Loviisan ydinvoimalaitoksen kaapelireittien tiedonhallinnan kehittäminen paloriskitutkimusta varten

Tässä diplomityössä kehitetään Loviisan voimalaitoksen todennäköisyyspohjaisen paloriskianalyysin kaapelitietokantaa tulevaisuuden haasteita varten. Tietokannan kehittämistä varten tutustutaan todennäköisyyspohjaiseen riskianalyysiin varsin-kin paloriskianalyysin osalta. Käytännönläheisempää kehittämistä varten tutustu-taan voimalaitoksella nykyisin käytössä oleviin kaapelitietokantoihin: paloriski-tutkimusta varten laadittuun PSA-ELTIEen, kunnossapidon tiedonhallintajärjes-telmä LOMAXiin, sähkö- ja automaatiosuunnitteluyksikköjen arkistoihin sekä automaatiouudistuksen tietokantaan. Tietokannan käytännönläheisempien ominai-suuksien selvittämiseksi voimalaitoksella kokeiltiin kenttätarkastusmenetelmää, joka on ensisijainen kaapelikartoitusmenetelmä. Tietokantoihin tutustumisen perusteella vaihtoehtoisiksi tulevaisuuden tietokan-noiksi mietittiin LOMAXia, PSA-ELTIEtä tai uutta tietokantaa. Tulevaisuuden tietokantavaihtoehdoksi on päädytty ehdottamaan LOMAXia, joka vaatii vähem-män muutoksia muihin vaihtoehtoihin nähden. Tällainen laajalti käytössä oleva yhteinen tietokanta mahdollistaa sen, että tiedot ovat helpommin ja varmemmin kaikkien niitä tarvitsevien käytettävissä ja asiantuntijoiden muokattavissa, millä myös varmistetaan tietojen oikeellisuutta ja pysymistä ajan tasalla. Tulevaan LOMAX päivitykseen on ehdotettu tarpeellisia tietokenttien lisäyksiä ja kaapeli-hierarkian parantamista kaapelitietokannaksi käyttöönottamista varten.

Mapping out customer segments and marketing channels in the Finnish Homelift market

Työn tavoitteena oli saada selville ketkä ovat uuden tuotteen, eli kotihissin asiakkaat. Mitkä ovat tuotteen mahdollisuudet Suomen markkinoilla ja onko markkinoilla odotettavissa kasvua, sekä miten tähän mahdolliseen kasvuun päästäisiin käsiksi. Kotihissin ominaisuudet vaikuttavat siihen, että se on tarkoitettu asennettavaksi yksityisiin pientaloihin. Uuden tuotteen ansiosta KONE voi liittää nykyiseen vahvaan toimialaansa, eli kerrostaloihin, uuden aluevaltauksen; Pientalot. Tämä 'laajentuminen' tuo mukanaan kuluttajamarkkinoiden haasteet. Markkinatilanteen selvittämiseen käyttin jo olemassa olevaa tietoa hyväkseni; sanomalehdistä markkinatutkimuksiin. Asiakasryhmät kartoitin tutustumalla messutapahtumissa saatuihin kontakteihin. Päätutkimusmenetelmänä käytin haastatteluja. Niihin osallistui kaikkiaan 14 vastaajaa. He vasatsivat kysymyksiin ostomotiiveista ja tuotteesta. Eräs haastattelujen tärkeimmistä teemoista liittyi yhteydenpito- ja jakelukanaviin, joista 12 vastaajaa antoivat mielipiteitään. Työni tulokset viittaavat siihen, että markkinatilanne näyttää positiiviselta KONEen kannalta. Tutkimuksesta sain selville kotihissin asiakassegmentit ja myös miten nämä potentiaaliset asiakkaat saadaan tehokkaimmin tavoitettua.

Multi-sensor Simultaneous Localization and Mapping

Simultaneous localization and mapping(SLAM) is a very important problem in mobile robotics. Many solutions have been proposed by different scientists during the last two decades, nevertheless few studies have considered the use of multiple sensors simultane¬ously. The solution is on combining several data sources with the aid of an Extended Kalman Filter (EKF). Two approaches are proposed. The first one is to use the ordinary EKF SLAM algorithm for each data source separately in parallel and then at the end of each step, fuse the results into one solution. Another proposed approach is the use of multiple data sources simultaneously in a single filter. The comparison of the computational com¬plexity of the two methods is also presented. The first method is almost four times faster than the second one.

A systematic mapping study of web services discovery mechanisms

Context: Web services have been gaining popularity due to the success of service oriented architecture and cloud computing. Web services offer tremendous opportunity for service developers to publish their services and applications over the boundaries of the organization or company. However, to fully exploit these opportunities it is necessary to find efficient discovery mechanism thus, Web services discovering mechanism has attracted a considerable attention in Semantic Web research, however, there have been no literature surveys that systematically map the present research result thus overall impact of these research efforts and level of maturity of their results are still unclear. This thesis aims at providing an overview of the current state of research into Web services discovering mechanism using systematic mapping. The work is based on the papers published 2004 to 2013, and attempts to elaborate various aspects of the analyzed literature including classifying them in terms of the architecture, frameworks and methods used for web services discovery mechanism. Objective: The objective if this work is to summarize the current knowledge that is available as regards to Web service discovery mechanisms as well as to systematically identify and analyze the current published research works in order to identify different approaches presented. Method: A systematic mapping study has been employed to assess the various Web Services discovery approaches presented in the literature. Systematic mapping studies are useful for categorizing and summarizing the level of maturity research area. Results: The result indicates that there are numerous approaches that are consistently being researched and published in this field. In terms of where these researches are published, conferences are major contributing publishing arena as 48% of the selected papers were conference published papers illustrating the level of maturity of the research topic. Additionally selected 52 papers are categorized into two broad segments namely functional and non-functional based approaches taking into consideration architectural aspects and information retrieval approaches, semantic matching, syntactic matching, behavior based matching as well as QOS and other constraints.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

A systematic mapping study on open data

This thesis presented the overview of Open Data research area, quantity of evidence and establishes the research evidence based on the Systematic Mapping Study (SMS). There are 621 such publications were identified published between years 2005 and 2014, but only 243 were selected in the review process. This thesis highlights the implications of Open Data principals’ proliferation in the emerging era of the accessibility, reusability and sustainability of data transparency. The findings of mapping study are described in quantitative and qualitative measurement based on the organization affiliation, countries, year of publications, research method, star rating and units of analysis identified. Furthermore, units of analysis were categorized by development lifecycle, linked open data, type of data, technical platforms, organizations, ontology and semantic, adoption and awareness, intermediaries, security and privacy and supply of data which are important component to provide a quality open data applications and services. The results of the mapping study help the organizations (such as academia, government and industries), re-searchers and software developers to understand the existing trend of open data, latest research development and the demand of future research. In addition, the proposed conceptual framework of Open Data research can be adopted and expanded to strengthen and improved current open data applications.