Bayes quadratic unbiased estimator of spatial covariance parameters

This work presents Bayes invariant quadratic unbiased estimator, for short BAIQUE. Bayesian approach is used here to estimate the covariance functions of the regionalized variables which appear in the spatial covariance structure in mixed linear model. Firstly a brief review of spatial process, variance covariance components structure and Bayesian inference is given, since this project deals with these concepts. Then the linear equations model corresponding to BAIQUE in the general case is formulated. That Bayes estimator of variance components with too many unknown parameters is complicated to be solved analytically. Hence, in order to facilitate the handling with this system, BAIQUE of spatial covariance model with two parameters is considered. Bayesian estimation arises as a solution of a linear equations system which requires the linearity of the covariance functions in the parameters. Here the availability of prior information on the parameters is assumed. This information includes apriori distribution functions which enable to find the first and the second moments matrix. The Bayesian estimation suggested here depends only on the second moment of the prior distribution. The estimation appears as a quadratic form y'Ay , where y is the vector of filtered data observations. This quadratic estimator is used to estimate the linear function of unknown variance components. The matrix A of BAIQUE plays an important role. If such a symmetrical matrix exists, then Bayes risk becomes minimal and the unbiasedness conditions are fulfilled. Therefore, the symmetry of this matrix is elaborated in this work. Through dealing with the infinite series of matrices, a representation of the matrix A is obtained which shows the symmetry of A. In this context, the largest singular value of the decomposed matrix of the infinite series is considered to deal with the convergence condition and also it is connected with Gerschgorin Discs and Poincare theorem. Then the BAIQUE model for some experimental designs is computed and compared. The comparison deals with different aspects, such as the influence of the position of the design points in a fixed interval. The designs that are considered are those with their points distributed in the interval [0, 1]. These experimental structures are compared with respect to the Bayes risk and norms of the matrices corresponding to distances, covariance structures and matrices which have to satisfy the convergence condition. Also different types of the regression functions and distance measurements are handled. The influence of scaling on the design points is studied, moreover, the influence of the covariance structure on the best design is investigated and different covariance structures are considered. Finally, BAIQUE is applied for real data. The corresponding outcomes are compared with the results of other methods for the same data. Thereby, the special BAIQUE, which estimates the general variance of the data, achieves a very close result to the classical empirical variance.

Entwicklung und Anwendung einer Kraftwerks- und Speichereinsatzoptimierung für die Untersuchung von Energieversorgungsszenarien mit hohem Anteil erneuerbarer Energien in Deutschland

In dieser Arbeit wurde ein gemischt-ganzzahliges lineares Einsatzoptimierungsmodell für Kraftwerke und Speicher aufgebaut und für die Untersuchung der Energieversorgung Deutschlands im Jahre 2050 gemäß den Leitstudie-Szenarien 2050 A und 2050 C ([Nitsch und Andere, 2012]) verwendet, in denen erneuerbare Energien einen Anteil von über 85 % an der Stromerzeugung haben und die Wind- und Solarenergie starke Schwankungen der durch steuerbare Kraftwerke und Speicher zu deckenden residualen Stromnachfrage (Residuallast) verursachen. In Szenario 2050 A sind 67 TWh Wasserstoff, die elektrolytisch aus erneuerbarem Strom zu erzeugen sind, für den Verkehr vorgesehen. In Szenario 2050 C ist kein Wasserstoff für den Verkehr vorgesehen und die effizientere Elektromobilität hat einen Anteil von 100% am Individualverkehr. Daher wird weniger erneuerbarer Strom zur Erreichung desselben erneuerbaren Anteils im Verkehrssektor benötigt. Da desweiteren Elektrofahrzeuge Lastmanagementpotentiale bieten, weisen die Residuallasten der Szenarien eine unterschiedliche zeitliche Charakteristik und Jahressumme auf. Der Schwerpunkt der Betrachtung lag auf der Ermittlung der Auslastung und Fahrweise des in den Szenarien unterstellten ’Kraftwerks’-parks bestehend aus Kraftwerken zur reinen Stromerzeugung, Kraft-Wärme-Kopplungskraftwerken, die mit Wärmespeichern, elektrischen Heizstäben und Gas-Backupkesseln ausgestattet sind, Stromspeichern und Wärmepumpen, die durch Wärmespeicher zum Lastmanagment eingesetzt werden können. Der Fahrplan dieser Komponenten wurde auf minimale variable Gesamtkosten der Strom- und Wärmeerzeugung über einen Planungshorizont von jeweils vier Tagen hin optimiert. Das Optimierungsproblem wurde mit dem linearen Branch-and-Cut-Solver der software CPLEX gelöst. Mittels sogenannter rollierender Planung wurde durch Zusammensetzen der Planungsergebnisse für überlappende Planungsperioden der Kraftwerks- und Speichereinsatz für die kompletten Szenariojahre erhalten. Es wurde gezeigt, dass der KWK-Anteil an der Wärmelastdeckung gering ist. Dies wurde begründet durch die zeitliche Struktur der Stromresiduallast, die wärmeseitige Dimensionierung der Anlagen und die Tatsache, dass nur eine kurzfristige Speicherung von Wärme vorgesehen war. Die wärmeseitige Dimensionierung der KWK stellte eine Begrenzung des Deckungsanteils dar, da im Winter bei hoher Stromresiduallast nur wenig freie Leistung zur Beladung der Speicher zur Verfügung stand. In den Berechnungen für das Szenario 2050 A und C lag der mittlere Deckungsanteil der KWK an der Wärmenachfrage von ca. 100 TWh_th bei 40 bzw. 60 %, obwohl die Auslegung der KWK einen theoretischen Anteil von über 97 % an der Wärmelastdeckung erlaubt hätte, gäbe es die Beschränkungen durch die Stromseite nicht. Desweiteren wurde die CO2-Vermeidungswirkung der KWK-Wärmespeicher und des Lastmanagements mit Wärmepumpen untersucht. In Szenario 2050 A ergab sich keine signifikante CO2-Vermeidungswirkung der KWK-Wärmespeicher, in Szenario 2050 C hingegen ergab sich eine geringe aber signifikante CO2-Einsparung in Höhe von 1,6 % der Gesamtemissionen der Stromerzeugung und KWK-gebundenen Wärmeversorgung. Das Lastmanagement mit Wärmepumpen vermied Emissionen von 110 Tausend Tonnen CO2 (0,4 % der Gesamtemissionen) in Szenario A und 213 Tausend Tonnen in Szenario C (0,8 % der Gesamtemissionen). Es wurden darüber hinaus Betrachtungen zur Konkurrenz zwischen solarthermischer Nahwärme und KWK bei Einspeisung in dieselben Wärmenetze vorgenommen. Eine weitere Einschränkung der KWK-Erzeugung durch den Einspeisevorrang der Solarthermie wurde festgestellt. Ferner wurde eine untere Grenze von 6,5 bzw. 8,8 TWh_th für die in den Szenarien mindestens benötigte Wasserstoff-Speicherkapazität ermittelt. Die Ergebnisse dieser Arbeit legen nahe, das technisch-ökonomische Potential von Langzeitwärmespeichern für eine bessere Integration von KWK ins System zu ermitteln bzw. generell nach geeigneteren Wärmesektorszenarien zu suchen, da deutlich wurde, dass für die öffentliche Wärmeversorgung die KWK in Kombination mit Kurzzeitwärmespeicherung, Gaskesseln und elektrischen Heizern keine sehr effektive CO2 -Reduktion in den Szenarien erreicht. Es sollte dabei z.B. untersucht werden, ob ein multivalentes System aus KWK, Wärmespeichern und Wärmepumpen eine ökonomisch darstellbare Alternative sein könnte und im Anschluss eine Betrachtung der optimalen Anteile von KWK, Wärmepumpen und Solarthermie im Wärmemarkt vorgenommen werden.

The PHD: A Planar, Harmonic Drive Robot for Joint Torque Control

This thesis details the development of a model of a seven degree of freedom manipulator for position control. Then, it goes on to discuss the design and construction of a the PHD, a robot built to serve two purposes: first, to perform research on joint torque control schemes, and second, to determine the important dynamic characteristics of the Harmonic Drive. The PHD, is a planar, three degree of freedom arm with torque sensors integral to each joint. Preliminary testing has shown that a simple linear spring model of the Harmonic Drive's flexibility is suitable in many situations.

La diplomacia cultural como herramienta para el mejoramiento de la relación económica de Colombia con Corea del Sur y Australia

Esta investigación se preocupa por dilucidar la función de la diplomacia cultural como herramienta para mejorar la relación económica de Colombia con Corea del Sur y Australia. Así, se analiza a la diplomacia cultural y lo que hace Colombia en esta materia en ambos países; así como el estado de la relación económica de Colombia en un periodo de ocho años con dichos países, y cómo las acciones culturales colombianas podrían llegar a mejorar dicha relación económica. De esta manera además del desarrollo conceptual de diplomacia cultural y los indicadores económicos, a saber; exportaciones; Inversión Extranjera Directa y turismo; se corrió un modelo de regresión lineal para saber si efectivamente hay relación entre ambas variables y una contribución final que consiste en una propuesta de generación de indicadores de gestión a utilizarse al momento de implementar la diplomacia cultural como herramienta en política exterior.

Use of Large Clear-Cuts by Wilson’s Warbler in an Eastern Canadian Boreal Forest

Wilson’s Warbler (Cardellina pusilla; WIWA) has been declining for several decades, possibly because of habitat loss. We compared occupancy of territorial males in two habitat types of Québec’s boreal forest, alder (Alnus spp.) scrubland and recent clear-cuts. Singing males occurred in clusters, their occupancy was similar in both habitats, but increased with the amount of alder or clear-cut within 400 m of point-count stations. A despotic distribution of males between habitats appeared unlikely, because there were no differences in morphology between males captured in clear-cuts vs. alder. Those results contrast with the prevailing view, mostly based on western populations, that WIWA are wetland or riparian specialists, and provide the first evidence for a preference for large tracts of habitat in this species. Clear-cuts in the boreal forest may benefit WIWA by supplying alternative nesting habitat. However, the role of clear-cuts as source or sink habitats needs to be addressed with data on reproduction.

Serial clustering of extratropical cyclones

The clustering in time (seriality) of extratropical cyclones is responsible for large cumulative insured losses in western Europe, though surprisingly little scientific attention has been given to this important property. This study investigates and quantifies the seriality of extratropical cyclones in the Northern Hemisphere using a point-process approach. A possible mechanism for serial clustering is the time-varying effect of the large-scale flow on individual cyclone tracks. Another mechanism is the generation by one parent cyclone of one or more offspring through secondary cyclogenesis. A long cyclone-track database was constructed for extended October March winters from 1950 to 2003 using 6-h analyses of 850-mb relative vorticity derived from the NCEP NCAR reanalysis. A dispersion statistic based on the varianceto- mean ratio of monthly cyclone counts was used as a measure of clustering. It reveals extensive regions of statistically significant clustering in the European exit region of the North Atlantic storm track and over the central North Pacific. Monthly cyclone counts were regressed on time-varying teleconnection indices with a log-linear Poisson model. Five independent teleconnection patterns were found to be significant factors over Europe: the North Atlantic Oscillation (NAO), the east Atlantic pattern, the Scandinavian pattern, the east Atlantic western Russian pattern, and the polar Eurasian pattern. The NAO alone is not sufficient for explaining the variability of cyclone counts in the North Atlantic region and western Europe. Rate dependence on time-varying teleconnection indices accounts for the variability in monthly cyclone counts, and a cluster process did not need to be invoked.

Farming systems methodology for efficient resource management at the farm level: a review from an Indian perspective

Farming systems research is a multi-disciplinary holistic approach to solve the problems of small farms. Small and marginal farmers are the core of the Indian rural economy Constituting 0.80 of the total farming community but possessing only 0.36 of the total operational land. The declining trend of per capita land availability poses a serious challenge to the sustainability and profitability of farming. Under such conditions, it is appropriate to integrate land-based enterprises such as dairy, fishery, poultry, duckery, apiary, field and horticultural cropping within the farm, with the objective of generating adequate income and employment for these small and marginal farmers Under a set of farm constraints and varying levels of resource availability and Opportunity. The integration of different farm enterprises can be achieved with the help of a linear programming model. For the current review, integrated farming systems models were developed, by Way Of illustration, for the marginal, small, medium and large farms of eastern India using linear programming. Risk analyses were carried out for different levels of income and enterprise combinations. The fishery enterprise was shown to be less risk-prone whereas the crop enterprise involved greater risk. In general, the degree of risk increased with the increasing level of income. With increase in farm income and risk level, the resource use efficiency increased. Medium and large farms proved to be more profitable than small and marginal farms with higher level of resource use efficiency and return per Indian rupee (Rs) invested. Among the different enterprises of integrated farming systems, a chain of interaction and resource flow was observed. In order to make fanning profitable and improve resource use efficiency at the farm level, the synergy among interacting components of farming systems should be exploited. In the process of technology generation, transfer and other developmental efforts at the farm level (contrary to the discipline and commodity-based approaches which have a tendency to be piecemeal and in isolation), it is desirable to place a whole-farm scenario before the farmers to enhance their farm income, thereby motivating them towards more efficient and sustainable fanning.

Analysis of the calving pattern of herds in small-scale dairy systems in central Mexico

This study sets out to find the best calving pattern for small-scale dairy systems in Michoacan State, central Mexico. Two models were built. First, a linear programming model was constructed to optimize calving pattern and herd structure according to metabolizable energy availability. Second, a Markov chain model was built to investigate three reproductive scenarios (good, average and poor) in order to suggest factors that maintain the calving pattern given by the linear programming model. Though it was not possible to maintain the optimal linear programming pattern, the Markov chain model suggested adopting different reproduction strategies according to period of the year that the cow is expected to calve. Comparing different scenarios, the Markov model indicated the effect of calving interval on calving pattern and herd structure.

When are ant-attractant devices a worthwhile investment? Vicia faba extrafloral nectaries and Lasius niger ants

Most studies aiming to determine the beneficial effect of ants on plants simply consider the effects of the presence or exclusion of ants on plant yield. This approach is often inadequate, however, as ants interact with both non-tended herbivores and tended Homoptera. Moreover, the interaction with these groups of organisms is dependent on ant density, and these functional relationships are likely to be non-linear. A model is presented here that segregates plant herbivores into two categories depending on the sign of their numerical response to ants (myrmecophiles increase with ants, non-tended herbivores decline). The changes in these two components of herbivores with increasing ant density and the resulting implications for ant-plant mutualisms are considered. It emerges that a wide range of ant densities needs to be considered as the interaction sign (mutualism or parasitism) and strength is likely to change with ant density. The model is used to interpret the results of an experimental study that varied levels of Aphis fabae infestation and Lasius niger ant attendance on Vicia faba bean plants. Increasing ant density consistently reduced plant fitness and thus, in this location, the interaction between the ants and the plant can be considered parasitic. In the Vicia faba system, these costs of ants are unlikely to be offset by other beneficial agents (e.g., parasitoids), which also visit extrafloral nectaries.

Bayesian decision procedures for binary and continuous bivariate dose-escalation studies

In this paper, Bayesian decision procedures are developed for dose-escalation studies based on binary measures of undesirable events and continuous measures of therapeutic benefit. The methods generalize earlier approaches where undesirable events and therapeutic benefit are both binary. A logistic regression model is used to model the binary responses, while a linear regression model is used to model the continuous responses. Prior distributions for the unknown model parameters are suggested. A gain function is discussed and an optional safety constraint is included. Copyright (C) 2006 John Wiley & Sons, Ltd.

Dynamic integrated system optimization and parameter estimation for discrete time optimal control of nonlinear systems

An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.

A new approach for the solution of the optimal set-point tracking problem for nonlinear systems

In this paper, a discrete time dynamic integrated system optimisation and parameter estimation algorithm is applied to the solution of the nonlinear tracking optimal control problem. A version of the algorithm with a linear-quadratic model-based problem is developed and implemented in software. The algorithm implemented is tested with simulation examples.

Optimal control of nonlinear differential algebraic equation systems

A novel iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified linear quadratic model based problem with parameter updating in such a manner that the correct solution of the original non-linear problem is achieved. The resulting algorithm has a particular advantage in that the solution is achieved without the need to solve the differential algebraic equations . Convergence aspects are discussed and a simulation example is described which illustrates the performance of the technique. 1. Introduction When modelling industrial processes often the resulting equations consist of coupled differential and algebraic equations (DAEs). In many situations these equations are nonlinear and cannot readily be directly reduced to ordinary differential equations.

Gaussian quadrature 4D-VAR

A new incremental four-dimensional variational (4D-Var) data assimilation algorithm is introduced. The algorithm does not require the computationally expensive integrations with the nonlinear model in the outer loops. Nonlinearity is accounted for by modifying the linearization trajectory of the observation operator based on integrations with the tangent linear (TL) model. This allows us to update the linearization trajectory of the observation operator in the inner loops at negligible computational cost. As a result the distinction between inner and outer loops is no longer necessary. The key idea on which the proposed 4D-Var method is based is that by using Gaussian quadrature it is possible to get an exact correspondence between the nonlinear time evolution of perturbations and the time evolution in the TL model. It is shown that J-point Gaussian quadrature can be used to derive the exact adjoint-based observation impact equations and furthermore that it is straightforward to account for the effect of multiple outer loops in these equations if the proposed 4D-Var method is used. The method is illustrated using a three-level quasi-geostrophic model and the Lorenz (1996) model.

Modelling and inverting complex-valued Wiener systems

We develop a complex-valued (CV) B-spline neural network approach for efficient identification and inversion of CV Wiener systems. The CV nonlinear static function in the Wiener system is represented using the tensor product of two univariate B-spline neural networks. With the aid of a least squares parameter initialisation, the Gauss-Newton algorithm effectively estimates the model parameters that include the CV linear dynamic model coefficients and B-spline neural network weights. The identification algorithm naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. An accurate inverse of the CV Wiener system is then obtained, in which the inverse of the CV nonlinear static function of the Wiener system is calculated efficiently using the Gaussian-Newton algorithm based on the estimated B-spline neural network model, with the aid of the De Boor recursions. The effectiveness of our approach for identification and inversion of CV Wiener systems is demonstrated using the application of digital predistorter design for high power amplifiers with memory