BP4D-Spontaneous: a high-resolution spontaneous 3D dynamic facial expression database

Facial expression is central to human experience. Its efficiency and valid measurement are challenges that automated facial image analysis seeks to address. Most publically available databases are limited to 2D static images or video of posed facial behavior. Because posed and un-posed (aka “spontaneous”) facial expressions differ along several dimensions including complexity and timing, well-annotated video of un-posed facial behavior is needed. Moreover, because the face is a three-dimensional deformable object, 2D video may be insufficient, and therefore 3D video archives are required. We present a newly developed 3D video database of spontaneous facial expressions in a diverse group of young adults. Well-validated emotion inductions were used to elicit expressions of emotion and paralinguistic communication. Frame-level ground-truth for facial actions was obtained using the Facial Action Coding System. Facial features were tracked in both 2D and 3D domains. To the best of our knowledge, this new database is the first of its kind for the public. The work promotes the exploration of 3D spatiotemporal features in subtle facial expression, better understanding of the relation between pose and motion dynamics in facial action units, and deeper understanding of naturally occurring facial action.     

NEW CHROMATOGRAPHIC METHODS FOR ASPHALT ANALYSIS

ABSTRACT

New methods in the analysis of asphalt by size exclusion chromatography (SEC) and supercritical fluid chromatography (SFC) are described. The evaporative analyser and viscometric detectors provide a more nearly universal response in SEC than does the UV detector; a number of alternatives to polystyrene as retention volume calibration standards were investigated. SFC permitted simulated distillation at much lower temperatures than in GC, with closer correspondence to actual distillation behaviour     

A Comparative Evaluation of Short-Term Streamflow Forecasting Using Time Series Analysis and Rainfall-Runoff Models in eWater Source

Over the past few decades, many numerical streamflow prediction techniques using observed time series (TS) have been developed and widely used in water resources planning and management. Recent advances in quantitative rainfall forecasting by numerical weather prediction (NWP) models have made it possible to produce improved streamflow forecasts using continuous rainfall-runoff (RR) models. In the absence of a suitable integrated system of NWP, RR and river system models, river operators in Australia mostly use spreadsheet-based tools to forecast streamflow using gauged records. The eWater Cooperative Research Centre of Australia has recently developed a new generation software package called eWater Source, which allows a seamless integration of continuous RR and river system models for operational and planning purposes. This paper presents the outcomes of a study that was carried out using Source for a comparative evaluation of streamflow forecasting by several well-known TS based linear techniques and RR models in two selected sub-basins in the upper Murray river system of the Murray-Darling Basin in Australia. The results were compared with the actual forecasts made by the Murray River operators and the observed data. The results show that while streamflow forecasts by the river operators were reasonably accurate up to day 3 and traditional TS based approaches were reasonably accurate up to 2?days. Well calibrated RR models can provide better forecasts for longer periods when using high quality quantitative precipitation forecasts. The river operators tended to underestimate large magnitude flows.     

真实自然环境测试

为检验螺钉在室外暴露情况下的抗腐蚀性能,伊利诺建筑产品Buildex中国于2008年开展了一项科研项目,称作'真实自然环境测试'。自2009年,该项目受到中国武汉材料保护研究所的支持和监督。区别于实验室内单一模拟循环条件,唯有在真实自然环境中才能测试使用在建筑中的螺钉同时经受酸雨,盐雾,潮湿和紫外线这四大主要环境腐蚀考验的情况。Buildex是目前世界上唯一实施真实自然环境测试的建筑用轻钢围护系统螺钉专业制造公司。     

Issues in multi-item scale testing and development using structural equation models

Employing a structural equation model to evaluate a measurement scale can be challenging, especially for a multidimensional scale that contains many items. We describe two issues that can contribute to the poor fit of such models: the statistical power associated with the test of a large measurement scale; and the degree of correlation between items and factors within the scale. These issues are not well understood, so our purpose is to explain them at an applied level, clarify their practical implications for tests of measurement scales and other large structural equation models, and discuss potential strategies for addressing them.     

Collaborative Network Topologies in Spatial Economies

Networks and Spatial Economics - Recently, it has been shown that networks with an arbitrary degree sequence may be a stable solution to a network formation game. Further, in recent years there has...     

Energy-efficient and delay-aware mobile cloud offloading over cellular networks

Telecommunication Systems - The latest mobile applications, such as GPS, games, virus scanning, and face detection and recognition, are compute-intensive applications consuming a lot of energy when...     

A framework for the governance of information security

This paper highlights the importance of protecting an organization's vital business information assets by investigating several fundamental considerations that should be taken into account in this regard. Based on this, it is illustrated that information security should be a priority of executive management, including the Board and CEO and should therefore commence as a corporate governance responsibility. This paper, therefore, motivates that there is a need to integrate information security into corporate governance through the development of an information security governance (ISG) framework. This paper further proposes such a framework to aid an organization in its ISG efforts.     

Spreadsheet-based calculation tool for direct daylight illuminance adaptable for different glazing properties and sky models

The methods normally used to calculate daylight illuminance of rooms are limited in their capacity to model different sky luminance distributions and different window glazing properties. A spreadsheet-based model is presented in this paper using first-principle calculations, which allows for a free choice of sky luminance distribution and glazing material properties. The glazing is specified in terms of material refractive index, absorption coefficient and thickness, and may be either single or double glazed. The calculations need to be repeated for each of a large number of small elements of window area, which is easily achieved using a spreadsheet. Use is illustrated by comparing the calculation of sky components with standard published data, and demonstrating the effect of substituting double for single glazing. The model was developed for educational use, but would also be useful for designers who need to investigate quickly the effect of altering glazing properties and sky conditions, without recourse to specialist software.     

Deep learning for automatic segmentation of thigh and leg muscles

Objective

In this study we address the automatic segmentation of selected muscles of the thigh and leg through a supervised deep learning approach.

Material and methods

The application of quantitative imaging in neuromuscular diseases requires the availability of regions of interest (ROI) drawn on muscles to extract quantitative parameters. Up to now, manual drawing of ROIs has been considered the gold standard in clinical studies, with no clear and universally accepted standardized procedure for segmentation. Several automatic methods, based mainly on machine learning and deep learning algorithms, have recently been proposed to discriminate between skeletal muscle, bone, subcutaneous and intermuscular adipose tissue. We develop a supervised deep learning approach based on a unified framework for ROI segmentation.

Results

The proposed network generates segmentation maps with high accuracy, consisting in Dice Scores ranging from 0.89 to 0.95, with respect to “ground truth” manually segmented labelled images, also showing high average performance in both mild and severe cases of disease involvement (i.e. entity of fatty replacement).

Discussion

The presented results are promising and potentially translatable to different skeletal muscle groups and other MRI sequences with different contrast and resolution.