Fast Predictive Image Registration

We present a method to predict image deformations based on patch-wise image appearance. Specifically, we design a patch-based deep encoder-decoder network which learns the pixel/voxel-wise mapping between image appearance and registration parameters. Our approach can predict general deformation parameterizations, however, we focus on the large deformation diffeomorphic metric mapping (LDDMM) registration model. By predicting the LDDMM momentum-parameterization we retain the desirable theoretical properties of LDDMM, while reducing computation time by orders of magnitude: combined with patch pruning, we achieve a 1500x/66x speed up compared to GPU-based optimization for 2D/3D image registration. Our approach has better prediction accuracy than predicting deformation or velocity fields and results in diffeomorphic transformations. Additionally, we create a Bayesian probabilistic version of our network, which allows evaluation of deformation field uncertainty through Monte Carlo sampling using dropout at test time. We show that deformation uncertainty highlights areas of ambiguous deformations. We test our method on the OASIS brain image dataset in 2D and 3D

Revealing the impacts of passive cooling techniques on building energy performance: A residential case in Hong Kong

Environmental concerns and growing energy costs raise the importance of sustainable development and energy conservation. The building sector accounts for a significant portion of total energy consumption. Passive cooling techniques provide a promising and cost-efficient solution to reducing the energy demand of buildings. Based on a typical residential case in Hong Kong, this study aims to analyze the integration of various passive cooling techniques on annual and hourly building energy demand with whole building simulation. The results indicate that infiltration and insulation improvement are effective in regard to energy conservation in buildings, while the effectiveness of variations in building orientation, increasing natural ventilation rate, and phase change materials (PCM) are less significant. The findings will be helpful in the passive house standard development in Hong Kong and contribute to the further optimization work to realize both energy efficiency and favorably built environments in residential buildings.</jats:p

The effectiveness of private tutoring: students’ perceptions in comparison with mainstream schooling in Hong Kong.

This paper examines Hong Kong students’ perceptions on the effectiveness of private supplementary tutoring relative to mainstream schooling. Drawing on survey and interview data, it shows that large proportions of secondary school students receive private tutoring. Students generally perceive private tutoring and private tutors to be more effective in the provision of examination support compared with mainstream schooling and teachers. However, perceptions vary according to students’ selfreported academic levels and motives for taking private tutoring. The operations of the parallel sector of private tutoring have significant implications for the nature of schooling and therefore need to be considered by teachers and school administrators. The Hong Kong data contribute to the international analysis of private tutoring and add a significant component to the wider conceptual literature.postprin

Cultural-based visual expression: Emotional analysis of human face via Peking Opera Painted Faces (POPF)

© 2015 The Author(s) Peking Opera as a branch of Chinese traditional cultures and arts has a very distinct colourful facial make-up for all actors in the stage performance. Such make-up is stylised in nonverbal symbolic semantics which all combined together to form the painted faces to describe and symbolise the background, the characteristic and the emotional status of specific roles. A study of Peking Opera Painted Faces (POPF) was taken as an example to see how information and meanings can be effectively expressed through the change of facial expressions based on the facial motion within natural and emotional aspects. The study found that POPF provides exaggerated features of facial motion through images, and the symbolic semantics of POPF provides a high-level expression of human facial information. The study has presented and proved a creative structure of information analysis and expression based on POPF to improve the understanding of human facial motion and emotion

Treatment outcomes of various types of tuberculosis in Pakistan, 2006 and 2007

Measuring treatment outcome is important for successful tuberculosis (TB) control programmes. The purpose of this study was to examine the outcomes of various types of TB cases registered in Pakistan over a 2-year period and compare those outcomes among the different provinces and regions of the country. A retrospective, cohort study was conducted in which TB treatment outcome reports were reviewed. Of the 349 694 pulmonary TB cases registered in Pakistan during 2006 and 2007, 309 154 (88.4%) were treated successfully. Treatment success was significantly higher in new smear-positive cases and lower in retreatment cases. Among the provinces and regions, treatment success was significantly higher in 4 out of 8 provinces. Treatment success needs to be improved, particularly in retreatment cases. The national TB control programme should review the provincial and regional programmes and learn lessons from well-performing programmes. Patient factors that may affect the treatment outcome should be also studied

Ultrasonically assisted machining of Titanium alloys

In this chapter we discuss the nuances of a non-conventional machining technique known as ultrasonically assisted machining, which has been used to demonstrate tractable benefits in the machining of titanium alloys. We also demonstrate how further improvements may be achieved by combining this machining technique with the well known advantages of hot machining in metals and alloys

A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks

With the advent of deep learning, the number of works proposing new methods or improving existent ones has grown exponentially in the last years. In this scenario, "very deep" models were emerging, once they were expected to extract more intrinsic and abstract features while supporting a better performance. However, such models suffer from the gradient vanishing problem, i.e., backpropagation values become too close to zero in their shallower layers, ultimately causing learning to stagnate. Such an issue was overcome in the context of convolution neural networks by creating "shortcut connections" between layers, in a so-called deep residual learning framework. Nonetheless, a very popular deep learning technique called Deep Belief Network still suffers from gradient vanishing when dealing with discriminative tasks. Therefore, this paper proposes the Residual Deep Belief Network, which considers the information reinforcement layer-by-layer to improve the feature extraction and knowledge retaining, that support better discriminative performance. Experiments conducted over three public datasets demonstrate its robustness concerning the task of binary image classification

An examination of the molecular distribution of a tropical lake sediment sequence to assess organic carbon records of climate and environmental changes

(DIPPI-C) - Development of Isotopic Proxies for Palaeoenvironmental Interpretation: a Carbon PerspectiveThe bulk organic carbon isotope (δ13C), as the conventional indicator of the C3 and C4 vegetation change, turns relatively contentious in the application of palaeoclimate reconstruction from the lacustrine sediments due to the similar δ13C value between C3 and aquatic plants, particularly in the eutrophic lakes. A long successive lacustrine sequence from Tianyang Maar Lake, locating in the tropical region of South China, has complex organic matter (OM) sources due to relatively high inputs from the aquatic macrophytes and diatoms. We examined the n-alkanes concentration of 80 selected samples from the Tianyangcore, as an additional index to assess the paleovegetation and lake-level changes. The n-alkanes results show some distributional patterns of compounds with carbon numbers ranging from C15 to C39. These patterns indicate differences in OM sources and relative contributions from higher and lower plants, improving the interpretation of δ13C records of changes in climate and depositional conditions. Meanwhile, more details of the aquatic macrophyte and diatom inputs revealed by the n-alkanes based proxies (TAR, Paq) replenish the evidence of the lake-level changes during the evolution history of Tianyang Lake.postprintThe 1st DIPPI-C Workshop, Durham, UK., 8-10 May 2012. In Abstract Bok of the 1st DIPPI-C Workshop, 2012, p. 3