Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

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.

Applications and Benefits of Adaptive Pulsed GMAW

In ship and offshore terminal construction, welded cross sections are thick and the number of welds very high. Consequently, there are two aspects of great importance; cost and heat input. Reduction in the welding operation time decreases the costs of the work force and avoids excessive heat, preventing distortion and other weld defects. The need to increase productivity while using a single wire in the GMAW process has led to the use of a high current and voltage to improve the melting rate. Unfortunately, this also increases the heat input. Innovative GMAW processes, mostly implemented for sheet plate sections, have shown significant reduction in heat input (Q), low distortion and increase in welding speed. The aim of this study is to investigate adaptive pulsed GMAW processes and assess relevant applications in the high power range, considering possible benefits when welding thicker sections and high yield strength steel. The study experimentally tests the usability of adaptive welding processes and evaluates their effects on weld properties, penetration and shapes of the weld bead.The study first briefly reviews adaptive GMAW to evaluate different approaches and their applications and to identify benefits in adaptive pulsed. Experiments are then performed using Synergic Pulsed GMAW, WiseFusionTM and Synergic GMAW processes to weld a T-joint in a horizontal position (PB). The air gap between the parts ranges from 0 to 2.5 mm. The base materials are structural steel grade S355MC and filler material G3Si1. The experiment investigates heat input, mechanical properties and microstructure of the welded joint. Analysis of the literature reveals that different approaches have been suggested using advanced digital power sources with accurate waveform, current, voltage, and feedback control. In addition, studies have clearly indicated the efficiency of lower energy welding processes. Interest in the high power range is growing and a number of different approaches have been suggested. The welding experiments in this study reveal a significant reduction of heat input and a weld microstructure with the presence of acicular ferrite (AF) beneficial for resistance to crack propagation. The WiseFusion bead had higher dilution, due to the weld bead shape, and low defects. Adaptive pulse GMAW processes can be a favoured choice when welding structures with many welded joints. The total heat reduction mitigates residual stresses and the bead shape allows a higher amperage limit. The stability of the arc during the process is virtually spatter free and allows an increase in welding speed.

The genetics of behaviour and other adaptive traits in nine-spined sticklebacks (Pungitius pungitius)

One of the main goals in current evolutionary biology research is to identify genes behind adaptive phenotypic variations. The advances in genomic technologies have made it possible to identify genetic loci behind these variations, also concerning non-model species. This thesis investigates the genetics of the behaviour and other adaptive traits of the nine-spined stickleback (Pungitius pungitius) through the application of different genetic approaches. Fennoscandian nine-spined stickleback populations express large phenotypical differences especially in behaviour, life –history traits and morphology. However the underlying genetic bases for these phenotypical differences have not been studied in detail. The results of the project will lay the foundation for further genetics studies and provide valuable information for our understanding of the genetics of the adaptive divergence of the nine-spined stickleback. A candidate gene approach was used to develop microsatellite markers situating close to candidate genes for behaviour in the nine-spined stickleback. Altogether 13 markers were developed and these markers were used in the subsequent studies with the anonymous random markers and physiologically important gene markers which are already currently available for nine-spined sticklebacks. It was shown that heterozygosity correlated with behaviour in one of the marine nine-spined stickleback populations but with contrasting effects: correlations with behaviour were negative when using physiological gene markers and positive with random markers. No correlation was found between behavioural markers and behaviour. From the physiological gene markers, a strong correlation was found between osmoregulation-related gene markers and behaviour. These results indicate that both local (physiological) and general (random) effects are important in the shaping of behaviour and that heterozygosity– behaviour correlations are population dependent. In this thesis a second linkage map for nine-spined sticklebacks was constructed. Compared to the earlier nine-spined stickleback linkage map, genomic rearrangements were observed between autosomal (LG7) and sex-determing (LG12) linkage groups. This newly constructed map was used in QTL mapping studies in order to locate genomic regions associated with pelvic structures, behaviour and body size/growth. One major QTL was found for pelvic structures and Pitx1 gene was related to these traits as was predicted from three-spined stickleback studies, but this was in contrast to earlier nine-spined stickleback study. The QTL studies also revealed that behaviour and body size/growth were genetically more complex by having more QTL than pelvic traits. However, in many cases, pelvic structure, body size/growth and behaviour were linked to similar map locations indicating possible pleiotropic effects of genes locating in these QTL regions. Many of the gene related markers resided in the QTL area. In the future, studying these possible candidate genes in depth might reveal the underlying mechanism behind the measured traits.

An Hp-Adaptive Hierarchical Formulation for the Boundary Element Method Applied to Elasticity in Two Dimensions

This paper presents an HP-Adaptive Procedure with Hierarchical formulation for the Boundary Element Method in 2-D Elasticity problems. Firstly, H, P and HP formulations are defined. Then, the hierarchical concept, which allows a substantial reduction in the dimension of equation system, is introduced. The error estimator used is based on the residual computation over each node inside an element. Finally, the HP strategy is defined and applied to two examples.

Mathematics inspired by Darwin. Adaptive dynamics of dispersal and cooperation

In 1859, Charles Darwin published his theory of evolution by natural selection, the process occurring based on fitness benefits and fitness costs at the individual level. Traditionally, evolution has been investigated by biologists, but it has induced mathematical approaches, too. For example, adaptive dynamics has proven to be a very applicable framework to the purpose. Its core concept is the invasion fitness, the sign of which tells whether a mutant phenotype can invade the prevalent phenotype. In this thesis, four real-world applications on evolutionary questions are provided. Inspiration for the first two studies arose from a cold-adapted species, American pika. First, it is studied how the global climate change may affect the evolution of dispersal and viability of pika metapopulations. Based on the results gained here, it is shown that the evolution of dispersal can result in extinction and indeed, evolution of dispersalshould be incorporated into the viability analysis of species living in fragmented habitats. The second study is focused on the evolution of densitydependent dispersal in metapopulations with small habitat patches. It resulted a very surprising unintuitive evolutionary phenomenon, how a non-monotone density-dependent dispersal may evolve. Cooperation is surprisingly common in many levels of life, despite of its obvious vulnerability to selfish cheating. This motivated two applications. First, it is shown that density-dependent cooperative investment can evolve to have a qualitatively different, monotone or non-monotone, form depending on modelling details. The last study investigates the evolution of investing into two public-goods resources. The results suggest one general path by which labour division can arise via evolutionary branching. In addition to applications, two novel methodological derivations of fitness measures in structured metapopulations are given.

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.

Flexible multibody dynamics and intelligent control of a hydraulically driven hybrid redundant robot machine

The assembly and maintenance of the International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. The VV is made of stainless steel, which has poor machinability and tends to work harden very rapidly, and all the machining operations need to be carried out from inside of the ITER VV. A general industrial robot cannot be used due to its poor stiffness in the heavy duty machining process, and this will cause many problems, such as poor surface quality, tool damage, low accuracy. Therefore, one of the most suitable options should be a light weight mobile robot which is able to move around inside of the VV and perform different machining tasks by replacing different cutting tools. Reducing the mass of the robot manipulators offers many advantages: reduced material costs, reduced power consumption, the possibility of using smaller actuators, and a higher payload-to-robot weight ratio. Offsetting these advantages, the lighter weight robot is more flexible, which makes it more difficult to control. To achieve good machining surface quality, the tracking of the end effector must be accurate, and an accurate model for a more flexible robot must be constructed. This thesis studies the dynamics and control of a 10 degree-of-freedom (DOF) redundant hybrid robot (4-DOF serial mechanism and 6-DOF 6-UPS hexapod parallel mechanisms) hydraulically driven with flexible rods under the influence of machining forces. Firstly, the flexibility of the bodies is described using the floating frame of reference method (FFRF). A finite element model (FEM) provided the Craig-Bampton (CB) modes needed for the FFRF. A dynamic model of the system of six closed loop mechanisms was assembled using the constrained Lagrange equations and the Lagrange multiplier method. Subsequently, the reaction forces between the parallel and serial parts were used to study the dynamics of the serial robot. A PID control based on position predictions was implemented independently to control the hydraulic cylinders of the robot. Secondly, in machining, to achieve greater end effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. This thesis investigates the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two schemes of intelligent control for a hydraulically driven parallel mechanism based on the dynamic model: (1) a fuzzy-PID self-tuning controller composed of the conventional PID control and with fuzzy logic, and (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self-tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel mechanism based on rod length predictions. The serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should be controlled to hold the hexa-element. Thirdly, a finite element approach of multibody systems using the Special Euclidean group SE(3) framework is presented for a parallel mechanism with flexible piston rods under the influence of machining forces. The flexibility of the bodies is described using the nonlinear interpolation method with an exponential map. The equations of motion take the form of a differential algebraic equation on a Lie group, which is solved using a Lie group time integration scheme. The method relies on the local description of motions, so that it provides a singularity-free formulation, and no parameterization of the nodal variables needs to be introduced. The flexible slider constraint is formulated using a Lie group and used for modeling a flexible rod sliding inside a cylinder. The dynamic model of the system of six closed loop mechanisms was assembled using Hamilton’s principle and the Lagrange multiplier method. A linearized hydraulic control system based on rod length predictions was implemented independently to control the hydraulic cylinders. Consequently, the results of the simulations demonstrating the behavior of the robot machine are presented for each case study. In conclusion, this thesis studies the dynamic analysis of a special hybrid (serialparallel) robot for the above-mentioned special task involving the ITER and investigates different control algorithms that can significantly improve machining performance. These analyses and results provide valuable insight into the design and control of the parallel robot with flexible rods.

Adaptive value of ryegrass biotypes with low-level resistance and susceptible to the herbicide fluazifop and competitive ability with the wheat culture

Ryegrass is the main weed in wheat crop, causing yield loss due to competition by environmental resources. The objectives of this study were to estimate the fitness cost of ryegrass biotypes with low-level resistance and susceptible to fluazifop and to investigate the relative competitive ability of these biotypes between themselves and against the crop. Thus, fitness cost and competitive ability experiments were conducted under greenhouse conditions. For the fitness cost experiments, the low-level resistant ryegrass biotypes and those susceptible to fluazifop were used. For competitive ability, the treatments were arranged in a replacement series, with five proportions of the wheat cultivar FUNDACEP Horizonte and the low-level resistant and susceptible ryegrass biotypes 100:0, 75:25, 50:50, 25:75 and 0:100. Competitive analysis was carried out through diagrams applied to the replacement experiments and use of relative competitiveness indices. Variables evaluated were plant height, in the fitness cost experiment, and leaf area and shoot dry biomass in both experiments. The ryegrass biotypes show overall similar fitness cost and competitive ability. The wheat cultivar FUNDACEP Horizonte is superior in competitive ability to the ryegrass biotype with low-level resistance and equivalent to the susceptible biotype.

Adaptive control of Hydraulic Drive

Adaptive control systems are one of the most significant research directions of modern control theory. It is well known that every mechanical appliance’s behavior noticeably depends on environmental changes, functioning-mode parameter changes and changes in technical characteristics of internal functional devices. An adaptive controller involved in control process allows reducing an influence of such changes. In spite of this such type of control methods is applied seldom due to specifics of a controller designing. The work presented in this paper shows the design process of the adaptive controller built by Lyapunov’s function method for the Hydraulic Drive. The calculation needed and the modeling were conducting with MATLAB® software including Simulink® and Symbolic Math Toolbox™ etc. In the work there was applied the Jacobi matrix linearization of the object’s mathematical model and derivation of the suitable reference models based on Newton’s characteristic polynomial. The intelligent adaptive to nonlinearities algorithm for solving Lyapunov’s equation was developed. Developed algorithm works properly but considered plant is not met requirement of functioning with. The results showed confirmation that adaptive systems application significantly increases possibilities in use devices and might be used for correction a system’s behavior dynamics.