Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

Prosessiautomaatio pinnankorkeusmittauksen koelaitteistoissa

Pinnankorkeuden tunteminen kiehutusvesireaktorin painesäiliössä on erittäin tärkeää sen turvallisuusvaikutusten takia. Pinnankorkeutta mitataan vesipatsaiden korkeutta havaitsevien paine-eromittausten avulla. Säteilyturvakeskuksen YVL-ohjeiden mukaan turvallisuuteen vaikuttavien mittausten täytyy noudattaa moninkertaistus- ja erilaisuusperiaatteita. Yleensä erilaisuusperiaatetta on toteutettu käyttämällä erityyppisiä paine-eromittareita, mutta erilaisella fysikaalisella toimintaperiaatteella oleva mittaus olisi parempi ja toteuttaisi paremmin erilaisuusperiaatetta. Uimurikytkin olisi tällainen fysikaalisesti eri periaatteeseen perustuva pinnankorkeuden mittauslaite. Ydinvoimalaan tarkoitettu teknologia tulee kelpoistaa riippumattoman tahon toimesta ennen käyttöönottoa. Kelpoistamiskokeita varten Lappeenrannan teknillisen yliopiston Ydinturvallisuuden tutkimusyksikköön rakennettiin vuosina 2011–2013 kaksi koelaitteistoa. Näillä koelaitteistoilla tutkittiin uimurikytkimien toimintaa ja ominaisuuksia erilaisissa kiehutusvesireaktorin käyttötilanteissa. Koelaitteistot tarvitsivat toimiakseen automaatiojärjestelmät, jotka suunniteltiin pääosin noudattamalla suunnittelun elinkaarimallia sekä automaatiosuunnittelun sisältökokonaisuuksia. Automaatiojärjestelmien suunnittelu aloitettiin määrittelemällä koejärjestelyjen asettamat vaatimukset, jonka jälkeen tehtiin teknologiavalinnat. Seuraavaksi suunniteltiin automaatiojärjestelmien logiikkaohjelmistot, joiden kuvaukseen tämä työ pääasiassa keskittyy. Logiikkaohjelmistot toteutettiin graafisella National Instruments LabView -ohjelmointikielellä. Logiikkaohjelmistojen tuli hoitaa tiedonkeruuta, käyttöautomaatiota, turvallisuustehtäviä sekä kokeisiin liittyviä erikoistehtäviä. Ohjelmistot saatiin esikokeiden aikana toimimaan halutusti, ja varsinaiset kokeet voitiin suorittaa ilman merkittäviä ongelmia.

Critical infrastructure protection against cyber threats

A postgraduate seminar series with a title Critical Infrastructure Protection against Cyber Threats held at the Department of Military Technology of the National Defence University in the fall of 2013 and 2014. This book is a collection of some of talks that were presented in the seminar. The papers address origin of critical infrastructure protection, wargaming cyberwar in critical infrastructure defence, cyber-target categorization, supervisory control and data acquisition systems vulnerabilities, electric power as critical infrastructure, improving situational awareness of critical infrastructure and trust based situation awareness in high security cloud environment. This set of papers tries to give some insight to current issues of the network-centric critical infrastructure protection. The seminar has always made a publication of the papers but this has been an internal publication of the Finnish Defence Forces and has not hindered publication of the papers in international conferences. Publication of these papers in peer reviewed conferences has indeed been always the goal of the seminar, since it teaches writing conference level papers. We still hope that an internal publication in the department series is useful to the Finnish Defence Forces by offering an easy access to these papers.

Mittausdatan havainnollistaminen MATLAB animaationa

The visualization of measurement data is important in the fields of engineering for research analysis and presentation purposes. A suitable visualization method for scientific visualization is needed when handling measurement data. Visualization methods and techniques will be presented throughout this work. They are the bases of scientific visualization from the abstract visualization process to the applied techniques suited for each situation. This work also proposes a visualization tool using the MATLAB® software. The tool was designed as general as possible to encompass the most needs in terms of measurement data visualization. It offers possibilities for both static and dynamic visualization of the data.

Matematiskt gestaltande i förskolan

The purpose of the thesis is to study how mathematics is experienced and used in preschool children’s activities and how preschool teachers frame their teaching of mathematical content. The studies include analyses of children’s actions in different activities from a mathematical perspective and preschool teachers’ intentions with and their teaching of mathematics. Preschool teachers’ understanding of the knowledge required in this area is also scrutinised. The theoretical points of departure are variation theory and sociocultural theory. With variation theory the focus is directed towards how mathematical content is dealt with in teaching situations where preschool teachers have chosen the learning objects. The sociocultural perspective has been chosen because children’s mathematical learning in play often takes place in interactions with others and in the encounter with culturally mediated concepts. The theoretical framework also includes didactical points of departure. The study is qualitative, with videography and phenomenography as metholological research approaches. In the study, video observations and interviews with preschool teachers have been used as data collection methods. The results show that in children’s play mathematics consists of volume, geometrical shapes, gravity, quantity and positioning. The situations also include size, patterns, proportions, counting and the creation of pairs. The preschool teachers’ intentions, planning and staging of their goal-oriented work are that all children should be given the opportunity to discern a mathematical content. This also includes making learning objects visible in here-and-now-situations. Variation and a clear focus on the mathematical content are important in this context. One of the study’s knowledge contributions concerns the didactics of mathematics in the preschool. This relates to the teaching of mathematics and includes the knowledge that preschool teachers regard as essential for their teaching. This includes theoretical and practical knowledge about children and children’s learning and didactical issues and strategies. The conclusion is that preschool teachers need to have a basic knowledge of mathematics and the didactics of mathematics.

An Update on Inter-Country Differences in Recovery and Utilization of Recycled Paper

The use of recovered paper as raw material in the paper and board industry has increased heavily during recent decades. At the same time, growing environmental awareness has raised the interest in recycling and a more sustainable way of living, at least in high-income countries. This paper combines these topics and explores how economic, demographic and environmental factors have affected the recovery and utilization of recycled paper between 1992 and 2010 in a sample of 70 countries. This study updates and extends the previous research on the topic using panel data and panel data estimation methods. The results confirm the roles of economic determinants but also indicate that concern for the environment impacts the recovery of recycled paper particularly in high-income countries. Moreover, the motives for recycling appear to depend on the income level of a country, which is something that future policies should consider.

Foreign Direct Investment, Clean Development Mechanism, and Environmental Management: A case of Sub-Saharan Africa

This doctoral dissertation explores the contribution of environmental management practices, the so-called clean development mechanism (CDM) projects, and foreign direct investment (FDI) in achieving sustainable development in developing countries, particularly in Sub- Saharan Africa. Because the climate change caused by greenhouse gas emissions is one of the most serious global environmental challenges, the main focus is on the causal links between carbon dioxide (CO2) emissions, energy consumption, and economic development in Sub-Saharan Africa. In addition, the dissertation investigates the factors that have affected the distribution of CDM projects in developing countries and the relationships between FDI and other macroeconomic variables of interest. The main contribution of the dissertation is empirical. One of the publications uses crosssectional data and Tobit and Poisson regressions. Three of the studies use time-series data and vector autoregressive and vector error correction models, while two publications use panel data and panel data estimation methods. One of the publications uses thus both timeseries and panel data. The concept of Granger causality is utilized in four of the publications. The results indicate that there are significant differences in the Granger causality relationships between CO2 emissions, energy consumption, economic growth, and FDI in different countries. It appears also that the causality relationships change over time. Furthermore, the results support the environmental Kuznets curve hypothesis but only for some of the countries. As to CDM activities, past emission levels, institutional quality, and the size of the host country appear to be among the significant determinants of the distribution of CDM projects. FDI and exports are also found to be significant determinants of economic growth.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

Finnish doctoral dissertations of nursing education research

Nursing education research has confirmed its place in the discipline of nursing and caring sciences being one of the most central research areas. However, extensive and systematic analysis of nursing education research has been lacking both nationally and internationally. The aim of this study was to describe the focus of nursing education research in Finnish doctoral dissertations in the field of nursing and caring sciences between the years 1990–2014. In addition, the characteristics (i.e. methods, study informants and reporting of validity, reliability, and research ethics) of the dissertations were described. Also, international reviews (N=39) focusing on nursing education research were analysed for a background literature. A literature review was carried out. Altogether 51 (=N) Finnish doctoral dissertations of nursing and caring sciences in the field of nursing education research were included in the final analysis. The data for this research was collected from the open publication lists of each university offering education in nursing and caring sciences in Finland. The dissertations were published in 1990–2014. The data were analysed by content analysis both deductively and inductively. This study consists of a scientific article manuscript and a background literature review. Nursing education research has focused both nationally and internationally on four main areas: structural factors in nursing education, nurse teacherhood, teaching activities, and learning and learning outcomes in nursing education. In Finland, the most central focus area was learning (84.3 %) whereas nurse teacherhood and structural factors in nursing education were studied the least. Students were the predominant study informant group while nurse staff including nurse mentors were next and nurse educators only the third. Surveys and interviews were the most common data collection methods. In the findings there were a lot of similarities with international reviews of nursing education research. Finnish nursing education research has been very student-centred yet studies focusing on the education of other nursing based professions or different levels of education are rare. Future research about nurse teacherhood, curricula and structural factors in nursing education is recommended. There is also a need for experimental designs. In addition, nursing education research should focus on the central phenomena of nursing education and working life. All in all, more nursing education research is needed. Nursing education dissertations cover only 12.3 % of all the dissertations of nursing and caring sciences in Finland.

Dynamic capabilities as enablers of value co-creation between an MBA school and its students

This study presents an understanding of how a U.S. based, international MBA school has been able to achieve competitive advantage within a relatively short period of time. A framework is built to comprehend how the dynamic capability and value co-creation theories are connected and to understand how the dynamic capabilities have enabled value co-creation to happen between the school and its students, leading to such competitive advantage for the school. The data collection method followed a qualitative single-case study with a process perspective. Seven semi-structured interviews were made in September and October of 2015; one current employee of the MBA school was interviewed, with the other six being graduates and/or former employees of the MBA school. In addition, the researcher has worked as a recruiter at the MBA school, enabling to build bridges and a coherent whole of the empirical findings. Data analysis was conducted by first identifying themes from interviews, after which a narrative was written and a causal network model was built. Thus, a combination of thematic analysis, narrative and grounded theory were used as data analysis methods. This study finds that value co-creation is enabled by the dynamic capabilities of the MBA school; also capabilities would not be dynamic if value co-creation did not take place. Thus, this study presents that even though the two theories represent different level analyses, they are intertwined and together they can help to explain competitive advantage. The MBA case school’s dynamic capabilities are identified to be the sales & marketing capabilities and international market creation capabilities, thus the study finds that the MBA school does not only co-create value with existing students (customers) in the school setting, but instead, most of the value co-creation happens between the school and the student cohorts (network) already in the recruiting phase. Therefore, as a theoretical implication, the network should be considered as part of the context. The main value created seem to lie in the MBA case school’s international setting & networks. MBA schools around the world can learn from this study; schools should try to find their own niche and specialize, based on their own values and capabilities. With a differentiating focus and a unique and practical content, the schools can and should be well-marketed and proactively sold in order to receive more student applications and enhance competitive advantage. Even though an MBA school can effectively be treated as a business, as the study shows, the main emphasis should still be on providing quality education. Good content with efficient marketing can be the winning combination for an MBA school.

Building IT architecture for developing nations using TOGAF

Developing nations vary in data usage techniques with respect to developed nations because of lack of standard information technology architecture. With the concept of globalization in the modern times, there is a necessity of information sharing between different developing nations for better advancements in socio-economic and science and technology fields. A robust IT architecture is needed and has to be built between different developing nations which eases information sharing and other data usage methods. A framework like TOGAF may work in this case as a normal IT framework may not fit to meet the requirements of an enterprise architecture. The intention of the thesis is to build an enterprise architecture between different developing nations using a framework TOGAF

Analysis of Automotive Cybersecurity - Attack surfaces and users’ privacy concerns

Modern automobiles are no longer just mechanical tools. The electronics and computing services they are shipping with are making them not less than a computer. They are massive kinetic devices with sophisticated computing power. Most of the modern vehicles are made with the added connectivity in mind which may be vulnerable to outside attack. Researchers have shown that it is possible to infiltrate into a vehicle’s internal system remotely and control the physical entities such as steering and brakes. It is quite possible to experience such attacks on a moving vehicle and unable to use the controls. These massive connected computers can be life threatening as they are related to everyday lifestyle. First part of this research studied the attack surfaces in the automotive cybersecurity domain. It also illustrated the attack methods and capabilities of the damages. Online survey has been deployed as data collection tool to learn about the consumers’ usage of such vulnerable automotive services. The second part of the research portrayed the consumers’ privacy in automotive world. It has been found that almost hundred percent of modern vehicles has the capabilities to send vehicle diagnostic data as well as user generated data to their manufacturers, and almost thirty five percent automotive companies are collecting them already. Internet privacy has been studies before in many related domain but no privacy scale were matched for automotive consumers. It created the research gap and motivation for this thesis. A study has been performed to use well established consumers privacy scale – IUIPC to match with the automotive consumers’ privacy situation. Hypotheses were developed based on the IUIPC model for internet consumers’ privacy and they were studied by the finding from the data collection methods. Based on the key findings of the research, all the hypotheses were accepted and hence it is found that automotive consumers’ privacy did follow the IUIPC model under certain conditions. It is also found that a majority of automotive consumers use the services and devices that are vulnerable and prone to cyber-attacks. It is also established that there is a market for automotive cybersecurity services and consumers are willing to pay certain fees to avail that.

Detection of Epilepsy with a Commercial EEG Headband

Epilepsy is a chronic brain disorder, characterized by reoccurring seizures. Automatic sei-zure detector, incorporated into a mobile closed-loop system, can improve the quality of life for the people with epilepsy. Commercial EEG headbands, such as Emotiv Epoc, have a potential to be used as the data acquisition devices for such a system. In order to estimate that potential, epileptic EEG signals from the commercial devices were emulated in this work based on the EEG data from a clinical dataset. The emulated characteristics include the referencing scheme, the set of electrodes used, the sampling rate, the sample resolution and the noise level. Performance of the existing algorithm for detection of epileptic seizures, developed in the context of clinical data, has been evaluated on the emulated commercial data. The results show, that after the transformation of the data towards the characteristics of Emotiv Epoc, the detection capabilities of the algorithm are mostly preserved. The ranges of acceptable changes in the signal parameters are also estimated.