Cu and Co exchanged ZSM-5 zeolites: activity towards no reduction and hydrocarbon oxidation

|Cu x|[Si yAl]-MFI and |Co x|[Si yAl]-MFI catalysts were prepared by ion exchange from |Na|[Si yAl]-MFI zeolites (y = 12, 25 and 45). The activity of the catalysts was evaluated in the reduction of NO to N2 in an oxidative atmosphere using propane or methane as reducing agents. The Cu catalysts were only active with propane and they presented higher activity than the Co-based catalysts, the latter being active with both hydrocarbons. H2-TPR and DRS-UV/Vis data allowed correlation between the activity towards NO reduction and the presence of cationic charge-compensating species in the zeolite. It was also verified that the hydrocarbons are preferentially oxidised by O2, a reaction that occurs simultaneously with their oxidation with NO.

Computational Techniques for Spectral Image Analysis

Multispectral images are becoming more common in the field of remote sensing, computer vision, and industrial applications. Due to the high accuracy of the multispectral information, it can be used as an important quality factor in the inspection of industrial products. Recently, the development on multispectral imaging systems and the computational analysis on the multispectral images have been the focus of a growing interest. In this thesis, three areas of multispectral image analysis are considered. First, a method for analyzing multispectral textured images was developed. The method is based on a spectral cooccurrence matrix, which contains information of the joint distribution of spectral classes in a spectral domain. Next, a procedure for estimating the illumination spectrum of the color images was developed. Proposed method can be used, for example, in color constancy, color correction, and in the content based search from color image databases. Finally, color filters for the optical pattern recognition were designed, and a prototype of a spectral vision system was constructed. The spectral vision system can be used to acquire a low dimensional component image set for the two dimensional spectral image reconstruction. The data obtained by the spectral vision system is small and therefore convenient for storing and transmitting a spectral image.

Markkinointiviestinnän välittämä imago business-to-business markkinoilla, mielikuvatavoitteena kestävä kehitys

Tässä pro gradu -tutkielmassa tarkasteltiin kansainvälisen metsäteollisuudessa toimivan yrityksen markkinointiviestintää ja sen välittämien imagoviestien siirtymistä business-to-business markkinoilla. Tutkittavat viestit liittyivät kartonkipakkausten kestävän kehityksen ja ympäristöystävällisyyden imagon rakentumiseen. Tutkimuksessa käytettiin kvalitatiivista tutkimusmenetelmää. Tutkimus pohjautui yrityksen teettämän aiemman asiakastutkimuksen aineistoon, jossa selvitettiin pakkauskartonkien mielikuvia kohderyhmässä. Lisäksi tutkittiin imagon viestintää markkinointiviestinnän näkökulmasta. Yrityksen online viestintää verrattiin asiakkaiden vastaavaan viestintään loppukäyttäjille ja selvitettiin siirtyivätkö kestävän kehityksen viestit loppukäyttäjille asti. Tuloksena saatiin osittain yhtenevä viestintä sekä yrityksen asiakkaiden että näiden loppukäyttäjille viestimien teemojen sisällöstä. Tutkimus osoitti, että tärkein viestinnällinen teema on pakkauksen kierrätettävyys. Toisena tärkeänä teemana ilmeni hiilijalanjäljen pienentämisestä viestivät seikat. Nousevana teemana voitiin havaita biohajoavia materiaaleja kohtaan osoitettu kiinnostus. Tutkimuksessa jaettiin vastaajat eri segmentteihin pakkauskartonkien käyttötarkoituksen mukaan ja verrattiin kestävän kehityksen tärkeyttä näiden segmenttien välillä. Segmenteittäin tarkasteltuna suuria eroja ei ollut havaittavissa.

Image Segmentation Using Information Bottleneck Method

In image processing, segmentation algorithms constitute one of the main focuses of research. In this paper, new image segmentation algorithms based on a hard version of the information bottleneck method are presented. The objective of this method is to extract a compact representation of a variable, considered the input, with minimal loss of mutual information with respect to another variable, considered the output. First, we introduce a split-and-merge algorithm based on the definition of an information channel between a set of regions (input) of the image and the intensity histogram bins (output). From this channel, the maximization of the mutual information gain is used to optimize the image partitioning. Then, the merging process of the regions obtained in the previous phase is carried out by minimizing the loss of mutual information. From the inversion of the above channel, we also present a new histogram clustering algorithm based on the minimization of the mutual information loss, where now the input variable represents the histogram bins and the output is given by the set of regions obtained from the above split-and-merge algorithm. Finally, we introduce two new clustering algorithms which show how the information bottleneck method can be applied to the registration channel obtained when two multimodal images are correctly aligned. Different experiments on 2-D and 3-D images show the behavior of the proposed algorithms

An octree isosurface codification based on discrete planes

Describes a method to code a decimated model of an isosurface on an octree representation while maintaining volume data if it is needed. The proposed technique is based on grouping the marching cubes (MC) patterns into five configurations according the topology and the number of planes of the surface that are contained in a cell. Moreover, the discrete number of planes on which the surface lays is fixed. Starting from a complete volume octree, with the isosurface codified at terminal nodes according to the new configuration, a bottom-up strategy is taken for merging cells. Such a strategy allows one to implicitly represent co-planar faces in the upper octree levels without introducing any error. At the end of this merging process, when it is required, a reconstruction strategy is applied to generate the surface contained in the octree intersected leaves. Some examples with medical data demonstrate that a reduction of up to 50% in the number of polygons can be achieved

Efficient image mosaicing for multi-robot visual underwater mapping

Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

Improving the oscillating grid method to characterize aquaculture biosolids using a laser beam and image analysis

Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.

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.

pH effect on the synthesis of magnetite nanoparticles by the chemical reduction-precipitation method

This work aimed at putting in evidence the influence of the pH on the chemical nature and properties of the synthesized magnetic nanocomposites. Saturation magnetization measurements evidenced a marked difference of the magnetic behavior of samples, depending on the final pH of the solution after reaction. Magnetite and maghemite in different proportions were the main magnetic iron oxides actually identified. Synthesis with final pH between 9.7-10.6 produced nearly pure magnetite with little or no other associated iron oxide. Under other synthetic conditions, goethite also appears in proportions that depended upon the pH of the synthesis medium.

Effect of dye structure and redox mediators on anaerobic azo and anthraquinone dye reduction

We investigated the biological decolourisation of dyes with different molecular structures. The kinetic constant values (k1) achieved with azo dye Reactive Red 120 were 7.6 and 10.1 times higher in the presence of RM (redox mediators) AQDS and riboflavin, respectively, than the assays lacking RM. The kinetic constant achieved with the azo dye Congo Red was 42 times higher than that obtained with the anthraquinone dye Reactive Blue 4. The effect of RM on dye reduction was more evident for azo dyes resistant to reductive processes, and ineffective for anthraquinone dyes because of the structural stability of the latter.

Electrochemical evidence of sulfinic acid derivative as an intermediate in the reduction of aromatic sulfonyl chloride in an aprotic medium

The electrochemical reduction of p-nitrobenzenesulfonyl chloride (NBSCl) in dimethylsulfoxide (DMSO) solution is used here as a model to investigate the role of sulfinic acid derivative in this compound's global reduction process. Cyclic voltammetric experiments reveal the production of sulfinic acid derivative, which is important in chemical reactions involving the original compound and other intermediates. This paper also discusses the probable mechanisms of the reduction.

Role of oxidation-reduction cycle of iron in direct leaching of zinc concentrate

Direct leaching is an alternative to conventional roast-leach-electrowin (RLE) zinc production method. The basic reaction of direct leach method is the oxidation of sphalerite concentrate in acidic liquid by ferric iron. The reaction mechanism and kinetics, mass transfer and current modifications of zinc concentrate direct leaching process are considered. Particular attention is paid to the oxidation-reduction cycle of iron and its role in direct leaching of zinc concentrate, since it can be one of the limiting factors of the leaching process under certain conditions. The oxidation-reduction cycle of iron was experimentally studied with goal of gaining new knowledge for developing the direct leaching of zinc concentrate. In order to obtain this aim, ferrous iron oxidation experiments were carried out. Affect of such parameters as temperature, pressure, sulfuric acid concentration, ferrous iron and copper concentrations was studied. Based on the experimental results, mathematical model of the ferrous iron oxidation rate was developed. According to results obtained during the study, the reaction rate orders for ferrous iron concentration, oxygen concentration and copper concentration are 0.777, 0.652 and 0.0951 respectively. Values predicted by model were in good concordance with the experimental results. The reliability of estimated parameters was evaluated by MCMC analysis which showed good parameters reliability.

Examining the Role of Rebranding in Perceived Image of a Product Line

The main objective for this study was to explore certain organization’s product line rebranding process and its impact on product line’s perceived image. The case company is a global paper, packaging and forest products company, business segment paper board. The audience explored is one of the company’s major customers, merchant in Germany. The research was performed as a descriptive case study with a purpose to provide longitudinal insight into the product line image and its eventual alteration as a result of the case company’s rebranding process. Mainly qualitative methods were used for conducting the research. The data for the empirical part was collected with a web-based survey at two different points of time; before the rebranded products entered the market and after they had been available approximately six months. The results of this study reveal that the case company has performed well in its attempt to improve product line’s brand image through rebranding. It was found that between the two brand image measurements the product brand image seems to have improved in all of the areas which according to theoretical framework of this study contribute to formation of brand image; brand associations, marketing communications and interpersonal relationships, not forgetting the original platform that initiated the change; technical quality modifications. In other words it may be concluded that as technical quality was brought to a new level, also assessments about the brand image improved respectively.

Adsorption isotherm studies of BOD, TSS and colour reduction from palm oil mill effluent (POME) using boiler fly ash

Palm oil is one of the two most important vegetable oils in the world's oil and fats market. The extraction and purification processes generate different kinds of waste generally known as palm oil mill effluent (POME). Earlier studies had indicated the possibility of using boiler fly ash to adsorb impurities and colour in POME treatment. The adsorption treatment of POME using boiler fly ash was further investigated in detail in this work with regards to the reduction of BOD, colour and TSS from palm oil mill effluent. The amount of BOD, colour and TSS adsorbed increased as the weight of the boiler fly ash used was increased. Also, the smaller particle size of 425µm adsorbed more than the 850µm size. Attempts were made to fit the experimental data with the Freundlich, Langmuir and Dubinin-Radushkevich isotherms. The R² values, which ranged from 0.8974-0.9898, 0.8848-0.9824 and 0.6235-0.9101 for Freundlich, Langmuir and Dubinin-Radushkevich isotherms respectively, showed that Freundlich isotherm gave a better fit followed by Langmuir and then Dubinin-Radushkevich isotherm. The sorption trend could be put as BOD > Colour > TSS. The apparent energy of adsorption was found to be 1.25, 0.58 and 0.97 (KJ/mol) for BOD, colour and TSS respectively, showing that sorption process occurs by physiosorption. Therefore, boiler fly ash is capable of reducing BOD, Colour and TSS from POME and hence could be used to develop a good adsorbent for POME treatment.

Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.