Differential Evolution approach and parameter estimation of chaotic

Parameter estimation still remains a challenge in many important applications. There is a need to develop methods that utilize achievements in modern computational systems with growing capabilities. Owing to this fact different kinds of Evolutionary Algorithms are becoming an especially perspective field of research. The main aim of this thesis is to explore theoretical aspects of a specific type of Evolutionary Algorithms class, the Differential Evolution (DE) method, and implement this algorithm as codes capable to solve a large range of problems. Matlab, a numerical computing environment provided by MathWorks inc., has been utilized for this purpose. Our implementation empirically demonstrates the benefits of a stochastic optimizers with respect to deterministic optimizers in case of stochastic and chaotic problems. Furthermore, the advanced features of Differential Evolution are discussed as well as taken into account in the Matlab realization. Test "toycase" examples are presented in order to show advantages and disadvantages caused by additional aspects involved in extensions of the basic algorithm. Another aim of this paper is to apply the DE approach to the parameter estimation problem of the system exhibiting chaotic behavior, where the well-known Lorenz system with specific set of parameter values is taken as an example. Finally, the DE approach for estimation of chaotic dynamics is compared to the Ensemble prediction and parameter estimation system (EPPES) approach which was recently proposed as a possible solution for similar problems.

Opinion Mining

In this thesis we study the field of opinion mining by giving a comprehensive review of the available research that has been done in this topic. Also using this available knowledge we present a case study of a multilevel opinion mining system for a student organization's sales management system. We describe the field of opinion mining by discussing its historical roots, its motivations and applications as well as the different scientific approaches that have been used to solve this challenging problem of mining opinions. To deal with this huge subfield of natural language processing, we first give an abstraction of the problem of opinion mining and describe the theoretical frameworks that are available for dealing with appraisal language. Then we discuss the relation between opinion mining and computational linguistics which is a crucial pre-processing step for the accuracy of the subsequent steps of opinion mining. The second part of our thesis deals with the semantics of opinions where we describe the different ways used to collect lists of opinion words as well as the methods and techniques available for extracting knowledge from opinions present in unstructured textual data. In the part about collecting lists of opinion words we describe manual, semi manual and automatic ways to do so and give a review of the available lists that are used as gold standards in opinion mining research. For the methods and techniques of opinion mining we divide the task into three levels that are the document, sentence and feature level. The techniques that are presented in the document and sentence level are divided into supervised and unsupervised approaches that are used to determine the subjectivity and polarity of texts and sentences at these levels of analysis. At the feature level we give a description of the techniques available for finding the opinion targets, the polarity of the opinions about these opinion targets and the opinion holders. Also at the feature level we discuss the various ways to summarize and visualize the results of this level of analysis. In the third part of our thesis we present a case study of a sales management system that uses free form text and that can benefit from an opinion mining system. Using the knowledge gathered in the review of this field we provide a theoretical multi level opinion mining system (MLOM) that can perform most of the tasks needed from an opinion mining system. Based on the previous research we give some hints that many of the laborious market research tasks that are done by the sales force, which uses this sales management system, can improve their insight about their partners and by that increase the quality of their sales services and their overall results.

Design of User Authentication System for Multi-operator wireless LANs

Langattomat lähiverkot ovat viime vuosikymmeninä saavuttaneet suuren suosion. Tässä työssä käsitellään käyttäjien todentamisjärjestelmän suunnittelua ja kehitystä langattomaan monioperaattoriverkkoon. Langattomassa monioperaattoriverkossa käyttäjillä on mahdollisuus käyttää eri operaattoreiden palveluita. Aluksi käsitellään olemassa olevia todentamismenetelmiä ja -järjestelmiä. minkä jälkeen kuvaillaan todentamisjärjestelmä langattomille monioperaattoriverkoille. Todentamisjärjestelmän ratkaisuvaihtoehtoja esitellään kaksi, niin sanotut moni- istunto - ja yksittäisistuntomalli. Moni-istuntomalli on normaali lähestymistapa käyttäjien todentamiseen tietokonejärjestelmissä. Siinä käyttäjän pitää tunnistautua ja todentaa itsensä jokaiselle verkon palvelulle erikseen. Yksittäisistuntomallissa pyritään parempaan luotettavuuteen ja käytettävyyteen. Siinä käyttäjä todentaa itsensä vain kerran ja voi sen jälkeen päästä useisiin palveluihin. Työn loppuosassa kuvaillaan suunnitellun järjestelmän toteutusta. Lisäksi ehdotetaan vaihtoehtoisia toteutustapoja, analysoidaan järjestelmän heikkouksia ja kerrotaan jatkokehitysmahdoillisuuksista.

Modification of a quantum efficiency measurement system for multi-junction solar cells

In this thesis the basic structure and operational principals of single- and multi-junction solar cells are considered and discussed. Main properties and characteristics of solar cells are briefly described. Modified equipment for measuring the quantum efficiency for multi-junction solar cell is presented. Results of experimental research single- and multi-junction solar cells are described.

Influence of multi-phase phenomena on semibatch crystallization processes of aqueous solutions

Crystal properties, product quality and particle size are determined by the operating conditions in the crystallization process. Thus, in order to obtain desired end-products, the crystallization process should be effectively controlled based on reliable kinetic information, which can be provided by powerful analytical tools such as Raman spectrometry and thermal analysis. The present research work studied various crystallization processes such as reactive crystallization, precipitation with anti-solvent and evaporation crystallization. The goal of the work was to understand more comprehensively the fundamentals, phenomena and utilizations of crystallization, and establish proper methods to control particle size distribution, especially for three phase gas-liquid-solid crystallization systems. As a part of the solid-liquid equilibrium studies in this work, prediction of KCl solubility in a MgCl2-KCl-H2O system was studied theoretically. Additionally, a solubility prediction model by Pitzer thermodynamic model was investigated based on solubility measurements of potassium dihydrogen phosphate with the presence of non-electronic organic substances in aqueous solutions. The prediction model helps to extend literature data and offers an easy and economical way to choose solvent for anti-solvent precipitation. Using experimental and modern analytical methods, precipitation kinetics and mass transfer in reactive crystallization of magnesium carbonate hydrates with magnesium hydroxide slurry and CO2 gas were systematically investigated. The obtained results gave deeper insight into gas-liquid-solid interactions and the mechanisms of this heterogeneous crystallization process. The research approach developed can provide theoretical guidance and act as a useful reference to promote development of gas-liquid reactive crystallization. Gas-liquid mass transfer of absorption in the presence of solid particles in a stirred tank was investigated in order to gain understanding of how different-sized particles interact with gas bubbles. Based on obtained volumetric mass transfer coefficient values, it was found that the influence of the presence of small particles on gas-liquid mass transfer cannot be ignored since there are interactions between bubbles and particles. Raman spectrometry was successfully applied for liquid and solids analysis in semi-batch anti-solvent precipitation and evaporation crystallization. Real-time information such as supersaturation, formation of precipitates and identification of crystal polymorphs could be obtained by Raman spectrometry. The solubility prediction models, monitoring methods for precipitation and empirical model for absorption developed in this study together with the methodologies used gives valuable information for aspects of industrial crystallization. Furthermore, Raman analysis was seen to be a potential controlling method for various crystallization processes.

Control of multi-actuator system by an electrically driven hydraulic pump-motor

The awareness and concern of our environment together with legislation have set more and more tightening demands for energy efficiency of non-road mobile machinery (NRMM). Integrated electro-hydraulic energy converter (IEHEC) has been developed in Lappeenranta University of Technology (LUT). The elimination of resistance flow, and the recuperation of energy makes it very efficient alternative. The difficulties of IEHEC machine to step to the market has been the requirement of one IEHEC machine per one actuator. The idea is to switch IEHEC between two actuators of log crane using fast on/off valves. The control system architecture is introduced. The system has been simulated in co-simulation using two different software. The simulated responses of pump-controlled system is compared to the responses of the conventional valve-controlled system.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.

Multi-site -sertifikaatin vaatimukset ympäristöjohtamisjärjestelmän rakentamisessa

Diplomityö muodostuu kahdesta kokonaisuudesta. Työn teoriaosa kertoo mitä ympäristöjohtaminen on, millaisia ovat multi-site -organisaatio ja multi-site -johtamisjärjestelmä sekä mitä vaatimuksia nämä asettavat yritykselle. Työssä esitetään malli, jota käyttämällä kansainvälisten johtamisjärjestelmästandardien mukaan rakennetut laatu-, ympäristö-, terveys- ja turvallisuusjärjestelmät voidaan yhdistää yhdeksi kokonaisuudeksi, multi-site - johtamisjärjestelmäksi. Malli rakentuu kolmesta tasosta, joita ovat paikallinen, maakohtainen ja konsernitaso. Esimerkkien avulla kerrotaan miteneri lähtökohdista voidaan näiden tasojen kautta edetä kohti yhtä johtamiskokonaisuutta. Esille tuodaan myös multi-site -johtamisjärjestelmän käyttöönottoa puoltavat ja vastustavat näkökohdat. Työn konkreettinen osa on johtamisjärjestelmämallin paikallisen tason toteuttaminen. Ympäristöjohtamisjärjestelmän rakentaminen standardin EN ISO 14001:2004 vaatimusten mukaiseksi Kvaerner Power Oy:n Suomen toimipaikoille sekä tämän järjestelmän yhdistäminen sertifioituun EN ISO 9001 -standardin mukaiseen laatujärjestelmään. Työssä kerrotaan miten ympäristöjohtamisjärjestelmä on rakennettu ja miten laatu- ja ympäristöjärjestelmät on liitetty yhdeksi kokonaisuudeksi. Työn tuloksena syntyi malli johtamisjärjestelmien yhdistämisestä sekä sertifioitu ympäristöjohtamisjärjestelmä, jonka yhdistäminen laatujärjestelmään toteutettiin tavoitteiden mukaisesti.

Modeling and Simulation ofReal-Time System as a Tool to Improve Capacity Management - Case Fenix

Tämän tutkimustyön kohteena on TietoEnator Oy:n kehittämän Fenix-tietojärjestelmän kapasiteettitarpeen ennustaminen. Työn tavoitteena on tutustua Fenix-järjestelmän eri osa-alueisiin, löytää tapa eritellä ja mallintaa eri osa-alueiden vaikutus järjestelmän kuormitukseen ja selvittää alustavasti mitkä parametrit vaikuttavat kyseisten osa-alueiden luomaan kuormitukseen. Osa tätä työtä on tutkia eri vaihtoehtoja simuloinnille ja selvittää eri vaihtoehtojen soveltuvuus monimutkaisten järjestelmien mallintamiseen. Kerätyn tiedon pohjaltaluodaan järjestelmäntietovaraston kuormitusta kuvaava simulaatiomalli. Hyödyntämällä mallista saatua tietoa ja tuotantojärjestelmästä mitattua tietoa mallia kehitetään vastaamaan yhä lähemmin todellisen järjestelmän toimintaa. Mallista tarkastellaan esimerkiksi simuloitua järjestelmäkuormaa ja jonojen käyttäytymistä. Tuotantojärjestelmästä mitataan eri kuormalähteiden käytösmuutoksia esimerkiksi käyttäjämäärän ja kellonajan suhteessa. Tämän työn tulosten on tarkoitus toimia pohjana myöhemmin tehtävälle jatkotutkimukselle, jossa osa-alueiden parametrisointia tarkennetaan lisää, mallin kykyä kuvata todellista järjestelmää tehostetaanja mallin laajuutta kasvatetaan.

Field Sales Management Control: Towards a Multi-Level Theory

The purpose of this dissertation is to increase the understanding and knowledge of field sales management control systems (i.e. sales managers monitoring, directing, evaluating and rewarding activities) and their potential consequences on salespeople. This topic is important because research conducted in the past has indicated that the choice of control system type can on the other hand have desirable consequences, such as high levels of motivation and performance, and on the other hand leadto harmful unintended consequences, such as opportunistic or unethical behaviors. Despite the fact that marketing and sales management control systems have been under rigorous research for over two decades, it still is at a very early stage of development, and several inconsistencies can be found in the research results. This dissertation argues that these inconsistencies are mainly derived from misspecification of the level of analysis in the past research. These different levels of analysis (i.e. strategic, tactical, and operational levels) involve very different decision-making situations regarding the control and motivation of sales force, which should be taken into consideration when conceptualizing the control. Moreover, the study of salesperson consequences of a field sales management control system is actually a cross-level phenomenon, which means that at least two levels of analysis are simultaneously involved. The results of this dissertation confirm the need to re-conceptualize the field sales management control system concept. It provides empirical evidence for the assertion that control should be conceptualized with more details atthe tactical/operational level of analysis than at the strategic levelof analysis. Moreover, the results show that some controls are more efficiently communicated to field salespeople than others. It is proposed that this difference is due to different purposes of control; some controls aredesigned for influencing salespersons' behavior (aim at motivating) whereas some controls are designed to aid decision-making (aim at providing information). According to the empirical results of this dissertation, the both types of controls have an impact to the sales force, but this impactis not as strong as expected. The results obtained in this dissertation shed some light to the nature of field sales management control systems, and their consequences on salespeopl

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.

Application of Neural Network Methods in the Prediction of Stock Markets

The purpose of the research is to define practical profit which can be achieved using neural network methods as a prediction instrument. The thesis investigates the ability of neural networks to forecast future events. This capability is checked on the example of price prediction during intraday trading on stock market. The executed experiments show predictions of average 1, 2, 5 and 10 minutes’ prices based on data of one day and made by two different types of forecasting systems. These systems are based on the recurrent neural networks and back propagation neural nets. The precision of the predictions is controlled by the absolute error and the error of market direction. The economical effectiveness is estimated by a special trading system. In conclusion, the best structures of neural nets are tested with data of 31 days’ interval. The best results of the average percent of profit from one transaction (buying + selling) are 0.06668654, 0.188299453, 0.349854787 and 0.453178626, they were achieved for prediction periods 1, 2, 5 and 10 minutes. The investigation can be interesting for the investors who have access to a fast information channel with a possibility of every-minute data refreshment.

Design and Comparison оf Mixed Hinf/H2 Controller fоr АMB System

This master’s thesis is focused on the active magnetic bearings control, specifically the robust control. As carrying out of such kind of control used mixed H2/Hinf controller. So the goal of this work is to design it using Robust Control Toolbox™ in MATLAB and compare it performance and robustness with Hinf robust controller characteristics. But only one degree-of-freedom controller considered.

Phase voltage control and filtering in a converter-fed single-phase customer-end system of the LVDC distribution network

In recent years, the network vulnerability to natural hazards has been noticed. Moreover, operating on the limits of the network transmission capabilities have resulted in major outages during the past decade. One of the reasons for operating on these limits is that the network has become outdated. Therefore, new technical solutions are studied that could provide more reliable and more energy efficient power distributionand also a better profitability for the network owner. It is the development and price of power electronics that have made the DC distribution an attractive alternative again. In this doctoral thesis, one type of a low-voltage DC distribution system is investigated. Morespecifically, it is studied which current technological solutions, used at the customer-end, could provide better power quality for the customer when compared with the current system. To study the effect of a DC network on the customer-end power quality, a bipolar DC network model is derived. The model can also be used to identify the supply parameters when the V/kW ratio is approximately known. Although the model provides knowledge of the average behavior, it is shown that the instantaneous DC voltage ripple should be limited. The guidelines to choose an appropriate capacitance value for the capacitor located at the input DC terminals of the customer-end are given. Also the structure of the customer-end is considered. A comparison between the most common solutions is made based on their cost, energy efficiency, and reliability. In the comparison, special attention is paid to the passive filtering solutions since the filter is considered a crucial element when the lifetime expenses are determined. It is found out that the filter topology most commonly used today, namely the LC filter, does not provide economical advantage over the hybrid filter structure. Finally, some of the typical control system solutions are introduced and their shortcomings are presented. As a solution to the customer-end voltage regulation problem, an observer-based control scheme is proposed. It is shown how different control system structures affect the performance. The performance meeting the requirements is achieved by using only one output measurement, when operating in a rigid network. Similar performance can be achieved in a weak grid by DC voltage measurement. An additional improvement can be achieved when an adaptive gain scheduling-based control is introduced. As a conclusion, the final power quality is determined by a sum of various factors, and the thesis provides the guidelines for designing the system that improves the power quality experienced by the customer.

Choosing the optimal energy system for buildings and districts

The purpose of this master’s thesis was to develop a method to be used in the selection of an optimal energy system for buildings and districts. The term optimal energy system was defined as the energy system which best fulfils the requirements of the stakeholder on whose preferences the energy systems are evaluated. The most influential stakeholder in the process of selecting an energy system was considered to be the district developer. The selection method consisted of several steps: Definition of the district, calculating the energy consumption of the district and buildings within the district, defining suitable energy system alternatives for the district, definition of the comparing criteria, calculating the parameters of the comparing criteria for each energy system alternative and finally using a multi-criteria decision method to rank the alternatives. For the purposes of the selection method, the factors affecting the energy consumption of buildings and districts and technologies enabling the use of renewable energy were reviewed. The key element of the selection method was a multi-criteria decision making method, PROMETHEE II. In order to compare the energy system alternatives with the developed method, the comparing criteria were defined in the study. The criteria included costs, environmental impacts and technological and technical characteristics of the energy systems. Each criterion was given an importance, based on a questionnaire which was sent for the steering groups of two district development projects. The selection method was applied in two case study analyses. The results indicate that the selection method provides a viable and easy way to provide the decision makers alternatives and recommendations regarding the selection of an energy system. Since the comparison is carried out by changing the alternatives into numeric form, the presented selection method was found to exclude any unjustified preferences over certain energy systems alternatives which would affect the selection.