Optimisation of data analysis method for a fluidized bed combustion test rig

Nowadays the used fuel variety in power boilers is widening and new boiler constructions and running models have to be developed. This research and development is done in small pilot plants where more faster analyse about the boiler mass and heat balance is needed to be able to find and do the right decisions already during the test run. The barrier on determining boiler balance during test runs is the long process of chemical analyses of collected input and outputmatter samples. The present work is concentrating on finding a way to determinethe boiler balance without chemical analyses and optimise the test rig to get the best possible accuracy for heat and mass balance of the boiler. The purpose of this work was to create an automatic boiler balance calculation method for 4 MW CFB/BFB pilot boiler of Kvaerner Pulping Oy located in Messukylä in Tampere. The calculation was created in the data management computer of pilot plants automation system. The calculation is made in Microsoft Excel environment, which gives a good base and functions for handling large databases and calculations without any delicate programming. The automation system in pilot plant was reconstructed und updated by Metso Automation Oy during year 2001 and the new system MetsoDNA has good data management properties, which is necessary for big calculations as boiler balance calculation. Two possible methods for calculating boiler balance during test run were found. Either the fuel flow is determined, which is usedto calculate the boiler's mass balance, or the unburned carbon loss is estimated and the mass balance of the boiler is calculated on the basis of boiler's heat balance. Both of the methods have their own weaknesses, so they were constructed parallel in the calculation and the decision of the used method was left to user. User also needs to define the used fuels and some solid mass flowsthat aren't measured automatically by the automation system. With sensitivity analysis was found that the most essential values for accurate boiler balance determination are flue gas oxygen content, the boiler's measured heat output and lower heating value of the fuel. The theoretical part of this work concentrates in the error management of these measurements and analyses and on measurement accuracy and boiler balance calculation in theory. The empirical part of this work concentrates on the creation of the balance calculation for the boiler in issue and on describing the work environment.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Data analysis tools and methods for DNA microarray and high-throughput sequencing data

The recent rapid development of biotechnological approaches has enabled the production of large whole genome level biological data sets. In order to handle thesedata sets, reliable and efficient automated tools and methods for data processingand result interpretation are required. Bioinformatics, as the field of studying andprocessing biological data, tries to answer this need by combining methods and approaches across computer science, statistics, mathematics and engineering to studyand process biological data. The need is also increasing for tools that can be used by the biological researchers themselves who may not have a strong statistical or computational background, which requires creating tools and pipelines with intuitive user interfaces, robust analysis workflows and strong emphasis on result reportingand visualization. Within this thesis, several data analysis tools and methods have been developed for analyzing high-throughput biological data sets. These approaches, coveringseveral aspects of high-throughput data analysis, are specifically aimed for gene expression and genotyping data although in principle they are suitable for analyzing other data types as well. Coherent handling of the data across the various data analysis steps is highly important in order to ensure robust and reliable results. Thus,robust data analysis workflows are also described, putting the developed tools andmethods into a wider context. The choice of the correct analysis method may also depend on the properties of the specific data setandthereforeguidelinesforchoosing an optimal method are given. The data analysis tools, methods and workflows developed within this thesis have been applied to several research studies, of which two representative examplesare included in the thesis. The first study focuses on spermatogenesis in murinetestis and the second one examines cell lineage specification in mouse embryonicstem cells.

Spurring innovation through idea contests : data analysis and process improvements

This research concerns the Urban Living Idea Contest conducted by Creator Space™ of BASF SE during its 150th anniversary in 2015. The main objectives of the thesis are to provide a comprehensive analysis of the Urban Living Idea Contest (ULIC) and propose a number of improvement suggestions for future years. More than 4,000 data points were collected and analyzed to investigate the functionality of different elements of the contest. Furthermore, a set of improvement suggestions were proposed to BASF SE. Novelty of this thesis lies in the data collection and the original analysis of the contest, which identified its critical elements, as well as the areas that could be improved. The author of this research was a member of the organizing team and involved in the decision making process from the beginning until the end of the ULIC.

Skill Development in Music Reading. The Eye-Movement Approach

This dissertation examined skill development in music reading by focusing on the visual processing of music notation in different music-reading tasks. Each of the three experiments of this dissertation addressed one of the three types of music reading: (i) sight-reading, i.e. reading and performing completely unknown music, (ii) rehearsed reading, during which the performer is already familiar with the music being played, and (iii) silent reading with no performance requirements. The use of the eye-tracking methodology allowed the recording of the readers’ eye movements from the time of music reading with extreme precision. Due to the lack of coherence in the smallish amount of prior studies on eye movements in music reading, the dissertation also had a heavy methodological emphasis. The present dissertation thus aimed to promote two major issues: (1) it investigated the eye-movement indicators of skill and skill development in sight-reading, rehearsed reading and silent reading, and (2) developed and tested suitable methods that can be used by future studies on the topic. Experiment I focused on the eye-movement behaviour of adults during their first steps of learning to read music notation. The longitudinal experiment spanned a nine-month long music-training period, during which 49 participants (university students taking part in a compulsory music course) sight-read and performed a series of simple melodies in three measurement sessions. Participants with no musical background were entitled as “novices”, whereas “amateurs” had had musical training prior to the experiment. The main issue of interest was the changes in the novices’ eye movements and performances across the measurements while the amateurs offered a point of reference for the assessment of the novices’ development. The experiment showed that the novices tended to sight-read in a more stepwise fashion than the amateurs, the latter group manifesting more back-and-forth eye movements. The novices’ skill development was reflected by the faster identification of note symbols involved in larger melodic intervals. Across the measurements, the novices also began to show sensitivity to the melodies’ metrical structure, which the amateurs demonstrated from the very beginning. The stimulus melodies consisted of quarter notes, making the effects of meter and larger melodic intervals distinguishable from effects caused by, say, different rhythmic patterns. Experiment II explored the eye movements of 40 experienced musicians (music education students and music performance students) during temporally controlled rehearsed reading. This cross-sectional experiment focused on the eye-movement effects of one-bar-long melodic alterations placed within a familiar melody. The synchronizing of the performance and eye-movement recordings enabled the investigation of the eye-hand span, i.e., the temporal gap between a performed note and the point of gaze. The eye-hand span was typically found to remain around one second. Music performance students demonstrated increased professing efficiency by their shorter average fixation durations as well as in the two examined eye-hand span measures: these participants used larger eye-hand spans more frequently and inspected more of the musical score during the performance of one metrical beat than students of music education. Although all participants produced performances almost indistinguishable in terms of their auditory characteristics, the altered bars indeed affected the reading of the score: the general effects of expertise in terms of the two eye- hand span measures, demonstrated by the music performance students, disappeared in the face of the melodic alterations. Experiment III was a longitudinal experiment designed to examine the differences between adult novice and amateur musicians’ silent reading of music notation, as well as the changes the 49 participants manifested during a nine-month long music course. From a methodological perspective, an opening to research on eye movements in music reading was the inclusion of a verbal protocol in the research design: after viewing the musical image, the readers were asked to describe what they had seen. A two-way categorization for verbal descriptions was developed in order to assess the quality of extracted musical information. More extensive musical background was related to shorter average fixation duration, more linear scanning of the musical image, and more sophisticated verbal descriptions of the music in question. No apparent effects of skill development were observed for the novice music readers alone, but all participants improved their verbal descriptions towards the last measurement. Apart from the background-related differences between groups of participants, combining verbal and eye-movement data in a cluster analysis identified three styles of silent reading. The finding demonstrated individual differences in how the freely defined silent-reading task was approached. This dissertation is among the first presentations of a series of experiments systematically addressing the visual processing of music notation in various types of music-reading tasks and focusing especially on the eye-movement indicators of developing music-reading skill. Overall, the experiments demonstrate that the music-reading processes are affected not only by “top-down” factors, such as musical background, but also by the “bottom-up” effects of specific features of music notation, such as pitch heights, metrical division, rhythmic patterns and unexpected melodic events. From a methodological perspective, the experiments emphasize the importance of systematic stimulus design, temporal control during performance tasks, and the development of complementary methods, for easing the interpretation of the eye-movement data. To conclude, this dissertation suggests that advances in comprehending the cognitive aspects of music reading, the nature of expertise in this musical task, and the development of educational tools can be attained through the systematic application of the eye-tracking methodology also in this specific domain.

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

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.

Kroppen som bärare av hälsa och lidande

The overall aim of this study is to seek new knowledge and deeper understanding of the body as a phenomenon from a caring science point of view. By means of a hermeneutic definition, the body is studied on a contextual as well as an ontological level in order to create a deeper understanding for human beings in relation to health and suffering. The study focuses of the body as a perspective of human beings. It is important for the knowledge growth in caring science to create a deeper understanding for the body, thus making it possible to understand patients in nursing care. The overall methodology is a hermeneutic definition which covers a contextual and an ontological concept definition. In the three empirical studies, Giorgi’s phenomenological method was used. The first empirical study comprises twelve students’ statements about experiences of their body in different situatons in life. The second study is composed of interviews with fifteen patients who had been afflicted by illness and been subjected to surgical treatment. In the third empirical study, ten patients who had been cared for in perioperative nursing care were interviewed. In the data analysis, the essential meaning of the body as a phenomenon is described, along with its variations and nuances. In the ontological determination of the body, an etymologic and semantic analysis is carried out, as well as a qualitative analysis of ideas, where the material is comprised of chosen texts on the body from different perspectives. In the concluding analysis the results were synthesized. The result of the first empirical study shows that a body is expressive and manifests movement in its striving for dignity. The body harbours language and inherent powers to cope with the unexpected, as well as feelings of anxiety, fear and powerlessness. The second study shows that the body is experienced as mysterious when it is afflicted by illness, but it is also found mysterious as an opponent to man and life. A battle is fought between the illness that breaks down the body, and human beings fighting to keep their unity whole. The body appears as a prison and a host for a threatening illness. The body bears a feeling of powerlessness when it is changed by illness and suffering. In a care and treatment context, the body is objectified by the patient and the caregiver. It is the illness that forces the patient to sacrifice parts of the body in order to once again become whole in the unity. The third study shows that the patient in a perioperative nursing context delivers him-/herself over to the hands of the caregiver, who defends and protects body and life. The patient experiences a sense of well-being when the caretaker receives him/her and protects the body from dangers. Suffering is alleviated when the patients are allowed to talk about what has happened in their body. The result of the semantic analysis shows that the body as a concept is described as bending around the human soul and spirit. Linguistically, dimensions like corporeal, shape, totality, unity and mortal clay, are described. Different ideas about the body described it as: a material animate part of man, active and demanding, something that perceives its surrounding world and as a subjective body of senses, thoughts and language. Ideas about the body also describe it as a biological and physiological, living organism, submitted to the laws of nature, a passive apparatus and a socially constructed gender. The results of the different studies were synthesized and reflected against a caring science perspective. The research has created a deeper understanding for the body as a material abode and as an entity of body, soul and spirit.

Optimization as a method of search engine marketing

This study is dedicated to search engine marketing (SEM). It aims for developing a business model of SEM firms and to provide explicit research of trustworthy practices of virtual marketing companies. Optimization is a general term that represents a variety of techniques and methods of the web pages promotion. The research addresses optimization as a business activity, and it explains its role for the online marketing. Additionally, it highlights issues of unethical techniques utilization by marketers which created relatively negative attitude to them on the Internet environment. Literature insight combines in the one place both technical and economical scientific findings in order to highlight technological and business attributes incorporated in SEM activities. Empirical data regarding search marketers was collected via e-mail questionnaires. 4 representatives of SEM companies were engaged in this study to accomplish the business model design. Additionally, the fifth respondent was a representative of the search engine portal, who provided insight on relations between search engines and marketers. Obtained information of the respondents was processed qualitatively. Movement of commercial organizations to the online market increases demand on promotional programs. SEM is the largest part of online marketing, and it is a prerogative of search engines portals. However, skilled users, or marketers, are able to implement long-term marketing programs by utilizing web page optimization techniques, key word consultancy or content optimization to increase web site visibility to search engines and, therefore, user’s attention to the customer pages. SEM firms are related to small knowledge-intensive businesses. On the basis of data analysis the business model was constructed. The SEM model includes generalized constructs, although they represent a wider amount of operational aspects. Constructing blocks of the model includes fundamental parts of SEM commercial activity: value creation, customer, infrastructure and financial segments. Also, approaches were provided on company’s differentiation and competitive advantages evaluation. It is assumed that search marketers should apply further attempts to differentiate own business out of the large number of similar service providing companies. Findings indicate that SEM companies are interested in the increasing their trustworthiness and the reputation building. Future of the search marketing is directly depending on search engines development.

Practical Data Curation and Management for Institutional Repositories

Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Analysis of testicular cell populations using flow cytometry

Studying testis is complex, because the tissue has a very heterogeneous cell composition and its structure changes dynamically during development. In reproductive field, the cell composition is traditionally studied by morphometric methods such as immunohistochemistry and immunofluorescence. These techniques provide accurate quantitative information about cell composition, cell-cell association and localization of the cells of interest. However, the sample preparation, processing, staining and data analysis are laborious and may take several working days. Flow cytometry protocols coupled with DNA stains have played an important role in providing quantitative information of testicular cells populations ex vivo and in vitro studies. Nevertheless, the addition of specific cells markers such as intracellular antibodies would allow the more specific identification of cells of crucial interest during spermatogenesis. For this study, adult rat Sprague-Dawley rats were used for optimization of the flow cytometry protocol. Specific steps within the protocol were optimized to obtain a singlecell suspension representative of the cell composition of the starting material. Fixation and permeabilization procedure were optimized to be compatible with DNA stains and fluorescent intracellular antibodies. Optimization was achieved by quantitative analysis of specific parameters such as recovery of meiotic cells, amount of debris and comparison of the proportions of the various cell populations with already published data. As a result, a new and fast flow cytometry method coupled with DNA stain and intracellular antigen detection was developed. This new technique is suitable for analysis of population behavior and specific cells during postnatal testis development and spermatogenesis in rodents. This rapid protocol recapitulated the known vimentin and γH2AX protein expression patterns during rodent testis ontogenesis. Moreover, the assay was applicable for phenotype characterization of SCRbKO and E2F1KO mouse models.

Software for Transport Accessibility Analysis: The Case of Moscow

In this thesis the process of building a software for transport accessibility analysis is described. The goal was to create a software which is easy to distribute and simple to use for the user without particular background in the field of the geographical data analysis. It was shown that existing tools do not suit for this particular task due to complex interface or significant rendering time. The goal was accomplished by applying modern approaches in the process of building web applications such as maps based on vector tiles, FLUX architecture design pattern and module bundling. It was discovered that vector tiles have considerable advantages over image-based tiles such as faster rendering and real-time styling.