Web Presence Building and Performance Measuring in Business-to-Business Markets

Tutkimuksen tavoite oli selvittää yrityksen web toiminnan rakentamisen vaiheita sekä menestyksen mittaamista. Rakennusprosessia tutkittiin viisiportaisen askelmallin avulla. Mallin askeleet ovat; arviointi, strategian muotoilu, suunnitelma, pohjapiirros ja toteutus. Arviointi- ja toteutusvaiheiden täydentämiseksi sekä erityisesti myös internet toiminnan onnistumisen mittaamisen avuksi internet toiminnan hyödyt (CRM,kommunikointi-, myynti-, ja jakelukanava hyödyt markkinoinnin kannalta) käsiteltiin. Toiminnan menestyksen arvioinnin avuksi esiteltiin myös porrasmalli internet toimintaan. Porrasmalli määrittelee kauppakulissi-, dynaaminen-, transaktio- ja e-businessportaat. Tutkimuksessa löydettiin menestystekijöitä internet toimintojen menestykselle. Nämä tekijät ovat laadukas sisältö, kiinnostavuus, viihdyttävyys, informatiivisuus, ajankohtaisuus, personoitavuus, luottamus, interaktiivisuus, käytettävyys, kätevyys, lojaalisuus, suoriutuminen, responssiivisuus ja käyttäjätiedon kerääminen. Mittarit jaettiin tutkimuksessa aktiivisuus-, käyttäytymis- ja muunnosmittareihin. Lisäksi muita mittareita ja menestysindikaattoreita esiteltiin. Nämä menestyksen elementit ja mittarit koottiin yhteen uudessa internet toimintojen menestyksenarviointimallissa. Tutkielman empiirisessä osuudessa,esitettyjä teorioita peilattiin ABB:n (ABB:n sisällä erityisesti ABB Stotz-Kontakt) web toimintaan. Apuna olivat dokumenttianalyysi sekä haastattelut. Empiirinen osa havainnollisti teoriat käytännössä ja toi ilmi mahdollisuuden teorioiden laajentamiseen. Internet toimintojen rakentamismallia voidaan käyttää myös web toimintojen kehittämiseen ja porrasmalli sopii myös nykyisten internet toimintojen arvioimiseen. Mittareiden soveltaminen käytännössä toi kuitenkin ilmi tarpeen niiden kehittämiseen ja aiheen lisätutkimukseen. Niiden tulisi olla myös aiempaatiiviimmin liitetty kokonaisvaltaisen liiketoiminnan menestyksen mittaamiseen.

R&D Performance Analysis: Case Studies on the Challenges and Promotion of the Evaluation and Measurement of R&D

Due to the intense international competition, demanding, and sophisticated customers, and diverse transforming technological change, organizations need to renew their products and services by allocating resources on research and development (R&D). Managing R&D is complex, but vital for many organizations to survive in the dynamic, turbulent environment. Thus, the increased interest among decision-makers towards finding the right performance measures for R&D is understandable. The measures or evaluation methods of R&D performance can be utilized for multiple purposes; for strategic control, for justifying the existence of R&D, for providing information and improving activities, as well as for the purposes of motivating and benchmarking. The earlier research in the field of R&D performance analysis has generally focused on either the activities and considerable factors and dimensions - e.g. strategic perspectives, purposes of measurement, levels of analysis, types of R&D or phases of R&D process - prior to the selection of R&Dperformance measures, or on proposed principles or actual implementation of theselection or design processes of R&D performance measures or measurement systems. This study aims at integrating the consideration of essential factors anddimensions of R&D performance analysis to developed selection processes of R&D measures, which have been applied in real-world organizations. The earlier models for corporate performance measurement that can be found in the literature, are to some extent adaptable also to the development of measurement systemsand selecting the measures in R&D activities. However, it is necessary to emphasize the special aspects related to the measurement of R&D performance in a way that make the development of new approaches for especially R&D performance measure selection necessary: First, the special characteristics of R&D - such as the long time lag between the inputs and outcomes, as well as the overall complexity and difficult coordination of activities - influence the R&D performance analysis problems, such as the need for more systematic, objective, balanced and multi-dimensional approaches for R&D measure selection, as well as the incompatibility of R&D measurement systems to other corporate measurement systems and vice versa. Secondly, the above-mentioned characteristics and challenges bring forth the significance of the influencing factors and dimensions that need to be recognized in order to derive the selection criteria for measures and choose the right R&D metrics, which is the most crucial step in the measurement system development process. The main purpose of this study is to support the management and control of the research and development activities of organizations by increasing the understanding of R&D performance analysis, clarifying the main factors related to the selection of R&D measures and by providing novel types of approaches and methods for systematizing the whole strategy- and business-based selection and development process of R&D indicators.The final aim of the research is to support the management in their decision making of R&D with suitable, systematically chosen measures or evaluation methods of R&D performance. Thus, the emphasis in most sub-areas of the present research has been on the promotion of the selection and development process of R&D indicators with the help of the different tools and decision support systems, i.e. the research has normative features through providing guidelines by novel types of approaches. The gathering of data and conducting case studies in metal and electronic industry companies, in the information and communications technology (ICT) sector, and in non-profit organizations helped us to formulate a comprehensive picture of the main challenges of R&D performance analysis in different organizations, which is essential, as recognition of the most importantproblem areas is a very crucial element in the constructive research approach utilized in this study. Multiple practical benefits regarding the defined problemareas could be found in the various constructed approaches presented in this dissertation: 1) the selection of R&D measures became more systematic when compared to the empirical analysis, as it was common that there were no systematic approaches utilized in the studied organizations earlier; 2) the evaluation methods or measures of R&D chosen with the help of the developed approaches can be more directly utilized in the decision-making, because of the thorough consideration of the purpose of measurement, as well as other dimensions of measurement; 3) more balance to the set of R&D measures was desired and gained throughthe holistic approaches to the selection processes; and 4) more objectivity wasgained through organizing the selection processes, as the earlier systems were considered subjective in many organizations. Scientifically, this dissertation aims to make a contribution to the present body of knowledge of R&D performance analysis by facilitating dealing with the versatility and challenges of R&D performance analysis, as well as the factors and dimensions influencing the selection of R&D performance measures, and by integrating these aspects to the developed novel types of approaches, methods and tools in the selection processes of R&D measures, applied in real-world organizations. In the whole research, facilitation of dealing with the versatility and challenges in R&D performance analysis, as well as the factors and dimensions influencing the R&D performance measure selection are strongly integrated with the constructed approaches. Thus, the research meets the above-mentioned purposes and objectives of the dissertation from the scientific as well as from the practical point of view.

Ramp-up Predictability - Designing and Prototyping Ramp-up Predictability concept for new product creation

Diplomityön tavoitteena on tutkia ja kehittää menetelmä tuotekehitysprojektin ajalliselle ennustamiselle tuotteen siirtyessä tuotekehityksestä massatuotantoon. Ajallisen ennustamisen merkitys korostuu mitä lähemmäksi uuden tuotteen massatuotannon aloittaminen (ramp-up) tulee, koska strategiset päätökset koskien mm. uusia tuotantolinjoja, materiaalien- ja komponenttien tilaamisia sekä vahvistus asiakastoimitusten aloittamista täytyy tehdä jo paljon aikaisemmin.Työ aloitetaan tutkimalla rinnakkaista insinöörityötä (concurrent engineering) sekä suoritusten mittaamista (performance measurement), joiden sisältämistä ajattelumalleista, työkaluista ja tekniikoista hahmottuivat ajallisen ennustettavuuden onnistumisen edellytykset. Näitä olivat suunnitellun tuotteen ja tuotekehitysprosessin laatu sekä resurssien ja tiimien kompetenssit. Toisaalta ajalliseen ennustettavuuteen vaikuttavat myös projektien riippuvuudet ulkoisista toimittajista ja heidän aikatauluistaan.Teoreettisena viitekehyksenä käytetään Bradford L. Goldense:n luomaa mallia tuotekehityksen proaktiiviseksi mittaamiseksi sekä sovelletaan W. Edward Deming:in jatkuvan parantamisen silmukkaa. Työssä kehitetään Ramp-up Predictability konsepti, joka koostuu keskipitkän ja pitkän aikavälin ennustamisesta. Työhön ei kuulunut mallin käyttöönotto ja seuranta.Toimenpide ehdotuksena esitetään lisätutkimusta mittareiden keskinäisestä korrelaatioista ja niiden luotettavuudesta sekä mallien tarjoamista mahdollisuuksista muille tulosyksiköille.

Many valued algebraic structures as measures of comparison

This thesis studies the properties and usability of operators called t-norms, t-conorms, uninorms, as well as many valued implications and equivalences. Into these operators, weights and a generalized mean are embedded for aggregation, and they are used for comparison tasks and for this reason they are referred to as comparison measures. The thesis illustrates how these operators can be weighted with a differential evolution and aggregated with a generalized mean, and the kinds of measures of comparison that can be achieved from this procedure. New operators suitable for comparison measures are suggested. These operators are combination measures based on the use of t-norms and t-conorms, the generalized 3_-uninorm and pseudo equivalence measures based on S-type implications. The empirical part of this thesis demonstrates how these new comparison measures work in the field of classification, for example, in the classification of medical data. The second application area is from the field of sports medicine and it represents an expert system for defining an athlete's aerobic and anaerobic thresholds. The core of this thesis offers definitions for comparison measures and illustrates that there is no actual difference in the results achieved in comparison tasks, by the use of comparison measures based on distance, versus comparison measures based on many valued logical structures. The approach has been highly practical in this thesis and all usage of the measures has been validated mainly by practical testing. In general, many different types of operators suitable for comparison tasks have been presented in fuzzy logic literature and there has been little or no experimental work with these operators.

Reconstruction and analysis of surface variation using photometric stereo

In many industrial applications, accurate and fast surface reconstruction is essential for quality control. Variation in surface finishing parameters, such as surface roughness, can reflect defects in a manufacturing process, non-optimal product operational efficiency, and reduced life expectancy of the product. This thesis considers reconstruction and analysis of high-frequency variation, that is roughness, on planar surfaces. Standard roughness measures in industry are calculated from surface topography. A fast and non-contact method to obtain surface topography is to apply photometric stereo in the estimation of surface gradients and to reconstruct the surface by integrating the gradient fields. Alternatively, visual methods, such as statistical measures, fractal dimension and distance transforms, can be used to characterize surface roughness directly from gray-scale images. In this thesis, the accuracy of distance transforms, statistical measures, and fractal dimension are evaluated in the estimation of surface roughness from gray-scale images and topographies. The results are contrasted to standard industry roughness measures. In distance transforms, the key idea is that distance values calculated along a highly varying surface are greater than distances calculated along a smoother surface. Statistical measures and fractal dimension are common surface roughness measures. In the experiments, skewness and variance of brightness distribution, fractal dimension, and distance transforms exhibited strong linear correlations to standard industry roughness measures. One of the key strengths of photometric stereo method is the acquisition of higher frequency variation of surfaces. In this thesis, the reconstruction of planar high-frequency varying surfaces is studied in the presence of imaging noise and blur. Two Wiener filterbased methods are proposed of which one is optimal in the sense of surface power spectral density given the spectral properties of the imaging noise and blur. Experiments show that the proposed methods preserve the inherent high-frequency variation in the reconstructed surfaces, whereas traditional reconstruction methods typically handle incorrect measurements by smoothing, which dampens the high-frequency variation.

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.

Color ad spectral image assessment using novel quality and fidelity techniques

The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.

Conventional and novel cardiovascular risk factors in young Finns and their associations with structural and functional vascular changes of subclinical atherosclerosis. The Cardiovascular Risk in Young Finns Study

Background: Atherosclerosis begins in early life progressing from asymptomatic to symptomatic as we age. Although substantial progress has been made in identifying the determinants of atherosclerosis in middle to older age adults at increased cardiovascular risk, there is lack of data examining determinants and prediction of atherosclerosis in young adults. Aims: The current study was designed to investigate levels of cardiovascular risk factors in young adults, subclinical measures of atherosclerosis, and prediction of subclinical arterial changes with conventional risk factor measures and novel metabolic profiling of serum samples. Subjects and Methods: This thesis utilised data from the follow-ups performed in 2001 and 2007 in the Cardiovascular Risk in Young Finns study, a Finnish population-based prospective cohort study that examined 2,204 subjects who were aged 30-45 years in 2007. Subclinical atherosclerosis was studied using noninvasive ultrasound measurements of carotid intima-media thickness (IMT), carotid arterial distensibility (CDist) and brachial flow-mediated dilation (FMD). Measurements included conventional risk factors and metabolic profiling using highthroughput nuclear magnetic resonance (NMR) methods that provided data on 42 lipid markers and 16 circulating metabolites. Results: Trends in lipids were favourable between 2001 and 2007, whereas waist circumference, fasting glucose, and blood pressure levels increased. To study the stability of noninvasive ultrasound markers, 6-year tracking (the likelihood to maintain the original fractile over time) in 6 years was examined. IMT tracked more strongly than CDist and FMD. Cardiovascular risk scores (Framingham, SCORE, Finrisk, Reynolds and PROCAM) predicted subclinical atherosclerosis equally. Lipoprotein subclass testing did not improve the prediction of subclinical atherosclerosis over and above conventional risk factors. However, circulating metabolites improved risk stratification. Tyrosine and docosahexaenoic acid were found to be novel biomarkers of high IMT. Conclusions: Prediction of cardiovascular risk in young Finnish adults can be performed with any of the existing risk scores. The addition of metabonomics to risk stratification improves prediction of subclinical changes and enables more accurate targeting of prevention at an early stage.

Search and Paper SKU Analysis of Recipes Meeting EUPS Standard

The theoretical research of the study concentrated on finding theoretical frameworks to optimize the amount of needed stock keeping units (SKUs) in manufacturing industry. The goal was to find ways for a company to acquire an optimal collection of stock keeping units needed for manufacturing needed amount of end products. The research follows constructive research approach leaning towards practical problem solving. In the empirical part of this study, a recipe search tool was developed to an existing database used in the target company. The purpose of the tools was to find all the recipes meeting the EUPS performance standard and put the recipes in a ranking order using the data available in the database. The ranking of the recipes was formed from the combination of the performance measures and price of the recipes. In addition, the tool researched what kind of paper SKUs were needed to manufacture the best performing recipes. The tool developed during this process meets the requirements. It eases and makes it much faster to search for all the recipes meeting the EUPS standard. Furthermore, many future development possibilities for the tool were discovered while writing the thesis.

Corporate Social Responsibility and Shipping Views of Baltic Sea Shipping Companies on the Benefits of Responsibility

The safety of shipping operations in the Baltic Sea is an extensively studied issue due to the density of traffic and the ecological sensitivity of the area. The focus has, however, mainly been on ship technology or on traffic control measures and the operative safety aspect of shipping is in a minor position in maritime safety studies and is lacking in terms of solutions. Self-regulatory and voluntary measures could be effective ways to improve the operational safety of shipping. Corporate social responsibility, or CSR, is one example of a voluntary measure that the shipping companies can take. CSR can enhance maritime safety and improve the shipping companies’ competitiveness. The aim of this study is to increase the knowledge of CSR in the maritime sector and study its applicability and benefits to the shipping companies. The research comprises of a theory part and a questionnaire study, which examine the significance of corporate social responsibility in shipping companies’ maritime safety and competitiveness. The aim of the questionnaire study is to find out how corporate social responsibility is implemented in the shipping companies. According to the literature review, responsible actions can produce financial and time costs, but due to these actions cost savings in the form of learning and increased efficiency can be achieved. Responsible actions can also produce concrete improvements and a reputation of responsibility that can lead to both cost savings and increase in the company’s income. CSR is recognised as having real business benefits in terms of attracting customers and high-quality employees. In shipping, CSR usually focuses on environmental issues. Environmental social responsibility in shipping is mainly motivated by the need to comply with existing and forthcoming regulation. Shipping companies engage in CSR to gain competitive advantage and to increase maritime safety. The social aspects of CSR take into account the well-being and skills of the employees, corporation and other stakeholders of the company. The questionnaire study revealed that the most common CSR measures in shipping companies are environmental measures, and that environmental concerns are considered to be the most important reason to engage in CSR. From the preliminary question about the concept of CSR it can also be seen that safety issues are commonly considered to be a part of CSR and safety gains are the second most important reason to engage in CSR. From the questionnaire, it can also be extrapolated that gaining a better reputation is one of the most important reasons to engage in CSR in the first place. For example, the main economic benefit was seen to be the increase of customer numbers as a result of a better reputation. Based on the study, it would seem that companies are starting to realise that they might gain competitive advantage and be favoured as shippers if they engage in sustainable, responsible operations and present themselves as “green”.

Neurobiological Correlates of Personality Traits: A Study on Harm Avoidance and Neuroticism

Harm Avoidance and Neuroticism are traits that predispose to mental illnesses. Studying them provides a unique way to study predisposition of mental illnesses. Understanding the biological mechanisms that mediate vulnerability could lead to improvement in treatment and ultimately to pre-emptive psychiatry. These personality traits describe a tendency to feel negative emotions such as fear, shyness and worry. Previous studies suggest these traits are regulated by serotonin and opiate pathways. The aim of this thesis was to test the following hypotheses using personality trait measures and positron emission tomography (PET): 1) Brain serotonin transporter density in vivo is associated with Harm Avoidance and Neuroticism traits. 2) μ-opioid receptor binding is associated with Harm Avoidance. In addition, we developed a methodology for studying neurotransmitter interactions in the brain using the opiate and serotonin pathways. 32 healthy subjects who were consistently in either the highest or lowest quartile of the Harm Avoidance trait were recruited from a population-based cohort. Each subject underwent two PET scans, serotonin transporter binding was measured with [11C] MADAM and μ-opioid receptor binding with [11C]carfentanil. We found that the serotonin transporter is not associated with anxious personality traits. However, Harm Avoidance positively correlated with μ-opioid receptor availability. Particularly the tendency to feel shy and the inability to cope with stress were associated μ-opioid receptor availability. We also demonstrated that serotonin transporter binding correlates with μ-opioid receptor binding, suggesting interplay between the two systems. These findings shed light on the neurobiological correlates of personality and have an impact on etiological considerations of affective disorders.

Long-term nutrient load management and lake restoration: Case of Säkylän Pyhäjärvi (SW Finland)

Eutrophication caused by anthropogenic nutrient pollution has become one of the most severe threats to water bodies. Nutrients enter water bodies from atmospheric precipitation, industrial and domestic wastewaters and surface runoff from agricultural and forest areas. As point pollution has been significantly reduced in developed countries in recent decades, agricultural non-point sources have been increasingly identified as the largest source of nutrient loading in water bodies. In this study, Lake Säkylän Pyhäjärvi and its catchment are studied as an example of a long-term, voluntary-based, co-operative model of lake and catchment management. Lake Pyhäjärvi is located in the centre of an intensive agricultural area in southwestern Finland. More than 20 professional fishermen operate in the lake area, and the lake is used as a drinking water source and for various recreational activities. Lake Pyhäjärvi is a good example of a large and shallow lake that suffers from eutrophication and is subject to measures to improve this undesired state under changing conditions. Climate change is one of the most important challenges faced by Lake Pyhäjärvi and other water bodies. The results show that climatic variation affects the amounts of runoff and nutrient loading and their timing during the year. The findings from the study area concerning warm winters and their influences on nutrient loading are in accordance with the IPCC scenarios of future climate change. In addition to nutrient reduction measures, the restoration of food chains (biomanipulation) is a key method in water quality management. The food-web structure in Lake Pyhäjärvi has, however, become disturbed due to mild winters, short ice cover and low fish catch. Ice cover that enables winter seining is extremely important to the water quality and ecosystem of Lake Pyhäjärvi, as the vendace stock is one of the key factors affecting the food web and the state of the lake. New methods for the reduction of nutrient loading and the treatment of runoff waters from agriculture, such as sand filters, were tested in field conditions. The results confirm that the filter technique is an applicable method for nutrient reduction, but further development is needed. The ability of sand filters to absorb nutrients can be improved with nutrient binding compounds, such as lime. Long-term hydrological, chemical and biological research and monitoring data on Lake Pyhäjärvi and its catchment provide a basis for water protection measures and improve our understanding of the complicated physical, chemical and biological interactions between the terrestrial and aquatic realms. In addition to measurements carried out in field conditions, Lake Pyhäjärvi and its catchment were studied using various modelling methods. In the calibration and validation of models, long-term and wide-ranging time series data proved to be valuable. Collaboration between researchers, modellers and local water managers further improves the reliability and usefulness of models. Lake Pyhäjärvi and its catchment can also be regarded as a good research laboratory from the point of view of the Baltic Sea. The main problem in both of them is eutrophication caused by excess nutrients, and nutrient loading has to be reduced – especially from agriculture. Mitigation measures are also similar in both cases.

Power Electronic Converters in Low-Voltage Direct Current Distribution – Analysis and Implementation

Over the recent years, smart grids have received great public attention. Many proposed functionalities rely on power electronics, which play a key role in the smart grid, together with the communication network. However, “smartness” is not the driver that alone motivates the research towards distribution networks based on power electronics; the network vulnerability to natural hazards has resulted in tightening requirements for the supply security, set both by electricity end-users and authorities. Because of the favorable price development and advancements in the field, direct current (DC) distribution has become an attractive alternative for distribution networks. In this doctoral dissertation, power electronic converters for a low-voltage DC (LVDC) distribution system are investigated. These include the rectifier located at the beginning of the LVDC network and the customer-end inverter (CEI) on the customer premises. Rectifier topologies are introduced, and according to the LVDC system requirements, topologies are chosen for the analysis. Similarly, suitable CEI topologies are addressed and selected for study. Application of power electronics into electricity distribution poses some new challenges. Because the electricity end-user is supplied with the CEI, it is responsible for the end-user voltage quality, but it also has to be able to supply adequate current in all operating conditions, including a short-circuit, to ensure the electrical safety. Supplying short-circuit current with power electronics requires additional measures, and therefore, the short-circuit behavior is described and methods to overcome the high-current supply to the fault are proposed. Power electronic converters also produce common-mode (CM) and radio-frequency (RF) electromagnetic interferences (EMI), which are not present in AC distribution. Hence, their magnitudes are investigated. To enable comprehensive research on the LVDC distribution field, a research site was built into a public low-voltage distribution network. The implementation was a joint task by the LVDC research team of Lappeenranta University of Technology and a power company Suur-Savon S¨ahk¨o Oy. Now, the measurements could be conducted in an actual environment. This is important especially for the EMI studies. The main results of the work concern the short-circuit operation of the CEI and the EMI issues. The applicability of the power electronic converters to electricity distribution is demonstrated, and suggestions for future research are proposed.

Energy Efficiency in Electrical Drive Systems: Technical potentials, barriers and policy approaches for small and medium industries in Ghana

Today industries and commerce in Ghana are facing enormous energy challenge. The pressure is on for industries to reduce energy consumption, lower carbon emissions and provide se-cured power supply. Industrial electric motor energy efficiency improvement is one of the most important tools to reduce global warming threat and reduce electricity bills. In order to develop a strategic industrial energy efficiency policy, it is therefore necessary to study the barriers that inhibit the implementation of cost – effective energy efficiency measures and the driving forces that promote the implementation. The aim of this thesis is to analyse the energy consumption pattern of electric motors, study factors that promote or inhibit energy efficiency improvements in EMDS and provide cost – effective solutions that improve energy efficiency to bridge the existing energy efficiency gap in the surveyed industries. The results from this thesis has revealed that, the existence of low energy efficiency in motor-driven systems in the surveyed industries were due to poor maintenance practices, absence of standards, power quality issues, lack of access to capital and limited awareness to the im-portance of energy efficiency improvements in EMDS. However, based on the results pre-sented in this thesis, a policy approach towards industrial SMEs should primarily include dis-counted or free energy audit in providing the industries with the necessary information on potential energy efficiency measures, practice best motor management programmes and estab-lish a minimum energy performance standard (MEPS) for motors imported into the country. The thesis has also shown that education and capacity development programmes, financial incentives and system optimization are effective means to promote energy efficiency in elec-tric motor – driven systems in industrial SMEs in Ghana