Aluminium fouling and its impact on activated carbon based dioxin and furan removal in a wet scrubber at a co-incineration plant

Dioxins and furans, PCDD/Fs, are highly toxic substances formed in post combustion zones in furnaces. PCDD/F emissions are regulated by a waste incineration directive which relates also to co-incineration plants. Several observations of dioxin and furan enhancements in wet scrub- bers have been reported previously. This is thought to be due to the so-called "memory effect" which occurs when dioxins and furans absorb into plastic material in scrubbers and desorb when ambient circumstances alter significantly. At the co-incineration plant involved, dioxins and furans are controlled with a wet scrubber, the tower packing of which is made of plastic in which activated carbon particles are dispersed. This should avoid the memory effect and act as a dioxin and furan sink since dioxins and furans are absorbed irreversibly into the packing ma- terial. In this case, the tower packing in the scrubber is covered with a white layer that has been found to be mainly aluminium. The aim of this thesis was to determine the aluminium balance and the dioxin and furan behaviour in the scrubber and, thus, the impacts that the foul- ing has on dioxin and furan removal. The source of aluminium, reasons for fouling and further actions to minimize its impacts on dioxin and furan removal were also to be discovered. Measurements in various media around the scrubber and in fuels were made and a profile analysis of PCDD/F and mass balance calculations were carried out. PCDD/F content de- creased in the scrubber. The reduced PCDD/F was not discharged into scrubbing water. The removal mechanism seems to work in spite of the fouling, at least with low PCDD/F loads. Most of the PCDD/F in excess water originates from the Kymijoki River which is used as feeding water in the scrubber. Fouling turned out to consist mainly of aluminium hydroxides. Sludge combusted in the furnace was found to be a significant source of aluminium. Ways to minimize the fouling would be adjustment of pH to a proper lever, installation of a mechanical filter to catch the loose material from the scrubbing water and affecting the aluminium content of the sludge.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

A Dependency Parsing Approach to Biomedical Text Mining

Biomedical research is currently facing a new type of challenge: an excess of information, both in terms of raw data from experiments and in the number of scientific publications describing their results. Mirroring the focus on data mining techniques to address the issues of structured data, there has recently been great interest in the development and application of text mining techniques to make more effective use of the knowledge contained in biomedical scientific publications, accessible only in the form of natural human language. This thesis describes research done in the broader scope of projects aiming to develop methods, tools and techniques for text mining tasks in general and for the biomedical domain in particular. The work described here involves more specifically the goal of extracting information from statements concerning relations of biomedical entities, such as protein-protein interactions. The approach taken is one using full parsing—syntactic analysis of the entire structure of sentences—and machine learning, aiming to develop reliable methods that can further be generalized to apply also to other domains. The five papers at the core of this thesis describe research on a number of distinct but related topics in text mining. In the first of these studies, we assessed the applicability of two popular general English parsers to biomedical text mining and, finding their performance limited, identified several specific challenges to accurate parsing of domain text. In a follow-up study focusing on parsing issues related to specialized domain terminology, we evaluated three lexical adaptation methods. We found that the accurate resolution of unknown words can considerably improve parsing performance and introduced a domain-adapted parser that reduced the error rate of theoriginal by 10% while also roughly halving parsing time. To establish the relative merits of parsers that differ in the applied formalisms and the representation given to their syntactic analyses, we have also developed evaluation methodology, considering different approaches to establishing comparable dependency-based evaluation results. We introduced a methodology for creating highly accurate conversions between different parse representations, demonstrating the feasibility of unification of idiverse syntactic schemes under a shared, application-oriented representation. In addition to allowing formalism-neutral evaluation, we argue that such unification can also increase the value of parsers for domain text mining. As a further step in this direction, we analysed the characteristics of publicly available biomedical corpora annotated for protein-protein interactions and created tools for converting them into a shared form, thus contributing also to the unification of text mining resources. The introduced unified corpora allowed us to perform a task-oriented comparative evaluation of biomedical text mining corpora. This evaluation established clear limits on the comparability of results for text mining methods evaluated on different resources, prompting further efforts toward standardization. To support this and other research, we have also designed and annotated BioInfer, the first domain corpus of its size combining annotation of syntax and biomedical entities with a detailed annotation of their relationships. The corpus represents a major design and development effort of the research group, with manual annotation that identifies over 6000 entities, 2500 relationships and 28,000 syntactic dependencies in 1100 sentences. In addition to combining these key annotations for a single set of sentences, BioInfer was also the first domain resource to introduce a representation of entity relations that is supported by ontologies and able to capture complex, structured relationships. Part I of this thesis presents a summary of this research in the broader context of a text mining system, and Part II contains reprints of the five included publications.

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.

High pressure compression of filter cakes

The purpose of this thesis was to investigate the compression of filter cakes at high filtration pressures with five different test materials and to compare the energy consumption of high pressure compression with the energy consumption of thermal drying. The secondary target of this study was to investigate the particle deformation of test materials during filtration and compression. Literature part consists of basic theory of filtration and compression and of the basic parameters that influence the filtration process. There is also a brief description about all of the test materials including their properties and their industrial production and processing. Theoretical equations for calculating the energy consumptions of the filtrations at different conditions are also presented. At the beginning of the experiments at experimental part, the basic filtration tests were done with all the five test materials. Filtration tests were made at eight different pressures, from 6 bars up to 100 bars, by using piston press pressure filter. Filtration tests were then repeated by using a cylinder with smaller slurry volume than in the first series of filtration tests. Separate filtration tests were also done for investigating the deformation of solid particles during filtration and for finding the optimal curve for raising the filtration pressure. Energy consumption differences between high pressure filtration and ideal thermal drying process were done partly experimentally and partly by using theoretical calculation equations. By comparing these two water removal methods, the optimal ranges for their use were found considering their energy efficiency. The results of the measurements shows that the filtration rate increased and the moisture content of the filter cakes decreased as the filtration pressure was increased. Also the porosity of the filter cakes mainly decreased when the filtration pressure was increased. Particle deformation during the filtration was observed only with coal particles.

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

Corporate Social Responsibility in Global Mining Industry

Corporate Social Responsibility is company’s interest and actions towards its environment and the society that the company takes from its free will, to give back to the community and environment. Corporate Social Responsibility is current topic as companies are challenged to take responsibility for their action, due to the constant tightening environmental legislations and raising pressure for transparency from the public. The objective of this Master’s Thesis research is to study if Corporate Social Responsibility affects suppliers’ brand image and mining companies’ buying decisions within global mining industry. The research method is qualitative and the research is conducted with secondary and primary research methods. The research aims to find out what are the implications of the research for the case company Larox. The objective is to answer to the question; how should case company Larox start to develop Corporate Social Responsibility (CSR) program of its own, and how the case company could benefit from CSR as a competitive advantage and what actions could be taken in the company marketing. Conclusions are drawn based on both the secondary and primary research results. Both of the researches imply that CSR is well present in the global mining industry, and that suppliers’ CSR policy has positive effect on company image, which positively affects company’s brand, and furthermore brand has a positive effect on mining companies buying decision. It can be concluded that indirectly CSR has an effect on buying decisions, and case company should consider developing a CSR program of its own.

Mining in Developing Countries: A Case Study of Sustainability Challenges

Mining has severe impacts on its surrounding. Particularly in the developing countries it has degraded the environment and signigicantly altered the socio-economical dynamics of the hosts. Especially relocation disrupts people from their homes, livelihoods, cultures and social activities. Mining industry has failed to develop the local host and streghten its governance structures; instead it has further degraded the development of mineral rich third world countries, which are among the world poorest ones. Cash flows derived from mining companies have not benefitted the crass-root level that however, bears most of the detrimental impacts. Especially if the governance structure of the host is weak, the sudden wealth is likely to accelerate disparities, corruption and even fuel wars. Environmental degradation, miscommunication, mistrust and disputes over land use have created conflicts between the communities and a mining company in Obuasi, Ghana; a case study of this thesis. The disputes are deeply rooted and further fuelled by unrealistic expectations and broken promises. The relations with artisanal and illegal miners have been especially troublesome. Illegal activities, mainly encroachment of the land and assets of the mine, such as vandalising tailings pipes have resulted in profits losses, environmental degradation and security hazards. All challenges mentioned above have to be addressed locally with site-specific solutions. It is vital to increase two-way communication, initiate collaboration and build capacity of the stakeholders such as local communities, NGOs and governance authorities. The locals must be engaged to create livelihood opportunities that are designed with and for them. Capacity can also be strengthened through education and skills training, such as women’s literacy programs. In order to diminish the overdependence of locals to the mine, the activities have to be self -sufficient and able to survive without external financial and managerial inputs. Additionally adequate and fair compensation practises and dispute resolution methods that are understood and accepted by all parties have to be agreed on as early as possible.

Adsorptive removal of harmful organic compound from aqueous solutions

Adsorption is one of the most commonly used methods in water treatment processes. It is attractive due to it easy operation and the availability of a wide variety of commercial adsorbents. This doctoral thesis focuses on investigating and explaining the influence of external phase conditions (temperature, pH, ionic strength, acidity, presence of cosolutes) on adsorption phenomena. In order to cover a wide range of factors and phenomena, case studies were chosen from various fields where adsorption is applied. These include the adsorptive removal of surface active agents (used in cleaning chemicals, for example) from aqueous effluents, the removal of hormones (estradiol) from drinking water, and the adsorption of antibiotics onto silica. The latter can beused to predict the diffusion of antibiotics in the aquatic system if they are released into the environment. Also the adsorption of living cells on functionalized polymers to purify infected water streams was studied. In addition to these examples, the adsorptive separation of harmful compounds from internal water streams within a chemical process was investigated. The model system was removal of fermentation inhibitors from lignocelluloses hydrolyzates. The detoxification of the fermentation broth is an important step in the manufacture of bioethanol from wood, but has not been studied previously in connection with concentrated acid hydrolyzates. New knowledge on adsorption phenomena was generated for all of the applications investigated. In most cases, the results could be explained by combining classical theories for individual phenomena. As an example, it was demonstrated how liquid phase aggregation could explain abnormal-looking adsorption equilibrium data. In addition to the fundamental phenomena, also process performance was of interest. This aspect is often neglected in adsorption studies. It was demonstrated that adsorbents should not be selected for a target application based on their adsorption properties only, but regeneration of the spent adsorbent must be considered. It was found that using a suitable amount of organic co-solvent in the regeneration can significantly improve the productivity of the process.

Enhancement of water removal in the press section

The effectiveness of water removal on press section is very important for a paper and board machine’s functioning, efficiency and economy. Today, the most effective method for wet pressing is shoe press technology. Metso has carried out a number of studies concerning anew type of water removal method for a press section, which has also been patented. These studies include rough sketches and some test runs. These issues form the basis of this thesis. The objective of this work was to gather together information for a new and enhanced waterremoval method for a press section by studying the functioning of the device andcarrying out test runs. This method is referred to here as Hydronip. The main goal was tobuild a functional test site which fulfills all the necessary requirements and has all thenecessary information gathering devices. The design process was carried out by emphasizing the safety aspects. The goal was also to gather together information about the nip structure in running conditions, the seal function, and to carry out the nip tests with paper or board wads. This thesis consists of a theory part, the design and construction of the test site, and carrying out test runs through information gathering. The theory part consists of the principals of water removal from a press section, Hydronip construction, and the requirements for the test place. The safety aspects were taken into account especially in test runs, but also in the assembly stages. The design and construction of the test site includes the selection of equipment and surroundings that are needed for managing the test runs in the best possible way at certain premises. The test site included the equipment that was already on the premises. Some equipment could be used as it was but some equipment had to be manufactured or modified from existing equipment. A functional test site with information gathering devices was accomplished as a result of thethesis. Test runs demonstrated that the Hydronip concept is, at least on a small scale,functional. Short-term tests for seal functioning showed that the seal can be lubricatedsufficiently under different kinds of nip load situations. Wad tests demonstrated that the metal belt is durable against different sizes of external particles. The seal also endured wad tests even though the pressure impacts impaired the lubrication. MTS tests showing dry content increases, combined with a rough cost calculation and the basic function of the machine in test runs, show that with some further study Hydronip could be a promising new product for water removal from a paper or board machine’s press section.

EDTA- and DTPA-functionalized silica gel and chitosan adsorbents for the removal of heavy metals from aqueous solutions

Adsorbents functionalized with chelating agents are effective in removal of heavy metals from aqueous solutions. Important properties of such adsorbents are high binding affinity as well as regenerability. In this study, aminopolycarboxylic acid, EDTA and DTPA, were immobilized on the surface of silica gel, chitosan, and their hybrid materials to achieve chelating adsorbents for heavy metals such as Co(II), Ni(II), Cd(II), and Pb(II). New knowledge about the adsorption properties of EDTA- and DTPA-functionalizedadsorbents was obtained. Experimental work showed the effectiveness, regenerability, and stability of the studied adsorbents. Both advantages and disadvantages of the adsorbents were evaluated. For example, the EDTA-functionalized chitosan-silica hybrid materials combined the benefits of the silica gel and chitosan while at the same time diminishing their observed drawbacks. Modeling of adsorption kinetics and isotherms is an important step in design process. Therefore, several kinetic and isotherm models were introduced and applied in this work. Important aspects such as effect of error function, data range, initial guess values, and linearization were discussed and investigated. The selection of the most suitable model was conducted by comparing the experimental and simulated data as well as evaluating the correspondence between the theory behind the model and properties of the adsorbent. In addition, modeling of two-component data was conducted using various extended isotherms. Modeling results for both one- and twocomponent systems supported each other. Finally, application testing of EDTA- and DTPA-functionalized adsorbents was conducted. The most important result was the applicability of DTPA-functionalized silica gel and chitosan in the capturing of Co(II) from its aqueous EDTA-chelate. Moreover, these adsorbents were efficient in various solution matrices. In addition, separation of Ni(II) from Co(II) and Ni(II) and Pb(II) from Co(II) and Cd(II) was observed in two- and multimetal systems. Lastly, prior to their analysis, EDTA- and DTPA-functionalized silica gels were successfully used to preconcentrate metal ions from both pure and salty waters

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.