Paradigms and prisons: a narrative of translation and transformation : my hero's journey from "at-risk" youth to teacher/learner in a jail setting /

All life is suffering. Life is the pursuit ofhappiness. These are two foundational Buddhist dictums that, in their simplicity, I have entirely misunderstood regarding their depth, misreading them as contradictory. Indeed, my superficial interpretations led me to Thoreau's life ofquiet desperation and deep depression. We come to know and bring understanding to our lives by storying them. My own Hero's Journey, the path from my egoic selftoward the universal Self, can be understood as the resultant translations and transformations. Inevitably each of us is involved in such a story, though most are unaware of the stages along our own Hero's journey. ' Narrative honours writing as a means of knowing. The contemplative reflection allows insight into our imprisoning paradigms, beliefs, behaviours, and blind spots. My research revisits and explores nodal experiences along my Hero's Journey through 4 categories: self, society, soil, and Self. While the value of this process of narrative inquiry lay in its ability to come to know and understand one's self, perhaps its greater value is of a more universal nature. My inquiry, while adding to the body of academic educational narrative literature, may also illuminate a path to educators, students, and all interested, encouraging a response to the call of their own Hero's journey. I am a teacher/learner in a jail setting, working with youth between the ages of 12 and 18 who have committed crimes such as armed robbery, assault, rape, and murder. As this thesis follows my continual development from egoic self/teacher/learner to universal Self/Teacher/Learner, it also enables me to both consciously and unconsciously open the ways in which I expand my care, compassion, and love to work with at-risk youth.

Wave Height Ano Speotral Transformation In The Shallow Waters Of Kerala Ooast And Their Preoiotion

There are basically two methods for prediction of shallow water waves, viz. the graphical method and the numerical method. The numerical methods are being widely used, now—a—days, because they are fast, accurate and are especially useful when the prediction over a large spatial frame is required. Practically little has been done on the development of numerical models for the prediction of height and spectral transformation of waves as applicable to our coasts. Synchronized deep and shallow water wave measurements which are essential for study of wave transformation are very much lacking for our coasts. Under these circumstances, a comprehensive study of the wave transformation in the shallow waters of our coast was felt very important and is undertaken in the present investigation.

Wirkung von Ernterückständen transgener Pflanzen auf die mikrobielle C- und N-Transformation in landwirtschaftlich genutzten Böden am Beispiel von Bt-Mais

In der vorliegenden Arbeit ging es um die Erarbeitung, Anwendung und Beurteilung von quantitativen Analysenverfahren / Methoden für ein Monitoring von durch Bt-Mais verursachbaren Umwelteffekten im Boden. Die Ausgangsthese besagte, dass sich transgene Maisstreu beim mikrobiellen Abbau anders verhält als konventionelle. Bezugnehmend auf die These wurden zwei Freilandversuche (Freilandmikrokosmenmethode nach Raubuch 1997 über 2 Jahre, Quantifizierung des Maisstreuabbaus mit Hilfe kleiner Bodensäulen über 1 Jahr) und zwei Inkubationsversuche im Labor (INK bei drei verschiedenen Temperaturen über 49 Tage und INK mit verschiedenen landwirtschaftlich genutzten Böden über 49 Tage mit jeweils kontinuierlicher Respirationsratenermittlung nach Isermeyer 1952) sowie Inhaltsstoffbestimmungen der Maisstreu durchgeführt. Für alle Untersuchungen wurde Streu der vier Maissorten Novelis (transgen, Monsanto 810), Nobilis (Isolinie von Novelis), Valmont (transgen, Bt 176, Fa. Syngenta) und Prelude (Isolinie von Valmont) eingesetzt. Nach Beendigung der Laborversuche sowie des Freilandversuches nach der Freilandmikrokosmenmethode wurden mikrobielle Messgrößen wie Adenylategehalt, Ergosterolgehalt, Cmik- und Nmik-Gehalt am Boden-Streu-Gemisch bestimmt. Der Einsatz der Isotopentechnik (Bestimmung von 13C/12C an gemahlenem Boden-Streu-Gemisch bzw. gefriergetrocknetem K2SO4 als Extrakt aus dem Boden-Streu-Gemisch) ermöglichte eine genaue Quantifizierung der abgebauten Maisstreu und brachte dadurch Aufschluss über das Abbauverhalten verschiedener Maissorten. Bezüglich der Ermittlung der mikrobiellen Messgrößen ergab sich für die transgene Sorte Novelis* stets eine durchschnittlich geringere pilzliche Biomasse. Langfristig ergaben sich bei der Kohlenstoff- und Stickstoffdynamik keine Trends hinsichtlich transgener bzw. konventioneller Maisstreu. Sowohl im Freilandversuch nach der Mikrokosmenmethode als auch in den Inkubationsversuchen trat das Phänomen der kurzzeitigen Respirationsratenerhöhung der Mikroorganismen nach Zugabe der transgenen Maissorten auf, welches nicht bei Zugabe der konventionellen Maisstreu auszumachen war. ______________________________

Statistical evaluation of texture analysis from the biocrystallization method

The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

Synthesis of N-amino compounds and C2 symmetric N-amino compounds and transformation into aziridines using olefins

Aziridine, Stickstoffanaloga der Epoxide, können regio- und stereoselektive Ringöffnungsreaktionen eingehen, wodurch ihnen als „building blocks“ in der Organischen Synthese eine große Bedeutung zukommt. In dieser Arbeit wurden unterschiedliche N-Aminoverbindungen synthetisiert sowie die Anwendungsmöglichkeit dieser Hydrazinderivate als Stickstoffquellen in Aziridinierungen von Olefinen untersucht. In der vorliegenden Dissertation wurde eine neue Methode zur Darstellung von N-Aminosuccinimid entwickelt und die Einsatzmöglichkeit als Stickstoffquelle in Aziridinierungsreaktionen in einer Reihe von Umsetzungen mit funktionalisierten ebenso wie mit nicht-funktionalisierten Olefinen demonstriert. Die ableitbaren Aziridine wurden hierbei in Ausbeuten von bis zu 80 % erhalten. In der Aziridinierungsreaktion von N-Aminosuccinimid mit 4,7-Dihydro-2-isopropyl-1,3-dioxepin resultieren bicyclische Aziridinierungsprodukte, die als endo/exo-Isomere in einem 1:1-Verhältnis anfallen. Es ist in dieser Arbeit gelungen, die Isomere in guten Ausbeuten zu erhalten, sie säulenchromatographisch zu trennen und ihre Konfiguration im festen Zustand mittels Kristallstrukturanalyse eindeutig zu bestimmen. Enantiomerenangereicherte Olefine, wie z. B. in 2-Position alkylsubstituierte 5-Methyl-4H-1,3-dioxine mit Enantiomerenüberschüssen von 92% ee liefern in der Aziridinierung mit N-Aminosuccinimid und Iodosylbenzol ein 4-Methyl-1,3-oxazolidin-4-carbaldehydderivat in einer zweistufigen Reaktion- der Aziridinierung und einer Umlagerung- ein 4-Methyl-1,3-oxazolidin-4-carbaldehydderivat. Für die Diastereoselektivität des Aziridinierungsschrittes wurde 65 % de bestimmt. In einer neuen Synthese über zwei Stufen ausgehend von (+)-3,4-Dimethoxysuccinanhydrid konnte ein chiraler Stickstoffüberträger - (+)-N-Amino-3,4-dimethoxysuccinimid - in Ausbeuten bis zu 86 % synthetisiert. Die Umsetzung dieser optisch aktiven Stickstoffquelle mit einer Vielzahl prochiraler Alkene führt zu diastereomeren Aziridinen in Ausbeuten bis zu 65% und Diastereoselektivitäten von bis zu 66% de. Anhand ausgewählter Verbindungen konnten die Absolutkonfigurationen der Reaktionsprodukte mittels Kristallstrukturanalyse eindeutig geklärt werden.

Analyse selbsterregter Strömungsfelder im Verdichter-Leitrad durch Kopplung von Particle Image Velocimetry und Hitzdrahtanemometrie mittels Fast Fourier Transformation

Der Einsatz der Particle Image Velocimetry (PIV) zur Analyse selbsterregter Strömungsphänomene und das dafür notwendige Auswerteverfahren werden in dieser Arbeit beschrieben. Zur Untersuchung von solchen Mechanismen, die in Turbo-Verdichtern als Rotierende Instabilitäten in Erscheinung treten, wird auf Datensätze zurückgegriffen, die anhand experimenteller Untersuchungen an einem ringförmigen Verdichter-Leitrad gewonnen wurden. Die Rotierenden Instabilitäten sind zeitabhängige Strömungsphänomene, die bei hohen aerodynamischen Belastungen in Verdichtergittern auftreten können. Aufgrund der fehlenden Phaseninformation kann diese instationäre Strömung mit konventionellen PIV-Systemen nicht erfasst werden. Die Kármánsche Wirbelstraße und Rotierende Instabilitäten stellen beide selbsterregte Strömungsvorgänge dar. Die Ähnlichkeit wird genutzt um die Funktionalität des Verfahrens anhand der Kármánschen Wirbelstraße nachzuweisen. Der mittels PIV zu visualisierende Wirbeltransport erfordert ein besonderes Verfahren, da ein externes Signal zur Festlegung des Phasenwinkels dieser selbsterregten Strömung nicht zur Verfügung steht. Die Methodik basiert auf der Kopplung der PIV-Technik mit der Hitzdrahtanemometrie. Die gleichzeitige Messung mittels einer zeitlich hochaufgelösten Hitzdraht-Messung ermöglicht den Zeitpunkten der PIV-Bilder einen Phasenwinkel zuzuordnen. Hierzu wird das Hitzdrahtsignal mit einem FFT-Verfahren analysiert, um die PIV-Bilder entsprechend ihrer Phasenwinkel zu gruppieren. Dafür werden die aufgenommenen Bilder auf der Zeitachse der Hitzdrahtmessungen markiert. Eine systematische Analyse des Hitzdrahtsignals in der Umgebung der PIV-Messung liefert Daten zur Festlegung der Grundfrequenz und erlaubt es, der markierten PIV-Position einen Phasenwinkel zuzuordnen. Die sich aus den PIV-Bildern einer Klasse ergebenden Geschwindigkeitskomponenten werden anschließend gemittelt. Aus den resultierenden Bildern jeder Klasse ergibt sich das zweidimensionale zeitabhängige Geschwindigkeitsfeld, in dem die Wirbelwanderung der Kármánschen Wirbelstraße ersichtlich wird. In hierauf aufbauenden Untersuchungen werden Zeitsignale aus Messungen in einem Verdichterringgitter analysiert. Dabei zeigt sich, dass zusätzlich Filterfunktionen erforderlich sind. Im Ergebnis wird schließlich deutlich, dass die Übertragung der anhand der Kármánschen Wirbelstraße entwickelten Methode nur teilweise gelingt und weitere Forschungsarbeiten erforderlich sind.

Compact Representations for Fast Nonrigid Registration of Medical Images

We develop efficient techniques for the non-rigid registration of medical images by using representations that adapt to the anatomy found in such images. Images of anatomical structures typically have uniform intensity interiors and smooth boundaries. We create methods to represent such regions compactly using tetrahedra. Unlike voxel-based representations, tetrahedra can accurately describe the expected smooth surfaces of medical objects. Furthermore, the interior of such objects can be represented using a small number of tetrahedra. Rather than describing a medical object using tens of thousands of voxels, our representations generally contain only a few thousand elements. Tetrahedra facilitate the creation of efficient non-rigid registration algorithms based on finite element methods (FEM). We create a fast, FEM-based method to non-rigidly register segmented anatomical structures from two subjects. Using our compact tetrahedral representations, this method generally requires less than one minute of processing time on a desktop PC. We also create a novel method for the non-rigid registration of gray scale images. To facilitate a fast method, we create a tetrahedral representation of a displacement field that automatically adapts to both the anatomy in an image and to the displacement field. The resulting algorithm has a computational cost that is dominated by the number of nodes in the mesh (about 10,000), rather than the number of voxels in an image (nearly 10,000,000). For many non-rigid registration problems, we can find a transformation from one image to another in five minutes. This speed is important as it allows use of the algorithm during surgery. We apply our algorithms to find correlations between the shape of anatomical structures and the presence of schizophrenia. We show that a study based on our representations outperforms studies based on other representations. We also use the results of our non-rigid registration algorithm as the basis of a segmentation algorithm. That algorithm also outperforms other methods in our tests, producing smoother segmentations and more accurately reproducing manual segmentations.

Towards a unifying framework for pattern transformation in swarm systems

This paper identifies the major challenges in the area of pattern formation. The work is also motivated by the need for development of a single framework to surmount these challenges. A framework based on the control of macroscopic parameters is proposed. The issue of transformation of patterns is specifically considered. A definition for transformation and four special cases, namely elementary and geometrical transformations by repositioning all or some robots in the pattern are provided. Two feasible tools for pattern transformation namely, a macroscopic parameter method and a mathematical tool - Moebius transformation also known as the linear fractional transformation are introduced. The realization of the unifying framework considering planning and communication is reported.

Swarm pattern transformation methodologies

The work reported in this paper is motivated by the need for developing swarm pattern transformation methodologies. Two methods, namely a macroscopic method and a mathematical method are investigated for pattern transformation. The first method is based on macroscopic parameters while the second method is based on both microscopic and macroscopic parameters. A formal definition to pattern transformation considering four special cases of transformation is presented. Simulations on a physics simulation engine are used to confirm the feasibility of the proposed transformation methods. A brief comparison between the two methods is also presented.

Investigating feasible tools for swarm pattern transformation

Abstract-The work reported in this paper is motivated by the need for developing swarm pattern transformation methodologies. Two methods, namely a macroscopic method and a mathematical method are investigated for pattern transformation. The first method is based on macroscopic parameters while the second method is based on both microscopic and macroscopic parameters. A formal definition to pattern transformation considering four special cases of transformation is presented. Simulations on a physics simulation engine are used to confirm the feasibility of the proposed transformation methods. A brief comparison between the two methods is also presented.

Modified radial basis function neural network using output transformation

A modified radial basis function (RBF) neural network and its identification algorithm based on observational data with heterogeneous noise are introduced. The transformed system output of Box-Cox is represented by the RBF neural network. To identify the model from observational data, the singular value decomposition of the full regression matrix consisting of basis functions formed by system input data is initially carried out and a new fast identification method is then developed using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator (MLE) for a model base spanned by the largest eigenvectors. Finally, the Box-Cox transformation-based RBF neural network, with good generalisation and sparsity, is identified based on the derived optimal Box-Cox transformation and an orthogonal forward regression algorithm using a pseudo-PRESS statistic to select a sparse RBF model with good generalisation. The proposed algorithm and its efficacy are demonstrated with numerical examples.

A method for incorporating climate variability in climate change impact assessments: sensitivity of river flows in the Eden catchment to precipitation scenarios

Interest in the impacts of climate change is ever increasing. This is particularly true of the water sector where understanding potential changes in the occurrence of both floods and droughts is important for strategic planning. Climate variability has been shown to have a significant impact on UK climate and accounting for this in future climate cahgne projections is essential to fully anticipate potential future impacts. In this paper a new resampling methodology is developed which includes the variability of both baseline and future precipitation. The resampling methodology is applied to 13 CMIP3 climate models for the 2080s, resulting in an ensemble of monthly precipitation change factors. The change factors are applied to the Eden catchment in eastern Scotland with analysis undertaken for the sensitivity of future river flows to the changes in precipitation. Climate variability is shown to influence the magnitude and direction of change of both precipitation and in turn river flow, which are not apparent without the use of the resampling methodology. The transformation of precipitation changes to river flow changes display a degree of non-linearity due to the catchment's role in buffering the response. The resampling methodology developed in this paper provides a new technique for creating climate change scenarios which incorporate the important issue of climate variability.

Technical Note: The normal quantile transformation and its application in a flood forecasting system.

The Normal Quantile Transform (NQT) has been used in many hydrological and meteorological applications in order to make the Cumulated Distribution Function (CDF) of the observed, simulated and forecast river discharge, water level or precipitation data Gaussian. It is also the heart of the meta-Gaussian model for assessing the total predictive uncertainty of the Hydrological Uncertainty Processor (HUP) developed by Krzysztofowicz. In the field of geo-statistics this transformation is better known as the Normal-Score Transform. In this paper some possible problems caused by small sample sizes when applying the NQT in flood forecasting systems will be discussed and a novel way to solve the problem will be outlined by combining extreme value analysis and non-parametric regression methods. The method will be illustrated by examples of hydrological stream-flow forecasts.

A nonparametric ensemble transform method for Bayesian inference

Many applications, such as intermittent data assimilation, lead to a recursive application of Bayesian inference within a Monte Carlo context. Popular data assimilation algorithms include sequential Monte Carlo methods and ensemble Kalman filters (EnKFs). These methods differ in the way Bayesian inference is implemented. Sequential Monte Carlo methods rely on importance sampling combined with a resampling step, while EnKFs utilize a linear transformation of Monte Carlo samples based on the classic Kalman filter. While EnKFs have proven to be quite robust even for small ensemble sizes, they are not consistent since their derivation relies on a linear regression ansatz. In this paper, we propose another transform method, which does not rely on any a priori assumptions on the underlying prior and posterior distributions. The new method is based on solving an optimal transportation problem for discrete random variables. © 2013, Society for Industrial and Applied Mathematics

An ASIFT-based local registration method for satellite imagery

Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensing applications in which ground control points (GCPs) are not always available, such as in selecting a landing zone on an outer space planet. In this paper, a framework for localization in image registration is developed. It strengthened the local registration accuracy from two aspects: less reprojection error and better feature point distribution. Affine scale-invariant feature transform (ASIFT) was used for acquiring feature points and correspondences on the input images. Then, a homography matrix was estimated as the transformation model by an improved random sample consensus (IM-RANSAC) algorithm. In order to identify a registration region with a better spatial distribution of feature points, the Euclidean distance between the feature points is applied (named the S criterion). Finally, the parameters of the homography matrix were optimized by the Levenberg–Marquardt (LM) algorithm with selective feature points from the chosen registration region. In the experiment section, the Chang’E-2 satellite remote sensing imagery was used for evaluating the performance of the proposed method. The experiment result demonstrates that the proposed method can automatically locate a specific region with high registration accuracy between input images by achieving lower root mean square error (RMSE) and better distribution of feature points.