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.

Learning Robot Environment through Simulation

Traditionally simulators have been used extensively in robotics to develop robotic systems without the need to build expensive hardware. However, simulators can be also be used as a “memory”for a robot. This allows the robot to try out actions in simulation before executing them for real. The key obstacle to this approach is an uncertainty of knowledge about the environment. The goal of the Master’s Thesis work was to develop a method, which allows updating the simulation model based on actual measurements to achieve a success of the planned task. OpenRAVE was chosen as an experimental simulation environment on planning,trial and update stages. Steepest Descent algorithm in conjunction with Golden Section search procedure form the principle part of optimization process. During experiments, the properties of the proposed method, such as sensitivity to different parameters, including gradient and error function, were examined. The limitations of the approach were established, based on analyzing the regions of convergence.

Distribution of tree species in a geomorphological and pedological gradient of submontane semidecidual seasonal forest in the vicinity of Rio Doce state park, Minas Gerais

The objective of this study was to test the hypothesis that the distribution of tree species in a fragment of submontane seasonal semideciduous forest, a buffer zone in the Parque Estadual do Rio Doce, Minas Gerais, is influenced by geomorphological and weather and soil variables, therefore it can represent a source of information for the restoration of degraded areas where environmental conditions are similar to those of the study area. A detailed soil survey was conducted in the area by sampling three soil profiles per slope segment, totaling 12 profiles. To sample the topsoil, four composite samples were collected from the 10-20 cm layers in each topographic range totaling 16 composite samples. In the low ramp and the lower and upper concave slopes, the texture ranged from clay to sandy-clay. The soil and topographic gradient was characterized by changes in the soil physical-chemical properties. The soil in the 10-20 cm sampled layer was sandier, slightly more fertile and less acid in the low ramp than the clayer soil, nutrient-poor and highly acid soil at the top. The soil conditions in the lower and upper slope of the sampled layers, in turn, were intermediate. The P levels were limiting in all soils. The species distribution along the topographic gradient was associated with variations in chemical fertility, acidity and soil texture. The distribution of Pera leandri, Astronium fraxinifolium, Pouteria torta, Machaerium brasiliense and Myrcia rufipes was correlated with high aluminum levels and to low soil fertility and these species may be indicated for restoration of degraded areas on hillsides and hilltops in regions where environmental conditions are similar. The distribution of Pouteria venosa, Apuleia leiocarpa and Acacia polyphylla was correlated with the less acid and more fertile soil in the environment of the low ramps, indicating the potential for the restoration of similar areas.

Efficiency of distinct data mining algorithms for classifying stress level in piglets from their vocalization

Among the challenges of pig farming in today's competitive market, there is factor of the product traceability that ensures, among many points, animal welfare. Vocalization is a valuable tool to identify situations of stress in pigs, and it can be used in welfare records for traceability. The objective of this work was to identify stress in piglets using vocalization, calling this stress on three levels: no stress, moderate stress, and acute stress. An experiment was conducted on a commercial farm in the municipality of Holambra, São Paulo State , where vocalizations of twenty piglets were recorded during the castration procedure, and separated into two groups: without anesthesia and local anesthesia with lidocaine base. For the recording of acoustic signals, a unidirectional microphone was connected to a digital recorder, in which signals were digitized at a frequency of 44,100 Hz. For evaluation of sound signals, Praat® software was used, and different data mining algorithms were applied using Weka® software. The selection of attributes improved model accuracy, and the best attribute selection was used by applying Wrapper method, while the best classification algorithms were the k-NN and Naive Bayes. According to the results, it was possible to classify the level of stress in pigs through their vocalization.

Heat flux measurement inside internal combustion engine with gradient heat flux sensor.

This master’s thesis is devoted to study different heat flux measurement techniques such as differential temperature sensors, semi-infinite surface temperature methods, calorimetric sensors and gradient heat flux sensors. The possibility to use Gradient Heat Flux Sensors (GHFS) to measure heat flux in the combustion chamber of compression ignited reciprocating internal combustion engines was considered in more detail. A. Mityakov conducted an experiment, where Gradient Heat Flux Sensor was placed in four stroke diesel engine Indenor XL4D to measure heat flux in the combustion chamber. The results which were obtained from the experiment were compared with model’s numerical output. This model (a one – dimensional single zone model) was implemented with help of MathCAD and the result of this implementation is graph of heat flux in combustion chamber in relation to the crank angle. The values of heat flux throughout the cycle obtained with aid of heat flux sensor and theoretically were sufficiently similar, but not identical. Such deviation is rather common for this type of experiment.

Heat Source Estimation with the Conjugate Gradient Method in Inverse Linear Diffusive Problems

In this work, we present the solution of a class of linear inverse heat conduction problems for the estimation of unknown heat source terms, with no prior information of the functional forms of timewise and spatial dependence of the source strength, using the conjugate gradient method with an adjoint problem. After describing the mathematical formulation of a general direct problem and the procedure for the solution of the inverse problem, we show applications to three transient heat transfer problems: a one-dimensional cylindrical problem; a two-dimensional cylindrical problem; and a one-dimensional problem with two plates.

Scalable algorithms for height field illumination

Global illumination algorithms are at the center of realistic image synthesis and account for non-trivial light transport and occlusion within scenes, such as indirect illumination, ambient occlusion, and environment lighting. Their computationally most difficult part is determining light source visibility at each visible scene point. Height fields, on the other hand, constitute an important special case of geometry and are mainly used to describe certain types of objects such as terrains and to map detailed geometry onto object surfaces. The geometry of an entire scene can also be approximated by treating the distance values of its camera projection as a screen-space height field. In order to shadow height fields from environment lights a horizon map is usually used to occlude incident light. We reduce the per-receiver time complexity of generating the horizon map on N N height fields from O(N) of the previous work to O(1) by using an algorithm that incrementally traverses the height field and reuses the information already gathered along the path of traversal. We also propose an accurate method to integrate the incident light within the limits given by the horizon map. Indirect illumination in height fields requires information about which other points are visible to each height field point. We present an algorithm to determine this intervisibility in a time complexity that matches the space complexity of the produced visibility information, which is in contrast to previous methods which scale in the height field size. As a result the amount of computation is reduced by two orders of magnitude in common use cases. Screen-space ambient obscurance methods approximate ambient obscurance from the depth bu er geometry and have been widely adopted by contemporary real-time applications. They work by sampling the screen-space geometry around each receiver point but have been previously limited to near- field effects because sampling a large radius quickly exceeds the render time budget. We present an algorithm that reduces the quadratic per-pixel complexity of previous methods to a linear complexity by line sweeping over the depth bu er and maintaining an internal representation of the processed geometry from which occluders can be efficiently queried. Another algorithm is presented to determine ambient obscurance from the entire depth bu er at each screen pixel. The algorithm scans the depth bu er in a quick pre-pass and locates important features in it, which are then used to evaluate the ambient obscurance integral accurately. We also propose an evaluation of the integral such that results within a few percent of the ray traced screen-space reference are obtained at real-time render times.

Similarity among periphyton algal communities in a lentic-lotic gradient of the upper Paraná river floodplain, Brazil

Floristic comparison of periphyton communities from three systems with different hydrodynamic regimes (lentic, semilotic, and lotic) was carried out during high and low water periods on the Upper Paraná River floodplain. For each period and system, glass slides were sampled every two days during 18-day periods, and Eichhornia azurea Kunth petioles were sampled three times. A total of 228 species was collected, representing 12 classes, mainly diatoms and desmids. The highest species-richness was found in communities from lentic system and during high water. Species richness in the lotic system was more stable over succession and hydrological periods. Algal taxonomic structure in river community was clearly separated from the other two systems, with 43% of similarity level. The hydrological period was next in importance, followed last by the substratum type, with communities associated at 65-78% similarity levels, depending on system and hydrological period. The type of system, but not the water levels,was the main factor that influenced community richness, followed by disturbances caused by flood pulses and the operation of reservoirs upstream. The periphyton on artificial and natural substrata presented high degree of similarity.

Phytosociology of the remaining xerophytic woodland associated to an environmental gradient at the banks of the São Francisco river - Petrolina, Pernambuco, Brazil

Floristic and phytosociological surveys were carried out for 12 months in the Embrapa-SPSB, Petrolina, Pernambuco, Brazil. A transect was laid on starting at the river bank extending for 790 m away from the river and divided into 140 10 × 10 m contiguous plots. In each plot, all standing plants, alive or dead, with stem diameter at soil level > 3 cm and total height > 1 m were sampled. Along this transect, an elevation range of 9.40 m was registered and five topographical environments were identified: riverside (MR), dike (D), floodable depression (DI), boundary terrace (TL) - all of them belonging to the fluvial terrace with Fluvic Neosol and Haplic Cambisol both silty textured eutrophic soils - and the inlander tableland (TS), with medium sandy-textured Red-Yellow Argisols. Fourty-eight species/morphospecies, distributed into 39 genera and 21 families, were identified. Four phytogeoenvironments (MR, D + TL, DI + TL, and TS) were registered based on environmental variations and floristic similarities among plots using cluster analyses. The MR environment showed the largest total density, total basal area, maximum and medium heights and maximum diameter. Moreover, it had 8.1% of plants with heights above 8 m against 0.6% for D + TL, 0.2% for DI + TL, and 0% for TS. The species with the largest importance value were Inga vera subsp. affinis (DC.) T.D. Pennington in MR, Mimosa bimucronata Kunth in D + TL and DI + TL and M. tenuiflora (Willd.) Poir. in TS.

Along-scan radiometric gradient in Landsat images: understanding the relation between floristic and remote sensing information in tropical forests

The along-scan radiometric gradient causes severe interpretation problems in Landsat images of tropical forests. It creates a decreasing trend in pixel values with the column number of the image. In practical applications it has been corrected assuming the trend to be linear within structurally similar forests. This has improved the relation between floristic and remote sensing information, but just in some cases. I use 3 Landsat images and 105 floristic inventories to test the assumption of linearity, and to examine how the gradient and linear corrections affect the relation between floristic and Landsat data. Results suggest the gradient to be linear in infrared bands. Also, the relation between floristic and Landsat data could be conditioned by the distribution of the sampling sites and the direction in which images are mosaicked. Additionally, there seems to be a conjunction between the radiometric gradient and a natural east-west vegetation gradient common in Western Amazonia. This conjunction might have enhanced artificially correlations between field and remotely-sensed information in previous studies. Linear corrections may remove such artificial enhancement, but along with true and relevant spectral information about floristic patterns, because they can´t separate the radiometric gradient from a natural one.

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.

High baseline serum total and LDL cholesterol levels are associated with MDR1 haplotypes in Brazilian hypercholesterolemic individuals of European descent

The MDR1 gene encodes the P-glycoprotein, an efflux transporter with broad substrate specificity. P-glycoprotein has raised great interest in pharmacogenetics because it transports a variety of structurally divergent drugs, including lipid-lowering drugs. The synonymous single-nucleotide polymorphism C3435T and the nonsynonymous single-nucleotide polymorphism G2677T/A in MDR1 have been indicated as potential determinants of variability in drug disposition and efficacy. In order to evaluate the effect of G2677T/A and C3435T MDR1 polymorphisms on serum levels of lipids before and after atorvastatin administration, 69 unrelated hypercholesterolemic individuals from São Paulo city, Brazil, were selected and treated with 10 mg atorvastatin orally once daily for four weeks. MDR1 polymorphisms were analyzed by PCR-RFLP. C3435T and G2677T polymorphisms were found to be linked. The allelic frequencies for C3435T polymorphism were 0.536 and 0.464 for the 3435C and 3435T alleles, respectively, while for G2677T/A polymorphism allele frequencies were 0.580 for the 2677G allele, 0.384 for the 2677T allele and 0.036 for the 2677A allele. There was no significant relation between atorvastatin response and MDR1 polymorphisms (repeated measures ANOVA; P > 0.05). However, haplotype analysis revealed an association between T/T carriers and higher basal serum total (TC) and LDL cholesterol levels (TC: 303 ± 56, LDL-C: 216 ± 57 mg/dl, respectively) compared with non-T/T carriers (TC: 278 ± 28, LDL-C: 189 ± 24 mg/dl; repeated measures ANOVA/Tukey test; P < 0.05). These data indicate that MDR1 polymorphism may have an important contribution to the control of basal serum cholesterol levels in Brazilian hypercholesterolemic individuals of European descent.