MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

A generalized 1D particle transport method for convection diffusion reaction model

This work is devoted to the development of numerical method to deal with convection diffusion dominated problem with reaction term, non - stiff chemical reaction and stiff chemical reaction. The technique is based on the unifying Eulerian - Lagrangian schemes (particle transport method) under the framework of operator splitting method. In the computational domain, the particle set is assigned to solve the convection reaction subproblem along the characteristic curves created by convective velocity. At each time step, convection, diffusion and reaction terms are solved separately by assuming that, each phenomenon occurs separately in a sequential fashion. Moreover, adaptivities and projection techniques are used to add particles in the regions of high gradients (steep fronts) and discontinuities and transfer a solution from particle set onto grid point respectively. The numerical results show that, the particle transport method has improved the solutions of CDR problems. Nevertheless, the method is time consumer when compared with other classical technique e.g., method of lines. Apart from this advantage, the particle transport method can be used to simulate problems that involve movingsteep/smooth fronts such as separation of two or more elements in the system.

Structured software development with the IPIDDDT method - A lean method for small agile organizations

A software development process is a predetermined sequence of steps to create a piece of software. A software development process is used, so that an implementing organization could gain significant benefits. The benefits for software development companies, that can be attributed to software process improvement efforts, are improved predictability in the development effort and improved quality software products. The implementation, maintenance, and management of a software process as well as the software process improvement efforts are expensive. Especially the implementation phase is expensive with a best case scenario of a slow return on investment. Software processes are rare in very small software development companies because of the cost of implementation and an improbable return on investment. This study presents a new method to enable benefits that are usually related to software process improvement to small companies with a low cost. The study presents reasons for the development of the method, a description of the method, and an implementation process for the method, as well as a theoretical case study of a method implementation. The study's focus is on describing the method. The theoretical use case is used to illustrate the theory of the method and the implementation process of the method. The study ends with a few conclusions on the method and on the method's implementation process. The main conclusion is that the method requires further study as well as implementation experiments to asses the value of the method.

Orthogonal function method in modelling paper web quality variation

This work is devoted to the analysis of signal variation of the Cross-Direction and Machine-Direction measurements from paper web. The data that we possess comes from the real paper machine. Goal of the work is to reconstruct the basis weight structure of the paper and to predict its behaviour to the future. The resulting synthetic data is needed for simulation of paper web. The main idea that we used for describing the basis weight variation in the Cross-Direction is Empirical Orthogonal Functions (EOF) algorithm, which is closely related to Principal Component Analysis (PCA) method. Signal forecasting in time is based on Time-Series analysis. Two principal mathematical procedures that we used in the work are Autoregressive-Moving Average (ARMA) modelling and Ornstein–Uhlenbeck (OU) process.

Chaotic Behaviour of Active Magnetic Bearing System by Time Series Analysis

Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

Long-term nutrient load management and lake restoration: Case of Säkylän Pyhäjärvi (SW Finland)

Eutrophication caused by anthropogenic nutrient pollution has become one of the most severe threats to water bodies. Nutrients enter water bodies from atmospheric precipitation, industrial and domestic wastewaters and surface runoff from agricultural and forest areas. As point pollution has been significantly reduced in developed countries in recent decades, agricultural non-point sources have been increasingly identified as the largest source of nutrient loading in water bodies. In this study, Lake Säkylän Pyhäjärvi and its catchment are studied as an example of a long-term, voluntary-based, co-operative model of lake and catchment management. Lake Pyhäjärvi is located in the centre of an intensive agricultural area in southwestern Finland. More than 20 professional fishermen operate in the lake area, and the lake is used as a drinking water source and for various recreational activities. Lake Pyhäjärvi is a good example of a large and shallow lake that suffers from eutrophication and is subject to measures to improve this undesired state under changing conditions. Climate change is one of the most important challenges faced by Lake Pyhäjärvi and other water bodies. The results show that climatic variation affects the amounts of runoff and nutrient loading and their timing during the year. The findings from the study area concerning warm winters and their influences on nutrient loading are in accordance with the IPCC scenarios of future climate change. In addition to nutrient reduction measures, the restoration of food chains (biomanipulation) is a key method in water quality management. The food-web structure in Lake Pyhäjärvi has, however, become disturbed due to mild winters, short ice cover and low fish catch. Ice cover that enables winter seining is extremely important to the water quality and ecosystem of Lake Pyhäjärvi, as the vendace stock is one of the key factors affecting the food web and the state of the lake. New methods for the reduction of nutrient loading and the treatment of runoff waters from agriculture, such as sand filters, were tested in field conditions. The results confirm that the filter technique is an applicable method for nutrient reduction, but further development is needed. The ability of sand filters to absorb nutrients can be improved with nutrient binding compounds, such as lime. Long-term hydrological, chemical and biological research and monitoring data on Lake Pyhäjärvi and its catchment provide a basis for water protection measures and improve our understanding of the complicated physical, chemical and biological interactions between the terrestrial and aquatic realms. In addition to measurements carried out in field conditions, Lake Pyhäjärvi and its catchment were studied using various modelling methods. In the calibration and validation of models, long-term and wide-ranging time series data proved to be valuable. Collaboration between researchers, modellers and local water managers further improves the reliability and usefulness of models. Lake Pyhäjärvi and its catchment can also be regarded as a good research laboratory from the point of view of the Baltic Sea. The main problem in both of them is eutrophication caused by excess nutrients, and nutrient loading has to be reduced – especially from agriculture. Mitigation measures are also similar in both cases.

Process modeling method for electric accessories manufacturing enterprise

The theoretical research of the study focused to business process management and business process modeling, the goal was to found a new business process modeling method for electrical accessories manufacturing enterprise. The focus was to find few options for business process modeling methods where company could have chosen the best one for its needs The study was carried out as a qualitative research with an action study and a case study as the most important ways collect data. In the empirical part of the study examples of company’s processes modeled with the new modeling method and process modeling process are presented. The new way of modeling processes improves especially visual presentation of the processes and improves the understanding how employees should work in the organizational interfaces of the process and in the interfaces between different processes. The results of the study is a new unified way to model company’s processes, which makes it easier to understand and create the process models. This improved readability makes it possible to reduce the costs that were created from the unclear old process models.

The Pay-Off Method as a Tool for Evaluating the Risk and Profitability of Public Real Estate Investments

Real option valuation, in particular the fuzzy pay-off method, has proven to be useful in defining risk and visualizing imprecision of investments in various industry applications. This study examines whether the evaluation of risk and profitability for public real estate investments can be improved by using real option methodology. Firstly, the context of real option valuation in the real estate industry is examined. Further, an empirical case study is performed on 30 real estate investments of a Finnish government enterprise in order to determine whether the presently used investment analysis system can be complemented by the pay-off method. Despite challenges in the application of the pay-off method to the case company’s large investment base, real option valuation is found to create additional value and facilitate more robust risk analysis in public real estate applications.

Parameter identification in time series models

Time series analysis can be categorized into three different approaches: classical, Box-Jenkins, and State space. Classical approach makes a basement for the analysis and Box-Jenkins approach is an improvement of the classical approach and deals with stationary time series. State space approach allows time variant factors and covers up a broader area of time series analysis. This thesis focuses on parameter identifiablity of different parameter estimation methods such as LSQ, Yule-Walker, MLE which are used in the above time series analysis approaches. Also the Kalman filter method and smoothing techniques are integrated with the state space approach and MLE method to estimate parameters allowing them to change over time. Parameter estimation is carried out by repeating estimation and integrating with MCMC and inspect how well different estimation methods can identify the optimal model parameters. Identification is performed in probabilistic and general senses and compare the results in order to study and represent identifiability more informative way.

Monolithic zirconium dioxide as a full contour restorative material: With special emphasis on the optical and mechanical properties

Full contour monolithic zirconia restorations have shown an increased popularity in the dental field over the recent years, owing to its mechanical and acceptable optical properties. However, many features of the restoration are yet to be researched and supported by clinical studies to confirm its place among the other indirect restorative materials This series of in vitro studies aimed at evaluating and comparing the optical and mechanical properties, light cure irradiance, and cement polymerization of multiple monolithic zirconia material at variable thicknesses, environments, treatments, and stabilization. Five different monolithic zirconia materials, four of which were partially stabilized and one fully stabilized were investigated. The optical properties in terms of surface gloss, translucency parameter, and contrast ratio were determined via a reflection spectrophotometer at variable thicknesses, coloring, sintering method, and after immersion in an acidic environment. Light cure irradiance and radiant exposure were quantified through the specimens at variable thicknesses and the degree of conversion of two dual-cure cements was determined via Fourier Transform Infrared spectroscopy. Bi-axial flexural strength was evaluated to compare between the partially and fully stabilized zirconia prepared using different coloring and sintering methods. Surface characterization was performed using a scanning electron microscope and a spinning disk confocal microscope. The surface gloss and translucency of the zirconia investigated were brand and thickness dependent with the translucency values decreasing as the thickness increased. Staining decreased the translucency of the zirconia and enhanced surface gloss as well as the flexural strength of the fully stabilized zirconia but had no effect on partially stabilized zirconia. Immersion in a corrosive acid increased surface gloss and decreased the translucency of some zirconia brands. Zirconia thickness was inversely related to the amount of light irradiance, radiant exposure, and degree of monomer conversion. Type of sintering furnace had no effect on the optical and mechanical properties of zirconia. Monolithic zirconia maybe classified as a semi-translucent material that is well influenced by the thickness, limiting its use in the esthetic zones. Conventional acid-base reaction, autopolymerizing and dual-cure cements are recommended for its cementation. Its desirable mechanical properties give it a high potential as a restoration for posterior teeth. However, close monitoring with controlled clinical studies must be determined before any definite clinical recommendations can be drawn.

Promoting Healthy Lifestyles with Personalized, APOE Genotype Based Health Information: The Effects on Psychological-, Health Behavioral and Clinical Factors

There is an increasing demand for individualized, genotype-based health advice. The general population-based dietary recommendations do not always motivate people to change their life-style, and partly following this, cardiovascular diseases (CVD) are a major cause of death in worldwide. Using genotype-based nutrition and health information (e.g. nutrigenetics) in health education is a relatively new approach, although genetic variation is known to cause individual differences in response to dietary factors. Response to changes in dietary fat quality varies, for example, among different APOE genotypes. Research in this field is challenging, because several non-modifiable (genetic, age, sex) and modifiable (e.g. lifestyle, dietary, physical activity) factors together and with interaction affect the risk of life-style related diseases (e.g. CVD). The other challenge is the psychological factors (e.g. anxiety, threat, stress, motivation, attitude), which also have an effect on health behavior. The genotype-based information is always a very sensitive topic, because it can also cause some negative consequences and feelings (e.g. depression, increased anxiety). The aim of this series of studies was firstly to study how individual, genotype-based health information affects an individual’s health form three aspects, and secondly whether this could be one method in the future to prevent lifestyle-related diseases, such as CVD. The first study concentrated on the psychological effects; the focus of the second study was on health behavior effects, and the third study concentrated on clinical effects. In the fourth study of this series, the focus was on all these three aspects and their associations with each other. The genetic risk and health information was the APOE gene and its effects on CVD. To study the effect of APOE genotype-based health information in prevention of CVD, a total of 151 volunteers attended the baseline assessments (T0), of which 122 healthy adults (aged 20 – 67 y) passed the inclusion criteria and started the one-year intervention. The participants (n = 122) were randomized into a control group (n = 61) and an intervention group (n = 61). There were 21 participants in the intervention Ɛ4+ group (including APOE genotypes 3/4 and 4/4) and 40 participants in the intervention Ɛ4- group (including APOE genotypes 2/3 and 3/3). The control group included 61 participants (including APOE genotypes 3/4, 4/4, 2/3, 3/3 and 2/2). The baseline (T0) and follow-up assessments (T1, T2, T3) included detailed measurements of psychological (threat and anxiety experience, stage of change), and behavioral (dietary fat quality, consumption of vegetables, - high fat/sugar foods and –alcohol, physical activity and health and taste attitudes) and clinical factors (total-, LDL- HDL cholesterol, triglycerides, blood pressure, blood glucose (0h and 2h), body mass index, waist circumference and body fat percentage). During the intervention six different communication sessions (lectures on healthy lifestyle and nutrigenomics, health messages by mail, and personal discussion with the doctor) were arranged. The intervention groups (Ɛ4+ and Ɛ4-) received their APOE genotype information and health message at the beginning of the intervention. The control group received their APOE genotype information after the intervention. For the analyses in this dissertation, the results for 106/107 participants were analyzed. In the intervention, there were 16 participants in the high-risk (Ɛ4+) group and 35 in the low-risk (Ɛ4-) group. The control group had 55 participants in studies III-IV and 56 participants in studies I-II. The intervention had both short-term (≤ 6 months) and long-term (12 months) effects on health behavior and clinical factors. The short-term effects were found in dietary fat quality and waist circumference. Dietary fat quality improved more in the Ɛ4+ group than the Ɛ4- and the control groups as the personal, genotype-based health information and waist circumference lowered more in the Ɛ4+ group compared with the control group. Both these changes differed significantly between the Ɛ4+ and control groups (p<0.05). A long-term effect was found in triglyceride values (p<0.05), which lowered more in Ɛ4+ compared with the control group during the intervention. Short-term effects were also found in the threat experience, which increased mostly in the Ɛ4+ group after the genetic feedback (p<0.05), but it decreased after 12 months, although remaining at a higher level compared to the baseline (T0). In addition, Study IV found that changes in the psychological factors (anxiety and threat experience, motivation), health and taste attitudes, and health behaviors (dietary, alcohol consumption, and physical activity) did not directly explain the changes in triglyceride values and waist circumference. However, change caused by a threat experience may have affected the change in triglycerides through total- and HDL cholesterol. In conclusion, this dissertation study has given some indications that individual, genotypebased health information could be one potential option in the future to prevent lifestyle-related diseases in public health care. The results of this study imply that personal genetic information, based on APOE, may have positive effects on dietary fat quality and some cardiovascular risk markers (e.g., improvement in triglyceride values and waist circumference). This study also suggests that psychological factors (e.g. anxiety and threat experience) may not be an obstacle for healthy people to use genotype-based health information to promote healthy lifestyles. However, even in the case of very personal health information, in order to achieve a permanent health behavior change, it is important to include attitudes and other psychological factors (e.g. motivation), as well as intensive repetition and a longer intervention duration. This research will serve as a basis for future studies and its information can be used to develop targeted interventions, including health information based on genotyping that would aim at preventing lifestyle diseases. People’s interest in personalized health advices has increased, while also the costs of genetic screening have decreased. Therefore, generally speaking, it can be assumed that genetic screening as a part of the prevention of lifestyle-related diseases may become more common in the future. In consequence, more research is required about how to make genetic screening a practical tool in public health care, and how to efficiently achieve long-term changes.