On state and parameter estimation in chaotic systems

State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

Creating an open-books implementation framework for a maintenance-related value-based life-cycle model

This study is a qualitative action research by its nature with elements of personal design in the form of a tangible model implementation framework construction. Utilized empirical data has been gathered via two questionnaires in relation to the arranged four workshop events with twelve individual participants. Five of them represented maintenance customers, three maintenance service providers and four equipment providers respectively. Further, there are two main research objectives in proportion to the two complementary focusing areas of this thesis. Firstly, the value-based life-cycle model, which first version has already been developed prior to this thesis, requires updating in order to increase its real-life applicability as an inter-firm decision-making tool in industrial maintenance. This first research objective is fulfilled by improving appearance, intelligibility and usability of the above-mentioned model. In addition, certain new features are also added. The workshop participants from the collaborating companies were reasonably pleased with made changes, although further attention will be required in future on the model’s intelligibility in particular as main results, charts and values were all reckoned as slightly hard to understand. Moreover, upgraded model’s appearance and added new features satisfied them the most. Secondly and more importantly, the premises of the model’s possible inter-firm implementation process need to be considered. This second research objective is delivered in two consecutive steps. At first, a bipartite open-books supported implementation framework is created and its different characteristics discussed in theory. Afterwards, the prerequisites and the pitfalls of increasing inter-organizational information transparency are studied in empirical context. One of the main findings was that the organizations are not yet prepared for network-wide information disclosure as dyadic collaboration was favored instead. However, they would be willing to share information bilaterally at least. Another major result was that the present state of companies’ cost accounting systems will definitely need implementation-wise enhancing in future since accurate and sufficiently detailed maintenance data is not available. Further, it will also be crucial to create supporting and mutually agreed network infrastructure. There are hardly any collaborative models, methods or tools currently in usage. Lastly, the essential questions about mutual trust and predominant purchasing strategies are cooperation-wise important. If inter-organizational activities are expanded, a more relational approach should be favored in this regard. Mutual trust was also recognized as a significant cooperation factor, but it is hard to measure in reality.

Comparison between dSPACE and NI systems based on real-time intelligent control of a teleoperated hydraulic servo system

The Laboratory of Intelligent Machine researches and develops energy-efficient power transmissions and automation for mobile construction machines and industrial processes. The laboratory's particular areas of expertise include mechatronic machine design using virtual technologies and simulators and demanding industrial robotics. The laboratory has collaborated extensively with industrial actors and it has participated in significant international research projects, particularly in the field of robotics. For years, dSPACE tools were the lonely hardware which was used in the lab to develop different control algorithms in real-time. dSPACE's hardware systems are in widespread use in the automotive industry and are also employed in drives, aerospace, and industrial automation. But new competitors are developing new sophisticated systems and their features convinced the laboratory to test new products. One of these competitors is National Instrument (NI). In order to get to know the specifications and capabilities of NI tools, an agreement was made to test a NI evolutionary system. This system is used to control a 1-D hydraulic slider. The objective of this research project is to develop a control scheme for the teleoperation of a hydraulically driven manipulator, and to implement a control algorithm between human and machine interaction, and machine and task environment interaction both on NI and dSPACE systems simultaneously and to compare the results.

Design and validation of stateful composite RESTful web services

A web service is a software system that provides a machine-processable interface to the other machines over the network using different Internet protocols. They are being increasingly used in the industry in order to automate different tasks and offer services to a wider audience. The REST architectural style aims at producing scalable and extensible web services using technologies that play well with the existing tools and infrastructure of the web. It provides a uniform set of operation that can be used to invoke a CRUD interface (create, retrieve, update and delete) of a web service. The stateless behavior of the service interface requires that every request to a resource is independent of the previous ones facilitating scalability. Automated systems, e.g., hotel reservation systems, provide advanced scenarios for stateful services that require a certain sequence of requests that must be followed in order to fulfill the service goals. Designing and developing such services for advanced scenarios with REST constraints require rigorous approaches that are capable of creating web services that can be trusted for their behavior. Systems that can be trusted for their behavior can be termed as dependable systems. This thesis presents an integrated design, analysis and validation approach that facilitates the service developer to create dependable and stateful REST web services. The main contribution of this thesis is that we provide a novel model-driven methodology to design behavioral REST web service interfaces and their compositions. The behavioral interfaces provide information on what methods can be invoked on a service and the pre- and post-conditions of these methods. The methodology uses Unified Modeling Language (UML), as the modeling language, which has a wide user base and has mature tools that are continuously evolving. We have used UML class diagram and UML state machine diagram with additional design constraints to provide resource and behavioral models, respectively, for designing REST web service interfaces. These service design models serve as a specification document and the information presented in them have manifold applications. The service design models also contain information about the time and domain requirements of the service that can help in requirement traceability which is an important part of our approach. Requirement traceability helps in capturing faults in the design models and other elements of software development environment by tracing back and forth the unfulfilled requirements of the service. The information about service actors is also included in the design models which is required for authenticating the service requests by authorized actors since not all types of users have access to all the resources. In addition, following our design approach, the service developer can ensure that the designed web service interfaces will be REST compliant. The second contribution of this thesis is consistency analysis of the behavioral REST interfaces. To overcome the inconsistency problem and design errors in our service models, we have used semantic technologies. The REST interfaces are represented in web ontology language, OWL2, that can be part of the semantic web. These interfaces are used with OWL 2 reasoners to check unsatisfiable concepts which result in implementations that fail. This work is fully automated thanks to the implemented translation tool and the existing OWL 2 reasoners. The third contribution of this thesis is the verification and validation of REST web services. We have used model checking techniques with UPPAAL model checker for this purpose. The timed automata of UML based service design models are generated with our transformation tool that are verified for their basic characteristics like deadlock freedom, liveness, reachability and safety. The implementation of a web service is tested using a black-box testing approach. Test cases are generated from the UPPAAL timed automata and using the online testing tool, UPPAAL TRON, the service implementation is validated at runtime against its specifications. Requirement traceability is also addressed in our validation approach with which we can see what service goals are met and trace back the unfulfilled service goals to detect the faults in the design models. A final contribution of the thesis is an implementation of behavioral REST interfaces and service monitors from the service design models. The partial code generation tool creates code skeletons of REST web services with method pre and post-conditions. The preconditions of methods constrain the user to invoke the stateful REST service under the right conditions and the post condition constraint the service developer to implement the right functionality. The details of the methods can be manually inserted by the developer as required. We do not target complete automation because we focus only on the interface aspects of the web service. The applicability of the approach is demonstrated with a pedagogical example of a hotel room booking service and a relatively complex worked example of holiday booking service taken from the industrial context. The former example presents a simple explanation of the approach and the later worked example shows how stateful and timed web services offering complex scenarios and involving other web services can be constructed using our approach.

Interoperability specifications and an automatic validation tool as a key factor for the support of a repository ecosystem

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

Toward a-state-of-the-art IR copyright management system: a needs assessment

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

A platform for assessing the current state of data repositories in Korea, Japan and China

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

AOD 2.0: A category based submission add-on for DSpace 4.0

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

Planktic Cyanobacteria from São Paulo State, Brazil: Chroococcales

The biodiversity studies of planktic cyanobacteria started in 1997 with intensive collecting in different water bodies of São Paulo State. Due to the problems brougth by eutrophication and cyanobacterial blooms, the samplings were concentrated in reservoirs of Alto Tietê region that supply drinking water to millions of people. The samples were collected with 20 µm plankton net or Van Dorn's bottle. Part of each one was preserved in formaldehyde or lugol solution and part was isolated. The culture strains were kept in BG11 and/or AMS1 media. Based on natural and culture material, 26 species were identified belonging to the families Chroococcaceae (2 taxa), Merismopediaceae (12), Microcystaceae (7) and Synechococcaceae (5). Among these species, six are potentialy toxic: Aphanocapsa incerta (Lemmerm.) Cronberg & Komárek, Microcystis aeruginosa (Kütz.) Kütz., M. botrys Teiling, M. panniformis Komárek et al., M. wesenbergii (Komárek) Komárek, and Radiocystis fernandoi Komárek & Komár.-Legn. Bacularia and Coelosphaeriopsis are genera reported for the first time in Brazil.

Genus Bourrellyodesmus (Desmidiaceae, Zygnemaphyceae) in the state of São Paulo, Brazil

Floristic survey of genus Bourrellyodesmus (Desmidiaceae, Zygnemaphyceae) was based on 149 sample units, 76 of which were already deposited at the Herbário Científico do Estado "Maria Eneyda P. Kauffmann Fidalgo" (SP) of the Instituto de Botânica, Secretaria do Meio Ambiente do Estado de São Paulo, and 73 of which were collected during 2000-2001. Two species of Bourrellyodesmus were identified: B. jolyanus (C. Bicudo & Azevedo) C. Bicudo & Compère e B. guarrerae sp. nov.

The genera Eriochrysis P. Beauv., Imperata Cirillo and Saccharum L. (Poaceae - Andropogoneae - Saccharinae) in the state of Rio Grande do Sul, Brazil

The subtribe Saccharinae belongs to the tribe Andropogoneae and comprises ca. 140 species in 13 genera, including Eriochrysis, Imperata and Saccharum. This work presents a survey of the species of these three genera in the state of Rio Grande do Sul. Intensive field collections were made in different physiographic regions of the state, as well as studies in several herbaria. The occurrence of three native species of each genus was confirmed in Rio Grande do Sul, in addition to sugar cane (Saccharum officinarum) that is cultivated in the region. Based on the material examined, Eriochrysis villosa is reported for the first time in the state of Paraná, Brazil. Identification keys for the species, descriptions, data on their geographical distributions, habitats and flowering and fruiting periods, as well as illustrations of important taxonomic characters are provided.

Impacts of the Belo Monte hydroelectric dam construction on pioneer vegetation formations along the Xingu River, Pará State, Brazil

There is an important pioneer vegetation formation along the Xingu River in the area where the Belo Monte hydroelectric dam is being constructed that is highly adapted to a seasonally fluctuating water levels. The aim of this study was to examine the habitat and flora of the pioneer formations in the Belo Monte area. The area was divided in three sections for study purposes (Reservoir, Low Flow, and Control) that were expected to experience different degrees of impact from the dam project. The calculations of habitat losses were based on satellite imagery classifications, and a total of 111 plots were established in the three areas for vegetation sampling. Habitat losses of the pioneer formations will total 89.7% when the project is fully functional. Forty-five of the 72 recorded species are restricted to single areas. Species richness and diversity were significantly lower in the control area. The completion of the Belo Monte reservoir will result in habitat reductions and will consequently reduce the richness and diversity of pioneer formations. Studies suggest monitoring the populations located in the reduced flow area to determine possible impacts resulting from changes in the regional hydrological cycle caused by the Xingu River dam.

Modeling temporal variations of Gracilaria Greville and Hypnea J.V. Lamouroux (Rhodophyta) assemblages on a midlittoral reef platform at Piedade Beach, Pernambuco State, Brazil

The diversity of algal banks composed of species out the genera Gracilaria Greville and Hypnea J.V. Lamouroux have been impacted by commercial exploitation and coastal eutrophication. The present study sought to construct dynamic models based on algal physiology to simulate seasonal variations in the biomasses of Gracilaria and Hypnea an intertidal reef at Piedade Beach in Jaboatão dos Guararapes, Pernambuco State, Brazil. Five 20 × 20 cm plots in a reef pool on a midlittoral reef platform were randomly sampled during April, June, August, October, and December/2009 and in January and March/2010. Water temperature, pH, irradiance, oxygen and salinity levels as well as the concentrations of ammonia, nitrate and phosphate were measured at the sampling site. Forcing functions were employed in the model to represent abiotic factors, and algal decay was simulated with a dispersal function. Algal growth was modeled using a logistic function and was found to be sensitive to temperature and salinity. Maximum absorption rates of ammonia and phosphate were higher in Hypnea than in Gracilaria, indicating that the former takes up nutrients more efficiently at higher concentrations. Gracilaria biomass peaked at approximately 120 g (dry weight m-2) in March/2010 and was significantly lower in August/2009; Hypnea biomasses, on the other hand, did not show any significant variations among the different months, indicating that resource competition may influence the productivity of these algae.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

A Phase Model for Building a Customer Value Based Sales Tool – Case Mining and Metals Industry

The objective of this research is to observe the state of customer value management in Outotec Oyj, determine the key development areas and develop a phase model with which to guide the development of a customer value based sales tool. The study was conducted with a constructive research approach with the focus of identifying a problem and developing a solution for the problem. As a basis for the study, the current literature involving customer value assessment and solution and customer value selling was studied. The data was collected by conducting 16 interviews in two rounds within the company and it was analyzed by coding openly. First, seven important development areas were identified, out of which the most critical were “Customer value mindset inside the company” and “Coordination of customer value management activities”. Utilizing these seven areas three functionality requirements, “Preparation”, “Outotec’s value creation and communication” and “Documentation” and three development requirements for a customer value sales tool were identified. The study concluded with the formulation of a phase model for building a customer value based sales tool. The model included five steps that were defined as 1) Enable customer value utilization, 2) Connect with the customer, 3) Create customer value, 4) Define tool to facilitate value selling and 5) Develop sales tool. Further practical activities were also recommended as a guide for executing the phase model.