Robust pose invariant face recognition using coupled latent space discriminant analysis

We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for different poses such that the projected images of the same subject in different poses are maximally correlated in the latent space. Discriminant analysis with artificially simulated pose errors in the latent space makes it robust to small pose errors caused due to a subject’s incorrect pose estimation. We do a comparative analysis of three popular latent space learning approaches: Partial Least Squares (PLSs), Bilinear Model (BLM) and Canonical Correlational Analysis (CCA) in the proposed coupled latent subspace framework. We experimentally demonstrate that using more than two poses simultaneously with CCA results in better performance. We report state-of-the-art results for pose-invariant face recognition on CMU PIE and FERET and comparable results on MultiPIE when using only four fiducial points for alignment and intensity features.     

Robust H ∞ static output feedback stabilization of T-S fuzzy systems subject to actuator saturation

This paper proposes a method for designing robust H_?? static output feedback stabilization of Takagi-Sugeno (T-S) fuzzy systems under actuator saturation. In this paper, the input saturation is represented by a polytopic model and the modeling error is assumed a norm-bounded uncertainty. A set invariance condition for robust H_?? static output feedback system under actuator saturation is first established. Then, the estimation of the largest domain of attraction for the system is formulated and solved as a Linear Matrix Inequality (LMI) optimization problem. Two examples are used to demonstrate the effectiveness of the proposed design method.     

An improved light attenuation technique for measuring large interfacial areas

A laser-based light attenuation technique was successfully used to measure interfacial areas as high as 5832 m²/m³ and Sauter mean bubble diameter varying between 50 and 5600 μm. Good agreement between this approach and the photographic technique was obtained particularly at low gas holdups.     

Silhouette-based human action recognition using SAX-Shapes

Human action recognition is an important problem in Computer Vision. Although most of the existing solutions provide good accuracy results, the methods are often overly complex and computationally expensive, hindering practical applications. In this regard, we introduce the combination of time-series representation for the silhouette and Symbolic Aggregate approXimation (SAX), which we refer to as SAX-Shapes, to address the problem of human action recognition. Given an action sequence, the extracted silhouettes of an actor from every frame are transformed into time series. Each of these time series is then efficiently converted into the symbolic vector: SAX. The set of all these SAX vectors (SAX-Shape) represents the action. We propose a rotation invariant distance function to be used by a random forest algorithm to perform the human action recognition. Requiring only silhouettes of actors, the proposed method is validated on two public datasets. It has an accuracy comparable to the related works and it performs well even in varying rotation.     

PRIVACY LEAKAGE IN HEALTH SOCIAL NETWORKS

Members of health social networks may be susceptible to privacy leaks by the amount of information they leave behind. The threat to privacy increases when members of these networks reuse their pseudonyms in other social networks. The risk of re‐identifying users from such networks requires quantitative estimates to evaluate its magnitude. The estimates will enable managers and members of health social communities to take corrective measures. We introduce a new re‐identification attack, the social network attack, that takes advantage of the fact that users reuse their pseudonyms. To demonstrate the attack, we establish links between MedHelp and Twitter (two popular social networks) based on matching pseudonyms. We used Bayesian networks to model the re‐identification risk and used stylometric techniques to identify the strength of the links. On the basis of our model 7‐11. 8% of the MedHelp members in the sample population who reused their pseudonyms in Twitter were re‐identifiable compared with 1% who did not. The risk estimates were measured at the 5% risk threshold. Our model was able to re‐identify users with a sensitivity of 41% and specificity of 96%. The potential for re‐identification increases as more data is accumulated from these profiles, which makes the threat of re‐identification more serious.     

Tensile Stress Relaxation of Alumina at High Temperature

The development of a tensile testing methodology for ceramics which enables a stress vs strain-rate response to be measured at high temperature is described. The test involves a carefully controled stress relaxation test at constant total strain using an experimental procedure and phenomenological analysis previously developed for metallic materials. It is demonstrated here with preliminary tests on alumina at 1050° and 1150°C. This offers, with further development, the possibility of establishing design stresses associated with low strain-rate behavior for structural applications. The results demonstrate that data covering four decades of strain rate may be generated in tests lasting a few hours. The inelastic strain consists of substantial anelastic recoverable strain in addition to a permanent creep strain.     

Robust Fault Diagnosis for Quadrotor UAVs Using Adaptive Thau Observer

A robust Fault Diagnosis (FD) scheme for a real quadrotor Unmanned Aerial Vehicle (UAV) is proposed in this paper. Firstly, a novel Adaptive Thau observer (ATO) is developed to estimate the quadrotor system states and build a set of offset residuals to indicate actuators’ faults. Based on these residuals, some rules of Fault Diagnosis (FD) are designed to detect and isolate the faults as well as estimate the fault offset parameters. Secondly, a synthetic robust optimization scheme is presented to improve Fault Estimation (FE) accuracies, three key issues include modeling uncertainties, and magnitude order unbalances as well as noises are addressed. Finally, a typical fault of rotors is simulated and injected into one of four rotors of the quadrotor, and experiments for the FD scheme have been carried out. Unlike former research works on the FD schemes for quadrotors, our proposed FD scheme based on the ATO can not only detect and isolate the failed actuators, but also estimate the fault severities. Regardless of roughness of the real flying data, the FD results still have sufficient FE accuracies.     

Thermal conversion (visbreaking) of heavy Iraqi residue

A heavy Iraqi residue was thermally cracked using a soaker visbreaking process at temperatures between 435 and 480 °C, with a range of residence times of 43–109 s in the coil and 151–379 s in the soaker. The pressure was kept constant at 7 bar. Visbroken products were characterized, evaluated and fractionated into light, middle and heavy cuts. The stability of the visbroken products was compared with that of the original feedstock. Also an activation energy was calculated for the visbreaking process and related to the severity of the process. The results obtained show that the conditions used were not severe and could be applied to obtain a required conversion depending on the uses of the products.     

Synchronous receiver initiated MAC protocol for long-lived sensor networks

In this paper, we discuss the design of a new Medium Access Control (MAC) protocol, SRI-MAC (Synchronous Receiver Initiated MAC), for wireless sensor networks whose goal is to extend the lifetime of the network by avoiding major energy waste causes, such as collisions, overhearing and idle listening.