Free-field characterization via directional transmission through a nanoaperture

We propose a scheme based on extraordinary transmission of light through a single nanoaperture, surrounded by periodic corrugations, for direct characterization of focal-region optical fields with subwavelength-scale structure. We describe the design of the device on the basis of rigorous diffraction theory and fabricate a prototype using a process that involves electron beam lithography, dry etching, and template stripping. First experimental results performed with a transmission-type confocal optical microscope demonstrate the potential of the method.     

The Bayesian Framework for Inverse Problems in Heat Transfer

The aim of this paper is to provide researchers dealing with inverse heat transfer problems a review of the Bayesian approach to inverse problems, the related modeling issues, and the methods that are used to carry out inference. In Bayesian inversion, the aim is not only to obtain a single point estimate for the unknown, but rather to characterize uncertainties in estimates, or predictions. Before any measurements are available, we have some uncertainty in the unknown. After carrying out measurements, the uncertainty has been reduced, and the task is to quantify this uncertainty, and in addition to give plausible suggestions for answers to questions of interest. The focus of this review is on the modeling-related topics in inverse problems in general, and the methods that are used to compute answers to questions. In particular, we build a scene of how to handle and model the unavoidable uncertainties that arise with real physical measurements. In addition to giving a brief review of existing Bayesian treatments of inverse heat transfer problems, we also describe approaches that might be successful with inverse heat transfer problems.     

Extracting Conditionally Heteroskedastic Components using Independent Component Analysis

In the independent component model, the multivariate data are assumed to be a mixture of mutually independent latent components. The independent component analysis (ICA) then aims at estimating these latent components. In this article, we study an ICA method which combines the use of linear and quadratic autocorrelations to enable efficient estimation of various kinds of stationary time series. Statistical properties of the estimator are studied by finding its limiting distribution under general conditions, and the asymptotic variances are derived in the case of ARMA-GARCH model. We use the asymptotic results and a finite sample simulation study to compare different choices of a weight coefficient. As it is often of interest to identify all those components which exhibit stochastic volatility features we suggest a test statistic for this problem. We also show that a slightly modified version of the principal volatility component analysis can be seen as an ICA method. Finally, we apply the estimators in analysing a data set which consists of time series of exchange rates of seven currencies to US dollar. Supporting information including proofs of the theorems is available online.     

Improvements and Modifications to Room‐Temperature Fabrication Method for Dielectric Li2MoO4 Ceramics

Dielectric properties of lithium molybdate disks fabricated by moistening water‐soluble Li₂MoO₄ powder, compressing it, and postprocessing the samples at 120°C, were improved by the optimization of powder particle size, sample pressing pressure, and postprocessing time. It appeared that the postprocessing temperature of the Li₂MoO₄ ceramics could be chosen so as to be applicable to the associated integrated materials as long as the postprocessing time was adequately adjusted to ensure the removal of the residual water. In addition, the dielectric properties of Li₂MoO₄ ceramic were modified with an inclusion of suitable additives. For example, at 1 GHz the relative permittivity of Li₂MoO₄ disks fabricated at room temperature and postprocessed at 120°C was increased from 6.4 to 8.8 with an addition of 10 vol% of rutile TiO₂ and to 9.7 with an addition of 10 vol% of BaTiO₃. At the same time the loss tangent value increased from 0.0006 to 0.0014 and to 0.011, respectively.     

A 35-year follow-up study on burnout among Finnish employees.

This three-wave 35-year prospective study used the Job Demands-Resources model and life course epidemiology to examine how life conditions in adolescence (1961–1963) through achieved educational level and working conditions in early adulthood (1985) may be indirectly related to job burnout 35 years later (1998). We used data (N = 511) from the Finnish Healthy Child study (1961–1963) to investigate the hypothesized relationships by employing structural equation modeling analyses. The results supported the hypothesized model in which both socioeconomic status and cognitive ability in adolescence (1961–1963) were positively associated with educational level (measured in 1985), which in turn was related to working conditions in early adulthood (1985). Furthermore, working conditions (1985) were associated with job burnout (1998) 13 years later. Moreover, adult education (1985) and skill variety (1985) mediated the associations between original socioeconomic status and cognitive ability, and burnout over a 35-year time period. The results suggest that socioeconomic, individual, and work-related resources may accumulate over the life course and may protect employees from job burnout. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics

Forest inventories based on single-tree interpretation of airborne laser scanning (ALS) data often rely on an allometric estimation chain in which inaccuracies in the estimates of the diameter at breast height (DBH) propagate to other characteristics of interest such as the stem volume. Our purpose was to test nearest neighbor imputation by the k-Most Similar Neighbor (k-MSN) and the Random Forest (RF) methods for the simultaneous estimation of species, DBH, height and stem volume using ALS data. The predictors included computational alpha shape metrics and variables based on the height and intensity distributions in the ALS data. Separate data sets covering 1898 and 1249 dominant to intermediate trees in a typical Scandinavian stand structure were used for training and validation, respectively. RF proved to be a flexible method with an ability to handle 1846 predictors with no need for their reduction. Classification of Scots pine, Norway spruce and deciduous trees showed an accuracy of 78%, and the estimates of DBH, height and volume had root mean square errors of 13%, 3%, and 31%, respectively, when evaluated against the validation data. The two selection strategies implemented here reduced the number of candidate variables effectively without any substantial effect on the accuracy relative to the use of all predictors. Differences in k-MSN and RF imputations were marginal when the reduced sets of variables were used. Estimation accuracies could be maintained practically unchanged with only 12.5% of the initial reference data (237 trees), provided the distribution of the observations was similar in the reference and target data. Since we used information collected in the field for extracting the ALS point clouds for individual trees, our results represent an optimal case and should nevertheless be validated against automated tree delineation.     

Budget-bounded model-checking pushdown systems

We address the verification problem for concurrent programs modeled as multi-pushdown systems (MPDS). In general, MPDS are Turing powerful and hence come along with undecidability of all basic decision problems. Because of this, several subclasses of MPDS have been proposed and studied in the literature (Atig et al. in LNCS, Springer, Berlin, 2005; La Torre et al. in LICS, IEEE, 2007; Lange and Lei in Inf Didact 8, 2009; Qadeer and Rehof in TACAS, LNCS, Springer, Berlin, 2005). In this paper, we propose the class of bounded-budget MPDS, which are restricted in the sense that each stack can perform an unbounded number of context switches only if its depth is below a given bound, and a bounded number of context switches otherwise. We show that the reachability problem for this subclass is Pspace-complete and that LTL-model-checking is Exptime-complete. Furthermore, we propose a code-to-code translation that inputs a concurrent program \(P\) and produces a sequential program \(P'\) such that running \(P\) under the budget-bounded restriction yields the same set of reachable states as running \(P'\) . Moreover, detecting (fair) non-terminating executions in \(P\) can be reduced to LTL-Model-Checking of \(P'\) . By leveraging standard sequential analysis tools, we have implemented a prototype tool and applied it on a set of benchmarks, showing the feasibility of our translation.     

Computational calibration method for optical tomography

We propose a computational calibration method for optical tomography. The model of the calibration scheme is based on the rotation symmetry of source and detector positions in the measurement setup. The relative amplitude losses and phase shifts at the optic fibers are modeled by complex-valued coupling coefficients. The coupling coefficients can be estimated when optical tomography data from a homogeneous and isotropic object are given. Once these coupling coefficients have been estimated, any data measured with the same measurement setup can be corrected for the relative variation in the data due to source and detector losses. The final calibration of the data for the source and detector losses and the source calibration between the data and the forward model are obtained as part of the initial estimation for reconstruction. The calibration method was tested with simulations and measurements. The results show that the coupling coefficients of the sources and detectors can be estimated with good accuracy. Furthermore, the results show that the method can significantly improve the quality of reconstructed images.     

Perspectives on personal learning environments held by vocational students

This article focuses on personal learning environments (PLEs). The idea with PLEs is to put students in a more central position in the learning process by allowing them to design their own learning environments and by emphasising the self-regulated nature of the learning. This study describes the structure, functions and challenges of PLEs made by 33 students from vocational and polytechnic level schools in Eastern Finland after the first year of using them. Document and artefact analysis revealed that students built their PLEs for: mirroring the conventional learning environment; as an environment for reflection; as an environment to showcase skills; and as an environment for collaboration and networking. Student reflections indicate that building and using a PLE is a challenging task which requires specific teacher and pedagogical support. Designing a PLE demands both ICT skills and an awareness of one’s own learning methods.