Soil penetration resistance analysis by multivariate and geostatistical methods

The penetration resistance (PR) is a soil attribute that allows identifies areas with restrictions due to compaction, which results in mechanical impedance for root growth and reduced crop yield. The aim of this study was to characterize the PR of an agricultural soil by geostatistical and multivariate analysis. Sampling was done randomly in 90 points up to 0.60 m depth. It was determined spatial distribution models of PR, and defined areas with mechanical impedance for roots growth. The PR showed a random distribution to 0.55 and 0.60 m depth. PR in other depths analyzed showed spatial dependence, with adjustments to exponential and spherical models. The cluster analysis that considered sampling points allowed establishing areas with compaction problem identified in the maps by kriging interpolation. The analysis with main components identified three soil layers, where the middle layer showed the highest values of PR.

Comparison measures of maps generated by geostatistical methods

This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

Evaluation of empirical methods to estimate reference evapotranspiration in Uberaba, State of Minas Gerais, Brazil

Evapotranspiration is the process of water loss of vegetated soil due to evaporation and transpiration, and it may be estimated by various empirical methods. This study had the objective to carry out the evaluation of the performance of the following methods: Blaney-Criddle, Jensen-Haise, Linacre, Solar Radiation, Hargreaves-Samani, Makkink, Thornthwaite, Camargo, Priestley-Taylor and Original Penman in the estimation of the potential evapotranspiration when compared to the Penman-Monteith standard method (FAO56) to the climatic conditions of Uberaba, state of Minas Gerais, Brazil. A set of 21 years monthly data (1990 to 2010) was used, working with the climatic elements: temperature, relative humidity, wind speed and insolation. The empirical methods to estimate reference evapotranspiration were compared with the standard method using linear regression, simple statistical analysis, Willmott agreement index (d) and performance index (c). The methods Makkink and Camargo showed the best performance, with "c" values ​​of 0.75 and 0.66, respectively. The Hargreaves-Samani method presented a better linear relation with the standard method, with a correlation coefficient (r) of 0.88.

Estimation of evaporation in the Banabuiú dam, in the state of Ceará, Brazil, by different combined methods, derived from the Penman equation

The state of Ceará, Brazil, has 75% of its area covered by Brazilian semiarid, with its peculiar features. In this state, the dams are constituted in water structure of strategic importance, ensuring, both in time and space, the development and supply of water to population. However, construction of reservoirs results in various impacts that should be carefully observed when deciding on their implementation. One of the impacts identified as negative is the increased evaporation, which constitutes a major component of water balance in reservoirs, especially in arid regions. Several methods for estimating evaporation have been proposed over time, many of them deriving from the Penman equation. This study evaluated six different methods for estimating evaporation in order to determine the most suitable for use in hydrological models for water balance in reservoirs in the state of Ceará. The tested methods were proposed by Penman, Kohler-Nordenson-Fox, Priestley-Taylor, deBruim-Keijman, Brutsaert-Stricker and deBruim. The methods presented good performance when tested for water balance during the dry season, and the Priestley-Taylor was the most appropriate, since the data from de simulated water balance with evaporation estimated by this method were the closest of the water balance data observed from measures of reservoir level and the elevation-volume curve provided by the Company of Management of Water Resources of the state of Ceará - COGERH.

Evaluation of protein extraction methods to obtain protein concentrate from cassava leaf

The cassava leaf, waste generated in the harvest of the roots, is characterized by high content of protein, vitamins and minerals; however, its use is limited due to the high fiber content and antinutritional substances, which can be removed by obtaining protein concentrates. In this context, the objective of this study was to evaluate protein extraction processes, aiming the use of cassava leaves (Manihot esculenta Crantz) as an alternative protein. Four methods were tested: 1) Coagulation of Proteins by Lowering the Temperature, 2) Extraction by Isoelectric Precipitation, 3) Solubilization of Proteins and 4) Fermentation of Filter Leaf Juice. To obtain the concentrates, the use of fresh or dried leaves and extraction in one or two steps were also evaluated. The solubilization of proteins (method 3) showed a higher extraction yield; however, with concentrate of low quality. The fermentation of the juice (method 4) produced concentrates with higher quality and lower costs and the isoelectric precipitation (method 2) promoted the obtention of concentrates in less time, both with good prospects for use. The use of two extraction steps was not advantageous to the process and there was no difference between the use of fresh or dried leaf, and the use of fresh leaves is presented as a good option for the simplicity of the method.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Estimation methods of reference evapotranspiration (ETo) for Uberlândia -MG

One approach to verify the adequacy of estimation methods of reference evapotranspiration is the comparison with the Penman-Monteith method, recommended by the United Nations of Food and Agriculture Organization - FAO, as the standard method for estimating ET0. This study aimed to compare methods for estimating ET0, Makkink (MK), Hargreaves (HG) and Solar Radiation (RS), with Penman-Monteith (PM). For this purpose, we used daily data of global solar radiation, air temperature, relative humidity and wind speed for the year 2010, obtained through the automatic meteorological station, with latitude 18° 91' 66" S, longitude 48° 25' 05" W and altitude of 869m, at the National Institute of Meteorology situated in the Campus of Federal University of Uberlandia - MG, Brazil. Analysis of results for the period were carried out in daily basis, using regression analysis and considering the linear model y = ax, where the dependent variable was the method of Penman-Monteith and the independent, the estimation of ET0 by evaluated methods. Methodology was used to check the influence of standard deviation of daily ET0 in comparison of methods. The evaluation indicated that methods of Solar Radiation and Penman-Monteith cannot be compared, yet the method of Hargreaves indicates the most efficient adjustment to estimate ETo.

Bankruptcy prediction using fuzzy methods

In this thesis, a classi cation problem in predicting credit worthiness of a customer is tackled. This is done by proposing a reliable classi cation procedure on a given data set. The aim of this thesis is to design a model that gives the best classi cation accuracy to e ectively predict bankruptcy. FRPCA techniques proposed by Yang and Wang have been preferred since they are tolerant to certain type of noise in the data. These include FRPCA1, FRPCA2 and FRPCA3 from which the best method is chosen. Two di erent approaches are used at the classi cation stage: Similarity classi er and FKNN classi er. Algorithms are tested with Australian credit card screening data set. Results obtained indicate a mean classi cation accuracy of 83.22% using FRPCA1 with similarity classi- er. The FKNN approach yields a mean classi cation accuracy of 85.93% when used with FRPCA2, making it a better method for the suitable choices of the number of nearest neighbors and fuzziness parameters. Details on the calibration of the fuzziness parameter and other parameters associated with the similarity classi er are discussed.

Techno-Economic Feasibility of Novel On-Line Condition Monitoring Methods in Low Voltage Distribution Networks

The focus in this thesis is to study both technical and economical possibilities of novel on-line condition monitoring techniques in underground low voltage distribution cable networks. This thesis consists of literature study about fault progression mechanisms in modern low voltage cables, laboratory measurements to determine the base and restrictions of novel on-line condition monitoring methods, and economic evaluation, based on fault statistics and information gathered from Finnish distribution system operators. This thesis is closely related to master’s thesis “Channel Estimation and On-line Diagnosis of LV Distribution Cabling”, which focuses more on the actual condition monitoring methods and signal theory behind them.

A Case Study of Agile Software Engineering Methods and Practices in the MeeGo Harmattan Open Source and Product Context

The aim of this master’s thesis is to study how Agile method (Scrum) and open source software are utilized to produce software for a flagship product in a complex production environment. The empirical case and the used artefacts are taken from the Nokia MeeGo N9 product program, and from the related software program, called as the Harmattan. The single research case is analysed by using a qualitative method. The Grounded Theory principles are utilized, first, to find out all the related concepts from artefacts. Second, these concepts are analysed, and finally categorized to a core category and six supported categories. The result is formulated as the operation of software practices conceivable in circumstances, where the accountable software development teams and related context accepts a open source software nature as a part of business vision and the whole organization supports the Agile methods.

Novel Regression Methods For Spectral Data

Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) are some of the mathematical pre- liminaries that are discussed prior to explaining PLS and PCR models. Both PLS and PCR are applied to real spectral data and their di erences and similarities are discussed in this thesis. The challenge lies in establishing the optimum number of components to be included in either of the models but this has been overcome by using various diagnostic tools suggested in this thesis. Correspondence analysis (CA) and PLS were applied to ecological data. The idea of CA was to correlate the macrophytes species and lakes. The di erences between PLS model for ecological data and PLS for spectral data are noted and explained in this thesis. i

Simulation methods in the modelling of bioaffinity assays

Computational model-based simulation methods were developed for the modelling of bioaffinity assays. Bioaffinity-based methods are widely used to quantify a biological substance in biological research, development and in routine clinical in vitro diagnostics. Bioaffinity assays are based on the high affinity and structural specificity between the binding biomolecules. The simulation methods developed are based on the mechanistic assay model, which relies on the chemical reaction kinetics and describes the forming of a bound component as a function of time from the initial binding interaction. The simulation methods were focused on studying the behaviour and the reliability of bioaffinity assay and the possibilities the modelling methods of binding reaction kinetics provide, such as predicting assay results even before the binding reaction has reached equilibrium. For example, a rapid quantitative result from a clinical bioaffinity assay sample can be very significant, e.g. even the smallest elevation of a heart muscle marker reveals a cardiac injury. The simulation methods were used to identify critical error factors in rapid bioaffinity assays. A new kinetic calibration method was developed to calibrate a measurement system by kinetic measurement data utilizing only one standard concentration. A nodebased method was developed to model multi-component binding reactions, which have been a challenge to traditional numerical methods. The node-method was also used to model protein adsorption as an example of nonspecific binding of biomolecules. These methods have been compared with the experimental data from practice and can be utilized in in vitro diagnostics, drug discovery and in medical imaging.

Active inverter output filtering methods

Frequency converters are widely used in the industry to enable better controllability and efficiency of variable speed AC motor drives. Despite these advantages, certain challenges concerning the inverter and motor interfacing have been present for decades. As insulated gate bipolar transistors entered the market, the inverter output voltage transition rate significantly increased compared with their predecessors. Inverters operate based on pulse width modulation of the output voltage, and the steep voltage edge fed by the inverter produces a motor terminal overvoltage. The overvoltage causes extra stress to the motor insulation, which may lead to a prematuremotor failure. The overvoltage is not generated by the inverter alone, but also by the sum effect of the motor cable length and the impedance mismatch between the cable and the motor. Many solutions have been shown to limit the overvoltage, and the mainstream products focus on passive filters. This doctoral thesis studies an alternative methodology for motor overvoltage reduction. The focus is on minimization of the passive filter dimensions, physical and electrical, or better yet, on operation without any filter. This is achieved by additional inverter control and modulation. The studied methods are implemented on different inverter topologies, varying in nominal voltage and current.For two-level inverters, the studied method is termed active du/dt. It consists of a small output LC filter, which is controlled by an independent modulator. The overvoltage is limited by a reduced voltage transition rate. For multilevel inverters, an overvoltage mitigation method operating without a passive filter, called edge modulation, is implemented. The method uses the capability of the inverter to produce two switching operations in the same direction to cancel the oscillating voltages of opposite phases. For parallel inverters, two methods are studied. They are both intended for two-level inverters, but the first uses individual motor cables from each inverter while the other topology applies output inductors. The overvoltage is reduced by interleaving the switching operations to produce a similar oscillation accumulation as with the edge modulation. The implementation of these methods is discussed in detail, and the necessary modifications to the control system of the inverter are presented. Each method is experimentally verified by operating industrial frequency converters with the modified control. All the methods are found feasible, and they provide sufficient overvoltage protection. The limitations and challenges brought about by the methods are discussed.

Application of capillary electrophoretic methods for determining carbohydrates and aliphatic carboxylic acids formed during wood processing

Knowledge of the behaviour of cellulose, hemicelluloses, and lignin during wood and pulp processing is essential for understanding and controlling the processes. Determination of monosaccharide composition gives information about the structural polysaccharide composition of wood material and helps when determining the quality of fibrous products. In addition, monitoring of the acidic degradation products gives information of the extent of degradation of lignin and polysaccharides. This work describes two capillary electrophoretic methods developed for the analysis of monosaccharides and for the determination of aliphatic carboxylic acids from alkaline oxidation solutions of lignin and wood. Capillary electrophoresis (CE), in its many variants is an alternative separation technique to chromatographic methods. In capillary zone electrophoresis (CZE) the fused silica capillary is filled with an electrolyte solution. An applied voltage generates a field across the capillary. The movement of the ions under electric field is based on the charge and hydrodynamic radius of ions. Carbohydrates contain hydroxyl groups that are ionised only in strongly alkaline conditions. After ionisation, the structures are suitable for electrophoretic analysis and identification through either indirect UV detection or electrochemical detection. The current work presents a new capillary zone electrophoretic method, relying on in-capillary reaction and direct UV detection at the wavelength of 270 nm. The method has been used for the simultaneous separation of neutral carbohydrates, including mono- and disaccharides and sugar alcohols. The in-capillary reaction produces negatively charged and UV-absorbing compounds. The optimised method was applied to real samples. The methodology is fast since no other sample preparation, except dilution, is required. A new method for aliphatic carboxylic acids in highly alkaline process liquids was developed. The goal was to develop a method for the simultaneous analysis of the dicarboxylic acids, hydroxy acids and volatile acids that are oxidation and degradation products of lignin and wood polysaccharides. The CZE method was applied to three process cases. First, the fate of lignin under alkaline oxidation conditions was monitored by determining the level of carboxylic acids from process solutions. In the second application, the degradation of spruce wood using alkaline and catalysed alkaline oxidation were compared by determining carboxylic acids from the process solutions. In addition, the effectiveness of membrane filtration and preparative liquid chromatography in the enrichment of hydroxy acids from black liquor was evaluated, by analysing the effluents with capillary electrophoresis.

On Dynamic Monitoring Methods for Networks-on-Chip

Rapid ongoing evolution of multiprocessors will lead to systems with hundreds of processing cores integrated in a single chip. An emerging challenge is the implementation of reliable and efficient interconnection between these cores as well as other components in the systems. Network-on-Chip is an interconnection approach which is intended to solve the performance bottleneck caused by traditional, poorly scalable communication structures such as buses. However, a large on-chip network involves issues related to congestion problems and system control, for instance. Additionally, faults can cause problems in multiprocessor systems. These faults can be transient faults, permanent manufacturing faults, or they can appear due to aging. To solve the emerging traffic management, controllability issues and to maintain system operation regardless of faults a monitoring system is needed. The monitoring system should be dynamically applicable to various purposes and it should fully cover the system under observation. In a large multiprocessor the distances between components can be relatively long. Therefore, the system should be designed so that the amount of energy-inefficient long-distance communication is minimized. This thesis presents a dynamically clustered distributed monitoring structure. The monitoring is distributed so that no centralized control is required for basic tasks such as traffic management and task mapping. To enable extensive analysis of different Network-on-Chip architectures, an in-house SystemC based simulation environment was implemented. It allows transaction level analysis without time consuming circuit level implementations during early design phases of novel architectures and features. The presented analysis shows that the dynamically clustered monitoring structure can be efficiently utilized for traffic management in faulty and congested Network-on-Chip-based multiprocessor systems. The monitoring structure can be also successfully applied for task mapping purposes. Furthermore, the analysis shows that the presented in-house simulation environment is flexible and practical tool for extensive Network-on-Chip architecture analysis.