Comparison and problems between Traditional and Agile software development methods

In today’s world because of the rapid advancement in the field of technology and business, the requirements are not clear, and they are changing continuously in the development process. Due to those changes in the requirements the software development becomes very difficult. Use of traditional software development methods such as waterfall method is not a good option, as the traditional software development methods are not flexible to requirements and the software can be late and over budget. For developing high quality software that satisfies the customer, the organizations can use software development methods, such as agile methods which are flexible to change requirements at any stage in the development process. The agile methods are iterative and incremental methods that can accelerate the delivery of the initial business values through the continuous planning and feedback, and there is close communication between the customer and developers. The main purpose of the current thesis is to find out the problems in traditional software development and to show how agile methods reduced those problems in software development. The study also focuses the different success factors of agile methods, the success rate of agile projects and comparison between traditional and agile software development.

3D Mesh Simplification. A survey of algorithms and CAD model simplification tests

Simplification of highly detailed CAD models is an important step when CAD models are visualized or by other means utilized in augmented reality applications. Without simplification, CAD models may cause severe processing and storage is- sues especially in mobile devices. In addition, simplified models may have other advantages like better visual clarity or improved reliability when used for visual pose tracking. The geometry of CAD models is invariably presented in form of a 3D mesh. In this paper, we survey mesh simplification algorithms in general and focus especially to algorithms that can be used to simplify CAD models. We test some commonly known algorithms with real world CAD data and characterize some new CAD related simplification algorithms that have not been surveyed in previous mesh simplification reviews.

Multidata inverse problems and Bayesian solution methods in astronomy

Statistical analyses of measurements that can be described by statistical models are of essence in astronomy and in scientific inquiry in general. The sensitivity of such analyses, modelling approaches, and the consequent predictions, is sometimes highly dependent on the exact techniques applied, and improvements therein can result in significantly better understanding of the observed system of interest. Particularly, optimising the sensitivity of statistical techniques in detecting the faint signatures of low-mass planets orbiting the nearby stars is, together with improvements in instrumentation, essential in estimating the properties of the population of such planets, and in the race to detect Earth-analogs, i.e. planets that could support liquid water and, perhaps, life on their surfaces. We review the developments in Bayesian statistical techniques applicable to detections planets orbiting nearby stars and astronomical data analysis problems in general. We also discuss these techniques and demonstrate their usefulness by using various examples and detailed descriptions of the respective mathematics involved. We demonstrate the practical aspects of Bayesian statistical techniques by describing several algorithms and numerical techniques, as well as theoretical constructions, in the estimation of model parameters and in hypothesis testing. We also apply these algorithms to Doppler measurements of nearby stars to show how they can be used in practice to obtain as much information from the noisy data as possible. Bayesian statistical techniques are powerful tools in analysing and interpreting noisy data and should be preferred in practice whenever computational limitations are not too restrictive.

Methods and Models for Accelerating Dynamic Simulation of Fluid Power Circuits

The objective of this dissertation is to improve the dynamic simulation of fluid power circuits. A fluid power circuit is a typical way to implement power transmission in mobile working machines, e.g. cranes, excavators etc. Dynamic simulation is an essential tool in developing controllability and energy-efficient solutions for mobile machines. Efficient dynamic simulation is the basic requirement for the real-time simulation. In the real-time simulation of fluid power circuits there exist numerical problems due to the software and methods used for modelling and integration. A simulation model of a fluid power circuit is typically created using differential and algebraic equations. Efficient numerical methods are required since differential equations must be solved in real time. Unfortunately, simulation software packages offer only a limited selection of numerical solvers. Numerical problems cause noise to the results, which in many cases leads the simulation run to fail. Mathematically the fluid power circuit models are stiff systems of ordinary differential equations. Numerical solution of the stiff systems can be improved by two alternative approaches. The first is to develop numerical solvers suitable for solving stiff systems. The second is to decrease the model stiffness itself by introducing models and algorithms that either decrease the highest eigenvalues or neglect them by introducing steady-state solutions of the stiff parts of the models. The thesis proposes novel methods using the latter approach. The study aims to develop practical methods usable in dynamic simulation of fluid power circuits using explicit fixed-step integration algorithms. In this thesis, twomechanisms whichmake the systemstiff are studied. These are the pressure drop approaching zero in the turbulent orifice model and the volume approaching zero in the equation of pressure build-up. These are the critical areas to which alternative methods for modelling and numerical simulation are proposed. Generally, in hydraulic power transmission systems the orifice flow is clearly in the turbulent area. The flow becomes laminar as the pressure drop over the orifice approaches zero only in rare situations. These are e.g. when a valve is closed, or an actuator is driven against an end stopper, or external force makes actuator to switch its direction during operation. This means that in terms of accuracy, the description of laminar flow is not necessary. But, unfortunately, when a purely turbulent description of the orifice is used, numerical problems occur when the pressure drop comes close to zero since the first derivative of flow with respect to the pressure drop approaches infinity when the pressure drop approaches zero. Furthermore, the second derivative becomes discontinuous, which causes numerical noise and an infinitely small integration step when a variable step integrator is used. A numerically efficient model for the orifice flow is proposed using a cubic spline function to describe the flow in the laminar and transition areas. Parameters for the cubic spline function are selected such that its first derivative is equal to the first derivative of the pure turbulent orifice flow model in the boundary condition. In the dynamic simulation of fluid power circuits, a tradeoff exists between accuracy and calculation speed. This investigation is made for the two-regime flow orifice model. Especially inside of many types of valves, as well as between them, there exist very small volumes. The integration of pressures in small fluid volumes causes numerical problems in fluid power circuit simulation. Particularly in realtime simulation, these numerical problems are a great weakness. The system stiffness approaches infinity as the fluid volume approaches zero. If fixed step explicit algorithms for solving ordinary differential equations (ODE) are used, the system stability would easily be lost when integrating pressures in small volumes. To solve the problem caused by small fluid volumes, a pseudo-dynamic solver is proposed. Instead of integration of the pressure in a small volume, the pressure is solved as a steady-state pressure created in a separate cascade loop by numerical integration. The hydraulic capacitance V/Be of the parts of the circuit whose pressures are solved by the pseudo-dynamic method should be orders of magnitude smaller than that of those partswhose pressures are integrated. The key advantage of this novel method is that the numerical problems caused by the small volumes are completely avoided. Also, the method is freely applicable regardless of the integration routine applied. The superiority of both above-mentioned methods is that they are suited for use together with the semi-empirical modelling method which necessarily does not require any geometrical data of the valves and actuators to be modelled. In this modelling method, most of the needed component information can be taken from the manufacturer’s nominal graphs. This thesis introduces the methods and shows several numerical examples to demonstrate how the proposed methods improve the dynamic simulation of various hydraulic circuits.

Fluid flow and dispersion predictions in porous media by utilizing advanced numerical methods

Diplomityön tavoitteena oli tarkastella numeerisen virtauslaskennan avulla virtaukseen liittyviä ilmiöitä ja kaasun dispersiota. Diplomityön sisältö on jaettu viiteen osaan; johdantoon, teoriaan, katsaukseen virtauksen mallinnukseen huokoisessa materiaalissa liittyviin tutkimusselvityksiin, numeeriseen mallinnukseen sekä tulosten esittämiseen ja johtopäätöksiin. Diplomityön alussa kiinnitettiin huomiota erilaisiin kokeellisiin, numeerisiin ja teoreettisiin mallinnusmenetelmiin, joilla voidaan mallintaa virtausta huokoisessa materiaalissa. Kirjallisuusosassa tehtiin katsaus aikaisemmin julkaistuihin puoliempiirisiin ja empiirisiin tutkimusselvityksiin, jotka liittyvät huokoisen materiaalin aiheuttamaan painehäviöön. Numeerisessa virtauslaskenta osassa rakennettiin ja esitettiin huokoista materiaalia kuvaavat numeeriset mallit käyttäen kaupallista FLUENT -ohjelmistoa. Työn lopussa arvioitiin teorian, numeerisen virtauslaskennan ja kokeellisten tutkimusselvitysten tuloksia. Kolmiulotteisen huokoisen materiaalinnumeerisessa mallinnuksesta saadut tulokset vaikuttivat lupaavilta. Näiden tulosten perusteella tehtiin suosituksia ajatellen tulevaa virtauksen mallinnusta huokoisessa materiaalissa. Osa tässä diplomityössä esitetyistä tuloksista tullaan esittämään 55. Kanadan Kemiantekniikan konferenssissa Torontossa 1619 Lokakuussa 2005. ASME :n kansainvälisessä tekniikan alan julkaisussa. Työ on hyväksytty esitettäväksi esitettäväksi laskennallisen virtausmekaniikan (CFD) aihealueessa 'Peruskäsitteet'. Lisäksi työn yksityiskohtaiset tulokset tullaan lähettämään myös CES:n julkaisuun.

Theoretical and numerical study of thermomagnetic convection in magnetic fluids

In this thesis, the magnetic field control of convection instabilities and heat and mass transfer processesin magnetic fluids have been investigated by numerical simulations and theoretical considerations. Simulation models based on finite element and finite volume methods have been developed. In addition to standard conservation equations, themagnetic field inside the simulation domain is calculated from Maxwell equations and the necessary terms to take into account for the magnetic body force and magnetic dissipation have been added to the equations governing the fluid motion.Numerical simulations of magnetic fluid convection near the threshold supportedexperimental observations qualitatively. Near the onset of convection the competitive action of thermal and concentration density gradients leads to mostly spatiotemporally chaotic convection with oscillatory and travelling wave regimes, previously observed in binary mixtures and nematic liquid crystals. In many applications of magnetic fluids, the heat and mass transfer processes including the effects of external magnetic fields are of great importance. In addition to magnetic fluids, the concepts and the simulation models used in this study may be applied also to the studies of convective instabilities in ordinary fluids as well as in other binary mixtures and complex fluids.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

A Practical Micro Mechanical Model Based Local Approach Methodology for the Analysis of Ductile Fracture of Welded T-Joints

This thesis concentrates on developing a practical local approach methodology based on micro mechanical models for the analysis of ductile fracture of welded joints. Two major problems involved in the local approach, namely the dilational constitutive relation reflecting the softening behaviour of material, and the failure criterion associated with the constitutive equation, have been studied in detail. Firstly, considerable efforts were made on the numerical integration and computer implementation for the non trivial dilational Gurson Tvergaard model. Considering the weaknesses of the widely used Euler forward integration algorithms, a family of generalized mid point algorithms is proposed for the Gurson Tvergaard model. Correspondingly, based on the decomposition of stresses into hydrostatic and deviatoric parts, an explicit seven parameter expression for the consistent tangent moduli of the algorithms is presented. This explicit formula avoids any matrix inversion during numerical iteration and thus greatly facilitates the computer implementation of the algorithms and increase the efficiency of the code. The accuracy of the proposed algorithms and other conventional algorithms has been assessed in a systematic manner in order to highlight the best algorithm for this study. The accurate and efficient performance of present finite element implementation of the proposed algorithms has been demonstrated by various numerical examples. It has been found that the true mid point algorithm (a = 0.5) is the most accurate one when the deviatoric strain increment is radial to the yield surface and it is very important to use the consistent tangent moduli in the Newton iteration procedure. Secondly, an assessment of the consistency of current local failure criteria for ductile fracture, the critical void growth criterion, the constant critical void volume fraction criterion and Thomason's plastic limit load failure criterion, has been made. Significant differences in the predictions of ductility by the three criteria were found. By assuming the void grows spherically and using the void volume fraction from the Gurson Tvergaard model to calculate the current void matrix geometry, Thomason's failure criterion has been modified and a new failure criterion for the Gurson Tvergaard model is presented. Comparison with Koplik and Needleman's finite element results shows that the new failure criterion is fairly accurate indeed. A novel feature of the new failure criterion is that a mechanism for void coalescence is incorporated into the constitutive model. Hence the material failure is a natural result of the development of macroscopic plastic flow and the microscopic internal necking mechanism. By the new failure criterion, the critical void volume fraction is not a material constant and the initial void volume fraction and/or void nucleation parameters essentially control the material failure. This feature is very desirable and makes the numerical calibration of void nucleation parameters(s) possible and physically sound. Thirdly, a local approach methodology based on the above two major contributions has been built up in ABAQUS via the user material subroutine UMAT and applied to welded T joints. By using the void nucleation parameters calibrated from simple smooth and notched specimens, it was found that the fracture behaviour of the welded T joints can be well predicted using present methodology. This application has shown how the damage parameters of both base material and heat affected zone (HAZ) material can be obtained in a step by step manner and how useful and capable the local approach methodology is in the analysis of fracture behaviour and crack development as well as structural integrity assessment of practical problems where non homogeneous materials are involved. Finally, a procedure for the possible engineering application of the present methodology is suggested and discussed.

Teaching mathematics and programming : new approaches with empirical evaluation

Programming and mathematics are core areas of computer science (CS) and consequently also important parts of CS education. Introductory instruction in these two topics is, however, not without problems. Studies show that CS students find programming difficult to learn and that teaching mathematical topics to CS novices is challenging. One reason for the latter is the disconnection between mathematics and programming found in many CS curricula, which results in students not seeing the relevance of the subject for their studies. In addition, reports indicate that students' mathematical capability and maturity levels are dropping. The challenges faced when teaching mathematics and programming at CS departments can also be traced back to gaps in students' prior education. In Finland the high school curriculum does not include CS as a subject; instead, focus is on learning to use the computer and its applications as tools. Similarly, many of the mathematics courses emphasize application of formulas, while logic, formalisms and proofs, which are important in CS, are avoided. Consequently, high school graduates are not well prepared for studies in CS. Motivated by these challenges, the goal of the present work is to describe new approaches to teaching mathematics and programming aimed at addressing these issues: Structured derivations is a logic-based approach to teaching mathematics, where formalisms and justifications are made explicit. The aim is to help students become better at communicating their reasoning using mathematical language and logical notation at the same time as they become more confident with formalisms. The Python programming language was originally designed with education in mind, and has a simple syntax compared to many other popular languages. The aim of using it in instruction is to address algorithms and their implementation in a way that allows focus to be put on learning algorithmic thinking and programming instead of on learning a complex syntax. Invariant based programming is a diagrammatic approach to developing programs that are correct by construction. The approach is based on elementary propositional and predicate logic, and makes explicit the underlying mathematical foundations of programming. The aim is also to show how mathematics in general, and logic in particular, can be used to create better programs.

Novel Methods for Error Modeling and Parameter Identification of a Redundant Serial-Parallel Hybrid Robot

To obtain the desirable accuracy of a robot, there are two techniques available. The first option would be to make the robot match the nominal mathematic model. In other words, the manufacturing and assembling tolerances of every part would be extremely tight so that all of the various parameters would match the “design” or “nominal” values as closely as possible. This method can satisfy most of the accuracy requirements， but the cost would increase dramatically as the accuracy requirement increases. Alternatively, a more cost-effective solution is to build a manipulator with relaxed manufacturing and assembling tolerances. By modifying the mathematical model in the controller, the actual errors of the robot can be compensated. This is the essence of robot calibration. Simply put, robot calibration is the process of defining an appropriate error model and then identifying the various parameter errors that make the error model match the robot as closely as possible. This work focuses on kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial-parallel hybrid robot. The robot consists of a 4-DOF serial mechanism and a 6-DOF hexapod parallel manipulator. The redundant 4-DOF serial structure is used to enlarge workspace and the 6-DOF hexapod manipulator is used to provide high load capabilities and stiffness for the whole structure. The main objective of the study is to develop a suitable calibration method to improve the accuracy of the redundant serial-parallel hybrid robot. To this end, a Denavit–Hartenberg (DH) hybrid error model and a Product-of-Exponential (POE) error model are developed for error modeling of the proposed robot. Furthermore, two kinds of global optimization methods, i.e. the differential-evolution (DE) algorithm and the Markov Chain Monte Carlo (MCMC) algorithm, are employed to identify the parameter errors of the derived error model. A measurement method based on a 3-2-1 wire-based pose estimation system is proposed and implemented in a Solidworks environment to simulate the real experimental validations. Numerical simulations and Solidworks prototype-model validations are carried out on the hybrid robot to verify the effectiveness, accuracy and robustness of the calibration algorithms.

PEAP 802.1x-tunnistuksen toteutus RADIUS-palvelimeen

Valimo iDServer -tunnistuspalvelin on ohjelmisto, joka tukee eri käyttäjientunnistusmenetelmiä, kuten tekstiviestillä lähetettävää kertakäyttösalasanaa tai normaaliakäyttäjätunnusta ja salasanaa. Tässä diplomityössä kuvataan, kuinka palvelimeenon lisätty tuki käyttäjien kirjautumiselle langattoman verkon tukiasemien ja virtuaalilähiverkkoa tukevien kytkinten kautta käyttäen normaaleja Windows-käyttöjärjestelmän mukana tulevia asiakasohjelmistoja. Työn ensimmäisessä vaiheessa kuvataan lähtökohdat ja vaatimukset tulevalle järjestelmälle. Työn osana käytännössä tehty kokonaisuus muodostuu useista eri määrityksistä koostuvista osista. Työn toisessa vaiheessa käydään läpi korkealla tasolla sovelluksen vaatimat protokollat. Osana näihin protokolliin kuului erilaisten avainten jatarkisteiden laskenta sekä salausmenetelmien käyttö, jotka myös kuvataan tässä työssä. Viimeisessä kappaleessa analysoidaan työn tuloksia jakäydään läpi toteutukseen ja itse sovelluksen toimintaan liittyvät ongelmat. Suurin osa havaituista ongelmista liittyi tilanteisiin, joihin itse palvelinsovelluksen toteutuksella ei voitu vaikuttaa. Eniten ongelmia aiheuttivat asiakasohjelmiston sekä verkkokorttien ja niiden ajureiden toiminta ongelmatilanteissa. Asiakasohjelmistoa ei selkeästi ole suunniteltu käytettäväksi kuin muuttumattomien salasanojen kanssa, koska käyttäjän näkökulmasta käyttökokemus ei ollut optimaalinen. Ongelmista huolimatta työn tuloksena saatiin asiakkaan vaatimukset täyttävä järjestelmä. Myös tuotekehitysnäkökulmasta projektia voitaneen pitää onnistuneena, koska nyt tehty sovellus luo pohjan uusien tunnistustapojen ja menetelmien toteuttamiselle tuotteen jatkokehitystä ajatellen.

Computational Analysis and Optimization of Real Gas Flow In Small Centrifugal Compressors

Small centrifugal compressors are more and more widely used in many industrialsystems because of their higher efficiency and better off-design performance comparing to piston and scroll compressors as while as higher work coefficient perstage than in axial compressors. Higher efficiency is always the aim of the designer of compressors. In the present work, the influence of four partsof a small centrifugal compressor that compresses heavy molecular weight real gas has been investigated in order to achieve higher efficiency. Two parts concern the impeller: tip clearance and the circumferential position of the splitter blade. The other two parts concern the diffuser: the pinch shape and vane shape. Computational fluid dynamics is applied in this study. The Reynolds averaged Navier-Stokes flow solver Finflo is used. The quasi-steady approach is utilized. Chien's k-e turbulence model is used to model the turbulence. A new practical real gas model is presented in this study. The real gas model is easily generated, accuracy controllable and fairly fast. The numerical results and measurements show good agreement. The influence of tip clearance on the performance of a small compressor is obvious. The pressure ratio and efficiency are decreased as the size of tip clearance is increased, while the total enthalpy rise keeps almost constant. The decrement of the pressure ratio and efficiency is larger at higher mass flow rates and smaller at lower mass flow rates. The flow angles at the inlet and outlet of the impeller are increased as the size of tip clearance is increased. The results of the detailed flow field show that leakingflow is the main reason for the performance drop. The secondary flow region becomes larger as the size of tip clearance is increased and the area of the main flow is compressed. The flow uniformity is then decreased. A detailed study shows that the leaking flow rate is higher near the exit of the impeller than that near the inlet of the impeller. Based on this phenomenon, a new partiallyshrouded impeller is used. The impeller is shrouded near the exit of the impeller. The results show that the flow field near the exit of the impeller is greatly changed by the partially shrouded impeller, and better performance is achievedthan with the unshrouded impeller. The loading distribution on the impeller blade and the flow fields in the impeller is changed by moving the splitter of the impeller in circumferential direction. Moving the splitter slightly to the suction side of the long blade can improve the performance of the compressor. The total enthalpy rise is reduced if only the leading edge of the splitter ismoved to the suction side of the long blade. The performance of the compressor is decreased if the blade is bended from the radius direction at the leading edge of the splitter. The total pressure rise and the enthalpy rise of thecompressor are increased if pinch is used at the diffuser inlet. Among the fivedifferent pinch shape configurations, at design and lower mass flow rates the efficiency of a straight line pinch is the highest, while at higher mass flow rate, the efficiency of a concave pinch is the highest. The sharp corner of the pinch is the main reason for the decrease of efficiency and should be avoided. The variation of the flow angles entering the diffuser in spanwise direction is decreased if pinch is applied. A three-dimensional low solidity twisted vaned diffuser is designed to match the flow angles entering the diffuser. The numerical results show that the pressure recovery in the twisted diffuser is higher than in a conventional low solidity vaned diffuser, which also leads to higher efficiency of the twisted diffuser. Investigation of the detailed flow fields shows that the separation at lower mass flow rate in the twisted diffuser is later than in the conventional low solidity vaned diffuser, which leads to a possible wider flow range of the twisted diffuser.

Classification-Based compression of Multispectral Images

The purpose of this thesis is to present a new approach to the lossy compression of multispectral images. Proposed algorithm is based on combination of quantization and clustering. Clustering was investigated for compression of the spatial dimension and the vector quantization was applied for spectral dimension compression. Presenting algo¬rithms proposes to compress multispectral images in two stages. During the first stage we define the classes' etalons, another words to each uniform areas are located inside the image the number of class is given. And if there are the pixels are not yet assigned to some of the clusters then it doing during the second; pass and assign to the closest eta¬lons. Finally a compressed image is represented with a flat index image pointing to a codebook with etalons. The decompression stage is instant too. The proposed method described in this paper has been tested on different satellite multispectral images from different resources. The numerical results and illustrative examples of the method are represented too.

Characterisation of Hydrophobic Nonfibrous Material and Its Removal From Pulp Suspension

Paperin ja kartongin kierrätys lisääntyy taloudellisten intressien ja ympäristöhygieenisten tavoitteiden takia jatkuvasti. Lisääntyvän kierrätyksen myötä myös paperin ja kartongin epäpuhtauksien määrä kasvaa, mikä huonontaa kierrätysraaka-aineen laatua. Tämän työn tarkoituksena on antaa perustietoa eräästä kartongin päällystyksessä käytettävästä hydrofobisesta materiaalista, epäpuhtaan kartongin kierrätyksestä sekä ongelmista, joita epäpuhtaan kartongin kierrätyksestä syntyy. Kierrätyskuidun fraktiointi on yksinkertainen prosessi aallotuskartongin, testilainerin ja taivekartongin valmistuksessa. Kierrätysprosessin ensisijaisia tehtäviä ovat kuidutus ja epäpuhtauksien poisto sekä näiden epäpuhtauksien vaikutusten eliminointi, jotta kierrätysmassan laatuvaatimukset täyttyvät. Lisääntynyt epäpuhtauksien määrä raaka-aineessa asettaa vaatimuksia lajitteluprosessin kehittämiseksi. Nykyaikaisilla kierrätyslaitoksilla ei pystytä käsittelemään ylettömiä määriä epäpuhtauksia. Epäpuhtaudet aiheuttavat ongelmia ajettavuuteen ja heikentävät tuotteen laatua kierrätysprosessissa. Epäpuhtauksien poistoon on olemassa useita teknisiä ratkaisuja, mutta minkään niistä ei ole todettu täysin poistavan kaikkia ongelmia. Työn kokeellisessa osassa kartongin päällystykseen käytettävää hydrofobista materiaalia analysoitiin erilaisin menetelmin. Tutkittiin myös erilaisten olosuhteiden vaikutusta tämän materiaalin poistoon.

Bayesian Estimation of Noise

In mathematical modeling the estimation of the model parameters is one of the most common problems. The goal is to seek parameters that fit to the measurements as well as possible. There is always error in the measurements which implies uncertainty to the model estimates. In Bayesian statistics all the unknown quantities are presented as probability distributions. If there is knowledge about parameters beforehand, it can be formulated as a prior distribution. The Bays’ rule combines the prior and the measurements to posterior distribution. Mathematical models are typically nonlinear, to produce statistics for them requires efficient sampling algorithms. In this thesis both Metropolis-Hastings (MH), Adaptive Metropolis (AM) algorithms and Gibbs sampling are introduced. In the thesis different ways to present prior distributions are introduced. The main issue is in the measurement error estimation and how to obtain prior knowledge for variance or covariance. Variance and covariance sampling is combined with the algorithms above. The examples of the hyperprior models are applied to estimation of model parameters and error in an outlier case.