Effectiveness of Pilotage

The objective of the pilotage effectiveness study was to come up with a process descrip-tion of the pilotage procedure, to design performance indicators based on this process description, to be used by Finnpilot, and to work out a preliminary plan for the imple-mentation of the indicators within the Finnpilot organisation. The theoretical aspects of pilotage as well as the guidelines and standards used were determined through a literature review. Based on the literature review, a process flow model with the following phases was created: the planning of pilotage, the start of pilo-tage, the act of pilotage, the end of pilotage and the closing of pilotage. The model based on the literature review was tested through interviews and observation of pilotage. At the same time an e-mail survey directed at foreign pilotage organisations, which included a questionnaire concerning their standards and management systems, operations procedures, measurement tools and their attitude to the passage planning, was conducted. The main issues in the observations and interviews were the passage plan and the bridge team co-operation. The phases of the pilotage process model emerged in both the pilotage activities and the interviews whereas bridge team co-operation was relatively marginal. Most of the pilotage organisations, who responded to the query, also use some standard-based management system. All organisations who answered the survey use some sort of a pilotage process model. According to the query, the main measuring tools for pilotage are statistical information concerning pilotage and the organisations, the customer feedback surveys, and financial results. Attitudes to-wards passage planning were mostly positive among the organisations. A workshop with pilotage experts was arranged where the process model constructed on the basis of the literature review was tuned to match practical pilotage. In the workshop it was determined that certain phases and the corresponding tasks, through which pilo-tage can be described as a process, were identifiable in all pilotage. The result of the workshop was a complemented process model, which separates incoming and outgoing traffic, as well as the fairway pilotage and harbour pilotage from each other. Addition-ally indicators divided according to the data gathering method were defined. Data con-cerning safety and traffic flow is gathered in the form of customer feedback. The pilot's own perceptions of the pilotage process are gathered through self-assessment. The measurement data which is connected to the phases of the pilotage process is generated e.g. by gathering statistics of the success of the pilot dispatches, the accuracy of the pi-lotage and the incidents that occurred during the pilotage, near misses, deviations and accidents. The measurement data is collected via the PilotWeb at the closing of the pilo-tage. A separate project and a project group with pilots also participating will be established for the deployment of the performance indicators. The phases of the project are: the definition phase, the implementation phase and the deployment phase. The purpose of the definition phase is to prepare questions for ship commanders concerning the cus-tomer feedback questionnaire and also to work out the self-assessment queries and the queries concerning the process indicators.

On Energy Efficient Computing Platforms

In accordance with the Moore's law, the increasing number of on-chip integrated transistors has enabled modern computing platforms with not only higher processing power but also more affordable prices. As a result, these platforms, including portable devices, work stations and data centres, are becoming an inevitable part of the human society. However, with the demand for portability and raising cost of power, energy efficiency has emerged to be a major concern for modern computing platforms. As the complexity of on-chip systems increases, Network-on-Chip (NoC) has been proved as an efficient communication architecture which can further improve system performances and scalability while reducing the design cost. Therefore, in this thesis, we study and propose energy optimization approaches based on NoC architecture, with special focuses on the following aspects. As the architectural trend of future computing platforms, 3D systems have many bene ts including higher integration density, smaller footprint, heterogeneous integration, etc. Moreover, 3D technology can signi cantly improve the network communication and effectively avoid long wirings, and therefore, provide higher system performance and energy efficiency. With the dynamic nature of on-chip communication in large scale NoC based systems, run-time system optimization is of crucial importance in order to achieve higher system reliability and essentially energy efficiency. In this thesis, we propose an agent based system design approach where agents are on-chip components which monitor and control system parameters such as supply voltage, operating frequency, etc. With this approach, we have analysed the implementation alternatives for dynamic voltage and frequency scaling and power gating techniques at different granularity, which reduce both dynamic and leakage energy consumption. Topologies, being one of the key factors for NoCs, are also explored for energy saving purpose. A Honeycomb NoC architecture is proposed in this thesis with turn-model based deadlock-free routing algorithms. Our analysis and simulation based evaluation show that Honeycomb NoCs outperform their Mesh based counterparts in terms of network cost, system performance as well as energy efficiency.

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.

Prosessiautomaatio pinnankorkeusmittauksen koelaitteistoissa

Pinnankorkeuden tunteminen kiehutusvesireaktorin painesäiliössä on erittäin tärkeää sen turvallisuusvaikutusten takia. Pinnankorkeutta mitataan vesipatsaiden korkeutta havaitsevien paine-eromittausten avulla. Säteilyturvakeskuksen YVL-ohjeiden mukaan turvallisuuteen vaikuttavien mittausten täytyy noudattaa moninkertaistus- ja erilaisuusperiaatteita. Yleensä erilaisuusperiaatetta on toteutettu käyttämällä erityyppisiä paine-eromittareita, mutta erilaisella fysikaalisella toimintaperiaatteella oleva mittaus olisi parempi ja toteuttaisi paremmin erilaisuusperiaatetta. Uimurikytkin olisi tällainen fysikaalisesti eri periaatteeseen perustuva pinnankorkeuden mittauslaite. Ydinvoimalaan tarkoitettu teknologia tulee kelpoistaa riippumattoman tahon toimesta ennen käyttöönottoa. Kelpoistamiskokeita varten Lappeenrannan teknillisen yliopiston Ydinturvallisuuden tutkimusyksikköön rakennettiin vuosina 2011–2013 kaksi koelaitteistoa. Näillä koelaitteistoilla tutkittiin uimurikytkimien toimintaa ja ominaisuuksia erilaisissa kiehutusvesireaktorin käyttötilanteissa. Koelaitteistot tarvitsivat toimiakseen automaatiojärjestelmät, jotka suunniteltiin pääosin noudattamalla suunnittelun elinkaarimallia sekä automaatiosuunnittelun sisältökokonaisuuksia. Automaatiojärjestelmien suunnittelu aloitettiin määrittelemällä koejärjestelyjen asettamat vaatimukset, jonka jälkeen tehtiin teknologiavalinnat. Seuraavaksi suunniteltiin automaatiojärjestelmien logiikkaohjelmistot, joiden kuvaukseen tämä työ pääasiassa keskittyy. Logiikkaohjelmistot toteutettiin graafisella National Instruments LabView -ohjelmointikielellä. Logiikkaohjelmistojen tuli hoitaa tiedonkeruuta, käyttöautomaatiota, turvallisuustehtäviä sekä kokeisiin liittyviä erikoistehtäviä. Ohjelmistot saatiin esikokeiden aikana toimimaan halutusti, ja varsinaiset kokeet voitiin suorittaa ilman merkittäviä ongelmia.

Mathematical modeling and optimal control of malaria

Malaria continues to infect millions and kill hundreds of thousands of people worldwide each year, despite over a century of research and attempts to control and eliminate this infectious disease. Challenges such as the development and spread of drug resistant malaria parasites, insecticide resistance to mosquitoes, climate change, the presence of individuals with subpatent malaria infections which normally are asymptomatic and behavioral plasticity in the mosquito hinder the prospects of malaria control and elimination. In this thesis, mathematical models of malaria transmission and control that address the role of drug resistance, immunity, iron supplementation and anemia, immigration and visitation, and the presence of asymptomatic carriers in malaria transmission are developed. A within-host mathematical model of severe Plasmodium falciparum malaria is also developed. First, a deterministic mathematical model for transmission of antimalarial drug resistance parasites with superinfection is developed and analyzed. The possibility of increase in the risk of superinfection due to iron supplementation and fortification in malaria endemic areas is discussed. The model results calls upon stakeholders to weigh the pros and cons of iron supplementation to individuals living in malaria endemic regions. Second, a deterministic model of transmission of drug resistant malaria parasites, including the inflow of infective immigrants, is presented and analyzed. The optimal control theory is applied to this model to study the impact of various malaria and vector control strategies, such as screening of immigrants, treatment of drug-sensitive infections, treatment of drug-resistant infections, and the use of insecticide-treated bed nets and indoor spraying of mosquitoes. The results of the model emphasize the importance of using a combination of all four controls tools for effective malaria intervention. Next, a two-age-class mathematical model for malaria transmission with asymptomatic carriers is developed and analyzed. In development of this model, four possible control measures are analyzed: the use of long-lasting treated mosquito nets, indoor residual spraying, screening and treatment of symptomatic, and screening and treatment of asymptomatic individuals. The numerical results show that a disease-free equilibrium can be attained if all four control measures are used. A common pitfall for most epidemiological models is the absence of real data; model-based conclusions have to be drawn based on uncertain parameter values. In this thesis, an approach to study the robustness of optimal control solutions under such parameter uncertainty is presented. Numerical analysis of the optimal control problem in the presence of parameter uncertainty demonstrate the robustness of the optimal control approach that: when a comprehensive control strategy is used the main conclusions of the optimal control remain unchanged, even if inevitable variability remains in the control profiles. The results provide a promising framework for the design of cost-effective strategies for disease control with multiple interventions, even under considerable uncertainty of model parameters. Finally, a separate work modeling the within-host Plasmodium falciparum infection in humans is presented. The developed model allows re-infection of already-infected red blood cells. The model hypothesizes that in severe malaria due to parasite quest for survival and rapid multiplication, the Plasmodium falciparum can be absorbed in the already-infected red blood cells which accelerates the rupture rate and consequently cause anemia. Analysis of the model and parameter identifiability using Markov chain Monte Carlo methods is presented.

Creating a Branding Process Model for Living Area Brands - Developing and managing a new living area brand

The objective of this thesis is to understand how to create and develop a successful place brand and how to manage it systematically. The thesis thoroughly explains the phenomenon of place brands and place branding and presents different sub-categories of place branding. The theoretical part of the thesis provides a wide overview on the prevailing literature of place branding, place brand development and place brand management, which form the basis of the thesis’ theoretical framework. The theoretical evidence is gathered from a case living area. The living area is developed by one construction company, which has a significant role in the construction industry in Finland. The empirical evidence is gathered through semi-structured in-depth interviews by interviewing the new living area’s carefully selected stakeholder groups. Afterwards the empirical data is analyzed and reflected to the theoretical findings. After examining the case living area, the thesis will present a new living area branding process model based on prevailing theories and empirical findings.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Customer Need Assessment for Differentiation in Building Information Modeling

Building Information Modeling – BIM is widely spreading in the Architecture, Engineering, and Construction (AEC) industries. Manufacturers of building elements are also starting to provide more and more objects of their products. The ideal availability and distribution for these models is not yet stabilized. Usual goal of a manufacturer is to get their model into design as early as possible. Finding the ways to satisfy customer needs with a superior service would help to achieve this goal. This study aims to seek what case company’s customers want out of the model and what they think is the ideal way to obtain these models and what are the desired functionalities for this service. This master’s thesis uses a modified version of lead user method to gain understanding of what the needs are in a longer term. In this framework also benchmarking of current solutions and their common model functions is done. Empirical data is collected with survey and interviews. As a result this thesis provides understanding that what is the information customer uses when obtaining a model, what kind of model is expected to be achieved and how is should the process optimally function. Based on these results ideal service is pointed out.

Active Magnetic Bearing System Identification Methods and Rotor Model Updating

Active magnetic bearing is a type of bearing which uses magnetic field to levitate the rotor. These bearings require continuous control of the currents in electromagnets and data from position of the rotor and the measured current from electromagnets. Because of this different identification methods can be implemented with no additional hardware. In this thesis the focus was to implement and test identification methods for active magnetic bearing system and to update the rotor model. Magnetic center calibration is a method used to locate the magnetic center of the rotor. Rotor model identification is an identification method used to identify the rotor model. Rotor model update is a method used to update the rotor model based on identification data. These methods were implemented and tested with a real machine where rotor was levitated with active magnetic bearings and the functionality of the methods was ensured. Methods were developed with further extension in mind and also with the possibility to apply them for different machines with ease.

Palveluruokamarkkinoiden innovatiivisen toimintamallin suunnittelu

Diplomityön tavoitteena on ollut kehittää elintarvikeyrityksen palveluruokamarkkinoille uusi innovatiivinen toimintamalli haastattelujen, havainnoinnin ja kirjallisuuden perusteella. Tutkimusongelman päätutkimuskysymys on: Miten yrityksen palveluruoka- eli valmisruokatuotteille suunnitellaan innovatiivinen toimintamalli tuoteperheen ja jakelun suhteen? Tavoitteena on kartoittaa yrityksen palveluruoan nykytilanne ja luoda toimintamalli, joka toisi yritykselle selkeää lisäarvoa ja kilpailuetua. Teoreettisessa osuudessa selvitetään elintarviketeollisuuden, valmisruoan ja elintarvikelogistiikan tilannetta suomalaisesta ja globaalista näkökulmasta. Työssä on tarkasteltu elintarvikepuolen nykytilannetta ja tulevaisuuden suuntauksia tuotteiden, ruokailutottumusten ja logistiikan osalta. Innovaatioiden osalta työ painottuu palveluruokapuolen konseptin ja uuden logistisen yhteistyöhön pohjautuvan mallin kehittämiseen. Työn käytännön osiossa on tehty case-tutkimus ”yrityksen palveluruoan nykytilanne tuotteiden ja logistiikan osalta”. Toimialan markkinatilannetta on kartoitettu, jotta hahmotetaan, missä on potentiaalisimmat markkinat palveluruoalle. Työn tavoitteena on ollut kehittää Hoviruoka Oy:lle palveluruoan segmentointiin ja logistiikkaan liittyvä innovatiivinen toimintamalli. Toimintamallin avulla yritys saa kilpailuetua ja taloudellista hyötyä kilpailijoihin nähden, ja on edelläkävijä kyseisen toimintamallin ansiosta. Työn tuloksissa on käsitelty keskeiset tulokset ja mahdolliset jatkotoimenpiteet. Työssä kehitettiin yritykselle uusi toimintamalli palveluruoka puolelle. Työlle asetetut tavoitteet saavutettiin kaikkien kolmen - tekijän, yliopiston ja yrityksen - kannalta.

Using electroencephalography signals to control acoustical processing

Current hearing-assistive technology performs poorly in noisy multi-talker conditions. The goal of this thesis was to establish the feasibility of using EEG to guide acoustic processing in such conditions. To attain this goal, this research developed a model via the constructive research method, relying on literature review. Several approaches have revealed improvements in the performance of hearing-assistive devices under multi-talker conditions, namely beamforming spatial filtering, model-based sparse coding shrinkage, and onset enhancement of the speech signal. Prior research has shown that electroencephalography (EEG) signals contain information that concerns whether the person is actively listening, what the listener is listening to, and where the attended sound source is. This thesis constructed a model for using EEG information to control beamforming, model-based sparse coding shrinkage, and onset enhancement of the speech signal. The purpose of this model is to propose a framework for using EEG signals to control sound processing to select a single talker in a noisy environment containing multiple talkers speaking simultaneously. On a theoretical level, the model showed that EEG can control acoustical processing. An analysis of the model identified a requirement for real-time processing and that the model inherits the computationally intensive properties of acoustical processing, although the model itself is low complexity placing a relatively small load on computational resources. A research priority is to develop a prototype that controls hearing-assistive devices with EEG. This thesis concludes highlighting challenges for future research.

Online MBPeT dashboard : enabling performance testing as a service in the cloud

In this thesis, tool support is addressed for the combined disciplines of Model-based testing and performance testing. Model-based testing (MBT) utilizes abstract behavioral models to automate test generation, thus decreasing time and cost of test creation. MBT is a functional testing technique, thereby focusing on output, behavior, and functionality. Performance testing, however, is non-functional and is concerned with responsiveness and stability under various load conditions. MBPeT (Model-Based Performance evaluation Tool) is one such tool which utilizes probabilistic models, representing dynamic real-world user behavior patterns, to generate synthetic workload against a System Under Test and in turn carry out performance analysis based on key performance indicators (KPI). Developed at Åbo Akademi University, the MBPeT tool is currently comprised of a downloadable command-line based tool as well as a graphical user interface. The goal of this thesis project is two-fold: 1) to extend the existing MBPeT tool by deploying it as a web-based application, thereby removing the requirement of local installation, and 2) to design a user interface for this web application which will add new user interaction paradigms to the existing feature set of the tool. All phases of the MBPeT process will be realized via this single web deployment location including probabilistic model creation, test configurations, test session execution against a SUT with real-time monitoring of user configurable metric, and final test report generation and display. This web application (MBPeT Dashboard) is implemented with the Java programming language on top of the Vaadin framework for rich internet application development. The Vaadin framework handles the complicated web communications processes and front-end technologies, freeing developers to implement the business logic as well as the user interface in pure Java. A number of experiments are run in a case study environment to validate the functionality of the newly developed Dashboard application as well as the scalability of the solution implemented in handling multiple concurrent users. The results support a successful solution with regards to the functional and performance criteria defined, while improvements and optimizations are suggested to increase both of these factors.