Illumination-invariant face recognition from a single image across extreme pose using a dual dimension AAM ensemble in the thermal infrared spectrum

Over the course of the last decade, infrared (IR) and particularly thermal IR imaging based face recognition has emerged as a promising complement to conventional, visible spectrum based approaches which continue to struggle when applied in practice. While inherently insensitive to visible spectrum illumination changes, IR data introduces specific challenges of its own, most notably sensitivity to factors which affect facial heat emission patterns, e.g. emotional state, ambient temperature, and alcohol intake. In addition, facial expression and pose changes are more difficult to correct in IR images because they are less rich in high frequency detail which is an important cue for fitting any deformable model. In this paper we describe a novel method which addresses these major challenges. Specifically, when comparing two thermal IR images of faces, we mutually normalize their poses and facial expressions by using an active appearance model (AAM) to generate synthetic images of the two faces with a neutral facial expression and in the same view (the average of the two input views). This is achieved by piecewise affine warping which follows AAM fitting. A major contribution of our work is the use of an AAM ensemble in which each AAM is specialized to a particular range of poses and a particular region of the thermal IR face space. Combined with the contributions from our previous work which addressed the problem of reliable AAM fitting in the thermal IR spectrum, and the development of a person-specific representation robust to transient changes in the pattern of facial temperature emissions, the proposed ensemble framework accurately matches faces across the full range of yaw from frontal to profile, even in the presence of scale variation (e.g. due to the varying distance of a subject from the camera). The effectiveness of the proposed approach is demonstrated on the largest public database of thermal IR images of faces and a newly acquired data set of thermal IR motion videos. Our approach achieved perfect recognition performance on both data sets, significantly outperforming the current state of the art methods even when they are trained with multiple images spanning a range of head views.

Influence of non-hydrolysable groups in silane precursor on pore dimension and photochromic properties of sol-gel silica embedded with a spirooxazine dye

In this work, silica embedded with a spirooxazine dye was prepared by hydrolysis of silanes that bear a nonhydrolyzable group of different structures through a sol-gel route in the presence of a spirooxazine dye, and the pore dimension and photochromic properties of photochromic silica coatings on fabric were studied. The pore dimension in the silica was examined by small angle X-ray scattering (SAXS), transmission electron microscopy (TEM), and nitrogen adsorption porosimetry. The SAXS results revealed that the distance between pores was in the range between 0.8 nm and 1.9 nm and it increased with increasing the size of the non-hydrolyzable group. Pore size measured by nitrogen adsorption porosimetry was in the range of 2.1-2.7 nm. The photochromic optical absorption was influenced mainly by the hydrophobicity of the non-hydrolyzable groups, while the color changing rates were influenced by the steric effect of the non-hydrolyzable groups and their interaction with the dye.

Science into policy? Discourse, coastal management and knowledge

The world's coastal resources are under pressure, even more so under climate change with 90% of the world's population living near or along our coastal zone. Ecologically, this zone is also the most productive, and the mainstay of economic livelihoods on a global scale. Managing the coast effectively is crucial, but as an area it remains contested. Despite multiple efforts to manage the coast, it remains a contested space. This paper offers a reflection into the ways in which different discourses influence and impact on one specific dimension of coastal zone management-the transmission of science into the policy domain. Using historical and discourse analysis, we find that the science-policy interface is largely constructed within two knowledge discourses: (i) scientific knowledge and (ii) local knowledge. This arbitrary separation into a binary discursive landscape mitigates against science-policy integration in practice especially given each discourse in itself, encompasses multiple forms of knowledge. We argue that in order to better understand how to build scientific research outputs into policy, decision makers and researchers need to understand how knowledge works in practice, overcome this dichotomous construction of knowledge and specifically, re-construct or transition the notion of 'science as knowledge' into 'all knowledge types' into policy.

A parallel algorithm for calculation of determinants and minors using arbitrary precision arithmetic

We present a parallel algorithm for calculating determinants of matrices in arbitrary precision arithmetic on computer clusters. This algorithm limits data movements between the nodes and computes not only the determinant but also all the minors corresponding to a particular row or column at a little extra cost, and also the determinants and minors of all the leading principal submatrices at no extra cost. We implemented the algorithm in arbitrary precision arithmetic, suitable for very ill conditioned matrices, and empirically estimated the loss of precision. In our scenario the cost of computation is bigger than that of data movement. The algorithm was applied to studies of Riemann’s zeta function.

Network lifetime of application-specific randomly deployed wireless sensor networks in arbitrary sensor density

In many cases, sensors are randomly deployed in Wireless Sensor Networks (WSN), called Sensor-Randomly-Deployed WSN (SRD WSN). Several cluster-based routing protocols are provided to maximize network lifetime of SRD WSN in different sensor densities. LEACH performs better than direct routing in the density of 0.01. BCDCP excels LEACH in the density of 0.05. DMSTRP outperforms LEACH and BCDCP in the density of. However, simulation results under one or two kinds of sensor densities are not strong enough to prove the optimum of the routing protocols. In this paper, we give the general formulas to compute the network lifetimes of the above three routing protocols, discuss their optimal number of clusters, and compare their optimal network lifetime in arbitrary sensor densities. These formulas can provide more general design guidelines applicable to SRD WSN than simulation results under only one or two kinds of sensor densities. © 2007 IEEE.

‘We just call them people’: positive regard as a dimension of culture in group homes for people with severe intellectual disability

BackgroundA dimension of the culture in group homes is staff regard for residents. In underperforming group homes, staff regard residents as being not ‘like us’ (Bigby, Knox, Beadle-Brown, Clement & Mansell, 2012). We hypothesized the opposite pole of this dimension, in higher performing group homes, would be that staff regard residents positively.MethodThree in-depth qualitative case studies were conducted in higher performing group homes using participant observation, interviews and document review.ResultsConsistent pattern of staff practices and talk, as well as artefacts, demonstrated staff had a positive regard for residents, who were seen as being ‘like us’. Explicit and continuing attention was given to sustaining positive regard for residents in everyday staff practices and to turning abstract values into concrete realities.ConclusionsThis positive cultural norm was established, operationalized and embedded through structures, such as a formal policy about language, and processes such as peer monitoring and practice leadership.

Testing for predictability in panels of any time series dimension

The few panel data tests for the predictability of returns that exist are based on the prerequisite that both the number of time series observations, T, and the number of cross-section units, N, are large. As a result, it is impossible to apply these tests to stock markets, where lengthy time series of data are scarce. In response to this, the current paper develops a new test for predictability in panels where N is large and T≥. 2 can be either small or large, or indeed anything in between. This consideration represents an advancement relative to the usual large-. N and large-. T requirement. The new test is also very general, especially when it comes to allowable predictors, and is easy to implement. As an illustration, we consider the Chinese stock market, for which data are available for only 17 years, but where the number of firms is relatively large, 160.

Learning stable weights for data of varying dimension

In this paper we develop a data-driven weight learning method for weighted quasi-arithmetic means where the observed data may vary in dimension.

The new Anti-Semitism in Europe: the Islamic dimension of, and Jewish belonging in, the EU

This article examines the sense of Jewish vulnerability and exclusion in Europe that has resulted from manifestations, and Jewish perceptions, of the “new anti-Semitism,” and the role of Islamic communities in Europe in propagating this form of hatred of Jews. First emerging in 2000 with the outbreak of the second Palestinian Intifada, and tied in with the Middle East conflict, anger at Israel is directed at Diaspora Jewish communities. This “new anti-Semitism” targets the Jewish collective with the characteristics of anti-Semitism previously aimed at individual Jews. The article focuses on the wave of anti-Semitism that erupted as a result of the 2014 Israeli–Hamas War. Based on an analysis of European Jewish communities, it considers the active part played by European Muslim communities in perpetrating the new anti-Semitism. Using an analysis of survey data, emigration statistics and newspaper opinion articles by leading European Jewish intellectuals, the article considers how the new anti-Semitism is adversely affecting Jewish–Muslim relations and the concomitant sense of “belonging” of European Jewry. The article considers what is required to overcome the new anti-Semitism propagated by Muslim communities to restore a greater sense of Jewish belonging to, and identification with, Europe.

Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model

Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward-backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was 'Social support for health', and the hardest were 'Navigating the healthcare system' and 'Appraisal of health information'. CFA of the individual scales showed acceptably high loadings (range 0.49-0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach's α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes.