On state and parameter estimation in chaotic systems

State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

Probabilistic position and orientation estimation of rigid objects using an RGB-D sensor

The recent emergence of low-cost RGB-D sensors has brought new opportunities for robotics by providing affordable devices that can provide synchronized images with both color and depth information. In this thesis, recent work on pose estimation utilizing RGBD sensors is reviewed. Also, a pose recognition system for rigid objects using RGB-D data is implemented. The implementation uses half-edge primitives extracted from the RGB-D images for pose estimation. The system is based on the probabilistic object representation framework by Detry et al., which utilizes Nonparametric Belief Propagation for pose inference. Experiments are performed on household objects to evaluate the performance and robustness of the system.

Greenhouse gas emissions from peat and biomass-derived fuels, electricity and heat — Estimation of various production chains by using LCA methodology

More discussion is required on how and which types of biomass should be used to achieve a significant reduction in the carbon load released into the atmosphere in the short term. The energy sector is one of the largest greenhouse gas (GHG) emitters and thus its role in climate change mitigation is important. Replacing fossil fuels with biomass has been a simple way to reduce carbon emissions because the carbon bonded to biomass is considered as carbon neutral. With this in mind, this thesis has the following objectives: (1) to study the significance of the different GHG emission sources related to energy production from peat and biomass, (2) to explore opportunities to develop more climate friendly biomass energy options and (3) to discuss the importance of biogenic emissions of biomass systems. The discussion on biogenic carbon and other GHG emissions comprises four case studies of which two consider peat utilization, one forest biomass and one cultivated biomasses. Various different biomass types (peat, pine logs and forest residues, palm oil, rapeseed oil and jatropha oil) are used as examples to demonstrate the importance of biogenic carbon to life cycle GHG emissions. The biogenic carbon emissions of biomass are defined as the difference in the carbon stock between the utilization and the non-utilization scenarios of biomass. Forestry-drained peatlands were studied by using the high emission values of the peatland types in question to discuss the emission reduction potential of the peatlands. The results are presented in terms of global warming potential (GWP) values. Based on the results, the climate impact of the peat production can be reduced by selecting high-emission-level peatlands for peat production. The comparison of the two different types of forest biomass in integrated ethanol production in pulp mill shows that the type of forest biomass impacts the biogenic carbon emissions of biofuel production. The assessment of cultivated biomasses demonstrates that several selections made in the production chain significantly affect the GHG emissions of biofuels. The emissions caused by biofuel can exceed the emissions from fossil-based fuels in the short term if biomass is in part consumed in the process itself and does not end up in the final product. Including biogenic carbon and other land use carbon emissions into the carbon footprint calculations of biofuel reveals the importance of the time frame and of the efficiency of biomass carbon content utilization. As regards the climate impact of biomass energy use, the net impact on carbon stocks (in organic matter of soils and biomass), compared to the impact of the replaced energy source, is the key issue. Promoting renewable biomass regardless of biogenic GHG emissions can increase GHG emissions in the short term and also possibly in the long term.

Modeling and Parameter Estimation of Double-Star Permanent Magnet Synchronous Machines

The power rating of wind turbines is constantly increasing; however, keeping the voltage rating at the low-voltage level results in high kilo-ampere currents. An alternative for increasing the power levels without raising the voltage level is provided by multiphase machines. Multiphase machines are used for instance in ship propulsion systems, aerospace applications, electric vehicles, and in other high-power applications including wind energy conversion systems. A machine model in an appropriate reference frame is required in order to design an efficient control for the electric drive. Modeling of multiphase machines poses a challenge because of the mutual couplings between the phases. Mutual couplings degrade the drive performance unless they are properly considered. In certain multiphase machines there is also a problem of high current harmonics, which are easily generated because of the small current path impedance of the harmonic components. However, multiphase machines provide special characteristics compared with the three-phase counterparts: Multiphase machines have a better fault tolerance, and are thus more robust. In addition, the controlled power can be divided among more inverter legs by increasing the number of phases. Moreover, the torque pulsation can be decreased and the harmonic frequency of the torque ripple increased by an appropriate multiphase configuration. By increasing the number of phases it is also possible to obtain more torque per RMS ampere for the same volume, and thus, increase the power density. In this doctoral thesis, a decoupled d–q model of double-star permanent-magnet (PM) synchronous machines is derived based on the inductance matrix diagonalization. The double-star machine is a special type of multiphase machines. Its armature consists of two three-phase winding sets, which are commonly displaced by 30 electrical degrees. In this study, the displacement angle between the sets is considered a parameter. The diagonalization of the inductance matrix results in a simplified model structure, in which the mutual couplings between the reference frames are eliminated. Moreover, the current harmonics are mapped into a reference frame, in which they can be easily controlled. The work also presents methods to determine the machine inductances by a finite-element analysis and by voltage-source inverters on-site. The derived model is validated by experimental results obtained with an example double-star interior PM (IPM) synchronous machine having the sets displaced by 30 electrical degrees. The derived transformation, and consequently, the decoupled d–q machine model, are shown to model the behavior of an actual machine with an acceptable accuracy. Thus, the proposed model is suitable to be used for the model-based control design of electric drives consisting of double-star IPM synchronous machines.

Managing Customer Issues through a Support Channel Network

The importance of after-sales service or service in general can be seen and experienced by customers every day with industrial as well as other non-industrial services or products. This dissertation, drawing on theory and experience, focuses on practical engineering implications, specifically the management of customer issues in the after-sales phase in the mobile phone arena. The main objective of this doctoral dissertation is to investigate customer after-sales issue management, specifically regarding mobile phones. The case studies focus on issue resolution time and the issue of corrective actions. This dissertation consists of a main body and four peer-reviewed journal articles and one manuscript currently under review by a peer-reviewed journal. The main body of this dissertation examines the elements of customer satisfaction, loyalty, and retention with respect to corrective actions to address customer issues and issue resolution time through literature and empirical studies. The five independent works are case studies supporting the thesis research questions. This study examines four questions: 1) What are the factors affecting corrective actions for customers? 2) How can customer issue resolution time be controlled? 3) What are the factors affecting processes in the service chain? and 4) How can communication be measured in a service chain? In this work, both quantitative and qualitative analysis methods are used. The main body of the thesis reviews the literature regarding the elements that bridge the five case studies. The case studies of the articles and surveys lean more toward the methodology of critical positivism and then apply the interpretive approach in interpreting the results. The case study articles employ various statistical methods to analyze and to interpret the empirical and survey data. The statistical methods were used to create a model that is useful for significantly optimizing issue resolution time. Moreover, it was found that samples for verifying issues provided by the customer neither improve the perceived quality of corrective actions nor the perceived quality of issue resolution time. The term “service” in this work is limited to the technical services that are provided by product manufacturers and after-sales authorized service vendors. On the basis of this research work, it has been observed that corrective actions and issue resolution time are associated with customer satisfaction and hence, according to induction theory, to customer loyalty and retention. This thesis utilizes knowledge of marketing and customer relationships to contribute to the existing body of knowledge concerning information and communication technology for after-sales service recovery of mobile terminals. The established models in the thesis contribute to the existing knowledge of the after-sales process of dealing with customer issues in the field of mobile phones. The findings suggest that process managers could focus more on communication and training provided to the staff as new technology evolves rapidly. The study also suggest the managers formulate strategies for how customers can be kept informed on a regular basis of the status of issues that have been escalated for corrective action. The findings also lay the foundation for the comprehensive objective to control the entire product development process, starting with conceptualization. This implies that robust design should be applied to the new products so that problems affecting customer service quality are not repeated. The objective will be achieved when the entire service chain from product development to the final user can be modeled and this model can be used to support the organization at all levels.

Distribution channel plan for wound care products: Case 3M Finland Ltd.

The aim of this master’s thesis was to make a qualitative marketing research and on the basis of this to develop a distribution plan for the case company Finnish 3M Ltd.’s wound care products. The literature review includes three important parts: distribution channel planning, the buying behavior of seniors, and special characteristics of health care products’ marketing. The empirical part of this thesis comprises two different parts. The first part is a marketing research, in which the buying behavior of wound care products is studied in Espoo. The research aim was to examine, in which distribution channels the wound care patients under home care would most preferably buy wound care products during the time period, when municipalities will not yet provide the products for free. The data was collected through semi-structured phone interviews and regular interviews, and was treated qualitatively and anonymously. The study revealed that the recommendations of nurses and doctors influenced most the buying behavior of wound care customers. In the second part of the thesis a distribution channel plan for wound care products was made for the case company 3M Finland Ltd. based on the results. 3M Finland Ltd. should focus on pharmacies, online-stores and municipal health centers as their main distributors.

The estimation of tuberculosis transmission parameters using ABC and MCMC methods

The aim of this work is to apply approximate Bayesian computation in combination with Marcov chain Monte Carlo methods in order to estimate the parameters of tuberculosis transmission. The methods are applied to San Francisco data and the results are compared with the outcomes of previous works. Moreover, a methodological idea with the aim to reduce computational time is also described. Despite the fact that this approach is proved to work in an appropriate way, further analysis is needed to understand and test its behaviour in different cases. Some related suggestions to its further enhancement are described in the corresponding chapter.

Net working capital estimation model in project business

The objective of this Master’s thesis is to develop a model which estimates net working capital (NWC) monthly in a year period. The study is conducted by a constructive research which uses a case study. The estimation model is designed in the need of one case company which operates in project business. Net working capital components should be linked together by an automatic model and estimated individually, including advanced components of NWC for example POC receivables. Net working capital estimation model of this study contains three parts: output template, input template and calculation model. The output template gets estimate values automatically from the input template and the calculation model. Into the input template estimate values of more stable NWC components are inputted manually. The calculate model gets estimate values for major affecting components automatically from the systems of a company by using a historical data and made plans. As a precondition for the functionality of the estimation calculation is that sales are estimated in one year period because the sales are linked to all NWC components.

Remote sensing for three-dimensional modelling of hydromorphology

Successful management of rivers requires an understanding of the fluvial processes that govern them. This, in turn cannot be achieved without a means of quantifying their geomorphology and hydrology and the spatio-temporal interactions between them, that is, their hydromorphology. For a long time, it has been laborious and time-consuming to measure river topography, especially in the submerged part of the channel. The measurement of the flow field has been challenging as well, and hence, such measurements have long been sparse in natural environments. Technological advancements in the field of remote sensing in the recent years have opened up new possibilities for capturing synoptic information on river environments. This thesis presents new developments in fluvial remote sensing of both topography and water flow. A set of close-range remote sensing methods is employed to eventually construct a high-resolution unified empirical hydromorphological model, that is, river channel and floodplain topography and three-dimensional areal flow field. Empirical as well as hydraulic theory-based optical remote sensing methods are tested and evaluated using normal colour aerial photographs and sonar calibration and reference measurements on a rocky-bed sub-Arctic river. The empirical optical bathymetry model is developed further by the introduction of a deep-water radiance parameter estimation algorithm that extends the field of application of the model to shallow streams. The effect of this parameter on the model is also assessed in a study of a sandy-bed sub-Arctic river using close-range high-resolution aerial photography, presenting one of the first examples of fluvial bathymetry modelling from unmanned aerial vehicles (UAV). Further close-range remote sensing methods are added to complete the topography integrating the river bed with the floodplain to create a seamless high-resolution topography. Boat- cart- and backpack-based mobile laser scanning (MLS) are used to measure the topography of the dry part of the channel at a high resolution and accuracy. Multitemporal MLS is evaluated along with UAV-based photogrammetry against terrestrial laser scanning reference data and merged with UAV-based bathymetry to create a two-year series of seamless digital terrain models. These allow the evaluation of the methodology for conducting high-resolution change analysis of the entire channel. The remote sensing based model of hydromorphology is completed by a new methodology for mapping the flow field in 3D. An acoustic Doppler current profiler (ADCP) is deployed on a remote-controlled boat with a survey-grade global navigation satellite system (GNSS) receiver, allowing the positioning of the areally sampled 3D flow vectors in 3D space as a point cloud and its interpolation into a 3D matrix allows a quantitative volumetric flow analysis. Multitemporal areal 3D flow field data show the evolution of the flow field during a snow-melt flood event. The combination of the underwater and dry topography with the flow field yields a compete model of river hydromorphology at the reach scale.

Power efficiency estimation and simulation of different control methods for the rotary screw compressor

Nowadays the energy efficiency has become one of the most concerned topics. Compressors are the equipment, which is very common in industry. Moreover, they tend to operate during long cycles and therefore even small decrease in power consumption can significantly reduce electricity costs during the year. And therefore it is important to investigate ways of increasing the energy efficiency of the compressors. In the thesis rotary screw compressor alongside with different control approaches is described. Simulation models for various control types of rotary screw compressor are developed. Analysis of laboratory equipment is conducted and results are compared with simulation. Suggestions of the real laboratory equipment improvement are given.

Software business expansion through distribution channel : Case M-Files - Denmark

The purpose of this study was to find out how a software company can successfully expand business to the Danish software market through distribution channel. The study was commissioned by a Finnish software company and it was conducted using a qualitative research method by analyzing external and internal business environment, and interviewing Danish ICT organizations and M-Files personnel. Interviews were semi-structured interviews, which were designed to collect comprehensive information on the existing ICT and software market in Denmark. The research used three external and internal analyzing frameworks; PEST analysis (market level), Porter´s Five Force analysis (industry level competition) and SWOT analysis (company level). Distribution channels theory was a base to understand why and what kind of distribution channels the case company uses, and what kind of channels target markets companies’ uses. Channel strategy and design were integrated to the industry level analysis. The empirical findings revealed that Denmark has very business friendly ICT environment. Several organizations have ranked Denmark´s information and communication technology as the best in the world. Denmark’s ICT and software market are relatively small, compared to many other countries in Europe. Danish software market is centralized. Largest software clusters are in the largest cities; Copenhagen, Aarhus, Odense and Aalborg. From these clusters, software companies can most likely find suitable resellers. The following growing trends are clearly seen in the software market: mobile and wireless applications, outsourcing, security solutions, cloud computing, social business solutions and e-business solutions. When expanding software business to the Danish market, it is important to take into account these trends. In Denmark distribution channels varies depending on the product or service. For many, a natural distribution channel is a local partner or internet. In the public sector solutions are purchased through a public procurement process. In the private sector the buying process is more straight forwarded. Danish companies are buying software from reliable suppliers. This means that they usually buy software direct from big software vendors or local partners. Some customers prefer to use professional consulting companies. These consulting companies can strongly influence on the selection of the supplier and products, and in this light, consulting companies can be important partners for software companies. Even though the competition is fierce in ECM and DMS solutions, Danish market offers opportunities for foreign companies. Penetration to the Danish market through reseller channel requires advanced solutions and objective selection criteria for channel partners. Based on the findings, Danish companies are interested in advanced and efficient software solutions. Interest towards M-Files solutions was clearly seen and the company has excellent opportunity to expand business to the Danish market through reseller channel. Since the research explored the Danish ICT and software market, the results of the study may offer valuable information also to the other software companies which are expanding their business to the Danish market.

Comparison of Model-Based Flow Rate Estimation Methods in Frequency-Converter-Driven Pumps and Fans

Fluid handling systems such as pump and fan systems are found to have a significant potential for energy efficiency improvements. To deliver the energy saving potential, there is a need for easily implementable methods to monitor the system output. This is because information is needed to identify inefficient operation of the fluid handling system and to control the output of the pumping system according to process needs. Model-based pump or fan monitoring methods implemented in variable speed drives have proven to be able to give information on the system output without additional metering; however, the current model-based methods may not be usable or sufficiently accurate in the whole operation range of the fluid handling device. To apply model-based system monitoring in a wider selection of systems and to improve the accuracy of the monitoring, this paper proposes a new method for pump and fan output monitoring with variable-speed drives. The method uses a combination of already known operating point estimation methods. Laboratory measurements are used to verify the benefits and applicability of the improved estimation method, and the new method is compared with five previously introduced model-based estimation methods. According to the laboratory measurements, the new estimation method is the most accurate and reliable of the model-based estimation methods.

The new era of customer experience in the omni-channel environment of a communication service provider

This study discusses the evolution of an omni-channel model in managing customer experience. The purpose of this thesis is to expand the current academic literature available on omni-channel and offer suggestions for omni-channel creation. This is done by studying the features of an omni-channel approach into engaging with customers and through the sub-objectives of describing the process behind its initiation as well as the special features communication service providers need to take in consideration. Theories used as a background for this study are related to customer experience, channel management, omni-channel and finally change management. The empirical study of this thesis consists of seven expert interviews conducted in a case company. The interviews were held between March and November 2014. One of the interviewees is the manager of an omni-channel development team, whilst the rest were in charge of the management of the various customer channels of the company. The organization and analysis of the interview data was conducted topically. The use of themes related to major theories on the subject was utilized to create linkages between theory and practice. The responses were also organized in two groups based on the viewpoint to map responses related to the company perspective as well as the customers´ perspective. The findings in this study are that omni-channel is among the best tools for companies to respond to the challenge induced by changing customer needs and preferences, as well as intensifying competitive environment. The omni-channel model was found to promote excellent customer experience and thus to be a source of competition advantage and increasing financial returns by creating an omni-experience for the customer. Through omniexperience customers see all of the transactions with a company presenting one brand and providing ease and effortlessness in every encounter. The processes behind omni-channel formulation were identified as customer experience proclaimed as the most important strategic goal, mapping and establishing a unified brand experience in all (service) channels and empowering the first line personnel as the gate keepers of omniexperience. Further the tools, measurement and supporting strategies were to be in accordance with the omni-channel strategy and the customer needs to become a partner in a two way transaction with the firm. Based on these findings a model for omni-channel creation is offered. Future research is needed to firstly, further test these findings and expand the theoretical framework on omni-channel, as it is quite scarce to date and secondly, to increase the generalizability of the model suggested.