Size and shape of oxygen vacancies and protons in acceptor-doped barium zirconate

The defect induced chemical expansion in acceptor-doped barium zirconate is investigated using density-functional theory (DFT) calculations. The two defect species involved in the hydration reaction, the +2 charged oxygen vacancy and the proton interstitial forming a hydroxide ion, are considered both as free defects and in association with the dopants Y, In, Sc and Ga. The defect induced strain tensor lambda is introduced, which provides a natural generalisation of the ordinary chemical expansion to three dimensions and to anisotropic distortions. Both the addition of a vacancy and a proton cause anisotropic distortions and a net contraction of the lattice, indicating that both the vacancy and the hydroxide ion are smaller than the oxygen ion. The contraction is considerably larger for the vacancy and the net effect in hydration, when a vacancy is filled and two protons are added, is an expansion, consistent with the experimental findings. The effect of the dopants on the chemical expansion in hydration is found to be quite small, even if it is assumed that both the vacancy and the proton are fully associated with a dopant atom in the lattice

Parsimonious Mahalanobis Kernel for the Classification of High Dimensional Data

The classification of high dimensional data with kernel methods is considered in this article. Exploit- ing the emptiness property of high dimensional spaces, a kernel based on the Mahalanobis distance is proposed. The computation of the Mahalanobis distance requires the inversion of a covariance matrix. In high dimensional spaces, the estimated covariance matrix is ill-conditioned and its inversion is unstable or impossible. Using a parsimonious statistical model, namely the High Dimensional Discriminant Analysis model, the specific signal and noise subspaces are estimated for each considered class making the inverse of the class specific covariance matrix explicit and stable, leading to the definition of a parsimonious Mahalanobis kernel. A SVM based framework is used for selecting the hyperparameters of the parsimonious Mahalanobis kernel by optimizing the so-called radius-margin bound. Experimental results on three high dimensional data sets show that the proposed kernel is suitable for classifying high dimensional data, providing better classification accuracies than the conventional Gaussian kernel

Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image

Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or endmembers) with their corresponding proportions (or abundances). Endmember extraction algorithms can be employed for recovering the spectral signatures while abundances are estimated using an inversion step. Recent works have shown that exploiting spatial dependencies between image pixels can improve spectral unmixing. Markov random fields (MRF) are classically used to model these spatial correlations and partition the image into multiple classes with homogeneous abundances. This paper proposes to define the MRF sites using similarity regions. These regions are built using a self-complementary area filter that stems from the morphological theory. This kind of filter divides the original image into flat zones where the underlying pixels have the same spectral values. Once the MRF has been clearly established, a hierarchical Bayesian algorithm is proposed to estimate the abundances, the class labels, the noise variance, and the corresponding hyperparameters. A hybrid Gibbs sampler is constructed to generate samples according to the corresponding posterior distribution of the unknown parameters and hyperparameters. Simulations conducted on synthetic and real AVIRIS data demonstrate the good performance of the algorithm

Fjármögnun Háskóla Íslands

Efst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkin

Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods

Hyperspectral images show similar statistical properties to natural grayscale or color photographic images. However, the classification of hyperspectral images is more challenging because of the very high dimensionality of the pixels and the small number of labeled examples typically available for learning. These peculiarities lead to particular signal processing problems, mainly characterized by indetermination and complex manifolds. The framework of statistical learning has gained popularity in the last decade. New methods have been presented to account for the spatial homogeneity of images, to include user's interaction via active learning, to take advantage of the manifold structure with semisupervised learning, to extract and encode invariances, or to adapt classifiers and image representations to unseen yet similar scenes. This tutuorial reviews the main advances for hyperspectral remote sensing image classification through illustrative examples.Comment: IEEE Signal Processing Magazine, 201

Culturally responsive assessment in compulsory schooling in Denmark and Iceland - An illusion or a reality? A comparative study of student teachers’ experiences and perspectives

This paper explores and compares student teachers’ experiences and perspectives on culturally responsive assessment in compulsory schooling in Denmark and Iceland. The study’s theoretical framework draws on scholarship on culturally responsive assessment. The data was derived from fourteen interviews with Danish student teachers and ten interviews with Icelandic student teachers. As per the selection criteria, all participants had to be in the final stages of their education process, meaning they had completed their on-site schoolteacher training and most courses in their teacher education programme. During the interviews, the participants reflected on pre-instructional, formative, and summative assessment practices with cultural diversity in mind. Furthermore, they discussed the importance of assessing children’s well-being. In both countries, the participants demonstrated positive attitudes towards cultural diversity and expressed awareness of considering children’s cultural and linguistic backgrounds when assessing them. On the other hand, most participants expressed criticism of teacher education programmes for lacking attention to the topic of culturally responsive assessment, which resulted in their rudimentary understanding of the theoretical underpinnings.publishedVersio

Three simple steps for improving diagnostic accuracy in hypertension

Neðst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinn View/OpenObjective: Most patients have only had three measurements of blood pressure before being labelled as hypertensive. This abbreviated assessment may lead to inaccurate classification, unnecessary treatment and dilution in treatment benefit for the population. We aimed to explore how accurate current methods are in diagnosing mild hypertension, and to explore practical methods of improving targeting of antihypertensive treatment using clinic visits but without lengthy observation. Material and methods: We applied current diagnostic methods to 3965 individuals with mild hypertension who were followed for a year in the placebo arm of the MRC Mild Hypertension Trial (Medical Research Council). We thus calculated the proportion selected for treatment by current methods and the diagnostic accuracy, using average blood pressure beyond six months as representing "true" long-term blood pressure. We looked at the benefit of averaging blood pressures, prolonging observation modestly and estimating within-person blood pressure variability. Results: Prolonging observation to three months selects a smaller (by about 12%) proportion of the sample for treatment. At three months the proportion of the sample selected is similar to the proportion defined as "truly" hypertensive. The diagnostic accuracy of current methods is poor with up to 69% discrepancy in classification. This discrepancy was improved in absolute terms by up to 18% by prolonging observation to three months and using average blood pressures. Identifying those individuals with low within-person variability allows marked improvement in the prediction of "true" hypertension. Conclusion: Although some inaccuracy in the diagnosis of hypertension is inevitable, observation for three months, averaging blood pressures and estimating within-person blood pressure variability can markedly improve upon current methods used for targeting antihypertensive treatment.Tilgangur: Flestir sem greindir hafa verið með háþrýsting hafa fengið greininguna eftir þrjár eða færri mælingar á blóðþrýstingi hjá lækni. Þetta skyndimat gæti leitt til ónákvæmni í greiningu, ónauðsynlegrar meðhöndlunar og minni meðferðarávinnings en efni standa til. Við höfum reynt að meta hversu nákvæm greining fæst með hefðbundnum aðferðum og skoðað hagnýt ráð sem beita mætti til þess að bæta öryggi greiningarinnar án þess að seinka greiningu um of. Efniviður og aðferðir: 3965 manns var fylgt eftir í lyfleysuhluta "MRC Mild Hypertension Trial" (Medical Research Council). Hlutfall hópsins sem myndi hafa valist til meðferðar samkvæmt algengum klínískum vinnubrögðum var metið og einnig var reynt að áætla nákvæmni þeirrar greiningar með samanburði við meðalþrýsting eftir meira en sex mánaða eftirfylgni sem var talið ígildi raunverulegs langtímablóðþrýstings. Við litum á kosti þess að nota meðalþrýsting nokkurra heimsókna, eftirlit og bið í tiltölulega skamman tíma (þrjá mánuði) og áhrif þess að taka tillit til breytileika blóðþrýstings hvers einstaklings. Niðurstöður: Greining háþrýstings eftir þriggja mánaða eftirlit fremur en eftir þrjár mælingar minnkar hópinn sem talinn er hafa háþrýsting um næstum 12%. Ekki virtist ávinningur af því að lengja eftirlitið frekar. Greining háþrýstings samkvæmt þeim hefðbundnu vinnubrögðum sem oftast er beitt núna er ónákvæm og leiðir hugsanlega til rangrar greiningar hjá allt að 69% einstaklinga. Ónákvæmnina má minnka um allt að 18% með því að bíða með greiningu í þrjá mánuði og með því að nota meðalblóðþrýsting nokkurra heimsókna. Auðveldara reynist að spá fyrir um raunverulegan langtímablóðþrýsting með því að leggja mat á breytileika blóðþrýstings. Ályktun: Nokkur ónákvæmni í greiningu háþrýstings er óhjákvæmileg en auka má verulega öryggi greiningarinnar með því að fylgja fólki eftir í þrjá mánuði, nota meðalblóðþrýsting og leggja mat á breytileika blóðþrýstings hvers og eins