed, as new as possible articles were included. Also both the reference list of the included articles and article recommendations from professionals generated more articles for inclusion. The data was analyzed through thematization that resulted in themes that illuminate the purpose of the study and sub-questions. As an outcome of the analysis, each of the theory chapters in the study represents one sub-question. The literature used in this study revealed that strategic outsourcing of R&D is increasingly used in pharmaceutical industry and the major motives to practice it has to do with lowering costs, accessing skilled labor, resources and knowledge and enhancing their quality while speeding up the introduction of new drugs. Mainly for the above-mentioned motives India is frequently chosen as the target location for pharma outsourcers. Still, the literature is somewhat incomplete in this complex phenomenon and more research is needed.

Statistical analysis of survey-based event history data with application to modeling of unemployment duration

Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.

Open African Reference Pathology Data Center

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Building a Research Data Registry for the UK

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Evaluation of Location Intelligence exploitation in capital-intensive business

As technology has developed it has increased the number of data produced and collected from business environment. Over 80% of that data includes some sort of reference to geographical location. Individuals have used that information by utilizing Google Maps or different GPS devices, however such information has remained unexploited in business. This thesis will study the use and utilization of geographically referenced data in capital-intensive business by first providing theoretical insight into how data and data-driven management enables and enhances the business and how especially geographically referenced data adds value to the company and then examining empirical case evidence how geographical information can truly be exploited in capital-intensive business and what are the value adding elements of geographical information to the business. The study contains semi-structured interviews that are used to scan attitudes and beliefs of an organization towards the geographic information and to discover fields of applications for the use of geographic information system within the case company. Additionally geographical data is tested in order to illustrate how the data could be used in practice. Finally the outcome of the thesis provides understanding from which elements the added value of geographical information in business is consisted of and how such data can be utilized in the case company and in capital-intensive business.

Location intelligence strategisen päätöksenteon tukena

Kilpailuetua tavoittelevan yrityksen pitää kyetä jalostamaan tietoa ja tunnistamaan sen avulla uusia tulevaisuuden mahdollisuuksia. Tulevaisuuden mielikuvien luomiseksi yrityksen on tunnettava toimintaympäristönsä ja olla herkkänä havaitsemaan muutostrendit ja muut toimintaympäristön signaalit. Ympäristön elintärkeät signaalit liittyvät kilpailijoihin, teknologian kehittymiseen, arvomaailman muutoksiin, globaaleihin väestötrendeihin tai jopa ympäristön muutoksiin. Spatiaaliset suhteet ovat peruspilareita käsitteellistää maailmaamme. Pitney (2015) on arvioinut, että 80 % kaikesta bisnesdatasta sisältää jollakin tavoin viittauksia paikkatietoon. Siitä huolimatta paikkatietoa on vielä huonosti hyödynnetty yritysten strategisten päätösten tukena. Teknologioiden kehittyminen, tiedon nopea siirto ja paikannustekniikoiden integroiminen eri laitteisiin ovat mahdollistaneet sen, että paikkatietoa hyödyntäviä palveluja ja ratkaisuja tullaan yhä enemmän näkemään yrityskentässä. Tutkimuksen tavoitteena oli selvittää voiko location intelligence toimia strategisen päätöksenteon tukena ja jos voi, niin miten. Työ toteutettiin konstruktiivista tutkimusmenetelmää käyttäen, jolla pyritään ratkaisemaan jokin relevantti ongelma. Konstruktiivinen tutkimus tehtiin tiiviissä yhteistyössä kolmen pk-yrityksen kanssa ja siihen haastateltiin kuutta eri strategiasta vastaavaa henkilöä. Tutkimuksen tuloksena löydettiin, että location intelligenceä voidaan hyödyntää strategisen päätöksenteon tukena usealla eri tasolla. Yksinkertaisimmassa karttaratkaisussa halutut tiedot tuodaan kartalle ja luodaan visuaalinen esitys, jonka avulla johtopäätöksien tekeminen helpottuu. Toisen tason karttaratkaisu pitää sisällään sekä sijainti- että ominaisuustietoa, jota on yhdistetty eri lähteistä. Tämä toisen tason karttaratkaisu on usein kuvailevaa analytiikkaa, joka mahdollistaa erilaisten ilmiöiden analysoinnin. Kolmannen eli ylimmän tason karttaratkaisu tarjoaa ennakoivaa analytiikkaa ja malleja tulevaisuudesta. Tällöin ohjelmaan koodataan älykkyyttä, jossa informaation keskinäisiä suhteita on määritelty joko tiedon louhintaa tai tilastollisia analyysejä hyödyntäen. Tutkimuksen johtopäätöksenä voidaan todeta, että location intelligence pystyy tarjoamaan lisäarvoa strategisen päätöksenteon tueksi, mikäli yritykselle on hyödyllistä ymmärtää eri ilmiöiden, asiakastarpeiden, kilpailijoiden ja markkinamuutoksien maantieteellisiä eroavaisuuksia. Parhaimmillaan location intelligence -ratkaisu tarjoaa luotettavan analyysin, jossa tieto välittyy muuttumattomana päätöksentekijältä toiselle ja johtopäätökseen johtaneita syitä on mahdollista palata tarkastelemaan tarvittaessa uudelleen.