902 resultados para Incidental parameter bias


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The magnetic properties of amorphous Fe–Ni–B based metallic glass nanostructures were investigated. The nanostructures underwent a spin-glass transition at temperatures below 100 K and revealed an irreversible temperature following the linear de Almeida–Thouless dependence. When the nanostructures were cooled below 25 K in a magnetic field, they exhibited an exchange bias effect with enhanced coercivity. The observed onset of exchange bias is associated with the coexistence of the spin-glass phase along with the appearance of another spin-glass phase formed by oxidation of the structurally disordered surface layer, displaying a distinct training effect and cooling field dependence. The latter showed a maximum in exchange bias field and coercivity, which is probably due to competing multiple equivalent spin configurations at the boundary between the two spin-glass phases

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The major problem of the engineering entrance examination is the exclusion of certain sections of the society in social, economic, regional and gender dimensions. This has seldom been taken for analysis towards policy correction. To lessen this problem a minor policy shift was prepared in the year 2011 with a 50–50 proportion in academic marks and entrance marks. The impact of this change is yet to be scrutinized. The data for the study is obtained from the Nodal Centre of Kerala functioning at Cochin University of Science and Technology under the National Technical Manpower Information System and also estimated from the Centralized Allotment Process. The article focuses on two aspects of exclusion based on engineering entrance examination; gender centred as well as caste-linked. Rank order spectral density and Lorenz ratio are used to cognize the exclusion and inequality in community and gender levels in various performance scales. The article unfolds the fact that social status in society coupled with economic affordability to quality education seems to have significant influence in the performance of students in the Kerala engineering entrance examinations. But it also shows that there is wide gender disparity with respect to performance in the high ranking levels irrespective of social groups

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b-In2S3 thin filmsweredepositedonIndiumTinOxidesubstratesusingtheChemical SprayPyrolysistechnique.Metalcontactwasdepositedoverthe b-In2S3 thin filmto formahetero-structureofthetypeITO/b-In2S3/Metal.Theintensityoftwophoto- luminescenceemissionsfromthe b-In2S3 thin film,centeredat520and690nmcould be variedbytheapplicationofanexternalbiasvoltagetothishetero-structure.The emissionscouldbeswitchedonoroffdependinguponthemagnitudeoftheexternal appliedbiasvoltage.Thusthepresenceoftwoconductingstatesinthishetero-structure could beidentified.Thetemporalvariationinintensityofthephotoluminescence emissionwiththeapplicationofthebiasvoltagehasalsobeenstudied.Thecondition underwhichphotoluminescencequenchingoccurshasbeenrepresentedbyafirst order differentialequationbetweendiffusionlengthandcarrierconcentration

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In dieser Arbeit werden mithilfe der Likelihood-Tiefen, eingeführt von Mizera und Müller (2004), (ausreißer-)robuste Schätzfunktionen und Tests für den unbekannten Parameter einer stetigen Dichtefunktion entwickelt. Die entwickelten Verfahren werden dann auf drei verschiedene Verteilungen angewandt. Für eindimensionale Parameter wird die Likelihood-Tiefe eines Parameters im Datensatz als das Minimum aus dem Anteil der Daten, für die die Ableitung der Loglikelihood-Funktion nach dem Parameter nicht negativ ist, und dem Anteil der Daten, für die diese Ableitung nicht positiv ist, berechnet. Damit hat der Parameter die größte Tiefe, für den beide Anzahlen gleich groß sind. Dieser wird zunächst als Schätzer gewählt, da die Likelihood-Tiefe ein Maß dafür sein soll, wie gut ein Parameter zum Datensatz passt. Asymptotisch hat der Parameter die größte Tiefe, für den die Wahrscheinlichkeit, dass für eine Beobachtung die Ableitung der Loglikelihood-Funktion nach dem Parameter nicht negativ ist, gleich einhalb ist. Wenn dies für den zu Grunde liegenden Parameter nicht der Fall ist, ist der Schätzer basierend auf der Likelihood-Tiefe verfälscht. In dieser Arbeit wird gezeigt, wie diese Verfälschung korrigiert werden kann sodass die korrigierten Schätzer konsistente Schätzungen bilden. Zur Entwicklung von Tests für den Parameter, wird die von Müller (2005) entwickelte Simplex Likelihood-Tiefe, die eine U-Statistik ist, benutzt. Es zeigt sich, dass für dieselben Verteilungen, für die die Likelihood-Tiefe verfälschte Schätzer liefert, die Simplex Likelihood-Tiefe eine unverfälschte U-Statistik ist. Damit ist insbesondere die asymptotische Verteilung bekannt und es lassen sich Tests für verschiedene Hypothesen formulieren. Die Verschiebung in der Tiefe führt aber für einige Hypothesen zu einer schlechten Güte des zugehörigen Tests. Es werden daher korrigierte Tests eingeführt und Voraussetzungen angegeben, unter denen diese dann konsistent sind. Die Arbeit besteht aus zwei Teilen. Im ersten Teil der Arbeit wird die allgemeine Theorie über die Schätzfunktionen und Tests dargestellt und zudem deren jeweiligen Konsistenz gezeigt. Im zweiten Teil wird die Theorie auf drei verschiedene Verteilungen angewandt: Die Weibull-Verteilung, die Gauß- und die Gumbel-Copula. Damit wird gezeigt, wie die Verfahren des ersten Teils genutzt werden können, um (robuste) konsistente Schätzfunktionen und Tests für den unbekannten Parameter der Verteilung herzuleiten. Insgesamt zeigt sich, dass für die drei Verteilungen mithilfe der Likelihood-Tiefen robuste Schätzfunktionen und Tests gefunden werden können. In unverfälschten Daten sind vorhandene Standardmethoden zum Teil überlegen, jedoch zeigt sich der Vorteil der neuen Methoden in kontaminierten Daten und Daten mit Ausreißern.

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Auf dem Gebiet der Strukturdynamik sind computergestützte Modellvalidierungstechniken inzwischen weit verbreitet. Dabei werden experimentelle Modaldaten, um ein numerisches Modell für weitere Analysen zu korrigieren. Gleichwohl repräsentiert das validierte Modell nur das dynamische Verhalten der getesteten Struktur. In der Realität gibt es wiederum viele Faktoren, die zwangsläufig zu variierenden Ergebnissen von Modaltests führen werden: Sich verändernde Umgebungsbedingungen während eines Tests, leicht unterschiedliche Testaufbauten, ein Test an einer nominell gleichen aber anderen Struktur (z.B. aus der Serienfertigung), etc. Damit eine stochastische Simulation durchgeführt werden kann, muss eine Reihe von Annahmen für die verwendeten Zufallsvariablengetroffen werden. Folglich bedarf es einer inversen Methode, die es ermöglicht ein stochastisches Modell aus experimentellen Modaldaten zu identifizieren. Die Arbeit beschreibt die Entwicklung eines parameter-basierten Ansatzes, um stochastische Simulationsmodelle auf dem Gebiet der Strukturdynamik zu identifizieren. Die entwickelte Methode beruht auf Sensitivitäten erster Ordnung, mit denen Parametermittelwerte und Kovarianzen des numerischen Modells aus stochastischen experimentellen Modaldaten bestimmt werden können.

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This study addresses the effectivity of the Anti-Bias approach and training methodology as a pedagogical political strategy to challenge oppression among student groups in the cities of Bombay and Berlin. The Anti-Bias trainings conducted within the framework of this study also become the medium through which the perpetuation of oppressive structures by students within and outside the school is investigated. Empirical data from predominantly qualitative investigations in four secondary schools, two each in Bombay and Berlin, is studied and analysed on the basis of theoretical understandings of prejudice, discrimination and identity. This study builds on insights offered by previous research on prejudices and evaluations of anti-bias and diversity interventions, where the lack of sufficient research and thorough evaluations testing impact has been identified (Levy Paluck, 2006). The theoretical framework suggests that prejudices and discriminatory practices are learnt and performed by individuals over the years by way of pre-existing discourses, and that behaviour and practices can be unlearnt through a multi-step process. It proposes that the discursive practices of students contribute to the constitution of their viable selves and in the constitution of ‘others’. Drawing on this framework, the study demonstrates how student-subjects in Bombay and Berlin perpetuate oppressive discourses by performing their identities and performing identities onto ‘others’. Such performative constitution opens up the agency of the individual, disclosing the shifting and dynamic nature of identities. The Anti-Bias approach is posited as an alternative to oppressive discourses and a vehicle that encourages and assists the agency of individuals. The theoretical framework, which brings together a psychological approach to prejudice, a structural approach to discrimination and a poststructural approach to identity, facilitates the analysis of the perpetuation of dominant discourses by the students, as well as how they negotiate their way through familiar norms and discourses. Group discussions and interviews a year after the respective trainings serve to evaluate the agency of the students and the extent to which the training impacted on their perceptions, attitudes and behavioural practices. The study reveals the recurrence of the themes race, religion, gender and sexuality in the representational practices of the students groups in Berlin and Bombay. It demonstrates how students in this study not only perform, but also negotiate and resist oppressive structures. Of particular importance is the role of the school: When schools offer no spaces for discussion, debate and action on contemporary social issues, learning can neither be put into practice nor take on a positive, transformative form. In such cases, agency and resistance is limited and interventionist actions yield little. This study reports the potential of the Anti-Bias approach and training as a tool of political education and action in education. It demonstrates that a single training can initiate change but sustaining change requires long-term strategies and on-going actions. Taking a poststructural perspective, it makes concrete suggestions to adapt and alter the Anti-Bias approach and the implementation of Anti-Bias trainings.

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Aus den im Rahmen dieser Forschungsarbeit empirisch gewonnenen Erkenntnissen werden Gestaltungsempfehlungen für das Public Debt Management abgeleitet. Diese zeigen, dass ein wirtschaftliches Public Debt Management nicht ein ausschließlich kostenminimierendes (sparsames), sondern ein kosten-risiko-optimales Public Debt Management mit effektiven internen und externen Überwachungsinstrumenten und wirksamer externer Finanzkontrolle sein muss.

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This report examines how to estimate the parameters of a chaotic system given noisy observations of the state behavior of the system. Investigating parameter estimation for chaotic systems is interesting because of possible applications for high-precision measurement and for use in other signal processing, communication, and control applications involving chaotic systems. In this report, we examine theoretical issues regarding parameter estimation in chaotic systems and develop an efficient algorithm to perform parameter estimation. We discover two properties that are helpful for performing parameter estimation on non-structurally stable systems. First, it turns out that most data in a time series of state observations contribute very little information about the underlying parameters of a system, while a few sections of data may be extraordinarily sensitive to parameter changes. Second, for one-parameter families of systems, we demonstrate that there is often a preferred direction in parameter space governing how easily trajectories of one system can "shadow'" trajectories of nearby systems. This asymmetry of shadowing behavior in parameter space is proved for certain families of maps of the interval. Numerical evidence indicates that similar results may be true for a wide variety of other systems. Using the two properties cited above, we devise an algorithm for performing parameter estimation. Standard parameter estimation techniques such as the extended Kalman filter perform poorly on chaotic systems because of divergence problems. The proposed algorithm achieves accuracies several orders of magnitude better than the Kalman filter and has good convergence properties for large data sets.

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We present a technique for the rapid and reliable evaluation of linear-functional output of elliptic partial differential equations with affine parameter dependence. The essential components are (i) rapidly uniformly convergent reduced-basis approximations — Galerkin projection onto a space WN spanned by solutions of the governing partial differential equation at N (optimally) selected points in parameter space; (ii) a posteriori error estimation — relaxations of the residual equation that provide inexpensive yet sharp and rigorous bounds for the error in the outputs; and (iii) offline/online computational procedures — stratagems that exploit affine parameter dependence to de-couple the generation and projection stages of the approximation process. The operation count for the online stage — in which, given a new parameter value, we calculate the output and associated error bound — depends only on N (typically small) and the parametric complexity of the problem. The method is thus ideally suited to the many-query and real-time contexts. In this paper, based on the technique we develop a robust inverse computational method for very fast solution of inverse problems characterized by parametrized partial differential equations. The essential ideas are in three-fold: first, we apply the technique to the forward problem for the rapid certified evaluation of PDE input-output relations and associated rigorous error bounds; second, we incorporate the reduced-basis approximation and error bounds into the inverse problem formulation; and third, rather than regularize the goodness-of-fit objective, we may instead identify all (or almost all, in the probabilistic sense) system configurations consistent with the available experimental data — well-posedness is reflected in a bounded "possibility region" that furthermore shrinks as the experimental error is decreased.

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The literature related to skew–normal distributions has grown rapidly in recent years but at the moment few applications concern the description of natural phenomena with this type of probability models, as well as the interpretation of their parameters. The skew–normal distributions family represents an extension of the normal family to which a parameter (λ) has been added to regulate the skewness. The development of this theoretical field has followed the general tendency in Statistics towards more flexible methods to represent features of the data, as adequately as possible, and to reduce unrealistic assumptions as the normality that underlies most methods of univariate and multivariate analysis. In this paper an investigation on the shape of the frequency distribution of the logratio ln(Cl−/Na+) whose components are related to waters composition for 26 wells, has been performed. Samples have been collected around the active center of Vulcano island (Aeolian archipelago, southern Italy) from 1977 up to now at time intervals of about six months. Data of the logratio have been tentatively modeled by evaluating the performance of the skew–normal model for each well. Values of the λ parameter have been compared by considering temperature and spatial position of the sampling points. Preliminary results indicate that changes in λ values can be related to the nature of environmental processes affecting the data