Person-independent facial expression detection using constrained local models

In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP datasets.

Empirical Bayes method in the study of traffic safety via heterogeneous negative multinomial model

In the study of traffic safety, expected crash frequencies across sites are generally estimated via the negative binomial model, assuming time invariant safety. Since the time invariant safety assumption may be invalid, Hauer (1997) proposed a modified empirical Bayes (EB) method. Despite the modification, no attempts have been made to examine the generalisable form of the marginal distribution resulting from the modified EB framework. Because the hyper-parameters needed to apply the modified EB method are not readily available, an assessment is lacking on how accurately the modified EB method estimates safety in the presence of the time variant safety and regression-to-the-mean (RTM) effects. This study derives the closed form marginal distribution, and reveals that the marginal distribution in the modified EB method is equivalent to the negative multinomial (NM) distribution, which is essentially the same as the likelihood function used in the random effects Poisson model. As a result, this study shows that the gamma posterior distribution from the multivariate Poisson-gamma mixture can be estimated using the NM model or the random effects Poisson model. This study also shows that the estimation errors from the modified EB method are systematically smaller than those from the comparison group method by simultaneously accounting for the RTM and time variant safety effects. Hence, the modified EB method via the NM model is a generalisable method for estimating safety in the presence of the time variant safety and the RTM effects.

Predicting single-vehicle fatal crashes for two-lane rural highways in Southeastern United States

The rural two-lane highway in the southeastern United States is frequently associated with a disproportionate number of serious and fatal crashes and as such remains a focus of considerable safety research. The Georgia Department of Transportation spearheaded a regional fatal crash analysis to identify various safety performances of two-lane rural highways and to offer guidance for identifying suitable countermeasures with which to mitigate fatal crashes. The fatal crash data used in this study were compiled from Alabama, Georgia, Mississippi, and South Carolina. The database, developed for an earlier study, included 557 randomly selected fatal crashes from 1997 or 1998 or both (this varied by state). Each participating state identified the candidate crashes and performed physical or video site visits to construct crash databases with enhance site-specific information. Motivated by the hypothesis that single- and multiple-vehicle crashes arise from fundamentally different circumstances, the research team applied binary logit models to predict the probability that a fatal crash is a single-vehicle run-off-road fatal crash given roadway design characteristics, roadside environment features, and traffic conditions proximal to the crash site. A wide variety of factors appears to influence or be associated with single-vehicle fatal crashes. In a model transferability assessment, the authors determined that lane width, horizontal curvature, and ambient lighting are the only three significant variables that are consistent for single-vehicle run-off-road crashes for all study locations.

How automated speed enforcement may reduce travel time variability and result in travel time savings : the case study of the loop 101 speed enforcement program in Scottsdale, Arizona

The city of Scottsdale Arizona implemented the first fixed photo Speed Enforcement camera demonstration Program (SEP) on a US freeway in 2006. A comprehensive before-and-after analysis of the impact of the SEP on safety revealed significant reductions in crash frequency and severity, which indicates that the SEP is a promising countermeasure for improving safety. However, there is often a trade off between safety and mobility when safety investments are considered. As a result, identifying safety countermeasures that both improve safety and reduce Travel Time Variability (TTV) is a desirable goal for traffic safety engineers. This paper reports on the analysis of the mobility impacts of the SEP by simulating the traffic network with and without the SEP, calibrated to real world conditions. The simulation results show that the SEP decreased the TTV: the risk of unreliable travel was at least 23% higher in the ‘without SEP’ scenario than in the ‘with SEP’ scenario. In addition, the total Travel Time Savings (TTS) from the SEP was estimated to be at least ‘569 vehicle-hours/year.’ Consequently, the SEP is an efficient countermeasure not only for reducing crashes but also for improving mobility through TTS and reduced TTV.

Incorporating parameter uncertainty into quantitative microbial risk assessment (QMRA)

Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

A DRD2 polymorphism predicts PANSS score variability in schizophrenia patients treated with antipsychotics

Antipsychotic medications act as either antagonists or partial agonists of the dopamine D2 receptor (DRD2) and antipsychotic drugs vary widely in their binding affinity for the D2 receptor (Kapur and Seeman, 2000). The DRD2 957CNT (rs6277) polymorphism has previously been associated with schizophrenia (Lawford et al., 2005) and the T-allele of the 957CNT polymorphism is associated with reduced mRNA stability and synthesis of the dopamine D2 receptor (Duan et al., 2003). The aim of the study was to determine if the rs6277 polymorphism predicts some of the variability of positive and negative symptoms observed in schizophrenia patients being treated with antipsychotic medication.

Automatically detecting pain in video through facial action units

In a clinical setting, pain is reported either through patient self-report or via an observer. Such measures are problematic as they are: 1) subjective, and 2) give no specific timing information. Coding pain as a series of facial action units (AUs) can avoid these issues as it can be used to gain an objective measure of pain on a frame-by-frame basis. Using video data from patients with shoulder injuries, in this paper, we describe an active appearance model (AAM)-based system that can automatically detect the frames in video in which a patient is in pain. This pain data set highlights the many challenges associated with spontaneous emotion detection, particularly that of expression and head movement due to the patient's reaction to pain. In this paper, we show that the AAM can deal with these movements and can achieve significant improvements in both the AU and pain detection performance compared to the current-state-of-the-art approaches which utilize similarity-normalized appearance features only.

The circadian response of intrinsically photosensitive retinal ganglion cells

Intrinsically photosensitive retinal ganglion cells (ipRGC) signal environmental light level to the central circadian clock and contribute to the pupil light reflex. It is unknown if ipRGC activity is subject to extrinsic (central) or intrinsic (retinal) network-mediated circadian modulation during light entrainment and phase shifting. Eleven younger persons (18–30 years) with no ophthalmological, medical or sleep disorders participated. The activity of the inner (ipRGC) and outer retina (cone photoreceptors) was assessed hourly using the pupil light reflex during a 24 h period of constant environmental illumination (10 lux). Exogenous circadian cues of activity, sleep, posture, caffeine, ambient temperature, caloric intake and ambient illumination were controlled. Dim-light melatonin onset (DLMO) was determined from salivary melatonin assay at hourly intervals, and participant melatonin onset values were set to 14 h to adjust clock time to circadian time. Here we demonstrate in humans that the ipRGC controlled post-illumination pupil response has a circadian rhythm independent of external light cues. This circadian variation precedes melatonin onset and the minimum ipRGC driven pupil response occurs post melatonin onset. Outer retinal photoreceptor contributions to the inner retinal ipRGC driven post-illumination pupil response also show circadian variation whereas direct outer retinal cone inputs to the pupil light reflex do not, indicating that intrinsically photosensitive (melanopsin) retinal ganglion cells mediate this circadian variation.

Semi-supervised intelligent surveillance system for secure environments

This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted.

The influence of underreported crashes on hotspot identification

Hot spot identification (HSID) plays a significant role in improving the safety of transportation networks. Numerous HSID methods have been proposed, developed, and evaluated in the literature. The vast majority of HSID methods reported and evaluated in the literature assume that crash data are complete, reliable, and accurate. Crash under-reporting, however, has long been recognized as a threat to the accuracy and completeness of historical traffic crash records. As a natural continuation of prior studies, the paper evaluates the influence that under-reported crashes exert on HSID methods. To conduct the evaluation, five groups of data gathered from Arizona Department of Transportation (ADOT) over the course of three years are adjusted to account for fifteen different assumed levels of under-reporting. Three identification methods are evaluated: simple ranking (SR), empirical Bayes (EB) and full Bayes (FB). Various threshold levels for establishing hotspots are explored. Finally, two evaluation criteria are compared across HSID methods. The results illustrate that the identification bias—the ability to correctly identify at risk sites--under-reporting is influenced by the degree of under-reporting. Comparatively speaking, crash under-reporting has the largest influence on the FB method and the least influence on the SR method. Additionally, the impact is positively related to the percentage of the under-reported PDO crashes and inversely related to the percentage of the under-reported injury crashes. This finding is significant because it reveals that despite PDO crashes being least severe and costly, they have the most significant influence on the accuracy of HSID.

Mechanical evaluation of a new minimally invasive device for stabilization of proximal humeral fractures in elderly patients : a cadaver study

BACKGROUND: Treatment of proximal humerus fractures in elderly patients is challenging because of reduced bone quality. We determined the in vitro characteristics of a new implant developed to target the remaining bone stock, and compared it with an implant in clinical use. METHODS: Following osteotomy, left and right humeral pairs from cadavers were treated with either the Button-Fix or the Humerusblock fixation system. Implant stiffness was determined for three clinically relevant cases of load: axial compression, torsion, and varus bending. In addition, a cyclic varus-bending test was performed. RESULTS: We found higher stiffness values for the humeri treated with the ButtonFix system--with almost a doubling of the compression, torsion, and bending stiffness values. Under dynamic loading, the ButtonFix system had superior stiffness and less K-wire migration compared to the Humerusblock system. INTERPRETATION: When compared to the Humerusblock design, the ButtonFix system showed superior biomechanical properties, both static and dynamic. It offers a minimally invasive alternative for the treatment of proximal humerus fractures.

Management [4th Asia Pacific Edition]

The fourth edition of this popular text has been throughly updated, continuing its strong emphasis on the importance of the Asian region to contemporary Australian and New Zealand organizations. Many Asian case examples are featured to illustrate key management concepts. ----- ----- ----- Joining the author team for this edition and enhancing this edition's critical analysis of management theory and applications are the best-selling authors from another of Wiley's undergraduate introductory management texts - Management: Core Concepts and Applications, 2nd Australasian edition (Davidson et al.).----- ----- ----- This new edition also discusses the impact of recent events such as the global financial crisis on the management of organisations, both during the crisis and in its aftermath.----- ----- ----- Of course, Management, 4th Asia- Pacific edition also retains the features that made it so popular with students and lecturers in the earlier editions: a balanced coverage of small to medium-sized enterprises and larger multinational corporations an emphasis on the need for business activities to be sustainable in terms of preserving the welfare of future generations the Career Readiness Workbook at the end of the book, which includes a range of individual and group activities to encourage the practical applications of management theory. With its clear insights into dynamics of management in the workplace of today and the future, Management, 4th Asia-Pacific edition provides a sound basis for the contemporary undergraduate study of introductory management.

Bioactive SrO–SiO2 glass with well-ordered mesopores : characterization, physiochemistry and biological properties

For a biomaterial to be considered suitable for bone repair it should ideally be both bioactive and have a capacity for controllable drug delivery; as such, mesoporous SiO2 glass has been proposed as a new class of bone regeneration material by virtue of its high drug-loading ability and generally good biocompatibility. It does, however, have less than optimum bioactivity and controllable drug delivery properties. In this study, we incorporated strontium (Sr) into mesoporous SiO2 in an effort to develop a bioactive mesoporous SrO–SiO2 (Sr–Si) glass with the capacity to deliver Sr2+ ions, as well as a drug, at a controlled rate, thereby producing a material better suited for bone repair. The effects of Sr2+ on the structure, physiochemistry, drug delivery and biological properties of mesoporous Sr–Si glass were investigated. The prepared mesoporous Sr–Si glass was found to have an excellent release profile of bioactive Sr2+ ions and dexamethasone, and the incorporation of Sr2+ improved structural properties, such as mesopore size, pore volume and specific surface area, as well as rate of dissolution and protein adsorption. The mesoporous Sr–Si glass had no cytotoxic effects and its release of Sr2+ and SiO44− ions enhanced alkaline phosphatase activity – a marker of osteogenic cell differentiation – in human bone mesenchymal stem cells. Mesoporous Sr–Si glasses can be prepared to porous scaffolds which show a more sustained drug release. This study suggests that incorporating Sr2+ into mesoporous SiO2 glass produces a material with a more optimal drug delivery profile coupled with improved bioactivity, making it an excellent material for bone repair applications. Keywords: Mesoporous Sr–Si glass; Drug delivery; Bioactivity; Bone repair; Scaffolds

Textures of optical flow for real-time anomaly detection in crowds

Automated visual surveillance of crowds is a rapidly growing area of research. In this paper we focus on motion representation for the purpose of abnormality detection in crowded scenes. We propose a novel visual representation called textures of optical flow. The proposed representation measures the uniformity of a flow field in order to detect anomalous objects such as bicycles, vehicles and skateboarders; and can be combined with spatial information to detect other forms of abnormality. We demonstrate that the proposed approach outperforms state-of-the-art anomaly detection algorithms on a large, publicly-available dataset.

Feature-domain super-resolution for IRIS recognition

Uncooperative iris identification systems at a distance suffer from poor resolution of the captured iris images, which significantly degrades iris recognition performance. Superresolution techniques have been employed to enhance the resolution of iris images and improve the recognition performance. However, all existing super-resolution approaches proposed for the iris biometric super-resolve pixel intensity values. This paper considers transferring super-resolution of iris images from the intensity domain to the feature domain. By directly super-resolving only the features essential for recognition, and by incorporating domain specific information from iris models, improved recognition performance compared to pixel domain super-resolution can be achieved. This is the first paper to investigate the possibility of feature domain super-resolution for iris recognition, and experiments confirm the validity of the proposed approach.