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.

Evaluating multidimensional visualization techniques in data mining tasks

Visual data mining (VDM) tools employ information visualization techniques in order to represent large amounts of high-dimensional data graphically and to involve the user in exploring data at different levels of detail. The users are looking for outliers, patterns and models – in the form of clusters, classes, trends, and relationships – in different categories of data, i.e., financial, business information, etc. The focus of this thesis is the evaluation of multidimensional visualization techniques, especially from the business user’s perspective. We address three research problems. The first problem is the evaluation of projection-based visualizations with respect to their effectiveness in preserving the original distances between data points and the clustering structure of the data. In this respect, we propose the use of existing clustering validity measures. We illustrate their usefulness in evaluating five visualization techniques: Principal Components Analysis (PCA), Sammon’s Mapping, Self-Organizing Map (SOM), Radial Coordinate Visualization and Star Coordinates. The second problem is concerned with evaluating different visualization techniques as to their effectiveness in visual data mining of business data. For this purpose, we propose an inquiry evaluation technique and conduct the evaluation of nine visualization techniques. The visualizations under evaluation are Multiple Line Graphs, Permutation Matrix, Survey Plot, Scatter Plot Matrix, Parallel Coordinates, Treemap, PCA, Sammon’s Mapping and the SOM. The third problem is the evaluation of quality of use of VDM tools. We provide a conceptual framework for evaluating the quality of use of VDM tools and apply it to the evaluation of the SOM. In the evaluation, we use an inquiry technique for which we developed a questionnaire based on the proposed framework. The contributions of the thesis consist of three new evaluation techniques and the results obtained by applying these evaluation techniques. The thesis provides a systematic approach to evaluation of various visualization techniques. In this respect, first, we performed and described the evaluations in a systematic way, highlighting the evaluation activities, and their inputs and outputs. Secondly, we integrated the evaluation studies in the broad framework of usability evaluation. The results of the evaluations are intended to help developers and researchers of visualization systems to select appropriate visualization techniques in specific situations. The results of the evaluations also contribute to the understanding of the strengths and limitations of the visualization techniques evaluated and further to the improvement of these techniques.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Three mechanical weed control techniques in spring cereals

Selostus: Kolme viljojen mekaanista rikkakasvintorjuntamentelmää

Cell wall thickness and tangential and radial cell diameter of fertilized and irrigated Norway spruce

Abstract

Estimation of forest canopy cover : a comparison of field measurement techniques

Abstract

Studies on integrating kinematic design method with mechanical systems simulation techniques

Theultimate goal of any research in the mechanism/kinematic/design area may be called predictive design, ie the optimisation of mechanism proportions in the design stage without requiring extensive life and wear testing. This is an ambitious goal and can be realised through development and refinement of numerical (computational) technology in order to facilitate the design analysis and optimisation of complex mechanisms, mechanical components and systems. As a part of the systematic design methodology this thesis concentrates on kinematic synthesis (kinematic design and analysis) methods in the mechanism synthesis process. The main task of kinematic design is to find all possible solutions in the form of structural parameters to accomplish the desired requirements of motion. Main formulations of kinematic design can be broadly divided to exact synthesis and approximate synthesis formulations. The exact synthesis formulation is based in solving n linear or nonlinear equations in n variables and the solutions for the problem areget by adopting closed form classical or modern algebraic solution methods or using numerical solution methods based on the polynomial continuation or homotopy. The approximate synthesis formulations is based on minimising the approximation error by direct optimisation The main drawbacks of exact synthesis formulationare: (ia) limitations of number of design specifications and (iia) failure in handling design constraints- especially inequality constraints. The main drawbacks of approximate synthesis formulations are: (ib) it is difficult to choose a proper initial linkage and (iib) it is hard to find more than one solution. Recentformulations in solving the approximate synthesis problem adopts polynomial continuation providing several solutions, but it can not handle inequality const-raints. Based on the practical design needs the mixed exact-approximate position synthesis with two exact and an unlimited number of approximate positions has also been developed. The solutions space is presented as a ground pivot map but thepole between the exact positions cannot be selected as a ground pivot. In this thesis the exact synthesis problem of planar mechanism is solved by generating all possible solutions for the optimisation process ¿ including solutions in positive dimensional solution sets - within inequality constraints of structural parameters. Through the literature research it is first shown that the algebraic and numerical solution methods ¿ used in the research area of computational kinematics ¿ are capable of solving non-parametric algebraic systems of n equations inn variables and cannot handle the singularities associated with positive-dimensional solution sets. In this thesis the problem of positive-dimensional solutionsets is solved adopting the main principles from mathematical research area of algebraic geometry in solving parametric ( in the mathematical sense that all parameter values are considered ¿ including the degenerate cases ¿ for which the system is solvable ) algebraic systems of n equations and at least n+1 variables.Adopting the developed solution method in solving the dyadic equations in direct polynomial form in two- to three-precision-points it has been algebraically proved and numerically demonstrated that the map of the ground pivots is ambiguousand that the singularities associated with positive-dimensional solution sets can be solved. The positive-dimensional solution sets associated with the poles might contain physically meaningful solutions in the form of optimal defectfree mechanisms. Traditionally the mechanism optimisation of hydraulically driven boommechanisms is done at early state of the design process. This will result in optimal component design rather than optimal system level design. Modern mechanismoptimisation at system level demands integration of kinematic design methods with mechanical system simulation techniques. In this thesis a new kinematic design method for hydraulically driven boom mechanism is developed and integrated in mechanical system simulation techniques. The developed kinematic design method is based on the combinations of two-precision-point formulation and on optimisation ( with mathematical programming techniques or adopting optimisation methods based on probability and statistics ) of substructures using calculated criteria from the system level response of multidegree-of-freedom mechanisms. Eg. by adopting the mixed exact-approximate position synthesis in direct optimisation (using mathematical programming techniques) with two exact positions and an unlimitednumber of approximate positions the drawbacks of (ia)-(iib) has been cancelled.The design principles of the developed method are based on the design-tree -approach of the mechanical systems and the design method ¿ in principle ¿ is capable of capturing the interrelationship between kinematic and dynamic synthesis simultaneously when the developed kinematic design method is integrated with the mechanical system simulation techniques.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Design of axial-flux permanent-magnet low-speed machines and performance comparison between radial-flux and axial-flux machines

This thesis presents an alternative approach to the analytical design of surface-mounted axialflux permanent-magnet machines. Emphasis has been placed on the design of axial-flux machines with a one-rotor-two-stators configuration. The design model developed in this study incorporates facilities to include both the electromagnetic design and thermal design of the machine as well as to take into consideration the complexity of the permanent-magnet shapes, which is a typical requirement for the design of high-performance permanent-magnet motors. A prototype machine with rated 5 kW output power at 300 min-1 rotation speed has been designed and constructed for the purposesof ascertaining the results obtained from the analytical design model. A comparative study of low-speed axial-flux and low-speed radial-flux permanent-magnet machines is presented. The comparative study concentrates on 55 kW machines with rotation speeds 150 min-1, 300 min-1 and 600 min-1 and is based on calculated designs. A novel comparison method is introduced. The method takes into account the mechanical constraints of the machine and enables comparison of the designed machines, with respect to the volume, efficiency and cost aspects of each machine. It is shown that an axial-flux permanent-magnet machine with one-rotor-two-stators configuration has generally a weaker efficiency than a radial-flux permanent-magnet machine if for all designs the same electric loading, air-gap flux density and current density have been applied. On the other hand, axial-flux machines are usually smaller in volume, especially when compared to radial-flux machines for which the length ratio (axial length of stator stack vs. air-gap diameter)is below 0.5. The comparison results show also that radial-flux machines with alow number of pole pairs, p < 4, outperform the corresponding axial-flux machines.

Micronization of Pharmaceuticals and Food Ingredients using Supercritical Fluid Techniques

Micronization techniques based on supercritical fluids (SCFs) are promising for the production of particles with controlled size and distribution. The interest of the pharmaceutical field in the development of SCF techniques is increasing due to the need for clean processes, reduced consumption of energy, and to their several possible applications. The food field is still far from the application of SCF micronization techniques, but there is increasing interest mainly for the processing of products with high added value. The aim of this study is to use SCF micronization techniques for the production of particles of pharmaceuticals and food ingredients with controlled particle size and morphology, and to look at their production on semi-industrial scale. The results obtained are also used to understand the processes from the perspective of broader application within the pharmaceutical and food industries. Certain pharmaceuticals, a biopolymer and a food ingredient have been tested using supercritical antisolvent micronization (SAS) or supercritical assisted atomization (SAA) techniques. The reproducibility of the SAS technique has been studied using physically different apparatuses and on both laboratory and semi-industrial scale. Moreover, a comparison between semi-continuous and batch mode has been performed. The behaviour of the system during the SAS process has been observed using a windowed precipitation vessel. The micronized powders have been characterized by particle size and distribution, morphology and crystallinity. Several analyses have been performed to verify if the SCF process modified the structure of the compound or caused degradation or contamination of the product. The different powder morphologies obtained have been linked to the position of the process operating point with respect to the vapour-liquid equilibrium (VLE) of the systems studied, that is, mainly to the position of the mixture critical point (MCP) of the mixture. Spherical micro, submicro- and nanoparticles, expanded microparticles (balloons) and crystals were obtained by SAS. The obtained particles were amorphous or with different degrees of crystallinity and, in some cases, had different pseudo-polymorphic or polymorphic forms. A compound that could not be processed using SAS was micronized by SAA, and amorphous particles were obtained, stable in vials at room temperature. The SCF micronization techniques studied proved to be effective and versatile for the production of particles for several uses. Furthermore, the findings of this study and the acquired knowledge of the proposed processes can allow a more conscious application of SCF techniques to obtain products with the desired characteristics and enable the use of their principles for broader applications.

Selenium content of Finnish oats in 1997-1999 : effect of cultivars and cultivation techniques

Selostus: Suomalaisen kauran seleenipitoisuus vuosina 1997-1999

Kuumalanka-anemometri virtausmittauksissa

Tässä työssä selostetaan kuumalanka-anemometrin käyttö virtausmittauksissa. Kuumalanka-anemometrilla saadaan mitattua virtausnopeuden ja -suunnan lisäksi nopeusheilahteluja. Mittaustaajuus on tyypillisesti useita kymmeniä tuhansia mittauksia sekunnissa ja signaali on jatkuva. Nykytekniikalla pystytään helposti tallentamaan mittauslaitteistolta saatu viesti tietokoneelle ja muuntamaan se nopeudeksi. Hetkellisten nopeuksien avulla voidaan laskea turbulenttisen virtauksen ominaisuuksia, kuten turbulenssin intensiteetti ja spektri. Kuumalanka-anemometrissa lämmitetään sähköisesti ohutta lankaa, joka on mitattavassa virtauksessa. Langan sähköteho on suunnilleen yhtäsuuri kuin langasta konvektiolla siirtyvä lämpöteho. Tällöin on teoreettisesti mahdollista laskea virtausnopeus lämpötehosta lämmönsiirtokorrelaatioilla. Käytännössä laitteisto joudutaan kuitenkin erikseen kalibroimaan, mutta sähkötehon teoreettista riippuvuutta konvektiosta käytetään hyväksi. Kuumalangan lämmitettävä osuus on tyypillisesti halkaisijaltaan 5 µm ja pituudeltaan noin 1 mm. Sitä käytetään pääasiassa kaasuvirtausten mittaamiseen ja valtaosassa mittauksissa virtausaineena on ilma. Kuumalanka voi olla toteutettu kuumakalvotekniikalla, jossa halkaisijaltaan noin 50 - 70 µm paksuinen kuitu on päällystetty ohuella sähköä johtavalla kalvolla. Kuumakalvoanturin ei tarvitse olla muodoltaan sylinterimäinen, se voi olla mm. kartiomainen tai kiilamainen. Erikoispäällystetyllä kuumakalvoanturilla on mahdollista mitata myös nestevirtauksia. Mitattaessa kaasuvirtauksia kuumakalvon etuna on selvästi parempi kestävyys verrattuna kuumalankaan. Nimitystä kuumalanka-anemometri käytetään yleisesti molemmista anturityypeistä Tämän työn alussa käsitellään sylinterin yli tapahtuvaan virtaukseen liittyvää virtausmekaniikkaa ja lämmönsiirtoa. Anemometrin sähköinen osa, laitteisto ja sen kalibrointi käydään läpi. Langan suuntariippuvuuden laskentaan esitetään tarvittavat yhtälöt. Työssä esitellään kolme laitteistolla tehtyä perusmittausta: anturin kohtauskulman muuttaminen, pyörähdyssymmerisen suihkun nopeuskenttä ja tuulitunnelin rajakerros. Lisäksi esitellään yksi käytännöllinen ja vaativampi mittaus, jossa on mitattu nopeusprofiili radiaalikompressorin diffuusorin loppuosassa.

Mittausmenetelmien kehittaminen kuplakolonnille

Kuplakolonnireaktoreiden CFD-mallinnus on talla hetkella voimakkaasti kehittyva tutkimusalue. Kaksifaasivirtauksen luotettava simulointi ja mallintaminen on haastavaa kuplakolonnireaktorissa tapahtuvien ilmioiden monimutkaisuuden vuoksi. Reaktorin kayttaytymiseen vaikuttavat tekijat, kuten kolonnin hydrodynamiikka ja aineensiirto, tulee tuntea hyvin ennen mallien tekoa. Tassa tyossa on kokeellisesti tutkittu erilaisten mittausmenetelmien soveltuvuutta kuplakolonnin hydrodynamiikan tutkimiseen. Mittausmenetelmissa on keskitytty erityisesti CFD-mallien vaatimiin paikallisiin mittauksiin. Lisaksi tyossa on arvioitu mittausmenetelmien soveltuvuutta j a luotettavuutta CFD-mallien validointiin. Tyon kirjallisuusosassa on perehdytty kuplakolonnireaktorin hydrodynaamiseen kayttaytymiseen ja siihen vaikuttaviin tekijoihin. Naita ovat mm. reaktorityypit, kaasun dispergointi, virtaustyypit ja -alueet, kaasun tilavuusosuus, kaasukuplan koko ja kuplan nousunopeus. Mittauksia tehtiin kahdessa erikokoisessa kuplakolonnissa, joista pienemman halkaisija oli 0,078 m ja suuremman 0,182 m. Molempien kolonnien nestepinnan korkeus oli 4,62 m. Mittaukset tehtiin vesijohtovedella ja epaorgaanisella prosessiliuoksella. Hydrodynaamisista ominaisuuksista mitattiin kaasun tilavuusosuus, kaasukuplan koko seka kaasukuplan nousunopeus. Kaasun tilavuusosuusmittaukset tehtiin paaasiassa paine-eromittauksella ja joissakin tapauksissa pinnanmittausmenetelmalla. Kuplakoko- ja kuplan nousunopeusmittaukset tehtiin suumopeusvideokameralla ja laser Doppler-anemometrilla. Mittauksissa kaytettiin kahdeksaa erilaista kaasunjakolaitetta, joilla selvitettiin kaasunjakolaitteen ominaisuuksien vaikutusta kolonnin hydrodynamiikkaan. Tuloksista havaittiin, etta nestefaasin ominaisuuksilla oli suuri vaikutus kolonnin hydrodynaamiseen kayttaytymiseen. En kaasunjakolaitteilla vesijohtovedella mitatut hydrodynaamiset ominaisuudet eivat poikenneet paljoa toisistaan, kun taas prosessiliuoksella kaasunjakolaitteiden valille saatiin huomattavat erot. Mittausmenetelmista laser Doppler-anemometri ei kaytettavissa olleella optiikalla soveltunut kaasukuplien mittaamiseen. Kuplat olivat menetelmalle liian suuria. Suumopeusvideokamerallaja paine-eromittauksella paastiin hyviin tuloksiin.