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.

Comparison of energy balances of steam explosion and torrefaction technologies

The present study introduce two pretreatment technologies which are torrefaction and steam explosion, and compare energy balance for both technologies to investigate and compare the use of these technologies to improve pelletization. In this research, torrefaction and steam explosion pretreatments were accomplished on the mixed small diameter wood (70%) with moisture content of 40 %, and logging residues (30%) with moisture content of 45 % at temperature 230 ̊C, and treatment duration 10 min. Competing methods were evaluated, and the results showed higher volumetric energy for steam explosion pellet than torrefied pellet.

Adaptive Dynamics of Resource Specialization

Ecological specialization in resource utilization has various facades ranging from nutritional resources via host use of parasites or phytophagous insects to local adaptation in different habitats. Therefore, the evolution of specialization affects the evolution of most other traits, which makes it one of the core issues in the theory of evolution. Hence, the evolution of specialization has gained enormous amounts of research interest, starting already from Darwin’s Origin of species in 1859. Vast majority of the theoretical studies has, however, focused on the mathematically most simple case with well-mixed populations and equilibrium dynamics. This thesis explores the possibilities to extend the evolutionary analysis of resource usage to spatially heterogeneous metapopulation models and to models with non-equilibrium dynamics. These extensions are enabled by the recent advances in the field of adaptive dynamics, which allows for a mechanistic derivation of the invasion-fitness function based on the ecological dynamics. In the evolutionary analyses, special focus is set to the case with two substitutable renewable resources. In this case, the most striking questions are, whether a generalist species is able to coexist with the two specialist species, and can such trimorphic coexistence be attained through natural selection starting from a monomorphic population. This is shown possible both due to spatial heterogeneity and due to non-equilibrium dynamics. In addition, it is shown that chaotic dynamics may sometimes inflict evolutionary suicide or cyclic evolutionary dynamics. Moreover, the relations between various ecological parameters and evolutionary dynamics are investigated. Especially, the relation between specialization and dispersal propensity turns out to be counter-intuitively non-monotonous. This observation served as inspiration to the analysis of joint evolution of dispersal and specialization, which may provide the most natural explanation to the observed coexistence of specialist and generalist species.

Review of water electrolysis technologies and design of renewable hydrogen production systems

An electric system based on renewable energy faces challenges concerning the storage and utilization of energy due to the intermittent and seasonal nature of renewable energy sources. Wind and solar photovoltaic power productions are variable and difficult to predict, and thus electricity storage will be needed in the case of basic power production. Hydrogen’s energetic potential lies in its ability and versatility to store chemical energy, to serve as an energy carrier and as feedstock for various industries. Hydrogen is also used e.g. in the production of biofuels. The amount of energy produced during hydrogen combustion is higher than any other fuel’s on a mass basis with a higher-heating-value of 39.4 kWh/kg. However, even though hydrogen is the most abundant element in the universe, on Earth most hydrogen exists in molecular forms such as water. Therefore, hydrogen must be produced and there are various methods to do so. Today, the majority hydrogen comes from fossil fuels, mainly from steam methane reforming, and only about 4 % of global hydrogen comes from water electrolysis. Combination of electrolytic production of hydrogen from water and supply of renewable energy is attracting more interest due to the sustainability and the increased flexibility of the resulting energy system. The preferred option for intermittent hydrogen storage is pressurization in tanks since at ambient conditions the volumetric energy density of hydrogen is low, and pressurized tanks are efficient and affordable when the cycling rate is high. Pressurized hydrogen enables energy storage in larger capacities compared to battery technologies and additionally the energy can be stored for longer periods of time, on a time scale of months. In this thesis, the thermodynamics and electrochemistry associated with water electrolysis are described. The main water electrolysis technologies are presented with state-of-the-art specifications. Finally, a Power-to-Hydrogen infrastructure design for Lappeenranta University of Technology is presented. Laboratory setup for water electrolysis is specified and factors affecting its commissioning in Finland are presented.

Lean Methods and Digital Technologies in Healtchare

The experiences of several healthcare organizations were considered to distinguish the most frequently used lean tools, the success and failure factors, and the obstacles that may appear while implementing lean. As a result, two approaches to “go lean” were defined, and analyzed from the prospective of the applicability to healthcare processes. Industrialization of healthcare was studied, and the most promising digital technology tools to improve healthcare process were highlighted. Finally, the analysis of healthcare challenges and feasible ways to address them was conducted and presented as the main result of this work. The possible ways of implementation of the findings and limitations were described in the conclusion.

Role of the cardiac nerve in the adaptive changes of heart rate in response to an aversive stimulus in Megalobulimus mogianensis

The effect of an aversive stimulus represented by contact with a hot plate on the heart rate of Megalobulimus mogianensis was evaluated with electrocardiogram recording in intact snails (N = 8). All stimulated animals showed an increase in heart rate, with mean values ranging from 35.6 ± 1.2 (basal heart rate) to 43.8 ± 0.9 bpm (post-stimulation heart rate). The cardioacceleration was followed by gradual recovery of the basal heart rate, with mean recovery times varying from 4.3 ± 0.3 to 5.8 ± 0.6 min. Repetition of the stimulus did not affect the magnitude of variation nor did it influence the basal heart rate recovery time. To investigate the role of the cardiac nerve in mediating the heart rate alterations induced by the aversive stimulus, denervated (N = 8) and sham-operated (N = 8) animals were also tested. Although the aversive stimulus caused the heart rate to increase significantly in both experimental groups, the mean increase in heart rate in denervated animals (4.4 ± 0.4 bpm) was 57% of the value obtained in sham-operated animals (7.7 ± 1.3 bpm), indicating that the cardiac nerve is responsible for 43% of the cardioacceleration induced by the aversive stimulus. The cardioacceleration observed in denervated snails may be due to an increase in venous return promoted by the intense muscular activity associated with the withdrawal response. Humoral factors may also be involved. A probable delaying inhibitory effect of the cardiac nerve on the recuperation of the basal heart rate is suggested.

Vascular adaptive responses to physical exercise and to stress are affected differently by nandrolone administration

Androgenic anabolic steroid, physical exercise and stress induce cardiovascular adaptations including increased endothelial function. The present study investigated the effects of these conditions alone and in combination on the vascular responses of male Wistar rats. Exercise was started at 8 weeks of life (60-min swimming sessions 5 days per week for 8 weeks, while carrying a 5% body-weight load). One group received nandrolone (5 mg/kg, twice per week for 8 weeks, im). Acute immobilization stress (2 h) was induced immediately before the experimental protocol. Curves for noradrenaline were obtained for thoracic aorta, with and without endothelium from sedentary and trained rats, submitted or not to stress, treated or not with nandrolone. None of the procedures altered the vascular reactivity to noradrenaline in denuded aorta. In intact aorta, stress and exercise produced vascular adaptive responses characterized by endothelium-dependent hyporeactivity to noradrenaline. These conditions in combination did not potentiate the vascular adaptive response. Exercise-induced vascular adaptive response was abolished by nandrolone. In contrast, the aortal reactivity to noradrenaline of sedentary rats and the vascular adaptive response to stress of sedentary and trained rats were not affected by nandrolone. Maximum response for 7-10 rats/group (g): sedentary 3.8 ± 0.2 vs trained 3.0 ± 0.2*; sedentary/stress 2.7 ± 0.2 vs trained/stress 3.1 ± 0.1*; sedentary/nandrolone 3.6 ± 0.1 vs trained/nandrolone 3.8 ± 0.1; sedentary/stress/nandrolone 3.2 ± 0.1 vs trained/stress/nandrolone 2.5 ± 0.1*; *P < 0.05 compared to its respective control. Stress and physical exercise determine similar vascular adaptive response involving distinct mechanisms as indicated by the observation that only the physical exercise-induced adaptive response was abolished by nandrolone.

Searching to combine technologies for safer food attainment

Campylobacteriosis is an infection frequently acquired through the consumption of animal origin products. Chicken can be considered the main responsible cause in the transmission chain of this disease. Ionizing radiation was used to verify the reduction of the microbiological load of Campylobacter jejuni present in chicken liver, which, in natura, can present contamination in up to 100% of the cases. The doses of irradiation used were: 0.20 kGy, 0.27 kGy, 0.30 kGy and 0.35 kGy. The samples of chicken liver were acquired in aviaries, local supermarkets and large chain supermarkets. The samples were analyzed for Campylobacter at FIOCRUZ. Irradiation was performed at COPPE/UFRJ, using a Gamma Cell Irradiator with a 60Co gamma source. Only the frozen sample acquired at the local supermarket did not contain the bacterium. Campylobacter sp. was present in all other samples, even when using procedures and technologies that aimed at the impediment of the presence of this bacterium in food and, consequently, at the protection of human health. On the whole, the results were satisfactory; nevertheless, it is known that the bacterial growth conditions required by this bacterium are uncommon when compared to other enteropathogenic bacteria.

Postharvest technologies for mangosteen (Garcinia mangostana L.) conservation

The application of technologies to extend the postharvest life of mangosteen fruit was studied and compared to storage at 25 °C/70-75%R.H (25 °C control treatment). The fruits were packed in expanded polystyrene (EPS) trays (5 fruits/tray). Five treatments were carried out at 13 °C/ 90-95% RH: application of carnauba wax coating, lecithin + CMC (carboxymethyl cellulose) coating, 50 µm LDPE (low density polyethylene) film coating, 13 µm PVC (Polyvinyl chloride), and non-coated sample (13 °C control treatment). Physicochemical analyses were performed twice a week. A statistical design was completely randomized with 8 repetitions for each treatment plus the control treatment. The results were submitted to variance analysis, and the averages compared by the Tukey test at 5% probability. Among the quality parameters analyzed, more significant differences were observed for weight loss, texture, and peel moisture content. The results showed that the maximum storage period for mangosteen at 25 °C is two weeks; while storage at13 °C can guarantee the conservation of this fruit for 25 days. Therefore, the treatment at 13 °C/90-95% RH without the use of coatings and films was more effective and economical.

Power and Performance Management Strategies on NoC-Based Multicore Platforms, Using DVFS, Adaptive Algorithm and Task Parallelism

This work presents synopsis of efficient strategies used in power managements for achieving the most economical power and energy consumption in multicore systems, FPGA and NoC Platforms. In this work, a practical approach was taken, in an effort to validate the significance of the proposed Adaptive Power Management Algorithm (APMA), proposed for system developed, for this thesis project. This system comprise arithmetic and logic unit, up and down counters, adder, state machine and multiplexer. The essence of carrying this project firstly, is to develop a system that will be used for this power management project. Secondly, to perform area and power synopsis of the system on these various scalable technology platforms, UMC 90nm nanotechnology 1.2v, UMC 90nm nanotechnology 1.32v and UMC 0.18 μmNanotechnology 1.80v, in order to examine the difference in area and power consumption of the system on the platforms. Thirdly, to explore various strategies that can be used to reducing system’s power consumption and to propose an adaptive power management algorithm that can be used to reduce the power consumption of the system. The strategies introduced in this work comprise Dynamic Voltage Frequency Scaling (DVFS) and task parallelism. After the system development, it was run on FPGA board, basically NoC Platforms and on these various technology platforms UMC 90nm nanotechnology1.2v, UMC 90nm nanotechnology 1.32v and UMC180 nm nanotechnology 1.80v, the system synthesis was successfully accomplished, the simulated result analysis shows that the system meets all functional requirements, the power consumption and the area utilization were recorded and analyzed in chapter 7 of this work. This work extensively reviewed various strategies for managing power consumption which were quantitative research works by many researchers and companies, it's a mixture of study analysis and experimented lab works, it condensed and presents the whole basic concepts of power management strategy from quality technical papers.